00_original_index/.DS_Store

Original line number	Diff line number	Diff line
		# Filter to 2004-2024 and handle gaps in the data ----
		#******************************************************************************
		# Filter to 2004-2024
		final_data_clean <- final_data %>%
		filter(date >= as.Date("2004-01-01"),
		date <= as.Date("2024-12-31"))
		# Remove variables with missing data
		pca_data <- final_data_clean %>%
		select(-disp_income_bw, -real_income_bw)
		# Save
		write_csv(final_data_clean, "03_data/processed/affordability_data_2004_2024_complete.csv")
		write_csv(pca_data, "03_data/processed/affordability_data_pca_ready_2004_2024.csv")
		View(income_bw_quarterly_df)
		#******************************************************************************
		# Set WD and load required libraries ----
		#******************************************************************************
		rm(list = ls())
		library(tidyverse)
		library(zoo)
		library(stringr)
		library(lubridate)
		library(janitor)
		library(readxl)
		library(ggplot2)
		library(dplyr)
		# SR WD
		setwd("~/Main/Uni/Master/S3/git/mlw_project_tw_sr")
		#TW WD
		#setwd("C:/Users/tomwa/Documents/git/mlw_project_tw_sr")
		#******************************************************************************
		# Load data ----
		#******************************************************************************
		house_prices <- read_csv("03_data/data_given/house_price_index_D_q.csv")
		bb_ratios <- read_csv("03_data/data_given/bb_houseprice_income_ratios_D_q.csv")
		housing_costs <- read_csv("03_data/data_given/housing_costs_index_D_m.csv")
		construction_prices <- read_csv("03_data/data_given/construction_prices_bw_q.csv")
		bb_interest_rates <- read_csv("03_data/data_given/bb_interest_rates_D_m.csv")
		bb_volumes <- read_csv("03_data/data_given/bb_volumes_D_m.csv")
		income_raw <- read_excel("03_data/data_destatis/disp_income_y_bw.xlsx",
		sheet = "Verfügbares Einkommen",
		skip = 2)
		real_income_raw <- read.csv(
		"03_data/data_destatis/genesis_bw/31111_0001_real_income_bw_q.csv",
		sep = ";",
		skip = 6,
		encoding = "latin1",
		check.names = FALSE
		)
		priceindex_housing <- read.csv(
		"03_data/data_destatis/genesis_bw/61261_0003_priceindex_housing_bw_q.csv",
		sep = ";",
		skip = 3,
		encoding = "latin1",
		check.names = FALSE
		)
		#******************************************************************************
		# Clean data ----
		#******************************************************************************
		house_prices_clean <- house_prices %>%
		clean_names() %>%
		mutate(date = as.Date(as.yearqtr(date))) %>%
		arrange(date) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, quarter))
		bb_ratios_clean <- bb_ratios %>%
		clean_names() %>%
		mutate(date = as.Date(as.yearqtr(date))) %>%
		arrange(date) %>%
		rename_with(~ paste0(.x, "_ratio_d"),
		.cols = -c(date, year, quarter))
		housing_costs_clean <- housing_costs %>%
		clean_names() %>%
		mutate(date = ymd(paste0(date, "-01")),
		quarter = as.yearqtr(date)) %>%
		group_by(quarter) %>%
		summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
		mutate(date = as.Date(quarter)) %>%
		select(-quarter) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, month))
		construction_prices_clean <- construction_prices %>%
		clean_names() %>%
		mutate(date = as.Date(as.yearqtr(date))) %>%
		arrange(date) %>%
		rename_with(~ paste0(.x, "_bw"),
		.cols = -c(date, year, quarter))
		bb_interest_rates_clean <- bb_interest_rates %>%
		clean_names() %>%
		mutate(date = ymd(paste0(date, "-01")),
		quarter = as.yearqtr(date)) %>%
		group_by(quarter) %>%
		summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
		mutate(date = as.Date(quarter)) %>%
		select(-quarter) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, month))
		bb_volumes_clean <- bb_volumes %>%
		clean_names() %>%
		mutate(date = ymd(paste0(date, "-01")),
		quarter = as.yearqtr(date)) %>%
		group_by(quarter) %>%
		summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
		mutate(date = as.Date(quarter)) %>%
		select(-quarter) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, month))
		#******************************************************************************
		# Clean Disposable Household Income (BW and Germany) ----
		#******************************************************************************
		income_data <- income_raw %>%
		clean_names() %>%
		select(jahr, baden_wurttemberg, deutschland_18) %>%
		mutate(
		jahr = as.numeric(str_extract(jahr, "\\d{4}")),
		baden_wurttemberg = as.numeric(baden_wurttemberg),
		deutschland = as.numeric(deutschland_18)
		) %>%
		filter(!is.na(jahr)) %>%
		distinct(jahr, .keep_all = TRUE) %>%
		arrange(jahr)
		# Interpolate BW to quarterly
		income_bw_zoo <- zoo(income_data$baden_wurttemberg, as.yearqtr(income_data$jahr))
		quarter_seq <- seq(from = min(as.yearqtr(income_data$jahr)),
		to = max(as.yearqtr(income_data$jahr)),
		by = 0.25)
		income_bw_quarterly <- na.approx(income_bw_zoo, xout = quarter_seq)
		income_bw_quarterly_df <- tibble(
		date = as.Date(time(income_bw_quarterly)),
		disp_income_bw = as.numeric(income_bw_quarterly)
		)
		# Interpolate Germany to quarterly
		income_de_zoo <- zoo(income_data$deutschland, as.yearqtr(income_data$jahr))
		income_de_quarterly <- na.approx(income_de_zoo, xout = quarter_seq)
		income_de_quarterly_df <- tibble(
		date = as.Date(time(income_de_quarterly)),
		disp_income_de = as.numeric(income_de_quarterly)
		)
		# PLOT: Annual vs. Quarterly (interpolated)
		income_bw_annual_df <- income_data %>%
		mutate(date = as.Date(paste0(jahr, "-12-31"))) %>%
		select(date, disp_income_bw = baden_wurttemberg)
		ggplot() +
		geom_line(data = income_bw_quarterly_df,
		aes(x = date, y = disp_income_bw, color = "Quarterly (Interpolated)"),
		size = 1) +
		geom_point(data = income_bw_annual_df,
		aes(x = date, y = disp_income_bw, color = "Annual (Observed)"),
		size = 2.5) +
		scale_color_manual(values = c("Quarterly (Interpolated)" = "steelblue",
		"Annual (Observed)" = "firebrick")) +
		labs(title = "Income in Baden-Württemberg: Annual vs. Interpolated Quarterly Data",
		x = "Year",
		y = "Disposable Income (EUR)",
		color = "Data Type") +
		theme_minimal(base_size = 13)
		#******************************************************************************
		# Backcast BW income using Germany income ----
		#******************************************************************************
		# Merge BW and Germany income
		income_combined <- income_bw_quarterly_df %>%
		full_join(income_de_quarterly_df, by = "date") %>%
		filter(date >= as.Date("2004-01-01"))
		# Calculate BW/Germany ratio in overlap period
		ratio_disp <- income_combined %>%
		filter(!is.na(disp_income_bw), !is.na(disp_income_de)) %>%
		summarise(ratio = mean(disp_income_bw / disp_income_de, na.rm = TRUE)) %>%
		pull(ratio)
		# Backcast missing BW values using Germany * ratio
		income_combined <- income_combined %>%
		mutate(
		disp_income_bw_backcasted = if_else(
		is.na(disp_income_bw),
		disp_income_de * ratio_disp,
		disp_income_bw
		)
		)
		# Validation plot
		ggplot(income_combined, aes(x = date)) +
		geom_line(aes(y = disp_income_bw_backcasted), color = "steelblue", linewidth = 1) +
		geom_point(aes(y = disp_income_bw), color = "firebrick", size = 2.5) +
		labs(title = "Disposable Income Baden-Württemberg: Backcasted",
		subtitle = paste0("BW = ", round(ratio_disp * 100, 1), "% of Germany \| Red = observed, Blue = complete series"),
		x = "Quarter", y = "Disposable Income (EUR)") +
		theme_minimal()
		# Use backcasted version for merging
		income_bw_quarterly_df <- income_combined %>%
		select(date, disp_income_bw = disp_income_bw_backcasted)
		#******************************************************************************
		# Clean Real Income ----
		#******************************************************************************
		real_income_clean <- real_income_raw %>%
		clean_names() %>%
		select(
		year = 1,
		period = 2,
		reallohnindex_alle_arbeitnehmenden = 3
		) %>%
		filter(!is.na(reallohnindex_alle_arbeitnehmenden) & reallohnindex_alle_arbeitnehmenden != "") %>%
		mutate(
		reallohnindex_alle_arbeitnehmenden = as.numeric(str_replace(reallohnindex_alle_arbeitnehmenden, ",", ".")),
		year = as.numeric(year)
		) %>%
		filter(!is.na(reallohnindex_alle_arbeitnehmenden)) %>%
		filter(!str_detect(period, "Insgesamt")) %>%
		mutate(
		quarter = case_when(
		str_detect(period, "Erstes Quartal") ~ 1,
		str_detect(period, "Zweites Quartal") ~ 2,
		str_detect(period, "Drittes Quartal") ~ 3,
		str_detect(period, "Viertes Quartal") ~ 4
		),
		date = as.yearqtr(year + (quarter - 1)/4),
		date = as.Date(date)
		) %>%
		select(date, real_income_bw = reallohnindex_alle_arbeitnehmenden) %>%
		arrange(date)
		#******************************************************************************
		# Clean Housing Priceindex BW ----
		#******************************************************************************
		priceindex_housing_clean <- priceindex_housing[1:79, 1:2]
		housing_prices_clean <- priceindex_housing_clean %>%
		clean_names() %>%
		select(year = 1, index = 2) %>%
		filter(!is.na(index) & !index %in% c("Baupreisindizes", "Wohngebäude", "2021 = 100")) %>%
		mutate(
		year = as.numeric(year),
		index = as.numeric(str_replace(index, ",", "."))
		) %>%
		filter(!is.na(year) & !is.na(index)) %>%
		arrange(year)
		housing_zoo <- zoo(housing_prices_clean$index, as.yearqtr(housing_prices_clean$year))
		quarter_seq <- seq(from = min(as.yearqtr(housing_prices_clean$year)),
		to = max(as.yearqtr(housing_prices_clean$year)),
		by = 0.25)
		housing_quarterly <- na.approx(housing_zoo, xout = quarter_seq)
		housing_quarterly_df <- tibble(
		date = as.Date(time(housing_quarterly)),
		housing_price_bw = as.numeric(housing_quarterly)
		)
		# Prepare annual data for plotting
		housing_annual_df <- housing_prices_clean %>%
		mutate(date = as.Date(paste0(year, "-12-31"))) %>%
		select(date, housing_price_bw = index)
		ggplot() +
		geom_line(data = housing_quarterly_df,
		aes(x = date, y = housing_price_bw, color = "Quarterly (Interpolated)"),
		size = 1) +
		geom_point(data = housing_annual_df,
		aes(x = date, y = housing_price_bw, color = "Annual (Observed)"),
		size = 2.5) +
		scale_color_manual(values = c("Quarterly (Interpolated)" = "steelblue",
		"Annual (Observed)" = "firebrick")) +
		labs(title = "Housing Price Index in Baden-Württemberg: Annual vs. Interpolated Quarterly Data",
		x = "Year",
		y = "Housing Price Index (2021 = 100)",
		color = "Data Type") +
		theme_minimal(base_size = 13)
		#******************************************************************************
		# Merge ----
		#******************************************************************************
		final_data <- house_prices_clean %>%
		full_join(bb_ratios_clean, by = "date") %>%
		full_join(housing_costs_clean, by = "date") %>%
		full_join(construction_prices_clean, by = "date") %>%
		full_join(bb_interest_rates_clean, by = "date") %>%
		full_join(bb_volumes_clean, by = "date") %>%
		full_join(income_bw_quarterly_df, by = "date") %>%
		full_join(real_income_clean, by = "date") %>%
		arrange(date)
		#******************************************************************************
		# Filter to 2004-2024 and handle gaps in the data ----
		#******************************************************************************
		final_data_clean <- final_data %>%
		filter(date >= as.Date("2004-01-01"),
		date <= as.Date("2024-12-31"))
		pca_data <- final_data_clean %>%
		select(-real_income_bw)
		#******************************************************************************
		# Save ----
		#******************************************************************************
		write_csv(final_data, "03_data/processed/affordability_data_q.csv")
		write_csv(house_prices_clean, "03_data/processed/house_prices_q_d.csv")
		write_csv(bb_ratios_clean, "03_data/processed/bb_ratios_q_d.csv")
		write_csv(housing_costs_clean, "03_data/processed/housing_costs_m_d.csv")
		write_csv(construction_prices_clean, "03_data/processed/construction_prices_q_d.csv")
		write_csv(bb_interest_rates_clean, "03_data/processed/bb_interest_rates_m_d.csv")
		write_csv(bb_volumes_clean, "03_data/processed/bb_volumes_m_d.csv")
		write_csv(income_bw_quarterly_df, "03_data/processed/disp_income_q_bw.csv")
		write_csv(real_income_clean, "03_data/processed/real_income_q_bw.csv")
		write_csv(housing_quarterly_df, "03_data/processed/housing_priceindex_q_bw.csv")
		write_csv(final_data_clean, "03_data/processed/affordability_data_2004_2024_complete.csv")
		write_csv(pca_data, "03_data/processed/affordability_data_pca_ready_2004_2024.csv")
		View(income_raw)
		#******************************************************************************
		# PCA-based Housing Cost Index - Reduced Variable Specification
		#******************************************************************************
		# Reduced from 30 to 8 core variables (removed redundancy)
		#******************************************************************************
		rm(list = ls())
		library(tidyverse)
		library(ggplot2)
		library(gridExtra)
		setwd("~/Main/Uni/Master/S3/git/mlw_project_tw_sr")
		#setwd("C:/Users/tomwa/Documents/git/mlw_project_tw_sr")
		dir.create("05_output/reduced", showWarnings = FALSE, recursive = TRUE)
		#******************************************************************************
		# Load Data
		#******************************************************************************
		pca_data <- read_csv("03_data/processed/affordability_data_returns_q.csv")
		#******************************************************************************
		# Variable Selection
		#******************************************************************************
		vars_clean <- c(
		"r_index_house_price_d",
		"r_interest_new_avg_d",
		"r_actual_rent_d",
		"r_maintenance_repair_aprtm_d",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d"
		)
		# Verify variables exist
		missing_vars <- setdiff(vars_clean, names(pca_data))
		if(length(missing_vars) > 0) {
		stop("Missing variables: ", paste(missing_vars, collapse = ", "))
		}
		# Parameters
		W <- 20
		lambda <- 0.97
		N_obs <- nrow(pca_data)
		N_var <- length(vars_clean)
		#******************************************************************************
		# Helper Functions
		#******************************************************************************
		compute_ewma_cov <- function(R_window, lambda){
		p <- ncol(R_window)
		S <- matrix(0, p, p)
		for(i in seq_len(nrow(R_window))){
		rvec <- matrix(R_window[i, ], ncol = 1)
		S <- lambda * S + (1 - lambda) * (rvec %*% t(rvec))
		}
		return(S)
		}
		#******************************************************************************
		# Static PCA Check
		#******************************************************************************
		pca_static <- prcomp(pca_data %>% select(all_of(vars_clean)),
		center = TRUE, scale. = TRUE)
		static_var <- summary(pca_static)$importance[2,1] * 100
		cat(sprintf("Static PC1 variance: %.1f%%\n", static_var))
		#******************************************************************************
		# Rolling PCA
		#******************************************************************************
		pc1_variance <- rep(NA_real_, N_obs)
		pc2_variance <- rep(NA_real_, N_obs)
		r_HCI <- rep(NA_real_, N_obs)
		v1_matrix <- matrix(NA_real_, nrow = N_obs, ncol = N_var)
		colnames(v1_matrix) <- vars_clean
		contribs <- matrix(NA_real_, nrow = N_obs, ncol = N_var)
		colnames(contribs) <- vars_clean
		pb <- txtProgressBar(min = W, max = N_obs, style = 3)
		for(t in seq(W, N_obs)){
		window_idx <- (t - W + 1):t
		R_win <- as.matrix(pca_data[window_idx, vars_clean])
		S_t <- compute_ewma_cov(R_win, lambda = lambda)
		diagS <- diag(S_t)
		if(any(diagS <= 0 \| is.na(diagS))) next
		D_inv_sqrt <- diag(1 / sqrt(diagS))
		Omega_t <- D_inv_sqrt %% S_t %% D_inv_sqrt
		eig <- eigen(Omega_t, symmetric = TRUE)
		v1 <- eig$vectors[, 1]
		# Normalize: interest rates positive
		interest_idx <- which(vars_clean == "r_interest_new_avg_d")
		if(length(interest_idx) > 0 && v1[interest_idx] < 0) {
		v1 <- -v1
		}
		v1_matrix[t, ] <- v1
		pc1_variance[t] <- eig$values[1] / sum(eig$values) * 100
		pc2_variance[t] <- eig$values[2] / sum(eig$values) * 100
		r_t <- as.numeric(pca_data[t, vars_clean])
		r_HCI[t] <- sum(v1 * r_t)
		contribs[t, ] <- v1 * r_t
		setTxtProgressBar(pb, t)
		}
		close(pb)
		#******************************************************************************
		# Results
		#******************************************************************************
		results <- tibble(
		date = pca_data$date,
		r_HCI = r_HCI,
		pc1_variance = pc1_variance,
		pc2_variance = pc2_variance
		) %>%
		filter(!is.na(r_HCI)) %>%
		arrange(date) %>%
		mutate(
		HCI = 100 + cumsum(r_HCI),
		HAI = 200 - HCI
		)
		loadings_df <- as_tibble(v1_matrix) %>%
		mutate(date = pca_data$date) %>%
		select(date, everything()) %>%
		filter(!is.na(.[[2]]))
		contribs_df <- as_tibble(contribs) %>%
		mutate(date = pca_data$date) %>%
		select(date, everything()) %>%
		filter(!is.na(.[[2]]))
		#******************************************************************************
		# Summary Statistics
		#******************************************************************************
		avg_loadings <- colMeans(loadings_df %>% select(-date), na.rm = TRUE)
		avg_loadings_df <- tibble(
		variable = names(avg_loadings),
		avg_loading = avg_loadings
		) %>%
		arrange(desc(abs(avg_loading)))
		cumulative_contribs <- contribs_df %>%
		select(-date) %>%
		summarise(across(everything(), ~sum(., na.rm = TRUE))) %>%
		pivot_longer(everything(), names_to = "variable", values_to = "cumulative_contribution") %>%
		arrange(desc(abs(cumulative_contribution)))
		cat(sprintf("\nMean PC1 variance: %.1f%%\n", mean(results$pc1_variance, na.rm = TRUE)))
		cat(sprintf("Total cost change: %+.1f%%\n\n",
		(tail(results$HCI, 1) / head(results$HCI, 1) - 1) * 100))
		#******************************************************************************
		# Visualizations
		#******************************************************************************
		# 1. Housing Cost Index
		p1 <- ggplot(results, aes(x = date, y = HCI)) +
		geom_line(linewidth = 1.2, color = "darkred") +
		geom_hline(yintercept = 100, linetype = "dashed", color = "black", alpha = 0.5) +
		labs(title = "Housing Cost Index",
		subtitle = "Higher = More Expensive",
		y = "Cost Index (Base = 100)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold", size = 14))
		# 2. Housing Affordability Index
		p2 <- ggplot(results, aes(x = date, y = HAI)) +
		geom_line(linewidth = 1.2, color = "darkblue") +
		geom_hline(yintercept = 100, linetype = "dashed", color = "black", alpha = 0.5) +
		labs(title = "Housing Affordability Index",
		subtitle = "Higher = More Affordable",
		y = "Affordability Index (Base = 100)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold", size = 14))
		# 3. Quarterly changes
		p3 <- ggplot(results, aes(x = date, y = r_HCI)) +
		geom_col(aes(fill = r_HCI > 0)) +
		geom_hline(yintercept = 0, color = "black", linewidth = 0.5) +
		scale_fill_manual(values = c("TRUE" = "firebrick", "FALSE" = "forestgreen"),
		labels = c("Costs increased", "Costs decreased"),
		name = NULL) +
		labs(title = "Quarterly Changes in Housing Costs",
		y = "Change in Cost Index (%)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold"),
		legend.position = "bottom")
		# 4. PC1 variance
		p4 <- ggplot(results, aes(x = date, y = pc1_variance)) +
		geom_line(color = "darkgreen", linewidth = 1) +
		geom_hline(yintercept = 60, linetype = "dashed", color = "red", alpha = 0.5) +
		geom_hline(yintercept = mean(results$pc1_variance),
		linetype = "dashed", color = "blue", alpha = 0.5) +
		labs(title = "PC1 Variance Explained Over Time",
		y = "PC1 Variance (%)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold"))
		# 5. Time-varying loadings
		loadings_long <- loadings_df %>%
		pivot_longer(-date, names_to = "variable", values_to = "loading")
		p5 <- ggplot(loadings_long, aes(x = date, y = loading, color = variable)) +
		geom_line(linewidth = 0.8) +
		geom_hline(yintercept = 0, linetype = "dashed", alpha = 0.5) +
		labs(title = "Time-Varying PC1 Loadings",
		y = "PC1 Loading", x = NULL, color = "Variable") +
		theme_minimal(base_size = 11) +
		theme(plot.title = element_text(face = "bold"),
		legend.position = "bottom",
		legend.text = element_text(size = 8))
		# 6. Cumulative contributions
		contrib_plot <- cumulative_contribs %>%
		mutate(variable = fct_reorder(variable, cumulative_contribution))
		p6 <- ggplot(contrib_plot, aes(x = cumulative_contribution, y = variable)) +
		geom_col(aes(fill = cumulative_contribution > 0)) +
		scale_fill_manual(values = c("TRUE" = "firebrick", "FALSE" = "forestgreen"),
		labels = c("Increased costs", "Decreased costs"),
		name = NULL) +
		labs(title = "Cumulative Contributions to Cost Change",
		x = "Cumulative Contribution", y = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold"),
		legend.position = "bottom")
		# Save plots
		ggsave("05_output/reduced/01_housing_cost_index.pdf", p1, width = 14, height = 6)
		ggsave("05_output/reduced/02_affordability_index.pdf", p2, width = 14, height = 6)
		ggsave("05_output/reduced/03_quarterly_changes.pdf", p3, width = 14, height = 6)
		ggsave("05_output/reduced/04_PC1_variance.pdf", p4, width = 14, height = 6)
		ggsave("05_output/reduced/05_loadings_overtime.pdf", p5, width = 14, height = 7)
		ggsave("05_output/reduced/06_cumulative_contributions.pdf", p6, width = 12, height = 6)
		combined <- grid.arrange(p1, p3, p4, ncol = 1)
		ggsave("05_output/reduced/00_summary.pdf", combined, width = 14, height = 16)
		#******************************************************************************
		# Save Data
		#******************************************************************************
		write_csv(results, "05_output/reduced/housing_index_reduced.csv")
		write_csv(loadings_df, "05_output/reduced/loadings_reduced.csv")
		write_csv(contribs_df, "05_output/reduced/contributions_reduced.csv")
		write_csv(avg_loadings_df, "05_output/reduced/variable_summary_reduced.csv")
		write_csv(cumulative_contribs, "05_output/reduced/cumulative_contributions_reduced.csv")
		cat("Analysis complete\n")

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		#******************************************************************************
		# PCA-based Housing Cost Index - Reduced Variable Specification
		#******************************************************************************
		# Reduced from 30 to 8 core variables (removed redundancy)
		#******************************************************************************

		rm(list = ls())

		library(tidyverse)
		library(ggplot2)
		library(gridExtra)

		setwd("~/Main/Uni/Master/S3/git/mlw_project_tw_sr")
		#setwd("C:/Users/tomwa/Documents/git/mlw_project_tw_sr")

		dir.create("05_output/reduced", showWarnings = FALSE, recursive = TRUE)

		#******************************************************************************
		# Load Data
		#******************************************************************************

		pca_data <- read_csv("03_data/processed/affordability_data_returns_q.csv")

		#******************************************************************************
		# Variable Selection
		#******************************************************************************

		vars_clean <- c(
		"r_index_house_price_d",
		"r_interest_new_avg_d",
		"r_actual_rent_d",
		"r_maintenance_repair_aprtm_d",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d"
		)

		# Verify variables exist
		missing_vars <- setdiff(vars_clean, names(pca_data))
		if(length(missing_vars) > 0) {
		stop("Missing variables: ", paste(missing_vars, collapse = ", "))
		}

		# Parameters
		W <- 20
		lambda <- 0.97

		N_obs <- nrow(pca_data)
		N_var <- length(vars_clean)

		#******************************************************************************
		# Helper Functions
		#******************************************************************************

		compute_ewma_cov <- function(R_window, lambda){
		p <- ncol(R_window)
		S <- matrix(0, p, p)
		for(i in seq_len(nrow(R_window))){
		rvec <- matrix(R_window[i, ], ncol = 1)
		S <- lambda * S + (1 - lambda) * (rvec %*% t(rvec))
		}
		return(S)
		}

		#******************************************************************************
		# Static PCA Check
		#******************************************************************************

		pca_static <- prcomp(pca_data %>% select(all_of(vars_clean)),
		center = TRUE, scale. = TRUE)
		static_var <- summary(pca_static)$importance[2,1] * 100

		cat(sprintf("Static PC1 variance: %.1f%%\n", static_var))

		#******************************************************************************
		# Rolling PCA
		#******************************************************************************

		pc1_variance <- rep(NA_real_, N_obs)
		pc2_variance <- rep(NA_real_, N_obs)
		r_HCI <- rep(NA_real_, N_obs)
		v1_matrix <- matrix(NA_real_, nrow = N_obs, ncol = N_var)
		colnames(v1_matrix) <- vars_clean
		contribs <- matrix(NA_real_, nrow = N_obs, ncol = N_var)
		colnames(contribs) <- vars_clean

		pb <- txtProgressBar(min = W, max = N_obs, style = 3)

		for(t in seq(W, N_obs)){
		window_idx <- (t - W + 1):t
		R_win <- as.matrix(pca_data[window_idx, vars_clean])

		S_t <- compute_ewma_cov(R_win, lambda = lambda)

		diagS <- diag(S_t)
		if(any(diagS <= 0 \| is.na(diagS))) next

		D_inv_sqrt <- diag(1 / sqrt(diagS))
		Omega_t <- D_inv_sqrt %% S_t %% D_inv_sqrt

		eig <- eigen(Omega_t, symmetric = TRUE)
		v1 <- eig$vectors[, 1]

		# Normalize: interest rates positive
		interest_idx <- which(vars_clean == "r_interest_new_avg_d")
		if(length(interest_idx) > 0 && v1[interest_idx] < 0) {
		v1 <- -v1
		}

		v1_matrix[t, ] <- v1
		pc1_variance[t] <- eig$values[1] / sum(eig$values) * 100
		pc2_variance[t] <- eig$values[2] / sum(eig$values) * 100

		r_t <- as.numeric(pca_data[t, vars_clean])
		r_HCI[t] <- sum(v1 * r_t)

		contribs[t, ] <- v1 * r_t

		setTxtProgressBar(pb, t)
		}
		close(pb)

		#******************************************************************************
		# Results
		#******************************************************************************

		results <- tibble(
		date = pca_data$date,
		r_HCI = r_HCI,
		pc1_variance = pc1_variance,
		pc2_variance = pc2_variance
		) %>%
		filter(!is.na(r_HCI)) %>%
		arrange(date) %>%
		mutate(
		HCI = 100 + cumsum(r_HCI),
		HAI = 200 - HCI
		)

		loadings_df <- as_tibble(v1_matrix) %>%
		mutate(date = pca_data$date) %>%
		select(date, everything()) %>%
		filter(!is.na(.[[2]]))

		contribs_df <- as_tibble(contribs) %>%
		mutate(date = pca_data$date) %>%
		select(date, everything()) %>%
		filter(!is.na(.[[2]]))

		#******************************************************************************
		# Summary Statistics
		#******************************************************************************

		avg_loadings <- colMeans(loadings_df %>% select(-date), na.rm = TRUE)
		avg_loadings_df <- tibble(
		variable = names(avg_loadings),
		avg_loading = avg_loadings
		) %>%
		arrange(desc(abs(avg_loading)))

		cumulative_contribs <- contribs_df %>%
		select(-date) %>%
		summarise(across(everything(), ~sum(., na.rm = TRUE))) %>%
		pivot_longer(everything(), names_to = "variable", values_to = "cumulative_contribution") %>%
		arrange(desc(abs(cumulative_contribution)))

		cat(sprintf("\nMean PC1 variance: %.1f%%\n", mean(results$pc1_variance, na.rm = TRUE)))
		cat(sprintf("Total cost change: %+.1f%%\n\n",
		(tail(results$HCI, 1) / head(results$HCI, 1) - 1) * 100))

		#******************************************************************************
		# Visualizations
		#******************************************************************************

		# 1. Housing Cost Index
		p1 <- ggplot(results, aes(x = date, y = HCI)) +
		geom_line(linewidth = 1.2, color = "darkred") +
		geom_hline(yintercept = 100, linetype = "dashed", color = "black", alpha = 0.5) +
		labs(title = "Housing Cost Index",
		subtitle = "Higher = More Expensive",
		y = "Cost Index (Base = 100)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold", size = 14))

		# 2. Housing Affordability Index
		p2 <- ggplot(results, aes(x = date, y = HAI)) +
		geom_line(linewidth = 1.2, color = "darkblue") +
		geom_hline(yintercept = 100, linetype = "dashed", color = "black", alpha = 0.5) +
		labs(title = "Housing Affordability Index",
		subtitle = "Higher = More Affordable",
		y = "Affordability Index (Base = 100)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold", size = 14))

		# 3. Quarterly changes
		p3 <- ggplot(results, aes(x = date, y = r_HCI)) +
		geom_col(aes(fill = r_HCI > 0)) +
		geom_hline(yintercept = 0, color = "black", linewidth = 0.5) +
		scale_fill_manual(values = c("TRUE" = "firebrick", "FALSE" = "forestgreen"),
		labels = c("Costs increased", "Costs decreased"),
		name = NULL) +
		labs(title = "Quarterly Changes in Housing Costs",
		y = "Change in Cost Index (%)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold"),
		legend.position = "bottom")

		# 4. PC1 variance
		p4 <- ggplot(results, aes(x = date, y = pc1_variance)) +
		geom_line(color = "darkgreen", linewidth = 1) +
		geom_hline(yintercept = 60, linetype = "dashed", color = "red", alpha = 0.5) +
		geom_hline(yintercept = mean(results$pc1_variance),
		linetype = "dashed", color = "blue", alpha = 0.5) +
		labs(title = "PC1 Variance Explained Over Time",
		y = "PC1 Variance (%)", x = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold"))

		# 5. Time-varying loadings
		loadings_long <- loadings_df %>%
		pivot_longer(-date, names_to = "variable", values_to = "loading")

		p5 <- ggplot(loadings_long, aes(x = date, y = loading, color = variable)) +
		geom_line(linewidth = 0.8) +
		geom_hline(yintercept = 0, linetype = "dashed", alpha = 0.5) +
		labs(title = "Time-Varying PC1 Loadings",
		y = "PC1 Loading", x = NULL, color = "Variable") +
		theme_minimal(base_size = 11) +
		theme(plot.title = element_text(face = "bold"),
		legend.position = "bottom",
		legend.text = element_text(size = 8))

		# 6. Cumulative contributions
		contrib_plot <- cumulative_contribs %>%
		mutate(variable = fct_reorder(variable, cumulative_contribution))

		p6 <- ggplot(contrib_plot, aes(x = cumulative_contribution, y = variable)) +
		geom_col(aes(fill = cumulative_contribution > 0)) +
		scale_fill_manual(values = c("TRUE" = "firebrick", "FALSE" = "forestgreen"),
		labels = c("Increased costs", "Decreased costs"),
		name = NULL) +
		labs(title = "Cumulative Contributions to Cost Change",
		x = "Cumulative Contribution", y = NULL) +
		theme_minimal(base_size = 13) +
		theme(plot.title = element_text(face = "bold"),
		legend.position = "bottom")

		# Save plots
		ggsave("05_output/reduced/01_housing_cost_index.pdf", p1, width = 14, height = 6)
		ggsave("05_output/reduced/02_affordability_index.pdf", p2, width = 14, height = 6)
		ggsave("05_output/reduced/03_quarterly_changes.pdf", p3, width = 14, height = 6)
		ggsave("05_output/reduced/04_PC1_variance.pdf", p4, width = 14, height = 6)
		ggsave("05_output/reduced/05_loadings_overtime.pdf", p5, width = 14, height = 7)
		ggsave("05_output/reduced/06_cumulative_contributions.pdf", p6, width = 12, height = 6)

		combined <- grid.arrange(p1, p3, p4, ncol = 1)
		ggsave("05_output/reduced/00_summary.pdf", combined, width = 14, height = 16)

		#******************************************************************************
		# Save Data
		#******************************************************************************

		write_csv(results, "05_output/reduced/housing_index_reduced.csv")
		write_csv(loadings_df, "05_output/reduced/loadings_reduced.csv")
		write_csv(contribs_df, "05_output/reduced/contributions_reduced.csv")
		write_csv(avg_loadings_df, "05_output/reduced/variable_summary_reduced.csv")
		write_csv(cumulative_contribs, "05_output/reduced/cumulative_contributions_reduced.csv")

		cat("Analysis complete\n")
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		#******************************************************************************
		# Housing Affordability Index for Baden-Württemberg (2004-2024)
		# PCA-Based Composite Index Construction
		#******************************************************************************
		#
		# PROJECT STRUCTURE - Execute scripts in order:
		#
		# 1. 01_251104_Data_Cleaning.R → Preprocess raw data
		# 2. 02_251114_Index_Computation.R → Compute HAI and generate outputs
		# 3. 03_251118_Robustness_Test.R → Sensitivity analysis
		#
		# SETUP - Set your working directory:
		# 1. Copy the file path where you saved this project folder
		# 2. Replace the path below with your path
		# 3. Uncomment the setwd() line by removing the #
		#
		# setwd("YOUR_PATH_HERE/mlw_project_tw_sr")

		#******************************************************************************

		#******************************************************************************
		# Set WD and load required libraries ----
		#******************************************************************************

		rm(list = ls())


		library(tidyverse)
		library(zoo)
		library(stringr)
		library(lubridate)
		library(janitor)
		library(readxl)
		library(ggplot2)
		library(dplyr)
		library(forecast)
		library(tidyr)
		library(tseries)
		library(seastests)


		# SR WD
		#setwd("~/Main/Uni/Master/S3/git/mlw_project_tw_sr")

		#TW WD
		# setwd("C:/Users/tomwa/Documents/git/mlw_project_tw_sr")

		#******************************************************************************
		# Load data ----
		#******************************************************************************

		house_prices <- read_csv("03_data/data_given/house_price_index_D_q.csv")
		bb_ratios <- read_csv("03_data/data_given/bb_houseprice_income_ratios_D_q.csv")
		housing_costs <- read_csv("03_data/data_given/housing_costs_index_D_m.csv")
		construction_prices <- read_csv("03_data/data_given/construction_prices_bw_q.csv")
		bb_interest_rates <- read_csv("03_data/data_given/bb_interest_rates_D_m.csv")
		bb_volumes <- read_csv("03_data/data_given/bb_volumes_D_m.csv")
		income_raw <- read_excel("03_data/data_destatis/disp_income_y_bw.xlsx",
		sheet = "Verfügbares Einkommen",
		skip = 2)
		real_income_raw <- read.csv(
		"03_data/data_destatis/genesis_bw/31111_0001_real_income_bw_q.csv",
		sep = ";",
		skip = 6,
		encoding = "latin1",
		check.names = FALSE
		)
		priceindex_housing <- read.csv(
		"03_data/data_destatis/genesis_bw/61261_0003_priceindex_housing_bw_q.csv",
		sep = ";",
		skip = 3,
		encoding = "latin1",
		check.names = FALSE
		)



		#******************************************************************************
		# Clean data ----
		#******************************************************************************



		house_prices_clean <- house_prices %>%
		clean_names() %>%
		mutate(date = as.Date(as.yearqtr(date))) %>%
		arrange(date) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, quarter)) %>%
		select(-c("quarter", "year"))
		head(house_prices_clean)


		bb_ratios_clean <- bb_ratios %>%
		clean_names() %>%
		mutate(date = as.Date(as.yearqtr(date))) %>%
		arrange(date) %>%
		rename_with(~ paste0(.x, "_ratio_d"),
		.cols = -c(date, year, quarter)) %>%
		select(-c("quarter", "year"))

		head(bb_ratios_clean)


		housing_costs_clean <- housing_costs %>%
		clean_names() %>%
		mutate(date = ymd(paste0(date, "-01")),
		quarter = as.yearqtr(date)) %>%
		group_by(quarter) %>%
		summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
		mutate(date = as.Date(quarter)) %>%
		select(-quarter) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, month)) %>%
		select(-c("month", "year"))
		head(housing_costs_clean)


		construction_prices_clean <- construction_prices %>%
		clean_names() %>%
		mutate(date = as.Date(as.yearqtr(date))) %>%
		arrange(date) %>%
		rename_with(~ paste0(.x, "_bw"),
		.cols = -c(date, year, quarter)) %>%
		select(-c("quarter", "year"))
		head(construction_prices_clean)


		bb_interest_rates_clean <- bb_interest_rates %>%
		clean_names() %>%
		mutate(date = ymd(paste0(date, "-01")),
		quarter = as.yearqtr(date)) %>%
		group_by(quarter) %>%
		summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
		mutate(date = as.Date(quarter)) %>%
		select(-quarter) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, month)) %>%
		select(-c("month", "year"))
		head(bb_interest_rates_clean)


		bb_volumes_clean <- bb_volumes %>%
		clean_names() %>%
		mutate(date = ymd(paste0(date, "-01")),
		quarter = as.yearqtr(date)) %>%
		group_by(quarter) %>%
		summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
		mutate(date = as.Date(quarter)) %>%
		select(-quarter) %>%
		rename_with(~ paste0(.x, "_d"),
		.cols = -c(date, year, month)) %>%
		select(-c("month", "year"))
		head(bb_volumes_clean)


		#******************************************************************************
		# Clean Disposable Household Income ----
		#******************************************************************************


		income_bw <- income_raw %>%
		clean_names() %>%
		select(jahr, baden_wurttemberg) %>%
		mutate(
		jahr = as.numeric(str_extract(jahr, "\\d{4}")), # extract year number safely
		baden_wurttemberg = as.numeric(baden_wurttemberg)
		) %>%
		filter(!is.na(jahr), !is.na(baden_wurttemberg)) %>%
		distinct(jahr, .keep_all = TRUE) %>% # remove duplicates
		arrange(jahr) %>%
		rename(disp_income_bw = baden_wurttemberg)

		# Quick sanity check
		print(income_bw)

		# Create zoo object (annual data)
		income_bw_zoo <- zoo(income_bw$disp_income_bw, as.yearqtr(income_bw$jahr))

		# Define quarterly sequence safely
		quarter_seq <- seq(from = min(as.yearqtr(income_bw$jahr)),
		to = max(as.yearqtr(income_bw$jahr)),
		by = 0.25)

		# Interpolate linearly between annual points
		income_bw_quarterly <- na.approx(income_bw_zoo, xout = quarter_seq)

		# Convert back to tibble
		income_bw_quarterly_df <- tibble(
		date = as.Date(time(income_bw_quarterly)),
		disp_income_bw = as.numeric(income_bw_quarterly)
		)





		# PLOT: just for justification: ANNUAL vs. QUARTERLY (interpolated)
		income_bw_annual_df <- income_bw %>%
		mutate(date = as.Date(paste0(jahr, "-12-31"))) %>%
		select(date, disp_income_bw = disp_income_bw)
		ggplot() +
		# Quarterly interpolated line
		geom_line(data = income_bw_quarterly_df,
		aes(x = date, y = disp_income_bw, color = "Quarterly (Interpolated)"),
		size = 1) +
		# Annual observed points
		geom_point(data = income_bw_annual_df,
		aes(x = date, y = disp_income_bw, color = "Annual (Observed)"),
		size = 2.5) +
		# Labels and theme
		scale_color_manual(values = c("Quarterly (Interpolated)" = "steelblue",
		"Annual (Observed)" = "firebrick")) +
		labs(title = "Income in Baden-Württemberg: Annual vs. Interpolated Quarterly Data",
		x = "Year",
		y = "Disposable Income (EUR)",
		color = "Data Type") +
		theme_minimal(base_size = 13)


		#******************************************************************************
		# Clean Real Income ----
		#******************************************************************************


		real_income_clean <- real_income_raw[1:97,1:3]


		real_income_clean <- real_income_raw %>%
		clean_names() %>%
		select(
		year = 1,
		period = 2,
		reallohnindex_alle_arbeitnehmenden = 3
		) %>%
		# Remove empty rows
		filter(!is.na(reallohnindex_alle_arbeitnehmenden) & reallohnindex_alle_arbeitnehmenden != "") %>%
		# Convert numeric (comma → dot)
		mutate(
		reallohnindex_alle_arbeitnehmenden = as.numeric(str_replace(reallohnindex_alle_arbeitnehmenden, ",", ".")),
		year = as.numeric(year) # convert year to numeric
		) %>%
		# Remove empty rows
		filter(!is.na(reallohnindex_alle_arbeitnehmenden)) %>%
		# Keep only quarterly rows (drop "Insgesamt")
		filter(!str_detect(period, "Insgesamt")) %>%
		mutate(
		quarter = case_when(
		str_detect(period, "Erstes Quartal") ~ 1,
		str_detect(period, "Zweites Quartal") ~ 2,
		str_detect(period, "Drittes Quartal") ~ 3,
		str_detect(period, "Viertes Quartal") ~ 4
		),
		# Create yearqtr object
		date = as.yearqtr(year + (quarter - 1)/4),
		# Convert to Date (yyyy-mm-dd), first day of the quarter
		date = as.Date(date)
		) %>%
		select(date, real_income_bw = reallohnindex_alle_arbeitnehmenden) %>%
		arrange(date)

		head(real_income_clean)

		#******************************************************************************
		# Clean Housing Priceindex BW ----
		#******************************************************************************

		priceindex_housing_clean <- priceindex_housing[1:79,1:2]


		housing_prices_clean <- priceindex_housing_clean %>%
		clean_names() %>%
		select(
		year = 1,
		index = 2
		) %>%
		# Remove empty rows and non-numeric headers
		filter(!is.na(index) & !index %in% c("Baupreisindizes", "Wohngebäude", "2021 = 100")) %>%
		# Convert to numeric
		mutate(
		year = as.numeric(year),
		index = as.numeric(str_replace(index, ",", "."))
		) %>%
		filter(!is.na(year) & !is.na(index)) %>%
		arrange(year)

		# Step 2: Create a zoo object for interpolation
		housing_zoo <- zoo(housing_prices_clean$index, as.yearqtr(housing_prices_clean$year))

		# Step 3: Define quarterly sequence
		quarter_seq <- seq(from = min(as.yearqtr(housing_prices_clean$year)),
		to = max(as.yearqtr(housing_prices_clean$year)),
		by = 0.25) # 0.25 = quarterly steps

		# Step 4: Interpolate linearly to quarterly values
		housing_quarterly <- na.approx(housing_zoo, xout = quarter_seq)

		# Step 5: Convert back to tibble
		housing_quarterly_df <- tibble(
		date = as.Date(time(housing_quarterly)), # yyyy-mm-dd format
		housing_price_bw = as.numeric(housing_quarterly)
		)

		# Quick sanity check
		head(housing_quarterly_df)



		# Prepare annual data for plotting
		housing_annual_df <- housing_prices_clean %>%
		mutate(date = as.Date(paste0(year, "-12-31"))) %>% # assign Dec 31 to annual data
		select(date, housing_price_bw = index)

		# Plot: annual vs. quarterly interpolated
		ggplot() +
		# Quarterly interpolated line
		geom_line(data = housing_quarterly_df,
		aes(x = date, y = housing_price_bw, color = "Quarterly (Interpolated)"),
		size = 1) +
		# Annual observed points
		geom_point(data = housing_annual_df,
		aes(x = date, y = housing_price_bw, color = "Annual (Observed)"),
		size = 2.5) +
		# Color labels
		scale_color_manual(values = c("Quarterly (Interpolated)" = "steelblue",
		"Annual (Observed)" = "firebrick")) +
		# Labels and theme
		labs(title = "Housing Price Index in Baden-Württemberg: Annual vs. Interpolated Quarterly Data",
		x = "Year",
		y = "Housing Price Index (2021 = 100)",
		color = "Data Type") +
		theme_minimal(base_size = 13)



		#******************************************************************************
		# NOWCASTING DISP-INCOME BW ----
		#******************************************************************************


		# Create a full quarterly sequence from 2004 Q1 to 2024 Q4
		full_quarters <- seq(as.Date("2004-01-01"), as.Date("2024-12-31"), by = "quarter")

		# Merge your actual data into this full sequence
		income_bw_quarterly_df <- tibble(date = full_quarters) %>%
		left_join(income_bw_quarterly_df, by = "date")

		# Load and prepare the time series
		income_ts <- ts(income_bw_quarterly_df$disp_income_bw,
		start = c(2004, 1),
		frequency = 4)

		# Count NAs at the end (to forecast)
		n_ahead <- sum(is.na(income_ts))


		# 1. Explore and difference our timeseries


		# Plot the original time series
		autoplot(income_ts) +
		labs(title = "Disposable Income BW: Original Series",
		x = "Year", y = "Disposable Income (EUR)") +
		theme_minimal(base_size = 13)

		# First differences (relative growth)
		income_diff1 <- 100 * (income_ts[-1] - income_ts[-length(income_ts)]) / income_ts[-length(income_ts)]

		# Second differences (acceleration of growth)
		income_diff2 <- diff(income_diff1)

		# Convert to time series for plotting (starts 2 quarters later)
		income_diff2_ts <- ts(income_diff2, start = c(2004, 3), frequency = 4)


		# 2. Visualize the timeseries


		# Plot relative first differences
		autoplot(ts(income_diff1, start = c(2004, 2), frequency = 4)) +
		labs(title = "Relative First Differences (Quarterly Growth) of Disposable Income BW",
		x = "Year", y = "Δ% Disposable Income") +
		theme_minimal(base_size = 13)

		# Plot second differences
		autoplot(income_diff2_ts) +
		labs(title = "Second Differences of Disposable Income BW",
		x = "Year", y = "Δ² Disposable Income") +
		theme_minimal(base_size = 13)


		# 3. Test for Stationarity (find correct Integration-level)


		adf_test_diff2 <- adf.test(na.omit(income_diff2), alternative = "stationary")
		print(adf_test_diff2)
		# we can reject the Nullhypothesis of a unit root at the 5% level!!


		# 4. Inspect ACF and PACF


		income_diff2_clean <- na.omit(income_diff2)

		par(mfrow = c(1, 2))
		acf(income_diff2_clean, main = "ACF of Second Differences")
		pacf(income_diff2_clean, main = "PACF of Second Differences")
		par(mfrow = c(1, 1))

		# Compute ACF & PACF numerically (for reference)
		acf_result <- acf(income_diff2_clean, plot = FALSE)
		pacf_result <- pacf(income_diff2_clean, plot = FALSE)

		# Combine ACF and PACF (first 20 lags)
		result_table <- data.frame(
		lag = 1:length(pacf_result$acf),
		acf = acf_result$acf[-1, , 1],
		pacf = pacf_result$acf
		)
		print(result_table)


		# 5. Fit the ARIMA-Model to forecast the missing values at the end


		# ARIMA(p, d, q)
		# p -> number of autoregressive (AR) lags
		# d -> number of non-seasonal differences to achieve stationarity
		# q -> number of moving average (MA) lags

		income_ts_fit <- na.omit(income_ts)

		# Fit SARIMA(0,2,0)(0,0,0)[4]
		fit_sarima <- Arima(income_ts_fit,
		order = c(0, 2, 0),
		seasonal = list(order = c(0, 0, 0), period = 4))

		checkresiduals(fit_sarima)
		# including a seasonal MA-Term to account for the spikes at lag 8,12 & 16


		# 6. Forecast the missing values


		forecast_income <- forecast(fit_sarima, h = n_ahead)

		# Fill in forecasted values
		income_bw_quarterly_df$disp_income_bw[is.na(income_bw_quarterly_df$disp_income_bw)] <-
		as.numeric(forecast_income$mean)

		# Mark observed vs. forecasted data
		income_bw_quarterly_df <- income_bw_quarterly_df %>%
		mutate(series_type = if_else(row_number() > nrow(income_bw_quarterly_df) - n_ahead,
		"Forecasted", "Observed"))


		# 7. Plot the observed and forecasted Values


		plot_df <- income_bw_quarterly_df %>%
		select(date, disp_income_bw, series_type)

		ggplot(plot_df, aes(x = date, y = disp_income_bw, color = series_type)) +
		geom_line(size = 1) +
		scale_color_manual(values = c("Observed" = "firebrick", "Forecasted" = "steelblue")) +
		labs(title = "Disposable Income BW: Observed vs SARIMA Forecast",
		x = "Quarter", y = "Disposable Income (EUR)", color = "Series") +
		theme_minimal(base_size = 13)

		income_bw_quarterly_df <- income_bw_quarterly_df %>%
		select(-"series_type")


		#******************************************************************************
		# Merge ----
		#******************************************************************************

		final_data <- house_prices_clean %>%
		full_join(bb_ratios_clean, by = "date") %>%
		full_join(housing_costs_clean, by = "date") %>%
		full_join(construction_prices_clean, by = "date") %>%
		full_join(bb_interest_rates_clean, by = "date") %>%
		full_join(bb_volumes_clean, by = "date") %>%
		full_join(real_income_clean, by = "date") %>%
		full_join(income_bw_quarterly_df, by = "date") %>%
		arrange(date)


		final_data_clean <- final_data %>%
		filter(date >= as.Date("2004-01-01"),
		date <= as.Date("2024-12-31")) %>%
		select(-real_income_bw) # FOR NOW: REMOVING REAL-INCOME (MAYBE BACKCAST LATER)



		#******************************************************************************
		# Adjusting for Seasonality ----
		#******************************************************************************

		ts_to_plot <- final_data_clean

		# reshape to long format for ggplot
		ts_long <- ts_to_plot %>%
		pivot_longer(-date, names_to = "variable", values_to = "value")

		# plot: all time series as separate facets
		ggplot(ts_long, aes(x = date, y = value, color = variable)) +
		geom_line(show.legend = FALSE) +
		facet_wrap(~ variable, scales = "free_y", ncol = 2) + # 2 columns, separate y-scales
		labs(title = "Quarterly Time Series Overview: Detecting Seasonal Patterns",
		x = "Year", y = "Value") +
		theme_minimal(base_size = 13) +
		theme(strip.text = element_text(face = "bold", size = 12))

		data_sa <- final_data_clean

		# Identify numeric columns (but exclude date!)
		cols_to_adjust <- data_sa %>% select(-date) %>% names()

		# init list to store adjusted series
		adjusted_list <- list()

		# Loop through each column
		for(col in cols_to_adjust){

		# Convert to ts (quarterly)
		ts_data <- ts(data_sa[[col]], start = c(year(min(data_sa$date)), quarter(min(data_sa$date))),
		frequency = 4)

		# Check for seasonality
		seasonal_flag <- isSeasonal(ts_data, test = "combined", freq = 4)

		if(seasonal_flag){
		# Apply STL decomposition
		stl_fit <- stl(ts_data, s.window = "periodic", robust = TRUE)

		# Decide additive vs multiplicative
		# Heuristic: if all values positive, assume multiplicative
		if(all(ts_data > 0)){
		# Multiplicative: log-transform
		ts_adj <- exp(seasadj(stl(log(ts_data), s.window = "periodic")))
		} else {
		# Additive: directly adjust
		ts_adj <- seasadj(stl_fit)
		}

		} else {
		# if no seasonality detected: leave original data
		ts_adj <- ts_data
		}

		adjusted_list[[col]] <- ts_adj
		}

		# Combine adjusted series into a data frame
		data_sa_adjusted <- data.frame(date = data_sa$date, adjusted_list)

		adjusted_summary <- sapply(cols_to_adjust, function(col){
		ts_data <- ts(data_sa[[col]], start = c(year(min(data_sa$date)), quarter(min(data_sa$date))),
		frequency = 4)
		isSeasonal(ts_data, test = "combined", freq = 4)
		})

		# Print variables that were adjusted
		adjusted_vars <- names(adjusted_summary[adjusted_summary == TRUE])
		print("These variables got seasonally adjusted:")
		print(adjusted_vars)

		head(data_sa_adjusted)

		# implement the adjusted data to the final df
		final_data_clean <- data_sa_adjusted



		#******************************************************************************
		# Handling Outliars: Winsorization ----
		#******************************************************************************


		# define Winsorize function
		winsorize_manual <- function(x, probs = c(0.01, 0.99)) {
		q <- quantile(x, probs = probs, na.rm = TRUE)
		x[x < q[1]] <- q[1]
		x[x > q[2]] <- q[2]
		return(x)
		}

		# Apply to all cols
		data_sa_winsor <- data_sa_adjusted
		cols_to_winsor <- data_sa_winsor %>% select(-date) %>% names()

		for(col in cols_to_winsor){
		data_sa_winsor[[col]] <- winsorize_manual(data_sa_winsor[[col]], probs = c(0.01, 0.99))
		}

		summary(data_sa_winsor)
		final_data_clean <- data_sa_winsor



		#******************************************************************************
		# Computing LOG-returns of our variables ----
		#******************************************************************************


		# Keep the clean level data
		level_data <- final_data_clean

		# Identify numeric columns
		numeric_cols <- level_data %>% select(-date) %>% names()

		# Compute log-returns (percent)
		return_data <- level_data %>%
		arrange(date) %>%
		mutate(across(all_of(numeric_cols),
		~ 100 * (log(.) - log(lag(.))),
		.names = "r_{col}"))

		# Replace original values with returns (except date)
		return_data <- return_data %>%
		select(date, all_of(paste0("r_", numeric_cols)))

		# Drop the first NA row from lag()
		return_data <- return_data %>% filter(!is.na(.[[2]]))

		# Output: return_data is now the PCA input
		head(return_data)


		# Comment:
		# Applying with the methodology we avoid standardization, normalization or stabilize variances!
		# Instead the data is uses as Log-Returns.
		# This is important, as the EWMA covariance already handles scale and variance dynamically.
		# Furthermore the correlation matrix normalizes the variables automatically.
		# Variance stabilization is already achieved by using log returns.



		#******************************************************************************
		# Align sign for "negative" variables (higher = less affordable) ----
		#******************************************************************************


		# we need to define variables where an increase reduces affordability (then flip signs for them)
		neg_afford_vars <- c("r_index_house_price_d",
		"r_index_existing_buildings_d",
		"r_index_new_buildings_d",
		"r_annuity_income_ratio_d",
		"r_houseprice_income_ratio_d",
		"r_houseprice_rent_ratio_d",
		"r_actual_rent_d",
		"r_cost_gas_d",
		"r_cost_oil_d",
		"r_electricity_cost_d",
		"r_maintenance_repair_aprtm_d",
		"r_construction_price_index_bw",
		"r_interest_existing_1_d",
		"r_interest_existing_1_5_d",
		"r_interest_existing_5_d",
		"r_interest_new_1_d",
		"r_interest_new_1_5_d",
		"r_interest_new_5_10_d",
		"r_interest_new_10_d",
		"r_interest_new_avg_d")

		# Apply sign flip to their log returns
		return_data <- return_data %>%
		mutate(across(all_of(neg_afford_vars), ~ . * -1))

		# now all returns are aligned so that positive = more affordable
		head(return_data)

		# plot(cumsum(pca_data$r_houseprice_income_ratio_d))



		#******************************************************************************
		# Save cleaned data ----
		#******************************************************************************


		write_csv(return_data, "03_data/processed/affordability_data_returns_q.csv")
		write_csv(level_data, "03_data/processed/affordability_data_levels_q.csv")

00_original_index/02_code/02_251114_Index_Computation.R

0 → 100644

+518 −0

Original line number	Diff line number	Diff line
		#******************************************************************************
		# Housing Affordability Index for Baden-Württemberg (2004-2024)
		# PCA-Based Composite Index Construction
		#******************************************************************************
		#
		# PROJECT STRUCTURE - Execute scripts in order:
		#
		# 1. 01_251104_Data_Cleaning.R → Preprocess raw data
		# 2. 02_251114_Index_Computation.R → Compute HAI and generate outputs
		# 3. 03_251118_Robustness_Test.R → Sensitivity analysis
		#
		# SETUP - Set your working directory:
		# 1. Copy the file path where you saved this project folder
		# 2. Replace the path below with your path
		# 3. Uncomment the setwd() line by removing the #
		#
		# setwd("YOUR_PATH_HERE/mlw_project_tw_sr")

		#******************************************************************************

		#******************************************************************************
		# PCA-based Affordability Index ----
		#******************************************************************************

		rm(list = ls())

		library(tidyverse)
		library(ggplot2)
		library(scales)
		library(dplyr)

		#setwd("~/Main/Uni/Master/S3/git/mlw_project_tw_sr")
		#setwd("C:/Users/tomwa/Documents/git/mlw_project_tw_sr")

		#******************************************************************************
		# Load Data ----
		#******************************************************************************

		pca_data <- read_csv("03_data/processed/affordability_data_returns_q.csv")
		head(pca_data)

		#******************************************************************************
		# Correlation Matrix ----
		#******************************************************************************
		# Correlation analysis
		all_vars <- names(pca_data)[names(pca_data) != "date"]
		cor_matrix_full <- cor(pca_data %>% select(all_of(all_vars)), use = "complete.obs")

		# Identify high correlations (\|r\| > 0.90)
		high_cor_pairs <- which(abs(cor_matrix_full) > 0.90 & abs(cor_matrix_full) < 1, arr.ind = TRUE)

		high_cors <- data.frame()
		for(i in 1:nrow(high_cor_pairs)) {
		if(high_cor_pairs[i,1] < high_cor_pairs[i,2]) {
		var1 <- rownames(cor_matrix_full)[high_cor_pairs[i,1]]
		var2 <- colnames(cor_matrix_full)[high_cor_pairs[i,2]]
		corr <- cor_matrix_full[high_cor_pairs[i,1], high_cor_pairs[i,2]]
		high_cors <- rbind(high_cors, data.frame(var1 = var1, var2 = var2, correlation = corr))
		}
		}

		high_cors <- high_cors %>% arrange(desc(abs(correlation)))
		print(high_cors)

		# Save outputs
		dir.create("05_output/variable_selection", showWarnings = FALSE, recursive = TRUE)
		write_csv(high_cors, "05_output/variable_selection/high_correlations.csv")

		# Save full correlation matrix
		cor_df <- as.data.frame(cor_matrix_full) %>% rownames_to_column("variable")
		write_csv(cor_df, "05_output/variable_selection/correlation_matrix.csv")

		# Heatmap
		library(corrplot)
		pdf("05_output/variable_selection/correlation_heatmap.pdf", width = 16, height = 16)
		corrplot(cor_matrix_full, method = "color", type = "lower", tl.cex = 0.6, tl.col = "black")
		dev.off()

		#******************************************************************************
		# EWMA + Rolling PCA -> PCA-based Affordability Index ----
		#******************************************************************************

		# Parameters
		W <- 20 # rolling window (quarters)
		lambda <- 0.97 # EWMA decay (how much weight past observations get)
		# Higher lambda -> the PCA loadings and index change more smoothly over time
		# Lower lambda -> the index is more responsive to recent volatility, but may be noisier
		ref_var <- "r_disp_income_bw" # reference return used for sign normalization

		# setup for PCA
		# selected Variables for Model
		vars <- c(
		"r_index_house_price_d",
		"r_interest_new_avg_d",
		"r_actual_rent_d",
		"r_maintenance_repair_aprtm_d",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d",
		"r_construction_price_index_bw"
		)
		# EXPLANATION FOR VARIABLE SELECTION:
		# Economic Theory???Driven Selection
		# - too many variables can make the Model hard to interpret
		# - also highly correlated variables can cause PCA to become unstable
		# - redundant variables can also overweight some effects (e.g. 8 almost similar interest rate-timeseries)

		N_obs <- nrow(pca_data)
		N_var <- length(vars)

		# Pre-allocations
		pc1_variance <- rep(NA_real_, N_obs) # Stores the percentage of total variance explained by PC1 at each time step
		r_HAI <- rep(NA_real_, N_obs) # Stores the composite return of the PCA-based affordability index for each period
		v1_matrix <- matrix(NA_real_, nrow = N_obs, ncol = N_var) # Stores the PC1 loadings (eigenvector) at each time step
		colnames(v1_matrix) <- vars
		contribs <- matrix(NA_real_, nrow = N_obs, ncol = N_var) # Stores the contribution of each variable to r_HAI
		colnames(contribs) <- vars

		# Helper: compute EWMA cov across a sequence of return rows (matrix rows = time)
		compute_ewma_cov <- function(R_window, lambda){
		# R_window: matrix (rows = t in window, cols = variables)
		p <- ncol(R_window)
		S <- matrix(0, p, p)
		# iterate through rows: use r_{s} r_{s}' with s from 1..nrow, recursively
		for(i in seq_len(nrow(R_window))){
		rvec <- matrix(R_window[i, ], ncol = 1)
		S <- lambda * S + (1 - lambda) * (rvec %*% t(rvec)) # see Formula 2 in Baur/Dimpfl/Pena
		}
		return(S)
		}

		# Advantage compared to standard PCA:
		# Standard sample covariance treats all observations equally.
		# EWMA gives more weight to recent observations, which is useful for capturing changing dynamics in housing affordability.

		# Rolling loop: for t = W ... N_obs
		for(t in seq(W, N_obs)){
		# window returns rows: (t-W+1) ... t
		window_idx <- (t - W + 1):t
		R_win <- as.matrix(pca_data[window_idx, vars]) # rows x cols

		# compute EWMA covariance on that window
		S_t <- compute_ewma_cov(R_win, lambda = lambda)

		# convert to correlation matrix (guard against zero variance)
		diagS <- diag(S_t)
		if(any(diagS <= 0 \| is.na(diagS))){
		# skip this t if impossible to form correlation
		next
		}
		D_inv_sqrt <- diag(1 / sqrt(diagS))
		Omega_t <- D_inv_sqrt %% S_t %% D_inv_sqrt # see Formula 3 in Baur/Dimpfl/Pena

		# eigen-decomposition
		eig <- eigen(Omega_t, symmetric = TRUE) # see Formula 4 in Baur/Dimpfl/Pena
		v1 <- eig$vectors[, 1] # see Formula 5 in Baur/Dimpfl/Pena

		# make our reference asset loading positive (affordability rises with income)
		ref_idx <- which(vars == ref_var)
		if (length(ref_idx) == 0) stop("Reference variable not found.")

		if (v1[ref_idx] < 0) {
		v1 <- -v1
		}

		# Normalization of eigenvector sign:
		# Since v1,t is an eigenvector, its sign is arbitrary. To ensure the resulting index
		# r_HAI moves in the expected direction (affordability rises with income), we base
		# the sign of v1,t on the reference variable (ref_var). This prevents sudden flips
		# in the sign of the index over time, aligning with the normalization approach
		# discussed in Baur/Dimpfl/Pena


		v1_matrix[t, ] <- v1
		pc1_variance[t] <- eig$values[1] / sum(eig$values) * 100

		r_t <- as.numeric(pca_data[t, vars])
		r_HAI[t] <- sum(v1 * r_t) # see Formula 6 in Baur/Dimpfl/Pena

		contribs[t, ] <- v1 * r_t
		}


		# Build results
		results <- tibble(
		date = pca_data$date,
		r_HAI = r_HAI,
		pc1_variance = pc1_variance
		)

		loadings_df <- as_tibble(v1_matrix) %>%
		mutate(date = pca_data$date) %>%
		select(date, everything())

		contribs_df <- as_tibble(contribs) %>%
		mutate(date = pca_data$date) %>%
		select(date, everything())

		# Drop leading NA rows
		results <- results %>% filter(!is.na(r_HAI))
		loadings_df <- loadings_df %>% filter(!is.na(.[[2]]))
		contribs_df <- contribs_df %>% filter(!is.na(.[[2]]))


		# Build cumulative index WITH FLIPPED RETURNS for consistency
		results <- results %>%
		arrange(date) %>%
		mutate(
		r_HAI_flipped = -r_HAI,
		HAI = 100 + cumsum(r_HAI_flipped) # Higher HAI = more affordable
		)

		# Diagnostics: average loadings
		avg_loadings <- colMeans(loadings_df %>% select(-date), na.rm = TRUE)
		avg_loadings_df <- tibble(variable = names(avg_loadings), avg_loading = avg_loadings) %>%
		arrange(desc(abs(avg_loading)))

		# Print diagnostics
		cat("\n=== DIAGNOSTICS ===\n")
		cat("\nAverage loadings (top contributors):\n")
		print(head(avg_loadings_df, 10))

		cat("\nIndex summary statistics:\n")
		cat("Mean r_HAI:", mean(results$r_HAI, na.rm = TRUE), "\n")
		cat("SD r_HAI:", sd(results$r_HAI, na.rm = TRUE), "\n")
		cat("Final HAI value:", tail(results$HAI, 1), "\n")
		cat("HAI range:", min(results$HAI), "to", max(results$HAI), "\n")

		# Check correlation with key variable
		ref_returns <- pca_data %>%
		filter(date %in% results$date) %>%
		pull(all_of(ref_var))

		cat("\nCorrelation with disposable income:", cor(results$r_HAI, ref_returns, use = "complete.obs"), "\n")

		if("r_construction_price_index_bw" %in% vars) {
		constr_prices_returns <- pca_data %>%
		filter(date %in% results$date) %>%
		pull(r_construction_price_index_bw)
		cat("Correlation with construction prices bw:", cor(results$r_HAI, constr_prices_returns, use = "complete.obs"), "\n")
		}

		# Save outputs
		write_csv(results, "05_output/affordability_index_pca_returns.csv")
		write_csv(loadings_df, "05_output/loadings_rolling_pca.csv")
		write_csv(contribs_df, "05_output/contributions_rolling_pca.csv")
		write_csv(avg_loadings_df, "05_output/avg_loadings_pca.csv")



		#******************************************************************************
		# computing Plots for the final Poster ----
		#******************************************************************************

		# Define Plot-Settings:
		theme_clean <- function() {
		theme_classic() +
		theme(
		panel.background = element_rect(fill = "white", color = NA),
		plot.background = element_rect(fill = "white", color = NA),
		panel.grid.major = element_blank(),
		panel.grid.minor = element_blank(),
		axis.line = element_line(color = "black", linewidth = 0.5),
		axis.ticks = element_line(color = "black"),
		axis.text = element_text(color = "black", size = 9), # increase axis tick font
		axis.title = element_text(color = "black", size = 11), # increase axis title font
		plot.title = element_text(color = "black", face = "bold"),
		legend.text = element_text(size = 9), # increase legend text font
		legend.title = element_text(size = 11), # increase legend title font
		plot.margin = margin(5, 5, 5, 5)
		)
		}


		# Plot 1: Cumulative Affordability Index

		p1 <- ggplot(results, aes(x = date, y = HAI)) +
		geom_line(linewidth = 1.4, color = "#80B1D3") +
		geom_hline(yintercept = 100, linetype = "dashed", color = "#E74C3C", linewidth = 0.8) +
		scale_x_date(expand = c(0, 0), date_breaks = "2 years", date_labels = "%Y") +
		scale_y_continuous(expand = c(0, 0), limits = c(min(results$HAI) - 5, max(results$HAI) + 5)) +
		labs(
		# title = "Housing Affordability Index (2004-2024)",
		# subtitle = "Higher values indicate greater affordability",
		y = "Affordability Index (Base = 100)",
		x = ""
		) +
		theme_clean()

		print(p1)
		ggsave("05_output/01_Plot_hai_cumulative.pdf", p1, width = 7, height = 3.5, device = cairo_pdf)

		#"#8DD3C7" "#FFFFB3" "#BEBADA" "#FB8072" "#80B1D3" "#FDB462" "#B3DE69" "#FCCDE5" "#D9D9D9" "#BC80BD" "#CCEBC5" "#FFED6F"



		# Plot 2: Period Returns with Color-Coded Bars (USING FLIPPED RETURNS)

		p2 <- ggplot(results, aes(x = date, y = r_HAI_flipped)) +
		geom_col(aes(fill = r_HAI_flipped > 0), width = 80) +
		geom_hline(yintercept = 0, color = "black", linewidth = 0.5) +
		scale_fill_manual(values = c("#E74C3C", "#27AE60"), guide = "none") +
		scale_x_date(expand = c(0, 0), date_breaks = "2 years", date_labels = "%Y") +
		scale_y_continuous(expand = c(0, 0)) +
		labs(
		# title = "Quarterly Changes in Housing Affordability",
		# subtitle = "Green = improving affordability, Red = declining affordability",
		y = "Affordability Change (%)",
		x = ""
		) +
		theme_clean()

		print(p2)
		ggsave("05_output/02_Plot_hai_returns.pdf", p2, width = 7, height = 4, device = cairo_pdf)



		# Plot 3: PC1 Variance Explained Over Time

		p3 <- ggplot(results, aes(x = date, y = pc1_variance)) +
		geom_area(fill = "#3498DB", alpha = 0.6) +
		geom_line(color = "#2C3E50", linewidth = 1) +
		scale_x_date(expand = c(0, 0), date_breaks = "2 years", date_labels = "%Y") +
		scale_y_continuous(expand = c(0, 0), limits = c(0, max(results$pc1_variance, na.rm = TRUE) + 2)) +
		labs(
		# title = "Variance Explained by First Principal Component",
		# subtitle = "Measures how well PC1 captures overall affordability dynamics",
		y = "Variance Explained (%)",
		x = ""
		) +
		theme_clean()

		print(p3)
		ggsave("05_output/03_Plot_pc1_variance.pdf", p3, width = 7, height = 4, device = cairo_pdf)



		# Plot 4: Average Loadings Bar Chart

		# Create clean variable labels
		avg_loadings_df <- avg_loadings_df %>%
		mutate(
		var_label = case_when(
		variable == "r_actual_rent_d" ~ "Rent",
		variable == "r_maintenance_repair_aprtm_d" ~ "Maintenance",
		variable == "r_construction_price_index_bw" ~ "Construction Costs",
		variable == "r_disp_income_bw" ~ "Disposable Income",
		variable == "r_volume_existing_overall_d" ~ "Existing Sales Volume",
		variable == "r_index_house_price_d" ~ "House Prices",
		variable == "r_houseprice_income_ratio_d" ~ "Price-Income Ratio",
		variable == "r_interest_new_avg_d" ~ "Interest Rates",
		variable == "r_volume_new_overall_d" ~ "New Sales Volume",
		TRUE ~ variable
		),
		var_label = fct_reorder(var_label, avg_loading)
		)

		p4 <- ggplot(avg_loadings_df, aes(x = var_label, y = avg_loading)) +
		geom_col(aes(fill = avg_loading > 0), width = 0.7) +
		geom_hline(yintercept = 0, color = "black", linewidth = 0.5) +
		scale_fill_manual(values = c("#FB9A99", "darkseagreen2"), guide = "none") +

		scale_y_continuous(expand = c(0, 0), limits = c(min(avg_loadings_df$avg_loading) - 0.05,
		max(avg_loadings_df$avg_loading) + 0.05)) +
		coord_flip() +
		labs(
		# title = "Average PCA Loadings by Variable",
		# subtitle = "Positive = increases affordability, Negative = decreases affordability",
		y = "Average Loading",
		x = ""
		) +
		theme_clean()

		print(p4)
		ggsave("05_output/04_Plot_avg_loadings.pdf", p4, width = 7, height = 3.5, device = cairo_pdf)



		# Plot 5: Time-Varying Loadings Heatmap

		# Reshape loadings for heatmap
		loadings_long <- loadings_df %>%
		pivot_longer(-date, names_to = "variable", values_to = "loading") %>%
		mutate(
		var_label = case_when(
		variable == "r_actual_rent_d" ~ "Rent",
		variable == "r_maintenance_repair_aprtm_d" ~ "Maintenance",
		variable == "r_construction_price_index_bw" ~ "Construction Costs",
		variable == "r_disp_income_bw" ~ "Disposable Income",
		variable == "r_volume_existing_overall_d" ~ "Existing Sales Vol.",
		variable == "r_index_house_price_d" ~ "House Prices",
		variable == "r_houseprice_income_ratio_d" ~ "Price-Income Ratio",
		variable == "r_interest_new_avg_d" ~ "Interest Rates",
		variable == "r_volume_new_overall_d" ~ "New Sales Vol.",
		TRUE ~ variable
		)
		)

		p5 <- ggplot(loadings_long, aes(x = date, y = var_label, fill = loading)) +
		geom_tile() +
		scale_fill_gradient2(
		low = "#E74C3C",
		mid = "white",
		high = "#27AE60",
		midpoint = 0,
		name = "Loading"
		) +
		scale_x_date(expand = c(0, 0), date_breaks = "2 years", date_labels = "%Y") +
		scale_y_discrete(expand = c(0, 0)) +
		labs(
		# title = "Evolution of PCA Loadings Over Time",
		# subtitle = "Shows how variable importance changes across time",
		y = "",
		x = ""
		) +
		theme_clean() +
		theme(
		legend.position = "right"
		)

		print(p5)
		ggsave("05_output/05_Plot_loadings_heatmap.pdf", p5, width = 7, height = 4, device = cairo_pdf)



		# Plot 6: Time-Varying PC1 Loadings (Line Plot)

		# Select key variables to plot (to avoid overcrowding)
		# key_vars <- c("r_disp_income_bw", "r_index_house_price_d", "r_actual_rent_d",
		# "r_construction_price_index_bw", "r_interest_new_avg_d")
		key_vars <- vars

		loadings_key <- loadings_long %>%
		filter(variable %in% key_vars)

		p6 <- ggplot(loadings_key, aes(x = date, y = loading, color = var_label)) +
		geom_line(linewidth = 1) +
		geom_hline(yintercept = 0, linetype = "dashed", color = "black", linewidth = 0.5) +
		scale_color_manual(
		values = c(
		"Disposable Income" = "#1F78B4",
		"House Prices" = "#E31A1C",
		"Rent" = "#FF7F00",
		"Construction Costs" = "#33A02C",
		"Interest Rates" = "#6A3D9A",
		"Maintenance" = "#B15928",
		"New Sales Vol." = "#A6CEE3",
		"Existing Sales Vol." = "#FB9A99",
		"Price-Income Ratio" = "#CAB2D6"
		),
		name = ""
		) +
		scale_x_date(expand = c(0, 0), date_breaks = "2 years", date_labels = "%Y") +
		scale_y_continuous(expand = c(0.02, 0.02)) +
		labs(
		# title = "Evolution of Key PCA Loadings Over Time",
		# subtitle = "Shows how variable weights change in the affordability index",
		y = "PC1 Loading",
		x = ""
		) +
		theme_clean() +
		theme(
		legend.position = "bottom"
		)

		print(p6)
		ggsave("05_output/06_Plot_loadings_timeseries.pdf", p6, width = 7, height = 4, device = cairo_pdf)



		# Plot 7: Cumulative Contributions Stacked Area

		# Calculate cumulative contributions (flipped to match HAI direction)
		contribs_cumulative <- contribs_df %>%
		select(-date) %>%
		mutate(across(everything(), ~ -cumsum(.x))) %>% # Flip sign for consistency
		mutate(date = contribs_df$date)

		# Reshape for stacked area plot
		contribs_cum_long <- contribs_cumulative %>%
		pivot_longer(-date, names_to = "variable", values_to = "cum_contrib") %>%
		mutate(
		var_label = case_when(
		variable == "r_actual_rent_d" ~ "Rent",
		variable == "r_maintenance_repair_aprtm_d" ~ "Maintenance",
		variable == "r_construction_price_index_bw" ~ "Construction Costs",
		variable == "r_disp_income_bw" ~ "Disposable Income",
		variable == "r_volume_existing_overall_d" ~ "Existing Sales Vol.",
		variable == "r_index_house_price_d" ~ "House Prices",
		variable == "r_houseprice_income_ratio_d" ~ "Price-Income Ratio",
		variable == "r_interest_new_avg_d" ~ "Interest Rates",
		variable == "r_volume_new_overall_d" ~ "New Sales Vol.",
		TRUE ~ variable
		)
		)

		p7 <- ggplot(contribs_cum_long, aes(x = date, y = cum_contrib, fill = var_label)) +
		geom_area(position = "stack", alpha = 0.8) +
		scale_fill_brewer(palette = "Set3", name = "") +
		scale_x_date(expand = c(0, 0), date_breaks = "2 years", date_labels = "%Y") +
		scale_y_continuous(expand = c(0, 0)) +
		labs(
		# title = "Cumulative Contributions to Affordability Change",
		# subtitle = "Decomposition showing which factors drove affordability changes since 2009",
		y = "Cumulative Contribution",
		x = ""
		) +
		theme_clean() +
		theme(
		legend.position = "bottom"
		) +
		guides(fill = guide_legend(nrow = 2))

		print(p7)
		ggsave("05_output/07_Plot_cumulative_contributions.pdf", p7, width = 7, height = 4, device = cairo_pdf)

00_original_index/02_code/03_251118_Robustness_Test.R

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Original line number	Diff line number	Diff line
		#******************************************************************************
		# Housing Affordability Index for Baden-Württemberg (2004-2024)
		# PCA-Based Composite Index Construction
		#******************************************************************************
		#
		# PROJECT STRUCTURE - Execute scripts in order:
		#
		# 1. 01_251104_Data_Cleaning.R → Preprocess raw data
		# 2. 02_251114_Index_Computation.R → Compute HAI and generate outputs
		# 3. 03_251118_Robustness_Test.R → Sensitivity analysis
		#
		# SETUP - Set your working directory:
		# 1. Copy the file path where you saved this project folder
		# 2. Replace the path below with your path
		# 3. Uncomment the setwd() line by removing the #
		#
		# setwd("YOUR_PATH_HERE/mlw_project_tw_sr")

		#******************************************************************************

		#******************************************************************************
		# Robustness Tests - Reduced Index Specification
		#******************************************************************************

		rm(list = ls())

		library(tidyverse)
		library(ggplot2)

		#setwd("~/Main/Uni/Master/S3/git/mlw_project_tw_sr")
		dir.create("05_output/robustness", showWarnings = FALSE, recursive = TRUE)

		pca_data <- read_csv("03_data/processed/affordability_data_returns_q.csv")

		#******************************************************************************
		# Baseline Specification
		#******************************************************************************

		baseline_vars <- c(
		"r_index_house_price_d",
		"r_interest_new_avg_d",
		"r_actual_rent_d",
		"r_maintenance_repair_aprtm_d",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d"
		)

		baseline_W <- 20
		baseline_lambda <- 0.97

		#******************************************************************************
		# Helper Functions
		#******************************************************************************

		compute_ewma_cov <- function(R_window, lambda){
		p <- ncol(R_window)
		S <- matrix(0, p, p)
		for(i in seq_len(nrow(R_window))){
		rvec <- matrix(R_window[i, ], ncol = 1)
		S <- lambda * S + (1 - lambda) * (rvec %*% t(rvec))
		}
		return(S)
		}

		run_pca_analysis <- function(pca_data, vars, W, lambda) {

		N_obs <- nrow(pca_data)
		pc1_variance <- rep(NA_real_, N_obs)
		r_HCI <- rep(NA_real_, N_obs)

		for(t in seq(W, N_obs)){
		window_idx <- (t - W + 1):t
		R_win <- as.matrix(pca_data[window_idx, vars])

		S_t <- compute_ewma_cov(R_win, lambda = lambda)

		diagS <- diag(S_t)
		if(any(diagS <= 0 \| is.na(diagS))) next

		D_inv_sqrt <- diag(1 / sqrt(diagS))
		Omega_t <- D_inv_sqrt %% S_t %% D_inv_sqrt

		eig <- eigen(Omega_t, symmetric = TRUE)
		v1 <- eig$vectors[, 1]

		interest_idx <- which(grepl("interest", vars))[1]
		if(length(interest_idx) > 0 && !is.na(interest_idx) && v1[interest_idx] < 0) {
		v1 <- -v1
		}

		pc1_variance[t] <- eig$values[1] / sum(eig$values) * 100
		r_t <- as.numeric(pca_data[t, vars])
		r_HCI[t] <- sum(v1 * r_t)
		}

		results <- tibble(
		date = pca_data$date,
		r_HCI = r_HCI,
		pc1_variance = pc1_variance
		) %>%
		filter(!is.na(r_HCI)) %>%
		mutate(HCI = 100 + cumsum(r_HCI))

		list(
		results = results,
		mean_pc1_var = mean(results$pc1_variance, na.rm = TRUE),
		final_HCI = tail(results$HCI, 1),
		HCI_vector = results$HCI
		)
		}

		#******************************************************************************
		# TEST 1: Lambda Sensitivity
		#******************************************************************************

		cat("\nTEST 1: Lambda Sensitivity\n")
		cat(strrep("-", 80), "\n")

		lambda_values <- c(0.90, 0.95, 0.97, 0.99)
		lambda_results <- list()

		for(lambda in lambda_values) {
		lambda_results[[as.character(lambda)]] <- run_pca_analysis(pca_data, baseline_vars, baseline_W, lambda)
		}

		lambda_metrics <- data.frame(
		lambda = lambda_values,
		mean_pc1_var = sapply(lambda_values, function(l) lambda_results[[as.character(l)]]$mean_pc1_var),
		final_HCI = sapply(lambda_values, function(l) lambda_results[[as.character(l)]]$final_HCI),
		correlation = NA_real_
		)

		baseline_hci <- lambda_results[["0.97"]]$HCI_vector
		for(i in 1:nrow(lambda_metrics)) {
		lambda <- lambda_metrics$lambda[i]
		test_hci <- lambda_results[[as.character(lambda)]]$HCI_vector
		lambda_metrics$correlation[i] <- cor(baseline_hci, test_hci)
		}

		print(lambda_metrics)
		min_cor_lambda <- min(lambda_metrics$correlation[lambda_metrics$lambda != baseline_lambda])
		cat(sprintf("Min correlation (excl. baseline): %.4f\n\n", min_cor_lambda))

		#******************************************************************************
		# TEST 2: Window Size Sensitivity
		#******************************************************************************

		cat("TEST 2: Window Size Sensitivity\n")
		cat(strrep("-", 80), "\n")

		W_values <- c(16, 20, 24)
		W_results <- list()

		for(W in W_values) {
		W_results[[as.character(W)]] <- run_pca_analysis(pca_data, baseline_vars, W, baseline_lambda)
		}

		W_metrics <- data.frame(
		W = W_values,
		mean_pc1_var = sapply(W_values, function(w) W_results[[as.character(w)]]$mean_pc1_var),
		final_HCI = sapply(W_values, function(w) W_results[[as.character(w)]]$final_HCI),
		correlation = NA_real_
		)

		# Get HCI vectors
		hci_16 <- W_results[["16"]]$HCI_vector
		hci_20 <- W_results[["20"]]$HCI_vector
		hci_24 <- W_results[["24"]]$HCI_vector

		# Find minimum length and truncate
		min_len <- min(length(hci_16), length(hci_20), length(hci_24))
		hci_16_trunc <- tail(hci_16, min_len)
		hci_20_trunc <- tail(hci_20, min_len)
		hci_24_trunc <- tail(hci_24, min_len)

		# Calculate correlations
		W_metrics$correlation[1] <- cor(hci_16_trunc, hci_20_trunc)
		W_metrics$correlation[2] <- 1.0
		W_metrics$correlation[3] <- cor(hci_24_trunc, hci_20_trunc)

		print(W_metrics)
		min_cor_W <- min(W_metrics$correlation[W_metrics$W != baseline_W])
		cat(sprintf("Min correlation (excl. baseline): %.4f\n\n", min_cor_W))

		#******************************************************************************
		# TEST 3: Variable Selection
		#******************************************************************************

		cat("TEST 3: Variable Selection\n")
		cat(strrep("-", 80), "\n")

		var_specs <- list(
		baseline = baseline_vars,

		no_maintenance = c(
		"r_index_house_price_d",
		"r_interest_new_avg_d",
		"r_actual_rent_d",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d"
		),

		existing_interest = c(
		"r_index_house_price_d",
		"r_interest_existing_5_d",
		"r_actual_rent_d",
		"r_maintenance_repair_aprtm_d",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d"
		),

		construction_cost = c(
		"r_index_house_price_d",
		"r_interest_new_avg_d",
		"r_actual_rent_d",
		"r_construction_price_index_bw",
		"r_disp_income_bw",
		"r_volume_new_overall_d",
		"r_volume_existing_overall_d",
		"r_houseprice_income_ratio_d"
		)
		)

		var_results <- list()

		for(spec_name in names(var_specs)) {
		vars <- var_specs[[spec_name]]
		missing <- setdiff(vars, names(pca_data))

		if(length(missing) == 0) {
		var_results[[spec_name]] <- run_pca_analysis(pca_data, vars, baseline_W, baseline_lambda)
		}
		}

		var_metrics <- data.frame(
		specification = names(var_results),
		n_vars = sapply(names(var_results), function(x) length(var_specs[[x]])),
		mean_pc1_var = sapply(var_results, function(x) x$mean_pc1_var),
		final_HCI = sapply(var_results, function(x) x$final_HCI),
		correlation = NA_real_
		)

		baseline_hci_var <- var_results[["baseline"]]$HCI_vector
		for(i in 1:nrow(var_metrics)) {
		spec <- var_metrics$specification[i]
		test_hci <- var_results[[spec]]$HCI_vector
		var_metrics$correlation[i] <- cor(baseline_hci_var, test_hci)
		}

		print(var_metrics)
		min_cor_var <- min(var_metrics$correlation[var_metrics$specification != "baseline"])
		cat(sprintf("Min correlation (excl. baseline): %.4f\n\n", min_cor_var))

		#******************************************************************************
		# Summary
		#******************************************************************************

		cat(strrep("=", 80), "\n")
		cat("ROBUSTNESS SUMMARY\n")
		cat(strrep("=", 80), "\n\n")

		cat(sprintf("Lambda sensitivity: r = %.3f\n", min_cor_lambda))
		cat(sprintf("Window size sensitivity: r = %.3f\n", min_cor_W))
		cat(sprintf("Variable selection: r = %.3f\n\n", min_cor_var))

		#******************************************************************************
		# Save Results
		#******************************************************************************

		write_csv(lambda_metrics, "05_output/robustness/lambda_sensitivity.csv")
		write_csv(W_metrics, "05_output/robustness/window_sensitivity.csv")
		write_csv(var_metrics, "05_output/robustness/variable_sensitivity.csv")

		# Comparison plot
		if(!is.null(lambda_results[["0.90"]]) && !is.null(lambda_results[["0.97"]]) && !is.null(lambda_results[["0.99"]])) {
		comparison_data <- bind_rows(
		lambda_results[["0.90"]]$results %>% mutate(spec = "lambda=0.90"),
		lambda_results[["0.97"]]$results %>% mutate(spec = "lambda=0.97"),
		lambda_results[["0.99"]]$results %>% mutate(spec = "lambda=0.99")
		)

		p1 <- ggplot(comparison_data, aes(x = date, y = HCI, color = spec)) +
		geom_line(linewidth = 1) +
		labs(title = "Lambda Sensitivity",
		x = NULL, y = "Housing Cost Index", color = NULL) +
		theme_minimal() +
		theme(legend.position = "bottom")

		ggsave("05_output/robustness/lambda_comparison.pdf", p1, width = 12, height = 6)
		}

		cat("Robustness tests complete\n")
		No newline at end of file

00_original_index/02_code/05_output/.DS_Store

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Original line number	Diff line number	Diff line
		Version: 1.0

		RestoreWorkspace: Default
		SaveWorkspace: Default
		AlwaysSaveHistory: Default

		EnableCodeIndexing: Yes
		UseSpacesForTab: Yes
		NumSpacesForTab: 2
		Encoding: UTF-8

		RnwWeave: Sweave
		LaTeX: pdfLaTeX

00_original_index/03_data/.DS_Store

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00_original_index/03_data/data_destatis/.DS_Store

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00_original_index/03_data/data_destatis/12211-1003_Mikrozensus_D_y.csv

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Original line number	Diff line number	Diff line
		Tabelle: 12211-1003
		Bevölkerung, Erwerbstätige, Erwerbslose, Erwerbspersonen,;;;;;;;;
		Nichterwerbspersonen aus Hauptwohnsitzhaush.: Bundesländer,;;;;;;;;
		Jahre, Geschlecht, Größenkl. persönl. monatl. Nettoeinkommen;;;;;;;;
		Mikrozensus;;;;;;;;;;;;;
		;;;;Bevölkerung in Hauptwohnsitzhaushalten;;Erwerbstätige aus Hauptwohnsitzhaushalten;;Erwerbslose aus Hauptwohnsitzhaushalten;;Erwerbspersonen aus Hauptwohnsitzhaushalten;;Nichterwerbspersonen aus Hauptwohnsitzhaushalten;
		;;;;1000;1000;1000;1000;1000;1000;1000;1000;1000;1000
		2021;Baden-Württemberg;männlich;Kein Einkommen;870;e;9;();17;e;26;e;844;e
		;;weiblich;Kein Einkommen;1044;e;17;e;18;e;35;e;1009;e
		;;Insgesamt;Kein Einkommen;1914;e;26;e;35;e;61;e;1853;e
		;Bayern;männlich;Kein Einkommen;949;e;13;e;13;e;26;e;923;e
		;;weiblich;Kein Einkommen;1116;e;24;e;15;e;39;e;1077;e
		;;Insgesamt;Kein Einkommen;2065;e;38;e;28;e;65;e;2000;e
		;Berlin;männlich;Kein Einkommen;255;e;/;;/;;/;;247;e
		;;weiblich;Kein Einkommen;278;e;/;;/;;/;;271;e
		;;Insgesamt;Kein Einkommen;533;e;/;;11;();16;e;517;e
		;Brandenburg;männlich;Kein Einkommen;185;e;/;;/;;/;;182;e
		;;weiblich;Kein Einkommen;187;e;/;;/;;/;;183;e
		;;Insgesamt;Kein Einkommen;372;e;/;;/;;/;;365;e
		;Bremen;männlich;Kein Einkommen;44;e;/;;/;;/;;42;e
		;;weiblich;Kein Einkommen;55;e;/;;/;;/;;54;e
		;;Insgesamt;Kein Einkommen;99;e;/;;/;;/;;96;e
		;Hamburg;männlich;Kein Einkommen;138;e;/;;/;;/;;134;e
		;;weiblich;Kein Einkommen;157;e;/;;/;;/;;152;e
		;;Insgesamt;Kein Einkommen;294;e;/;;/;;8;();286;e
		;Hessen;männlich;Kein Einkommen;449;e;6;();7;();13;e;436;e
		;;weiblich;Kein Einkommen;565;e;10;e;10;e;20;e;545;e
		;;Insgesamt;Kein Einkommen;1015;e;16;e;17;e;33;e;981;e
		;Mecklenburg-Vorpommern;männlich;Kein Einkommen;119;e;/;;/;;/;;117;e
		;;weiblich;Kein Einkommen;120;e;/;;/;;/;;118;e
		;;Insgesamt;Kein Einkommen;239;e;/;;/;;/;;235;e
		;Niedersachsen;männlich;Kein Einkommen;555;e;7;();8;();15;e;541;e
		;;weiblich;Kein Einkommen;650;e;11;e;9;();20;e;630;e
		;;Insgesamt;Kein Einkommen;1205;e;18;e;17;e;35;e;1170;e
		;Nordrhein-Westfalen;männlich;Kein Einkommen;1178;e;12;();19;e;31;e;1147;e
		;;weiblich;Kein Einkommen;1476;e;22;e;21;e;42;e;1433;e
		;;Insgesamt;Kein Einkommen;2654;e;33;e;40;e;73;e;2581;e
		;Rheinland-Pfalz;männlich;Kein Einkommen;303;e;/;;/;;8;();295;e
		;;weiblich;Kein Einkommen;375;e;7;();7;();14;e;362;e
		;;Insgesamt;Kein Einkommen;678;e;10;e;12;e;22;e;656;e
		;Saarland;männlich;Kein Einkommen;74;e;/;;/;;/;;71;e
		;;weiblich;Kein Einkommen;98;e;/;;/;;/;;95;e
		;;Insgesamt;Kein Einkommen;172;e;/;;/;;6;();166;e
		;Sachsen;männlich;Kein Einkommen;308;e;/;;/;;/;;303;e
		;;weiblich;Kein Einkommen;314;e;/;;/;;6;();308;e
		;;Insgesamt;Kein Einkommen;622;e;/;;6;();11;e;611;e
		;Sachsen-Anhalt;männlich;Kein Einkommen;138;e;/;;/;;/;;134;e
		;;weiblich;Kein Einkommen;143;e;/;;/;;/;;139;e
		;;Insgesamt;Kein Einkommen;281;e;/;;/;;9;();273;e
		;Schleswig-Holstein;männlich;Kein Einkommen;195;e;/;;/;;/;;191;e
		;;weiblich;Kein Einkommen;233;e;/;;/;;8;();225;e
		;;Insgesamt;Kein Einkommen;429;e;/;;/;;13;();416;e
		;Thüringen;männlich;Kein Einkommen;158;e;/;;/;;/;;156;e
		;;weiblich;Kein Einkommen;157;e;/;;/;;/;;154;e
		;;Insgesamt;Kein Einkommen;315;e;/;;/;;6;();309;e
		2022;Baden-Württemberg;männlich;Kein Einkommen;861;e;9;();13;e;22;e;838;e
		;;weiblich;Kein Einkommen;999;e;14;e;17;e;31;e;968;e
		;;Insgesamt;Kein Einkommen;1860;e;23;e;30;e;53;e;1807;e
		;Bayern;männlich;Kein Einkommen;935;e;11;();11;e;22;e;913;e
		;;weiblich;Kein Einkommen;1096;e;20;e;15;e;34;e;1061;e
		;;Insgesamt;Kein Einkommen;2031;e;30;e;26;e;57;e;1974;e
		;Berlin;männlich;Kein Einkommen;256;e;/;;/;;/;;248;e
		;;weiblich;Kein Einkommen;280;e;/;;/;;/;;273;e
		;;Insgesamt;Kein Einkommen;536;e;/;;/;;14;();522;e
		;Brandenburg;männlich;Kein Einkommen;173;e;/;;/;;/;;169;e
		;;weiblich;Kein Einkommen;176;e;/;;/;;/;;171;e
		;;Insgesamt;Kein Einkommen;349;e;/;;/;;/;;340;e
		;Bremen;männlich;Kein Einkommen;48;e;/;;/;;/;;46;e
		;;weiblich;Kein Einkommen;58;e;/;;/;;/;;56;e
		;;Insgesamt;Kein Einkommen;106;e;/;;/;;/;;102;e
		;Hamburg;männlich;Kein Einkommen;133;e;/;;/;;/;;128;e
		;;weiblich;Kein Einkommen;150;e;/;;/;;/;;146;e
		;;Insgesamt;Kein Einkommen;283;e;/;;/;;9;();274;e
		;Hessen;männlich;Kein Einkommen;447;e;6;();9;();15;e;432;e
		;;weiblich;Kein Einkommen;548;e;9;();9;();18;e;530;e
		;;Insgesamt;Kein Einkommen;995;e;15;e;18;e;33;e;962;e
		;Mecklenburg-Vorpommern;männlich;Kein Einkommen;114;e;/;;/;;/;;112;e
		;;weiblich;Kein Einkommen;118;e;/;;/;;/;;115;e
		;;Insgesamt;Kein Einkommen;232;e;/;;/;;/;;227;e
		;Niedersachsen;männlich;Kein Einkommen;538;e;/;;9;();14;e;524;e
		;;weiblich;Kein Einkommen;616;e;10;();8;();18;e;597;e
		;;Insgesamt;Kein Einkommen;1154;e;16;e;17;e;33;e;1122;e
		;Nordrhein-Westfalen;männlich;Kein Einkommen;1218;e;16;e;21;e;37;e;1181;e
		;;weiblich;Kein Einkommen;1485;e;26;e;21;e;47;e;1437;e
		;;Insgesamt;Kein Einkommen;2702;e;42;e;43;e;85;e;2618;e
		;Rheinland-Pfalz;männlich;Kein Einkommen;286;e;/;;7;();10;e;276;e
		;;weiblich;Kein Einkommen;358;e;/;;7;();12;e;346;e
		;;Insgesamt;Kein Einkommen;645;e;8;();13;e;22;e;623;e
		;Saarland;männlich;Kein Einkommen;71;e;/;;/;;/;;69;e
		;;weiblich;Kein Einkommen;94;e;/;;/;;/;;91;e
		;;Insgesamt;Kein Einkommen;165;e;/;;/;;/;;160;e
		;Sachsen;männlich;Kein Einkommen;314;e;/;;/;;/;;310;e
		;;weiblich;Kein Einkommen;324;e;/;;/;;7;();317;e
		;;Insgesamt;Kein Einkommen;638;e;/;;8;();11;e;627;e
		;Sachsen-Anhalt;männlich;Kein Einkommen;141;e;/;;/;;/;;137;e
		;;weiblich;Kein Einkommen;143;e;/;;/;;/;;140;e
		;;Insgesamt;Kein Einkommen;283;e;/;;/;;7;();277;e
		;Schleswig-Holstein;männlich;Kein Einkommen;201;e;/;;/;;/;;196;e
		;;weiblich;Kein Einkommen;238;e;/;;/;;8;();230;e
		;;Insgesamt;Kein Einkommen;439;e;7;();/;;13;e;426;e
		;Thüringen;männlich;Kein Einkommen;159;e;/;;/;;/;;156;e
		;;weiblich;Kein Einkommen;160;e;/;;/;;/;;156;e
		;;Insgesamt;Kein Einkommen;318;e;/;;/;;/;;312;e
		2023;Baden-Württemberg;männlich;Kein Einkommen;1005;e;11;e;18;e;29;e;976;e
		;;weiblich;Kein Einkommen;1170;e;15;e;21;e;36;e;1135;e
		;;Insgesamt;Kein Einkommen;2176;e;26;e;39;e;65;e;2111;e
		;Bayern;männlich;Kein Einkommen;1143;e;19;e;15;e;33;e;1110;e
		;;weiblich;Kein Einkommen;1312;e;24;e;18;e;41;e;1270;e
		;;Insgesamt;Kein Einkommen;2455;e;42;e;32;e;74;e;2380;e
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		;;weiblich;Kein Einkommen;337;e;/;;8;();13;e;324;e
		;;Insgesamt;Kein Einkommen;643;e;10;();14;e;24;e;619;e
		;Brandenburg;männlich;Kein Einkommen;210;e;/;;/;;/;;204;e
		;;weiblich;Kein Einkommen;215;e;/;;/;;/;;209;e
		;;Insgesamt;Kein Einkommen;424;e;/;;/;;12;();413;e
		;Bremen;männlich;Kein Einkommen;54;e;/;;/;;/;;51;e
		;;weiblich;Kein Einkommen;65;e;/;;/;;/;;62;e
		;;Insgesamt;Kein Einkommen;118;e;/;;/;;5;();113;e
		;Hamburg;männlich;Kein Einkommen;153;e;/;;/;;/;;148;e
		;;weiblich;Kein Einkommen;174;e;/;;/;;7;();167;e
		;;Insgesamt;Kein Einkommen;327;e;/;;/;;12;e;315;e
		;Hessen;männlich;Kein Einkommen;534;e;8;();11;e;19;e;515;e
		;;weiblich;Kein Einkommen;635;e;11;e;11;e;22;e;613;e
		;;Insgesamt;Kein Einkommen;1169;e;19;e;21;e;41;e;1129;e
		;Mecklenburg-Vorpommern;männlich;Kein Einkommen;122;e;/;;/;;/;;120;e
		;;weiblich;Kein Einkommen;129;e;/;;/;;/;;126;e
		;;Insgesamt;Kein Einkommen;250;e;/;;/;;/;;246;e
		;Niedersachsen;männlich;Kein Einkommen;656;e;6;();11;e;18;e;638;e
		;;weiblich;Kein Einkommen;758;e;11;e;9;();20;e;738;e
		;;Insgesamt;Kein Einkommen;1414;e;17;e;20;e;38;e;1376;e
		;Nordrhein-Westfalen;männlich;Kein Einkommen;1464;e;23;e;24;e;47;e;1417;e
		;;weiblich;Kein Einkommen;1796;e;33;e;29;e;62;e;1734;e
		;;Insgesamt;Kein Einkommen;3260;e;56;e;52;e;109;e;3151;e
		;Rheinland-Pfalz;männlich;Kein Einkommen;353;e;/;;8;();12;e;340;e
		;;weiblich;Kein Einkommen;409;e;7;();6;();13;e;396;e
		;;Insgesamt;Kein Einkommen;762;e;12;e;14;e;25;e;737;e
		;Saarland;männlich;Kein Einkommen;76;e;/;;/;;/;;73;e
		;;weiblich;Kein Einkommen;101;e;/;;/;;/;;98;e
		;;Insgesamt;Kein Einkommen;177;e;/;;/;;5;();172;e
		;Sachsen;männlich;Kein Einkommen;305;e;/;;/;;/;;302;e
		;;weiblich;Kein Einkommen;322;e;/;;/;;/;;317;e
		;;Insgesamt;Kein Einkommen;627;e;/;;6;();9;();618;e
		;Sachsen-Anhalt;männlich;Kein Einkommen;142;e;/;;/;;/;;137;e
		;;weiblich;Kein Einkommen;140;e;/;;/;;/;;135;e
		;;Insgesamt;Kein Einkommen;282;e;6;();/;;10;();272;e
		;Schleswig-Holstein;männlich;Kein Einkommen;233;e;/;;/;;/;;227;e
		;;weiblich;Kein Einkommen;270;e;7;();/;;12;e;258;e
		;;Insgesamt;Kein Einkommen;503;e;11;();8;();19;e;484;e
		;Thüringen;männlich;Kein Einkommen;158;e;/;;/;;/;;154;e
		;;weiblich;Kein Einkommen;166;e;/;;/;;/;;163;e
		;;Insgesamt;Kein Einkommen;324;e;/;;/;;7;();317;e
		2024;Baden-Württemberg;männlich;Kein Einkommen;990;p;11;p;22;p;33;p;957;p
		;;weiblich;Kein Einkommen;1135;p;17;p;21;p;38;p;1097;p
		;;Insgesamt;Kein Einkommen;2125;p;28;p;44;p;71;p;2054;p
		;Bayern;männlich;Kein Einkommen;1151;p;18;p;19;p;37;p;1114;p
		;;weiblich;Kein Einkommen;1312;p;22;p;21;p;43;p;1269;p
		;;Insgesamt;Kein Einkommen;2463;p;41;p;39;p;80;p;2383;p
		;Berlin;männlich;Kein Einkommen;320;p;/;;8;();13;p;307;p
		;;weiblich;Kein Einkommen;350;p;/;;8;();12;();338;p
		;;Insgesamt;Kein Einkommen;670;p;9;();16;p;25;p;645;p
		;Brandenburg;männlich;Kein Einkommen;201;p;/;;/;;/;;194;p
		;;weiblich;Kein Einkommen;212;p;/;;/;;/;;207;p
		;;Insgesamt;Kein Einkommen;413;p;/;;/;;12;();401;p
		;Bremen;männlich;Kein Einkommen;50;p;/;;/;;/;;49;p
		;;weiblich;Kein Einkommen;66;p;/;;/;;/;;63;p
		;;Insgesamt;Kein Einkommen;116;p;/;;/;;/;;112;p
		;Hamburg;männlich;Kein Einkommen;159;p;/;;/;;/;;153;p
		;;weiblich;Kein Einkommen;174;p;/;;/;;/;;168;p
		;;Insgesamt;Kein Einkommen;332;p;/;;8;();12;p;321;p
		;Hessen;männlich;Kein Einkommen;548;p;9;();10;();19;p;529;p
		;;weiblich;Kein Einkommen;646;p;10;();11;p;21;p;625;p
		;;Insgesamt;Kein Einkommen;1194;p;19;p;21;p;40;p;1154;p
		;Mecklenburg-Vorpommern;männlich;Kein Einkommen;124;p;/;;/;;/;;122;p
		;;weiblich;Kein Einkommen;125;p;/;;/;;/;;122;p
		;;Insgesamt;Kein Einkommen;249;p;/;;/;;/;;244;p
		;Niedersachsen;männlich;Kein Einkommen;665;p;10;();10;();21;p;644;p
		;;weiblich;Kein Einkommen;761;p;13;p;14;p;27;p;734;p
		;;Insgesamt;Kein Einkommen;1426;p;23;p;24;p;48;p;1378;p
		;Nordrhein-Westfalen;männlich;Kein Einkommen;1511;p;28;p;29;p;58;p;1453;p
		;;weiblich;Kein Einkommen;1814;p;32;p;34;p;66;p;1748;p
		;;Insgesamt;Kein Einkommen;3325;p;61;p;63;p;124;p;3201;p
		;Rheinland-Pfalz;männlich;Kein Einkommen;353;p;/;;8;();13;p;339;p
		;;weiblich;Kein Einkommen;419;p;10;();7;();17;p;402;p
		;;Insgesamt;Kein Einkommen;772;p;15;p;15;p;30;p;742;p
		;Saarland;männlich;Kein Einkommen;62;p;/;;/;;/;;61;p
		;;weiblich;Kein Einkommen;85;p;/;;/;;/;;81;p
		;;Insgesamt;Kein Einkommen;147;p;/;;/;;/;;142;p
		;Sachsen;männlich;Kein Einkommen;315;p;/;;/;;/;;310;p
		;;weiblich;Kein Einkommen;314;p;/;;/;;7;();307;p
		;;Insgesamt;Kein Einkommen;629;p;/;;8;();11;p;617;p
		;Sachsen-Anhalt;männlich;Kein Einkommen;138;p;/;;/;;/;;132;p
		;;weiblich;Kein Einkommen;141;p;/;;/;;7;();134;p
		;;Insgesamt;Kein Einkommen;279;p;7;();/;;13;p;266;p
		;Schleswig-Holstein;männlich;Kein Einkommen;238;p;/;;/;;9;();229;p
		;;weiblich;Kein Einkommen;272;p;/;;/;;11;();261;p
		;;Insgesamt;Kein Einkommen;510;p;11;p;9;();20;p;490;p
		;Thüringen;männlich;Kein Einkommen;159;p;/;;/;;/;;156;p
		;;weiblich;Kein Einkommen;161;p;/;;/;;/;;157;p
		;;Insgesamt;Kein Einkommen;320;p;/;;/;;7;();313;p
		__________
		© Statistisches Bundesamt (Destatis), 2025
		Stand: 04.11.2025 / 13:53:47

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00_original_index/03_data/data_destatis/61111-0004_Verbraucherpreisindex_D_m.csv

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Original line number	Diff line number	Diff line
		Tabelle: 61111-0004
		Verbraucherpreisindex: Deutschland, Monate,;;;;;;;;;;;;;;;;;;;;;;;;;
		Klassifikation der Verwendungszwecke des Individualkonsums;;;;;;;;;;;;;;;;;;;;;;;;;
		(COICOP 2-5-Steller Hierarchie);;;;;;;;;;;;;;;;;;;;;;;;;
		Verbraucherpreisindex für Deutschland;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		Deutschland;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		Verbraucherpreisindex (2020=100);;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		;;2024;;;;;;;;;;;;;;;;;;;;;;;;2025;;;;;;;;;;;;;;;;;;;;;;;
		;;Januar;;Februar;;März;;April;;Mai;;Juni;;Juli;;August;;September;;Oktober;;November;;Dezember;;Januar;;Februar;;März;;April;;Mai;;Juni;;Juli;;August;;September;;Oktober;;November;;Dezember;
		CC13-04;Wohnung, Wasser, Strom, Gas und andere Brennstoffe;115,2;e;115,3;e;115,3;e;115,9;e;115,9;e;116,0;e;116,2;e;116,1;e;116,2;e;116,3;e;116,3;e;116,4;e;116,7;e;116,9;e;117,0;e;117,2;e;117,3;e;117,4;e;117,6;e;117,7;e;117,8;e;...;;...;;...;
		CC13-041; Tatsächliche Wohnungsmiete;106,4;e;106,7;e;106,8;e;107,1;e;107,3;e;107,4;e;107,6;e;107,7;e;107,9;e;108,1;e;108,2;e;108,4;e;108,6;e;108,8;e;109,0;e;109,3;e;109,5;e;109,7;e;109,9;e;110,0;e;110,2;e;...;;...;;...;
		CC13-0411; Tatsächliche Nettokaltmiete;106,7;e;106,9;e;107,1;e;107,4;e;107,5;e;107,7;e;107,8;e;108,0;e;108,2;e;108,4;e;108,5;e;108,6;e;108,9;e;109,1;e;109,3;e;109,6;e;109,8;e;110,0;e;110,2;e;110,4;e;110,5;e;...;;...;;...;
		CC13-04110; Tatsächliche Nettokaltmiete;106,7;e;106,9;e;107,1;e;107,4;e;107,5;e;107,7;e;107,8;e;108,0;e;108,2;e;108,4;e;108,5;e;108,6;e;108,9;e;109,1;e;109,3;e;109,6;e;109,8;e;110,0;e;110,2;e;110,4;e;110,5;e;...;;...;;...;
		CC13-0412; Andere Mieten;104,1;e;104,3;e;104,4;e;104,7;e;104,9;e;105,0;e;105,1;e;105,2;e;105,3;e;105,4;e;105,5;e;105,7;e;106,0;e;106,1;e;106,2;e;106,3;e;106,7;e;106,8;e;106,9;e;107,0;e;107,2;e;...;;...;;...;
		CC13-04122; Garagen- und andere Mieten;104,1;e;104,3;e;104,4;e;104,7;e;104,9;e;105,0;e;105,1;e;105,2;e;105,3;e;105,4;e;105,5;e;105,7;e;106,0;e;106,1;e;106,2;e;106,3;e;106,7;e;106,8;e;106,9;e;107,0;e;107,2;e;...;;...;;...;
		CC13-042; Unterstellte Nettokaltmiete;105,8;e;106,0;e;106,3;e;106,6;e;106,7;e;106,9;e;107,1;e;107,2;e;107,3;e;107,4;e;107,5;e;107,5;e;107,9;e;108,1;e;108,4;e;108,8;e;108,9;e;108,9;e;109,2;e;109,2;e;109,3;e;...;;...;;...;
		CC13-0421; Unterstellte Nettokaltmiete;105,8;e;106,0;e;106,3;e;106,6;e;106,7;e;106,9;e;107,1;e;107,2;e;107,3;e;107,4;e;107,5;e;107,5;e;107,9;e;108,1;e;108,4;e;108,8;e;108,9;e;108,9;e;109,2;e;109,2;e;109,3;e;...;;...;;...;
		CC13-04210; Unterstellte Nettokaltmiete;105,8;e;106,0;e;106,3;e;106,6;e;106,7;e;106,9;e;107,1;e;107,2;e;107,3;e;107,4;e;107,5;e;107,5;e;107,9;e;108,1;e;108,4;e;108,8;e;108,9;e;108,9;e;109,2;e;109,2;e;109,3;e;...;;...;;...;
		CC13-05;Möbel, Leuchten, Geräte u.a. Haushaltszubehör;118,5;e;118,4;e;118,4;e;118,6;e;118,2;e;118,1;e;117,9;e;117,5;e;117,1;e;117,3;e;117,7;e;118,2;e;117,6;e;117,6;e;118,1;e;118,2;e;117,9;e;118,2;e;118,3;e;118,1;e;118,1;e;...;;...;;...;
		CC13-055; Werkzeuge und Geräte für Haus und Garten;110,9;e;111,3;e;111,2;e;111,5;e;111,5;e;111,6;e;110,9;e;110,6;e;110,5;e;110,8;e;110,7;e;111,2;e;110,9;e;110,6;e;111,2;e;111,3;e;111,0;e;110,5;e;110,3;e;110,6;e;109,9;e;...;;...;;...;
		CC13-0551; Motorbetr. Großwerkzeuge u.Ä. für Haus und Garten;107,7;e;107,9;e;107,0;e;107,3;e;107,4;e;107,5;e;106,8;e;106,7;e;107,0;e;106,8;e;106,5;e;107,2;e;107,1;e;106,9;e;107,3;e;107,2;e;107,1;e;106,1;e;105,6;e;106,0;e;106,0;e;...;;...;;...;
		CC13-05512; Miete von motorbetriebenem Großwerkzeug o. -gerät;108,3;e;109,3;e;110,1;e;111,1;e;111,3;e;111,5;e;111,7;e;111,8;e;111,9;e;112,1;e;112,3;e;112,3;e;112,4;e;113,2;e;113,6;e;114,3;e;114,6;e;114,9;e;115,0;e;115,0;e;115,2;e;...;;...;;...;
		CC13-07;Verkehr;122,6;e;123,7;e;125,1;e;125,7;e;125,7;e;124,9;e;126,3;e;125,1;e;123,7;e;124,9;e;123,8;e;125,6;e;126,2;e;126,7;e;126,2;e;127,5;e;126,5;e;126,9;e;127,6;e;126,9;e;126,7;e;...;;...;;...;
		CC13-072; Waren und Dienstleistungen für Fahrzeuge;129,4;e;130,9;e;131,5;e;133,8;e;132,7;e;131,1;e;131,6;e;130,0;e;127,7;e;128,8;e;128,9;e;129,2;e;131,9;e;133,0;e;131,3;e;131,0;e;130,8;e;130,7;e;131,1;e;130,8;e;130,7;e;...;;...;;...;
		CC13-0724; Andere Dienstleistungen für Fahrzeuge;114,1;e;115,2;e;115,4;e;115,6;e;116,1;e;116,1;e;116,6;e;117,1;e;116,9;e;117,0;e;116,9;e;117,2;e;117,5;e;118,3;e;118,6;e;118,7;e;118,8;e;118,9;e;119,0;e;119,1;e;119,4;e;...;;...;;...;
		CC13-07241; Miete von Fahrzeugen, Garagen/Stellplätzen;127,7;e;129,5;e;130,1;e;131,7;e;130,8;e;130,8;e;135,0;e;139,4;e;136,5;e;137,6;e;135,1;e;136,9;e;134,5;e;134,9;e;137,6;e;139,0;e;138,7;e;139,5;e;140,7;e;140,9;e;143,5;e;...;;...;;...;
		__________
		"Dezember 2024:
		Aufgrund des Umstiegs auf den Erhebungskatalog 2025 mit
		erheblichen klassifikationsbedingten Strukturveränderungen
		sind die Werte für Dezember 2024 vor allem im Hinblick auf
		den Vormonatsvergleich teilweise in der Qualität
		beeinflusst."
		© Statistisches Bundesamt (Destatis), 2025
		Stand: 04.11.2025 / 10:25:10

00_original_index/03_data/data_destatis/61111-0011_Verbraucherpreisindex_BW_m.csv

0 → 100644

+386 −0

Original line number	Diff line number	Diff line
		Tabelle: 61111-0011
		Verbraucherpreisindex: Bundesländer, Monate;;
		Verbraucherpreisindex für Deutschland;;;
		Verbraucherpreisindex (2020=100);;;
		;;Baden-Württemberg;
		1995;Januar;69,9;e
		;Februar;70,2;e
		;März;70,3;e
		;April;70,5;e
		;Mai;70,6;e
		;Juni;70,7;e
		;Juli;70,8;e
		;August;70,7;e
		;September;70,7;e
		;Oktober;70,6;e
		;November;70,6;e
		;Dezember;70,7;e
		1996;Januar;70,8;e
		;Februar;71,2;e
		;März;71,3;e
		;April;71,3;e
		;Mai;71,4;e
		;Juni;71,4;e
		;Juli;71,5;e
		;August;71,5;e
		;September;71,4;e
		;Oktober;71,4;e
		;November;71,4;e
		;Dezember;71,5;e
		1997;Januar;72,1;e
		;Februar;72,2;e
		;März;72,2;e
		;April;72,0;e
		;Mai;72,2;e
		;Juni;72,4;e
		;Juli;72,8;e
		;August;72,9;e
		;September;72,8;e
		;Oktober;72,8;e
		;November;72,8;e
		;Dezember;72,9;e
		1998;Januar;72,8;e
		;Februar;73,0;e
		;März;72,9;e
		;April;73,1;e
		;Mai;73,4;e
		;Juni;73,4;e
		;Juli;73,5;e
		;August;73,4;e
		;September;73,3;e
		;Oktober;73,2;e
		;November;73,1;e
		;Dezember;73,3;e
		1999;Januar;73,1;e
		;Februar;73,2;e
		;März;73,3;e
		;April;73,5;e
		;Mai;73,5;e
		;Juni;73,6;e
		;Juli;73,9;e
		;August;73,9;e
		;September;73,8;e
		;Oktober;73,7;e
		;November;73,8;e
		;Dezember;74,0;e
		2000;Januar;74,4;e
		;Februar;74,6;e
		;März;74,6;e
		;April;74,6;e
		;Mai;74,5;e
		;Juni;74,9;e
		;Juli;75,1;e
		;August;75,0;e
		;September;75,1;e
		;Oktober;75,0;e
		;November;75,1;e
		;Dezember;75,9;e
		2001;Januar;75,7;e
		;Februar;76,2;e
		;März;76,2;e
		;April;76,2;e
		;Mai;76,6;e
		;Juni;76,9;e
		;Juli;77,1;e
		;August;76,9;e
		;September;76,8;e
		;Oktober;76,7;e
		;November;76,5;e
		;Dezember;77,3;e
		2002;Januar;77,5;e
		;Februar;77,6;e
		;März;77,8;e
		;April;77,7;e
		;Mai;77,8;e
		;Juni;77,8;e
		;Juli;78,1;e
		;August;77,9;e
		;September;77,9;e
		;Oktober;77,8;e
		;November;77,6;e
		;Dezember;78,4;e
		2003;Januar;78,4;e
		;Februar;79,0;e
		;März;79,0;e
		;April;78,8;e
		;Mai;78,7;e
		;Juni;78,9;e
		;Juli;79,0;e
		;August;79,1;e
		;September;79,1;e
		;Oktober;79,1;e
		;November;79,0;e
		;Dezember;79,5;e
		2004;Januar;79,5;e
		;Februar;79,8;e
		;März;80,1;e
		;April;80,3;e
		;Mai;80,5;e
		;Juni;80,4;e
		;Juli;80,6;e
		;August;80,7;e
		;September;80,6;e
		;Oktober;80,6;e
		;November;80,5;e
		;Dezember;81,2;e
		2005;Januar;80,4;e
		;Februar;80,8;e
		;März;81,2;e
		;April;80,9;e
		;Mai;81,2;e
		;Juni;81,3;e
		;Juli;81,6;e
		;August;81,7;e
		;September;81,8;e
		;Oktober;81,9;e
		;November;81,6;e
		;Dezember;82,3;e
		2006;Januar;81,9;e
		;Februar;82,3;e
		;März;82,4;e
		;April;82,7;e
		;Mai;82,7;e
		;Juni;82,9;e
		;Juli;83,2;e
		;August;83,1;e
		;September;82,7;e
		;Oktober;82,8;e
		;November;82,9;e
		;Dezember;83,5;e
		2007;Januar;83,4;e
		;Februar;83,8;e
		;März;84,0;e
		;April;84,4;e
		;Mai;84,4;e
		;Juni;84,4;e
		;Juli;84,9;e
		;August;84,7;e
		;September;84,8;e
		;Oktober;85,0;e
		;November;85,4;e
		;Dezember;85,9;e
		2008;Januar;85,6;e
		;Februar;86,0;e
		;März;86,5;e
		;April;86,3;e
		;Mai;86,8;e
		;Juni;87,1;e
		;Juli;87,6;e
		;August;87,3;e
		;September;87,3;e
		;Oktober;87,2;e
		;November;86,8;e
		;Dezember;87,1;e
		2009;Januar;86,5;e
		;Februar;87,1;e
		;März;86,8;e
		;April;86,9;e
		;Mai;86,7;e
		;Juni;87,1;e
		;Juli;87,1;e
		;August;87,4;e
		;September;87,1;e
		;Oktober;87,2;e
		;November;87,0;e
		;Dezember;87,7;e
		2010;Januar;87,1;e
		;Februar;87,3;e
		;März;88,0;e
		;April;87,9;e
		;Mai;87,9;e
		;Juni;87,9;e
		;Juli;88,0;e
		;August;88,1;e
		;September;88,1;e
		;Oktober;88,1;e
		;November;88,4;e
		;Dezember;88,9;e
		2011;Januar;88,6;e
		;Februar;89,1;e
		;März;89,7;e
		;April;89,7;e
		;Mai;89,7;e
		;Juni;89,8;e
		;Juli;90,0;e
		;August;90,0;e
		;September;90,1;e
		;Oktober;90,3;e
		;November;90,3;e
		;Dezember;90,5;e
		2012;Januar;90,4;e
		;Februar;91,1;e
		;März;91,6;e
		;April;91,3;e
		;Mai;91,2;e
		;Juni;91,1;e
		;Juli;91,4;e
		;August;91,6;e
		;September;91,8;e
		;Oktober;91,8;e
		;November;91,8;e
		;Dezember;92,1;e
		2013;Januar;91,6;e
		;Februar;92,2;e
		;März;92,6;e
		;April;92,1;e
		;Mai;92,5;e
		;Juni;92,6;e
		;Juli;93,0;e
		;August;92,9;e
		;September;93,0;e
		;Oktober;92,8;e
		;November;93,1;e
		;Dezember;93,3;e
		2014;Januar;92,8;e
		;Februar;93,3;e
		;März;93,5;e
		;April;93,4;e
		;Mai;93,3;e
		;Juni;93,5;e
		;Juli;93,7;e
		;August;93,7;e
		;September;93,7;e
		;Oktober;93,5;e
		;November;93,5;e
		;Dezember;93,4;e
		2015;Januar;92,6;e
		;Februar;93,2;e
		;März;93,7;e
		;April;94,2;e
		;Mai;94,4;e
		;Juni;94,4;e
		;Juli;94,6;e
		;August;94,5;e
		;September;94,4;e
		;Oktober;94,4;e
		;November;93,8;e
		;Dezember;93,8;e
		2016;Januar;93,1;e
		;Februar;93,4;e
		;März;94,0;e
		;April;94,2;e
		;Mai;94,6;e
		;Juni;94,7;e
		;Juli;95,0;e
		;August;94,9;e
		;September;95,0;e
		;Oktober;95,2;e
		;November;94,6;e
		;Dezember;95,2;e
		2017;Januar;94,5;e
		;Februar;95,1;e
		;März;95,4;e
		;April;95,8;e
		;Mai;95,8;e
		;Juni;96,1;e
		;Juli;96,6;e
		;August;96,6;e
		;September;96,7;e
		;Oktober;96,5;e
		;November;96,2;e
		;Dezember;96,7;e
		2018;Januar;96,1;e
		;Februar;96,4;e
		;März;96,9;e
		;April;97,2;e
		;Mai;97,9;e
		;Juni;98,1;e
		;Juli;98,5;e
		;August;98,5;e
		;September;98,9;e
		;Oktober;99,1;e
		;November;98,5;e
		;Dezember;98,4;e
		2019;Januar;97,5;e
		;Februar;98,1;e
		;März;98,3;e
		;April;99,2;e
		;Mai;99,5;e
		;Juni;99,8;e
		;Juli;100,2;e
		;August;100,0;e
		;September;100,1;e
		;Oktober;100,2;e
		;November;99,4;e
		;Dezember;99,9;e
		2020;Januar;99,7;e
		;Februar;99,8;e
		;März;100,1;e
		;April;100,2;e
		;Mai;100,3;e
		;Juni;100,3;e
		;Juli;99,8;e
		;August;99,8;e
		;September;99,9;e
		;Oktober;100,0;e
		;November;99,9;e
		;Dezember;100,1;e
		2021;Januar;101,1;e
		;Februar;101,6;e
		;März;102,1;e
		;April;102,4;e
		;Mai;102,6;e
		;Juni;102,9;e
		;Juli;103,3;e
		;August;103,3;e
		;September;103,6;e
		;Oktober;104,1;e
		;November;104,3;e
		;Dezember;104,6;e
		2022;Januar;104,9;e
		;Februar;105,5;e
		;März;107,3;e
		;April;108,4;e
		;Mai;109,2;e
		;Juni;109,3;e
		;Juli;109,5;e
		;August;109,6;e
		;September;111,8;e
		;Oktober;112,6;e
		;November;113,2;e
		;Dezember;112,9;e
		2023;Januar;113,8;e
		;Februar;114,7;e
		;März;115,7;e
		;April;116,3;e
		;Mai;116,4;e
		;Juni;116,8;e
		;Juli;117,0;e
		;August;117,3;e
		;September;117,5;e
		;Oktober;117,5;e
		;November;117,1;e
		;Dezember;117,2;e
		2024;Januar;117,4;e
		;Februar;117,8;e
		;März;118,4;e
		;April;118,7;e
		;Mai;118,9;e
		;Juni;119,0;e
		;Juli;119,4;e
		;August;119,1;e
		;September;119,2;e
		;Oktober;120,0;e
		;November;119,7;e
		;Dezember;120,3;e
		2025;Januar;120,1;e
		;Februar;120,7;e
		;März;121,0;e
		;April;121,6;e
		;Mai;121,5;e
		;Juni;121,7;e
		;Juli;122,2;e
		;August;122,1;e
		;September;122,4;e
		;Oktober;...;
		;November;...;
		;Dezember;...;
		__________
		"Dezember 2024:
		Aufgrund des Umstiegs auf den Erhebungskatalog 2025 mit
		erheblichen klassifikationsbedingten Strukturveränderungen
		sind die Werte für Dezember 2024 vor allem im Hinblick auf
		den Vormonatsvergleich teilweise in der Qualität
		beeinflusst."
		© Statistisches Bundesamt (Destatis), 2025
		Stand: 09.11.2025 / 19:40:02

00_original_index/03_data/data_destatis/61111-0021_Nettokaltmietenindex_BW_m.csv

0 → 100644

+260 −0

Original line number	Diff line number	Diff line
		Tabelle: 61111-0021
		Index der Nettokaltmieten: Bundesländer, Monate;;;;;;;;;;;;;;;;;
		Verbraucherpreisindex für Deutschland;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		Index der Nettokaltmieten (2020=100);;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		;;Baden-Württemberg;;Bayern;;Berlin;;Brandenburg;;Bremen;;Hamburg;;Hessen;;Mecklenburg-Vorpommern;;Niedersachsen;;Nordrhein-Westfalen;;Rheinland-Pfalz;;Saarland;;Sachsen;;Sachsen-Anhalt;;Schleswig-Holstein;;Thüringen;
		2005;Januar;79,0;e;78,0;e;79,2;e;89,5;e;73,7;e;-;;81,3;e;89,4;e;83,3;e;83,0;e;84,9;e;88,5;e;93,2;e;89,0;e;-;;86,3;e
		;Februar;79,1;e;78,2;e;79,2;e;89,5;e;73,8;e;-;;81,3;e;89,5;e;83,4;e;83,1;e;85,0;e;88,5;e;93,2;e;89,0;e;-;;86,3;e
		;März;79,2;e;78,4;e;79,2;e;89,6;e;73,9;e;-;;81,4;e;89,5;e;83,5;e;83,2;e;85,1;e;88,5;e;93,2;e;89,0;e;-;;86,3;e
		;April;79,2;e;78,5;e;79,4;e;89,6;e;73,9;e;-;;81,5;e;89,5;e;83,5;e;83,2;e;85,2;e;88,5;e;93,2;e;89,0;e;-;;86,2;e
		;Mai;79,3;e;78,5;e;79,3;e;89,6;e;74,3;e;-;;81,7;e;89,5;e;83,7;e;83,3;e;85,2;e;88,6;e;93,2;e;89,0;e;-;;86,2;e
		;Juni;79,5;e;78,6;e;79,5;e;89,6;e;74,3;e;-;;81,7;e;89,5;e;83,8;e;83,4;e;85,2;e;88,7;e;93,2;e;89,0;e;-;;86,2;e
		;Juli;79,6;e;78,6;e;79,5;e;89,6;e;74,4;e;-;;82,0;e;89,5;e;83,8;e;83,5;e;85,2;e;88,8;e;93,2;e;89,0;e;-;;86,2;e
		;August;79,6;e;78,6;e;79,7;e;89,7;e;74,5;e;-;;82,1;e;89,5;e;83,9;e;83,5;e;85,3;e;88,9;e;93,2;e;89,0;e;-;;86,2;e
		;September;79,7;e;78,7;e;79,7;e;89,7;e;74,6;e;-;;82,0;e;89,5;e;83,9;e;83,6;e;85,3;e;88,9;e;93,2;e;89,0;e;-;;86,2;e
		;Oktober;79,8;e;78,8;e;79,8;e;89,7;e;74,6;e;-;;82,1;e;89,6;e;83,9;e;83,7;e;85,3;e;88,9;e;93,2;e;89,1;e;-;;86,2;e
		;November;79,8;e;78,9;e;80,0;e;89,7;e;74,8;e;-;;82,1;e;89,6;e;83,8;e;83,8;e;85,3;e;88,9;e;93,3;e;89,1;e;-;;86,3;e
		;Dezember;79,9;e;79,2;e;80,0;e;89,7;e;74,8;e;-;;82,2;e;89,6;e;83,8;e;83,8;e;85,4;e;89,0;e;93,3;e;89,1;e;-;;86,3;e
		2006;Januar;80,1;e;79,4;e;80,0;e;89,9;e;74,5;e;-;;82,3;e;89,7;e;84,0;e;83,9;e;85,4;e;89,1;e;93,3;e;89,0;e;-;;86,5;e
		;Februar;80,2;e;79,6;e;80,3;e;90,0;e;75,3;e;-;;82,4;e;89,7;e;84,0;e;84,0;e;85,4;e;89,5;e;93,4;e;89,0;e;-;;86,5;e
		;März;80,3;e;79,7;e;80,5;e;90,0;e;75,4;e;-;;82,4;e;89,7;e;84,0;e;84,1;e;85,4;e;89,5;e;93,4;e;89,0;e;-;;86,5;e
		;April;80,3;e;80,0;e;80,5;e;90,0;e;75,4;e;-;;82,4;e;89,7;e;84,0;e;84,1;e;85,5;e;89,5;e;93,4;e;89,1;e;-;;86,5;e
		;Mai;80,4;e;80,1;e;80,6;e;90,0;e;75,6;e;-;;82,6;e;89,7;e;84,1;e;84,2;e;85,5;e;89,5;e;93,4;e;89,1;e;-;;86,6;e
		;Juni;80,5;e;80,2;e;80,7;e;90,0;e;75,8;e;-;;82,6;e;89,7;e;84,3;e;84,2;e;85,6;e;89,5;e;93,4;e;89,1;e;-;;86,6;e
		;Juli;80,5;e;80,2;e;80,7;e;90,2;e;75,7;e;-;;82,8;e;89,7;e;84,3;e;84,3;e;86,0;e;89,5;e;93,4;e;89,2;e;-;;86,5;e
		;August;80,6;e;80,4;e;80,7;e;90,2;e;75,8;e;-;;83,0;e;89,7;e;84,3;e;84,3;e;85,9;e;89,5;e;93,4;e;89,2;e;-;;86,5;e
		;September;80,7;e;80,5;e;80,8;e;90,2;e;76,0;e;-;;83,0;e;89,7;e;84,3;e;84,3;e;85,9;e;89,6;e;93,4;e;89,2;e;-;;86,6;e
		;Oktober;80,7;e;80,6;e;80,8;e;90,2;e;76,0;e;-;;83,2;e;89,7;e;84,3;e;84,5;e;86,0;e;89,6;e;93,4;e;89,4;e;-;;86,5;e
		;November;80,8;e;80,7;e;80,9;e;90,2;e;75,8;e;-;;83,2;e;89,8;e;84,4;e;84,7;e;86,2;e;89,8;e;93,6;e;89,4;e;-;;86,5;e
		;Dezember;80,9;e;80,8;e;81,0;e;90,1;e;75,9;e;-;;83,3;e;89,8;e;84,5;e;84,7;e;86,2;e;89,8;e;93,6;e;89,4;e;-;;86,5;e
		2007;Januar;81,1;e;80,9;e;79,8;e;90,4;e;75,9;e;-;;83,3;e;89,8;e;84,7;e;84,8;e;86,2;e;90,1;e;93,6;e;89,6;e;-;;86,6;e
		;Februar;81,2;e;80,9;e;79,8;e;90,4;e;76,1;e;-;;83,4;e;89,8;e;84,8;e;84,8;e;86,2;e;90,2;e;93,5;e;89,6;e;-;;86,6;e
		;März;81,3;e;81,2;e;80,1;e;90,4;e;76,0;e;-;;83,4;e;89,8;e;84,8;e;84,9;e;86,2;e;90,2;e;93,6;e;89,6;e;-;;86,7;e
		;April;81,5;e;81,3;e;80,3;e;90,4;e;75,9;e;-;;83,5;e;89,8;e;84,9;e;84,9;e;86,3;e;90,2;e;93,7;e;89,7;e;-;;86,7;e
		;Mai;81,6;e;81,3;e;80,7;e;90,4;e;76,0;e;-;;83,6;e;89,8;e;85,2;e;85,0;e;86,3;e;90,3;e;93,7;e;89,7;e;-;;86,8;e
		;Juni;81,7;e;81,7;e;80,9;e;90,4;e;75,6;e;-;;83,7;e;89,8;e;85,2;e;85,0;e;86,4;e;90,3;e;93,7;e;89,7;e;-;;86,8;e
		;Juli;81,9;e;81,8;e;81,1;e;90,6;e;75,8;e;-;;83,8;e;89,9;e;85,3;e;85,1;e;86,6;e;90,3;e;93,7;e;89,9;e;-;;86,8;e
		;August;82,1;e;82,0;e;81,4;e;90,6;e;75,8;e;-;;83,8;e;89,9;e;85,3;e;85,3;e;86,7;e;90,3;e;93,7;e;89,9;e;-;;86,8;e
		;September;82,1;e;82,1;e;81,4;e;90,6;e;76,1;e;-;;83,9;e;89,9;e;85,5;e;85,3;e;86,8;e;90,3;e;93,7;e;89,9;e;-;;86,8;e
		;Oktober;82,3;e;82,1;e;81,4;e;90,6;e;76,1;e;-;;83,9;e;90,4;e;85,5;e;85,3;e;86,9;e;90,3;e;93,8;e;89,9;e;-;;88,1;e
		;November;82,5;e;82,2;e;81,6;e;90,6;e;76,1;e;-;;84,0;e;90,4;e;85,6;e;85,3;e;87,0;e;90,4;e;93,7;e;89,9;e;-;;88,2;e
		;Dezember;82,5;e;82,3;e;81,8;e;90,6;e;76,2;e;-;;84,0;e;90,4;e;85,6;e;85,3;e;87,2;e;90,4;e;93,7;e;89,9;e;-;;88,2;e
		2008;Januar;82,7;e;82,4;e;81,8;e;90,6;e;76,5;e;-;;84,5;e;90,4;e;85,7;e;85,4;e;87,3;e;90,7;e;93,7;e;90,1;e;-;;88,5;e
		;Februar;82,9;e;82,4;e;82,0;e;90,7;e;76,5;e;-;;84,5;e;90,4;e;85,7;e;85,5;e;87,4;e;90,7;e;93,7;e;90,1;e;-;;88,5;e
		;März;83,0;e;82,7;e;82,0;e;90,7;e;76,5;e;-;;84,5;e;90,4;e;85,9;e;85,5;e;87,5;e;90,7;e;93,7;e;90,1;e;-;;88,5;e
		;April;83,1;e;82,8;e;82,0;e;90,7;e;76,6;e;-;;84,7;e;90,4;e;86,0;e;85,6;e;87,5;e;90,7;e;93,8;e;90,1;e;-;;88,6;e
		;Mai;83,2;e;83,0;e;82,4;e;90,7;e;76,6;e;-;;84,9;e;90,4;e;86,0;e;85,6;e;87,6;e;90,8;e;93,8;e;90,1;e;-;;88,9;e
		;Juni;83,3;e;83,0;e;82,7;e;90,8;e;77,1;e;-;;84,9;e;90,4;e;86,1;e;85,8;e;87,7;e;90,8;e;93,8;e;90,1;e;-;;88,9;e
		;Juli;83,4;e;83,1;e;83,0;e;90,8;e;77,1;e;-;;85,0;e;90,5;e;86,1;e;85,8;e;87,8;e;90,8;e;93,9;e;90,4;e;-;;89,0;e
		;August;83,4;e;83,2;e;83,0;e;90,9;e;77,1;e;-;;85,1;e;90,5;e;86,2;e;85,9;e;87,8;e;90,8;e;93,9;e;90,4;e;-;;89,1;e
		;September;83,5;e;83,5;e;83,0;e;90,9;e;77,5;e;-;;85,1;e;90,5;e;86,1;e;85,9;e;88,0;e;90,8;e;93,9;e;90,4;e;-;;89,1;e
		;Oktober;83,6;e;83,7;e;83,0;e;90,9;e;77,7;e;-;;85,3;e;90,9;e;86,2;e;86,1;e;88,1;e;90,8;e;93,9;e;90,9;e;-;;88,7;e
		;November;83,7;e;83,8;e;83,1;e;90,9;e;77,7;e;-;;85,4;e;90,9;e;86,4;e;86,1;e;88,1;e;90,8;e;93,9;e;90,9;e;-;;88,8;e
		;Dezember;83,7;e;83,8;e;83,1;e;90,9;e;77,7;e;-;;85,4;e;90,9;e;86,5;e;86,1;e;88,2;e;90,8;e;93,9;e;90,9;e;-;;88,8;e
		2009;Januar;83,8;e;83,9;e;83,1;e;91,0;e;77,8;e;-;;85,5;e;91,0;e;86,6;e;86,2;e;88,2;e;90,8;e;94,0;e;90,9;e;-;;88,9;e
		;Februar;84,0;e;84,0;e;83,8;e;91,0;e;78,0;e;-;;85,7;e;91,0;e;86,8;e;86,3;e;88,2;e;90,8;e;94,1;e;90,9;e;-;;88,9;e
		;März;84,1;e;84,1;e;83,8;e;91,0;e;78,0;e;-;;85,7;e;91,0;e;86,8;e;86,4;e;88,3;e;90,9;e;94,1;e;90,9;e;-;;88,9;e
		;April;84,2;e;84,2;e;83,8;e;91,0;e;78,0;e;-;;85,8;e;91,0;e;86,9;e;86,5;e;88,3;e;90,9;e;94,1;e;91,0;e;-;;88,9;e
		;Mai;84,2;e;84,3;e;83,8;e;91,0;e;78,1;e;-;;85,9;e;91,2;e;86,7;e;86,6;e;88,3;e;90,9;e;94,2;e;91,0;e;-;;88,9;e
		;Juni;84,2;e;84,5;e;84,0;e;91,0;e;78,3;e;-;;86,1;e;91,2;e;86,7;e;86,6;e;88,3;e;90,9;e;94,2;e;91,0;e;-;;88,9;e
		;Juli;84,3;e;84,5;e;84,2;e;91,0;e;78,3;e;-;;86,1;e;91,3;e;86,8;e;86,7;e;88,3;e;90,9;e;94,1;e;91,0;e;-;;89,0;e
		;August;84,4;e;84,6;e;84,2;e;91,0;e;78,8;e;-;;86,2;e;91,3;e;86,9;e;86,8;e;88,3;e;90,9;e;94,1;e;91,0;e;-;;89,0;e
		;September;84,4;e;84,8;e;84,4;e;91,0;e;78,8;e;-;;86,2;e;91,2;e;87,0;e;86,8;e;88,5;e;90,9;e;94,2;e;91,0;e;-;;89,0;e
		;Oktober;84,5;e;84,9;e;84,4;e;91,0;e;78,8;e;-;;86,3;e;91,4;e;87,0;e;86,9;e;88,5;e;91,0;e;94,2;e;91,2;e;-;;89,0;e
		;November;84,5;e;85,0;e;84,5;e;91,0;e;78,9;e;-;;86,5;e;91,4;e;87,2;e;87,0;e;88,5;e;91,0;e;94,2;e;91,2;e;-;;89,1;e
		;Dezember;84,5;e;85,0;e;84,5;e;91,0;e;78,3;e;-;;86,5;e;91,4;e;87,3;e;87,0;e;88,6;e;91,0;e;94,2;e;91,2;e;-;;89,1;e
		2010;Januar;84,6;e;85,1;e;84,5;e;91,1;e;78,3;e;-;;86,7;e;91,3;e;87,4;e;87,2;e;88,6;e;91,3;e;94,2;e;91,4;e;-;;89,3;e
		;Februar;84,9;e;85,4;e;84,9;e;91,4;e;78,6;e;-;;86,7;e;91,3;e;87,5;e;87,3;e;88,7;e;91,3;e;94,2;e;91,4;e;-;;89,3;e
		;März;85,1;e;85,4;e;84,9;e;91,4;e;78,6;e;-;;86,7;e;91,5;e;87,5;e;87,5;e;88,8;e;91,3;e;94,2;e;91,4;e;-;;89,3;e
		;April;85,2;e;85,7;e;85,0;e;91,5;e;78,6;e;-;;86,8;e;91,7;e;87,7;e;87,7;e;89,0;e;91,5;e;94,3;e;91,6;e;-;;89,3;e
		;Mai;85,2;e;85,8;e;85,0;e;91,5;e;78,8;e;-;;86,8;e;91,7;e;87,7;e;87,7;e;89,1;e;91,5;e;94,3;e;91,6;e;-;;89,4;e
		;Juni;85,3;e;86,0;e;85,3;e;91,5;e;79,2;e;-;;86,9;e;91,7;e;87,7;e;87,7;e;89,1;e;91,5;e;94,3;e;91,6;e;-;;89,4;e
		;Juli;85,3;e;86,1;e;85,4;e;91,5;e;79,2;e;-;;87,0;e;91,7;e;87,7;e;87,9;e;89,1;e;91,5;e;94,4;e;91,8;e;-;;89,5;e
		;August;85,3;e;86,2;e;85,4;e;91,5;e;80,5;e;-;;87,0;e;91,7;e;87,8;e;87,9;e;89,2;e;91,5;e;94,4;e;91,8;e;-;;89,5;e
		;September;85,6;e;86,1;e;85,5;e;91,5;e;80,6;e;-;;87,0;e;91,7;e;87,8;e;88,0;e;89,2;e;91,6;e;94,4;e;91,8;e;-;;89,5;e
		;Oktober;85,6;e;86,2;e;85,5;e;91,5;e;80,3;e;-;;87,1;e;91,8;e;87,9;e;88,0;e;89,3;e;91,7;e;94,5;e;91,9;e;-;;89,6;e
		;November;86,1;e;86,3;e;85,6;e;91,5;e;81,5;e;-;;87,2;e;91,8;e;88,0;e;88,2;e;89,4;e;91,7;e;94,6;e;91,9;e;-;;89,6;e
		;Dezember;86,2;e;86,3;e;85,6;e;91,5;e;81,5;e;-;;87,2;e;92,0;e;88,0;e;88,4;e;89,4;e;91,7;e;94,6;e;91,9;e;-;;89,6;e
		2011;Januar;86,2;e;86,5;e;85,6;e;91,7;e;81,3;e;-;;87,5;e;92,1;e;88,1;e;88,6;e;89,5;e;91,8;e;94,6;e;92,0;e;-;;89,7;e
		;Februar;86,2;e;86,6;e;86,0;e;92,0;e;81,4;e;-;;87,5;e;92,2;e;88,2;e;88,7;e;89,7;e;91,8;e;94,6;e;92,0;e;-;;89,8;e
		;März;86,3;e;86,7;e;86,2;e;92,0;e;81,3;e;-;;87,6;e;92,5;e;88,3;e;88,9;e;89,7;e;91,8;e;94,6;e;92,0;e;-;;89,8;e
		;April;86,3;e;86,8;e;86,3;e;92,0;e;81,4;e;-;;87,8;e;92,1;e;88,4;e;89,1;e;89,8;e;91,9;e;94,6;e;92,1;e;-;;89,9;e
		;Mai;86,4;e;86,9;e;86,3;e;92,0;e;82,5;e;-;;87,9;e;92,1;e;88,6;e;89,2;e;89,9;e;91,9;e;94,7;e;92,1;e;-;;89,8;e
		;Juni;86,4;e;87,0;e;86,5;e;92,0;e;82,6;e;-;;88,0;e;92,5;e;88,7;e;89,2;e;89,9;e;92,0;e;94,7;e;92,1;e;-;;89,8;e
		;Juli;86,6;e;87,1;e;86,5;e;92,0;e;82,8;e;-;;88,0;e;92,6;e;88,7;e;89,3;e;90,1;e;92,3;e;94,6;e;92,2;e;-;;89,9;e
		;August;86,6;e;87,2;e;86,7;e;92,0;e;83,1;e;-;;88,1;e;92,6;e;88,9;e;89,4;e;90,2;e;92,3;e;94,7;e;92,2;e;-;;90,0;e
		;September;86,7;e;87,2;e;87,0;e;92,0;e;83,2;e;-;;88,1;e;92,6;e;88,9;e;89,5;e;90,3;e;92,4;e;94,8;e;92,2;e;-;;90,0;e
		;Oktober;86,7;e;87,3;e;87,4;e;92,0;e;83,0;e;-;;88,2;e;92,6;e;89,0;e;89,7;e;90,4;e;92,3;e;94,8;e;92,4;e;-;;90,2;e
		;November;86,8;e;87,4;e;87,5;e;92,1;e;83,2;e;-;;88,3;e;92,6;e;89,1;e;89,8;e;90,4;e;92,3;e;94,9;e;92,4;e;-;;90,3;e
		;Dezember;86,9;e;87,7;e;87,5;e;92,1;e;83,1;e;-;;88,4;e;93,1;e;89,2;e;89,8;e;90,5;e;92,3;e;94,9;e;92,4;e;-;;90,3;e
		2012;Januar;87,0;e;87,7;e;87,6;e;92,4;e;83,1;e;-;;88,8;e;93,2;e;89,2;e;90,0;e;90,7;e;92,5;e;94,9;e;92,7;e;-;;90,4;e
		;Februar;87,1;e;87,8;e;87,9;e;92,6;e;83,5;e;-;;88,8;e;93,2;e;89,2;e;90,0;e;90,7;e;92,6;e;94,9;e;92,7;e;-;;90,4;e
		;März;87,1;e;87,9;e;88,0;e;92,6;e;83,6;e;-;;88,8;e;93,2;e;89,3;e;90,1;e;90,7;e;92,6;e;94,9;e;92,7;e;-;;90,4;e
		;April;87,2;e;87,9;e;88,0;e;92,6;e;83,6;e;-;;89,1;e;92,7;e;89,4;e;90,2;e;90,8;e;92,7;e;94,9;e;92,7;e;-;;90,4;e
		;Mai;87,2;e;88,2;e;88,0;e;92,6;e;84,0;e;-;;89,2;e;92,7;e;89,5;e;90,3;e;90,8;e;92,7;e;95,0;e;92,7;e;-;;90,4;e
		;Juni;87,3;e;88,2;e;88,0;e;92,6;e;83,9;e;-;;89,3;e;92,7;e;89,5;e;90,3;e;90,9;e;92,7;e;95,1;e;92,7;e;-;;90,4;e
		;Juli;87,3;e;88,3;e;88,1;e;92,7;e;83,9;e;-;;89,4;e;92,7;e;89,6;e;90,4;e;90,9;e;92,8;e;95,1;e;92,9;e;-;;90,5;e
		;August;87,4;e;88,4;e;88,2;e;92,7;e;84,5;e;-;;89,6;e;92,7;e;89,6;e;90,6;e;91,0;e;92,8;e;95,1;e;92,9;e;-;;90,6;e
		;September;87,5;e;88,5;e;88,2;e;92,7;e;84,5;e;-;;89,6;e;92,7;e;89,7;e;90,8;e;91,0;e;92,8;e;95,1;e;92,9;e;-;;90,7;e
		;Oktober;87,5;e;88,5;e;88,2;e;92,7;e;84,5;e;-;;89,7;e;93,2;e;89,8;e;90,9;e;91,2;e;93,0;e;95,2;e;92,9;e;-;;90,8;e
		;November;87,6;e;88,6;e;88,2;e;92,7;e;84,8;e;-;;89,8;e;93,2;e;90,0;e;90,9;e;91,3;e;93,1;e;95,2;e;92,9;e;-;;90,8;e
		;Dezember;87,7;e;88,6;e;88,2;e;92,7;e;84,9;e;-;;89,8;e;93,2;e;90,2;e;90,9;e;91,3;e;93,1;e;95,3;e;92,9;e;-;;90,8;e
		2013;Januar;87,8;e;88,8;e;90,0;e;93,0;e;84,9;e;-;;90,0;e;93,3;e;90,4;e;91,1;e;91,5;e;93,2;e;95,3;e;93,1;e;-;;91,0;e
		;Februar;87,9;e;88,8;e;90,2;e;93,2;e;84,9;e;-;;90,0;e;93,5;e;90,5;e;91,4;e;91,6;e;93,3;e;95,3;e;93,1;e;-;;91,0;e
		;März;88,0;e;88,9;e;90,3;e;93,2;e;84,8;e;-;;90,0;e;93,7;e;90,6;e;91,5;e;91,6;e;93,2;e;95,3;e;93,1;e;-;;91,0;e
		;April;88,1;e;89,1;e;90,3;e;93,3;e;84,9;e;-;;90,3;e;93,3;e;90,7;e;91,6;e;91,7;e;93,3;e;95,3;e;93,3;e;-;;91,1;e
		;Mai;88,2;e;89,1;e;90,3;e;93,3;e;85,0;e;-;;90,4;e;93,2;e;90,7;e;91,6;e;91,9;e;93,4;e;95,4;e;93,3;e;-;;91,1;e
		;Juni;88,2;e;89,3;e;90,4;e;93,3;e;84,9;e;-;;90,4;e;93,2;e;90,9;e;91,7;e;92,1;e;93,4;e;95,4;e;93,3;e;-;;91,1;e
		;Juli;88,3;e;89,5;e;90,4;e;93,4;e;84,9;e;-;;90,8;e;93,5;e;91,0;e;91,9;e;92,2;e;93,4;e;95,4;e;93,5;e;-;;91,1;e
		;August;88,4;e;89,6;e;90,4;e;93,4;e;85,6;e;-;;90,9;e;93,6;e;91,2;e;92,0;e;92,3;e;93,4;e;95,5;e;93,5;e;-;;91,1;e
		;September;88,6;e;89,6;e;90,4;e;93,4;e;85,6;e;-;;90,9;e;93,6;e;91,2;e;92,1;e;92,3;e;93,4;e;95,5;e;93,5;e;-;;91,2;e
		;Oktober;88,6;e;89,6;e;90,4;e;93,4;e;85,7;e;-;;91,0;e;93,5;e;91,4;e;92,2;e;92,4;e;93,5;e;95,5;e;93,7;e;-;;91,3;e
		;November;88,8;e;89,7;e;90,4;e;93,4;e;85,9;e;-;;91,0;e;93,5;e;91,5;e;92,8;e;92,5;e;93,6;e;95,6;e;93,7;e;-;;91,3;e
		;Dezember;88,9;e;89,8;e;90,4;e;93,5;e;86,2;e;-;;91,0;e;93,5;e;91,6;e;92,8;e;92,7;e;93,6;e;95,6;e;93,7;e;-;;91,3;e
		2014;Januar;89,2;e;90,0;e;90,7;e;93,8;e;86,4;e;-;;91,5;e;93,8;e;91,7;e;92,9;e;92,9;e;94,0;e;95,6;e;93,9;e;-;;91,4;e
		;Februar;89,2;e;90,1;e;91,8;e;94,0;e;86,9;e;-;;91,5;e;93,8;e;91,9;e;93,0;e;93,0;e;94,0;e;95,7;e;93,9;e;-;;91,4;e
		;März;89,3;e;90,2;e;91,9;e;94,0;e;87,0;e;-;;91,6;e;93,7;e;92,0;e;93,1;e;93,1;e;94,0;e;95,7;e;93,9;e;-;;91,5;e
		;April;89,5;e;90,4;e;91,8;e;94,0;e;87,3;e;-;;91,7;e;93,8;e;92,1;e;93,4;e;93,1;e;94,0;e;95,8;e;94,1;e;-;;91,7;e
		;Mai;89,7;e;90,5;e;91,8;e;94,1;e;88,5;e;-;;91,9;e;93,8;e;92,2;e;93,5;e;93,1;e;94,0;e;95,8;e;94,1;e;-;;91,8;e
		;Juni;89,8;e;90,6;e;91,8;e;94,1;e;88,5;e;-;;91,9;e;93,8;e;92,3;e;93,6;e;93,4;e;94,0;e;95,8;e;94,1;e;-;;91,8;e
		;Juli;89,8;e;90,7;e;91,8;e;94,2;e;88,5;e;-;;92,0;e;93,9;e;92,6;e;93,7;e;93,4;e;94,1;e;95,9;e;94,2;e;-;;92,0;e
		;August;89,9;e;91,0;e;91,8;e;94,2;e;88,9;e;-;;92,1;e;93,9;e;92,7;e;93,7;e;93,4;e;94,1;e;96,0;e;94,2;e;-;;92,1;e
		;September;90,0;e;91,0;e;91,8;e;94,3;e;88,8;e;-;;92,3;e;94,2;e;92,8;e;93,8;e;93,4;e;94,1;e;96,1;e;94,2;e;-;;92,1;e
		;Oktober;90,0;e;91,0;e;91,8;e;94,3;e;88,9;e;-;;92,4;e;94,3;e;92,8;e;94,0;e;93,8;e;94,2;e;96,1;e;94,3;e;-;;92,1;e
		;November;90,2;e;91,3;e;91,8;e;94,5;e;89,3;e;-;;92,5;e;94,3;e;93,0;e;94,1;e;93,8;e;94,3;e;96,1;e;94,3;e;-;;92,1;e
		;Dezember;90,2;e;91,3;e;91,8;e;94,5;e;89,3;e;-;;92,6;e;94,3;e;93,3;e;94,1;e;94,0;e;94,3;e;96,2;e;94,3;e;-;;92,0;e
		2015;Januar;90,6;e;91,7;e;91,8;e;94,5;e;89,4;e;94,1;e;92,8;e;94,3;e;93,4;e;94,1;e;94,1;e;94,6;e;96,4;e;94,3;e;93,6;e;92,3;e
		;Februar;90,7;e;91,8;e;91,8;e;94,5;e;89,4;e;94,1;e;92,8;e;94,3;e;93,4;e;94,2;e;94,1;e;94,6;e;96,5;e;94,3;e;94,0;e;92,3;e
		;März;90,8;e;91,8;e;92,9;e;94,5;e;89,5;e;94,1;e;92,9;e;94,4;e;93,5;e;94,2;e;94,2;e;94,7;e;96,5;e;94,3;e;94,1;e;92,6;e
		;April;91,1;e;92,0;e;92,9;e;94,5;e;89,9;e;94,1;e;93,0;e;94,4;e;93,6;e;94,3;e;94,3;e;94,8;e;96,5;e;94,7;e;94,2;e;92,6;e
		;Mai;91,2;e;92,1;e;92,9;e;94,5;e;90,0;e;94,1;e;93,1;e;94,4;e;93,7;e;94,4;e;94,5;e;94,9;e;96,6;e;94,7;e;94,3;e;93,0;e
		;Juni;91,4;e;92,1;e;92,9;e;94,5;e;90,0;e;94,1;e;93,3;e;94,4;e;93,7;e;94,5;e;94,5;e;94,9;e;96,6;e;94,7;e;94,3;e;93,0;e
		;Juli;91,7;e;92,2;e;92,9;e;94,5;e;90,1;e;94,4;e;93,4;e;94,4;e;93,7;e;94,5;e;94,6;e;95,1;e;96,8;e;94,8;e;94,3;e;93,0;e
		;August;91,8;e;92,2;e;92,9;e;94,5;e;90,1;e;94,8;e;93,5;e;94,6;e;93,7;e;94,6;e;94,6;e;95,1;e;96,8;e;94,8;e;94,5;e;93,1;e
		;September;91,9;e;92,3;e;92,9;e;94,5;e;90,1;e;95,1;e;93,6;e;94,6;e;93,6;e;94,6;e;94,6;e;95,0;e;96,8;e;95,0;e;94,6;e;93,1;e
		;Oktober;91,9;e;92,4;e;92,9;e;94,5;e;90,6;e;95,1;e;93,7;e;94,9;e;93,6;e;94,7;e;94,6;e;95,1;e;96,8;e;95,0;e;94,6;e;93,1;e
		;November;92,0;e;92,4;e;92,9;e;94,5;e;91,0;e;95,2;e;93,7;e;95,1;e;93,7;e;94,8;e;94,6;e;95,1;e;96,7;e;95,5;e;94,8;e;93,2;e
		;Dezember;92,0;e;92,5;e;93,0;e;94,5;e;91,1;e;95,3;e;93,7;e;95,1;e;93,7;e;94,8;e;94,6;e;95,1;e;96,8;e;95,6;e;94,9;e;93,2;e
		2016;Januar;92,2;e;92,9;e;93,1;e;94,5;e;91,2;e;95,4;e;94,0;e;95,1;e;94,1;e;95,1;e;94,7;e;95,4;e;96,9;e;95,8;e;95,0;e;93,2;e
		;Februar;92,4;e;93,1;e;93,1;e;94,5;e;91,5;e;95,5;e;94,0;e;95,2;e;94,2;e;95,1;e;94,7;e;95,4;e;96,9;e;95,8;e;95,1;e;93,4;e
		;März;92,5;e;93,2;e;93,2;e;94,5;e;91,6;e;95,5;e;94,1;e;95,2;e;94,2;e;95,1;e;94,7;e;95,4;e;96,7;e;95,8;e;95,3;e;93,4;e
		;April;92,6;e;93,3;e;93,5;e;94,6;e;91,7;e;95,5;e;94,2;e;95,2;e;94,3;e;95,3;e;94,7;e;95,6;e;96,8;e;95,8;e;95,3;e;93,4;e
		;Mai;92,6;e;93,4;e;93,6;e;94,7;e;91,9;e;95,5;e;94,3;e;95,2;e;94,4;e;95,3;e;94,7;e;95,6;e;96,7;e;95,8;e;95,3;e;93,4;e
		;Juni;92,6;e;93,4;e;93,7;e;94,7;e;91,9;e;95,5;e;94,4;e;95,1;e;94,5;e;95,3;e;94,8;e;95,6;e;96,7;e;95,8;e;95,4;e;93,6;e
		;Juli;92,6;e;93,6;e;94,3;e;94,8;e;92,0;e;95,7;e;94,5;e;95,1;e;94,6;e;95,4;e;94,9;e;95,8;e;96,7;e;95,8;e;95,4;e;93,6;e
		;August;92,7;e;93,7;e;94,4;e;94,9;e;92,3;e;96,1;e;94,6;e;95,1;e;94,7;e;95,4;e;95,0;e;95,8;e;96,8;e;95,9;e;95,6;e;93,7;e
		;September;92,7;e;93,9;e;94,4;e;95,4;e;92,3;e;96,2;e;94,7;e;95,1;e;95,0;e;95,6;e;95,2;e;95,8;e;96,9;e;95,9;e;95,6;e;93,9;e
		;Oktober;93,0;e;94,1;e;94,5;e;95,5;e;92,3;e;96,5;e;94,8;e;95,1;e;95,1;e;95,7;e;95,2;e;95,8;e;96,9;e;95,9;e;95,7;e;93,9;e
		;November;93,2;e;94,1;e;94,6;e;95,5;e;92,4;e;96,7;e;95,0;e;95,3;e;95,2;e;95,7;e;95,3;e;95,9;e;97,1;e;96,0;e;95,7;e;94,0;e
		;Dezember;93,2;e;94,2;e;94,8;e;95,5;e;92,4;e;97,0;e;95,0;e;96,5;e;95,2;e;95,8;e;95,3;e;95,9;e;97,1;e;96,1;e;95,8;e;94,0;e
		2017;Januar;93,4;e;94,3;e;94,9;e;95,5;e;92,5;e;97,3;e;95,1;e;96,6;e;95,3;e;96,1;e;95,4;e;96,1;e;97,2;e;96,1;e;95,9;e;94,1;e
		;Februar;93,6;e;94,6;e;94,9;e;95,6;e;92,6;e;97,4;e;95,1;e;96,6;e;95,4;e;96,3;e;95,5;e;96,2;e;97,1;e;96,2;e;95,9;e;94,1;e
		;März;93,7;e;94,7;e;95,2;e;95,8;e;92,7;e;97,5;e;95,2;e;96,7;e;95,5;e;96,4;e;95,5;e;96,2;e;97,1;e;96,2;e;96,0;e;94,0;e
		;April;93,9;e;94,9;e;95,3;e;95,8;e;92,8;e;97,6;e;95,3;e;96,9;e;95,8;e;96,6;e;95,6;e;96,3;e;97,2;e;96,3;e;96,0;e;94,1;e
		;Mai;94,1;e;95,0;e;95,4;e;96,0;e;93,2;e;97,6;e;95,3;e;96,9;e;95,9;e;96,7;e;95,7;e;96,3;e;97,3;e;96,3;e;96,0;e;94,1;e
		;Juni;94,1;e;95,1;e;95,5;e;96,3;e;93,3;e;97,7;e;95,4;e;97,1;e;96,0;e;96,7;e;95,7;e;96,4;e;97,3;e;96,3;e;96,1;e;94,1;e
		;Juli;94,3;e;95,2;e;95,6;e;96,3;e;93,4;e;97,8;e;95,5;e;97,1;e;96,2;e;96,8;e;95,8;e;96,5;e;97,3;e;96,3;e;96,2;e;94,2;e
		;August;94,4;e;95,3;e;95,9;e;96,3;e;93,6;e;97,9;e;95,6;e;97,1;e;96,3;e;96,8;e;95,8;e;96,5;e;97,5;e;96,4;e;96,3;e;94,3;e
		;September;94,4;e;95,4;e;96,2;e;96,4;e;93,6;e;97,9;e;95,7;e;97,2;e;96,4;e;96,8;e;95,9;e;96,5;e;97,5;e;96,4;e;96,4;e;94,4;e
		;Oktober;94,8;e;95,6;e;96,6;e;96,5;e;93,6;e;98,0;e;95,8;e;97,5;e;96,6;e;97,0;e;96,0;e;96,5;e;97,6;e;96,4;e;96,6;e;94,5;e
		;November;95,1;e;95,7;e;96,8;e;96,5;e;93,9;e;98,1;e;95,9;e;97,5;e;96,7;e;97,0;e;96,1;e;96,5;e;97,6;e;96,6;e;96,6;e;94,5;e
		;Dezember;95,2;e;95,8;e;97,1;e;96,6;e;93,9;e;98,1;e;96,2;e;97,6;e;97,0;e;97,1;e;96,1;e;96,6;e;97,8;e;96,9;e;96,6;e;94,7;e
		2018;Januar;95,4;e;96,2;e;97,4;e;96,8;e;94,0;e;98,3;e;96,5;e;97,6;e;97,0;e;97,4;e;96,3;e;96,8;e;97,9;e;96,9;e;96,8;e;94,7;e
		;Februar;95,4;e;96,3;e;97,5;e;96,9;e;94,2;e;98,3;e;96,7;e;97,7;e;97,1;e;97,6;e;96,4;e;96,8;e;98,0;e;97,0;e;96,8;e;94,8;e
		;März;95,5;e;96,4;e;97,6;e;97,0;e;94,2;e;98,3;e;96,8;e;97,7;e;97,2;e;97,6;e;96,7;e;96,9;e;98,0;e;97,0;e;96,9;e;94,8;e
		;April;95,5;e;96,7;e;97,7;e;97,0;e;94,2;e;98,4;e;96,9;e;97,7;e;97,4;e;97,7;e;96,7;e;96,9;e;98,1;e;97,0;e;97,1;e;94,8;e
		;Mai;95,7;e;96,8;e;97,7;e;97,5;e;94,7;e;98,5;e;96,9;e;97,8;e;97,5;e;97,7;e;96,9;e;96,9;e;98,1;e;97,0;e;97,2;e;94,9;e
		;Juni;95,9;e;96,8;e;97,8;e;97,6;e;94,7;e;98,5;e;97,2;e;97,8;e;97,5;e;97,8;e;96,9;e;96,9;e;98,3;e;97,1;e;97,4;e;95,0;e
		;Juli;96,1;e;97,0;e;98,0;e;97,6;e;94,9;e;98,6;e;97,4;e;97,8;e;97,6;e;97,9;e;96,9;e;97,1;e;98,4;e;97,1;e;97,4;e;95,0;e
		;August;96,2;e;97,2;e;98,1;e;97,6;e;94,9;e;98,6;e;97,4;e;97,9;e;97,7;e;98,1;e;97,0;e;97,1;e;98,5;e;97,2;e;97,5;e;95,2;e
		;September;96,3;e;97,1;e;98,2;e;97,7;e;94,9;e;98,6;e;97,4;e;98,0;e;97,9;e;98,2;e;97,4;e;97,6;e;98,6;e;97,2;e;97,6;e;95,4;e
		;Oktober;96,4;e;97,3;e;98,3;e;97,7;e;95,0;e;98,6;e;97,6;e;98,0;e;98,0;e;98,4;e;97,6;e;97,6;e;98,8;e;97,2;e;97,6;e;95,5;e
		;November;96,5;e;97,4;e;98,3;e;97,7;e;95,2;e;98,6;e;97,7;e;98,1;e;98,0;e;98,5;e;97,7;e;97,6;e;98,7;e;97,4;e;97,6;e;95,5;e
		;Dezember;96,6;e;97,5;e;98,4;e;97,8;e;95,3;e;98,6;e;97,8;e;98,1;e;98,1;e;98,5;e;97,8;e;97,6;e;98,7;e;98,0;e;97,5;e;95,6;e
		2019;Januar;96,8;e;97,9;e;98,6;e;97,8;e;95,4;e;98,7;e;97,9;e;98,2;e;98,2;e;98,8;e;98,0;e;97,9;e;98,9;e;98,0;e;97,6;e;95,7;e
		;Februar;97,0;e;98,0;e;99,0;e;98,4;e;95,5;e;98,9;e;98,2;e;98,4;e;98,2;e;98,8;e;98,1;e;97,9;e;99,0;e;98,1;e;97,7;e;95,8;e
		;März;97,1;e;98,0;e;99,0;e;98,4;e;95,7;e;99,0;e;98,4;e;98,4;e;98,4;e;98,9;e;98,3;e;98,1;e;99,1;e;98,1;e;97,8;e;96,0;e
		;April;97,3;e;98,2;e;99,2;e;98,6;e;95,7;e;99,0;e;98,5;e;98,6;e;98,6;e;99,1;e;98,5;e;98,2;e;99,1;e;98,2;e;97,9;e;96,1;e
		;Mai;97,5;e;98,3;e;99,2;e;98,7;e;95,9;e;99,0;e;98,6;e;98,7;e;98,6;e;99,1;e;98,6;e;98,1;e;99,2;e;98,4;e;98,4;e;96,1;e
		;Juni;97,6;e;98,3;e;99,3;e;98,7;e;95,9;e;99,2;e;98,8;e;99,0;e;98,9;e;99,2;e;98,7;e;98,1;e;99,4;e;98,4;e;98,5;e;96,2;e
		;Juli;97,8;e;98,5;e;99,5;e;98,9;e;96,2;e;99,3;e;98,8;e;99,0;e;99,1;e;99,2;e;98,9;e;99,0;e;99,4;e;98,4;e;98,7;e;96,1;e
		;August;98,0;e;98,5;e;99,4;e;99,1;e;97,2;e;99,3;e;98,9;e;99,4;e;99,1;e;99,3;e;98,9;e;99,0;e;99,5;e;98,6;e;98,7;e;96,1;e
		;September;98,2;e;98,6;e;99,5;e;99,2;e;97,4;e;99,3;e;99,0;e;99,5;e;99,4;e;99,3;e;99,0;e;99,0;e;99,5;e;98,6;e;98,7;e;96,3;e
		;Oktober;98,4;e;98,9;e;99,6;e;99,3;e;97,4;e;99,5;e;99,1;e;99,5;e;99,5;e;99,5;e;99,1;e;99,1;e;99,6;e;98,6;e;98,8;e;96,3;e
		;November;98,5;e;99,0;e;99,7;e;99,4;e;97,4;e;99,5;e;99,3;e;99,6;e;99,6;e;99,7;e;99,1;e;99,1;e;99,7;e;98,8;e;98,8;e;96,5;e
		;Dezember;98,6;e;99,1;e;99,8;e;99,4;e;97,4;e;99,5;e;99,4;e;99,6;e;99,8;e;99,8;e;99,3;e;99,1;e;99,8;e;98,8;e;98,9;e;96,6;e
		2020;Januar;98,7;e;99,4;e;99,9;e;99,5;e;97,6;e;99,7;e;99,5;e;99,6;e;99,5;e;99,6;e;99,6;e;99,5;e;99,8;e;98,8;e;99,5;e;96,6;e
		;Februar;98,9;e;99,6;e;100,0;e;99,6;e;97,6;e;99,7;e;99,6;e;99,6;e;99,6;e;99,7;e;99,6;e;99,5;e;99,9;e;100,0;e;99,5;e;96,6;e
		;März;99,6;e;99,7;e;100,0;e;99,7;e;97,7;e;99,8;e;99,9;e;99,8;e;99,9;e;99,7;e;99,9;e;99,7;e;99,9;e;100,0;e;99,6;e;99,7;e
		;April;99,7;e;99,7;e;100,0;e;99,8;e;97,8;e;99,9;e;100,0;e;99,8;e;99,9;e;99,8;e;99,9;e;99,8;e;99,9;e;100,0;e;99,7;e;99,7;e
		;Mai;99,9;e;99,8;e;100,0;e;100,0;e;98,0;e;99,9;e;100,0;e;99,9;e;99,9;e;99,9;e;99,9;e;99,8;e;99,9;e;100,1;e;99,8;e;99,7;e
		;Juni;100,0;e;99,8;e;100,0;e;100,0;e;98,0;e;99,9;e;100,1;e;99,9;e;100,0;e;99,9;e;100,0;e;99,9;e;100,0;e;100,1;e;100,1;e;100,9;e
		;Juli;100,0;e;100,2;e;100,0;e;100,0;e;98,0;e;100,0;e;100,2;e;99,9;e;100,0;e;100,1;e;100,0;e;100,1;e;100,0;e;100,1;e;100,1;e;100,9;e
		;August;100,1;e;100,2;e;100,0;e;100,1;e;103,1;e;100,1;e;100,1;e;100,0;e;100,0;e;100,2;e;100,1;e;100,3;e;99,9;e;100,1;e;100,2;e;101,2;e
		;September;100,4;e;100,3;e;100,0;e;100,1;e;103,1;e;100,1;e;100,2;e;100,3;e;100,1;e;100,2;e;100,1;e;100,3;e;100,1;e;100,1;e;100,2;e;101,2;e
		;Oktober;100,6;e;100,4;e;100,0;e;100,1;e;103,1;e;100,2;e;100,1;e;100,3;e;100,2;e;100,3;e;100,2;e;100,3;e;100,1;e;100,1;e;100,3;e;101,2;e
		;November;101,0;e;100,4;e;100,1;e;100,2;e;103,1;e;100,3;e;100,1;e;100,4;e;100,2;e;100,3;e;100,3;e;100,3;e;100,2;e;100,3;e;100,5;e;101,2;e
		;Dezember;101,1;e;100,5;e;100,0;e;100,7;e;103,1;e;100,4;e;100,2;e;100,4;e;100,8;e;100,4;e;100,3;e;100,3;e;100,4;e;100,3;e;100,5;e;101,2;e
		2021;Januar;101,5;e;100,6;e;99,8;e;100,7;e;103,2;e;100,4;e;100,3;e;100,4;e;100,8;e;100,5;e;100,3;e;100,5;e;100,5;e;100,5;e;100,6;e;101,2;e
		;Februar;101,6;e;100,7;e;99,5;e;100,8;e;103,8;e;100,4;e;100,4;e;100,5;e;100,9;e;100,6;e;100,4;e;100,5;e;100,5;e;100,5;e;100,7;e;101,3;e
		;März;101,7;e;100,8;e;99,5;e;101,1;e;103,9;e;100,5;e;100,5;e;100,5;e;101,1;e;100,7;e;100,6;e;100,6;e;101,6;e;100,5;e;100,7;e;101,3;e
		;April;101,7;e;101,0;e;99,6;e;101,3;e;103,9;e;100,5;e;100,6;e;100,5;e;101,1;e;100,9;e;100,6;e;101,1;e;101,7;e;100,6;e;100,8;e;101,3;e
		;Mai;101,8;e;101,1;e;99,7;e;101,3;e;104,1;e;100,5;e;100,6;e;100,8;e;101,2;e;101,0;e;100,7;e;101,3;e;101,7;e;100,7;e;100,8;e;101,4;e
		;Juni;101,8;e;101,2;e;99,9;e;101,3;e;104,4;e;100,6;e;100,6;e;100,8;e;101,2;e;101,1;e;100,7;e;101,4;e;101,7;e;100,7;e;100,9;e;101,4;e
		;Juli;101,9;e;101,3;e;99,9;e;101,4;e;104,4;e;100,6;e;100,7;e;101,0;e;101,2;e;101,3;e;100,7;e;101,6;e;101,7;e;100,7;e;101,3;e;101,4;e
		;August;102,0;e;101,7;e;100,0;e;101,5;e;104,5;e;100,6;e;100,7;e;101,0;e;101,2;e;101,3;e;100,8;e;101,6;e;101,7;e;100,8;e;101,4;e;101,4;e
		;September;102,1;e;101,7;e;100,2;e;101,5;e;104,6;e;100,6;e;100,8;e;101,1;e;101,2;e;101,4;e;100,9;e;101,5;e;101,8;e;100,8;e;101,5;e;101,5;e
		;Oktober;102,3;e;101,9;e;100,4;e;101,5;e;104,7;e;100,7;e;100,8;e;101,1;e;101,4;e;101,6;e;100,9;e;101,5;e;101,8;e;100,8;e;101,6;e;102,1;e
		;November;102,4;e;102,1;e;100,4;e;101,5;e;104,7;e;100,8;e;101,1;e;101,1;e;101,4;e;101,9;e;101,0;e;101,6;e;101,9;e;100,9;e;102,1;e;102,1;e
		;Dezember;102,5;e;102,2;e;100,5;e;101,5;e;104,7;e;101,1;e;101,1;e;101,3;e;101,4;e;102,0;e;101,2;e;101,6;e;101,9;e;100,9;e;102,1;e;102,2;e
		2022;Januar;102,7;e;102,5;e;100,5;e;101,7;e;104,9;e;101,2;e;101,7;e;101,3;e;101,5;e;102,1;e;101,3;e;101,8;e;102,0;e;100,9;e;102,3;e;102,3;e
		;Februar;102,8;e;102,6;e;101,2;e;101,7;e;105,0;e;101,3;e;101,9;e;101,5;e;101,6;e;102,2;e;101,9;e;101,8;e;102,1;e;100,9;e;102,4;e;102,3;e
		;März;103,4;e;102,7;e;101,2;e;101,8;e;105,1;e;101,4;e;102,1;e;101,6;e;101,6;e;102,3;e;102,5;e;101,9;e;102,2;e;100,9;e;102,5;e;102,3;e
		;April;103,5;e;102,8;e;102,1;e;101,9;e;105,1;e;101,6;e;102,2;e;101,6;e;101,7;e;102,4;e;102,9;e;102,0;e;102,2;e;100,9;e;102,6;e;102,3;e
		;Mai;103,7;e;103,0;e;103,3;e;102,0;e;105,3;e;101,7;e;102,5;e;101,6;e;101,9;e;102,5;e;103,0;e;102,1;e;102,5;e;101,0;e;102,6;e;102,4;e
		;Juni;103,7;e;103,1;e;103,4;e;102,0;e;105,4;e;102,1;e;102,6;e;101,7;e;102,0;e;102,6;e;103,0;e;102,1;e;102,5;e;101,1;e;102,8;e;102,4;e
		;Juli;103,9;e;103,3;e;103,4;e;102,0;e;105,4;e;102,3;e;102,7;e;101,7;e;102,1;e;102,8;e;103,1;e;102,2;e;102,6;e;101,1;e;102,8;e;102,4;e
		;August;103,9;e;104,0;e;103,4;e;102,1;e;105,9;e;102,4;e;102,8;e;101,7;e;102,2;e;102,9;e;103,1;e;102,3;e;102,6;e;101,1;e;102,9;e;102,5;e
		;September;104,1;e;104,1;e;103,6;e;102,1;e;106,0;e;102,7;e;102,8;e;102,6;e;102,6;e;102,9;e;103,1;e;102,6;e;102,7;e;101,1;e;103,3;e;102,5;e
		;Oktober;104,9;e;104,3;e;103,6;e;102,1;e;106,0;e;102,8;e;103,8;e;102,6;e;102,8;e;102,9;e;103,2;e;102,7;e;102,7;e;101,1;e;103,3;e;102,6;e
		;November;105,1;e;104,6;e;103,6;e;102,2;e;106,2;e;102,9;e;103,8;e;102,6;e;103,0;e;103,0;e;103,3;e;102,7;e;103,1;e;101,3;e;103,4;e;102,6;e
		;Dezember;105,2;e;104,7;e;103,6;e;102,2;e;106,4;e;102,9;e;103,9;e;102,7;e;103,0;e;103,0;e;103,4;e;102,8;e;103,1;e;101,3;e;103,5;e;102,7;e
		2023;Januar;106,0;e;105,3;e;103,7;e;102,2;e;106,5;e;103,1;e;104,2;e;102,7;e;103,3;e;103,2;e;103,6;e;103,0;e;103,3;e;101,3;e;103,7;e;102,7;e
		;Februar;106,6;e;105,4;e;104,1;e;102,5;e;106,7;e;103,1;e;104,4;e;102,8;e;103,3;e;103,3;e;103,6;e;103,0;e;103,4;e;101,3;e;103,7;e;102,7;e
		;März;107,1;e;105,5;e;104,1;e;103,0;e;106,8;e;103,2;e;104,8;e;102,9;e;103,5;e;103,5;e;104,0;e;103,1;e;103,4;e;101,3;e;103,9;e;102,8;e
		;April;107,2;e;105,5;e;104,2;e;103,0;e;106,8;e;103,3;e;104,9;e;103,0;e;103,6;e;103,8;e;104,2;e;103,4;e;103,5;e;101,3;e;104,1;e;102,8;e
		;Mai;107,6;e;105,6;e;104,2;e;103,0;e;106,8;e;103,4;e;105,1;e;103,0;e;103,7;e;103,9;e;104,4;e;103,5;e;103,5;e;101,4;e;104,4;e;102,9;e
		;Juni;108,4;e;105,7;e;104,3;e;103,0;e;109,5;e;103,6;e;105,3;e;103,1;e;103,8;e;104,1;e;104,3;e;103,6;e;103,7;e;101,4;e;104,5;e;102,9;e
		;Juli;108,5;e;106,3;e;104,4;e;103,1;e;109,5;e;103,6;e;105,3;e;103,1;e;103,9;e;104,2;e;104,4;e;103,9;e;103,7;e;101,4;e;104,5;e;102,9;e
		;August;108,7;e;106,4;e;104,5;e;106,0;e;109,5;e;103,7;e;105,4;e;103,2;e;104,0;e;104,4;e;104,5;e;104,0;e;103,8;e;101,5;e;104,7;e;102,9;e
		;September;108,8;e;106,5;e;104,5;e;106,1;e;109,9;e;104,0;e;105,4;e;103,2;e;104,1;e;104,4;e;104,6;e;104,0;e;103,9;e;101,5;e;104,7;e;103,1;e
		;Oktober;108,8;e;107,1;e;104,7;e;106,1;e;109,9;e;104,0;e;105,5;e;103,2;e;104,2;e;104,6;e;104,7;e;104,1;e;104,4;e;101,5;e;104,9;e;103,1;e
		;November;108,9;e;107,2;e;104,8;e;106,1;e;110,0;e;104,1;e;105,6;e;103,2;e;104,3;e;104,6;e;104,8;e;104,1;e;104,5;e;101,6;e;105,1;e;103,1;e
		;Dezember;109,1;e;107,5;e;104,9;e;106,2;e;110,0;e;104,1;e;105,7;e;103,2;e;104,5;e;104,7;e;104,8;e;104,1;e;104,5;e;101,7;e;105,1;e;103,3;e
		2024;Januar;109,3;e;108,0;e;106,0;e;106,2;e;110,3;e;104,4;e;106,1;e;103,3;e;104,9;e;105,1;e;105,1;e;104,5;e;104,6;e;101,8;e;105,3;e;103,3;e
		;Februar;109,3;e;108,1;e;106,6;e;106,2;e;110,6;e;104,4;e;106,5;e;103,3;e;104,9;e;105,4;e;105,6;e;104,7;e;104,8;e;101,9;e;105,3;e;103,3;e
		;März;109,4;e;108,3;e;106,7;e;106,3;e;110,6;e;104,5;e;106,7;e;103,3;e;105,0;e;105,5;e;107,2;e;105,0;e;104,8;e;104,7;e;105,4;e;103,7;e
		;April;109,7;e;109,2;e;106,7;e;106,5;e;110,7;e;104,6;e;106,9;e;103,3;e;105,1;e;105,7;e;107,4;e;105,2;e;104,9;e;104,7;e;105,6;e;103,8;e
		;Mai;109,9;e;109,4;e;106,8;e;106,7;e;110,7;e;104,7;e;106,9;e;103,6;e;105,1;e;105,9;e;107,5;e;105,3;e;105,0;e;104,8;e;105,8;e;103,8;e
		;Juni;110,0;e;109,4;e;106,9;e;106,8;e;110,8;e;105,0;e;107,2;e;103,6;e;106,0;e;105,9;e;107,5;e;105,3;e;105,1;e;104,8;e;105,9;e;103,9;e
		;Juli;110,1;e;109,5;e;106,9;e;106,8;e;110,9;e;105,1;e;107,3;e;103,9;e;106,2;e;105,9;e;107,6;e;105,4;e;106,7;e;104,9;e;106,9;e;103,9;e
		;August;110,2;e;109,7;e;107,0;e;106,9;e;111,6;e;105,1;e;107,4;e;103,9;e;106,2;e;106,0;e;107,8;e;105,9;e;106,8;e;104,9;e;107,3;e;103,9;e
		;September;110,4;e;109,8;e;107,0;e;107,0;e;111,7;e;105,1;e;107,5;e;104,1;e;106,7;e;106,1;e;107,8;e;106,0;e;106,8;e;105,0;e;107,5;e;103,9;e
		;Oktober;110,5;e;110,1;e;107,2;e;107,0;e;111,7;e;105,2;e;107,5;e;104,2;e;106,9;e;106,1;e;108,6;e;106,4;e;106,9;e;105,1;e;107,6;e;103,9;e
		;November;110,7;e;110,1;e;107,3;e;107,0;e;111,7;e;105,3;e;107,6;e;104,2;e;106,9;e;106,2;e;108,6;e;106,4;e;107,1;e;105,1;e;107,7;e;104,7;e
		;Dezember;110,8;e;110,2;e;107,4;e;107,0;e;111,7;e;105,5;e;107,7;e;104,3;e;107,0;e;106,3;e;108,6;e;106,4;e;107,4;e;105,2;e;107,8;e;104,8;e
		2025;Januar;111,6;e;110,2;e;107,6;e;107,0;e;112,0;e;105,6;e;108,0;e;104,3;e;107,4;e;106,5;e;109,4;e;106,7;e;107,5;e;105,2;e;108,1;e;104,8;e
		;Februar;111,7;e;110,3;e;108,0;e;107,7;e;112,0;e;106,3;e;108,5;e;104,4;e;107,6;e;106,8;e;109,5;e;106,9;e;107,6;e;105,3;e;108,3;e;104,9;e
		;März;111,8;e;110,4;e;108,8;e;107,7;e;112,9;e;106,3;e;109,3;e;104,4;e;107,8;e;106,8;e;109,5;e;107,0;e;108,8;e;106,9;e;108,5;e;104,9;e
		;April;113,0;e;110,8;e;108,9;e;107,8;e;112,9;e;106,8;e;109,4;e;104,5;e;108,0;e;107,2;e;109,7;e;107,1;e;108,8;e;107,0;e;108,6;e;105,0;e
		;Mai;112,7;e;110,9;e;109,1;e;107,8;e;114,7;e;106,9;e;109,6;e;104,8;e;108,1;e;107,4;e;109,8;e;107,1;e;108,9;e;107,1;e;108,7;e;105,2;e
		;Juni;112,9;e;111,0;e;109,1;e;107,9;e;114,9;e;107,0;e;109,6;e;104,8;e;108,3;e;107,5;e;109,9;e;107,1;e;109,0;e;107,1;e;108,8;e;105,3;e
		;Juli;113,0;e;111,3;e;110,7;e;107,7;e;114,9;e;107,2;e;109,8;e;104,9;e;108,3;e;107,8;e;110,0;e;107,3;e;109,4;e;107,1;e;108,9;e;105,4;e
		;August;113,1;e;111,4;e;110,8;e;107,8;e;114,9;e;107,2;e;110,0;e;104,9;e;108,4;e;107,9;e;110,2;e;107,7;e;109,6;e;107,3;e;109,0;e;105,4;e
		;September;113,2;e;111,4;e;110,8;e;107,9;e;115,4;e;107,3;e;110,0;e;104,9;e;108,7;e;108,0;e;110,2;e;108,0;e;109,7;e;107,3;e;109,6;e;105,7;e
		;Oktober;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;
		;November;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;
		;Dezember;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;;...;
		__________
		© Statistisches Bundesamt (Destatis), 2025
		Stand: 04.11.2025 / 16:43:46

00_original_index/03_data/data_destatis/61262-0004_Preisindizes_Wohneigentum_D_q.csv

0 → 100644

+20 −0

Original line number	Diff line number	Diff line
		Tabelle: 61262-0004
		Preisindizes für selbst genutztes Wohneigentum: Deutschland,;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		Quartale;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		Preisindizes für Wohnimmobilien;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		Deutschland;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
		;;2010;;;;;;;;2011;;;;;;;;2012;;;;;;;;2013;;;;;;;;2014;;;;;;;;2015;;;;;;;;2016;;;;;;;;2017;;;;;;;;2018;;;;;;;;2019;;;;;;;;2020;;;;;;;;2021;;;;;;;;2022;;;;;;;;2023;;;;;;;;2024;;;;;;;;2025;;;;;;;
		;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;;1. Quartal;;2. Quartal;;3. Quartal;;4. Quartal;
		Preisindex für selbst genutztes Wohneigentum;2015=100;87,6;e;88,2;e;88,6;e;88,8;e;90,0;e;90,7;e;91,3;e;91,7;e;92,8;e;93,4;e;93,9;e;94,3;e;95,0;e;95,6;e;96,0;e;96,2;e;97,2;e;97,6;e;98,0;e;98,2;e;99,3;e;99,7;e;100,3;e;100,7;e;101,7;e;102,6;e;103,2;e;103,8;e;105,0;e;105,9;e;106,9;e;107,7;e;109,5;e;110,5;r;112,1;e;112,7;r;114,4;e;115,6;e;116,6;e;117,7;r;119,0;e;120,0;e;118,5;e;119,7;e;123,7;e;128,1;e;132,4;e;135,5;e;140,4;e;148,0;e;151,3;e;153,6;e;156,8;e;157,6;e;157,9;e;157,9;e;159,6;e;160,9;e;162,3;e;162,9;e;165,1;p;166,4;p;...;;...;
		Erwerb von Wohneigentum;2015=100;87,6;e;88,2;e;88,6;e;88,9;e;90,0;e;90,8;e;91,4;e;91,8;e;92,9;e;93,4;e;93,9;e;94,3;e;95,0;e;95,6;e;96,0;e;96,2;e;97,2;e;97,5;e;98,0;e;98,2;e;99,3;e;99,7;e;100,3;e;100,7;e;101,7;e;102,7;e;103,3;e;103,9;e;105,0;e;106,0;e;107,0;e;107,8;r;109,6;r;110,7;e;112,3;e;113,0;e;114,5;e;115,7;e;116,8;e;117,9;r;119,1;e;120,1;e;118,7;e;119,9;e;123,9;e;128,4;e;132,8;e;136,0;e;140,8;e;148,6;e;151,8;e;154,0;e;156,6;e;157,3;e;157,5;e;157,5;e;158,9;e;160,2;e;161,6;e;162,0;e;164,2;p;165,5;p;...;;...;
		Wohneigentum;2015=100;88,6;e;89,2;e;89,7;e;89,9;e;91,0;e;91,8;e;92,5;e;92,7;e;93,6;e;94,1;e;94,7;e;95,1;e;95,6;e;96,2;e;96,5;e;96,7;e;97,6;e;97,9;e;98,4;e;98,6;e;99,3;e;99,7;e;100,3;e;100,7;e;101,6;e;102,5;e;103,1;e;103,6;e;104,7;e;105,7;e;106,7;e;107,5;e;109,3;e;110,3;e;111,9;e;112,5;e;114,2;e;115,2;e;116,2;e;117,3;e;118,4;e;119,3;e;117,5;e;118,6;e;122,7;e;127,1;e;131,4;e;134,4;e;139,2;e;147,5;e;151,1;e;154,0;e;157,1;e;158,0;e;158,5;e;158,7;e;160,3;e;161,5;e;162,9;e;163,3;e;165,6;p;166,8;p;...;;...;
		Schlüsselfertiges Bauen;2015=100;82,6;e;82,6;e;84,8;e;84,4;e;85,4;e;88,1;e;89,5;e;88,3;e;89,1;e;89,7;e;90,6;e;91,8;e;90,9;e;92,0;e;91,5;e;91,2;e;92,3;e;94,3;e;96,1;e;96,5;e;97,5;e;99,1;e;100,7;e;102,7;e;104,2;e;106,2;e;107,5;e;109,5;e;109,3;e;110,5;e;112,9;e;114,4;e;116,5;e;118,1;e;121,0;e;120,0;e;119,5;e;121,4;e;123,3;e;127,2;e;126,0;e;129,1;e;131,2;e;135,4;e;133,3;e;138,1;e;142,0;e;146,7;e;145,0;e;149,1;e;150,8;e;149,7;e;146,4;e;144,3;e;145,4;e;143,7;e;143,1;e;145,3;e;147,5;e;147,0;e;149,8;p;150,1;p;...;;...;
		Eigenbau, Fertigteilbau und Umbau;2015=100;89,2;e;89,9;e;90,2;e;90,5;e;91,6;e;92,2;e;92,8;e;93,1;e;94,1;e;94,6;e;95,1;e;95,4;e;96,1;e;96,6;e;97,0;e;97,3;e;98,1;e;98,3;e;98,7;e;98,9;e;99,6;e;99,8;e;100,2;e;100,4;e;101,2;e;102,0;e;102,5;e;102,8;e;104,1;e;105,0;e;105,8;e;106,5;e;108,3;e;109,2;e;110,6;e;111,5;e;113,5;e;114,4;e;115,2;e;115,9;e;117,4;e;117,9;e;115,6;e;116,1;e;121,1;e;125,5;e;129,8;e;132,6;e;138,3;e;147,1;e;151,0;e;154,5;e;158,6;e;160,0;e;160,4;e;160,9;e;162,9;e;163,9;e;165,1;e;165,7;e;168,0;p;169,3;p;...;;...;
		Erwerbsnebenkosten;2015=100;72,1;e;72,7;e;72,6;e;72,4;e;74,6;e;75,3;e;75,1;e;78,5;e;81,9;e;82,8;e;83,6;e;84,2;e;86,3;e;87,2;e;88,6;e;88,6;e;91,8;e;92,9;e;93,3;e;93,3;e;98,4;e;99,8;e;100,5;e;101,4;e;103,0;e;105,0;e;106,1;e;107,2;e;108,7;e;110,0;e;111,1;r;112,5;r;114,3;e;115,8;r;117,3;r;118,2;r;118,5;r;121,4;r;123,4;r;126,1;r;127,6;e;129,6;e;132,7;e;136,0;e;138,0;e;142,9;e;149,3;e;154,6;e;159,6;e;161,4;e;160,5;e;152,7;e;150,3;e;148,6;e;145,3;e;142,2;e;142,3;e;144,5;e;145,5;e;146,4;e;147,2;p;149,4;p;...;;...;
		Besitz von Wohneigentum;2015=100;87,4;e;87,7;e;88,0;e;88,3;e;89,5;e;90,1;e;90,6;e;91,0;e;92,6;e;93,1;e;93,5;e;93,9;e;95,2;e;95,8;e;96,2;e;96,5;e;97,4;e;97,8;e;98,2;e;98,5;e;99,5;e;99,8;e;100,2;e;100,5;e;101,7;e;102,3;e;102,7;e;103,0;e;104,3;r;105,0;e;106,0;e;106,5;r;108,1;e;109,0;e;110,1;r;110,9;e;113,5;r;114,4;r;115,1;r;115,7;r;118,1;e;118,9;e;116,9;e;117,4;e;122,0;e;125,4;e;128,6;e;131,3;e;137,3;e;143,1;e;146,8;e;150,4;e;157,7;e;159,8;e;160,9;e;161,5;e;164,8;e;166,1;e;167,9;e;169,1;e;171,6;p;173,3;p;...;;...;
		Instandhaltung;2015=100;87,1;e;87,5;e;88,0;e;88,3;e;89,4;e;90,1;e;90,7;e;91,2;e;92,3;e;92,9;e;93,3;e;93,8;e;94,8;e;95,5;e;95,9;e;96,2;e;97,1;e;97,6;e;98,1;e;98,4;e;99,4;e;99,8;e;100,2;e;100,5;e;101,6;e;102,2;e;102,7;e;103,0;e;104,4;e;105,2;e;106,1;e;106,6;e;108,3;e;109,3;e;110,4;e;111,1;e;113,0;e;114,0;e;114,9;e;115,6;e;117,5;e;118,1;e;115,6;e;116,2;e;121,2;e;125,4;e;129,4;e;132,7;e;138,9;e;145,7;e;150,3;e;154,5;e;159,0;e;161,4;e;162,7;e;163,7;e;166,1;e;167,4;e;168,7;e;169,6;e;172,2;p;173,8;p;...;;...;
		Versicherungen;2015=100;88,7;e;88,7;e;87,9;e;87,9;e;89,7;e;89,7;e;89,7;e;89,7;e;94,7;e;94,7;e;94,7;e;94,7;e;98,3;e;98,3;e;98,3;e;98,3;e;99,2;e;99,2;e;99,2;e;99,2;e;100,0;e;100,0;e;100,0;e;100,0;e;102,6;e;102,6;e;102,7;e;103,0;e;104,4;r;104,4;r;106,0;r;106,4;r;107,8;r;108,4;r;109,9;r;111,4;r;118,2;r;118,4;r;118,4;r;118,4;r;124,1;r;126,0;r;126,0;r;126,0;r;129,9;e;129,9;e;129,3;e;129,1;e;136,1;e;138,6;e;138,8;e;140,3;e;163,1;e;163,1;e;163,4;e;162,6;e;171,1;e;172,3;e;177,1;e;180,5;e;182,4;p;184,8;p;...;;...;
		Hausverwaltung;2015=100;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;-;;104,1;e;104,5;e;104,8;e;105,0;e;105,6;e;105,9;e;107,4;e;107,6;e;108,5;e;109,4;e;109,7;e;110,4;e;112,2;e;113,1;e;112,4;e;112,4;e;113,2;e;113,5;e;113,5;e;114,1;e;115,2;e;116,4;e;117,2;e;118,4;e;120,8;e;123,6;e;124,5;e;124,1;e;125,8;e;126,9;e;127,4;e;127,6;e;129,9;p;131,2;p;...;;...;
		__________
		© Statistisches Bundesamt (Destatis), 2025
		Stand: 04.11.2025 / 13:50:00

00_original_index/03_data/data_destatis/disp_income_y_bw.xlsx

0 → 100644

+166 KiB

File added.

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00_original_index/03_data/data_destatis/genesis_bw/31111_0001_real_income_bw_q.csv

0 → 100644

+155 −0

Original line number	Diff line number	Diff line
		Tabelle: 62361_0006
		Reallohnindex (Indizes);;;;;;;
		Verdiensterhebung;;;;;;;
		Baden-Württemberg;;;;;;;
		Land- und Forstwirtschaft, Fischerei, Produzierendes Gewerbe und Dienstleistungsbereich;;;;;;;
		;;Beschäftigungsumfang;Beschäftigungsumfang;Beschäftigungsumfang;Beschäftigungsumfang;Beschäftigungsumfang;Beschäftigungsumfang
		;;Alle Arbeitnehmenden;Alle Arbeitnehmenden;Alle Arbeitnehmenden;Vollzeitbeschäftigte;Vollzeitbeschäftigte;Vollzeitbeschäftigte
		;;Reallohnindex;Nominallohnindex;Verbraucherpreisindex;Reallohnindex;Nominallohnindex;Verbraucherpreisindex
		;;2022 = 100;2022 = 100;2020 = 100;2022 = 100;2022 = 100;2020 = 100
		2007;Insgesamt;96,5;74,5;84,6;97,2;75,1;84,6
		2007;Erstes Quartal;91,5;70,0;83,7;92,2;70,5;83,7
		2007;Zweites Quartal;98,5;75,9;84,4;99,6;76,8;84,4
		2007;Drittes Quartal;91,6;70,9;84,8;92,2;71,4;84,8
		2007;Viertes Quartal;103,8;81,0;85,4;104,5;81,5;85,4
		2008;Insgesamt;96,8;76,7;86,8;97,5;77,3;86,8
		2008;Erstes Quartal;91,8;72,1;86,0;92,5;72,7;86,0
		2008;Zweites Quartal;99,4;78,7;86,7;100,6;79,7;86,7
		2008;Drittes Quartal;91,0;72,6;87,4;91,6;73,1;87,4
		2008;Viertes Quartal;104,7;83,2;87,0;105,3;83,7;87,0
		2009;Insgesamt;94,9;75,4;87,1;95,4;75,8;87,1
		2009;Erstes Quartal;91,0;72,1;86,8;91,5;72,5;86,8
		2009;Zweites Quartal;96,0;76,2;86,9;96,8;76,8;86,9
		2009;Drittes Quartal;90,2;71,8;87,2;90,5;72,1;87,2
		2009;Viertes Quartal;102,4;81,6;87,3;102,6;81,8;87,3
		2010;Insgesamt;97,2;78,1;88,0;97,8;78,6;88,0
		2010;Erstes Quartal;91,5;73,1;87,5;91,9;73,4;87,5
		2010;Zweites Quartal;98,8;79,3;87,9;99,9;80,2;87,9
		2010;Drittes Quartal;92,5;74,4;88,1;92,9;74,7;88,1
		2010;Viertes Quartal;105,7;85,4;88,5;106,3;85,9;88,5
		2011;Insgesamt;99,1;81,3;89,8;99,9;81,9;89,8
		2011;Erstes Quartal;94,1;76,6;89,1;94,7;77,1;89,1
		2011;Zweites Quartal;102,3;83,8;89,7;103,7;85,0;89,7
		2011;Drittes Quartal;93,4;76,8;90,0;94,0;77,3;90,0
		2011;Viertes Quartal;106,4;87,8;90,4;107,0;88,3;90,4
		2012;Insgesamt;100,5;83,9;91,4;101,2;84,5;91,4
		2012;Erstes Quartal;94,8;78,8;91,0;95,6;79,5;91,0
		2012;Zweites Quartal;104,0;86,6;91,2;105,4;87,8;91,2
		2012;Drittes Quartal;95,0;79,5;91,6;95,5;79,9;91,6
		2012;Viertes Quartal;107,8;90,5;91,9;108,2;90,8;91,9
		2013;Insgesamt;99,8;84,4;92,6;100,5;85,0;92,6
		2013;Erstes Quartal;94,7;79,7;92,1;95,3;80,2;92,1
		2013;Zweites Quartal;102,4;86,4;92,4;103,6;87,4;92,4
		2013;Drittes Quartal;94,5;80,2;93,0;94,8;80,5;93,0
		2013;Viertes Quartal;107,5;91,4;93,1;107,9;91,7;93,1
		2014;Insgesamt;101,4;86,5;93,4;102,0;87,0;93,4
		2014;Erstes Quartal;96,3;82,0;93,2;96,9;82,5;93,2
		2014;Zweites Quartal;104,7;89,3;93,4;106,0;90,4;93,4
		2014;Drittes Quartal;95,4;81,6;93,7;95,7;81,9;93,7
		2014;Viertes Quartal;108,8;92,9;93,5;109,1;93,1;93,5
		2015;Insgesamt;103,1;88,5;94,0;103,7;89,0;94,0
		2015;Erstes Quartal;97,6;83,0;93,2;98,0;83,4;93,2
		2015;Zweites Quartal;106,6;91,8;94,3;108,0;93,0;94,3
		2015;Drittes Quartal;96,9;83,6;94,5;97,0;83,7;94,5
		2015;Viertes Quartal;111,5;95,7;94,0;111,6;95,8;94,0
		2016;Insgesamt;104,8;90,4;94,5;105,2;90,8;94,5
		2016;Erstes Quartal;99,8;85,2;93,5;100,4;85,7;93,5
		2016;Zweites Quartal;108,3;93,5;94,5;109,5;94,5;94,5
		2016;Drittes Quartal;98,1;85,1;95,0;98,4;85,3;95,0
		2016;Viertes Quartal;112,7;97,8;95,0;112,7;97,8;95,0
		2017;Insgesamt;105,6;92,6;96,0;106,1;93,0;96,0
		2017;Erstes Quartal;100,9;87,5;95,0;101,2;87,8;95,0
		2017;Zweites Quartal;109,6;96,0;95,9;110,9;97,1;95,9
		2017;Drittes Quartal;98,6;87,0;96,6;98,7;87,1;96,6
		2017;Viertes Quartal;113,4;99,9;96,5;113,3;99,8;96,5
		2018;Insgesamt;106,7;95,4;97,9;107,2;95,8;97,9
		2018;Erstes Quartal;101,9;89,8;96,5;102,3;90,1;96,5
		2018;Zweites Quartal;110,5;98,6;97,7;111,8;99,8;97,7
		2018;Drittes Quartal;100,0;90,1;98,6;100,0;90,1;98,6
		2018;Viertes Quartal;114,4;103,1;98,7;114,3;103,0;98,7
		2019;Insgesamt;107,9;97,9;99,4;108,1;98,1;99,4
		2019;Erstes Quartal;102,8;92,0;98,0;103,2;92,3;98,0
		2019;Zweites Quartal;110,7;100,6;99,5;111,7;101,5;99,5
		2019;Drittes Quartal;103,3;94,4;100,1;103,5;94,6;100,1
		2019;Viertes Quartal;114,5;104,4;99,8;114,1;104,0;99,8
		2020;Insgesamt;104,2;95,1;100,0;103,9;94,9;100,0
		2020;Erstes Quartal;101,6;92,7;99,9;101,5;92,6;99,9
		2020;Zweites Quartal;102,8;94,1;100,3;103,1;94,4;100,3
		2020;Drittes Quartal;99,3;90,5;99,8;98,9;90,2;99,8
		2020;Viertes Quartal;112,9;103,1;100,0;112,2;102,5;100,0
		2021;Insgesamt;105,0;98,7;103,0;105,0;98,7;103,0
		2021;Erstes Quartal;99,0;91,9;101,6;99,2;92,0;101,6
		2021;Zweites Quartal;107,4;100,7;102,6;108,2;101,4;102,6
		2021;Drittes Quartal;100,5;94,9;103,4;100,5;94,9;103,4
		2021;Viertes Quartal;112,4;107,1;104,3;111,9;106,6;104,3
		2022;Insgesamt;100,0;100,0;109,5;100,0;100,0;109,5
		2022;Erstes Quartal;98,7;95,5;105,9;98,7;95,5;105,9
		2022;Zweites Quartal;102,2;101,7;109,0;102,9;102,4;109,0
		2022;Drittes Quartal;94,3;95,0;110,3;94,2;94,9;110,3
		2022;Viertes Quartal;104,6;107,8;112,9;104,1;107,3;112,9
		2023;Insgesamt;99,9;106,2;116,4;100,0;106,3;116,4
		2023;Erstes Quartal;96,2;100,8;114,7;96,6;101,2;114,7
		2023;Zweites Quartal;102,5;109,0;116,5;103,2;109,8;116,5
		2023;Drittes Quartal;94,4;101,1;117,3;94,3;101,0;117,3
		2023;Viertes Quartal;106,2;113,7;117,3;105,7;113,2;117,3
		2024;Insgesamt;102,6;111,5;119,0;103,0;111,9;119,0
		2024;Erstes Quartal;98,5;106,0;117,9;98,9;106,5;117,9
		2024;Zweites Quartal;105,6;114,6;118,9;106,6;115,7;118,9
		2024;Drittes Quartal;97,3;105,9;119,2;97,3;106,0;119,2
		2024;Viertes Quartal;109,1;119,6;120,0;108,9;119,3;120,0
		2025;Insgesamt;...;...;...;...;...;...
		2025;Erstes Quartal;99,8;109,9;120,6;100,2;110,4;120,6
		2025;Zweites Quartal;106,2;117,9;121,6;107,3;119,2;121,6
		2025;Drittes Quartal;...;...;...;...;...;...
		2025;Viertes Quartal;...;...;...;...;...;...
		__________
		"bis 2021 WZ B-S, ab 2022 WZ A-S

		Alle Arbeitnehmenden = Vollzeit-, teilzeit- und geringfügig
		Beschäftigte

		Durch die Umbasierung des Verbraucherpreisindex auf das
		Basisjahr 2020=100 sowie die Erhebungsumstellung im
		Verdienstebereich ab 2022 ergeben sich Abweichungen zu den
		bisher veröffentlichten Werten.

		Anstieg der Kurzarbeit als Folge der Corona-Pandemie in den
		Jahren 2020 und 2021. Kurzarbeitergeld (KuG) wird in der
		Verdiensterhebung nicht erfasst.
		Weitreichende Erhebungsumstellung im Verdienstbereich,
		inhaltliche Zusammenführung der vierteljährlichen
		Verdiensterhebung (VVE) und der vierjährlichen
		Verdienststrukturerhebung (VSE) zur monatlichen
		Verdiensterhebung (VE) ab dem Jahr 2022. Die VE löste die
		VVE als Datenquelle für die Berechnung der Verdienstindizes
		zum Januar 2022 ab. Aufgrund unterschiedlicher
		Erhebungskonzepte sind die Daten der VE ab dem Jahr 2022
		nur eingeschränkt mit den Daten der Vorjahre aus der VVE
		vergleichbar und es gibt einen gewissen Bruch in den
		Zeitreihen der Verdienstindizes, der methodisch nicht
		vollständig herausgerechnet werden kann. So werden seit
		2022 z.B. auch Kleinstbetriebe erfasst und zusätzlich zu
		Vollzeit-, Teilzeit- und geringfügig Beschäftigten alle
		weiteren Beschäftigungsarten wie Auszubildende,
		Altersteilzeitbeschäftigte u.a. abgebildet. Zusätzlich zu
		den Wirtschaftsbereichen B bis S (Produzierendes Gewerbe
		und Dienstleistungsbereich) wird nun außerdem auch der
		Wirtschaftsabschnitt A (Landwirtschaft) erhoben (WZ 2008).
		Die Verdienstindizes und deren Veränderungsraten ab dem
		Berichtsjahr 2023 ermöglichen folglich eine umfassendere
		Abdeckung der Gesamtwirtschaft als zuvor. Um eine
		Darstellung längerfristiger Zeitreihen zur
		Verdienstentwicklung zu gewährleisten, wurden neue und alte
		Indexreihen rechnerisch verknüpft. Aufgrund der
		Neukonzeption der Verdiensterhebung und der
		Erhebungsumstellung zum Januar 2022 wurden nach Abschluss
		des Berichtsjahres 2022 alle Verdienstindizes für die
		Berichtszeiträume 2022 vom vorübergehenden Basiszeitraum 1.
		Quartal 2022 = 100 auf den Basiszeitraum Jahr 2022 = 100
		final umgestellt und neu berechnet (= Revision). Weiter
		zurückliegende Werte vor 2022 aus der VVE sind rein
		rechnerisch umbasiert. Veränderungsraten für zurückliegende
		Zeiträume vor 2022 können rundungsbedingt von den
		bisherigen Veröffentlichungen abweichen."
		© Statistisches Landesamt Baden-Württemberg, Fellbach 2025
		Stand: 06.11.2025 / 16:22:59

00_original_index/03_data/data_destatis/genesis_bw/61261_0003_priceindex_housing_bw_q.csv

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Original line number	Diff line number	Diff line
		Tabelle: 61261_0003
		Preisindizes für Wohngebäude mit Instandhaltung;;;;;;
		Preisindizes für die Bauwirtschaft;;;;;;
		Baden-Württemberg;;;;;;
		;Baupreisindizes;Baupreisindizes;Baupreisindizes;Baupreisindizes;Baupreisindizes;Baupreisindizes
		;Wohngebäude;Wohngebäude;Wohngebäude ohne Schönheitsreparaturen;Wohngebäude ohne Schönheitsreparaturen;Schönheitsreparaturen in einer Wohnung;Schönheitsreparaturen in einer Wohnung
		;2021 = 100;Veränderung zum Vorjahr (%);2021 = 100;Veränderung zum Vorjahr (%);2021 = 100;Veränderung zum Vorjahr (%)
		1949;8,0;.;-;.;-;.
		1950;7,3;-8,8;-;.;-;.
		1951;8,8;+20,5;-;.;-;.
		1952;9,6;+9,1;-;.;-;.
		1953;9,4;-2,1;-;.;-;.
		1954;9,5;+1,1;-;.;-;.
		1955;10,1;+6,3;-;.;-;.
		1956;10,6;+5,0;-;.;-;.
		1957;10,9;+2,8;-;.;-;.
		1958;11,3;+3,7;-;.;-;.
		1959;11,9;+5,3;-;.;-;.
		1960;13,0;+9,2;-;.;-;.
		1961;14,3;+10,0;-;.;-;.
		1962;15,5;+8,4;-;.;-;.
		1963;16,3;+5,2;-;.;-;.
		1964;17,1;+4,9;-;.;-;.
		1965;18,1;+5,8;-;.;-;.
		1966;18,3;+1,1;-;.;-;.
		1967;17,4;-4,9;-;.;-;.
		1968;17,9;+2,9;-;.;-;.
		1969;19,1;+6,7;-;.;-;.
		1970;22,1;+15,7;-;.;-;.
		1971;24,2;+9,5;-;.;-;.
		1972;25,7;+6,2;-;.;-;.
		1973;27,6;+7,4;-;.;-;.
		1974;28,9;+4,7;-;.;-;.
		1975;29,1;+0,7;-;.;-;.
		1976;29,9;+2,7;-;.;-;.
		1977;31,2;+4,3;-;.;-;.
		1978;33,4;+7,1;-;.;-;.
		1979;36,6;+9,6;-;.;-;.
		1980;40,6;+10,9;-;.;-;.
		1981;42,6;+4,9;-;.;-;.
		1982;42,8;+0,5;-;.;-;.
		1983;43,4;+1,4;-;.;-;.
		1984;44,6;+2,8;-;.;-;.
		1985;44,5;-0,2;-;.;-;.
		1986;45,0;+1,1;-;.;-;.
		1987;46,0;+2,2;-;.;-;.
		1988;47,0;+2,2;-;.;-;.
		1989;48,9;+4,0;-;.;-;.
		1990;52,2;+6,7;-;.;-;.
		1991;55,8;+6,9;-;.;-;.
		1992;58,5;+4,8;-;.;-;.
		1993;60,0;+2,6;-;.;-;.
		1994;60,3;+0,5;-;.;-;.
		1995;60,9;+1,0;-;.;-;.
		1996;59,9;-1,6;-;.;-;.
		1997;59,1;-1,3;-;.;-;.
		1998;59,3;+0,3;-;.;-;.
		1999;59,5;+0,3;-;.;-;.
		2000;60,2;+1,2;-;.;-;.
		2001;60,7;+0,8;-;.;-;.
		2002;60,9;+0,3;-;.;-;.
		2003;60,5;-0,7;-;.;-;.
		2004;61,2;+1,2;-;.;-;.
		2005;61,7;+0,8;-;.;-;.
		2006;63,1;+2,3;-;.;-;.
		2007;67,6;+7,1;-;.;-;.
		2008;69,6;+3,0;-;.;-;.
		2009;70,0;+0,6;-;.;-;.
		2010;70,6;+0,9;-;.;-;.
		2011;72,7;+3,0;-;.;-;.
		2012;74,5;+2,5;-;.;-;.
		2013;75,9;+1,9;-;.;-;.
		2014;77,4;+2,0;76,6;.;81,6;.
		2015;79,1;+2,2;78,6;+2,6;83,4;+2,2
		2016;80,9;+2,3;80,9;+2,9;85,4;+2,4
		2017;83,4;+3,1;83,5;+3,2;87,7;+2,7
		2018;87,4;+4,8;86,7;+3,8;90,0;+2,6
		2019;90,7;+3,8;89,5;+3,2;92,7;+3,0
		2020;91,7;+1,1;93,2;+4,1;94,8;+2,3
		2021;100,0;+9,1;100,0;+7,3;100,0;+5,5
		2022;114,4;+14,4;114,1;+14,1;108,3;+8,3
		2023;122,8;+7,3;126,2;+10,6;117,9;+8,9
		2024;126,9;+3,3;133,3;+5,6;124,8;+5,9
		__________
		© Statistisches Landesamt Baden-Württemberg, Fellbach 2025
		Stand: 06.11.2025 / 15:34:15

00_original_index/03_data/data_given/.DS_Store

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00_original_index/03_data/data_given/.gitkeep

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+0 −0

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00_original_index/03_data/data_given/bb_houseprice_income_ratios_D_q.csv

0 → 100644

+90 −0

Original line number	Diff line number	Diff line
		date,year,quarter,annuity_income,houseprice_income,houseprice_rent
		2003q1,2003,1,117.8,101,101.2
		2003q2,2003,2,114.4,101.1,99.3
		2003q3,2003,3,111.3,99.8,101.4
		2003q4,2003,4,115.4,100.6,101.6
		2004q1,2004,1,114.4,99.7,100.7
		2004q2,2004,2,113.5,100.5,101
		2004q3,2004,3,113.4,100,101.7
		2004q4,2004,4,110.9,100.2,101.4
		2005q1,2005,1,111,103.1,105.3
		2005q2,2005,2,107.4,101.6,105.3
		2005q3,2005,3,104.9,102,103.5
		2005q4,2005,4,103.5,100.4,104.7
		2006q1,2006,1,106.1,100.8,103.4
		2006q2,2006,2,109.9,101.5,103.2
		2006q3,2006,3,112.2,102,104.4
		2006q4,2006,4,108.4,99.3,102.4
		2007q1,2007,1,109.8,99.5,101.1
		2007q2,2007,2,111.1,98.8,101.3
		2007q3,2007,3,114.8,99.09999999999999,101.5
		2007q4,2007,4,112.7,98.2,102.1
		2008q1,2008,1,113.8,100.3,101.9
		2008q2,2008,2,114.3,100.6,101.2
		2008q3,2008,3,116.4,99.8,98.09999999999999
		2008q4,2008,4,117.3,102.9,99.2
		2009q1,2009,1,111.1,102.6,100.4
		2009q2,2009,2,106.3,100.4,101.4
		2009q3,2009,3,107.3,100.7,101.2
		2009q4,2009,4,106,100.6,102.3
		2010q1,2010,1,103.8,100.2,100.3
		2010q2,2010,2,101.2,100,99.40000000000001
		2010q3,2010,3,98.40000000000001,100.1,99.40000000000001
		2010q4,2010,4,96.59999999999999,99.7,101
		2011q1,2011,1,101.1,99.7,101.9
		2011q2,2011,2,103,99,102.5
		2011q3,2011,3,100.7,99.5,102.3
		2011q4,2011,4,95,99,102
		2012q1,2012,1,92.90000000000001,99.3,102
		2012q2,2012,2,91.7,100.7,103.4
		2012q3,2012,3,88.5,100.6,103.8
		2012q4,2012,4,88.5,101.8,103.8
		2013q1,2013,1,88.7,102.7,103.5
		2013q2,2013,2,87.5,102.7,104.9
		2013q3,2013,3,88.90000000000001,103.1,103.4
		2013q4,2013,4,90.59999999999999,103.1,104.1
		2014q1,2014,1,89.59999999999999,103.1,103.2
		2014q2,2014,2,88.3,104,102.1
		2014q3,2014,3,86.09999999999999,104.7,101.4
		2014q4,2014,4,83.5,104.9,102.1
		2015q1,2015,1,82.8,107.7,101.9
		2015q2,2015,2,79.59999999999999,106.4,101.8
		2015q3,2015,3,82.90000000000001,107.6,102.1
		2015q4,2015,4,83.09999999999999,107.9,103.3
		2016q1,2016,1,82.5,109,103.6
		2016q2,2016,2,82.2,110.8,104.6
		2016q3,2016,3,81.5,111.5,104.2
		2016q4,2016,4,80.8,111.5,106.9
		2017q1,2017,1,83.3,112.2,106.2
		2017q2,2017,2,84.40000000000001,112.9,108.2
		2017q3,2017,3,86,115.1,108.6
		2017q4,2017,4,86,115.2,110.7
		2018q1,2018,1,87.09999999999999,116.4,109.1
		2018q2,2018,2,88.8,117.3,108.9
		2018q3,2018,3,90.40000000000001,120.4,110.4
		2018q4,2018,4,90.5,120.5,110.2
		2019q1,2019,1,90.7,122,110
		2019q2,2019,2,89.5,123.3,110.8
		2019q3,2019,3,87.5,124.4,112.3
		2019q4,2019,4,86.59999999999999,125.6,111.6
		2020q1,2020,1,88.2,127.8,112.1
		2020q2,2020,2,91.8,132.7,113.5
		2020q3,2020,3,90.90000000000001,132.3,115.8
		2020q4,2020,4,91.3,134,117.6
		2021q1,2021,1,94.8,139.2,120.4
		2021q2,2021,2,97.40000000000001,141.7,123.6
		2021q3,2021,3,102.2,148.2,125.1
		2021q4,2021,4,102.2,147.7,127.7
		2022q1,2022,1,104.9,147.1,130.5
		2022q2,2022,2,118.2,148.9,129.9
		2022q3,2022,3,126.8,145.7,128.7
		2022q4,2022,4,132.7,141.9,124
		2023q1,2023,1,131.5,137,118.4
		2023q2,2023,2,129,132.3,117.3
		2023q3,2023,3,128.2,129.7,113.6
		2023q4,2023,4,126.5,127.1,109.7
		2024q1,2024,1,120.3,125.4,106.9
		2024q2,2024,2,120,124.4,106.2
		2024q3,2024,3,119.5,124.4,106.5
		2024q4,2024,4,116.5,124.4,106.1
		2025q1,2025,1,116.3,124.5,106

00_original_index/03_data/data_given/bb_interest_rates_D_m.csv

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Original line number	Diff line number	Diff line
		date,year,month,interest_existing_1,interest_existing_1_5,interest_existing_5,interest_new_1,interest_new_1_5,interest_new_5_10,interest_new_10,interest_new_avg
		2003m1,2003,1,5.86,5.46,5.96,5.45,4.94,5.39,5.38,5.32
		2003m2,2003,2,5.85,5.45,5.96,5.27,4.76,5.19,5.19,5.13
		2003m3,2003,3,5.83,5.41,5.95,5.27,4.6,5.05,5.12,5.02
		2003m4,2003,4,5.77,5.36,5.94,5.23,4.48,5.03,5.17,4.98
		2003m5,2003,5,5.7,5.32,5.93,5.17,4.46,4.97,5.03,4.9
		2003m6,2003,6,5.72,5.27,5.91,5,4.37,4.8,4.85,4.76
		2003m7,2003,7,5.53,5.2,5.88,4.58,4.16,4.7,4.85,4.6
		2003m8,2003,8,5.54,5.15,5.87,4.73,4.25,4.81,4.91,4.71
		2003m9,2003,9,5.48,5.11,5.85,4.63,4.52,4.96,5.03,4.84
		2003m10,2003,10,5.5,5.07,5.83,4.44,4.48,5,5.08,4.81
		2003m11,2003,11,5.44,5.04,5.82,4.68,4.62,5.07,5.12,4.93
		2003m12,2003,12,5.55,5.01,5.79,4.63,4.75,5.14,5.19,4.98
		2004m1,2004,1,5.43,4.97,5.78,4.57,4.65,5.15,5.19,4.94
		2004m2,2004,2,5.38,4.96,5.77,4.56,4.61,5.06,5.03,4.86
		2004m3,2004,3,5.32,4.9,5.75,4.43,4.48,4.99,4.98,4.77
		2004m4,2004,4,5.29,4.87,5.74,4.26,4.32,4.91,4.95,4.66
		2004m5,2004,5,5.27,4.84,5.73,4.49,4.37,4.91,4.94,4.72
		2004m6,2004,6,5.23,4.83,5.71,4.49,4.32,4.96,5.09,4.75
		2004m7,2004,7,5.24,4.77,5.69,4.26,4.51,4.92,5.11,4.73
		2004m8,2004,8,5.24,4.75,5.68,4.37,4.59,5.04,4.99,4.8
		2004m9,2004,9,5.27,4.72,5.67,4.44,4.53,4.96,4.97,4.77
		2004m10,2004,10,5.14,4.67,5.66,4.3,4.48,4.89,4.88,4.66
		2004m11,2004,11,5.12,4.65,5.65,4.45,4.4,4.78,4.76,4.64
		2004m12,2004,12,5.25,4.63,5.63,4.37,4.29,4.63,4.67,4.53
		2005m1,2005,1,5.2,4.6,5.61,4.37,4.2,4.56,4.62,4.47
		2005m2,2005,2,5.14,4.58,5.6,4.35,4.2,4.51,4.48,4.41
		2005m3,2005,3,5.14,4.56,5.59,4.34,4.13,4.47,4.52,4.4
		2005m4,2005,4,5.07,4.58,5.56,4.28,4.13,4.5,4.58,4.41
		2005m5,2005,5,4.99,4.56,5.54,4.33,4.08,4.39,4.4,4.32
		2005m6,2005,6,4.99,4.53,5.52,4.25,4.01,4.22,4.26,4.2
		2005m7,2005,7,4.93,4.49,5.49,4.15,3.94,4.17,4.23,4.14
		2005m8,2005,8,4.95,4.46,5.47,4.3,3.88,4.1,4.19,4.12
		2005m9,2005,9,4.95,4.4,5.45,4.21,3.95,4.11,4.16,4.11
		2005m10,2005,10,4.88,4.37,5.42,4.22,3.94,4.11,4.18,4.12
		2005m11,2005,11,4.89,4.35,5.4,4.36,4.05,4.14,4.25,4.19
		2005m12,2005,12,5,4.33,5.36,4.44,4.25,4.19,4.32,4.27
		2006m1,2006,1,5.07,4.31,5.34,4.55,4.27,4.29,4.35,4.35
		2006m2,2006,2,5.09,4.31,5.33,4.58,4.32,4.28,4.31,4.34
		2006m3,2006,3,5.17,4.3,5.3,4.71,4.37,4.39,4.39,4.43
		2006m4,2006,4,5.17,4.31,5.28,4.74,4.42,4.45,4.56,4.53
		2006m5,2006,5,5.21,4.31,5.27,4.82,4.58,4.58,4.56,4.61
		2006m6,2006,6,5.29,4.32,5.26,4.91,4.61,4.66,4.63,4.68
		2006m7,2006,7,5.29,4.32,5.25,4.92,4.66,4.67,4.8,4.75
		2006m8,2006,8,5.34,4.32,5.23,5.12,4.8,4.71,4.76,4.8
		2006m9,2006,9,5.39,4.33,5.22,5.1,4.8,4.71,4.69,4.78
		2006m10,2006,10,5.51,4.35,5.21,5.1,4.8,4.65,4.65,4.75
		2006m11,2006,11,5.57,4.36,5.2,5.27,4.84,4.65,4.61,4.76
		2006m12,2006,12,5.53,4.36,5.19,5.23,4.86,4.6,4.56,4.73
		2007m1,2007,1,5.58,4.38,5.17,5.44,4.87,4.64,4.67,4.81
		2007m2,2007,2,5.6,4.39,5.17,5.45,4.98,4.78,4.78,4.91
		2007m3,2007,3,5.64,4.41,5.16,5.46,4.99,4.78,4.76,4.91
		2007m4,2007,4,5.65,4.43,5.14,5.54,4.99,4.8,4.81,4.93
		2007m5,2007,5,5.67,4.44,5.13,5.56,5.06,4.87,4.85,4.98
		2007m6,2007,6,5.7,4.45,5.13,5.64,5.22,5.01,5.03,5.13
		2007m7,2007,7,5.85,4.48,5.12,5.69,5.37,5.14,5.16,5.27
		2007m8,2007,8,5.89,4.5,5.12,5.93,5.36,5.18,5.16,5.31
		2007m9,2007,9,5.94,4.53,5.12,5.86,5.34,5.12,5.08,5.27
		2007m10,2007,10,6.01,4.56,5.11,5.87,5.3,5.08,5.08,5.24
		2007m11,2007,11,6,4.59,5.11,5.91,5.3,5.08,5.02,5.22
		2007m12,2007,12,5.98,4.61,5.1,5.97,5.33,5.03,5.01,5.22
		2008m1,2008,1,6.19,4.62,5.09,5.99,5.17,5.04,5.06,5.23
		2008m2,2008,2,6.16,4.65,5.09,5.8,5.11,4.94,4.89,5.09
		2008m3,2008,3,6.18,4.66,5.08,5.73,5.01,4.89,4.88,5.02
		2008m4,2008,4,6.12,4.67,5.07,5.86,4.99,4.9,4.97,5.07
		2008m5,2008,5,6.18,4.69,5.07,6,5.06,4.96,4.97,5.12
		2008m6,2008,6,6.22,4.71,5.07,6.05,5.24,5.06,5.09,5.24
		2008m7,2008,7,6.21,4.76,5.06,6.18,5.43,5.21,5.28,5.42
		2008m8,2008,8,6.31,4.78,5.06,6.28,5.57,5.27,5.3,5.48
		2008m9,2008,9,6.28,4.82,5.06,6.24,5.5,5.17,5.21,5.39
		2008m10,2008,10,6.31,4.86,5.07,6.34,5.43,5.15,5.12,5.37
		2008m11,2008,11,6.31,4.87,5.06,6.07,5.2,5.03,5.01,5.21
		2008m12,2008,12,6.13,4.84,5.06,5.38,4.84,4.83,4.73,4.9
		2009m1,2009,1,5.81,4.77,5.03,4.97,4.58,4.73,4.77,4.76
		2009m2,2009,2,5.54,4.73,5.02,4.38,4.33,4.58,4.6,4.5
		2009m3,2009,3,5.34,4.65,5.01,4.19,4.12,4.4,4.49,4.34
		2009m4,2009,4,5.06,4.57,4.98,3.86,4.01,4.37,4.54,4.25
		2009m5,2009,5,4.97,4.54,4.97,3.8,3.93,4.35,4.47,4.21
		2009m6,2009,6,4.86,4.49,4.95,3.73,3.88,4.39,4.53,4.23
		2009m7,2009,7,4.64,4.44,4.93,3.56,3.89,4.45,4.54,4.22
		2009m8,2009,8,4.56,4.41,4.92,3.47,3.87,4.46,4.51,4.18
		2009m9,2009,9,4.51,4.38,4.91,3.38,3.81,4.37,4.45,4.14
		2009m10,2009,10,4.37,4.35,4.89,3.28,3.83,4.34,4.41,4.08
		2009m11,2009,11,4.38,4.33,4.88,3.24,3.78,4.35,4.32,4.06
		2009m12,2009,12,4.46,4.28,4.86,3.36,3.76,4.29,4.38,4.05
		2010m1,2010,1,4.37,4.26,4.85,3.2,3.71,4.27,4.49,3.99
		2010m2,2010,2,4.36,4.25,4.84,3.16,3.67,4.22,4.34,3.97
		2010m3,2010,3,4.34,4.22,4.83,3.04,3.56,4.09,4.3,3.88
		2010m4,2010,4,4.19,4.2,4.81,3.08,3.56,4.07,4.36,3.88
		2010m5,2010,5,4.16,4.17,4.8,3.16,3.42,4.01,4.1,3.8
		2010m6,2010,6,4.01,4.13,4.72,3.08,3.37,3.9,3.88,3.68
		2010m7,2010,7,3.9,4.1,4.71,2.89,3.35,3.81,3.77,3.56
		2010m8,2010,8,3.98,4.06,4.7,3.14,3.3,3.81,3.8,3.62
		2010m9,2010,9,4.07,4.03,4.67,3.14,3.25,3.66,3.62,3.52
		2010m10,2010,10,4.01,4,4.66,2.97,3.3,3.58,3.61,3.45
		2010m11,2010,11,3.94,3.97,4.64,3.22,3.26,3.62,3.66,3.53
		2010m12,2010,12,3.88,3.93,4.62,3.23,3.32,3.73,3.79,3.61
		2011m1,2011,1,3.84,3.9,4.61,3.17,3.4,3.87,4.05,3.69
		2011m2,2011,2,3.76,3.87,4.59,3.4,3.55,4.04,4.15,3.9
		2011m3,2011,3,3.81,3.85,4.58,3.36,3.69,4.13,4.26,3.97
		2011m4,2011,4,3.87,3.85,4.57,3.4,3.74,4.2,4.48,4.07
		2011m5,2011,5,3.96,3.83,4.56,3.73,3.86,4.27,4.4,4.15
		2011m6,2011,6,4.05,3.83,4.55,3.68,3.82,4.21,4.31,4.1
		2011m7,2011,7,4.08,3.84,4.55,3.53,3.82,4.16,4.24,4
		2011m8,2011,8,4.09,3.84,4.54,3.78,3.7,4.03,4.1,3.97
		2011m9,2011,9,4.12,3.83,4.53,3.68,3.49,3.8,3.78,3.73
		2011m10,2011,10,4.1,3.81,4.52,3.5,3.36,3.6,3.64,3.56
		2011m11,2011,11,4.1,3.8,4.5,3.66,3.29,3.56,3.54,3.53
		2011m12,2011,12,4.03,3.77,4.49,3.6,3.24,3.53,3.49,3.49
		2012m1,2012,1,3.98,3.74,4.47,3.5,3.18,3.47,3.59,3.46
		2012m2,2012,2,3.94,3.71,4.45,3.56,3.03,3.36,3.49,3.39
		2012m3,2012,3,3.9,3.68,4.43,3.27,2.93,3.27,3.42,3.27
		2012m4,2012,4,3.78,3.62,4.4,3.21,2.96,3.26,3.58,3.3
		2012m5,2012,5,3.7,3.59,4.38,3.19,2.89,3.16,3.34,3.18
		2012m6,2012,6,3.65,3.58,4.36,3.07,2.78,3.02,3.12,3.03
		2012m7,2012,7,3.57,3.53,4.34,3.1,2.78,2.96,3.05,2.99
		2012m8,2012,8,3.5,3.5,4.31,3.04,2.64,2.86,3.03,2.92
		2012m9,2012,9,3.45,3.47,4.3,2.87,2.58,2.84,2.98,2.86
		2012m10,2012,10,3.33,3.42,4.26,2.71,2.59,2.82,3,2.83
		2012m11,2012,11,3.36,3.37,4.24,2.81,2.43,2.8,2.94,2.8
		2012m12,2012,12,3.34,3.33,4.22,2.88,2.51,2.76,2.9,2.79
		2013m1,2013,1,3.24,3.31,4.19,2.62,2.49,2.74,2.96,2.75
		2013m2,2013,2,3.2,3.29,4.17,2.75,2.45,2.74,2.96,2.77
		2013m3,2013,3,3.19,3.26,4.15,2.73,2.5,2.75,2.94,2.78
		2013m4,2013,4,3.2,3.23,4.13,2.77,2.47,2.72,3,2.78
		2013m5,2013,5,3.18,3.2,4.11,2.8,2.39,2.63,2.8,2.68
		2013m6,2013,6,3.18,3.18,4.08,2.72,2.29,2.56,2.75,2.62
		2013m7,2013,7,3.14,3.14,4.05,2.63,2.36,2.67,2.82,2.67
		2013m8,2013,8,3.11,3.12,4.03,2.73,2.46,2.73,2.94,2.76
		2013m9,2013,9,3.13,3.09,4,2.8,2.45,2.82,3.03,2.83
		2013m10,2013,10,3.1,3.06,3.98,2.56,2.53,2.9,3.09,2.84
		2013m11,2013,11,3.05,3.04,3.96,2.75,2.5,2.89,3.06,2.87
		2013m12,2013,12,3.21,3.03,3.94,2.65,2.44,2.84,3.02,2.8
		2014m1,2014,1,3.1,3.02,3.91,2.64,2.51,2.84,3.04,2.81
		2014m2,2014,2,3.16,2.98,3.9,2.9,2.41,2.8,2.99,2.83
		2014m3,2014,3,3.18,2.96,3.88,2.66,2.35,2.72,2.9,2.72
		2014m4,2014,4,3.15,2.94,3.85,2.6,2.36,2.69,2.95,2.71
		2014m5,2014,5,3.14,2.92,3.83,2.6,2.3,2.61,2.79,2.63
		2014m6,2014,6,3.14,2.9,3.81,2.44,2.27,2.53,2.73,2.55
		2014m7,2014,7,3.06,2.87,3.79,2.43,2.18,2.45,2.61,2.46
		2014m8,2014,8,3.06,2.84,3.77,2.53,2.13,2.37,2.5,2.41
		2014m9,2014,9,3.05,2.82,3.74,2.39,2.04,2.28,2.39,2.3
		2014m10,2014,10,3,2.78,3.72,2.33,2.03,2.19,2.35,2.25
		2014m11,2014,11,2.87,2.74,3.7,2.32,1.83,2.11,2.28,2.17
		2014m12,2014,12,2.87,2.71,3.67,2.22,1.96,2.09,2.19,2.13
		2015m1,2015,1,2.85,2.68,3.64,2.23,1.95,2.02,1.83,1.96
		2015m2,2015,2,2.79,2.65,3.62,2.28,1.87,1.86,1.99,1.96
		2015m3,2015,3,2.79,2.62,3.59,2.19,1.88,1.77,1.88,1.88
		2015m4,2015,4,2.72,2.59,3.56,2.11,1.83,1.7,1.95,1.87
		2015m5,2015,5,2.69,2.56,3.53,2.2,1.84,1.61,1.78,1.77
		2015m6,2015,6,2.68,2.52,3.5,2.11,1.81,1.72,1.92,1.85
		2015m7,2015,7,2.64,2.49,3.46,2.17,1.91,1.86,2.1,1.99
		2015m8,2015,8,2.63,2.46,3.44,2.27,1.95,1.92,2.15,2.06
		2015m9,2015,9,2.64,2.44,3.41,2.17,1.98,1.92,2.12,2.03
		2015m10,2015,10,2.62,2.41,3.38,2.11,1.99,1.94,2.14,2.05
		2015m11,2015,11,2.61,2.38,3.36,2.27,1.94,1.89,2.09,2.02
		2015m12,2015,12,2.62,2.36,3.33,2.16,1.88,1.83,2.01,1.95
		2016m1,2016,1,2.61,2.34,3.3,2.22,1.87,1.84,2.05,1.97
		2016m2,2016,2,2.6,2.36,3.27,2.45,1.86,1.79,1.97,1.96
		2016m3,2016,3,2.63,2.34,3.24,2.1,1.82,1.7,1.86,1.82
		2016m4,2016,4,2.56,2.31,3.21,2.16,1.82,1.67,1.97,1.88
		2016m5,2016,5,2.57,2.29,3.19,2.19,1.83,1.62,1.83,1.79
		2016m6,2016,6,2.57,2.28,3.16,2.04,1.85,1.6,1.79,1.76
		2016m7,2016,7,2.5,2.25,3.13,2.01,1.79,1.59,1.75,1.73
		2016m8,2016,8,2.5,2.23,3.1,2.18,1.76,1.49,1.69,1.68
		2016m9,2016,9,2.49,2.22,3.07,2.01,1.75,1.48,1.66,1.64
		2016m10,2016,10,2.49,2.19,3.04,1.99,1.62,1.45,1.66,1.62
		2016m11,2016,11,2.42,2.13,3.02,1.88,1.66,1.43,1.68,1.62
		2016m12,2016,12,2.42,2.11,2.99,1.98,1.67,1.49,1.73,1.66
		2017m1,2017,1,2.43,2.1,2.96,2.08,1.66,1.59,1.86,1.77
		2017m2,2017,2,2.41,2.09,2.94,2.17,1.65,1.64,1.9,1.81
		2017m3,2017,3,2.47,2.07,2.91,2.08,1.69,1.67,1.89,1.82
		2017m4,2017,4,2.45,2.05,2.88,2.1,1.73,1.71,1.92,1.85
		2017m5,2017,5,2.44,2.04,2.85,2.17,1.77,1.66,1.88,1.83
		2017m6,2017,6,2.44,2.03,2.83,2.02,1.7,1.68,1.89,1.82
		2017m7,2017,7,2.46,2.01,2.8,2.04,1.68,1.66,1.92,1.82
		2017m8,2017,8,2.45,2,2.77,2.05,1.89,1.67,1.98,1.87
		2017m9,2017,9,2.42,2,2.75,2.04,1.71,1.71,1.96,1.86
		2017m10,2017,10,2.38,1.99,2.73,2.08,1.7,1.68,1.96,1.85
		2017m11,2017,11,2.44,1.98,2.71,2.04,1.72,1.68,1.94,1.84
		2017m12,2017,12,2.44,1.97,2.68,2.04,1.69,1.65,1.86,1.79
		2018m1,2018,1,2.33,1.96,2.66,2.03,1.69,1.65,1.92,1.82
		2018m2,2018,2,2.31,1.95,2.65,2.07,1.73,1.68,1.92,1.84
		2018m3,2018,3,2.31,1.94,2.62,2.05,1.73,1.74,1.98,1.89
		2018m4,2018,4,2.32,1.93,2.6,2.09,1.72,1.77,1.96,1.89
		2018m5,2018,5,2.31,1.93,2.58,2.09,1.74,1.77,2,1.91
		2018m6,2018,6,2.27,1.92,2.56,2.07,1.76,1.75,1.97,1.9
		2018m7,2018,7,2.27,1.9,2.54,2.16,1.74,1.73,1.95,1.88
		2018m8,2018,8,2.28,1.89,2.52,2.13,1.7,1.71,1.97,1.87
		2018m9,2018,9,2.27,1.89,2.5,2.11,1.71,1.69,1.94,1.86
		2018m10,2018,10,2.25,1.87,2.48,2.08,1.68,1.71,1.97,1.86
		2018m11,2018,11,2.25,1.87,2.46,2.02,1.74,1.72,1.98,1.88
		2018m12,2018,12,2.27,1.86,2.44,2.02,1.71,1.7,1.94,1.85
		2019m1,2019,1,2.27,1.85,2.42,2.09,1.69,1.7,1.95,1.86
		2019m2,2019,2,2.28,1.85,2.41,2.04,1.65,1.63,1.85,1.78
		2019m3,2019,3,2.27,1.85,2.39,2.04,1.64,1.59,1.79,1.74
		2019m4,2019,4,2.26,1.79,2.37,2.04,1.48,1.53,1.72,1.67
		2019m5,2019,5,2.26,1.79,2.35,2,1.5,1.46,1.67,1.63
		2019m6,2019,6,2.23,1.78,2.33,1.98,1.44,1.41,1.61,1.57
		2019m7,2019,7,2.22,1.77,2.31,1.98,1.43,1.34,1.49,1.49
		2019m8,2019,8,2.16,1.76,2.29,1.86,1.38,1.23,1.36,1.38
		2019m9,2019,9,2.16,1.75,2.27,1.88,1.38,1.14,1.24,1.28
		2019m10,2019,10,2.11,1.73,2.24,1.91,1.31,1.12,1.22,1.27
		2019m11,2019,11,2.07,1.71,2.22,1.84,1.3,1.09,1.25,1.26
		2019m12,2019,12,2.07,1.71,2.2,1.81,1.37,1.14,1.26,1.29
		2020m1,2020,1,2.05,1.69,2.18,1.83,1.32,1.16,1.35,1.34
		2020m2,2020,2,2.01,1.69,2.16,1.82,1.33,1.13,1.26,1.28
		2020m3,2020,3,2.04,1.68,2.14,1.83,1.32,1.07,1.18,1.22
		2020m4,2020,4,1.99,1.66,2.12,1.78,1.32,1.11,1.22,1.25
		2020m5,2020,5,1.97,1.66,2.1,1.93,1.47,1.12,1.27,1.33
		2020m6,2020,6,1.98,1.65,2.09,1.94,1.59,1.17,1.28,1.34
		2020m7,2020,7,1.99,1.65,2.06,1.81,1.39,1.12,1.24,1.27
		2020m8,2020,8,1.98,1.64,2.05,1.8,1.44,1.07,1.2,1.23
		2020m9,2020,9,1.95,1.62,2.03,1.77,1.35,1.07,1.17,1.21
		2020m10,2020,10,1.92,1.62,2,1.75,1.32,1.03,1.17,1.19
		2020m11,2020,11,1.92,1.6,1.99,1.72,1.28,1.03,1.14,1.17
		2020m12,2020,12,1.92,1.6,1.97,1.75,1.31,1.02,1.11,1.16
		2021m1,2021,1,1.9,1.59,1.95,1.79,1.34,1.03,1.15,1.19
		2021m2,2021,2,1.89,1.57,1.93,1.73,1.28,1.04,1.14,1.17
		2021m3,2021,3,1.89,1.56,1.91,1.75,1.25,1.02,1.17,1.18
		2021m4,2021,4,1.86,1.56,1.88,1.79,1.28,1.06,1.23,1.23
		2021m5,2021,5,1.94,1.55,1.87,1.83,1.3,1.09,1.29,1.27
		2021m6,2021,6,1.91,1.54,1.85,1.74,1.33,1.12,1.33,1.29
		2021m7,2021,7,1.92,1.53,1.83,1.76,1.32,1.14,1.34,1.31
		2021m8,2021,8,1.94,1.52,1.82,1.78,1.37,1.1,1.28,1.27
		2021m9,2021,9,1.94,1.52,1.8,1.8,1.33,1.09,1.27,1.26
		2021m10,2021,10,1.97,1.52,1.79,1.79,1.33,1.1,1.29,1.28
		2021m11,2021,11,2.08,1.52,1.77,1.83,1.43,1.15,1.33,1.32
		2021m12,2021,12,2.02,1.52,1.75,1.8,1.39,1.16,1.34,1.32
		2022m1,2022,1,2.02,1.52,1.74,1.83,1.35,1.19,1.37,1.35
		2022m2,2022,2,2.02,1.52,1.73,1.86,1.45,1.29,1.48,1.45
		2022m3,2022,3,2.1,1.53,1.71,1.93,1.65,1.5,1.71,1.65
		2022m4,2022,4,2.08,1.54,1.71,2.01,1.88,1.81,2.04,1.94
		2022m5,2022,5,2.15,1.55,1.7,2.1,2.1,2.12,2.42,2.25
		2022m6,2022,6,2.19,1.58,1.7,2.19,2.45,2.46,2.77,2.57
		2022m7,2022,7,2.28,1.7,1.7,2.33,2.64,2.73,3.04,2.8
		2022m8,2022,8,2.43,1.76,1.7,2.55,2.78,2.74,3.04,2.84
		2022m9,2022,9,2.61,1.86,1.7,2.73,2.93,2.96,3.18,3.01
		2022m10,2022,10,3.06,2.06,1.72,2.9,3.23,3.19,3.48,3.25
		2022m11,2022,11,3.35,2.21,1.73,3.4,3.75,3.51,3.75,3.6
		2022m12,2022,12,3.66,2.37,1.74,3.57,3.74,3.41,3.55,3.52
		2023m1,2023,1,4.1,2.52,1.76,3.95,3.8,3.45,3.7,3.66
		2023m2,2023,2,4.32,2.64,1.77,4.16,3.99,3.6,3.74,3.79
		2023m3,2023,3,4.45,2.77,1.78,4.44,4.1,3.64,3.8,3.88
		2023m4,2023,4,4.72,2.94,1.79,4.63,4.23,3.7,3.77,3.93
		2023m5,2023,5,4.93,3.03,1.81,4.82,4.27,3.66,3.76,3.94
		2023m6,2023,6,5.1,3.13,1.82,5.05,4.38,3.73,3.84,4.06
		2023m7,2023,7,5.34,3.26,1.83,5.2,4.37,3.71,3.82,4.02
		2023m8,2023,8,5.41,3.33,1.85,5.29,4.53,3.81,3.89,4.14
		2023m9,2023,9,5.49,3.38,1.86,5.4,4.48,3.89,3.85,4.12
		2023m10,2023,10,5.57,3.5,1.87,5.53,4.53,3.85,3.9,4.18
		2023m11,2023,11,5.7,3.58,1.89,5.62,4.61,3.92,3.92,4.22
		2023m12,2023,12,5.62,3.64,1.9,5.56,4.44,3.8,3.65,4.05
		2024m1,2024,1,5.66,3.69,1.91,5.44,4.08,3.56,3.55,3.85
		2024m2,2024,2,5.7,3.72,1.92,5.41,4.04,3.59,3.61,3.88
		2024m3,2024,3,5.68,3.75,1.93,5.28,4.09,3.55,3.61,3.83
		2024m4,2024,4,5.65,3.78,1.94,5.45,4.06,3.57,3.64,3.86
		2024m5,2024,5,5.55,3.81,1.95,5.44,4.14,3.6,3.69,3.91
		2024m6,2024,6,5.58,3.84,1.97,5.51,4.19,3.66,3.68,3.95
		2024m7,2024,7,5.45,3.87,1.98,5.38,4.15,3.64,3.71,3.92
		2024m8,2024,8,5.43,3.9,2,5.37,4.01,3.6,3.6,3.83
		2024m9,2024,9,5.38,3.91,2.01,5.29,3.88,3.47,3.5,3.73
		2024m10,2024,10,5.19,3.94,2.02,4.99,3.81,3.42,3.45,3.65
		2024m11,2024,11,5.15,3.99,2.04,5.02,3.67,3.36,3.39,3.59
		2024m12,2024,12,5.1,3.99,2.05,4.78,3.7,3.32,3.34,3.56
		2025m1,2025,1,4.8,3.93,2.06,4.6,3.5,3.3,3.41,3.52
		2025m2,2025,2,4.77,3.92,2.07,4.56,3.6,3.35,3.48,3.58
		2025m3,2025,3,4.63,3.89,2.08,4.41,3.62,3.39,3.54,3.6
		2025m4,2025,4,4.54,3.87,2.1,4.44,3.59,3.48,3.65,3.69
		2025m5,2025,5,4.47,3.85,2.11,4.33,3.52,3.51,3.63,3.66
		2025m6,2025,6,4.39,3.84,2.13,4.24,3.52,3.52,3.68,3.68
		2025m7,2025,7,4.19,3.8,2.14,4.12,3.5,3.55,3.69,3.68

00_original_index/03_data/data_given/bb_volumes_D_m.csv

0 → 100644

+272 −0

Original line number	Diff line number	Diff line
		date,year,month,volume_existing_1,volume_existing_1_5,volume_existing_5,volume_existing_overall,volume_new_1,volume_new_1_5,volume_new_5_10,volume_new_10,volume_new_overall
		2003m1,2003,1,7555,31280,864334,903169,3113,2871,6402,3161,15547
		2003m2,2003,2,7391,31136,865808,904335,2151,2260,4859,3228,12498
		2003m3,2003,3,7444,31077,872522,911043,2057,2559,6252,3342,14210
		2003m4,2003,4,7374,31064,872870,911308,2321,3135,7423,3661,16540
		2003m5,2003,5,7481,31255,874950,913686,1697,2676,4755,3151,12279
		2003m6,2003,6,7869,32343,874496,914708,2253,2685,5062,3149,13149
		2003m7,2003,7,7736,32615,876079,916430,2805,3589,6864,3973,17231
		2003m8,2003,8,7963,32704,877703,918370,1695,2701,5441,3600,13437
		2003m9,2003,9,8021,32866,879027,919914,2033,3166,6143,3584,14926
		2003m10,2003,10,7771,33141,882461,923373,2463,3292,6201,3200,15156
		2003m11,2003,11,7751,33163,884556,925470,1866,2903,5368,3108,13245
		2003m12,2003,12,7756,33048,886169,926973,2878,3710,7473,3380,17441
		2004m1,2004,1,7640,32903,885887,926430,2827,3280,5978,3201,15286
		2004m2,2004,2,7521,32805,884830,925156,1999,2457,4262,2628,11346
		2004m3,2004,3,7690,32177,880991,920858,2504,3240,5417,2983,14144
		2004m4,2004,4,7401,32145,881844,921390,2706,3127,5106,2964,13903
		2004m5,2004,5,7500,32264,882819,922583,2079,2736,4497,2865,12177
		2004m6,2004,6,7635,33003,886330,926968,2314,3479,5292,2934,14019
		2004m7,2004,7,7576,33069,888750,929395,3233,3279,5963,2873,15348
		2004m8,2004,8,7478,33200,890900,931578,2071,2291,3844,2648,10854
		2004m9,2004,9,7597,33358,894803,935758,2058,2371,4139,2551,11119
		2004m10,2004,10,7648,33772,895426,936846,3091,2343,4077,2730,12241
		2004m11,2004,11,7586,33276,896527,937389,1887,2131,3961,3164,11143
		2004m12,2004,12,7637,33188,897842,938667,2292,2682,5217,3598,13789
		2005m1,2005,1,7201,32928,896181,936310,2467,2321,4631,3507,12926
		2005m2,2005,2,7107,32850,895887,935844,1668,1962,3504,2816,9950
		2005m3,2005,3,7152,33787,894891,935830,2078,2210,4901,3655,12844
		2005m4,2005,4,7115,31174,897764,936053,2786,2376,5023,3484,13669
		2005m5,2005,5,6982,30994,898429,936405,2075,2204,4412,3324,12015
		2005m6,2005,6,7117,30946,899589,937652,2196,2449,5527,4262,14434
		2005m7,2005,7,7032,30816,902665,940513,3353,2699,6315,4226,16593
		2005m8,2005,8,6792,30940,904568,942300,2010,2439,5789,4615,14853
		2005m9,2005,9,6929,30914,906453,944296,2095,2331,5388,4390,14204
		2005m10,2005,10,6746,30686,908403,945835,2603,2395,5674,3873,14545
		2005m11,2005,11,6778,30699,911037,948514,2062,2620,6669,4629,15980
		2005m12,2005,12,6674,30825,913054,950553,2522,3138,8514,5545,19719
		2006m1,2006,1,6339,30239,920568,957146,3199,2857,8266,5913,20235
		2006m2,2006,2,6296,30128,921360,957784,2049,2275,6081,4479,14884
		2006m3,2006,3,6205,29958,921405,957568,2204,2588,6849,5710,17351
		2006m4,2006,4,6108,29513,922080,957701,3072,2364,6204,4470,16110
		2006m5,2006,5,5999,29957,922574,958530,2074,2435,6381,4871,15761
		2006m6,2006,6,6142,29878,923635,959655,2338,2395,6108,4902,15743
		2006m7,2006,7,6019,29697,925015,960731,2561,2415,6106,4363,15445
		2006m8,2006,8,6020,29598,927057,962675,2229,2398,5777,4498,14902
		2006m9,2006,9,6431,29571,929116,965118,2122,1964,4855,4191,13132
		2006m10,2006,10,5995,29456,929900,965351,2781,2254,5609,4527,15171
		2006m11,2006,11,5846,29155,931077,966078,2111,2295,5434,4580,14420
		2006m12,2006,12,6043,29537,930843,966423,2315,2494,5664,4528,15001
		2007m1,2007,1,5651,29312,928597,963560,2619,2744,6651,5200,17214
		2007m2,2007,2,5803,29069,928131,963003,1824,2009,4898,4032,12763
		2007m3,2007,3,6269,28582,927743,962594,2506,2565,6003,5329,16403
		2007m4,2007,4,5892,28304,926996,961192,2286,2315,6525,5131,16257
		2007m5,2007,5,5944,28091,926362,960397,2012,2167,6281,5236,15696
		2007m6,2007,6,6342,27850,926997,961189,2372,2128,6144,5466,16110
		2007m7,2007,7,5642,27779,926469,959890,2745,2484,6855,5229,17313
		2007m8,2007,8,5676,27650,927325,960651,2220,2207,5578,4883,14888
		2007m9,2007,9,5759,27517,928329,961605,2240,1967,4717,4242,13166
		2007m10,2007,10,5610,27337,927812,960759,2458,2380,5796,4619,15253
		2007m11,2007,11,5580,27097,928254,960931,1933,2248,4964,4478,13623
		2007m12,2007,12,5714,26823,927008,959545,2127,2094,4842,4025,13088
		2008m1,2008,1,5547,26525,924797,956869,2759,2776,5863,4813,16211
		2008m2,2008,2,5523,26172,924259,955954,1926,2085,4520,3734,12265
		2008m3,2008,3,5643,26003,922836,954482,1647,2181,4701,3915,12444
		2008m4,2008,4,5624,25744,922735,954103,2388,2966,6576,4787,16717
		2008m5,2008,5,5397,25588,923319,954304,1946,2510,5480,4197,14133
		2008m6,2008,6,5493,25544,923200,954237,2173,2634,6229,4703,15739
		2008m7,2008,7,5519,25309,924218,955046,2701,2829,6747,5113,17390
		2008m8,2008,8,5476,25164,924678,955318,1998,1932,4920,4213,13063
		2008m9,2008,9,5535,24990,924483,955008,2129,1979,5610,4418,14136
		2008m10,2008,10,5428,24655,923326,953409,2488,2431,6336,4437,15692
		2008m11,2008,11,5430,24457,923930,953817,1995,2363,5064,4024,13446
		2008m12,2008,12,5528,24239,921200,950967,2476,2918,5566,4200,15160
		2009m1,2009,1,5418,23858,918511,947787,3251,3343,6197,3970,16761
		2009m2,2009,2,5385,23699,917860,946944,2370,2749,5336,3395,13850
		2009m3,2009,3,5628,25122,914732,945482,2787,3343,6831,4609,17570
		2009m4,2009,4,5583,25146,915850,946579,3150,3521,7455,4272,18398
		2009m5,2009,5,5586,25160,916298,947044,2616,3031,6547,4000,16194
		2009m6,2009,6,5605,25260,916112,946977,2654,3410,7491,4261,17816
		2009m7,2009,7,5645,25363,917097,948105,3374,3747,8321,4424,19866
		2009m8,2009,8,5590,25464,919814,950868,2931,2812,6269,3767,15779
		2009m9,2009,9,5673,25577,920700,951950,2256,2587,5904,4060,14807
		2009m10,2009,10,5595,25654,922448,953697,2956,2707,6512,3780,15955
		2009m11,2009,11,5539,25787,923431,954757,2214,2462,5363,3681,13720
		2009m12,2009,12,5548,25772,922976,954296,2530,2741,5547,3668,14486
		2010m1,2010,1,5331,25666,920643,951640,2978,2512,5293,3006,13789
		2010m2,2010,2,5265,25617,919593,950475,2057,2096,4389,3354,11896
		2010m3,2010,3,5409,25698,919692,950799,2660,2470,5889,4291,15310
		2010m4,2010,4,5308,25751,920319,951378,2723,2485,5485,4104,14797
		2010m5,2010,5,5432,25886,920465,951783,2233,2271,5238,4104,13846
		2010m6,2010,6,5042,25736,920874,951652,2382,2221,5153,4863,14619
		2010m7,2010,7,5045,25877,922891,953813,3177,2746,6439,5364,17726
		2010m8,2010,8,5504,26087,923549,955140,2258,2237,5534,4736,14765
		2010m9,2010,9,5496,26300,925125,956921,2128,2238,6017,5497,15880
		2010m10,2010,10,5454,26375,926848,958677,2821,2301,6107,5273,16502
		2010m11,2010,11,5394,26557,927910,959861,2153,2257,5998,5472,15880
		2010m12,2010,12,5369,26562,927179,959110,2707,2593,6607,5506,17413
		2011m1,2011,1,5251,26420,926229,957900,3557,2705,6235,4130,16627
		2011m2,2011,2,5036,26475,926672,958183,2184,2340,5418,4174,14116
		2011m3,2011,3,5244,26701,926849,958794,2890,2653,6343,5160,17046
		2011m4,2011,4,5202,26839,927172,959213,2915,2435,6184,4626,16160
		2011m5,2011,5,5248,27062,928324,960634,2692,2375,6161,4699,15927
		2011m6,2011,6,5203,27212,929360,961775,2334,1929,5070,4184,13517
		2011m7,2011,7,5292,27349,930440,963081,3193,2252,5791,4265,15501
		2011m8,2011,8,5315,27537,931970,964822,2405,2195,5636,4817,15053
		2011m9,2011,9,5284,27816,934057,967157,2239,2087,5593,5085,15004
		2011m10,2011,10,5240,27897,935360,968497,2812,2204,6002,4890,15908
		2011m11,2011,11,5165,28069,937366,970600,2069,2273,6173,5370,15885
		2011m12,2011,12,5300,28122,937763,971185,2377,2349,6249,5434,16409
		2012m1,2012,1,5137,28154,936543,969834,2674,2343,6120,4063,15200
		2012m2,2012,2,5054,28188,936749,969991,2387,1952,5121,4278,13738
		2012m3,2012,3,5100,28402,937726,971228,2007,2338,6115,5429,15889
		2012m4,2012,4,5069,28290,936775,970134,2439,2246,5988,4515,15188
		2012m5,2012,5,5187,28501,938392,972080,2313,2019,6053,4550,14935
		2012m6,2012,6,5206,28620,940699,974525,2248,2009,6132,5816,16205
		2012m7,2012,7,5302,28775,942529,976606,2830,2360,7464,5868,18522
		2012m8,2012,8,5278,28844,945754,979876,2421,2046,6838,6031,17336
		2012m9,2012,9,5351,28910,948590,982851,2002,1911,5697,5287,14897
		2012m10,2012,10,5351,29062,951931,986344,2567,2175,6782,5533,17057
		2012m11,2012,11,5334,29210,955995,990539,2194,2265,6232,5567,16258
		2012m12,2012,12,5411,29153,957142,991706,2326,1690,5578,4473,14067
		2013m1,2013,1,5441,29130,956829,991400,3170,2193,7009,4725,17097
		2013m2,2013,2,5358,28985,957811,992154,2209,1760,5899,4389,14257
		2013m3,2013,3,5380,28892,959296,993568,2404,1941,6015,5011,15371
		2013m4,2013,4,5429,28943,960434,994806,2999,2278,7312,5352,17941
		2013m5,2013,5,5513,28887,962645,997045,2344,1923,6295,4933,15495
		2013m6,2013,6,5484,28964,965019,999467,2433,1980,6479,5591,16483
		2013m7,2013,7,5653,28977,968047,1002677,3402,2564,8735,6119,20820
		2013m8,2013,8,5525,28947,971598,1006070,2402,2055,6854,5204,16515
		2013m9,2013,9,5599,29073,973593,1008265,2397,1930,6327,4574,15228
		2013m10,2013,10,5786,29061,976282,1011129,3064,2261,6788,4684,16797
		2013m11,2013,11,5644,29027,979253,1013924,2208,1853,5493,4535,14089
		2013m12,2013,12,5683,28778,978740,1013201,2673,2027,6066,4183,14949
		2014m1,2014,1,5704,28563,977215,1011482,3235,2395,6530,4316,16476
		2014m2,2014,2,5602,28337,979347,1013286,2728,1967,5390,4534,14619
		2014m3,2014,3,5707,28267,980208,1014182,2579,2158,6224,5143,16104
		2014m4,2014,4,5744,28198,981947,1015889,2813,2459,7011,5318,17601
		2014m5,2014,5,5764,28197,984889,1018850,2361,2128,6252,5002,15743
		2014m6,2014,6,5762,28112,986700,1020574,2572,1980,6219,4803,15574
		2014m7,2014,7,5812,28148,989997,1023957,3029,2488,7704,5800,19021
		2014m8,2014,8,5667,28220,994510,1028397,2427,1907,6205,5319,15858
		2014m9,2014,9,5630,28295,997116,1031041,2214,1945,6630,5669,16458
		2014m10,2014,10,5766,28278,1000934,1034978,2681,2077,7208,5972,17938
		2014m11,2014,11,5631,28396,1004378,1038405,2253,1979,6201,5687,16120
		2014m12,2014,12,5083,28211,1013753,1047047,2762,2015,7445,6278,18500
		2015m1,2015,1,5160,28086,1012824,1046070,2606,2006,6927,8230,19769
		2015m2,2015,2,5016,27984,1014974,1047974,2199,1753,6492,6604,17048
		2015m3,2015,3,5088,27865,1016146,1049099,2760,2118,7693,8563,21134
		2015m4,2015,4,5047,27831,1019037,1051915,2640,1935,7330,8581,20486
		2015m5,2015,5,5034,27819,1022953,1055806,2315,1754,7123,8357,19549
		2015m6,2015,6,5037,27833,1026258,1059128,2798,2197,9297,9723,24015
		2015m7,2015,7,5202,27839,1031485,1064526,2915,2502,10095,9798,25310
		2015m8,2015,8,5133,27884,1035464,1068481,2290,1939,7566,7950,19745
		2015m9,2015,9,5034,27893,1040092,1073019,2344,1851,7276,7690,19161
		2015m10,2015,10,5064,27890,1044772,1077726,2577,2125,7230,7942,19874
		2015m11,2015,11,5040,27842,1048108,1080990,2190,1874,7319,7043,18426
		2015m12,2015,12,4930,27694,1050742,1083366,2713,2045,7385,7378,19521
		2016m1,2016,1,4918,27439,1050822,1083179,2413,2054,6800,7240,18507
		2016m2,2016,2,4928,27365,1052648,1084941,2584,1994,6837,7363,18778
		2016m3,2016,3,4930,27373,1055393,1087696,2618,2256,8246,9276,22396
		2016m4,2016,4,4846,27217,1059886,1091949,2206,1820,6054,7779,17859
		2016m5,2016,5,4879,27188,1062641,1094708,2133,1698,6635,7502,17968
		2016m6,2016,6,4789,27274,1067240,1099303,2567,1931,7424,9487,21409
		2016m7,2016,7,4765,27235,1072582,1104582,2464,1866,7230,8727,20287
		2016m8,2016,8,4706,27200,1076855,1108761,2185,1745,7197,8776,19903
		2016m9,2016,9,4576,27196,1081912,1113684,2062,1658,6555,8361,18636
		2016m10,2016,10,4640,27070,1085745,1117455,2093,1584,6317,7919,17913
		2016m11,2016,11,4471,27006,1089931,1121408,2611,1614,7008,8990,20223
		2016m12,2016,12,4319,26779,1092883,1123981,2347,1800,8054,9199,21400
		2017m1,2017,1,4407,26401,1093203,1124011,2283,1780,7454,8287,19804
		2017m2,2017,2,4256,26274,1095552,1126082,1784,1567,6556,7931,17838
		2017m3,2017,3,4286,26208,1099530,1130024,2428,1932,7609,10227,22196
		2017m4,2017,4,4241,26175,1104580,1134996,2001,1672,6456,7958,18087
		2017m5,2017,5,4304,26188,1108805,1139297,2288,1731,7308,9157,20484
		2017m6,2017,6,4200,26206,1115307,1145713,2265,1541,6573,8915,19294
		2017m7,2017,7,4076,26017,1120699,1150792,2389,1726,7420,8870,20405
		2017m8,2017,8,4035,25937,1125823,1155795,2340,1888,7199,8801,20228
		2017m9,2017,9,3934,25996,1131500,1161430,2025,1571,5950,7817,17363
		2017m10,2017,10,4208,25925,1135284,1165417,2134,1634,6611,7749,18128
		2017m11,2017,11,3898,25924,1139714,1169536,2170,1640,6550,8433,18793
		2017m12,2017,12,3851,25850,1143333,1173034,2150,1553,6084,7686,17473
		2018m1,2018,1,3906,25566,1144088,1173560,2354,1798,6864,8627,19643
		2018m2,2018,2,3869,25474,1147522,1176865,2090,1624,6400,8725,18839
		2018m3,2018,3,3983,25497,1153724,1183204,2256,1773,7047,9516,20592
		2018m4,2018,4,3933,25480,1157212,1186625,2369,1895,7418,9669,21351
		2018m5,2018,5,4024,25609,1162731,1192364,2193,1735,6847,8739,19514
		2018m6,2018,6,4139,25721,1169692,1199552,3226,1882,6771,9585,21464
		2018m7,2018,7,4217,25586,1174210,1204013,2675,1994,7666,9842,22177
		2018m8,2018,8,4215,25643,1180809,1210667,2337,1753,6974,9429,20493
		2018m9,2018,9,4306,26196,1186420,1216922,1973,1544,5923,8424,17864
		2018m10,2018,10,4311,26171,1191048,1221530,2443,1884,7669,9279,21275
		2018m11,2018,11,4299,26265,1196579,1227143,2313,1779,6738,9527,20357
		2018m12,2018,12,4242,26203,1199525,1229970,2113,1519,6088,7910,17630
		2019m1,2019,1,4379,25867,1200982,1231228,2475,1962,7080,9390,20907
		2019m2,2019,2,4300,25861,1204756,1234917,2163,1749,6344,9095,19352
		2019m3,2019,3,4424,25905,1210350,1240679,2413,1755,6884,10283,21335
		2019m4,2019,4,4418,25875,1218785,1249078,2570,2074,7760,10701,23105
		2019m5,2019,5,4534,26212,1224628,1255374,2560,2030,7324,10715,22629
		2019m6,2019,6,4575,26445,1230368,1261388,2280,1695,6429,9760,20164
		2019m7,2019,7,4643,26544,1236461,1267648,2743,2107,8473,12348,25672
		2019m8,2019,8,4658,26765,1243945,1275368,2529,1684,6856,11450,22520
		2019m9,2019,9,4636,26538,1250520,1281694,2182,1613,6714,11294,21803
		2019m10,2019,10,4749,26605,1257680,1289034,2452,1738,7268,11711,23169
		2019m11,2019,11,4787,26726,1265217,1296730,2206,1663,6889,11475,22234
		2019m12,2019,12,4610,26616,1268612,1299838,2396,1553,6622,9477,20048
		2020m1,2020,1,4755,26351,1271558,1302664,2545,1797,7106,10479,21927
		2020m2,2020,2,4813,26389,1278139,1309341,2019,1499,6555,10474,20546
		2020m3,2020,3,4755,26516,1284212,1315483,2503,1872,8045,12894,25314
		2020m4,2020,4,4673,26483,1291221,1322377,2525,1822,7769,12425,24541
		2020m5,2020,5,4752,26603,1299073,1330428,3000,1643,6872,10845,22361
		2020m6,2020,6,4628,26702,1303405,1334735,2235,1947,7983,10628,22793
		2020m7,2020,7,4720,26707,1312369,1343796,2518,1847,8036,11949,24349
		2020m8,2020,8,4727,26690,1315489,1346906,2209,1500,7032,10539,21280
		2020m9,2020,9,4705,26940,1329087,1360732,2213,1542,6957,11070,21782
		2020m10,2020,10,4792,26962,1337259,1369013,2362,1554,7579,11722,23217
		2020m11,2020,11,4616,27072,1345468,1377156,2372,1708,7413,11692,23185
		2020m12,2020,12,4557,27024,1353793,1385374,2195,1698,7733,10522,22148
		2021m1,2021,1,4663,26903,1357733,1389299,2124,1615,7316,10666,21721
		2021m2,2021,2,4642,26790,1363884,1395316,2098,1563,7547,10938,22145
		2021m3,2021,3,4545,26788,1373003,1404336,2684,1958,10006,13941,28589
		2021m4,2021,4,4496,26870,1381533,1412899,2343,1725,8741,11732,24541
		2021m5,2021,5,4575,26759,1390096,1421430,2064,1568,8416,10738,22786
		2021m6,2021,6,4485,26949,1399549,1430983,2374,1775,9196,11815,25161
		2021m7,2021,7,4642,26996,1410004,1441642,2686,1649,9216,11570,25121
		2021m8,2021,8,4581,27041,1418884,1450506,2324,1514,7975,10922,22735
		2021m9,2021,9,4521,27117,1427271,1458909,2204,1451,7631,10946,22232
		2021m10,2021,10,4623,27324,1436840,1468787,2353,1613,8013,10650,22630
		2021m11,2021,11,3680,26929,1446574,1477183,2022,1564,8171,10759,22516
		2021m12,2021,12,3547,26755,1454553,1484855,2383,1661,8614,11194,23851
		2022m1,2022,1,3690,26583,1457059,1487332,2527,1706,8661,12191,25085
		2022m2,2022,2,3559,26620,1464103,1494282,2270,1606,9322,13100,26299
		2022m3,2022,3,3620,26670,1473852,1504142,2704,1987,11809,15770,32270
		2022m4,2022,4,3636,26766,1483015,1513417,2323,1703,10024,11763,25813
		2022m5,2022,5,3584,26874,1492093,1522551,2491,1834,10907,12041,27272
		2022m6,2022,6,3573,26899,1500141,1530613,2461,1663,8659,10208,22990
		2022m7,2022,7,3687,27244,1508724,1539655,2814,1592,8023,8626,21054
		2022m8,2022,8,3713,27275,1515561,1546549,2488,1512,6880,7610,18491
		2022m9,2022,9,3627,27290,1522592,1553509,2186,1366,5969,6593,16113
		2022m10,2022,10,3689,27325,1528186,1559200,2522,1363,5433,5607,14926
		2022m11,2022,11,3604,27320,1533123,1564047,2330,1209,4846,5172,13557
		2022m12,2022,12,3497,26984,1535823,1566304,2620,1267,4837,4790,13514
		2023m1,2023,1,3550,26527,1534684,1564761,2244,1196,4531,4764,12735
		2023m2,2023,2,3429,26317,1536492,1566238,2097,1207,4229,4522,12055
		2023m3,2023,3,3493,26266,1540365,1570124,2459,1524,5388,5889,15260
		2023m4,2023,4,3490,26102,1542767,1572359,2109,1276,4471,5144,12999
		2023m5,2023,5,3423,25960,1544206,1573589,2148,1359,5038,5112,13657
		2023m6,2023,6,3298,25865,1546102,1575265,2301,1450,4986,5246,13983
		2023m7,2023,7,3413,25712,1548159,1577284,1949,1469,5352,5564,14335
		2023m8,2023,8,3391,25573,1550499,1579463,2198,1388,5275,5525,14386
		2023m9,2023,9,3233,25315,1553618,1582166,1523,1171,4534,5058,12286
		2023m10,2023,10,3312,25212,1554344,1582868,1989,1403,5304,5136,13831
		2023m11,2023,11,3294,24792,1556410,1584496,1723,1588,4936,5225,13473
		2023m12,2023,12,3198,24499,1556523,1584220,1576,1553,4349,4672,12151
		2024m1,2024,1,3354,24060,1554763,1582177,1862,1584,5397,5825,14667
		2024m2,2024,2,3250,23819,1555595,1582664,1783,1612,5153,5697,14245
		2024m3,2024,3,3184,23540,1558297,1585021,1739,1755,5414,6530,15439
		2024m4,2024,4,3289,23271,1559197,1585757,1869,1868,6234,6822,16793
		2024m5,2024,5,3400,23042,1561200,1587642,1828,1480,6051,6044,15403
		2024m6,2024,6,3272,22914,1564022,1590208,2039,1476,6163,6618,16296
		2024m7,2024,7,3483,22626,1566908,1593017,2340,1839,7547,7786,19511
		2024m8,2024,8,3344,22463,1570363,1596170,1816,1658,6122,7216,16811
		2024m9,2024,9,3308,22308,1572823,1598439,1898,1581,5987,7146,16611
		2024m10,2024,10,3325,22206,1574221,1599752,1991,1802,6232,7853,17878
		2024m11,2024,11,3189,22050,1577905,1603144,1984,1720,5062,8956,17721
		2024m12,2024,12,3162,21842,1579090,1604094,2088,1876,4961,8065,16989
		2025m1,2025,1,3394,21506,1579472,1604372,2276,1944,6090,9433,19743
		2025m2,2025,2,3282,21317,1582197,1606796,2265,1745,5622,9445,19077
		2025m3,2025,3,3414,21109,1585401,1609924,2494,2206,6585,10865,22151
		2025m4,2025,4,3377,21095,1590375,1614847,2720,2284,7032,9464,21500
		2025m5,2025,5,3366,21008,1593249,1617623,2214,2064,6235,9357,19870
		2025m6,2025,6,3389,20940,1595642,1619971,2411,2109,6088,8626,19234
		2025m7,2025,7,3545,21022,1600795,1625362,2698,2490,7271,9878,22337

00_original_index/03_data/data_given/building_investments_D_q.csv

0 → 100644

+139 −0

Original line number	Diff line number	Diff line
		date,year,quarter,building_inv_res_adj,building_inv_res_orig
		1991q1,1991,1,72.45999999999999,61.6
		1991q2,1991,2,71.20999999999999,76.95
		1991q3,1991,3,70.79000000000001,77.62
		1991q4,1991,4,75.31,71.62
		1992q1,1992,1,79.25,69.47
		1992q2,1992,2,78.37,83.31
		1992q3,1992,3,76.67,83.81999999999999
		1992q4,1992,4,82.05,80.16
		1993q1,1993,1,81.34,70.91
		1993q2,1993,2,81.16,87.12
		1993q3,1993,3,82.92,90.16
		1993q4,1993,4,85.20999999999999,83.28
		1994q1,1994,1,89.47,79.70999999999999
		1994q2,1994,2,92.52,98.52
		1994q3,1994,3,91.95,99.2
		1994q4,1994,4,95.65000000000001,92.59999999999999
		1995q1,1995,1,92.27,83.15000000000001
		1995q2,1995,2,95.39,100.3
		1995q3,1995,3,92.03,98.33
		1995q4,1995,4,91.43000000000001,89
		1996q1,1996,1,85.69,75.45999999999999
		1996q2,1996,2,95.44,100.26
		1996q3,1996,3,94.92,102.51
		1996q4,1996,4,95.3,92.22
		1997q1,1997,1,91.06999999999999,77.59999999999999
		1997q2,1997,2,94.2,101.26
		1997q3,1997,3,93.76000000000001,101.62
		1997q4,1997,4,93.68000000000001,91.13
		1998q1,1998,1,94.98,83.42
		1998q2,1998,2,92.84,97.45999999999999
		1998q3,1998,3,93.34999999999999,101.61
		1998q4,1998,4,91.44,90.83
		1999q1,1999,1,92.47,80.94
		1999q2,1999,2,94.09,99.58
		1999q3,1999,3,95.72,104.08
		1999q4,1999,4,94.2,93.81999999999999
		2000q1,2000,1,93.58,83.58
		2000q2,2000,2,92.59999999999999,96.86
		2000q3,2000,3,91.28,98.52
		2000q4,2000,4,88.69,86.93000000000001
		2001q1,2001,1,87.34,76.59999999999999
		2001q2,2001,2,86.79000000000001,90.77
		2001q3,2001,3,86.09,93.48
		2001q4,2001,4,85.45,83.48
		2002q1,2002,1,83.72,71.22
		2002q2,2002,2,80.81999999999999,85.56
		2002q3,2002,3,80.55,89
		2002q4,2002,4,80.09999999999999,78.12
		2003q1,2003,1,79.25,67.27
		2003q2,2003,2,79.54000000000001,83.22
		2003q3,2003,3,80.11,88.54000000000001
		2003q4,2003,4,79.93000000000001,78.52
		2004q1,2004,1,78.70999999999999,67.75
		2004q2,2004,2,76.70999999999999,81.20999999999999
		2004q3,2004,3,75.06,83.45999999999999
		2004q4,2004,4,74.23,74.5
		2005q1,2005,1,71.91,59.64
		2005q2,2005,2,72.77,78.8
		2005q3,2005,3,73.75,81.87
		2005q4,2005,4,74.04000000000001,73.54000000000001
		2006q1,2006,1,72.83,62.68
		2006q2,2006,2,77.88,81.43000000000001
		2006q3,2006,3,79.91,86.98999999999999
		2006q4,2006,4,81.65000000000001,80.73
		2007q1,2007,1,79.34999999999999,69.01000000000001
		2007q2,2007,2,75.62,79.16
		2007q3,2007,3,76.27,83.27
		2007q4,2007,4,76.26000000000001,74.81999999999999
		2008q1,2008,1,77.56999999999999,66
		2008q2,2008,2,72.89,78.93000000000001
		2008q3,2008,3,72.47,80.29000000000001
		2008q4,2008,4,73.01000000000001,71.56999999999999
		2009q1,2009,1,71.62,61
		2009q2,2009,2,71.22,74.81
		2009q3,2009,3,71.69,79.56
		2009q4,2009,4,72.16,71.90000000000001
		2010q1,2010,1,71.67,61.59
		2010q2,2010,2,76.48999999999999,80.88
		2010q3,2010,3,75.75,83.51000000000001
		2010q4,2010,4,73.95999999999999,73.51000000000001
		2011q1,2011,1,80.95999999999999,71.79000000000001
		2011q2,2011,2,82.09999999999999,86.48
		2011q3,2011,3,82.01000000000001,89.47
		2011q4,2011,4,82.98,81.58
		2012q1,2012,1,84.87,76.64
		2012q2,2012,2,85.43000000000001,88.84999999999999
		2012q3,2012,3,86.25,92.67
		2012q4,2012,4,84.65000000000001,82.17
		2013q1,2013,1,81.97,71.89
		2013q2,2013,2,84.61,88.98
		2013q3,2013,3,86.52,93.91
		2013q4,2013,4,85.79000000000001,82.83
		2014q1,2014,1,89.56,80.16
		2014q2,2014,2,86.36,89.77
		2014q3,2014,3,86.55,93.93000000000001
		2014q4,2014,4,86.47,83.7
		2015q1,2015,1,85.73999999999999,76.8
		2015q2,2015,2,85.75,89.17
		2015q3,2015,3,85.87,93.36
		2015q4,2015,4,87.04000000000001,85.8
		2016q1,2016,1,89.58,80.06
		2016q2,2016,2,89.81,96.13
		2016q3,2016,3,90.20999999999999,97.39
		2016q4,2016,4,91.09,88.76000000000001
		2017q1,2017,1,89.67,83.06999999999999
		2017q2,2017,2,92.52,95.69
		2017q3,2017,3,92.34999999999999,98.36
		2017q4,2017,4,92.23999999999999,88.5
		2018q1,2018,1,92.31999999999999,84.45999999999999
		2018q2,2018,2,94.45999999999999,98.62
		2018q3,2018,3,95.37,101.2
		2018q4,2018,4,95.98,92.38
		2019q1,2019,1,95.64,88
		2019q2,2019,2,95.43000000000001,98.51000000000001
		2019q3,2019,3,96.03,102.82
		2019q4,2019,4,96.65000000000001,92.65000000000001
		2020q1,2020,1,100.77,94.16
		2020q2,2020,2,98.52,101.55
		2020q3,2020,3,97.33,104.27
		2020q4,2020,4,101.69,100.02
		2021q1,2021,1,96.83,90.31999999999999
		2021q2,2021,2,99.59999999999999,103.63
		2021q3,2021,3,95.84999999999999,102.55
		2021q4,2021,4,95.43000000000001,93.62
		2022q1,2022,1,96.84999999999999,91.44
		2022q2,2022,2,93.47,97.36
		2022q3,2022,3,91.92,98.20999999999999
		2022q4,2022,4,89.81999999999999,86.73999999999999
		2023q1,2023,1,87.86,83.11
		2023q2,2023,2,88.23,91.06999999999999
		2023q3,2023,3,86.53,91.69
		2023q4,2023,4,84.34,80.73999999999999
		2024q1,2024,1,83.95999999999999,77.84999999999999
		2024q2,2024,2,82.2,85.94
		2024q3,2024,3,81.02,87.05
		2024q4,2024,4,81.19,76.91
		2025q1,2025,1,81.14,74.95999999999999
		2025q2,2025,2,78.90000000000001,81.76000000000001

00_original_index/03_data/data_given/building_permits_apartments_bw_m.csv

0 → 100644

+272 −0

Original line number	Diff line number	Diff line
		date,year,month,permits_apartments
		2003m1,2003,1,4006
		2003m2,2003,2,3478
		2003m3,2003,3,3201
		2003m4,2003,4,2573
		2003m5,2003,5,2778
		2003m6,2003,6,2199
		2003m7,2003,7,2667
		2003m8,2003,8,2712
		2003m9,2003,9,2190
		2003m10,2003,10,2664
		2003m11,2003,11,2844
		2003m12,2003,12,4320
		2004m1,2004,1,3644
		2004m2,2004,2,3615
		2004m3,2004,3,3711
		2004m4,2004,4,3165
		2004m5,2004,5,2412
		2004m6,2004,6,2079
		2004m7,2004,7,2409
		2004m8,2004,8,2634
		2004m9,2004,9,2192
		2004m10,2004,10,2219
		2004m11,2004,11,2754
		2004m12,2004,12,2999
		2005m1,2005,1,2681
		2005m2,2005,2,2470
		2005m3,2005,3,2666
		2005m4,2005,4,2842
		2005m5,2005,5,2333
		2005m6,2005,6,2358
		2005m7,2005,7,2604
		2005m8,2005,8,2685
		2005m9,2005,9,2679
		2005m10,2005,10,2735
		2005m11,2005,11,2709
		2005m12,2005,12,4341
		2006m1,2006,1,3216
		2006m2,2006,2,3636
		2006m3,2006,3,3995
		2006m4,2006,4,2379
		2006m5,2006,5,3437
		2006m6,2006,6,2293
		2006m7,2006,7,2387
		2006m8,2006,8,2873
		2006m9,2006,9,1911
		2006m10,2006,10,2071
		2006m11,2006,11,2668
		2006m12,2006,12,2222
		2007m1,2007,1,1887
		2007m2,2007,2,1598
		2007m3,2007,3,1958
		2007m4,2007,4,1884
		2007m5,2007,5,2349
		2007m6,2007,6,1704
		2007m7,2007,7,2049
		2007m8,2007,8,2070
		2007m9,2007,9,1846
		2007m10,2007,10,2319
		2007m11,2007,11,2131
		2007m12,2007,12,1706
		2008m1,2008,1,2020
		2008m2,2008,2,1880
		2008m3,2008,3,2028
		2008m4,2008,4,2155
		2008m5,2008,5,1942
		2008m6,2008,6,2083
		2008m7,2008,7,2216
		2008m8,2008,8,1708
		2008m9,2008,9,1886
		2008m10,2008,10,1993
		2008m11,2008,11,1288
		2008m12,2008,12,1635
		2009m1,2009,1,1234
		2009m2,2009,2,1480
		2009m3,2009,3,1631
		2009m4,2009,4,1622
		2009m5,2009,5,2635
		2009m6,2009,6,2379
		2009m7,2009,7,2209
		2009m8,2009,8,2083
		2009m9,2009,9,1956
		2009m10,2009,10,2236
		2009m11,2009,11,1879
		2009m12,2009,12,1990
		2010m1,2010,1,1050
		2010m2,2010,2,1518
		2010m3,2010,3,2691
		2010m4,2010,4,1873
		2010m5,2010,5,1966
		2010m6,2010,6,2203
		2010m7,2010,7,3058
		2010m8,2010,8,2280
		2010m9,2010,9,2016
		2010m10,2010,10,2154
		2010m11,2010,11,2912
		2010m12,2010,12,2038
		2011m1,2011,1,1736
		2011m2,2011,2,2196
		2011m3,2011,3,2976
		2011m4,2011,4,2260
		2011m5,2011,5,2891
		2011m6,2011,6,2605
		2011m7,2011,7,2833
		2011m8,2011,8,2714
		2011m9,2011,9,2866
		2011m10,2011,10,2254
		2011m11,2011,11,2054
		2011m12,2011,12,2642
		2012m1,2012,1,1972
		2012m2,2012,2,1990
		2012m3,2012,3,2352
		2012m4,2012,4,2899
		2012m5,2012,5,2917
		2012m6,2012,6,3161
		2012m7,2012,7,2948
		2012m8,2012,8,3118
		2012m9,2012,9,2471
		2012m10,2012,10,2653
		2012m11,2012,11,2150
		2012m12,2012,12,2942
		2013m1,2013,1,2652
		2013m2,2013,2,2238
		2013m3,2013,3,2873
		2013m4,2013,4,3327
		2013m5,2013,5,2500
		2013m6,2013,6,2513
		2013m7,2013,7,3643
		2013m8,2013,8,3027
		2013m9,2013,9,2803
		2013m10,2013,10,2640
		2013m11,2013,11,2319
		2013m12,2013,12,2627
		2014m1,2014,1,2314
		2014m2,2014,2,2226
		2014m3,2014,3,3066
		2014m4,2014,4,3394
		2014m5,2014,5,2792
		2014m6,2014,6,2577
		2014m7,2014,7,3043
		2014m8,2014,8,2677
		2014m9,2014,9,2597
		2014m10,2014,10,2654
		2014m11,2014,11,2695
		2014m12,2014,12,2930
		2015m1,2015,1,2224
		2015m2,2015,2,3493
		2015m3,2015,3,2771
		2015m4,2015,4,2441
		2015m5,2015,5,2568
		2015m6,2015,6,2707
		2015m7,2015,7,3147
		2015m8,2015,8,3267
		2015m9,2015,9,3610
		2015m10,2015,10,3286
		2015m11,2015,11,2518
		2015m12,2015,12,3577
		2016m1,2016,1,2625
		2016m2,2016,2,4212
		2016m3,2016,3,3742
		2016m4,2016,4,3427
		2016m5,2016,5,3713
		2016m6,2016,6,4234
		2016m7,2016,7,3053
		2016m8,2016,8,5384
		2016m9,2016,9,3153
		2016m10,2016,10,3121
		2016m11,2016,11,3630
		2016m12,2016,12,3928
		2017m1,2017,1,3296
		2017m2,2017,2,2643
		2017m3,2017,3,2841
		2017m4,2017,4,3343
		2017m5,2017,5,3416
		2017m6,2017,6,3307
		2017m7,2017,7,3221
		2017m8,2017,8,3376
		2017m9,2017,9,3073
		2017m10,2017,10,3126
		2017m11,2017,11,3057
		2017m12,2017,12,3810
		2018m1,2018,1,3058
		2018m2,2018,2,3761
		2018m3,2018,3,3575
		2018m4,2018,4,3514
		2018m5,2018,5,3716
		2018m6,2018,6,3199
		2018m7,2018,7,3221
		2018m8,2018,8,4378
		2018m9,2018,9,2845
		2018m10,2018,10,3127
		2018m11,2018,11,3164
		2018m12,2018,12,3111
		2019m1,2019,1,3139
		2019m2,2019,2,2570
		2019m3,2019,3,2258
		2019m4,2019,4,3779
		2019m5,2019,5,3461
		2019m6,2019,6,3138
		2019m7,2019,7,3635
		2019m8,2019,8,4199
		2019m9,2019,9,3720
		2019m10,2019,10,3509
		2019m11,2019,11,3286
		2019m12,2019,12,3513
		2020m1,2020,1,3781
		2020m2,2020,2,2800
		2020m3,2020,3,3136
		2020m4,2020,4,3722
		2020m5,2020,5,3063
		2020m6,2020,6,3558
		2020m7,2020,7,4161
		2020m8,2020,8,3632
		2020m9,2020,9,3615
		2020m10,2020,10,4287
		2020m11,2020,11,4287
		2020m12,2020,12,3451
		2021m1,2021,1,2740
		2021m2,2021,2,4426
		2021m3,2021,3,5353
		2021m4,2021,4,3391
		2021m5,2021,5,3779
		2021m6,2021,6,4188
		2021m7,2021,7,3541
		2021m8,2021,8,4485
		2021m9,2021,9,2741
		2021m10,2021,10,4117
		2021m11,2021,11,3028
		2021m12,2021,12,4155
		2022m1,2022,1,3843
		2022m2,2022,2,2985
		2022m3,2022,3,3545
		2022m4,2022,4,3875
		2022m5,2022,5,3481
		2022m6,2022,6,3565
		2022m7,2022,7,3999
		2022m8,2022,8,3444
		2022m9,2022,9,2996
		2022m10,2022,10,3205
		2022m11,2022,11,3489
		2022m12,2022,12,3745
		2023m1,2023,1,2786
		2023m2,2023,2,3071
		2023m3,2023,3,3110
		2023m4,2023,4,2109
		2023m5,2023,5,2782
		2023m6,2023,6,2310
		2023m7,2023,7,2548
		2023m8,2023,8,1857
		2023m9,2023,9,2033
		2023m10,2023,10,1816
		2023m11,2023,11,1722
		2023m12,2023,12,2184
		2024m1,2024,1,1257
		2024m2,2024,2,2033
		2024m3,2024,3,1572
		2024m4,2024,4,1502
		2024m5,2024,5,1835
		2024m6,2024,6,1390
		2024m7,2024,7,1746
		2024m8,2024,8,2089
		2024m9,2024,9,1464
		2024m10,2024,10,2070
		2024m11,2024,11,1433
		2024m12,2024,12,2282
		2025m1,2025,1,1512
		2025m2,2025,2,1374
		2025m3,2025,3,1651
		2025m4,2025,4,1934
		2025m5,2025,5,1710
		2025m6,2025,6,2556
		2025m7,2025,7,2835

00_original_index/03_data/data_given/construction_cost_index_labor_material_D_q.csv

0 → 100644

+103 −0

Original line number	Diff line number	Diff line
		date,year,quarter,labor_costs,material_costs,overall_costs
		2000q1,2000,1,61.4,63.3,62.6
		2000q2,2000,2,62.2,63.9,63.2
		2000q3,2000,3,62.6,63.5,63.1
		2000q4,2000,4,62.9,63.5,63.3
		2001q1,2001,1,62.9,63.4,63.2
		2001q2,2001,2,63.9,63.3,63.5
		2001q3,2001,3,63.8,63.3,63.5
		2001q4,2001,4,63.7,63.3,63.5
		2002q1,2002,1,64.90000000000001,63.1,63.8
		2002q2,2002,2,65.09999999999999,63.4,64.09999999999999
		2002q3,2002,3,65.40000000000001,63.5,64.2
		2002q4,2002,4,65.2,63.1,63.9
		2003q1,2003,1,66.7,63.4,64.7
		2003q2,2003,2,67.40000000000001,63.6,65.09999999999999
		2003q3,2003,3,66.5,63.4,64.59999999999999
		2003q4,2003,4,66,63.5,64.5
		2004q1,2004,1,67.2,64.5,65.59999999999999
		2004q2,2004,2,67,67,67
		2004q3,2004,3,67.09999999999999,67,67
		2004q4,2004,4,65.5,67,66.40000000000001
		2005q1,2005,1,67.40000000000001,67.5,67.5
		2005q2,2005,2,67.8,67.5,67.59999999999999
		2005q3,2005,3,67.40000000000001,67.8,67.59999999999999
		2005q4,2005,4,66.09999999999999,68.2,67.40000000000001
		2006q1,2006,1,68.5,68.90000000000001,68.7
		2006q2,2006,2,66.09999999999999,70,68.5
		2006q3,2006,3,65.59999999999999,71.59999999999999,69.3
		2006q4,2006,4,66.59999999999999,72.3,70.09999999999999
		2007q1,2007,1,66.90000000000001,73.3,70.8
		2007q2,2007,2,66.8,74.8,71.7
		2007q3,2007,3,68.3,74.3,72
		2007q4,2007,4,68.8,73.40000000000001,71.59999999999999
		2008q1,2008,1,69.40000000000001,74.59999999999999,72.59999999999999
		2008q2,2008,2,69.3,76.7,73.8
		2008q3,2008,3,70.59999999999999,78,75.09999999999999
		2008q4,2008,4,71.8,75.59999999999999,74.09999999999999
		2009q1,2009,1,72.90000000000001,75.09999999999999,74.2
		2009q2,2009,2,72.5,74.90000000000001,74
		2009q3,2009,3,72.7,74.90000000000001,74
		2009q4,2009,4,73.40000000000001,74.90000000000001,74.3
		2010q1,2010,1,73.7,75.40000000000001,74.8
		2010q2,2010,2,73.3,77.40000000000001,75.90000000000001
		2010q3,2010,3,73.5,77.5,76
		2010q4,2010,4,74.40000000000001,78.40000000000001,76.90000000000001
		2011q1,2011,1,74.2,79.8,77.7
		2011q2,2011,2,75.40000000000001,80.5,78.59999999999999
		2011q3,2011,3,75.59999999999999,81,79
		2011q4,2011,4,76.40000000000001,81.09999999999999,79.40000000000001
		2012q1,2012,1,77.09999999999999,81.59999999999999,79.90000000000001
		2012q2,2012,2,77.59999999999999,81.90000000000001,80.3
		2012q3,2012,3,77.90000000000001,81.90000000000001,80.40000000000001
		2012q4,2012,4,77.59999999999999,82.09999999999999,80.40000000000001
		2013q1,2013,1,78.2,82.40000000000001,80.8
		2013q2,2013,2,77.3,82.59999999999999,80.59999999999999
		2013q3,2013,3,76.8,82.90000000000001,80.59999999999999
		2013q4,2013,4,77.3,83.2,81
		2014q1,2014,1,78.3,83.5,81.59999999999999
		2014q2,2014,2,77.8,83.5,81.40000000000001
		2014q3,2014,3,78.2,83.7,81.7
		2014q4,2014,4,78.7,83.5,81.7
		2015q1,2015,1,80.7,83.8,82.59999999999999
		2015q2,2015,2,80.3,84.2,82.7
		2015q3,2015,3,80.40000000000001,84,82.7
		2015q4,2015,4,80.90000000000001,83.3,82.40000000000001
		2016q1,2016,1,81.7,83.3,82.7
		2016q2,2016,2,82.3,84.2,83.5
		2016q3,2016,3,83.09999999999999,84.7,84.09999999999999
		2016q4,2016,4,84.2,84.59999999999999,84.5
		2017q1,2017,1,85.8,85.40000000000001,85.5
		2017q2,2017,2,86.40000000000001,86,86.09999999999999
		2017q3,2017,3,87.3,86.7,86.90000000000001
		2017q4,2017,4,88.7,87.5,87.90000000000001
		2018q1,2018,1,89.59999999999999,88.59999999999999,89
		2018q2,2018,2,90.59999999999999,89.2,89.7
		2018q3,2018,3,91.09999999999999,89.7,90.2
		2018q4,2018,4,91.2,89.90000000000001,90.40000000000001
		2019q1,2019,1,91.5,90.59999999999999,90.90000000000001
		2019q2,2019,2,94,91.09999999999999,92.2
		2019q3,2019,3,92.8,91,91.7
		2019q4,2019,4,94.59999999999999,90.5,92
		2020q1,2020,1,95.2,91.5,92.90000000000001
		2020q2,2020,2,96.2,91.5,93.3
		2020q3,2020,3,98.3,91.59999999999999,94.09999999999999
		2020q4,2020,4,96.59999999999999,92.2,93.8
		2021q1,2021,1,96.59999999999999,94.3,95.3
		2021q2,2021,2,98.5,97.5,97.90000000000001
		2021q3,2021,3,103,103.4,103.2
		2021q4,2021,4,101.8,104.8,103.6
		2022q1,2022,1,104.2,109.5,107.4
		2022q2,2022,2,106.7,117.6,113.3
		2022q3,2022,3,106.4,119.7,114.5
		2022q4,2022,4,111.9,119.8,116.7
		2023q1,2023,1,107.8,122.1,116.6
		2023q2,2023,2,110.7,121.2,117.1
		2023q3,2023,3,111.5,119.8,116.7
		2023q4,2023,4,114.3,119.1,117.3
		2024q1,2024,1,116,119.9,118.3
		2024q2,2024,2,117.2,119.9,118.8
		2024q3,2024,3,117.2,120,118.8
		2024q4,2024,4,119,119.6,119.3
		2025q1,2025,1,120.6,120.2,120.3
		2025q2,2025,2,121.7,121.4,121.4

00_original_index/03_data/data_given/construction_prices_bw_q.csv

0 → 100644

+123 −0

Original line number	Diff line number	Diff line
		year,quarter,date,construction_price_index
		1995,1,1995q1,60.8
		1995,2,1995q2,61
		1995,3,1995q3,61
		1995,4,1995q4,60.7
		1996,1,1996q1,60.2
		1996,2,1996q2,60.1
		1996,3,1996q3,59.9
		1996,4,1996q4,59.5
		1997,1,1997q1,59.1
		1997,2,1997q2,59
		1997,3,1997q3,59
		1997,4,1997q4,59
		1998,1,1998q1,59
		1998,2,1998q2,59.4
		1998,3,1998q3,59.5
		1998,4,1998q4,59.4
		1999,1,1999q1,59.2
		1999,2,1999q2,59.4
		1999,3,1999q3,59.6
		1999,4,1999q4,59.7
		2000,1,2000q1,59.8
		2000,2,2000q2,60.1
		2000,3,2000q3,60.3
		2000,4,2000q4,60.5
		2001,1,2001q1,60.5
		2001,2,2001q2,60.6
		2001,3,2001q3,60.8
		2001,4,2001q4,60.7
		2002,1,2002q1,60.9
		2002,2,2002q2,60.9
		2002,3,2002q3,60.9
		2002,4,2002q4,60.8
		2003,1,2003q1,60.5
		2003,2,2003q2,60.5
		2003,3,2003q3,60.5
		2003,4,2003q4,60.3
		2004,1,2004q1,60.5
		2004,2,2004q2,61.3
		2004,3,2004q3,61.6
		2004,4,2004q4,61.6
		2005,1,2005q1,61.6
		2005,2,2005q2,61.6
		2005,3,2005q3,61.8
		2005,4,2005q4,61.6
		2006,1,2006q1,62.1
		2006,2,2006q2,62.6
		2006,3,2006q3,63.5
		2006,4,2006q4,64.3
		2007,1,2007q1,67.09999999999999
		2007,2,2007q2,67.5
		2007,3,2007q3,67.7
		2007,4,2007q4,68
		2008,1,2008q1,68.7
		2008,2,2008q2,69.5
		2008,3,2008q3,70.3
		2008,4,2008q4,69.8
		2009,1,2009q1,70.2
		2009,2,2009q2,69.90000000000001
		2009,3,2009q3,70.09999999999999
		2009,4,2009q4,69.90000000000001
		2010,1,2010q1,70
		2010,2,2010q2,70.59999999999999
		2010,3,2010q3,70.90000000000001
		2010,4,2010q4,71
		2011,1,2011q1,71.90000000000001
		2011,2,2011q2,72.7
		2011,3,2011q3,73.09999999999999
		2011,4,2011q4,73.3
		2012,1,2012q1,74.09999999999999
		2012,2,2012q2,74.5
		2012,3,2012q3,74.7
		2012,4,2012q4,74.90000000000001
		2013,1,2013q1,75.40000000000001
		2013,2,2013q2,75.7
		2013,3,2013q3,76.09999999999999
		2013,4,2013q4,76.3
		2014,1,2014q1,76.90000000000001
		2014,2,2014q2,77.2
		2014,3,2014q3,77.5
		2014,4,2014q4,77.8
		2015,1,2015q1,78.59999999999999
		2015,2,2015q2,79
		2015,3,2015q3,79.3
		2015,4,2015q4,79.3
		2016,1,2016q1,80.09999999999999
		2016,2,2016q2,80.8
		2016,3,2016q3,81.2
		2016,4,2016q4,81.40000000000001
		2017,1,2017q1,82.5
		2017,2,2017q2,83.2
		2017,3,2017q3,83.59999999999999
		2017,4,2017q4,84.3
		2018,1,2018q1,85.8
		2018,2,2018q2,86.90000000000001
		2018,3,2018q3,88
		2018,4,2018q4,88.8
		2019,1,2019q1,89.90000000000001
		2019,2,2019q2,90.40000000000001
		2019,3,2019q3,91
		2019,4,2019q4,91.40000000000001
		2020,1,2020q1,92.5
		2020,2,2020q2,92.7
		2020,3,2020q3,90.5
		2020,4,2020q4,91
		2021,1,2021q1,94.59999999999999
		2021,2,2021q2,99.09999999999999
		2021,3,2021q3,102.2
		2021,4,2021q4,104.1
		2022,1,2022q1,107.9
		2022,2,2022q2,114.1
		2022,3,2022q3,116.4
		2022,4,2022q4,119
		2023,1,2023q1,121.5
		2023,2,2023q2,122.3
		2023,3,2023q3,123.3
		2023,4,2023q4,123.9
		2024,1,2024q1,125.2
		2024,2,2024q2,126.6
		2024,3,2024q3,127.6
		2024,4,2024q4,128.1
		2025,1,2025q1,129.7
		2025,2,2025q2,130.7

00_original_index/03_data/data_given/earnings_construction_bw_m.csv

0 → 100644

+367 −0

Original line number	Diff line number	Diff line
		date,year,month,earnings
		1995m1,1995,1,191346
		1995m2,1995,2,196587
		1995m3,1995,3,225363
		1995m4,1995,4,214634
		1995m5,1995,5,239265
		1995m6,1995,6,233765
		1995m7,1995,7,232195
		1995m8,1995,8,247025
		1995m9,1995,9,224324
		1995m10,1995,10,230267
		1995m11,1995,11,344795
		1995m12,1995,12,210275
		1996m1,1996,1,208150
		1996m2,1996,2,175680
		1996m3,1996,3,185208
		1996m4,1996,4,209474
		1996m5,1996,5,214442
		1996m6,1996,6,202302
		1996m7,1996,7,220615
		1996m8,1996,8,216996
		1996m9,1996,9,204528
		1996m10,1996,10,209661
		1996m11,1996,11,281961
		1996m12,1996,12,201807
		1997m1,1997,1,176499
		1997m2,1997,2,162540
		1997m3,1997,3,173667
		1997m4,1997,4,189638
		1997m5,1997,5,188466
		1997m6,1997,6,188073
		1997m7,1997,7,198019
		1997m8,1997,8,188643
		1997m9,1997,9,188471
		1997m10,1997,10,188684
		1997m11,1997,11,238227
		1997m12,1997,12,186367
		1998m1,1998,1,164968
		1998m2,1998,2,149507
		1998m3,1998,3,168128
		1998m4,1998,4,183321
		1998m5,1998,5,174334
		1998m6,1998,6,182916
		1998m7,1998,7,187890
		1998m8,1998,8,181140
		1998m9,1998,9,181526
		1998m10,1998,10,178993
		1998m11,1998,11,228938
		1998m12,1998,12,178846
		1999m1,1999,1,159044
		1999m2,1999,2,142927
		1999m3,1999,3,170883
		1999m4,1999,4,185997
		1999m5,1999,5,175294
		1999m6,1999,6,185147
		1999m7,1999,7,186109
		1999m8,1999,8,185920
		1999m9,1999,9,183226
		1999m10,1999,10,179039
		1999m11,1999,11,230041
		1999m12,1999,12,181307
		2000m1,2000,1,157178
		2000m2,2000,2,158229
		2000m3,2000,3,170830
		2000m4,2000,4,173834
		2000m5,2000,5,181454
		2000m6,2000,6,179935
		2000m7,2000,7,176174
		2000m8,2000,8,185799
		2000m9,2000,9,174393
		2000m10,2000,10,175515
		2000m11,2000,11,223507
		2000m12,2000,12,171181
		2001m1,2001,1,160073
		2001m2,2001,2,148694
		2001m3,2001,3,155218
		2001m4,2001,4,169286
		2001m5,2001,5,172223
		2001m6,2001,6,168206
		2001m7,2001,7,173938
		2001m8,2001,8,178012
		2001m9,2001,9,161894
		2001m10,2001,10,171047
		2001m11,2001,11,208272
		2001m12,2001,12,158394
		2002m1,2002,1,147075
		2002m2,2002,2,138352
		2002m3,2002,3,146973
		2002m4,2002,4,164249
		2002m5,2002,5,163590
		2002m6,2002,6,156235
		2002m7,2002,7,170466
		2002m8,2002,8,168158
		2002m9,2002,9,159801
		2002m10,2002,10,162797
		2002m11,2002,11,192606
		2002m12,2002,12,154899
		2003m1,2003,1,140009
		2003m2,2003,2,119926
		2003m3,2003,3,138495
		2003m4,2003,4,154032
		2003m5,2003,5,149191
		2003m6,2003,6,149158
		2003m7,2003,7,156037
		2003m8,2003,8,149895
		2003m9,2003,9,149615
		2003m10,2003,10,148738
		2003m11,2003,11,170896
		2003m12,2003,12,145141
		2004m1,2004,1,127278
		2004m2,2004,2,116665
		2004m3,2004,3,127436
		2004m4,2004,4,135915
		2004m5,2004,5,131430
		2004m6,2004,6,140213
		2004m7,2004,7,139123
		2004m8,2004,8,138848
		2004m9,2004,9,136190
		2004m10,2004,10,130937
		2004m11,2004,11,157360
		2004m12,2004,12,134417
		2005m1,2005,1,116226
		2005m2,2005,2,101278
		2005m3,2005,3,111233
		2005m4,2005,4,124486
		2005m5,2005,5,124470
		2005m6,2005,6,132442
		2005m7,2005,7,126541
		2005m8,2005,8,135999
		2005m9,2005,9,130222
		2005m10,2005,10,126804
		2005m11,2005,11,151897
		2005m12,2005,12,126465
		2006m1,2006,1,112787
		2006m2,2006,2,102539
		2006m3,2006,3,110784
		2006m4,2006,4,122693
		2006m5,2006,5,130003
		2006m6,2006,6,127362
		2006m7,2006,7,126927
		2006m8,2006,8,130467
		2006m9,2006,9,124097
		2006m10,2006,10,128132
		2006m11,2006,11,155044
		2006m12,2006,12,126409
		2007m1,2007,1,119061
		2007m2,2007,2,108794
		2007m3,2007,3,115935
		2007m4,2007,4,125683
		2007m5,2007,5,128498
		2007m6,2007,6,127386
		2007m7,2007,7,132163
		2007m8,2007,8,133989
		2007m9,2007,9,128487
		2007m10,2007,10,136737
		2007m11,2007,11,163652
		2007m12,2007,12,127595
		2008m1,2008,1,126193
		2008m2,2008,2,119728
		2008m3,2008,3,116646
		2008m4,2008,4,134256
		2008m5,2008,5,132248
		2008m6,2008,6,130800
		2008m7,2008,7,137801
		2008m8,2008,8,130569
		2008m9,2008,9,134231
		2008m10,2008,10,133459
		2008m11,2008,11,156935
		2008m12,2008,12,128865
		2009m1,2009,1,113069
		2009m2,2009,2,105648
		2009m3,2009,3,118308
		2009m4,2009,4,135329
		2009m5,2009,5,127182
		2009m6,2009,6,132877
		2009m7,2009,7,137725
		2009m8,2009,8,127919
		2009m9,2009,9,131188
		2009m10,2009,10,130531
		2009m11,2009,11,157422
		2009m12,2009,12,127809
		2010m1,2010,1,108396
		2010m2,2010,2,102159
		2010m3,2010,3,119469
		2010m4,2010,4,133165
		2010m5,2010,5,128248
		2010m6,2010,6,134043
		2010m7,2010,7,140106
		2010m8,2010,8,134492
		2010m9,2010,9,134397
		2010m10,2010,10,132220
		2010m11,2010,11,165777
		2010m12,2010,12,125248
		2011m1,2011,1,116650
		2011m2,2011,2,114866
		2011m3,2011,3,130434
		2011m4,2011,4,133706
		2011m5,2011,5,136713
		2011m6,2011,6,139890
		2011m7,2011,7,144848
		2011m8,2011,8,143013
		2011m9,2011,9,140518
		2011m10,2011,10,137804
		2011m11,2011,11,174149
		2011m12,2011,12,138565
		2012m1,2012,1,128776
		2012m2,2012,2,113455
		2012m3,2012,3,131674
		2012m4,2012,4,141172
		2012m5,2012,5,142497
		2012m6,2012,6,144248
		2012m7,2012,7,152673
		2012m8,2012,8,148343
		2012m9,2012,9,139363
		2012m10,2012,10,148782
		2012m11,2012,11,179480
		2012m12,2012,12,136777
		2013m1,2013,1,130397
		2013m2,2013,2,117021
		2013m3,2013,3,128130
		2013m4,2013,4,148111
		2013m5,2013,5,149349
		2013m6,2013,6,145714
		2013m7,2013,7,164212
		2013m8,2013,8,152462
		2013m9,2013,9,150503
		2013m10,2013,10,155480
		2013m11,2013,11,186420
		2013m12,2013,12,148653
		2014m1,2014,1,143062
		2014m2,2014,2,133427
		2014m3,2014,3,145170
		2014m4,2014,4,155357
		2014m5,2014,5,153129
		2014m6,2014,6,155747
		2014m7,2014,7,171086
		2014m8,2014,8,156904
		2014m9,2014,9,160041
		2014m10,2014,10,160929
		2014m11,2014,11,192442
		2014m12,2014,12,157890
		2015m1,2015,1,143952
		2015m2,2015,2,133967
		2015m3,2015,3,148584
		2015m4,2015,4,163497
		2015m5,2015,5,156095
		2015m6,2015,6,164969
		2015m7,2015,7,176260
		2015m8,2015,8,163367
		2015m9,2015,9,168150
		2015m10,2015,10,167348
		2015m11,2015,11,205376
		2015m12,2015,12,165373
		2016m1,2016,1,146025
		2016m2,2016,2,150334
		2016m3,2016,3,164759
		2016m4,2016,4,178244
		2016m5,2016,5,174672
		2016m6,2016,6,181072
		2016m7,2016,7,186530
		2016m8,2016,8,187110
		2016m9,2016,9,182476
		2016m10,2016,10,178095
		2016m11,2016,11,229331
		2016m12,2016,12,181263
		2017m1,2017,1,160961
		2017m2,2017,2,168005
		2017m3,2017,3,181688
		2017m4,2017,4,197663
		2017m5,2017,5,200833
		2017m6,2017,6,198999
		2017m7,2017,7,205297
		2017m8,2017,8,204353
		2017m9,2017,9,197266
		2017m10,2017,10,199884
		2017m11,2017,11,253462
		2017m12,2017,12,193100
		2018m1,2018,1,186827
		2018m2,2018,2,176238
		2018m3,2018,3,189147
		2018m4,2018,4,216771
		2018m5,2018,5,218882
		2018m6,2018,6,216842
		2018m7,2018,7,231762
		2018m8,2018,8,222086
		2018m9,2018,9,212642
		2018m10,2018,10,227179
		2018m11,2018,11,287632
		2018m12,2018,12,214013
		2019m1,2019,1,203738
		2019m2,2019,2,204420
		2019m3,2019,3,209520
		2019m4,2019,4,245370
		2019m5,2019,5,237401
		2019m6,2019,6,241129
		2019m7,2019,7,252974
		2019m8,2019,8,235463
		2019m9,2019,9,234293
		2019m10,2019,10,243154
		2019m11,2019,11,303976
		2019m12,2019,12,237088
		2020m1,2020,1,223516
		2020m2,2020,2,213089
		2020m3,2020,3,226695
		2020m4,2020,4,257505
		2020m5,2020,5,236936
		2020m6,2020,6,248032
		2020m7,2020,7,267020
		2020m8,2020,8,242109
		2020m9,2020,9,250395
		2020m10,2020,10,248588
		2020m11,2020,11,314345
		2020m12,2020,12,252501
		2021m1,2021,1,214393
		2021m2,2021,2,215915
		2021m3,2021,3,244247
		2021m4,2021,4,271051
		2021m5,2021,5,249044
		2021m6,2021,6,256036
		2021m7,2021,7,270829
		2021m8,2021,8,255772
		2021m9,2021,9,259023
		2021m10,2021,10,252036
		2021m11,2021,11,338460
		2021m12,2021,12,265856
		2022m1,2022,1,237727
		2022m2,2022,2,233239
		2022m3,2022,3,257924
		2022m4,2022,4,277587
		2022m5,2022,5,279710
		2022m6,2022,6,269076
		2022m7,2022,7,276563
		2022m8,2022,8,274242
		2022m9,2022,9,287485
		2022m10,2022,10,265866
		2022m11,2022,11,362855
		2022m12,2022,12,268129
		2023m1,2023,1,247093
		2023m2,2023,2,244533
		2023m3,2023,3,268013
		2023m4,2023,4,290274
		2023m5,2023,5,295160
		2023m6,2023,6,285585
		2023m7,2023,7,295712
		2023m8,2023,8,286921
		2023m9,2023,9,282691
		2023m10,2023,10,286166
		2023m11,2023,11,371700
		2023m12,2023,12,273310
		2024m1,2024,1,257014
		2024m2,2024,2,260230
		2024m3,2024,3,262489
		2024m4,2024,4,305230
		2024m5,2024,5,292742
		2024m6,2024,6,288570
		2024m7,2024,7,320208
		2024m8,2024,8,294107
		2024m9,2024,9,289864
		2024m10,2024,10,309809
		2024m11,2024,11,390248
		2024m12,2024,12,294791
		2025m1,2025,1,280441
		2025m2,2025,2,267892
		2025m3,2025,3,287112
		2025m4,2025,4,333663
		2025m5,2025,5,312100
		2025m6,2025,6,310043

00_original_index/03_data/data_given/hours_apartment_bw_m.csv

0 → 100644

+367 −0

Original line number	Diff line number	Diff line
		date,year,month,hours_apartment
		1995m1,1995,1,2172
		1995m2,1995,2,3385
		1995m3,1995,3,3991
		1995m4,1995,4,3617
		1995m5,1995,5,4067
		1995m6,1995,6,3795
		1995m7,1995,7,3892
		1995m8,1995,8,2661
		1995m9,1995,9,3656
		1995m10,1995,10,3698
		1995m11,1995,11,3519
		1995m12,1995,12,2258
		1996m1,1996,1,2308
		1996m2,1996,2,2077
		1996m3,1996,3,3017
		1996m4,1996,4,3341
		1996m5,1996,5,3314
		1996m6,1996,6,3212
		1996m7,1996,7,3633
		1996m8,1996,8,2172
		1996m9,1996,9,3340
		1996m10,1996,10,3304
		1996m11,1996,11,2912
		1996m12,1996,12,2133
		1997m1,1997,1,1623
		1997m2,1997,2,2202
		1997m3,1997,3,2630
		1997m4,1997,4,3149
		1997m5,1997,5,2507
		1997m6,1997,6,2994
		1997m7,1997,7,3148
		1997m8,1997,8,1737
		1997m9,1997,9,2929
		1997m10,1997,10,2953
		1997m11,1997,11,2537
		1997m12,1997,12,1905
		1998m1,1998,1,1662
		1998m2,1998,2,1848
		1998m3,1998,3,2544
		1998m4,1998,4,2507
		1998m5,1998,5,2408
		1998m6,1998,6,2495
		1998m7,1998,7,2776
		1998m8,1998,8,1609
		1998m9,1998,9,2577
		1998m10,1998,10,2560
		1998m11,1998,11,2282
		1998m12,1998,12,1607
		1999m1,1999,1,1485
		1999m2,1999,2,1402
		1999m3,1999,3,2430
		1999m4,1999,4,2378
		1999m5,1999,5,2254
		1999m6,1999,6,2479
		1999m7,1999,7,2549
		1999m8,1999,8,1645
		1999m9,1999,9,2504
		1999m10,1999,10,2468
		1999m11,1999,11,2267
		1999m12,1999,12,1693
		2000m1,2000,1,1428
		2000m2,2000,2,2076
		2000m3,2000,3,2239
		2000m4,2000,4,2085
		2000m5,2000,5,2530
		2000m6,2000,6,2131
		2000m7,2000,7,2276
		2000m8,2000,8,1661
		2000m9,2000,9,2226
		2000m10,2000,10,2162
		2000m11,2000,11,2082
		2000m12,2000,12,1517
		2001m1,2001,1,1353
		2001m2,2001,2,1506
		2001m3,2001,3,1806
		2001m4,2001,4,1738
		2001m5,2001,5,1930
		2001m6,2001,6,1765
		2001m7,2001,7,1948
		2001m8,2001,8,1345
		2001m9,2001,9,1763
		2001m10,2001,10,1877
		2001m11,2001,11,1598
		2001m12,2001,12,1081
		2002m1,2002,1,954
		2002m2,2002,2,1185
		2002m3,2002,3,1426
		2002m4,2002,4,1652
		2002m5,2002,5,1432
		2002m6,2002,6,1590
		2002m7,2002,7,1713
		2002m8,2002,8,1101
		2002m9,2002,9,1588
		2002m10,2002,10,1581
		2002m11,2002,11,1379
		2002m12,2002,12,1011
		2003m1,2003,1,832
		2003m2,2003,2,872
		2003m3,2003,3,1318
		2003m4,2003,4,1458
		2003m5,2003,5,1439
		2003m6,2003,6,1426
		2003m7,2003,7,1617
		2003m8,2003,8,973
		2003m9,2003,9,1515
		2003m10,2003,10,1509
		2003m11,2003,11,1359
		2003m12,2003,12,1031
		2004m1,2004,1,761
		2004m2,2004,2,997
		2004m3,2004,3,1401
		2004m4,2004,4,1418
		2004m5,2004,5,1335
		2004m6,2004,6,1509
		2004m7,2004,7,1501
		2004m8,2004,8,930
		2004m9,2004,9,1427
		2004m10,2004,10,1391
		2004m11,2004,11,1341
		2004m12,2004,12,975
		2005m1,2005,1,707
		2005m2,2005,2,658
		2005m3,2005,3,984
		2005m4,2005,4,1373
		2005m5,2005,5,1267
		2005m6,2005,6,1495
		2005m7,2005,7,1368
		2005m8,2005,8,1004
		2005m9,2005,9,1391
		2005m10,2005,10,1280
		2005m11,2005,11,1272
		2005m12,2005,12,940
		2006m1,2006,1,590
		2006m2,2006,2,828
		2006m3,2006,3,1146
		2006m4,2006,4,1175
		2006m5,2006,5,1373
		2006m6,2006,6,1323
		2006m7,2006,7,1396
		2006m8,2006,8,1061
		2006m9,2006,9,1290
		2006m10,2006,10,1349
		2006m11,2006,11,1326
		2006m12,2006,12,984
		2007m1,2007,1,796
		2007m2,2007,2,888
		2007m3,2007,3,1088
		2007m4,2007,4,1109
		2007m5,2007,5,1164
		2007m6,2007,6,1155
		2007m7,2007,7,1259
		2007m8,2007,8,894
		2007m9,2007,9,1099
		2007m10,2007,10,1239
		2007m11,2007,11,1118
		2007m12,2007,12,782
		2008m1,2008,1,852
		2008m2,2008,2,906
		2008m3,2008,3,876
		2008m4,2008,4,1094
		2008m5,2008,5,1002
		2008m6,2008,6,1098
		2008m7,2008,7,1178
		2008m8,2008,8,772
		2008m9,2008,9,1110
		2008m10,2008,10,1053
		2008m11,2008,11,966
		2008m12,2008,12,689
		2009m1,2009,1,500
		2009m2,2009,2,614
		2009m3,2009,3,981
		2009m4,2009,4,1076
		2009m5,2009,5,989
		2009m6,2009,6,1057
		2009m7,2009,7,1203
		2009m8,2009,8,780
		2009m9,2009,9,1123
		2009m10,2009,10,1161
		2009m11,2009,11,1073
		2009m12,2009,12,765
		2010m1,2010,1,439
		2010m2,2010,2,611
		2010m3,2010,3,1055
		2010m4,2010,4,1131
		2010m5,2010,5,1076
		2010m6,2010,6,1181
		2010m7,2010,7,1269
		2010m8,2010,8,916
		2010m9,2010,9,1234
		2010m10,2010,10,1257
		2010m11,2010,11,1197
		2010m12,2010,12,687
		2011m1,2011,1,793
		2011m2,2011,2,979
		2011m3,2011,3,1181
		2011m4,2011,4,1181
		2011m5,2011,5,1320
		2011m6,2011,6,1139
		2011m7,2011,7,1246
		2011m8,2011,8,977
		2011m9,2011,9,1225
		2011m10,2011,10,1251
		2011m11,2011,11,1321
		2011m12,2011,12,922
		2012m1,2012,1,871
		2012m2,2012,2,716
		2012m3,2012,3,1309
		2012m4,2012,4,1200
		2012m5,2012,5,1282
		2012m6,2012,6,1272
		2012m7,2012,7,1380
		2012m8,2012,8,1063
		2012m9,2012,9,1260
		2012m10,2012,10,1395
		2012m11,2012,11,1322
		2012m12,2012,12,822
		2013m1,2013,1,862
		2013m2,2013,2,826
		2013m3,2013,3,1167
		2013m4,2013,4,1404
		2013m5,2013,5,1219
		2013m6,2013,6,1353
		2013m7,2013,7,1505
		2013m8,2013,8,1040
		2013m9,2013,9,1354
		2013m10,2013,10,1459
		2013m11,2013,11,1369
		2013m12,2013,12,1013
		2014m1,2014,1,1087
		2014m2,2014,2,1180
		2014m3,2014,3,1276
		2014m4,2014,4,1395
		2014m5,2014,5,1350
		2014m6,2014,6,1306
		2014m7,2014,7,1499
		2014m8,2014,8,1002
		2014m9,2014,9,1423
		2014m10,2014,10,1469
		2014m11,2014,11,1387
		2014m12,2014,12,1036
		2015m1,2015,1,919
		2015m2,2015,2,924
		2015m3,2015,3,1351
		2015m4,2015,4,1384
		2015m5,2015,5,1273
		2015m6,2015,6,1402
		2015m7,2015,7,1529
		2015m8,2015,8,994
		2015m9,2015,9,1509
		2015m10,2015,10,1568
		2015m11,2015,11,1452
		2015m12,2015,12,1076
		2016m1,2016,1,811
		2016m2,2016,2,1202
		2016m3,2016,3,1381
		2016m4,2016,4,1560
		2016m5,2016,5,1391
		2016m6,2016,6,1646
		2016m7,2016,7,1579
		2016m8,2016,8,1298
		2016m9,2016,9,1621
		2016m10,2016,10,1501
		2016m11,2016,11,1558
		2016m12,2016,12,1187
		2017m1,2017,1,711
		2017m2,2017,2,1332
		2017m3,2017,3,1666
		2017m4,2017,4,1514
		2017m5,2017,5,1740
		2017m6,2017,6,1661
		2017m7,2017,7,1717
		2017m8,2017,8,1353
		2017m9,2017,9,1651
		2017m10,2017,10,1585
		2017m11,2017,11,1674
		2017m12,2017,12,1157
		2018m1,2018,1,1288
		2018m2,2018,2,1179
		2018m3,2018,3,1626
		2018m4,2018,4,1720
		2018m5,2018,5,1689
		2018m6,2018,6,1779
		2018m7,2018,7,1808
		2018m8,2018,8,1345
		2018m9,2018,9,1632
		2018m10,2018,10,1816
		2018m11,2018,11,1671
		2018m12,2018,12,1187
		2019m1,2019,1,1203
		2019m2,2019,2,1543
		2019m3,2019,3,1674
		2019m4,2019,4,1774
		2019m5,2019,5,1825
		2019m6,2019,6,1654
		2019m7,2019,7,1973
		2019m8,2019,8,1338
		2019m9,2019,9,1791
		2019m10,2019,10,1897
		2019m11,2019,11,1768
		2019m12,2019,12,1312
		2020m1,2020,1,1513
		2020m2,2020,2,1457
		2020m3,2020,3,1810
		2020m4,2020,4,1899
		2020m5,2020,5,1816
		2020m6,2020,6,1842
		2020m7,2020,7,2108
		2020m8,2020,8,1399
		2020m9,2020,9,1993
		2020m10,2020,10,2052
		2020m11,2020,11,2027
		2020m12,2020,12,1459
		2021m1,2021,1,1033
		2021m2,2021,2,1584
		2021m3,2021,3,2163
		2021m4,2021,4,1978
		2021m5,2021,5,1852
		2021m6,2021,6,1991
		2021m7,2021,7,2055
		2021m8,2021,8,1424
		2021m9,2021,9,2052
		2021m10,2021,10,2001
		2021m11,2021,11,1971
		2021m12,2021,12,1459
		2022m1,2022,1,1441
		2022m2,2022,2,1777
		2022m3,2022,3,2119
		2022m4,2022,4,1860
		2022m5,2022,5,2043
		2022m6,2022,6,1954
		2022m7,2022,7,2019
		2022m8,2022,8,1526
		2022m9,2022,9,2039
		2022m10,2022,10,1910
		2022m11,2022,11,2044
		2022m12,2022,12,1339
		2023m1,2023,1,1502
		2023m2,2023,2,1754
		2023m3,2023,3,2181
		2023m4,2023,4,1851
		2023m5,2023,5,2089
		2023m6,2023,6,2059
		2023m7,2023,7,2053
		2023m8,2023,8,1525
		2023m9,2023,9,1930
		2023m10,2023,10,1941
		2023m11,2023,11,1902
		2023m12,2023,12,1298
		2024m1,2024,1,1290
		2024m2,2024,2,1683
		2024m3,2024,3,1785
		2024m4,2024,4,1850
		2024m5,2024,5,1601
		2024m6,2024,6,1801
		2024m7,2024,7,1883
		2024m8,2024,8,1348
		2024m9,2024,9,1770
		2024m10,2024,10,1838
		2024m11,2024,11,1725
		2024m12,2024,12,1260
		2025m1,2025,1,1278
		2025m2,2025,2,1483
		2025m3,2025,3,1661
		2025m4,2025,4,1757
		2025m5,2025,5,1707
		2025m6,2025,6,1595

00_original_index/03_data/data_given/house_price_index_D_q.csv

0 → 100644

+102 −0

Original line number	Diff line number	Diff line
		date,year,quarter,index_house_price,index_existing_buildings,index_new_buildings
		2000q1,2000,1,84.3,85.5,76.8
		2000q2,2000,2,83.8,85.2,76.40000000000001
		2000q3,2000,3,84.59999999999999,86.09999999999999,76.3
		2000q4,2000,4,84.7,86.2,75.8
		2001q1,2001,1,84.90000000000001,86.7,75.5
		2001q2,2001,2,84.90000000000001,86.90000000000001,73.90000000000001
		2001q3,2001,3,84.7,86.40000000000001,75.09999999999999
		2001q4,2001,4,83.09999999999999,84.59999999999999,74.8
		2002q1,2002,1,83.3,84.7,74.5
		2002q2,2002,2,84,85.7,74
		2002q3,2002,3,83.8,85.2,75.3
		2002q4,2002,4,82.09999999999999,83.59999999999999,73.8
		2003q1,2003,1,83.3,84.8,74.5
		2003q2,2003,2,84.90000000000001,86.59999999999999,75.8
		2003q3,2003,3,83.8,85.59999999999999,73
		2003q4,2003,4,82.5,84.09999999999999,73.8
		2004q1,2004,1,83.90000000000001,85.5,75
		2004q2,2004,2,82.8,84.3,74.5
		2004q3,2004,3,81.90000000000001,83.2,74.40000000000001
		2004q4,2004,4,80.59999999999999,81.5,75
		2005q1,2005,1,84.2,85.7,75.59999999999999
		2005q2,2005,2,82.7,84.2,73.59999999999999
		2005q3,2005,3,84.40000000000001,86.09999999999999,75.09999999999999
		2005q4,2005,4,82,83.40000000000001,74.2
		2006q1,2006,1,83.2,84.7,74.3
		2006q2,2006,2,83.5,85.40000000000001,72.7
		2006q3,2006,3,82.3,83.8,73.8
		2006q4,2006,4,83,84.5,74.59999999999999
		2007q1,2007,1,80,81.40000000000001,71.90000000000001
		2007q2,2007,2,81.7,82.59999999999999,76.3
		2007q3,2007,3,81.59999999999999,82.40000000000001,76.8
		2007q4,2007,4,81.59999999999999,82.5,76.5
		2008q1,2008,1,82.8,83.8,76.7
		2008q2,2008,2,83.09999999999999,84,77.59999999999999
		2008q3,2008,3,81.59999999999999,82.2,78
		2008q4,2008,4,81.8,82.59999999999999,77.40000000000001
		2009q1,2009,1,81.8,82.09999999999999,80.09999999999999
		2009q2,2009,2,83.09999999999999,83.59999999999999,79.90000000000001
		2009q3,2009,3,82.90000000000001,83,82.90000000000001
		2009q4,2009,4,84.2,84.2,83.59999999999999
		2010q1,2010,1,83,83.09999999999999,82.59999999999999
		2010q2,2010,2,84.3,84.59999999999999,82.59999999999999
		2010q3,2010,3,84.3,84.3,84.8
		2010q4,2010,4,83.8,83.59999999999999,84.40000000000001
		2011q1,2011,1,86.09999999999999,86.2,85.40000000000001
		2011q2,2011,2,87.09999999999999,87,88.09999999999999
		2011q3,2011,3,86.7,86.3,89.5
		2011q4,2011,4,87.3,87.2,88.3
		2012q1,2012,1,88,87.8,89.09999999999999
		2012q2,2012,2,89.09999999999999,89,89.7
		2012q3,2012,3,90.40000000000001,90.40000000000001,90.59999999999999
		2012q4,2012,4,91.59999999999999,91.59999999999999,91.8
		2013q1,2013,1,91.3,91.40000000000001,90.90000000000001
		2013q2,2013,2,93.09999999999999,93.2,92
		2013q3,2013,3,92.90000000000001,93.09999999999999,91.5
		2013q4,2013,4,93,93.3,91.2
		2014q1,2014,1,93.8,94,92.3
		2014q2,2014,2,95.7,95.90000000000001,94.3
		2014q3,2014,3,96.2,96.3,96.09999999999999
		2014q4,2014,4,96.2,96.09999999999999,96.5
		2015q1,2015,1,97.8,97.8,97.5
		2015q2,2015,2,99.90000000000001,100.1,99.09999999999999
		2015q3,2015,3,100.4,100.4,100.7
		2015q4,2015,4,101.8,101.7,102.7
		2016q1,2016,1,103.9,103.8,104.2
		2016q2,2016,2,106.9,107,106.2
		2016q3,2016,3,108.8,109,107.5
		2016q4,2016,4,110.4,110.5,109.5
		2017q1,2017,1,110.9,111.2,109.3
		2017q2,2017,2,113.1,113.5,110.5
		2017q3,2017,3,115,115.3,112.9
		2017q4,2017,4,117.3,117.8,114.4
		2018q1,2018,1,118.3,118.6,116.5
		2018q2,2018,2,120.6,121.1,118.1
		2018q3,2018,3,123.1,123.5,121
		2018q4,2018,4,124.6,125.4,120
		2019q1,2019,1,124.6,125.5,119.5
		2019q2,2019,2,127.8,129,121.4
		2019q3,2019,3,129.6,130.8,123.3
		2019q4,2019,4,132.7,133.7,127.2
		2020q1,2020,1,133.8,135.3,126
		2020q2,2020,2,136.2,137.5,129.1
		2020q3,2020,3,140.3,142,131.2
		2020q4,2020,4,144.3,145.9,135.4
		2021q1,2021,1,146.3,148.7,133.3
		2021q2,2021,2,151.8,154.4,138.1
		2021q3,2021,3,158.2,161.2,142
		2021q4,2021,4,162.5,165.5,146.7
		2022q1,2022,1,164.1,167.6,145
		2022q2,2022,2,167.4,170.8,149.1
		2022q3,2022,3,166.3,169.2,150.8
		2022q4,2022,4,158.5,160.2,149.7
		2023q1,2023,1,153.7,155.1,146.4
		2023q2,2023,2,151.6,153,144.3
		2023q3,2023,3,149.3,150,145.4
		2023q4,2023,4,146.4,146.9,143.7
		2024q1,2024,1,145.8,146.2,143.1
		2024q2,2024,2,147.8,148.2,145.3
		2024q3,2024,3,149,149,147.5
		2024q4,2024,4,149.2,149.5,147
		2025q1,2025,1,151.3,151.4,149.9

00_original_index/03_data/data_given/housing_costs_index_D_m.csv

0 → 100644

+368 −0

Original line number	Diff line number	Diff line
		date,year,month,actual_rent,cost_gas,cost_oil,electricity_cost,maintenance_repair_aprtm
		1995m1,1995,1,70.3,51.4,45.8,47.6,61.7
		1995m2,1995,2,70.7,51.3,45.2,47.6,61.9
		1995m3,1995,3,70.90000000000001,51.3,44.2,47.6,62
		1995m4,1995,4,71.2,50.8,45.2,47.6,62.1
		1995m5,1995,5,71.40000000000001,50.5,45.1,47.6,62.5
		1995m6,1995,6,71.40000000000001,50.5,45.1,47.6,62.6
		1995m7,1995,7,71.59999999999999,50.5,43.5,47.6,62.6
		1995m8,1995,8,72.59999999999999,50.5,43.5,47.7,62.8
		1995m9,1995,9,72.59999999999999,50.5,45.5,47.9,62.8
		1995m10,1995,10,72.8,50.3,44.4,47.9,62.9
		1995m11,1995,11,72.8,50.3,44.9,47.9,63
		1995m12,1995,12,72.90000000000001,50.3,46.9,47.9,63
		1996m1,1996,1,73.3,49.8,49.4,44.9,63
		1996m2,1996,2,73.5,49.8,51.5,44.9,63.1
		1996m3,1996,3,73.7,49.8,51,44.9,63.2
		1996m4,1996,4,73.90000000000001,49.7,53.1,44.9,63.2
		1996m5,1996,5,74,49.7,49.4,44.9,63.2
		1996m6,1996,6,74.09999999999999,49.7,48.3,44.9,63.2
		1996m7,1996,7,74.2,49.7,49.7,44.9,63.2
		1996m8,1996,8,74.2,49.7,49.7,44.9,63.3
		1996m9,1996,9,74.3,49.7,56.9,44.9,63.3
		1996m10,1996,10,74.5,49.8,61.7,44.9,63.4
		1996m11,1996,11,74.7,49.9,57.2,44.9,63.4
		1996m12,1996,12,74.90000000000001,50,58,44.9,63.4
		1997m1,1997,1,75.40000000000001,51,62.9,45,63.4
		1997m2,1997,2,75.59999999999999,51.3,57.6,45.1,63.5
		1997m3,1997,3,75.59999999999999,51.4,51.9,45.1,63.5
		1997m4,1997,4,75.7,51.6,51.1,45.2,63.5
		1997m5,1997,5,75.8,51.6,52.2,45.2,63.5
		1997m6,1997,6,75.8,51.9,51.7,45.2,63.5
		1997m7,1997,7,76,51.9,51.8,45.2,63.5
		1997m8,1997,8,76.09999999999999,51.9,54.5,45.2,63.6
		1997m9,1997,9,76.09999999999999,51.9,52.6,45.2,63.6
		1997m10,1997,10,76.2,52,55.8,45.2,63.6
		1997m11,1997,11,76.3,52,55.1,45.2,63.5
		1997m12,1997,12,76.40000000000001,52,53.8,45.2,63.5
		1998m1,1998,1,76.5,51.9,49.4,45.2,63.5
		1998m2,1998,2,76.7,52,48.7,45.3,63.6
		1998m3,1998,3,76.8,51.9,46.5,45.3,63.7
		1998m4,1998,4,76.90000000000001,52,48.3,45.8,63.7
		1998m5,1998,5,76.90000000000001,52,46.9,45.9,64.09999999999999
		1998m6,1998,6,76.90000000000001,52,44.6,45.9,64.2
		1998m7,1998,7,77,52,44.2,45.9,64.2
		1998m8,1998,8,77,52,42.8,45.9,64.2
		1998m9,1998,9,77,52,43.1,45.9,64.3
		1998m10,1998,10,77,51.3,43.1,45.9,64.3
		1998m11,1998,11,77,51.1,42.2,45.9,64.5
		1998m12,1998,12,77,51.1,40.5,45.9,64.5
		1999m1,1999,1,77.09999999999999,50.5,41.3,45.7,64.5
		1999m2,1999,2,77.2,50.3,40.2,45.9,64.5
		1999m3,1999,3,77.2,50.3,46.7,45.9,64.5
		1999m4,1999,4,77.3,50.8,51.4,49.3,64.5
		1999m5,1999,5,77.40000000000001,50.8,50.7,49.4,64.59999999999999
		1999m6,1999,6,77.59999999999999,50.8,49.7,49.4,64.59999999999999
		1999m7,1999,7,77.59999999999999,50.6,55.4,49.3,64.59999999999999
		1999m8,1999,8,77.59999999999999,50.6,56.9,49.2,64.59999999999999
		1999m9,1999,9,77.7,50.5,60.9,48.3,64.59999999999999
		1999m10,1999,10,77.8,50.8,61.1,46.7,64.7
		1999m11,1999,11,78,51.1,63,45.9,64.7
		1999m12,1999,12,78,51.1,68.3,45.5,64.7
		2000m1,2000,1,78.09999999999999,53.4,68.3,45.2,64.7
		2000m2,2000,2,78.3,53.5,71.5,45.2,64.7
		2000m3,2000,3,78.3,53.8,75.40000000000001,45.2,64.8
		2000m4,2000,4,78.40000000000001,56.9,70,45.1,64.8
		2000m5,2000,5,78.5,57.7,74.5,45,64.8
		2000m6,2000,6,78.5,58.5,75.40000000000001,45,64.8
		2000m7,2000,7,78.5,59.2,78.40000000000001,45,64.90000000000001
		2000m8,2000,8,78.5,60.2,81.90000000000001,44.9,64.90000000000001
		2000m9,2000,9,78.59999999999999,60.5,108.7,45.1,64.90000000000001
		2000m10,2000,10,78.59999999999999,63.2,99.7,45.3,65
		2000m11,2000,11,78.7,64.59999999999999,96.7,45.4,64.8
		2000m12,2000,12,78.8,65.2,90.8,45.5,64.8
		2001m1,2001,1,78.90000000000001,70.7,78.09999999999999,46.7,64.90000000000001
		2001m2,2001,2,79,71.59999999999999,78.8,46.9,64.90000000000001
		2001m3,2001,3,79.09999999999999,71.90000000000001,76.5,46.9,64.90000000000001
		2001m4,2001,4,79.2,72.2,78.40000000000001,46.9,64.90000000000001
		2001m5,2001,5,79.2,72.40000000000001,79.40000000000001,46.9,65.2
		2001m6,2001,6,79.3,72.3,82.59999999999999,47,65.2
		2001m7,2001,7,79.40000000000001,71.90000000000001,79.90000000000001,47.1,65.2
		2001m8,2001,8,79.59999999999999,71.90000000000001,80.09999999999999,47.1,65.2
		2001m9,2001,9,79.7,72,85.2,47.1,65.3
		2001m10,2001,10,79.7,70,77.2,47.1,65.40000000000001
		2001m11,2001,11,79.7,69.90000000000001,70.8,47.1,65.3
		2001m12,2001,12,79.8,69.90000000000001,65.3,47.1,65.40000000000001
		2002m1,2002,1,80,68.8,65.90000000000001,49,65.40000000000001
		2002m2,2002,2,80,68.7,65.3,49,65.5
		2002m3,2002,3,80.2,68.59999999999999,69.7,49,65.59999999999999
		2002m4,2002,4,80.3,67.5,73,49,65.59999999999999
		2002m5,2002,5,80.3,67.2,71.90000000000001,49,65.40000000000001
		2002m6,2002,6,80.40000000000001,67,68.2,49.1,65.40000000000001
		2002m7,2002,7,80.5,66.90000000000001,69.5,49.1,65.5
		2002m8,2002,8,80.59999999999999,66.8,70.09999999999999,49.1,65.40000000000001
		2002m9,2002,9,80.59999999999999,66.8,74.7,49.1,65.40000000000001
		2002m10,2002,10,80.7,66.59999999999999,76.5,49.3,65.5
		2002m11,2002,11,80.8,66.59999999999999,69.09999999999999,49.3,65.59999999999999
		2002m12,2002,12,80.90000000000001,66.5,73.5,49.3,65.59999999999999
		2003m1,2003,1,81,70,77.3,51.3,65.7
		2003m2,2003,2,81.09999999999999,70.09999999999999,83.5,51.4,65.7
		2003m3,2003,3,81.09999999999999,70.09999999999999,88.7,51.4,65.7
		2003m4,2003,4,81.3,70.3,71.59999999999999,51.5,65.7
		2003m5,2003,5,81.3,70.3,66.5,51.5,66
		2003m6,2003,6,81.40000000000001,70.59999999999999,67.3,51.5,66.09999999999999
		2003m7,2003,7,81.40000000000001,71.09999999999999,68.90000000000001,51.6,66.09999999999999
		2003m8,2003,8,81.5,71.2,70,51.6,66.2
		2003m9,2003,9,81.5,71.40000000000001,69.2,51.7,66.2
		2003m10,2003,10,81.5,71.40000000000001,73.5,51.8,66.2
		2003m11,2003,11,81.5,71.40000000000001,72.2,51.8,66.40000000000001
		2003m12,2003,12,81.5,71.40000000000001,70.59999999999999,51.8,66.40000000000001
		2004m1,2004,1,81.5,71.2,71.59999999999999,53.4,66.5
		2004m2,2004,2,81.59999999999999,71.2,67,53.5,66.5
		2004m3,2004,3,81.7,71.2,72.2,53.5,66.5
		2004m4,2004,4,81.8,71,74.3,53.7,66.7
		2004m5,2004,5,81.90000000000001,71,79.40000000000001,53.7,66.7
		2004m6,2004,6,81.90000000000001,70.90000000000001,77,53.7,66.8
		2004m7,2004,7,82,70.90000000000001,80.7,53.8,66.90000000000001
		2004m8,2004,8,82.09999999999999,71.09999999999999,87.3,53.8,66.90000000000001
		2004m9,2004,9,82.2,71.3,88.3,53.8,66.90000000000001
		2004m10,2004,10,82.2,72.59999999999999,103.2,53.8,66.90000000000001
		2004m11,2004,11,82.3,73,91.40000000000001,53.8,66.90000000000001
		2004m12,2004,12,82.3,73.3,86.7,53.8,67
		2005m1,2005,1,82.40000000000001,76,86.3,55.4,67.09999999999999
		2005m2,2005,2,82.40000000000001,76.40000000000001,87.40000000000001,55.7,67.2
		2005m3,2005,3,82.5,76.40000000000001,98.59999999999999,55.7,67.2
		2005m4,2005,4,82.59999999999999,76.7,100.9,55.8,67.40000000000001
		2005m5,2005,5,82.7,76.90000000000001,95.5,55.9,67.59999999999999
		2005m6,2005,6,82.7,77,108.1,56,67.7
		2005m7,2005,7,82.8,77.8,113.4,56,67.7
		2005m8,2005,8,82.90000000000001,78.7,117.2,56,67.8
		2005m9,2005,9,82.90000000000001,79.7,123.2,56,67.7
		2005m10,2005,10,83,83.8,126.1,56,67.8
		2005m11,2005,11,83,84.2,115.4,56,68.2
		2005m12,2005,12,83.09999999999999,84.2,115.5,56,68.09999999999999
		2006m1,2006,1,83.3,90.5,113.6,57.8,68.3
		2006m2,2006,2,83.3,91,116.3,57.8,68.3
		2006m3,2006,3,83.40000000000001,91,117.8,57.9,68.5
		2006m4,2006,4,83.5,91.7,123,57.9,68.8
		2006m5,2006,5,83.59999999999999,92.09999999999999,123.7,58.1,69.09999999999999
		2006m6,2006,6,83.59999999999999,92.2,123.3,58.1,69.2
		2006m7,2006,7,83.7,92.3,125.3,58.2,69.7
		2006m8,2006,8,83.7,92.5,126.6,58.2,69.8
		2006m9,2006,9,83.8,92.7,120.7,58.2,69.8
		2006m10,2006,10,83.90000000000001,95.90000000000001,117.5,58.2,70.40000000000001
		2006m11,2006,11,84,96.59999999999999,111.4,58.3,70.59999999999999
		2006m12,2006,12,84,96.59999999999999,108.8,58.3,70.7
		2007m1,2007,1,84.09999999999999,98.90000000000001,102.8,61.1,71.5
		2007m2,2007,2,84.2,98.8,106.3,61.5,71.5
		2007m3,2007,3,84.3,98.8,106.9,61.5,72
		2007m4,2007,4,84.40000000000001,95.5,112.1,61.6,73
		2007m5,2007,5,84.40000000000001,95,111,61.6,73.3
		2007m6,2007,6,84.59999999999999,95,113,61.7,73.40000000000001
		2007m7,2007,7,84.7,94.40000000000001,117.1,62.2,73.8
		2007m8,2007,8,84.8,94.3,116.5,62.3,73.90000000000001
		2007m9,2007,9,84.90000000000001,94,124.1,62.6,74
		2007m10,2007,10,84.90000000000001,94.3,123.9,62.9,74.40000000000001
		2007m11,2007,11,85,94.2,137.8,63.1,74.5
		2007m12,2007,12,85.09999999999999,94.3,135.9,63.2,74.59999999999999
		2008m1,2008,1,85.2,97.3,137.3,65.7,74.8
		2008m2,2008,2,85.3,97.5,141.3,65.90000000000001,75
		2008m3,2008,3,85.40000000000001,97.59999999999999,149.6,65.90000000000001,75.3
		2008m4,2008,4,85.5,98.90000000000001,155.7,66.09999999999999,75.59999999999999
		2008m5,2008,5,85.59999999999999,99.5,174.5,66.09999999999999,75.40000000000001
		2008m6,2008,6,85.7,100,182.9,66.2,75.5
		2008m7,2008,7,85.7,102,186.6,66.40000000000001,75.59999999999999
		2008m8,2008,8,85.8,104,167.1,66.7,75.5
		2008m9,2008,9,85.90000000000001,107.3,164,66.8,75.90000000000001
		2008m10,2008,10,86,114.4,151.8,66.90000000000001,76.2
		2008m11,2008,11,86.09999999999999,115.2,134.3,66.90000000000001,76.7
		2008m12,2008,12,86.09999999999999,115.4,106.9,67,76.90000000000001
		2009m1,2009,1,86.2,116.7,111.8,69.09999999999999,76.90000000000001
		2009m2,2009,2,86.3,115.8,103,69.59999999999999,79.09999999999999
		2009m3,2009,3,86.40000000000001,115.1,95.3,70.09999999999999,79.09999999999999
		2009m4,2009,4,86.5,103.6,100.2,70.59999999999999,79.3
		2009m5,2009,5,86.5,103,100.5,70.7,79.3
		2009m6,2009,6,86.59999999999999,102.5,109.4,70.7,79.3
		2009m7,2009,7,86.59999999999999,98.59999999999999,103.2,70.8,79.2
		2009m8,2009,8,86.7,97.59999999999999,112.8,70.8,79
		2009m9,2009,9,86.8,97.2,107.8,70.90000000000001,79.3
		2009m10,2009,10,86.8,94,113.8,70.90000000000001,79.5
		2009m11,2009,11,86.90000000000001,93.7,114.3,70.90000000000001,79.3
		2009m12,2009,12,86.90000000000001,92.7,111.6,70.90000000000001,79.5
		2010m1,2010,1,87,93,119.7,71.90000000000001,79.59999999999999
		2010m2,2010,2,87.2,93.3,117.1,72,79.7
		2010m3,2010,3,87.3,93.2,125.8,72.3,79.59999999999999
		2010m4,2010,4,87.5,93.40000000000001,133.2,72.5,80.09999999999999
		2010m5,2010,5,87.5,93.40000000000001,135.4,72.8,80
		2010m6,2010,6,87.59999999999999,93.3,135.3,72.8,80
		2010m7,2010,7,87.7,93.3,130.6,72.90000000000001,80.3
		2010m8,2010,8,87.7,93.5,130.4,73.2,80.2
		2010m9,2010,9,87.8,93.7,133.2,73.2,80.40000000000001
		2010m10,2010,10,87.8,94.59999999999999,133.4,73.3,81
		2010m11,2010,11,88,94.8,135.9,73.3,81
		2010m12,2010,12,88.09999999999999,95.3,143.3,73.3,81
		2011m1,2011,1,88.2,96.5,150.1,77,81.40000000000001
		2011m2,2011,2,88.3,96.5,154.7,77.40000000000001,81.5
		2011m3,2011,3,88.40000000000001,96.5,167.2,77.7,81.59999999999999
		2011m4,2011,4,88.5,96.7,168.8,78,82.2
		2011m5,2011,5,88.59999999999999,96.90000000000001,158.9,78.3,82.3
		2011m6,2011,6,88.7,96.7,160.9,78.3,82.3
		2011m7,2011,7,88.8,97.3,164.1,78.3,82.90000000000001
		2011m8,2011,8,88.8,98,159.3,78.3,83
		2011m9,2011,9,88.90000000000001,99.09999999999999,165,78.3,83.09999999999999
		2011m10,2011,10,89,101.1,167.4,78.3,83.40000000000001
		2011m11,2011,11,89.09999999999999,101.5,174.8,78.3,83.40000000000001
		2011m12,2011,12,89.2,101.7,169.5,78.40000000000001,83.5
		2012m1,2012,1,89.3,102.6,176,79.3,84
		2012m2,2012,2,89.40000000000001,103.3,182.1,79.40000000000001,83.90000000000001
		2012m3,2012,3,89.40000000000001,103.4,181.7,79.7,84.3
		2012m4,2012,4,89.5,103.4,178.2,80,84.90000000000001
		2012m5,2012,5,89.59999999999999,103.2,173.3,80.09999999999999,85
		2012m6,2012,6,89.7,103,165.9,80.40000000000001,84.90000000000001
		2012m7,2012,7,89.8,103,173.5,80.5,85.40000000000001
		2012m8,2012,8,89.90000000000001,103.5,180.9,80.7,85.40000000000001
		2012m9,2012,9,90,104.1,182.2,80.7,85.5
		2012m10,2012,10,90,104.2,186.3,80.8,85.8
		2012m11,2012,11,90.09999999999999,104.3,181.8,80.8,85.8
		2012m12,2012,12,90.2,104.3,172.5,80.90000000000001,85.7
		2013m1,2013,1,90.40000000000001,104.6,171.6,88.90000000000001,86.2
		2013m2,2013,2,90.5,104.6,175.8,89.2,86.3
		2013m3,2013,3,90.59999999999999,104.5,170.4,89.59999999999999,86.40000000000001
		2013m4,2013,4,90.7,104.6,165.1,90,86.3
		2013m5,2013,5,90.7,104.5,163.1,90,86.40000000000001
		2013m6,2013,6,90.8,104.6,161.9,90,86.40000000000001
		2013m7,2013,7,91,104.7,167.3,90.09999999999999,86.8
		2013m8,2013,8,91.09999999999999,104.8,166.3,90.09999999999999,86.8
		2013m9,2013,9,91.2,105.1,171.7,90.09999999999999,86.90000000000001
		2013m10,2013,10,91.2,105,166.9,90.09999999999999,87
		2013m11,2013,11,91.40000000000001,105.1,162.6,90,87
		2013m12,2013,12,91.5,105.3,162.9,90,87
		2014m1,2014,1,91.7,105.1,159.4,91.09999999999999,87.09999999999999
		2014m2,2014,2,91.8,105,160.6,91.2,87.09999999999999
		2014m3,2014,3,91.90000000000001,104.8,157.6,91.3,87.3
		2014m4,2014,4,92.09999999999999,104.8,158.9,91.59999999999999,87.8
		2014m5,2014,5,92.2,104.8,158.1,91.59999999999999,87.8
		2014m6,2014,6,92.3,104.7,158.8,91.59999999999999,87.8
		2014m7,2014,7,92.40000000000001,104.7,157.3,91.59999999999999,88
		2014m8,2014,8,92.5,104.7,158,91.7,88
		2014m9,2014,9,92.5,104.6,158.1,91.7,88.09999999999999
		2014m10,2014,10,92.59999999999999,104.7,148.9,91.7,88.5
		2014m11,2014,11,92.8,104.5,146.6,91.7,88.59999999999999
		2014m12,2014,12,92.90000000000001,103.8,125.7,91.7,88.59999999999999
		2015m1,2015,1,93.09999999999999,103.5,115.8,91.3,88.8
		2015m2,2015,2,93.09999999999999,103.5,123.4,91.2,88.8
		2015m3,2015,3,93.2,103.6,123.5,91,88.90000000000001
		2015m4,2015,4,93.40000000000001,103.5,122.1,90.8,89.3
		2015m5,2015,5,93.40000000000001,103.3,123.7,90.8,89.40000000000001
		2015m6,2015,6,93.5,103.2,120.8,90.8,89.40000000000001
		2015m7,2015,7,93.59999999999999,103,116.1,90.7,89.59999999999999
		2015m8,2015,8,93.7,103,110.6,90.7,89.7
		2015m9,2015,9,93.7,102.8,109,90.7,89.8
		2015m10,2015,10,93.8,102.8,106.8,90.59999999999999,90
		2015m11,2015,11,93.8,102.8,105.9,90.5,90.2
		2015m12,2015,12,93.90000000000001,102.7,95.2,90.5,89.90000000000001
		2016m1,2016,1,94.09999999999999,101.9,86.8,90.90000000000001,90.2
		2016m2,2016,2,94.2,101.7,85.5,90.90000000000001,90.2
		2016m3,2016,3,94.3,101.6,89.7,91,90.2
		2016m4,2016,4,94.3,101.5,88.40000000000001,91.40000000000001,90.8
		2016m5,2016,5,94.40000000000001,101.3,92.3,91.40000000000001,90.8
		2016m6,2016,6,94.40000000000001,101.1,94.7,91.40000000000001,90.90000000000001
		2016m7,2016,7,94.5,100.8,92,91.2,91.2
		2016m8,2016,8,94.59999999999999,100.6,89.90000000000001,91.2,91.2
		2016m9,2016,9,94.8,100.4,91.09999999999999,91.2,91.3
		2016m10,2016,10,94.90000000000001,100.1,97.40000000000001,91.2,91.5
		2016m11,2016,11,95,99.90000000000001,94,91.2,91.59999999999999
		2016m12,2016,12,95.09999999999999,99.90000000000001,101.1,91.2,91.59999999999999
		2017m1,2017,1,95.2,98.8,102.4,92,91.90000000000001
		2017m2,2017,2,95.3,98.7,103.5,92.2,91.90000000000001
		2017m3,2017,3,95.40000000000001,98.59999999999999,101.3,92.3,91.90000000000001
		2017m4,2017,4,95.59999999999999,98.2,103.7,92.3,92.59999999999999
		2017m5,2017,5,95.7,98,99.8,92.40000000000001,92.59999999999999
		2017m6,2017,6,95.8,97.8,96.8,92.7,92.59999999999999
		2017m7,2017,7,95.90000000000001,97.40000000000001,97.2,92.8,93.09999999999999
		2017m8,2017,8,95.90000000000001,97.40000000000001,98.5,92.8,93.09999999999999
		2017m9,2017,9,96,97.40000000000001,101.8,92.90000000000001,93.2
		2017m10,2017,10,96.2,97.5,103.5,92.90000000000001,93.7
		2017m11,2017,11,96.3,97.5,107.2,92.90000000000001,93.8
		2017m12,2017,12,96.40000000000001,97.5,108.2,92.90000000000001,93.7
		2018m1,2018,1,96.7,97.09999999999999,110.3,93.5,94
		2018m2,2018,2,96.8,96.90000000000001,106.8,93.59999999999999,94.09999999999999
		2018m3,2018,3,96.8,96.8,107.5,93.59999999999999,94.3
		2018m4,2018,4,97,96.7,111.6,93.90000000000001,95.09999999999999
		2018m5,2018,5,97,96.7,117.4,93.90000000000001,95.09999999999999
		2018m6,2018,6,97.2,96.40000000000001,117.8,93.8,95.2
		2018m7,2018,7,97.3,96.40000000000001,117.8,93.7,95.7
		2018m8,2018,8,97.40000000000001,96.3,120.7,93.8,95.7
		2018m9,2018,9,97.5,96.40000000000001,129.4,93.8,95.90000000000001
		2018m10,2018,10,97.59999999999999,96.5,135.1,93.8,96.2
		2018m11,2018,11,97.7,96.5,141.5,93.90000000000001,96.3
		2018m12,2018,12,97.8,96.40000000000001,125.9,93.90000000000001,96.90000000000001
		2019m1,2019,1,98,97.59999999999999,122,95.8,97.3
		2019m2,2019,2,98.09999999999999,97.8,123.1,96.3,97.40000000000001
		2019m3,2019,3,98.2,98.09999999999999,123.9,96.3,97.5
		2019m4,2019,4,98.3,98.5,125.5,96.7,98.7
		2019m5,2019,5,98.40000000000001,98.59999999999999,127.5,96.90000000000001,98.8
		2019m6,2019,6,98.59999999999999,98.7,121.5,97,99
		2019m7,2019,7,98.7,98.8,123.2,97.2,99.40000000000001
		2019m8,2019,8,98.8,98.90000000000001,121.6,97.3,99.40000000000001
		2019m9,2019,9,98.90000000000001,99.09999999999999,124.2,97.40000000000001,99.59999999999999
		2019m10,2019,10,99,99.59999999999999,123.3,97.40000000000001,99.90000000000001
		2019m11,2019,11,99.09999999999999,100,121.3,97.5,99.90000000000001
		2019m12,2019,12,99.3,100.3,120.7,97.7,99.90000000000001
		2020m1,2020,1,99.40000000000001,100.7,120.5,99.59999999999999,100.3
		2020m2,2020,2,99.5,100.7,115.3,100.7,100.4
		2020m3,2020,3,99.7,100.7,109.2,100.9,100.5
		2020m4,2020,4,99.8,100.5,106.5,101.1,101.2
		2020m5,2020,5,99.90000000000001,100.5,102,101.1,101.2
		2020m6,2020,6,100,100.6,99.5,101.1,101.2
		2020m7,2020,7,100.1,99.40000000000001,96.5,99.3,99.2
		2020m8,2020,8,100.1,99.5,93.3,99.40000000000001,99
		2020m9,2020,9,100.2,99.3,89,99.3,99.09999999999999
		2020m10,2020,10,100.3,99.40000000000001,88.3,99.3,99.3
		2020m11,2020,11,100.5,99.3,87.2,99.2,99.2
		2020m12,2020,12,100.5,99.40000000000001,92.59999999999999,99.09999999999999,99.40000000000001
		2021m1,2021,1,100.7,102.1,98,100.8,101.6
		2021m2,2021,2,100.8,102.3,99.8,100.9,101.7
		2021m3,2021,3,100.9,102.5,102.3,100.9,101.9
		2021m4,2021,4,101.1,102.4,100.7,100.8,103
		2021m5,2021,5,101.2,102.4,102.8,100.9,103.2
		2021m6,2021,6,101.3,102.4,104.8,101,103.7
		2021m7,2021,7,101.4,102.8,107,100.9,105.1
		2021m8,2021,8,101.6,103.3,106.5,101.2,105.4
		2021m9,2021,9,101.7,103.8,109.9,101.3,105.8
		2021m10,2021,10,101.8,105.4,122.5,101.9,107.5
		2021m11,2021,11,101.9,107.1,125.6,102.4,107.7
		2021m12,2021,12,102,108.6,122.5,102.9,107.9
		2022m1,2022,1,102.2,120.6,128.9,110.5,110
		2022m2,2022,2,102.4,124.8,136.1,113.4,110.5
		2022m3,2022,3,102.5,132.8,197.6,118.4,111
		2022m4,2022,4,102.7,138.1,173.2,120,113.8
		2022m5,2022,5,102.9,143.9,178.9,122.3,114.7
		2022m6,2022,6,103,147.5,194.6,123.4,115.1
		2022m7,2022,7,103.2,158.8,198.6,115.3,118.3
		2022m8,2022,8,103.3,166.7,205.9,116.7,118.6
		2022m9,2022,9,103.5,176.6,214.1,121.9,118.8
		2022m10,2022,10,103.7,188.3,222.6,127.9,121.3
		2022m11,2022,11,103.8,195.8,207.3,129.7,121.6
		2022m12,2022,12,103.9,151.7,195,130.4,121.9
		2023m1,2023,1,104.2,186.9,193.5,138.9,124.1
		2023m2,2023,2,104.4,190.3,185.9,139.6,124.3
		2023m3,2023,3,104.6,193.7,184.6,138.7,124.5
		2023m4,2023,4,104.8,195.2,178.6,138.5,126.3
		2023m5,2023,5,105,196.3,168.8,137.8,127.1
		2023m6,2023,6,105.1,196.6,167.5,136.3,127.3
		2023m7,2023,7,105.3,196.7,166.2,135.6,128.4
		2023m8,2023,8,105.5,196.8,175.5,136.1,128.4
		2023m9,2023,9,105.6,196.1,179.2,135.4,128.5
		2023m10,2023,10,105.8,194.6,177.1,133.9,129.4
		2023m11,2023,11,105.9,190.5,172.1,131.8,129.8
		2023m12,2023,12,106.1,188.2,167.9,130.4,129.8
		2024m1,2024,1,106.4,192.4,165.9,129.4,130.6
		2024m2,2024,2,106.7,190.9,168.2,128.6,130.5
		2024m3,2024,3,106.8,189.1,164.9,127.5,130.8
		2024m4,2024,4,107.1,192.4,167.4,127.7,132
		2024m5,2024,5,107.3,190.8,161.5,127.6,132.2
		2024m6,2024,6,107.4,189.7,160.9,127.7,132.1
		2024m7,2024,7,107.6,188.9,162.4,127.2,132.7
		2024m8,2024,8,107.7,187.7,159.1,126.9,132.9
		2024m9,2024,9,107.9,187,154.8,126.7,133.1
		2024m10,2024,10,108.1,186.5,158.1,126.5,133.9
		2024m11,2024,11,108.2,186.3,155.3,126.4,133.9
		2024m12,2024,12,108.4,186.7,154.1,126.6,134.1
		2025m1,2025,1,108.6,185.6,160.4,124.8,134.5
		2025m2,2025,2,108.8,185.9,157.4,124.7,134.6
		2025m3,2025,3,109,186,151.7,124.8,134.6
		2025m4,2025,4,109.3,185.9,148.7,124.5,135.8
		2025m5,2025,5,109.5,185.2,145.7,124.6,136.1
		2025m6,2025,6,109.7,185.1,147.7,124.6,136.1
		2025m7,2025,7,109.9,185.2,148.9,124.6,136.8

00_original_index/03_data/data_given/ifo_business_climate_construction_bw_m.csv

0 → 100644

+368 −0

Original line number	Diff line number	Diff line
		date,year,month,ifo_constr_bw
		1995m1,1995,1,-38.7
		1995m2,1995,2,-37
		1995m3,1995,3,-42.2
		1995m4,1995,4,-44.9
		1995m5,1995,5,-49
		1995m6,1995,6,-51.6
		1995m7,1995,7,-52
		1995m8,1995,8,-54.9
		1995m9,1995,9,-58.9
		1995m10,1995,10,-58.2
		1995m11,1995,11,-58.6
		1995m12,1995,12,-57.7
		1996m1,1996,1,-63.1
		1996m2,1996,2,-66
		1996m3,1996,3,-60.2
		1996m4,1996,4,-52.1
		1996m5,1996,5,-57.2
		1996m6,1996,6,-63.3
		1996m7,1996,7,-57.6
		1996m8,1996,8,-58
		1996m9,1996,9,-56.6
		1996m10,1996,10,-50.6
		1996m11,1996,11,-57.7
		1996m12,1996,12,-56.7
		1997m1,1997,1,-49.4
		1997m2,1997,2,-47.7
		1997m3,1997,3,-52
		1997m4,1997,4,-49.2
		1997m5,1997,5,-45.8
		1997m6,1997,6,-49.4
		1997m7,1997,7,-52.8
		1997m8,1997,8,-53.7
		1997m9,1997,9,-46.6
		1997m10,1997,10,-48.6
		1997m11,1997,11,-46.9
		1997m12,1997,12,-45.3
		1998m1,1998,1,-48.5
		1998m2,1998,2,-41.8
		1998m3,1998,3,-42.6
		1998m4,1998,4,-44.6
		1998m5,1998,5,-40.7
		1998m6,1998,6,-35
		1998m7,1998,7,-34.6
		1998m8,1998,8,-31.7
		1998m9,1998,9,-37.8
		1998m10,1998,10,-34.6
		1998m11,1998,11,-35.5
		1998m12,1998,12,-30.7
		1999m1,1999,1,-29.2
		1999m2,1999,2,-26.7
		1999m3,1999,3,-25.7
		1999m4,1999,4,-19.9
		1999m5,1999,5,-22.4
		1999m6,1999,6,-21.8
		1999m7,1999,7,-13.9
		1999m8,1999,8,-20.4
		1999m9,1999,9,-20.8
		1999m10,1999,10,-17
		1999m11,1999,11,-18.6
		1999m12,1999,12,-19.4
		2000m1,2000,1,-19.7
		2000m2,2000,2,-23.1
		2000m3,2000,3,-21.4
		2000m4,2000,4,-20
		2000m5,2000,5,-19.9
		2000m6,2000,6,-23.3
		2000m7,2000,7,-24
		2000m8,2000,8,-27.9
		2000m9,2000,9,-22.3
		2000m10,2000,10,-25.2
		2000m11,2000,11,-24.3
		2000m12,2000,12,-25.7
		2001m1,2001,1,-22.2
		2001m2,2001,2,-23.2
		2001m3,2001,3,-28.5
		2001m4,2001,4,-27.1
		2001m5,2001,5,-40.2
		2001m6,2001,6,-33.7
		2001m7,2001,7,-32.7
		2001m8,2001,8,-31.5
		2001m9,2001,9,-42
		2001m10,2001,10,-35.9
		2001m11,2001,11,-33.4
		2001m12,2001,12,-33.7
		2002m1,2002,1,-38.3
		2002m2,2002,2,-42.8
		2002m3,2002,3,-40
		2002m4,2002,4,-41.9
		2002m5,2002,5,-40.1
		2002m6,2002,6,-45.9
		2002m7,2002,7,-45
		2002m8,2002,8,-45.1
		2002m9,2002,9,-47.5
		2002m10,2002,10,-47
		2002m11,2002,11,-50.9
		2002m12,2002,12,-48.5
		2003m1,2003,1,-51.8
		2003m2,2003,2,-53.1
		2003m3,2003,3,-53.3
		2003m4,2003,4,-57.7
		2003m5,2003,5,-50.8
		2003m6,2003,6,-51.2
		2003m7,2003,7,-58.6
		2003m8,2003,8,-51.6
		2003m9,2003,9,-49.7
		2003m10,2003,10,-52.9
		2003m11,2003,11,-51.3
		2003m12,2003,12,-44.6
		2004m1,2004,1,-42.9
		2004m2,2004,2,-40.9
		2004m3,2004,3,-40.6
		2004m4,2004,4,-46.9
		2004m5,2004,5,-47.5
		2004m6,2004,6,-44.8
		2004m7,2004,7,-50.7
		2004m8,2004,8,-45.6
		2004m9,2004,9,-44
		2004m10,2004,10,-44.7
		2004m11,2004,11,-41.5
		2004m12,2004,12,-43.5
		2005m1,2005,1,-43.1
		2005m2,2005,2,-46
		2005m3,2005,3,-45.7
		2005m4,2005,4,-40.4
		2005m5,2005,5,-33.9
		2005m6,2005,6,-39.7
		2005m7,2005,7,-39
		2005m8,2005,8,-33.3
		2005m9,2005,9,-33.4
		2005m10,2005,10,-28.8
		2005m11,2005,11,-24.7
		2005m12,2005,12,-22.4
		2006m1,2006,1,-24.4
		2006m2,2006,2,-22.3
		2006m3,2006,3,-18.3
		2006m4,2006,4,-11.2
		2006m5,2006,5,-10.7
		2006m6,2006,6,-4.3
		2006m7,2006,7,-1.4
		2006m8,2006,8,-10.9
		2006m9,2006,9,-12.9
		2006m10,2006,10,-9.1
		2006m11,2006,11,-9.9
		2006m12,2006,12,-6.9
		2007m1,2007,1,-3.6
		2007m2,2007,2,-8.800000000000001
		2007m3,2007,3,-16.6
		2007m4,2007,4,-14.2
		2007m5,2007,5,-15.3
		2007m6,2007,6,-12.7
		2007m7,2007,7,-15
		2007m8,2007,8,-11
		2007m9,2007,9,-14.7
		2007m10,2007,10,-15.7
		2007m11,2007,11,-16.5
		2007m12,2007,12,-20.9
		2008m1,2008,1,-16.9
		2008m2,2008,2,-25.2
		2008m3,2008,3,-21.8
		2008m4,2008,4,-24.2
		2008m5,2008,5,-24.4
		2008m6,2008,6,-19.6
		2008m7,2008,7,-21.5
		2008m8,2008,8,-24.8
		2008m9,2008,9,-20.2
		2008m10,2008,10,-24.2
		2008m11,2008,11,-31.7
		2008m12,2008,12,-31.4
		2009m1,2009,1,-31
		2009m2,2009,2,-32.2
		2009m3,2009,3,-34.7
		2009m4,2009,4,-32.4
		2009m5,2009,5,-28.1
		2009m6,2009,6,-30.5
		2009m7,2009,7,-26.8
		2009m8,2009,8,-19.1
		2009m9,2009,9,-22.8
		2009m10,2009,10,-26
		2009m11,2009,11,-28.2
		2009m12,2009,12,-31.5
		2010m1,2010,1,-33.1
		2010m2,2010,2,-30.3
		2010m3,2010,3,-28.1
		2010m4,2010,4,-24.8
		2010m5,2010,5,-29.3
		2010m6,2010,6,-22.7
		2010m7,2010,7,-16.7
		2010m8,2010,8,-20.6
		2010m9,2010,9,-17.3
		2010m10,2010,10,-12.8
		2010m11,2010,11,-9
		2010m12,2010,12,-7.4
		2011m1,2011,1,-11
		2011m2,2011,2,-9.6
		2011m3,2011,3,-9.1
		2011m4,2011,4,-5.1
		2011m5,2011,5,-3
		2011m6,2011,6,1.9
		2011m7,2011,7,-.6
		2011m8,2011,8,-.7
		2011m9,2011,9,-1.9
		2011m10,2011,10,-3.8
		2011m11,2011,11,-1.5
		2011m12,2011,12,-5.1
		2012m1,2012,1,-5.5
		2012m2,2012,2,-5.3
		2012m3,2012,3,-1.7
		2012m4,2012,4,-1
		2012m5,2012,5,2.5
		2012m6,2012,6,-4.1
		2012m7,2012,7,-1.3
		2012m8,2012,8,-2.5
		2012m9,2012,9,-2.2
		2012m10,2012,10,-5.4
		2012m11,2012,11,-1
		2012m12,2012,12,-2.6
		2013m1,2013,1,2.4
		2013m2,2013,2,1.8
		2013m3,2013,3,4.8
		2013m4,2013,4,6.2
		2013m5,2013,5,4
		2013m6,2013,6,6.9
		2013m7,2013,7,6.9
		2013m8,2013,8,3.1
		2013m9,2013,9,3.7
		2013m10,2013,10,-1
		2013m11,2013,11,1.2
		2013m12,2013,12,6
		2014m1,2014,1,7.4
		2014m2,2014,2,6.8
		2014m3,2014,3,3.6
		2014m4,2014,4,10.3
		2014m5,2014,5,3.1
		2014m6,2014,6,2.9
		2014m7,2014,7,.1
		2014m8,2014,8,6.2
		2014m9,2014,9,6
		2014m10,2014,10,2.1
		2014m11,2014,11,.5
		2014m12,2014,12,-3.9
		2015m1,2015,1,1.4
		2015m2,2015,2,5.4
		2015m3,2015,3,4.3
		2015m4,2015,4,7.2
		2015m5,2015,5,7.8
		2015m6,2015,6,6.8
		2015m7,2015,7,7.5
		2015m8,2015,8,7.6
		2015m9,2015,9,8.6
		2015m10,2015,10,7.5
		2015m11,2015,11,6
		2015m12,2015,12,3.5
		2016m1,2016,1,7.1
		2016m2,2016,2,9.300000000000001
		2016m3,2016,3,14.9
		2016m4,2016,4,9.4
		2016m5,2016,5,13.1
		2016m6,2016,6,12.1
		2016m7,2016,7,15.4
		2016m8,2016,8,12.7
		2016m9,2016,9,14.1
		2016m10,2016,10,14.8
		2016m11,2016,11,17.9
		2016m12,2016,12,13.4
		2017m1,2017,1,20.7
		2017m2,2017,2,20.4
		2017m3,2017,3,17.6
		2017m4,2017,4,24.5
		2017m5,2017,5,21
		2017m6,2017,6,21.5
		2017m7,2017,7,26.1
		2017m8,2017,8,21.8
		2017m9,2017,9,20.9
		2017m10,2017,10,24.8
		2017m11,2017,11,28.4
		2017m12,2017,12,28
		2018m1,2018,1,24.1
		2018m2,2018,2,24.9
		2018m3,2018,3,27.2
		2018m4,2018,4,24.1
		2018m5,2018,5,26.6
		2018m6,2018,6,24.8
		2018m7,2018,7,32.6
		2018m8,2018,8,33.1
		2018m9,2018,9,35
		2018m10,2018,10,35.1
		2018m11,2018,11,27.6
		2018m12,2018,12,31
		2019m1,2019,1,24.8
		2019m2,2019,2,26.6
		2019m3,2019,3,26.7
		2019m4,2019,4,27.2
		2019m5,2019,5,27
		2019m6,2019,6,31.8
		2019m7,2019,7,29.3
		2019m8,2019,8,27.5
		2019m9,2019,9,22.4
		2019m10,2019,10,23.8
		2019m11,2019,11,24
		2019m12,2019,12,21.9
		2020m1,2020,1,21.5
		2020m2,2020,2,18.4
		2020m3,2020,3,16.7
		2020m4,2020,4,-8.699999999999999
		2020m5,2020,5,-1.8
		2020m6,2020,6,-5.5
		2020m7,2020,7,-5.3
		2020m8,2020,8,-.2
		2020m9,2020,9,4.9
		2020m10,2020,10,-3.8
		2020m11,2020,11,2.7
		2020m12,2020,12,2.7
		2021m1,2021,1,.8
		2021m2,2021,2,.3
		2021m3,2021,3,9.800000000000001
		2021m4,2021,4,7.6
		2021m5,2021,5,9.199999999999999
		2021m6,2021,6,7.1
		2021m7,2021,7,4.8
		2021m8,2021,8,11.7
		2021m9,2021,9,17.4
		2021m10,2021,10,14.7
		2021m11,2021,11,14.6
		2021m12,2021,12,16
		2022m1,2022,1,22.7
		2022m2,2022,2,21.8
		2022m3,2022,3,4.4
		2022m4,2022,4,-11.9
		2022m5,2022,5,-8.5
		2022m6,2022,6,-6.9
		2022m7,2022,7,-11.6
		2022m8,2022,8,-10.7
		2022m9,2022,9,-15.7
		2022m10,2022,10,-13.1
		2022m11,2022,11,-20.6
		2022m12,2022,12,-16.8
		2023m1,2023,1,-14.3
		2023m2,2023,2,-14.3
		2023m3,2023,3,-17.1
		2023m4,2023,4,-23.6
		2023m5,2023,5,-20.4
		2023m6,2023,6,-17.5
		2023m7,2023,7,-30.1
		2023m8,2023,8,-39
		2023m9,2023,9,-33.2
		2023m10,2023,10,-35.8
		2023m11,2023,11,-34.1
		2023m12,2023,12,-38.4
		2024m1,2024,1,-42
		2024m2,2024,2,-41
		2024m3,2024,3,-37.5
		2024m4,2024,4,-29.2
		2024m5,2024,5,-34.4
		2024m6,2024,6,-33.6
		2024m7,2024,7,-34
		2024m8,2024,8,-29.3
		2024m9,2024,9,-31.7
		2024m10,2024,10,-33
		2024m11,2024,11,-33
		2024m12,2024,12,-27.3
		2025m1,2025,1,-36.3
		2025m2,2025,2,-29.5
		2025m3,2025,3,-19.3
		2025m4,2025,4,-18.2
		2025m5,2025,5,-16.2
		2025m6,2025,6,-16.7
		2025m7,2025,7,-14.1

00_original_index/03_data/data_given/inc_orders_apartment_bw_m.csv

0 → 100644

+367 −0

Original line number	Diff line number	Diff line
		date,year,month,inc_orders_apartment
		1995m1,1995,1,157873
		1995m2,1995,2,188548
		1995m3,1995,3,241232
		1995m4,1995,4,177338
		1995m5,1995,5,196121
		1995m6,1995,6,220220
		1995m7,1995,7,171550
		1995m8,1995,8,176390
		1995m9,1995,9,193113
		1995m10,1995,10,176198
		1995m11,1995,11,164592
		1995m12,1995,12,174646
		1996m1,1996,1,105735
		1996m2,1996,2,157536
		1996m3,1996,3,177654
		1996m4,1996,4,176200
		1996m5,1996,5,161728
		1996m6,1996,6,202023
		1996m7,1996,7,163509
		1996m8,1996,8,152904
		1996m9,1996,9,207069
		1996m10,1996,10,166150
		1996m11,1996,11,137313
		1996m12,1996,12,159207
		1997m1,1997,1,94881
		1997m2,1997,2,140087
		1997m3,1997,3,168897
		1997m4,1997,4,168689
		1997m5,1997,5,130583
		1997m6,1997,6,187895
		1997m7,1997,7,165485
		1997m8,1997,8,142582
		1997m9,1997,9,185594
		1997m10,1997,10,160556
		1997m11,1997,11,128983
		1997m12,1997,12,149210
		1998m1,1998,1,112409
		1998m2,1998,2,120426
		1998m3,1998,3,179504
		1998m4,1998,4,133332
		1998m5,1998,5,128603
		1998m6,1998,6,158006
		1998m7,1998,7,165899
		1998m8,1998,8,137672
		1998m9,1998,9,158365
		1998m10,1998,10,142040
		1998m11,1998,11,123085
		1998m12,1998,12,128658
		1999m1,1999,1,97406
		1999m2,1999,2,121232
		1999m3,1999,3,156632
		1999m4,1999,4,141514
		1999m5,1999,5,123137
		1999m6,1999,6,150040
		1999m7,1999,7,144564
		1999m8,1999,8,125322
		1999m9,1999,9,182468
		1999m10,1999,10,145176
		1999m11,1999,11,119941
		1999m12,1999,12,132474
		2000m1,2000,1,110790
		2000m2,2000,2,116843
		2000m3,2000,3,153869
		2000m4,2000,4,134914
		2000m5,2000,5,136530
		2000m6,2000,6,143692
		2000m7,2000,7,132419
		2000m8,2000,8,112483
		2000m9,2000,9,131876
		2000m10,2000,10,112186
		2000m11,2000,11,98323
		2000m12,2000,12,90125
		2001m1,2001,1,94242
		2001m2,2001,2,92536
		2001m3,2001,3,147703
		2001m4,2001,4,115097
		2001m5,2001,5,116228
		2001m6,2001,6,142981
		2001m7,2001,7,106231
		2001m8,2001,8,96498
		2001m9,2001,9,117771
		2001m10,2001,10,101509
		2001m11,2001,11,80889
		2001m12,2001,12,75564
		2002m1,2002,1,74220
		2002m2,2002,2,84249
		2002m3,2002,3,125148
		2002m4,2002,4,106086
		2002m5,2002,5,112883
		2002m6,2002,6,114573
		2002m7,2002,7,106626
		2002m8,2002,8,102436
		2002m9,2002,9,107848
		2002m10,2002,10,95768
		2002m11,2002,11,93515
		2002m12,2002,12,87788
		2003m1,2003,1,66141
		2003m2,2003,2,77159
		2003m3,2003,3,111232
		2003m4,2003,4,101570
		2003m5,2003,5,96711
		2003m6,2003,6,97856
		2003m7,2003,7,102884
		2003m8,2003,8,90728
		2003m9,2003,9,102931
		2003m10,2003,10,96340
		2003m11,2003,11,87529
		2003m12,2003,12,84335
		2004m1,2004,1,78029
		2004m2,2004,2,83826
		2004m3,2004,3,115978
		2004m4,2004,4,100971
		2004m5,2004,5,95770
		2004m6,2004,6,105846
		2004m7,2004,7,103372
		2004m8,2004,8,92090
		2004m9,2004,9,105825
		2004m10,2004,10,87252
		2004m11,2004,11,81951
		2004m12,2004,12,84315
		2005m1,2005,1,64083
		2005m2,2005,2,62529
		2005m3,2005,3,95596
		2005m4,2005,4,87609
		2005m5,2005,5,86489
		2005m6,2005,6,107281
		2005m7,2005,7,103196
		2005m8,2005,8,96368
		2005m9,2005,9,100430
		2005m10,2005,10,91451
		2005m11,2005,11,86749
		2005m12,2005,12,88268
		2006m1,2006,1,64684
		2006m2,2006,2,75455
		2006m3,2006,3,107343
		2006m4,2006,4,94273
		2006m5,2006,5,104109
		2006m6,2006,6,103441
		2006m7,2006,7,109011
		2006m8,2006,8,97777
		2006m9,2006,9,99041
		2006m10,2006,10,106332
		2006m11,2006,11,85258
		2006m12,2006,12,77499
		2007m1,2007,1,76009
		2007m2,2007,2,77666
		2007m3,2007,3,96072
		2007m4,2007,4,85297
		2007m5,2007,5,88739
		2007m6,2007,6,92976
		2007m7,2007,7,99084
		2007m8,2007,8,80893
		2007m9,2007,9,88910
		2007m10,2007,10,84743
		2007m11,2007,11,87996
		2007m12,2007,12,70912
		2008m1,2008,1,63695
		2008m2,2008,2,81207
		2008m3,2008,3,88802
		2008m4,2008,4,83079
		2008m5,2008,5,92697
		2008m6,2008,6,90826
		2008m7,2008,7,99090
		2008m8,2008,8,73211
		2008m9,2008,9,87695
		2008m10,2008,10,87171
		2008m11,2008,11,87538
		2008m12,2008,12,60973
		2009m1,2009,1,42107
		2009m2,2009,2,55744
		2009m3,2009,3,95414
		2009m4,2009,4,89117
		2009m5,2009,5,78815
		2009m6,2009,6,114301
		2009m7,2009,7,86232
		2009m8,2009,8,89900
		2009m9,2009,9,89688
		2009m10,2009,10,90326
		2009m11,2009,11,82520
		2009m12,2009,12,83457
		2010m1,2010,1,53366
		2010m2,2010,2,94333
		2010m3,2010,3,93935
		2010m4,2010,4,128270
		2010m5,2010,5,91926
		2010m6,2010,6,98528
		2010m7,2010,7,110464
		2010m8,2010,8,104588
		2010m9,2010,9,102953
		2010m10,2010,10,93192
		2010m11,2010,11,92721
		2010m12,2010,12,85622
		2011m1,2011,1,73483
		2011m2,2011,2,83931
		2011m3,2011,3,127426
		2011m4,2011,4,104045
		2011m5,2011,5,110672
		2011m6,2011,6,114402
		2011m7,2011,7,125128
		2011m8,2011,8,103107
		2011m9,2011,9,116970
		2011m10,2011,10,113179
		2011m11,2011,11,115851
		2011m12,2011,12,86968
		2012m1,2012,1,81966
		2012m2,2012,2,93316
		2012m3,2012,3,143607
		2012m4,2012,4,134331
		2012m5,2012,5,113476
		2012m6,2012,6,125248
		2012m7,2012,7,130223
		2012m8,2012,8,144696
		2012m9,2012,9,133803
		2012m10,2012,10,127929
		2012m11,2012,11,115361
		2012m12,2012,12,91083
		2013m1,2013,1,99686
		2013m2,2013,2,93204
		2013m3,2013,3,148675
		2013m4,2013,4,124539
		2013m5,2013,5,141525
		2013m6,2013,6,119021
		2013m7,2013,7,133599
		2013m8,2013,8,130750
		2013m9,2013,9,132137
		2013m10,2013,10,136556
		2013m11,2013,11,124743
		2013m12,2013,12,99458
		2014m1,2014,1,107332
		2014m2,2014,2,117990
		2014m3,2014,3,135577
		2014m4,2014,4,151048
		2014m5,2014,5,147965
		2014m6,2014,6,165671
		2014m7,2014,7,151330
		2014m8,2014,8,103363
		2014m9,2014,9,133443
		2014m10,2014,10,126250
		2014m11,2014,11,108324
		2014m12,2014,12,102408
		2015m1,2015,1,94286
		2015m2,2015,2,131681
		2015m3,2015,3,131323
		2015m4,2015,4,151519
		2015m5,2015,5,110234
		2015m6,2015,6,147768
		2015m7,2015,7,135134
		2015m8,2015,8,139432
		2015m9,2015,9,147890
		2015m10,2015,10,143535
		2015m11,2015,11,132118
		2015m12,2015,12,141885
		2016m1,2016,1,120389
		2016m2,2016,2,130818
		2016m3,2016,3,174025
		2016m4,2016,4,162524
		2016m5,2016,5,157843
		2016m6,2016,6,193342
		2016m7,2016,7,154437
		2016m8,2016,8,132709
		2016m9,2016,9,187736
		2016m10,2016,10,164298
		2016m11,2016,11,151817
		2016m12,2016,12,131661
		2017m1,2017,1,123918
		2017m2,2017,2,151479
		2017m3,2017,3,229343
		2017m4,2017,4,147552
		2017m5,2017,5,205234
		2017m6,2017,6,169895
		2017m7,2017,7,166386
		2017m8,2017,8,144441
		2017m9,2017,9,166282
		2017m10,2017,10,165601
		2017m11,2017,11,153194
		2017m12,2017,12,168634
		2018m1,2018,1,174694
		2018m2,2018,2,162327
		2018m3,2018,3,193375
		2018m4,2018,4,211882
		2018m5,2018,5,177874
		2018m6,2018,6,220184
		2018m7,2018,7,200260
		2018m8,2018,8,150796
		2018m9,2018,9,156283
		2018m10,2018,10,199656
		2018m11,2018,11,174505
		2018m12,2018,12,191951
		2019m1,2019,1,202303
		2019m2,2019,2,186691
		2019m3,2019,3,206916
		2019m4,2019,4,205988
		2019m5,2019,5,188524
		2019m6,2019,6,197442
		2019m7,2019,7,222746
		2019m8,2019,8,174506
		2019m9,2019,9,204011
		2019m10,2019,10,197481
		2019m11,2019,11,188942
		2019m12,2019,12,162178
		2020m1,2020,1,216408
		2020m2,2020,2,173225
		2020m3,2020,3,237954
		2020m4,2020,4,199940
		2020m5,2020,5,254930
		2020m6,2020,6,216547
		2020m7,2020,7,235235
		2020m8,2020,8,176469
		2020m9,2020,9,214971
		2020m10,2020,10,248295
		2020m11,2020,11,245386
		2020m12,2020,12,228501
		2021m1,2021,1,210237
		2021m2,2021,2,223930
		2021m3,2021,3,262153
		2021m4,2021,4,262339
		2021m5,2021,5,264129
		2021m6,2021,6,256739
		2021m7,2021,7,208048
		2021m8,2021,8,184780
		2021m9,2021,9,214212
		2021m10,2021,10,219534
		2021m11,2021,11,216328
		2021m12,2021,12,298338
		2022m1,2022,1,275896
		2022m2,2022,2,222550
		2022m3,2022,3,302579
		2022m4,2022,4,227113
		2022m5,2022,5,240645
		2022m6,2022,6,255328
		2022m7,2022,7,236840
		2022m8,2022,8,216175
		2022m9,2022,9,256410
		2022m10,2022,10,229564
		2022m11,2022,11,171123
		2022m12,2022,12,197492
		2023m1,2023,1,206679
		2023m2,2023,2,164221
		2023m3,2023,3,213837
		2023m4,2023,4,194691
		2023m5,2023,5,198205
		2023m6,2023,6,190859
		2023m7,2023,7,220061
		2023m8,2023,8,182557
		2023m9,2023,9,188371
		2023m10,2023,10,181474
		2023m11,2023,11,183330
		2023m12,2023,12,132768
		2024m1,2024,1,130675
		2024m2,2024,2,177571
		2024m3,2024,3,192950
		2024m4,2024,4,204917
		2024m5,2024,5,205193
		2024m6,2024,6,177530
		2024m7,2024,7,210826
		2024m8,2024,8,260430
		2024m9,2024,9,186421
		2024m10,2024,10,203770
		2024m11,2024,11,211472
		2024m12,2024,12,181689
		2025m1,2025,1,191080
		2025m2,2025,2,179422
		2025m3,2025,3,199863
		2025m4,2025,4,200708
		2025m5,2025,5,191286
		2025m6,2025,6,169755

00_original_index/03_data/data_given/insolvencies_bw_q.csv

0 → 100644

+70 −0

Original line number	Diff line number	Diff line
		date,year,quarter,insolv_constr,affected_workers_constr,insolv_realest,affected_workers_realest
		2008q1,2008,1,50,268,9,14
		2008q2,2008,2,52,390,12,33
		2008q3,2008,3,42,185,11,22
		2008q4,2008,4,57,233,16,133
		2009q1,2009,1,59,185,18,30
		2009q2,2009,2,66,523,16,95
		2009q3,2009,3,57,252,18,26
		2009q4,2009,4,62,343,13,2
		2010q1,2010,1,63,208,12,42
		2010q2,2010,2,49,336,10,28
		2010q3,2010,3,50,335,9,19
		2010q4,2010,4,63,417,10,6
		2011q1,2011,1,54,528,14,10
		2011q2,2011,2,71,777,30,23
		2011q3,2011,3,54,505,19,43
		2011q4,2011,4,53,222,15,9
		2012q1,2012,1,70,324,9,37
		2012q2,2012,2,52,184,7,3
		2012q3,2012,3,56,425,9,9
		2012q4,2012,4,42,226,11,5
		2013q1,2013,1,47,217,9,32
		2013q2,2013,2,40,280,14,11
		2013q3,2013,3,53,298,15,9
		2013q4,2013,4,41,279,4,5
		2014q1,2014,1,42,232,8,7
		2014q2,2014,2,50,424,18,219
		2014q3,2014,3,35,78,6,6
		2014q4,2014,4,52,291,9,22
		2015q1,2015,1,46,309,5,11
		2015q2,2015,2,61,329,6,6
		2015q3,2015,3,43,210,12,15
		2015q4,2015,4,62,376,13,35
		2016q1,2016,1,51,145,12,3
		2016q2,2016,2,41,110,15,68
		2016q3,2016,3,65,223,11,19
		2016q4,2016,4,44,169,6,2
		2017q1,2017,1,56,333,2,1
		2017q2,2017,2,48,220,13,29
		2017q3,2017,3,45,154,15,41
		2017q4,2017,4,57,298,9,2
		2018q1,2018,1,56,333,2,1
		2018q2,2018,2,48,220,13,29
		2018q3,2018,3,45,154,15,41
		2018q4,2018,4,57,298,9,2
		2019q1,2019,1,57,264,6,5
		2019q2,2019,2,56,309,11,98
		2019q3,2019,3,46,391,10,21
		2019q4,2019,4,42,254,11,2
		2020q1,2020,1,44,128,11,32
		2020q2,2020,2,43,376,6,16
		2020q3,2020,3,32,131,7,13
		2020q4,2020,4,32,141,6,161
		2021q1,2021,1,43,129,5,1
		2021q2,2021,2,45,172,2,
		2021q3,2021,3,35,213,2,10
		2021q4,2021,4,50,266,6,2
		2022q1,2022,1,46,119,4,20
		2022q2,2022,2,63,267,8,3
		2022q3,2022,3,48,353,5,7
		2022q4,2022,4,47,293,3,12
		2023q1,2023,1,68,600,6,25
		2023q2,2023,2,63,354,7,1
		2023q3,2023,3,62,282,11,13
		2023q4,2023,4,58,378,11,8
		2024q1,2024,1,74,262,31,40
		2024q2,2024,2,90,718,11,100
		2024q3,2024,3,63,243,29,23
		2024q4,2024,4,73,406,14,68
		2025q1,2025,1,72,384,21,18

00_original_index/03_data/data_given/order_stocks_bw_q.csv

0 → 100644

+123 −0

Original line number	Diff line number	Diff line
		date,year,quarter,order_stocks
		1995q1,1995,1,938127
		1995q2,1995,2,876763
		1995q3,1995,3,806238
		1995q4,1995,4,734169
		1996q1,1996,1,748818
		1996q2,1996,2,722924
		1996q3,1996,3,700762
		1996q4,1996,4,664992
		1997q1,1997,1,656667
		1997q2,1997,2,615257
		1997q3,1997,3,584909
		1997q4,1997,4,530272
		1998q1,1998,1,560395
		1998q2,1998,2,529266
		1998q3,1998,3,522193
		1998q4,1998,4,514510
		1999q1,1999,1,548898
		1999q2,1999,2,516135
		1999q3,1999,3,510470
		1999q4,1999,4,460163
		2000q1,2000,1,476136
		2000q2,2000,2,481977
		2000q3,2000,3,432444
		2000q4,2000,4,365261
		2001q1,2001,1,389929
		2001q2,2001,2,394389
		2001q3,2001,3,377129
		2001q4,2001,4,288565
		2002q1,2002,1,326463
		2002q2,2002,2,336216
		2002q3,2002,3,324748
		2002q4,2002,4,299782
		2003q1,2003,1,321091
		2003q2,2003,2,326193
		2003q3,2003,3,325025
		2003q4,2003,4,322477
		2004q1,2004,1,348218
		2004q2,2004,2,331250
		2004q3,2004,3,330399
		2004q4,2004,4,285140
		2005q1,2005,1,335298
		2005q2,2005,2,334726
		2005q3,2005,3,353489
		2005q4,2005,4,349269
		2006q1,2006,1,398997
		2006q2,2006,2,404712
		2006q3,2006,3,386891
		2006q4,2006,4,343273
		2007q1,2007,1,371962
		2007q2,2007,2,355116
		2007q3,2007,3,338182
		2007q4,2007,4,312402
		2008q1,2008,1,324445
		2008q2,2008,2,310761
		2008q3,2008,3,319057
		2008q4,2008,4,283971
		2009q1,2009,1,309435
		2009q2,2009,2,350206
		2009q3,2009,3,334674
		2009q4,2009,4,348416
		2010q1,2010,1,386358
		2010q2,2010,2,414894
		2010q3,2010,3,434421
		2010q4,2010,4,406322
		2011q1,2011,1,451297
		2011q2,2011,2,481239
		2011q3,2011,3,451394
		2011q4,2011,4,427660
		2012q1,2012,1,454161
		2012q2,2012,2,475744
		2012q3,2012,3,523287
		2012q4,2012,4,530142
		2013q1,2013,1,599664
		2013q2,2013,2,597904
		2013q3,2013,3,610879
		2013q4,2013,4,568892
		2014q1,2014,1,615722
		2014q2,2014,2,634072
		2014q3,2014,3,602607
		2014q4,2014,4,569801
		2015q1,2015,1,613107
		2015q2,2015,2,688316
		2015q3,2015,3,697519
		2015q4,2015,4,716844
		2016q1,2016,1,753388
		2016q2,2016,2,856339
		2016q3,2016,3,894988
		2016q4,2016,4,858023
		2017q1,2017,1,949521
		2017q2,2017,2,995279
		2017q3,2017,3,939791
		2017q4,2017,4,928430
		2018q1,2018,1,1054732
		2018q2,2018,2,1093669
		2018q3,2018,3,1135303
		2018q4,2018,4,1115490
		2019q1,2019,1,1242773
		2019q2,2019,2,1264667
		2019q3,2019,3,1293613
		2019q4,2019,4,1214510
		2020q1,2020,1,1346919
		2020q2,2020,2,1342087
		2020q3,2020,3,1373974
		2020q4,2020,4,1375991
		2021q1,2021,1,1515696
		2021q2,2021,2,1600033
		2021q3,2021,3,1573912
		2021q4,2021,4,1693978
		2022q1,2022,1,1823052
		2022q2,2022,2,1799336
		2022q3,2022,3,1771708
		2022q4,2022,4,1672486
		2023q1,2023,1,1680900
		2023q2,2023,2,1520087
		2023q3,2023,3,1423033
		2023q4,2023,4,1324920
		2024q1,2024,1,1328605
		2024q2,2024,2,1320686
		2024q3,2024,3,1372134
		2024q4,2024,4,1358708
		2025q1,2025,1,1420168
		2025q2,2025,2,1455244

00_original_index/03_data/data_given/rett_bw_q.csv

0 → 100644

+106 −0

Original line number	Diff line number	Diff line
		date,year,quarter,rett_bw
		1999q1,1999,1,227118
		1999q2,1999,2,196469
		1999q3,1999,3,213101
		1999q4,1999,4,205861
		2000q1,2000,1,207260
		2000q2,2000,2,177884
		2000q3,2000,3,174225
		2000q4,2000,4,162842
		2001q1,2001,1,197477
		2001q2,2001,2,160496
		2001q3,2001,3,169953
		2001q4,2001,4,159105
		2002q1,2002,1,191504
		2002q2,2002,2,167472
		2002q3,2002,3,171791
		2002q4,2002,4,163508
		2003q1,2003,1,231069
		2003q2,2003,2,153802
		2003q3,2003,3,164037
		2003q4,2003,4,177740
		2004q1,2004,1,199414
		2004q2,2004,2,145200
		2004q3,2004,3,155286
		2004q4,2004,4,172496
		2005q1,2005,1,187241
		2005q2,2005,2,153741
		2005q3,2005,3,177561
		2005q4,2005,4,186846
		2006q1,2006,1,261659
		2006q2,2006,2,172072
		2006q3,2006,3,175929
		2006q4,2006,4,203184
		2007q1,2007,1,238321
		2007q2,2007,2,192470
		2007q3,2007,3,215891
		2007q4,2007,4,217744
		2008q1,2008,1,236602
		2008q2,2008,2,185283
		2008q3,2008,3,193825
		2008q4,2008,4,178740
		2009q1,2009,1,168064
		2009q2,2009,2,161991
		2009q3,2009,3,189200
		2009q4,2009,4,169521
		2010q1,2010,1,188715
		2010q2,2010,2,174669
		2010q3,2010,3,216124
		2010q4,2010,4,210412
		2011q1,2011,1,214182
		2011q2,2011,2,199721
		2011q3,2011,3,236529
		2011q4,2011,4,292613
		2012q1,2012,1,268936
		2012q2,2012,2,274612
		2012q3,2012,3,318424
		2012q4,2012,4,307538
		2013q1,2013,1,339435
		2013q2,2013,2,314400
		2013q3,2013,3,335804
		2013q4,2013,4,327575
		2014q1,2014,1,345146
		2014q2,2014,2,313877
		2014q3,2014,3,349479
		2014q4,2014,4,350228
		2015q1,2015,1,377673
		2015q2,2015,2,367263
		2015q3,2015,3,437107
		2015q4,2015,4,422214
		2016q1,2016,1,419313
		2016q2,2016,2,401423
		2016q3,2016,3,403166
		2016q4,2016,4,372287
		2017q1,2017,1,446161
		2017q2,2017,2,424259
		2017q3,2017,3,430958
		2017q4,2017,4,451172
		2018q1,2018,1,490837
		2018q2,2018,2,444082
		2018q3,2018,3,495139
		2018q4,2018,4,492337
		2019q1,2019,1,510160
		2019q2,2019,2,525706
		2019q3,2019,3,523316
		2019q4,2019,4,531855
		2020q1,2020,1,581606
		2020q2,2020,2,516496
		2020q3,2020,3,557378
		2020q4,2020,4,600537
		2021q1,2021,1,624666
		2021q2,2021,2,595963
		2021q3,2021,3,628232
		2021q4,2021,4,612313
		2022q1,2022,1,668633
		2022q2,2022,2,575496
		2022q3,2022,3,548494
		2022q4,2022,4,445337
		2023q1,2023,1,391425
		2023q2,2023,2,435383
		2023q3,2023,3,391897
		2023q4,2023,4,439532
		2024q1,2024,1,432403
		2024q2,2024,2,454866
		2024q3,2024,3,476214
		2024q4,2024,4,452155
		2025q1,2025,1,490162

00_original_index/03_data/data_given/turnover_apartment_bw_m.csv

0 → 100644

+367 −0

Original line number	Diff line number	Diff line
		date,year,month,turnover_apartment
		1995m1,1995,1,167742
		1995m2,1995,2,189321
		1995m3,1995,3,249821
		1995m4,1995,4,243450
		1995m5,1995,5,255563
		1995m6,1995,6,256891
		1995m7,1995,7,271212
		1995m8,1995,8,221921
		1995m9,1995,9,235725
		1995m10,1995,10,271509
		1995m11,1995,11,273988
		1995m12,1995,12,281556
		1996m1,1996,1,158145
		1996m2,1996,2,146045
		1996m3,1996,3,186714
		1996m4,1996,4,223380
		1996m5,1996,5,225707
		1996m6,1996,6,233847
		1996m7,1996,7,272000
		1996m8,1996,8,208676
		1996m9,1996,9,227574
		1996m10,1996,10,246302
		1996m11,1996,11,234190
		1996m12,1996,12,237824
		1997m1,1997,1,115959
		1997m2,1997,2,146841
		1997m3,1997,3,169630
		1997m4,1997,4,199194
		1997m5,1997,5,192811
		1997m6,1997,6,222904
		1997m7,1997,7,223260
		1997m8,1997,8,187782
		1997m9,1997,9,200395
		1997m10,1997,10,217179
		1997m11,1997,11,207374
		1997m12,1997,12,210659
		1998m1,1998,1,115224
		1998m2,1998,2,124107
		1998m3,1998,3,196228
		1998m4,1998,4,175400
		1998m5,1998,5,173258
		1998m6,1998,6,183140
		1998m7,1998,7,211559
		1998m8,1998,8,156531
		1998m9,1998,9,173504
		1998m10,1998,10,195092
		1998m11,1998,11,186070
		1998m12,1998,12,196321
		1999m1,1999,1,109910
		1999m2,1999,2,107434
		1999m3,1999,3,154293
		1999m4,1999,4,179450
		1999m5,1999,5,174395
		1999m6,1999,6,187266
		1999m7,1999,7,205699
		1999m8,1999,8,170489
		1999m9,1999,9,193043
		1999m10,1999,10,203987
		1999m11,1999,11,207048
		1999m12,1999,12,194325
		2000m1,2000,1,109510
		2000m2,2000,2,134760
		2000m3,2000,3,174350
		2000m4,2000,4,161228
		2000m5,2000,5,196976
		2000m6,2000,6,182587
		2000m7,2000,7,193142
		2000m8,2000,8,173723
		2000m9,2000,9,180557
		2000m10,2000,10,175838
		2000m11,2000,11,183253
		2000m12,2000,12,182384
		2001m1,2001,1,102327
		2001m2,2001,2,110470
		2001m3,2001,3,133336
		2001m4,2001,4,135103
		2001m5,2001,5,146269
		2001m6,2001,6,144719
		2001m7,2001,7,159486
		2001m8,2001,8,125117
		2001m9,2001,9,134188
		2001m10,2001,10,140866
		2001m11,2001,11,141524
		2001m12,2001,12,136546
		2002m1,2002,1,83129
		2002m2,2002,2,87150
		2002m3,2002,3,106823
		2002m4,2002,4,122995
		2002m5,2002,5,116191
		2002m6,2002,6,121800
		2002m7,2002,7,136472
		2002m8,2002,8,121474
		2002m9,2002,9,121056
		2002m10,2002,10,123006
		2002m11,2002,11,125359
		2002m12,2002,12,129246
		2003m1,2003,1,64901
		2003m2,2003,2,64238
		2003m3,2003,3,90566
		2003m4,2003,4,106181
		2003m5,2003,5,117793
		2003m6,2003,6,120595
		2003m7,2003,7,136596
		2003m8,2003,8,109440
		2003m9,2003,9,115639
		2003m10,2003,10,129669
		2003m11,2003,11,127468
		2003m12,2003,12,127138
		2004m1,2004,1,66276
		2004m2,2004,2,75498
		2004m3,2004,3,101011
		2004m4,2004,4,112147
		2004m5,2004,5,113068
		2004m6,2004,6,132849
		2004m7,2004,7,131738
		2004m8,2004,8,105974
		2004m9,2004,9,117165
		2004m10,2004,10,122336
		2004m11,2004,11,125581
		2004m12,2004,12,121017
		2005m1,2005,1,63648
		2005m2,2005,2,57973
		2005m3,2005,3,74612
		2005m4,2005,4,105854
		2005m5,2005,5,115540
		2005m6,2005,6,124598
		2005m7,2005,7,124205
		2005m8,2005,8,109686
		2005m9,2005,9,125883
		2005m10,2005,10,124152
		2005m11,2005,11,128752
		2005m12,2005,12,129926
		2006m1,2006,1,61738
		2006m2,2006,2,71495
		2006m3,2006,3,98251
		2006m4,2006,4,110840
		2006m5,2006,5,135080
		2006m6,2006,6,129777
		2006m7,2006,7,135218
		2006m8,2006,8,121418
		2006m9,2006,9,130844
		2006m10,2006,10,142905
		2006m11,2006,11,156322
		2006m12,2006,12,175756
		2007m1,2007,1,82606
		2007m2,2007,2,70522
		2007m3,2007,3,92004
		2007m4,2007,4,95909
		2007m5,2007,5,104647
		2007m6,2007,6,103709
		2007m7,2007,7,121720
		2007m8,2007,8,95983
		2007m9,2007,9,106995
		2007m10,2007,10,123317
		2007m11,2007,11,117051
		2007m12,2007,12,108242
		2008m1,2008,1,72058
		2008m2,2008,2,85851
		2008m3,2008,3,87916
		2008m4,2008,4,102244
		2008m5,2008,5,93458
		2008m6,2008,6,105649
		2008m7,2008,7,117187
		2008m8,2008,8,91775
		2008m9,2008,9,105171
		2008m10,2008,10,105241
		2008m11,2008,11,112835
		2008m12,2008,12,107215
		2009m1,2009,1,47037
		2009m2,2009,2,56408
		2009m3,2009,3,81885
		2009m4,2009,4,100020
		2009m5,2009,5,113059
		2009m6,2009,6,103746
		2009m7,2009,7,126944
		2009m8,2009,8,95401
		2009m9,2009,9,110889
		2009m10,2009,10,112166
		2009m11,2009,11,124750
		2009m12,2009,12,120038
		2010m1,2010,1,45577
		2010m2,2010,2,51250
		2010m3,2010,3,91969
		2010m4,2010,4,103416
		2010m5,2010,5,110333
		2010m6,2010,6,113388
		2010m7,2010,7,127533
		2010m8,2010,8,102658
		2010m9,2010,9,119789
		2010m10,2010,10,136671
		2010m11,2010,11,131988
		2010m12,2010,12,116212
		2011m1,2011,1,64023
		2011m2,2011,2,86041
		2011m3,2011,3,110849
		2011m4,2011,4,124374
		2011m5,2011,5,137157
		2011m6,2011,6,123778
		2011m7,2011,7,135645
		2011m8,2011,8,121482
		2011m9,2011,9,134736
		2011m10,2011,10,138318
		2011m11,2011,11,164301
		2011m12,2011,12,158292
		2012m1,2012,1,82648
		2012m2,2012,2,85178
		2012m3,2012,3,123838
		2012m4,2012,4,128097
		2012m5,2012,5,146077
		2012m6,2012,6,151511
		2012m7,2012,7,155487
		2012m8,2012,8,144840
		2012m9,2012,9,149156
		2012m10,2012,10,157416
		2012m11,2012,11,165328
		2012m12,2012,12,148289
		2013m1,2013,1,82590
		2013m2,2013,2,84132
		2013m3,2013,3,132623
		2013m4,2013,4,144639
		2013m5,2013,5,143587
		2013m6,2013,6,156718
		2013m7,2013,7,173131
		2013m8,2013,8,146706
		2013m9,2013,9,156313
		2013m10,2013,10,173455
		2013m11,2013,11,164892
		2013m12,2013,12,166177
		2014m1,2014,1,102342
		2014m2,2014,2,135113
		2014m3,2014,3,149357
		2014m4,2014,4,157277
		2014m5,2014,5,153989
		2014m6,2014,6,157296
		2014m7,2014,7,178976
		2014m8,2014,8,137154
		2014m9,2014,9,160549
		2014m10,2014,10,172548
		2014m11,2014,11,194861
		2014m12,2014,12,177244
		2015m1,2015,1,101416
		2015m2,2015,2,107794
		2015m3,2015,3,153526
		2015m4,2015,4,151429
		2015m5,2015,5,160343
		2015m6,2015,6,172925
		2015m7,2015,7,189731
		2015m8,2015,8,151456
		2015m9,2015,9,169856
		2015m10,2015,10,196246
		2015m11,2015,11,182134
		2015m12,2015,12,195708
		2016m1,2016,1,96417
		2016m2,2016,2,144854
		2016m3,2016,3,168911
		2016m4,2016,4,179078
		2016m5,2016,5,174125
		2016m6,2016,6,195347
		2016m7,2016,7,198662
		2016m8,2016,8,183963
		2016m9,2016,9,190582
		2016m10,2016,10,200518
		2016m11,2016,11,201575
		2016m12,2016,12,293190
		2017m1,2017,1,102673
		2017m2,2017,2,135429
		2017m3,2017,3,208162
		2017m4,2017,4,203001
		2017m5,2017,5,225013
		2017m6,2017,6,240571
		2017m7,2017,7,249729
		2017m8,2017,8,229857
		2017m9,2017,9,244035
		2017m10,2017,10,232447
		2017m11,2017,11,282385
		2017m12,2017,12,263285
		2018m1,2018,1,193793
		2018m2,2018,2,191967
		2018m3,2018,3,225385
		2018m4,2018,4,240851
		2018m5,2018,5,237170
		2018m6,2018,6,239736
		2018m7,2018,7,273065
		2018m8,2018,8,234530
		2018m9,2018,9,235473
		2018m10,2018,10,284377
		2018m11,2018,11,266732
		2018m12,2018,12,264514
		2019m1,2019,1,167550
		2019m2,2019,2,212662
		2019m3,2019,3,251709
		2019m4,2019,4,255310
		2019m5,2019,5,270518
		2019m6,2019,6,245752
		2019m7,2019,7,290550
		2019m8,2019,8,243280
		2019m9,2019,9,256007
		2019m10,2019,10,293744
		2019m11,2019,11,296217
		2019m12,2019,12,292930
		2020m1,2020,1,205351
		2020m2,2020,2,216408
		2020m3,2020,3,285312
		2020m4,2020,4,277882
		2020m5,2020,5,284978
		2020m6,2020,6,278500
		2020m7,2020,7,342022
		2020m8,2020,8,251135
		2020m9,2020,9,278808
		2020m10,2020,10,337489
		2020m11,2020,11,363688
		2020m12,2020,12,407474
		2021m1,2021,1,156754
		2021m2,2021,2,219253
		2021m3,2021,3,300355
		2021m4,2021,4,307130
		2021m5,2021,5,276052
		2021m6,2021,6,313595
		2021m7,2021,7,326768
		2021m8,2021,8,269404
		2021m9,2021,9,316753
		2021m10,2021,10,325458
		2021m11,2021,11,317876
		2021m12,2021,12,349558
		2022m1,2022,1,202160
		2022m2,2022,2,228843
		2022m3,2022,3,342945
		2022m4,2022,4,307717
		2022m5,2022,5,323983
		2022m6,2022,6,297408
		2022m7,2022,7,377874
		2022m8,2022,8,321064
		2022m9,2022,9,340042
		2022m10,2022,10,334332
		2022m11,2022,11,374248
		2022m12,2022,12,353307
		2023m1,2023,1,222612
		2023m2,2023,2,288995
		2023m3,2023,3,350942
		2023m4,2023,4,306375
		2023m5,2023,5,341381
		2023m6,2023,6,351364
		2023m7,2023,7,368615
		2023m8,2023,8,310196
		2023m9,2023,9,323272
		2023m10,2023,10,324815
		2023m11,2023,11,330870
		2023m12,2023,12,345701
		2024m1,2024,1,194904
		2024m2,2024,2,259219
		2024m3,2024,3,292040
		2024m4,2024,4,292124
		2024m5,2024,5,264819
		2024m6,2024,6,305314
		2024m7,2024,7,317771
		2024m8,2024,8,266967
		2024m9,2024,9,277530
		2024m10,2024,10,296073
		2024m11,2024,11,308495
		2024m12,2024,12,324544
		2025m1,2025,1,184491
		2025m2,2025,2,229071
		2025m3,2025,3,279405
		2025m4,2025,4,270266
		2025m5,2025,5,282960
		2025m6,2025,6,273543

00_original_index/03_data/data_given/vacancies_construction_D_m.csv

0 → 100644

+224 −0

Original line number	Diff line number	Diff line
		date,year,month,vacancies_constr
		2007m1,2007,1,19057
		2007m2,2007,2,21174
		2007m3,2007,3,22269
		2007m4,2007,4,21713
		2007m5,2007,5,20399
		2007m6,2007,6,20180
		2007m7,2007,7,21129
		2007m8,2007,8,21895
		2007m9,2007,9,21674
		2007m10,2007,10,20365
		2007m11,2007,11,17881
		2007m12,2007,12,15273
		2008m1,2008,1,14883
		2008m2,2008,2,17574
		2008m3,2008,3,18407
		2008m4,2008,4,18560
		2008m5,2008,5,18752
		2008m6,2008,6,19914
		2008m7,2008,7,20895
		2008m8,2008,8,21535
		2008m9,2008,9,21164
		2008m10,2008,10,19954
		2008m11,2008,11,17863
		2008m12,2008,12,14606
		2009m1,2009,1,13584
		2009m2,2009,2,14903
		2009m3,2009,3,15720
		2009m4,2009,4,15552
		2009m5,2009,5,15402
		2009m6,2009,6,15058
		2009m7,2009,7,15584
		2009m8,2009,8,16665
		2009m9,2009,9,17069
		2009m10,2009,10,16158
		2009m11,2009,11,14391
		2009m12,2009,12,12803
		2010m1,2010,1,12246
		2010m2,2010,2,14509
		2010m3,2010,3,17343
		2010m4,2010,4,18913
		2010m5,2010,5,19634
		2010m6,2010,6,19827
		2010m7,2010,7,20641
		2010m8,2010,8,21273
		2010m9,2010,9,22042
		2010m10,2010,10,21649
		2010m11,2010,11,20017
		2010m12,2010,12,16797
		2011m1,2011,1,17867
		2011m2,2011,2,22451
		2011m3,2011,3,24540
		2011m4,2011,4,25965
		2011m5,2011,5,26119
		2011m6,2011,6,26019
		2011m7,2011,7,26562
		2011m8,2011,8,27224
		2011m9,2011,9,27702
		2011m10,2011,10,26997
		2011m11,2011,11,25159
		2011m12,2011,12,22231
		2012m1,2012,1,22814
		2012m2,2012,2,25465
		2012m3,2012,3,27864
		2012m4,2012,4,28122
		2012m5,2012,5,27584
		2012m6,2012,6,26717
		2012m7,2012,7,26967
		2012m8,2012,8,26558
		2012m9,2012,9,26438
		2012m10,2012,10,25480
		2012m11,2012,11,23945
		2012m12,2012,12,21385
		2013m1,2013,1,21798
		2013m2,2013,2,24700
		2013m3,2013,3,26450
		2013m4,2013,4,26898
		2013m5,2013,5,26988
		2013m6,2013,6,26623
		2013m7,2013,7,26719
		2013m8,2013,8,26919
		2013m9,2013,9,26897
		2013m10,2013,10,26083
		2013m11,2013,11,24868
		2013m12,2013,12,22881
		2014m1,2014,1,23444
		2014m2,2014,2,26106
		2014m3,2014,3,27591
		2014m4,2014,4,27362
		2014m5,2014,5,26089
		2014m6,2014,6,25911
		2014m7,2014,7,26003
		2014m8,2014,8,26312
		2014m9,2014,9,26591
		2014m10,2014,10,26271
		2014m11,2014,11,25152
		2014m12,2014,12,23388
		2015m1,2015,1,24141
		2015m2,2015,2,27051
		2015m3,2015,3,29231
		2015m4,2015,4,29478
		2015m5,2015,5,29882
		2015m6,2015,6,29710
		2015m7,2015,7,30161
		2015m8,2015,8,30574
		2015m9,2015,9,31189
		2015m10,2015,10,31328
		2015m11,2015,11,30612
		2015m12,2015,12,29225
		2016m1,2016,1,29782
		2016m2,2016,2,33345
		2016m3,2016,3,35541
		2016m4,2016,4,36958
		2016m5,2016,5,37182
		2016m6,2016,6,37349
		2016m7,2016,7,37773
		2016m8,2016,8,38042
		2016m9,2016,9,38449
		2016m10,2016,10,38549
		2016m11,2016,11,37375
		2016m12,2016,12,35724
		2017m1,2017,1,36183
		2017m2,2017,2,39975
		2017m3,2017,3,42358
		2017m4,2017,4,43709
		2017m5,2017,5,44249
		2017m6,2017,6,44557
		2017m7,2017,7,45081
		2017m8,2017,8,45809
		2017m9,2017,9,46566
		2017m10,2017,10,46519
		2017m11,2017,11,45420
		2017m12,2017,12,43861
		2018m1,2018,1,44020
		2018m2,2018,2,47755
		2018m3,2018,3,49205
		2018m4,2018,4,50386
		2018m5,2018,5,50739
		2018m6,2018,6,50743
		2018m7,2018,7,51048
		2018m8,2018,8,51090
		2018m9,2018,9,51290
		2018m10,2018,10,50622
		2018m11,2018,11,49203
		2018m12,2018,12,47443
		2019m1,2019,1,46926
		2019m2,2019,2,49669
		2019m3,2019,3,51455
		2019m4,2019,4,51969
		2019m5,2019,5,52066
		2019m6,2019,6,51754
		2019m7,2019,7,51439
		2019m8,2019,8,50739
		2019m9,2019,9,50491
		2019m10,2019,10,49327
		2019m11,2019,11,47240
		2019m12,2019,12,44470
		2020m1,2020,1,44130
		2020m2,2020,2,46673
		2020m3,2020,3,47568
		2020m4,2020,4,44648
		2020m5,2020,5,43834
		2020m6,2020,6,44256
		2020m7,2020,7,45056
		2020m8,2020,8,45540
		2020m9,2020,9,46176
		2020m10,2020,10,46552
		2020m11,2020,11,45961
		2020m12,2020,12,44326
		2021m1,2021,1,44449
		2021m2,2021,2,46847
		2021m3,2021,3,49221
		2021m4,2021,4,51074
		2021m5,2021,5,52041
		2021m6,2021,6,52673
		2021m7,2021,7,53869
		2021m8,2021,8,54925
		2021m9,2021,9,55677
		2021m10,2021,10,56324
		2021m11,2021,11,56058
		2021m12,2021,12,53134
		2022m1,2022,1,53780
		2022m2,2022,2,56733
		2022m3,2022,3,58273
		2022m4,2022,4,59439
		2022m5,2022,5,59954
		2022m6,2022,6,59526
		2022m7,2022,7,59120
		2022m8,2022,8,58326
		2022m9,2022,9,57621
		2022m10,2022,10,55827
		2022m11,2022,11,53425
		2022m12,2022,12,50210
		2023m1,2023,1,49912
		2023m2,2023,2,51169
		2023m3,2023,3,52003
		2023m4,2023,4,52064
		2023m5,2023,5,52080
		2023m6,2023,6,51384
		2023m7,2023,7,51009
		2023m8,2023,8,50001
		2023m9,2023,9,49465
		2023m10,2023,10,48843
		2023m11,2023,11,47823
		2023m12,2023,12,46045
		2024m1,2024,1,45656
		2024m2,2024,2,46701
		2024m3,2024,3,47307
		2024m4,2024,4,47884
		2024m5,2024,5,47906
		2024m6,2024,6,47914
		2024m7,2024,7,47790
		2024m8,2024,8,47702
		2024m9,2024,9,47499
		2024m10,2024,10,47050
		2024m11,2024,11,46202
		2024m12,2024,12,45197
		2025m1,2025,1,45030
		2025m2,2025,2,45995
		2025m3,2025,3,46828
		2025m4,2025,4,47407
		2025m5,2025,5,47235
		2025m6,2025,6,47136
		2025m7,2025,7,46901

00_original_index/03_data/data_given/value_added_construction_D_q.csv

0 → 100644

+123 −0

Original line number	Diff line number	Diff line
		date,year,quarter,value_added_original,value_added_seasonadj
		1995q1,1995,1,118.57,142.83
		1995q2,1995,2,148.09,146.42
		1995q3,1995,3,150.38,143.21
		1995q4,1995,4,154.83,140.05
		1996q1,1996,1,101.7,126.71
		1996q2,1996,2,141.29,140.02
		1996q3,1996,3,146.3,137.33
		1996q4,1996,4,150.61,137.34
		1997q1,1997,1,101.62,130.02
		1997q2,1997,2,138.63,134.56
		1997q3,1997,3,142.03,132.81
		1997q4,1997,4,146.39,132.73
		1998q1,1998,1,106.87,131.96
		1998q2,1998,2,128.58,128.04
		1998q3,1998,3,136.05,126.49
		1998q4,1998,4,139.75,123.5
		1999q1,1999,1,100.74,125.19
		1999q2,1999,2,126.59,125.1
		1999q3,1999,3,136.94,127.37
		1999q4,1999,4,143.07,126.83
		2000q1,2000,1,104.49,126.69
		2000q2,2000,2,124.58,124.7
		2000q3,2000,3,131.21,123.26
		2000q4,2000,4,135.22,121.31
		2001q1,2001,1,95.54000000000001,118.56
		2001q2,2001,2,115.87,116.31
		2001q3,2001,3,123.74,115.67
		2001q4,2001,4,129.08,115.64
		2002q1,2002,1,89.31,114.53
		2002q2,2002,2,111.33,110.67
		2002q3,2002,3,119.64,110.26
		2002q4,2002,4,121.46,108.11
		2003q1,2003,1,81.29000000000001,105.82
		2003q2,2003,2,105.73,106.36
		2003q3,2003,3,116.43,107.09
		2003q4,2003,4,118.44,104.29
		2004q1,2004,1,81.04000000000001,104.44
		2004q2,2004,2,103.42,102.87
		2004q3,2004,3,109.33,100.06
		2004q4,2004,4,114.79,98.13
		2005q1,2005,1,71.76000000000001,96.8
		2005q2,2005,2,100.23,97.63
		2005q3,2005,3,107.22,98.52
		2005q4,2005,4,111.87,96.25
		2006q1,2006,1,69.45999999999999,92.18000000000001
		2006q2,2006,2,97.09,97.56
		2006q3,2006,3,107.12,99.88
		2006q4,2006,4,116.7,101.45
		2007q1,2007,1,76.81,99.81999999999999
		2007q2,2007,2,94.95,95.48
		2007q3,2007,3,102.77,95.73
		2007q4,2007,4,112.29,97.52
		2008q1,2008,1,75.20999999999999,99.78
		2008q2,2008,2,96.33,93.89
		2008q3,2008,3,100.65,92.59
		2008q4,2008,4,107.66,92.58
		2009q1,2009,1,69.41,93.05
		2009q2,2009,2,92.20999999999999,92.8
		2009q3,2009,3,100.89,92.70999999999999
		2009q4,2009,4,109.44,92.33
		2010q1,2010,1,69.95,93.15000000000001
		2010q2,2010,2,100.27,99.86
		2010q3,2010,3,105.41,97.3
		2010q4,2010,4,110.53,93.53
		2011q1,2011,1,76.73999999999999,99.03
		2011q2,2011,2,99.95999999999999,99.53
		2011q3,2011,3,105.48,97.81
		2011q4,2011,4,117.25,101.56
		2012q1,2012,1,79.48999999999999,100.62
		2012q2,2012,2,99.56999999999999,100.18
		2012q3,2012,3,105.26,99.09
		2012q4,2012,4,111.88,97.55
		2013q1,2013,1,73.20999999999999,95.77
		2013q2,2013,2,98.61,98.14
		2013q3,2013,3,106.54,99.70999999999999
		2013q4,2013,4,114.4,100.68
		2014q1,2014,1,80.73999999999999,102.1
		2014q2,2014,2,99.01000000000001,99.59999999999999
		2014q3,2014,3,105.6,99.23999999999999
		2014q4,2014,4,113.03,99.02
		2015q1,2015,1,77.04000000000001,97.45999999999999
		2015q2,2015,2,95.84999999999999,96.39
		2015q3,2015,3,102.14,96.06
		2015q4,2015,4,112.88,96.89
		2016q1,2016,1,77.98,98.66
		2016q2,2016,2,101.12,98.53
		2016q3,2016,3,103.56,98.13
		2016q4,2016,4,111.95,97.41
		2017q1,2017,1,81.34,98.98999999999999
		2017q2,2017,2,99.68000000000001,100.35
		2017q3,2017,3,104.05,100.03
		2017q4,2017,4,113.99,101.24
		2018q1,2018,1,81.93000000000001,100.73
		2018q2,2018,2,102.81,102.44
		2018q3,2018,3,106.32,102.59
		2018q4,2018,4,117.25,104.26
		2019q1,2019,1,81.14,99.55
		2019q2,2019,2,97.75,98.38
		2019q3,2019,3,103.79,99.17
		2019q4,2019,4,111.18,98.69
		2020q1,2020,1,84.06,101.12
		2020q2,2020,2,96.54000000000001,97.16
		2020q3,2020,3,100.38,95.8
		2020q4,2020,4,119.02,104.01
		2021q1,2021,1,77.51000000000001,93.83
		2021q2,2021,2,98.61,98.20999999999999
		2021q3,2021,3,100.29,96.14
		2021q4,2021,4,110.37,96.02
		2022q1,2022,1,74.56,89.11
		2022q2,2022,2,86.53,86.34999999999999
		2022q3,2022,3,87.23999999999999,83.76000000000001
		2022q4,2022,4,95.09,82.73
		2023q1,2023,1,70.44,83.64
		2023q2,2023,2,81.77,82.59
		2023q3,2023,3,84.04000000000001,81.84
		2023q4,2023,4,92.03,80.65000000000001
		2024q1,2024,1,67.67,81.43000000000001
		2024q2,2024,2,79.64,79.8
		2024q3,2024,3,80.98,78.16
		2024q4,2024,4,87.45,77.11
		2025q1,2025,1,64.67,78.13
		2025q2,2025,2,74.18000000000001,75.20999999999999

00_original_index/03_data/data_given/workers_construction_bw_m.csv

0 → 100644

+163 −0

Original line number	Diff line number	Diff line
		date,year,month,workers
		2012m1,2012,1,47529
		2012m2,2012,2,47189
		2012m3,2012,3,47733
		2012m4,2012,4,48005
		2012m5,2012,5,48209
		2012m6,2012,6,48684
		2012m7,2012,7,48480
		2012m8,2012,8,48616
		2012m9,2012,9,48752
		2012m10,2012,10,49160
		2012m11,2012,11,48956
		2012m12,2012,12,48480
		2013m1,2013,1,47801
		2013m2,2013,2,47869
		2013m3,2013,3,48345
		2013m4,2013,4,48752
		2013m5,2013,5,49160
		2013m6,2013,6,49228
		2013m7,2013,7,49840
		2013m8,2013,8,50112
		2013m9,2013,9,50520
		2013m10,2013,10,50724
		2013m11,2013,11,50316
		2013m12,2013,12,49840
		2014m1,2014,1,49432
		2014m2,2014,2,49364
		2014m3,2014,3,49976
		2014m4,2014,4,50248
		2014m5,2014,5,50248
		2014m6,2014,6,50588
		2014m7,2014,7,50792
		2014m8,2014,8,50996
		2014m9,2014,9,51404
		2014m10,2014,10,50996
		2014m11,2014,11,50792
		2014m12,2014,12,49908
		2015m1,2015,1,49364
		2015m2,2015,2,49704
		2015m3,2015,3,49976
		2015m4,2015,4,50860
		2015m5,2015,5,50928
		2015m6,2015,6,51132
		2015m7,2015,7,51268
		2015m8,2015,8,51608
		2015m9,2015,9,52220
		2015m10,2015,10,52016
		2015m11,2015,11,51880
		2015m12,2015,12,51132
		2016m1,2016,1,51692
		2016m2,2016,2,51909
		2016m3,2016,3,52672
		2016m4,2016,4,53237
		2016m5,2016,5,54081
		2016m6,2016,6,54324
		2016m7,2016,7,54716
		2016m8,2016,8,55189
		2016m9,2016,9,55562
		2016m10,2016,10,55390
		2016m11,2016,11,55406
		2016m12,2016,12,54836
		2017m1,2017,1,55842
		2017m2,2017,2,55867
		2017m3,2017,3,56253
		2017m4,2017,4,57618
		2017m5,2017,5,57963
		2017m6,2017,6,58114
		2017m7,2017,7,58466
		2017m8,2017,8,58824
		2017m9,2017,9,59196
		2017m10,2017,10,59069
		2017m11,2017,11,59011
		2017m12,2017,12,58631
		2018m1,2018,1,58770
		2018m2,2018,2,58808
		2018m3,2018,3,59729
		2018m4,2018,4,60253
		2018m5,2018,5,60656
		2018m6,2018,6,61023
		2018m7,2018,7,61503
		2018m8,2018,8,61640
		2018m9,2018,9,62196
		2018m10,2018,10,62138
		2018m11,2018,11,62101
		2018m12,2018,12,61517
		2019m1,2019,1,62472
		2019m2,2019,2,62812
		2019m3,2019,3,63673
		2019m4,2019,4,64574
		2019m5,2019,5,64816
		2019m6,2019,6,64876
		2019m7,2019,7,65099
		2019m8,2019,8,65173
		2019m9,2019,9,65860
		2019m10,2019,10,66070
		2019m11,2019,11,65854
		2019m12,2019,12,65250
		2020m1,2020,1,65998
		2020m2,2020,2,65840
		2020m3,2020,3,66135
		2020m4,2020,4,66255
		2020m5,2020,5,66341
		2020m6,2020,6,66691
		2020m7,2020,7,66945
		2020m8,2020,8,67013
		2020m9,2020,9,67877
		2020m10,2020,10,67382
		2020m11,2020,11,67659
		2020m12,2020,12,66982
		2021m1,2021,1,67304
		2021m2,2021,2,67362
		2021m3,2021,3,67700
		2021m4,2021,4,68030
		2021m5,2021,5,68074
		2021m6,2021,6,68058
		2021m7,2021,7,67957
		2021m8,2021,8,68056
		2021m9,2021,9,68576
		2021m10,2021,10,68518
		2021m11,2021,11,68480
		2021m12,2021,12,67826
		2022m1,2022,1,68776
		2022m2,2022,2,68804
		2022m3,2022,3,69116
		2022m4,2022,4,68873
		2022m5,2022,5,68938
		2022m6,2022,6,69111
		2022m7,2022,7,68750
		2022m8,2022,8,68896
		2022m9,2022,9,69843
		2022m10,2022,10,69883
		2022m11,2022,11,69628
		2022m12,2022,12,69202
		2023m1,2023,1,70481
		2023m2,2023,2,70823
		2023m3,2023,3,70882
		2023m4,2023,4,70928
		2023m5,2023,5,71054
		2023m6,2023,6,71022
		2023m7,2023,7,70974
		2023m8,2023,8,70928
		2023m9,2023,9,71598
		2023m10,2023,10,71396
		2023m11,2023,11,70970
		2023m12,2023,12,70300
		2024m1,2024,1,70645
		2024m2,2024,2,70452
		2024m3,2024,3,70552
		2024m4,2024,4,70537
		2024m5,2024,5,70612
		2024m6,2024,6,70725
		2024m7,2024,7,70751
		2024m8,2024,8,70567
		2024m9,2024,9,71080
		2024m10,2024,10,71187
		2024m11,2024,11,70921
		2024m12,2024,12,70745
		2025m1,2025,1,72150
		2025m2,2025,2,72283
		2025m3,2025,3,72295
		2025m4,2025,4,72606
		2025m5,2025,5,72400
		2025m6,2025,6,72625

00_original_index/03_data/processed/affordability_data_levels_q.csv

0 → 100644

+85 −0

Original line number	Diff line number	Diff line
		date,index_house_price_d,index_existing_buildings_d,index_new_buildings_d,annuity_income_ratio_d,houseprice_income_ratio_d,houseprice_rent_ratio_d,actual_rent_d,cost_gas_d,cost_oil_d,electricity_cost_d,maintenance_repair_aprtm_d,construction_price_index_bw,interest_existing_1_d,interest_existing_1_5_d,interest_existing_5_d,interest_new_1_d,interest_new_1_5_d,interest_new_5_10_d,interest_new_10_d,interest_new_avg_d,volume_existing_1_d,volume_existing_1_5_d,volume_existing_5_d,volume_existing_overall_d,volume_new_1_d,volume_new_1_5_d,volume_new_5_10_d,volume_new_10_d,volume_new_overall_d,disp_income_bw
		2004-01-01,83.9,85.5,75.5000766554781,114.4,99.7,100.7,81.828972723089,71.2,75.7723333333333,53.3610305127859,66.6505192959007,61.0676020244897,5.37666666666667,4.8714,5.73346666666667,4.52,4.58,5.06666666666667,5.06666666666667,4.85666666666667,7617,32738.4964972294,885728.155117416,925995.208383674,2443.33333333333,2992.33333333333,5219,2937.33333333333,13592,202440.65314
		2004-04-01,82.8,84.3,74.7090047228467,113.5,100.5,101,81.8712033066344,71.0773333333333,76.9,53.4334431168482,66.6608197903689,61.1819744171865,5.26333333333333,4.84666666666667,5.72666666666667,4.41333333333333,4.33666666666667,4.92666666666667,4.99333333333333,4.71,7512,32598.0572853747,885751.998043729,925974.528348573,2366.33333333333,3114,4965,2921,13366.3333333333,202682.845
		2004-07-01,81.9,83.2,73.9578004168651,113.4,100,101.7,82.0707888140685,71.1,85.4333333333333,54.0224628623976,66.8558611048506,61.5166573409748,5.25,4.74666666666667,5.68,4.35666666666667,4.54333333333333,4.97333333333333,5.02333333333333,4.76666666666667,7550.33333333333,33140.3204063002,890320.630191998,930977.424553633,2454,2647,4648.66666666667,2881.84333333333,12440.3333333333,204107.503
		2004-10-01,80.6,81.5,74.7390199957468,110.9,100.2,101.4,82.2684126826614,72.9666666666667,93.7666666666667,54.3121747076376,66.9494753165943,61.793056575515,5.17,4.65,5.64666666666667,4.37333333333333,4.39,4.76666666666667,4.77,4.61,7618.13333333333,33238.1780190121,893925.79021724,934782.918965773,2423.33333333333,2385.33333333333,4418.33333333333,3164,12391,205532.161
		2005-01-01,84.2,85.7,76.104077268722,111,103.1,105.3,82.4563541643467,76.2666666666667,90.7666666666667,55.1224985574207,67.267900111565,61.6093628300098,5.16,4.58,5.6,4.35333333333333,4.17666666666667,4.51333333333333,4.54,4.42666666666667,7153.33333333333,33248.7535844252,897384.798844246,937865.554441505,2071,2164.33333333333,4405.92333333333,3326,12308.6633333333,206956.819
		2005-04-01,82.7,84.2,73.8064798335775,107.4,101.6,105.3,82.671247638621,76.8666666666667,101.5,55.622522723125,67.493247609929,61.4813968042201,5.01666666666667,4.55666666666667,5.54,4.28666666666667,4.07333333333333,4.37,4.41333333333333,4.31,7071.33333333333,31159.7699058677,900716.936178376,938961.368298479,2352.33333333333,2343,4987.33333333333,3690,13372.6666666667,208552.4045
		2005-07-01,84.4,86.1,74.6536399369162,104.9,102,103.5,82.8371827006798,78.7333333333333,117.933333333333,56.2315598567708,67.688644626336,61.716386747926,4.94333333333333,4.45,5.47,4.22,3.92333333333333,4.12666666666667,4.19333333333333,4.12333333333333,6917.66666666667,30826.1163344459,903381.225866822,941089.67067351,2486,2489.66666666667,5830.66666666667,4410.33333333333,15216.6666666667,210147.99
		2005-10-01,82,83.4,73.9418037824588,103.5,100.4,104.7,83.035095620952,84.0666666666667,119,56.5331186547901,68.0497405981916,61.793056575515,4.92333333333333,4.35,5.39333333333333,4.34,4.08,4.14666666666667,4.25,4.19333333333333,6732.66666666667,30576.7627911439,908116.365081304,945417.151301953,2395.66666666667,2717.66666666667,6952.33333333333,4682.33333333333,16748,211743.5755
		2006-01-01,83.2,84.7,74.7954092733603,106.1,100.8,103.4,83.3566055037876,90.8333333333333,115.9,57.3366516769334,68.469708748794,62.1094388270066,5.11,4.30666666666667,5.32333333333333,4.61333333333333,4.32,4.32,4.35,4.37333333333333,6280,30209.9882118021,922892.023415566,959413.205132976,2484,2573.33333333333,7065.33333333333,5367.33333333333,17490,213339.161
		2006-04-01,83.5,85.4,72.9039549443081,109.9,101.5,103.2,83.571297512106,92,123.333333333333,57.7452665837571,68.9583205723547,62.4794714276652,5.22333333333333,4.31333333333333,5.27,4.82333333333333,4.53666666666667,4.56333333333333,4.58333333333333,4.60666666666667,6083,29899.5115831074,924943.035652104,960939.555259558,2494.66666666667,2398,6231,4747.66666666667,15871.3333333333,214463.58525
		2006-07-01,82.3,83.8,73.3613665425354,112.2,102,104.4,83.7035410072839,92.5,124.2,58.4406568511439,69.7206364187605,63.4140867070113,5.34,4.32333333333333,5.23333333333333,5.04666666666667,4.75333333333333,4.69666666666667,4.75,4.77666666666667,6156.66666666667,29560.7386875674,925852.521185611,961533.53121246,2304,2259,5579.33333333333,4350.66666666667,14493,215588.0095
		2006-10-01,83,84.5,74.3404118891029,108.4,99.3,102.4,83.9684487632188,96.3666666666667,112.566666666667,58.8213639336744,70.5836848830827,64.5015184708704,5.53666666666667,4.35666666666667,5.2,5.2,4.83333333333333,4.63333333333333,4.60666666666667,4.74666666666667,5961.33333333333,29229.8068161128,927832.752921428,963013.482620725,2402.33333333333,2347.66666666667,5569,4545,14864,216712.43375
		2007-01-01,80.498,81.483,72.8147817632412,109.8,99.5,101.1,84.223514201027,98.8333333333333,105.333333333333,60.8396401943715,71.7746825011736,67.1101987969749,5.60666666666667,4.39333333333333,5.16666666666667,5.45,4.94666666666667,4.73333333333333,4.73666666666667,4.87666666666667,5907.66666666667,29085.5378340763,929951.647279559,964977.304597731,2316.33333333333,2439.33333333333,5850.66666666667,4853.66666666667,15460,217836.858
		2007-04-01,81.7,82.6,76.5140545013853,111.1,98.8,101.3,84.471347385591,95.1666666666667,112.033333333333,61.3273968485738,73.1537567829373,67.3700370825464,5.67333333333333,4.44,5.13333333333333,5.58,5.09,4.89333333333333,4.89666666666667,5.01333333333333,6059.33333333333,28191.8381308914,928974.537662254,963242.426588551,2223.33333333333,2203.33333333333,6316.66666666667,5277.66666666667,16021,218907.3415
		2007-07-01,81.6,82.4,76.3435359141832,114.8,99.1,101.5,84.7698281538734,94.2333333333333,119.233333333333,62.6245526738203,73.8512426853282,67.6084042529868,5.89333333333333,4.50333333333333,5.12,5.82666666666667,5.35666666666667,5.14666666666667,5.13333333333333,5.28333333333333,5692.33333333333,27591.4864085135,926163.781016774,959410.418902481,2401.66666666667,2219.33333333333,5716.66666666667,4784.66666666667,15122.3333333333,219977.825
		2007-10-01,81.6,82.5,76.2338003956617,112.7,98.698,102.1,85.0018040278714,94.2666666666667,132.533333333333,63.6670598183707,74.5179667990977,68.2131144015425,5.99666666666667,4.58666666666667,5.10666666666667,5.91666666666667,5.31,5.06333333333333,5.03666666666667,5.22666666666667,5634.66666666667,26944.7566871271,924926.109492751,957491.325160404,2172.66666666667,2240.66666666667,5200.66666666667,4374,13988,221048.3085
		2008-01-01,82.8,83.8,77.2114117263356,113.8,100.3,101.9,85.323821393677,97.4666666666667,142.733333333333,65.2679464333969,75.1464234000659,68.7104419873648,6.17666666666667,4.64333333333333,5.08666666666667,5.84,5.09666666666667,4.95666666666667,4.94333333333333,5.11333333333333,5571,26321.9050348057,925750.53986234,957678.745170164,2110.66666666667,2347.33333333333,5028,4154,13640,222118.792
		2008-04-01,83.1,84,77.8177015636632,114.3,100.6,101.2,85.6047435225721,99.4666666666667,171.033333333333,65.8050596795945,75.4179604521407,69.3661863294366,6.17333333333333,4.69,5.07,5.97,5.09666666666667,4.97333333333333,5.01,5.14333333333333,5504.66666666667,25725.8679820809,925265.462259081,956514.914786763,2169,2703.33333333333,6095,4562.33333333333,15529.6666666667,220919.63775
		2008-07-01,81.6,82.2,77.5364036628424,116.4,99.8,99.013,85.7694723538012,104.433333333333,172.566666666667,66.9088619962409,75.6167437508773,70.2048865433527,6.25283333333333,4.78666666666667,5.06,6.01476666666667,5.38103333333333,5.15856666666667,5.15543333333333,5.30826666666667,5510,25102.3116105135,923252.919023537,953826.680130514,2276,2246.66666666667,5759,4581.33333333333,14863,219720.4835
		2008-10-01,81.8,82.6,77.1306686356107,117.3,102.9,99.2,86.0684933333191,115,131,67.5705370588205,76.6184732457837,70.0187556651127,6.25,4.85666666666667,5.06333333333333,5.93,5.15666666666667,5.00333333333333,4.95333333333333,5.16,5462,24323.1333639865,920067.967068739,949834.013238834,2319.66666666667,2570.66666666667,5655.33333333333,4220.33333333333,14766,218521.32925
		2009-01-01,81.8,82.1,80.6340818680506,111.1,102.6,100.4,86.3241006597224,115.866666666667,103.366666666667,69.0022643812318,78.4847807257019,70.2106699783553,5.56333333333333,4.71666666666667,5.02,4.51333333333333,4.34333333333333,4.57,4.62,4.53333333333333,5477,24308.1287931975,918807.474269165,948630.027798225,2802.66666666667,3145,6121.33333333333,3991.33333333333,16060.3333333333,217322.175
		2009-04-01,83.1,83.6,80.1241540584625,106.3,100.4,101.4,86.5381285765565,103.033333333333,103.366666666667,70.3158903834378,79.2138313093345,69.7654161788146,4.96333333333333,4.53333333333333,4.96666666666667,3.79666666666667,3.94,4.37,4.51333333333333,4.23,5591.33333333333,25287.4881618961,918250.929422922,949149.201557468,2806.66666666667,3174.86333333333,7164.33333333333,4177.66666666667,17469.3333333333,218706.01675
		2009-07-01,82.9,83,82.4072803032004,107.3,100.7,101.2,86.6691521337362,97.8,107.933333333333,71.1262289854987,79.1144345411161,70.0051571364015,4.57,4.41,4.92,3.47,3.85666666666667,4.42666666666667,4.5,4.18,5636,25415.3295825726,918003.779967114,949016.88869638,2853.66666666667,3048.66666666667,6831.33333333333,4083.66666666667,16817.3333333333,220089.8585
		2009-10-01,84.2,84.2,83.3090942885924,106,100.6,102.3,86.868510312405,93.4666666666667,113.233333333333,71.5749662968681,79.4524898802012,70.1190690686444,4.40333333333333,4.32,4.87666666666667,3.29333333333333,3.79,4.32666666666667,4.37,4.06333333333333,5560.66666666667,25603.769497805,920200.570627857,951348.394387458,2566.66666666667,2636.66666666667,5807.33333333333,3709.66666666667,14720.3333333333,221473.70025
		2010-01-01,83,83.1,83.1507510898999,103.8,100.2,100.3,87.1910093569618,93.1666666666667,120.866666666667,71.4477469311413,79.7533565094436,70.0106395795566,4.35666666666667,4.24333333333333,4.84,3.13333333333333,3.64666666666667,4.19333333333333,4.37666666666667,3.94666666666667,5335,25746.9704127621,921754.828824928,952872.156815684,2565,2359.33333333333,5190.33333333333,3550.33333333333,13665,222857.542
		2010-04-01,84.3,84.6,82.8317287262704,101.2,100,99.4,87.5381839915399,93.3666666666667,134.633333333333,72.3391306256027,79.9463677905474,70.4640684152262,4.12,4.16666666666667,4.77666666666667,3.10666666666667,3.45,3.99333333333333,4.11333333333333,3.78666666666667,5260.66666666667,25892.1846008839,922727.480386953,953898.288933986,2446,2325.66666666667,5292,4357,14420.6666666667,225088.199
		2010-07-01,84.3,84.3,84.2959875719107,98.4,100.1,99.4,87.7021178069948,93.5,131.4,73.4022683130347,80.2470201303363,70.8040747642063,3.98333333333333,4.06333333333333,4.69333333333333,3.05666666666667,3.3,3.76,3.73,3.56666666666667,5348.33333333333,26034.0473594375,922649.041661261,953993.78617937,2521,2407,5996.66666666667,5199,16123.6666666667,227318.856
		2010-10-01,83.8,83.6,84.1063105018804,96.6,99.7,101,87.968533658648,94.9,137.533333333333,73.9978142392162,81.0195343721734,71.2225165074929,3.94333333333333,3.96666666666667,4.64,3.14,3.29333333333333,3.64333333333333,3.68666666666667,3.53,5405.66666666667,26360.1472868366,924548.239200228,956299.294179471,2560.33333333333,2383.66666666667,6237.33333333333,5417,16598.3333333333,229549.513
		2011-01-01,86.1,86.2,85.9694206183711,101.1,99.7,101.9,88.3246591918134,96.5,157.333333333333,76.7022297072983,81.6228366117997,71.9109283681445,3.80333333333333,3.87333333333333,4.59333333333333,3.31,3.54666666666667,4.01333333333333,4.15333333333333,3.85333333333333,5177,26621.5800908563,928374.93783392,960207.790199706,2857.63333333333,2566,5998.66666666667,4488,15929.6666666667,231780.17
		2011-04-01,87.1,87,88.3471586051382,103,99,102.5,88.604909767522,96.7666666666667,162.866666666667,77.8118296412948,82.1772743469683,72.560025124461,3.96,3.83666666666667,4.56,3.60333333333333,3.80666666666667,4.22666666666667,4.39666666666667,4.10666666666667,5217.66666666667,27143.7422554573,930478.4155462,962856.164363316,2647,2246.33333333333,5805,4503,15201.3333333333,233248.45425
		2011-07-01,86.7,86.3,88.9680529208255,100.7,99.5,102.3,88.8017264269154,98.1333333333333,162.8,78.6237702997349,82.9452387399492,73.0010982406697,4.09666666666667,3.83666666666667,4.54,3.66333333333333,3.67,3.99666666666667,4.04,3.9,5297,27510.3212807958,930938.873014829,963709.238653357,2612.33333333333,2178,5673.33333333333,4722.33333333333,15186,234716.7385
		2011-10-01,87.3,87.2,87.9927395416593,95,99,102,89.1018910456864,101.433333333333,170.566666666667,79.0790647849741,83.4534545405555,73.5297247887215,4.07666666666667,3.79333333333333,4.50333333333333,3.58666666666667,3.29666666666667,3.56333333333333,3.55666666666667,3.52666666666667,5235,27883.5140394937,934037.203661194,967144.21724381,2419.33333333333,2275.33333333333,6141.33333333333,5231.33333333333,16067.3333333333,236185.02275
		2012-01-01,88,87.8,89.694091066708,92.9,99.3,102,89.3916237422618,103.1,179.933333333333,78.78419458087,84.1933717525394,74.1112627549306,3.94,3.71,4.45,3.44333333333333,3.04666666666667,3.36666666666667,3.5,3.37333333333333,5097,28343.3738280759,938817.757352291,972290.560008037,2356,2211,5785.33333333333,4590,14942.3333333333,237653.307
		2012-04-01,89.1,89,89.9516472971725,91.7,100.7,103.4,89.6049651825053,103.2,172.466666666667,79.768734137815,84.8410433695605,74.3565594466623,3.71,3.59666666666667,4.38,3.15666666666667,2.87666666666667,3.14666666666667,3.34666666666667,3.17,5154,28582.0296349643,940839.502678205,974590.048933862,2333.33333333333,2091.33333333333,6057.66666666667,4960.33333333333,15442.6666666667,238543.81325
		2012-07-01,90.4,90.4,90.0615150237631,88.5,100.6,103.8,89.868013573505,103.533333333333,178.866666666667,80.9667519604336,85.3769666226866,74.5989334962794,3.50666666666667,3.5,4.31666666666667,3.00333333333333,2.66666666666667,2.88666666666667,3.02,2.92333333333333,5310.33333333333,28783.3497388936,944389.958296019,978446.860368588,2417.66666666667,2105.66666666667,6666.33333333333,5728.66666666667,16918.3333333333,239434.3195
		2012-10-01,91.6,91.6,91.4805604747941,88.5,101.8,103.8,90.1019122695436,104.266666666667,180.2,81.6028647249201,85.7873505924288,75.1347392452285,3.34333333333333,3.37333333333333,4.24,2.8,2.51,2.79333333333333,2.94666666666667,2.80666666666667,5365.33333333333,28990.0605901286,952175.974721542,986520.785519611,2362.33333333333,2043.33333333333,6197.33333333333,5191,15794,240324.82575
		2013-01-01,91.3,91.4,91.5060929064395,88.7,102.7,103.5,90.5252735771134,104.566666666667,172.6,88.4669835960524,86.4300711607155,75.4114603471223,3.21,3.28666666666667,4.17,2.7,2.48,2.74333333333333,2.95333333333333,2.76666666666667,5393,29100.2540198645,959830.975929009,994357.580089488,2594.33333333333,1964.66666666667,6307.66666666667,4708.33333333333,15575,241215.332
		2013-04-01,93.1,93.2,92.2580997919718,87.5,102.7,104.9,90.7383613194865,104.566666666667,163.366666666667,89.553256620416,86.2728192192038,75.5542489947965,3.18666666666667,3.20333333333333,4.10666666666667,2.76333333333333,2.38333333333333,2.63666666666667,2.85,2.69333333333333,5475.33333333333,29044.8382542892,964973.718921966,999509.642788313,2592,2060.33333333333,6695.33333333333,5292,16639.6666666667,243345.39575
		2013-07-01,92.9,93.1,90.9561658352574,88.9,103.1,103.4,91.0675866134183,104.866666666667,168.433333333333,90.4725632695543,86.7760429387821,75.997039344938,3.12666666666667,3.11666666666667,4.02666666666667,2.72,2.42333333333333,2.74,2.93,2.75333333333333,5592.33333333333,28939.027115008,969811.730495647,1004304.69058605,2733.66666666667,2183,7305.33333333333,5299,17521,245475.4595
		2013-10-01,93,93.3,90.8826483148282,90.6,103.1,104.1,91.3686058197629,105.133333333333,164.133333333333,90.8904485039213,87.0209813627047,76.539126894672,3.12,3.04333333333333,3.96,2.65333333333333,2.49,2.87666666666667,3.05666666666667,2.83666666666667,5704.33333333333,28804.6966339389,975176.211603373,1009671.84163523,2648.33333333333,2047,6115.66666666667,4467.33333333333,15278.3333333333,247605.52325
		2014-01-01,93.8,94,92.9154276706751,89.6,103.1,103.2,91.8256366229724,104.966666666667,159.2,90.416760223683,87.2980440653809,76.9116883381129,3.14666666666667,2.98666666666667,3.89666666666667,2.73333333333333,2.42333333333333,2.78666666666667,2.97666666666667,2.78666666666667,5671,28484.8498869034,980816.140366047,1015008.10783466,2847.33333333333,2173.33333333333,6048,4664.33333333333,15733,249735.587
		2014-04-01,95.7,95.9,94.5645522867711,88.3,104,102.1,92.205109261462,104.766666666667,158.6,91.1453145158901,87.704595068847,77.0513609299641,3.14333333333333,2.92,3.83,2.54666666666667,2.31,2.61,2.82333333333333,2.63,5756.66666666667,28279.5140949284,986837.918204267,1020892.73197851,2582,2189,6494,5041,16306,251624.17125
		2014-07-01,96.2,96.3,95.5288255384506,86.1,104.7,101.4,92.4337670199862,104.666666666667,157.8,92.0457080988807,87.9752512097211,77.3951451935965,3.05666666666667,2.84333333333333,3.76666666666667,2.45,2.11666666666667,2.36666666666667,2.5,2.39,5703,28162.6360982324,992576.97493841,1026402.30182365,2556.66666666667,2113.33333333333,6846.33333333333,5596,17112.3333333333,253512.7555
		2014-10-01,96.2,96.1,96.1642057278609,83.5,104.9,102.1,92.7686355331631,104.333333333333,140.4,92.5729817972187,88.5880258546767,78.0438279476472,2.91333333333333,2.74333333333333,3.69666666666667,2.29,1.94,2.13,2.27333333333333,2.18333333333333,5493.33333333333,28147.7986067266,1003355.29876523,1036980.55027455,2565.33333333333,2023.66666666667,6951.33333333333,5979,17519.3333333333,255401.33975
		2015-01-01,97.8,97.8,98.1500996521215,82.8,107.7,101.9,93.159342311033,103.533333333333,120.9,90.3837131621978,88.9672227281989,78.6119467279021,2.81,2.65,3.61666666666667,2.23333333333333,1.9,1.88333333333333,1.9,1.93333333333333,5088,28072.7966848337,1016609.88282037,1049808.52896026,2521.66666666667,1959,7037.33333333333,7799,19317,257289.924
		2015-04-01,99.9,100.1,99.378018362874,80.596,106.4,101.8,93.4385109399415,103.333333333333,122.2,90.349285568153,89.26955936962,78.8478952521654,2.69666666666667,2.55666666666667,3.53,2.14,1.82666666666667,1.67666666666667,1.88333333333333,1.83,5039.33333333333,27936.8416247992,1025165.58757178,1058161.0222499,2584.33333333333,1962,7916.66666666667,8887,21350,259264.11725
		2015-07-01,100.4,100.4,100.101485241644,82.9,107.6,102.1,93.6333400598996,102.933333333333,111.9,91.0750442680198,89.640818252692,79.1927098561575,2.63666666666667,2.46333333333333,3.43666666666667,2.20333333333333,1.94666666666667,1.9,2.12333333333333,2.02666666666667,5123,27814.3578657713,1034328.4032856,1067223.77966704,2516.33333333333,2097.33333333333,8312.33333333333,8479.33333333333,21405.3333333333,261238.3105
		2015-10-01,101.8,101.7,102.342631380843,83.1,107.9,103.3,93.8353248386109,102.766666666667,102.633333333333,91.3952084919105,90.05504623014,79.5485290006224,2.61666666666667,2.38333333333333,3.35666666666667,2.18,1.93666666666667,1.88666666666667,2.08,2.00666666666667,5011.33333333333,27663.9953650794,1044750.54065247,1077407.91377958,2493.33333333333,2014.66666666667,7311.33333333333,7454.33333333333,19273.6666666667,263212.50375
		2016-01-01,103.9,103.8,104.894773166678,82.5,109,103.6,94.2263068614815,101.733333333333,87.3333333333333,90.1523837318009,90.3359492317097,80.1121747188926,2.61333333333333,2.34666666666667,3.27,2.25666666666667,1.85,1.77666666666667,1.96,1.91666666666667,4925.33333333333,27484.8181708415,1054990.28374885,1087441.26675918,2538.33333333333,2101.33333333333,7294.33333333333,7959.66666666667,19893.6666666667,265186.697
		2016-04-01,106.9,107,106.497936933776,82.2,110.8,104.6,94.3718959939259,101.3,91.8,90.9463072789558,90.7346323320457,80.6444295743666,2.56666666666667,2.29333333333333,3.18666666666667,2.13,1.83333333333333,1.63,1.86333333333333,1.81,4838,27333.1491090638,1065767.61747162,1097960.39933457,2302,1816.33333333333,6704.33333333333,8256,19078.6666666667,267750.20775
		2016-07-01,108.8,109,106.861069150712,81.5,111.5,104.2,94.5996627864963,100.6,91,91.577111766741,91.1731399322252,81.090139222194,2.49666666666667,2.23333333333333,3.1,2.06666666666667,1.76666666666667,1.52,1.7,1.68333333333333,4682.33333333333,27154.0595931493,1075710.31461397,1107502.66217252,2237,1756.33333333333,6994,8621.33333333333,19608.6666666667,270313.7185
		2016-10-01,110.4,110.5,109.11896919379,80.8,111.5,106.9,95.0020162664445,99.9666666666667,97.5,92.0682218092295,91.5887493499424,81.6551104747877,2.44333333333333,2.14333333333333,3.01666666666667,1.95,1.65,1.45666666666667,1.69,1.63333333333333,4476.66666666667,26811.4538062894,1086272.07164363,1117539.51269775,2350.33333333333,1666,7126.33333333333,8702.66666666667,19845.3333333333,272877.22925
		2017-01-01,110.9,111.2,110.02877837925,83.3,112.2,106.2,95.3266140541315,98.7,102.4,91.3751250067556,92.0385114677841,82.5125395044773,2.43666666666667,2.08666666666667,2.93666666666667,2.11,1.66666666666667,1.63333333333333,1.88333333333333,1.8,4316.33333333333,26383.1109893339,1098214.36548438,1128957.75199651,2165,1759.66666666667,7206.33333333333,8815,19946,275440.74
		2017-04-01,113.1,113.5,110.810000293618,84.4,112.9,108.2,95.7053032139036,98,100.1,92.0076792092718,92.4993793095129,83.0398086706349,2.44333333333333,2.04,2.85333333333333,2.09666666666667,1.73333333333333,1.68333333333333,1.89666666666667,1.83333333333333,4248.33333333333,26292.41533748,1112185.35464717,1142750.11061809,2184.66666666667,1648,6779,8676.66666666667,19288.3333333333,277854.436
		2017-07-01,115,115.3,112.228974019678,86,115.1,108.6,95.8992002464025,97.4,99.1666666666667,93.2171989292301,93.071886361212,83.4868921056086,2.44333333333333,2.00333333333333,2.77333333333333,2.04333333333333,1.76,1.68,1.95333333333333,1.85,4015,25929.5971540958,1124537.49452409,1154435.49449991,2251.33333333333,1728.33333333333,6856.33333333333,8496,19332,280268.132
		2017-10-01,117.3,117.8,114.001918500179,86,115.2,110.7,96.302043857459,97.5,106.3,93.7844057683928,93.7559385409676,84.5641991772064,2.42,1.98,2.70666666666667,2.05333333333333,1.70333333333333,1.67,1.92,1.82666666666667,3985.66666666667,25764.926711952,1136047.26025555,1165773.39969682,2151.33333333333,1609,6415,7956,18131.3333333333,282681.828
		2018-01-01,118.3,118.6,117.276785738176,87.1,116.4,109.1,96.7936903109981,96.9333333333333,108.2,92.7631015891367,94.2752108759601,85.8130410846564,2.31666666666667,1.95,2.64333333333333,2.05,1.71666666666667,1.69,1.94,1.85,3919.33333333333,25598.4707198084,1150665.25337426,1180230.69977449,2233.33333333333,1731.66666666667,6770.33333333333,8956,19691.3333333333,285095.524
		2018-04-01,120.6,121.1,118.431321580781,88.8,117.3,108.9,97.0720456143808,96.6,115.6,93.4007298678116,95.0299598809755,86.7326847773819,2.3,1.92666666666667,2.58,2.08333333333333,1.74,1.76333333333333,1.97666666666667,1.9,4032,25703.7816705297,1165959.7643952,1195722.49978549,2596,1837.33333333333,7012,9331,20776.3333333333,286328.8025
		2018-07-01,123.1,123.5,120.280831323127,90.4,120.4,110.4,97.3653450729631,96.3666666666667,122.633333333333,94.1543915935096,95.7034822891059,87.8809390585354,2.27333333333333,1.89333333333333,2.52,2.13333333333333,1.71666666666667,1.71,1.95333333333333,1.87,4246,25754.9590719162,1178938.72214861,1208889.76342874,2328.33333333333,1763.66666666667,6854.33333333333,9231.66666666667,20178,287562.081
		2018-10-01,124.6,125.4,119.582431993195,90.5,120.5,110.2,97.7020735708592,96.4666666666667,134.166666666667,94.7602750785052,96.4899310588763,89.078302336132,2.25666666666667,1.86666666666667,2.46,2.04,1.71,1.71,1.96333333333333,1.86333333333333,4284,26076.629965652,1192153.18871117,1222485.76074567,2289.66666666667,1727.33333333333,6831.66666666667,8905.33333333333,19754,288795.3595
		2019-01-01,124.6,125.5,120.296788804395,90.7,122,110,98.1273959990588,97.8333333333333,123,95.3077253235021,97.5468010550833,89.9136642600305,2.27333333333333,1.85,2.40666666666667,2.05666666666667,1.66,1.64,1.86333333333333,1.79333333333333,4367.66666666667,25965.0375294418,1207693.30774422,1238077.76183094,2350.33333333333,1822,6769.33333333333,9589.33333333333,20531.3333333333,290028.638
		2019-04-01,127.8,129,121.740579508102,89.5,123.3,110.8,98.438788014858,98.6,124.833333333333,96.3858384218255,98.7259393998221,90.2259459594399,2.25,1.78666666666667,2.35,2.00666666666667,1.47333333333333,1.46666666666667,1.66666666666667,1.62333333333333,4509,26280.033617368,1227486.77990666,1258306.00196901,2470,1933,7171,10392,21966,289243.50725
		2019-07-01,129.6,130.8,122.567161174724,87.5,124.4,112.3,98.764846952862,98.9333333333333,123,97.7023352511392,99.4010411245013,90.8768801628036,2.18,1.76,2.29,1.90666666666667,1.39666666666667,1.23666666666667,1.36333333333333,1.38333333333333,4645.66666666667,26560.6227577047,1242018.60624199,1273171.66558547,2484.66666666667,1801.33333333333,7347.66666666667,11697.3333333333,23331.6666666667,288458.3765
		2019-10-01,132.7,133.7,126.757377912787,86.6,125.6,111.6,99.1354373250546,99.9666666666667,121.766666666667,98.4618483237593,99.9240923923471,91.6864508279557,2.08333333333333,1.71666666666667,2.22,1.85333333333333,1.32666666666667,1.11666666666667,1.24333333333333,1.27333333333333,4715.33333333333,26510.3617271835,1260069.14242192,1291262.32606015,2351.33333333333,1651.33333333333,6926.33333333333,10887.6666666667,21817,287673.24575
		2020-01-01,133.8,135.3,126.840128781203,88.2,127.8,112.1,99.5611296137239,100.7,115,99.537749193616,100.551322648156,92.5140594444141,2.03333333333333,1.68666666666667,2.16,1.82666666666667,1.32333333333333,1.12,1.26333333333333,1.28,4774.33333333333,26507.8641097657,1280440.69773753,1311779.45126552,2355.66666666667,1722.66666666667,7235.33333333333,11282.3333333333,22595.6666666667,286888.115
		2020-04-01,136.2,137.5,129.462181338517,91.8,132.7,113.5,99.9055359568336,100.533333333333,102.666666666667,100.598158270267,101.090034407373,92.5215175933636,1.98,1.65666666666667,2.10333333333333,1.88333333333333,1.46,1.13333333333333,1.25666666666667,1.30666666666667,4684.33333333333,26700.3428190108,1300965.96597232,1332384.14672198,2586.66666666667,1804,7541.33333333333,11299.3333333333,23231.6666666667,289144.05175
		2020-07-01,140.3,142,130.42020718673,90.9,132.3,115.8,100.097705886099,99.4,92.9333333333333,99.7440764126053,99.0346163750477,90.3775566454256,1.97333333333333,1.63666666666667,2.04666666666667,1.79333333333333,1.39333333333333,1.08666666666667,1.20333333333333,1.23666666666667,4717.33333333333,26723.6183010724,1317259.92793108,1348643.68116527,2313.33333333333,1629.66666666667,7341.66666666667,11186,22470.3333333333,291399.9885
		2020-10-01,144.3,145.9,134.928844098988,91.3,134,117.6,100.435464916069,99.3666666666667,89.3666666666667,100.144381617057,99.323947693294,91.2851972138289,1.92,1.60666666666667,1.98666666666667,1.75383333333333,1.30333333333333,1.02943333333333,1.15106666666667,1.17886666666667,4655,26878.7684451204,1341496.0362138,1372993.38027866,2309.66666666667,1653.33333333333,7575,11312,22850,293655.92525
		2021-01-01,146.3,148.7,134.188802909003,94.8,139.2,120.4,100.828150017381,102.3,100.033333333333,100.00040805441,101.88666557841,94.6143786318007,1.90163333333333,1.57333333333333,1.93,1.75666666666667,1.30106666666667,1.03,1.15333333333333,1.18,4616.66666666667,26917.5761004599,1367512.39786079,1399107.99069485,2302,1712,8289.66666666667,11848.3333333333,24151.6666666667,295911.862
		2021-04-01,151.8,154.4,138.48743023121,97.4,141.7,123.6,101.205607996312,102.4,102.766666666667,100.399151033333,103.187752512664,98.9091951834125,1.90333333333333,1.55,1.86666666666667,1.78666666666667,1.30333333333333,1.09,1.28333333333333,1.26333333333333,4518.66666666667,26964.7092754581,1393677.48149318,1425198.01422005,2260.33333333333,1689.33333333333,8784.33333333333,11428.3333333333,24162.6666666667,301808.57475
		2021-07-01,158.2,161.2,141.156016924662,102.2,148.2,125.1,101.530529239329,103.3,107.8,101.551519408001,105.363771138337,102.061726952072,1.93333333333333,1.52333333333333,1.81666666666667,1.78,1.34,1.11,1.29666666666667,1.28,4581.33333333333,26995.3884213405,1416867.7344778,1448382.35781205,2404.66666666667,1538,8274,11146,23362.6666666667,307705.2875
		2021-10-01,162.5,165.5,146.189523111681,102.2,147.7,127.7,101.90216271106,107.033333333333,123.533333333333,103.374845540187,107.725973480038,104.426253076479,2.02333333333333,1.52276666666667,1.77,1.80666666666667,1.38333333333333,1.13666666666667,1.32,1.30666666666667,3950,26862.1884848172,1441678.8559765,1472450.7028423,2252.66666666667,1612.66666666667,8266,10867.6666666667,22999,313602.00025
		2022-01-01,164.1,167.6,145.966814867258,104.9,147.1,130.002,102.395254200853,126.066666666667,154.2,113.12009146406,110.666545344833,107.916400151916,2.04666666666667,1.52333333333333,1.72666666666667,1.87333333333333,1.48333333333333,1.32666666666667,1.52,1.48333333333333,3623,26714.2251695684,1467837.34113831,1498240.74425969,2500.33333333333,1766.33333333333,9874.78,12160.9066666667,25787.81,319498.713
		2022-04-01,166.487,169.472,149.518289988946,118.2,148.319,129.9,102.872367021284,143.166666666667,182.233333333333,121.29491091143,114.408879520334,113.880314535089,2.14,1.55666666666667,1.70333333333333,2.1,2.14333333333333,2.13,2.41,2.25333333333333,3597.66666666667,26951.6582731778,1495273.9382915,1525863.09582395,2425,1733.33333333333,9863.33333333333,11337.3333333333,25358.3333333333,325131.08325
		2022-07-01,166.3,169.2,149.583812028012,126.8,145.7,128.7,103.296567325868,167.366666666667,206.2,118.454458531614,118.488439436947,116.242514845608,2.44,1.77333333333333,1.70276666666667,2.53666666666667,2.78333333333333,2.81,3.08666666666667,2.88333333333333,3675.66666666667,27213.2702191074,1513647.23778862,1544470.33318829,2496,1490,6957.33333333333,7609.66666666667,18552.6666666667,330763.4535
		2022-10-01,158.5,160.2,149.179083911511,131.704,141.9,124,103.802203036389,178.6,206.557,130.564583559872,121.629325674769,119.372950202699,3.35666666666667,2.21333333333333,1.73,3.29,3.57333333333333,3.37,3.59333333333333,3.45666666666667,3596.66666666667,27068.1115917828,1527809.6865497,1558430.46519888,2490.66666666667,1304.01333333333,5038.66666666667,5189.66666666667,13999,336395.82375
		2023-01-01,153.7,155.1,147.376149631493,131.5,137,118.4,104.429155375145,190.3,188,137.024331797862,124.487344672966,121.51846727023,4.29,2.64333333333333,1.77,4.18333333333333,3.96333333333333,3.56333333333333,3.74666666666667,3.77666666666667,3490.66666666667,26459.0331296503,1540152.56378939,1570173.23777226,2266.66666666667,1309,4716,5058.33333333333,13350,342028.194
		2023-04-01,151.6,153,144.704823912843,129,132.3,117.3,104.972483392749,196.033333333333,171.633333333333,136.850643265125,126.762108362605,122.06452644734,4.91666666666667,3.03333333333333,1.80666666666667,4.83333333333333,4.29333333333333,3.69666666666667,3.79,3.97666666666667,3403.66666666667,26077.5757614811,1548006.89339295,1577531.34877587,2186,1361.66666666667,4831.66666666667,5167.33333333333,13546.3333333333,347660.56425
		2023-07-01,149.3,150,144.535808879196,128.2,129.7,113.6,105.429141619047,196.118333333333,173.633333333333,136.261119152925,128.348596331335,123.133179385425,5.41333333333333,3.32333333333333,1.84666666666667,5.29666666666667,4.46,3.80333333333333,3.85333333333333,4.09333333333333,3345.66666666667,25480.5277999196,1548734.3767668,1577492.08626919,1890,1342.66666666667,5053.66666666667,5382.33333333333,13669,353292.9345
		2023-10-01,146.4,146.9,143.199962311851,126.5,127.1,109.7,105.935581647284,191.1,172.366666666667,133.290287495014,129.697937739817,124.288306975752,5.63,3.57333333333333,1.88666666666667,5.57,4.52666666666667,3.85666666666667,3.82333333333333,4.15,3268,24705.1356493721,1551121.65811437,1579045.25690233,1789.22666666667,1514.66666666667,4863,5011,13151.6666666667,358925.30475
		2024-01-01,145.8,146.2,144.054146258652,120.3,125.4,106.9,106.663112402647,190.8,166.333333333333,127.396422025694,130.830223591674,125.219029648007,5.68,3.72,1.92,5.37666666666667,4.07,3.56666666666667,3.59,3.85333333333333,3262.66666666667,23886.7107456263,1559227.3749053,1586452.04465219,1794.66666666667,1650.33333333333,5321.33333333333,6017.33333333333,14783.6666666667,364557.675
		2024-04-01,147.8,148.2,145.707629345364,120,124.4,106.2,107.272610847211,190.966666666667,163.266666666667,127.032952909701,131.956457956659,126.356247328154,5.59333333333333,3.81,1.95333333333333,5.46666666666667,4.13,3.61,3.67,3.90666666666667,3320.33333333333,23166.1983297195,1565161.99360919,1591696.74737153,1912,1608,6149.33333333333,6494.66666666667,16164,370190.04525
		2024-07-01,149,149,146.623327439349,119.5,124.4,106.5,107.69500180555,187.866666666667,158.766666666667,127.458202342014,132.812316006497,127.427361634876,5.42,3.89333333333333,1.99666666666667,5.34666666666667,4.01333333333333,3.57,3.60333333333333,3.82666666666667,3378.33333333333,22419.2053803027,1567981.88577012,1593707.69773926,2018,1692.66666666667,6552,7382.66666666667,17644.3333333333,375822.4155
		2024-10-01,149.2,149.5,146.488479191664,116.5,124.4,106.1,107.786908677173,186.5,155.833333333333,127.704276961267,133.014047992841,127.609960044041,5.14666666666667,3.97333333333333,2.03666666666667,4.93,3.72666666666667,3.36666666666667,3.39333333333333,3.6,3256.32,22334.0080004602,1568728.05715459,1594345.20926758,2021,1799.33333333333,5418.33333333333,8291.33333333333,17529.3333333333,376779.9184425

00_original_index/03_data/processed/affordability_data_returns_q.csv

0 → 100644

+84 −0

Original line number	Diff line number	Diff line
		date,r_index_house_price_d,r_index_existing_buildings_d,r_index_new_buildings_d,r_annuity_income_ratio_d,r_houseprice_income_ratio_d,r_houseprice_rent_ratio_d,r_actual_rent_d,r_cost_gas_d,r_cost_oil_d,r_electricity_cost_d,r_maintenance_repair_aprtm_d,r_construction_price_index_bw,r_interest_existing_1_d,r_interest_existing_1_5_d,r_interest_existing_5_d,r_interest_new_1_d,r_interest_new_1_5_d,r_interest_new_5_10_d,r_interest_new_10_d,r_interest_new_avg_d,r_volume_existing_1_d,r_volume_existing_1_5_d,r_volume_existing_5_d,r_volume_existing_overall_d,r_volume_new_1_d,r_volume_new_1_5_d,r_volume_new_5_10_d,r_volume_new_10_d,r_volume_new_overall_d,r_disp_income_bw
		2004-04-01,1.3197552081947173,1.4134510934905364,1.0533041533123289,0.7898242024239721,-0.7992050531338002,-0.2974717116742909,-0.05159503857159464,0.17243322486688584,-1.4772646092843011,-0.1356111654446046,-0.015453290859390734,-0.1871130017710776,2.1304063869566736,0.5090186677055186,0.118672280683918,2.38817320033875,5.459299426978936,2.8020512332175063,1.4579449763157504,3.066442351067744,-1.388084948468915,-0.42989542610420983,0.002691864909998287,-0.002233301623810746,-3.2021586841310956,3.9854611305365495,-4.9892515164140505,-0.5576116866382819,-1.6742276692026437,0.1195644735318524
		2004-07-01,1.0929070532189833,1.3134517180646732,1.0105964121196465,0.0881445627805455,0.4987541511038529,-0.6906786213254357,-0.243483202142869,-0.031885063993364327,-10.523046819031734,-1.0963113468475338,-0.29216042805968456,-0.5455378744457562,0.2536462995908595,2.0848566121543843,0.8182395154939792,1.2923022872731504,-4.655495318402725,-0.9427679255559207,-0.599003454933067,-1.1959340569425603,0.5089970490759654,1.649798609282982,0.5144656983414819,0.5388301298431486,3.637770589958045,-16.248115016684217,-6.583285736642708,-1.349588770372545,-7.179522544152839,0.7004413116931119
		2004-10-01,1.6000341346440905,2.0644327580345845,-1.0507645887953387,2.2292496937330597,-0.1998002662672249,0.2954211897431058,-0.240507392093825,-2.59153790515132,-9.307308212578569,-0.5348474732866482,-0.1399259992486357,-0.4483015792848377,1.5355388083194699,2.057539771645489,0.5885832177261241,-0.3818255879812327,3.433172995325129,4.244305750975319,5.174741907004465,3.3419391589194714,0.8939657913106913,0.2948475362568814,0.4041106531236238,0.4079301720107509,-1.257534341140154,-10.408804626660118,-5.081788905783036,9.340691420352965,-0.3973479601720342,0.6955692376205747
		2005-01-01,-4.369627173569857,-5.024980535691714,-1.8099529415543714,-0.09013069560124265,-2.8531202372150233,-3.7740327982846544,-0.22818859219979615,-4.423325497682562,3.251731581609718,-1.4809541359073641,-0.47449205645682113,0.2977152021328422,0.19361090268663617,1.5168221473171428,0.8298802814695083,0.45836596676578356,4.9815746847212905,5.461126978173292,4.94192928469932,4.058100162837919,-6.295292177538592,0.0318124637345818,0.3861991267600118,0.3292276477854017,-15.711242046387053,-9.722649212012335,-0.28127033585683137,4.993333086532736,-0.6667052140844731,0.6907644732025986
		2005-04-01,1.7975319218636265,1.7657904355452558,3.0655310832983673,3.297001923756948,1.4655855878532797,-0,-0.2602758027629548,-0.783634832931579,-11.176668747023744,-0.9030249085818731,-0.3344401739182601,0.20792149186688036,2.81708769666964,0.5107636058345078,1.0772096981911172,1.5432405038811492,2.505181516452759,3.2272969708520227,2.829675021250422,2.670895126452155,-1.1529396119273727,-6.488944352021164,0.3706287673907127,0.11677304584853943,12.737616093713644,7.931977466741813,12.395151706779295,10.385607728169965,8.290947224088363,0.7680182545872327
		2005-07-01,-2.034779957226629,-2.23144901854031,-1.1412752460529418,2.355266667251321,-0.3929278139889192,1.7241806434506124,-0.20051560795524281,-2.3994295928303266,-15.006069457573368,-1.0889958389652676,-0.289087760579676,-0.38148450713197946,1.4725835045043878,2.3687265889599685,1.2715884325302573,1.5674302093443337,3.7520032471263898,5.729303051915835,5.113429923656754,4.427600637936968,-2.1970526543755753,-1.0765573072285761,0.29535994009428634,0.22640909635658346,5.526724973793495,6.0716673181161696,15.622998010046096,17.832381433972877,12.917849563847206,0.7621646622972378
		2005-10-01,2.8848154337658194,3.1861102068983627,0.9580934406065111,1.3435902696827817,1.5810606026641416,-1.152750517106771,-0.23863302077220538,-6.55435197675569,-0.9004000053954186,-0.5348474732866038,-0.5320482088676748,-0.1241521868677431,0.40540596065523626,2.272825107755616,1.4114993471653792,-2.803922006439308,-3.9155355811994585,-0.4834820054583133,-1.34230203321406,-1.6834064867897958,-2.7107224935157603,-0.8121929055567634,0.522788440097699,0.4587832038033923,-3.701344327032352,8.762483630584406,17.594598976382336,5.984628878849918,9.588752978402937,0.7563996239616344
		2006-01-01,-1.452810056290943,-1.54672922933079,-1.1478161316745172,-2.481043291451357,-0.39761483796389996,1.249415580216251,-0.3864499019972101,-7.741619057247995,2.6395742765823904,-1.4113427253930055,-0.6152522257941051,-0.5106966378630062,-3.7213596340434307,1.0011635414246545,1.306394940342459,-6.107631340910036,-5.715841383994857,-4.095060361309533,-2.3256862164267256,-4.202953224364836,-6.96013204561492,-1.2067729378438585,1.6139717511830298,1.4695592881198039,3.620861425303712,-5.45715936440887,1.61228613160187,13.653463802901555,4.335044087361339,0.7507211451716955
		2006-04-01,-0.3599284029647265,-0.8230499136515412,2.561362056656691,-3.518881578963917,-0.6920442844573493,0.19361090268663617,-0.2572273692019067,-1.2762251613851028,-6.216296662445497,-0.710131756853194,-0.7110832991169325,-0.5940074247950733,-2.193636348420669,-0.1546790718298663,1.0069311005540538,-4.451459045386885,-4.8937125739246135,-5.479794837622887,-5.225069034387797,-5.1979034823580905,-3.1871985141538772,-1.0330459939940084,0.22199092594927805,0.1589656316784982,0.42849556725013116,-7.056701876325278,-12.56633624003225,-12.267792992533977,-9.711474205830228,0.5256753721971208
		2006-07-01,1.447552417378617,1.8913093306487383,-0.6254566492224001,-2.0712131679020196,-0.4914014802428923,-1.1560822401076365,-0.15811525977200702,-0.5420067469339429,-0.7002452529217607,-1.197044444691464,-1.0994076409840403,-1.4847978939742212,-2.2089885272283727,-0.23157092555980974,0.6981938867118176,-4.52627073659102,-4.665359832277516,-2.8799686610231356,-3.5718082602079315,-3.6238423500556616,1.2037510204471857,-1.139506005176294,0.09828050465685578,0.06179290373236057,-7.950837691008861,-5.971281911945603,-11.046753861951153,-8.732417922137437,-9.084877273182812,0.5229264702315106
		2006-10-01,-0.8469500113574391,-0.8318526875091159,-1.3257249793978687,3.445490408305041,2.68272422331437,1.9342962843131417,-0.3159835780718545,-4.095171583581081,9.83475307759658,-0.6493294548799433,-1.2302676666069878,-1.7002741137776667,-3.6166981984990354,-0.7680529307777961,0.6389798098771049,-2.9930666246188675,-1.669023444037876,1.357648577394266,3.0640088375135877,0.6300335856250561,-3.2241335839415797,-1.12581151933977,0.21365358151737013,0.15379740680234733,4.17937444405494,3.8499689609297505,-0.18537903350406282,4.369863756647696,2.5276407831102077,0.5202061683108994
		2007-01-01,3.0608268401212335,3.635712483106879,2.0735724675929212,-1.2832440069884044,-0.20120731134198877,1.2776586578981508,-0.303302998368693,-2.5274569415479675,6.64157138046102,-3.3736432287872375,-1.673277698224851,-3.964726071273361,-1.2563730919598504,-0.8381001438230617,0.6430890330290318,-4.695698308777119,-2.317758831270589,-2.135312447056892,-2.782912376948543,-2.7019309048203155,-0.9043227298731082,-0.4947901010657674,0.22810992240991368,0.20371701661545671,-3.6455011610113885,3.8302850833741076,4.9340110257233505,6.570670543121615,3.9313861087794777,0.5175140224048747
		2007-04-01,-1.4821662470571262,-1.3615270994873363,-4.95554621406642,-1.1770167570154477,0.7060039410724528,-0.19762852282116938,-0.2938244360665365,3.7805189341715284,-6.166652114414806,-0.7985120335349372,-1.9031680930867267,-0.3864338982179305,-1.1820468600426182,-1.0566136037882146,0.6472514505617699,-2.3573167718066834,-2.856388149130651,-3.3244058579154467,-3.3221048076776727,-2.763910348966081,2.534884062357712,-3.1208560925142237,-0.10512625140339793,-0.1799461388406698,-4.097790440465765,-10.175341273341942,7.663602799556024,8.374964779052974,3.564431850529992,0.49021172802525825
		2007-07-01,0.12247398958962208,0.24242436115065047,0.22310787115138453,-3.276078723988185,-0.3031836582120029,-0.19723872272043863,-0.35272867468520985,0.985576439652025,-6.228591153391161,-2.093074270252071,-0.9489352591126377,-0.353193318689371,-3.804493406426923,-1.416348685986435,0.26007817000572864,-4.325630516606016,-5.106406051888013,-5.047552141026057,-4.720051923379764,-5.245618180159584,-6.247954279147727,-2.152524639032194,-0.30302417539029847,-0.39861723026444196,7.715536952395219,0.7235485289237786,-9.980575791648683,-9.806772051141621,-5.772768183179444,0.4878203705915851
		2007-10-01,-0,-0.12128564252087415,0.14384251304466744,1.8462062839735616,0.4064758526331147,-0.589392668877764,-0.2732800708657557,-0.035366932287317354,-10.575182851744724,-1.6509898070600215,-0.8987425408562011,-0.8904541050726245,-1.7381990752944443,-1.8335680533090093,0.2607563407080793,-1.532814569403529,0.87500558274640206,1.6324227988948614,1.9010733134935398,1.0783485401027804,-1.0182248591346976,-2.371854031641618,-0.13372356629481885,-0.2002287690730853,-10.020764903611568,0.9566590150081211,-9.459906244582683,-8.973843808519533,-7.79728606316521,0.48545223104543567
		2008-01-01,-1.459879942115272,-1.563471414740203,-1.2742327307086576,-0.9713100646499662,-1.610101215827875,0.19607849419402967,-0.37812014331768395,-3.338279385320586,-7.414390137316396,-2.483373499367403,-0.8398260854467487,-0.7264342030868676,-2.957499233482652,-1.2278955286516569,0.3924138456134152,1.304243041317954,4.100510398098622,2.129155613561773,1.8704620134807337,2.192221898315161,-1.1363420606967267,-2.338723778270868,0.08909502634200095,0.01957215322665462,-2.8951438396603635,4.650649142994645,-3.376453177001082,-5.160619680065537,-2.5193166785813403,0.4831069728838955
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		2008-07-01,1.8215439891341667,2.166149678117879,0.3621381074310648,-1.8205964496572413,0.798407434822046,2.1847602208276307,-0.19224465141443048,-4.872632962853984,-0.8925165959936088,-1.663469447113819,-0.26322879177387293,-1.2018397393021907,-1.2795753807208765,-2.0401692493780432,0.19743343037177397,-0.7470629360589731,-5.429369385068039,-3.6568457020795586,-2.8615259621652234,-3.156397613459272,0.09684058376961957,-2.45370840173873,-0.21774671554322111,-0.2814403913761865,4.815328441934685,-18.503794320310618,-5.670491440869974,0.4155888012769893,-4.387726993004648,-0.5442796297858266
		2008-10-01,-0.24479816386406839,-0.48543784647980814,0.524657190322042,-0.7702220362092227,-3.0589459522585294,-0.18868596457384257,-0.3480270266713603,-9.638321907321412,27.558631203859463,-0.9840621044086006,-1.316047591045777,0.2654773255444276,0.0453230608822075,-1.451805658703531,-0.06585446401976558,1.4193343755466437,4.259004920667664,3.055440615103966,3.9990424096922217,2.832877434808112,-0.8749600113310052,-3.1532050154906344,-0.3455670847431591,-0.41947315087078607,1.9003980930518694,13.47176323840289,-1.8164795807102507,-8.207596270378303,-0.6547662529783338,-0.5472582523694314
		2009-01-01,-0,0.6071664068549865,-4.442043324499867,5.43040590138455,0.2919710103334694,-1.2024192966801905,-0.29654117708100003,-0.7507976359876878,23.691478576285796,-2.0967275461185153,-2.406651712677288,-0.2737149242110881,11.638401474267624,2.9249996117866717,0.8595094235934075,27.298823419361472,17.164827344822076,9.059115207114775,6.9666045527855935,12.94790754195747,0.27424827500723836,-0.061707513231645805,-0.1370938964825541,-0.12683786218712356,18.914784771193727,20.16486215122688,7.9180885001433055,-5.578877003495641,8.402522316645644,-0.5502696560293785
		2009-04-01,-1.5767458252700983,-1.8105503632273034,0.6344054684412015,4.416541129768259,2.167572547903962,-0.9910883899453715,-0.24762844624612868,11.7387544253166,-0,-1.88584888448311,-0.9246191430854367,0.6361876710670344,11.411989097782605,3.9644831347240395,1.068100942033401,17.29124900250383,9.74613791588017,4.47501957986145,2.335872627762825,6.925551101571004,2.0660274092524133,3.949892170688507,-0.06059087312095812,0.05471382173052319,0.14261946795848246,0.9450696646382539,15.733507433816385,4.562753312622547,8.409449895803434,0.6347508819517955
		2009-07-01,0.24096397201534003,0.7202912294057562,-2.8096428794291306,-0.9363364288750731,-0.2983592466887508,0.19743343037177397,-0.1512910792595079,5.212798342918923,-4.323121513713168,-1.1458361508014825,0.1255578474792074,-0.3430495947928769,8.256435312169463,2.7582814615142004,0.9440393779087008,8.996889483221304,2.1377470772366847,-1.2883846272679245,0.29585820397450835,1.1890746521521667,0.7956814142325186,0.5042784495111974,-0.02691886436423374,-0.013941125803640375,1.6607177506113402,-4.05602502310316,-4.759514034761203,-2.275759931735166,-3.8036862204627653,0.6307471952094801
		2009-10-01,-1.5559859107032281,-1.4354313451683254,-1.088393214009642,1.2189555524585671,0.09935420588780275,-1.0810916104215806,-0.22975792523372007,4.531971054844686,-4.793683392300352,-0.6289208574585814,-0.42638886072055016,-0.16258709920684566,3.7151375039989,2.061928720273576,0.8846604140293479,5.225437086710105,1.7437233443140743,2.284943277234386,2.9314387668775366,2.830759171159447,-1.3456588885123466,0.7387067805566971,0.23901496107914255,0.24537460051909932,-10.59966769007108,-14.518884345630134,-16.239838498082726,-9.605325232074513,-13.318034258496247,0.6267936985112854
		2010-01-01,1.4354313451683254,1.315021938687888,0.19024797973568042,2.0973123380279013,0.39840690148746916,1.9743977989691075,-0.370562224009241,0.3214862565280363,-6.523742315421277,0.1779009730807246,-0.37795972224721197,0.15475592117333292,1.06545908981035,1.7906278354813399,0.7547205635382914,4.980282248381829,3.855251076860955,3.1301460003649417,-0.15243905390964763,2.913231403732053,-4.142912039759494,0.5577379660772763,0.1687618024211801,0.1600405743438671,-0.06495615687951428,-11.113639985629131,-11.23235655374124,-4.390052953026036,-7.439193859184279,0.6228894539624719
		2010-04-01,-1.5541257211211246,-1.78895647507753,0.3844053382326962,2.5367213878422668,0.1998002662672249,0.9013581305361562,-0.39738647537364,-0.21443896709083532,-10.786702424861616,-1.239883818377674,-0.24171785634097276,-0.6455687531167875,5.585407560658573,1.8232768261059684,1.317176755656968,0.8547060578458332,5.543927728245701,4.886965858499126,6.205366983746319,4.138521616285429,-1.4031123322983063,0.5624203992642407,0.10546608631862853,0.10763038829857408,-4.750444135775211,-1.4372356966172006,1.9398325061532162,20.474225134238644,5.382454349316923,0.9959578737484875
		2010-07-01,-0,0.3552401604368427,-1.752308169619532,2.805795279515788,-0.09995003330827146,-0,-0.18709607503897274,-0.14270426966884742,2.4308927850746898,-1.4589630031816014,-0.3753621753042502,-0.48136401860343625,3.3734173652025135,2.511270081507533,1.7599891110184007,1.6225342429126544,4.445176257083383,6.0207346617390245,9.782549615340796,5.985467182514492,1.652722446297794,0.5464024873257145,-0.008501108018066361,0.010010759697465232,3.020161094080187,3.4374422511945113,12.500751304162172,17.668255226627316,11.16258090513469,0.9861362913238025
		2010-10-01,0.5948857519772588,0.8338344917153684,0.22526670052558373,1.8462062839734728,0.40040093533821874,-1.5968403178731272,-0.30331310743143547,-1.4862269321240795,-4.562020591853155,-0.8080716869738325,-0.9580661696928061,-0.5892459296082286,1.0092600387224149,2.4077543375696564,1.1428695823622714,-2.6897802319898245,0.20222453807678953,3.151994388146573,1.1685526229645138,1.033358185454536,1.066280017541743,1.2448101950896628,0.20563025160935666,0.2413775292586351,1.5481810142652819,-0.9741240402785678,3.934898131943676,4.107585727418339,2.901411679094501,0.9765065287803409
		2011-01-01,-2.70764039456477,-3.0626657578991967,-2.191005895897913,-4.553138480795305,-0,-0.8871423387419419,-0.40401561946064035,-1.6719302729057972,-13.450038494840388,-3.5895222989951847,-0.7418792569782617,-0.9619235664357184,3.614851411631115,2.3810648693718406,1.0108389320760969,-5.272538946880956,-7.410797215372189,-9.672313769222773,-11.918851726511836,-8.764070363091637,-4.32220481493637,0.9868871356284004,0.4130450869856972,0.40787758842153465,10.985631808387275,7.370834779529556,-3.901551830295169,-18.813498845536536,-4.111908989214541,0.9670630209281939
		2011-04-01,-1.1547472424772387,-0.9237940984935911,-2.728237876528272,-1.8618862203210185,0.704582683320254,-0.5870858349783958,-0.3167936391138326,-0.27595740175341277,-3.4565173238084945,-1.4362693120285819,-0.6769712784271853,-0.8985904893803465,-4.036615006051458,0.9511528689973847,0.7283353391108305,-8.491115359403567,-7.074572031436599,-5.179150912840491,-5.693545336991623,-6.367309486114214,0.7824565318211185,1.9424363497332564,0.22632001672455715,0.2754329445583181,-7.6566853187343575,-13.30490088974745,-3.281760716096116,0.3336673099038734,-4.680005551998434,0.6314833335734349
		2011-07-01,0.46030000719605724,0.8078520565201863,-0.7003311763946307,2.258318850511909,-0.5037794029957077,0.19531256208820125,-0.2218820494678475,-1.4024515824137218,0.04094165870904831,-1.0380603261048726,-0.9301819792900012,-0.606033336340861,-3.392960964344449,2.220446049250313e-14,0.439561147303813,-1.6514136764413045,3.6562253493275687,5.595297996965698,8.460198608805491,5.163511630166329,1.509031932441296,1.341472157443846,0.04947385853242281,0.08855908493519138,-1.3183103842346888,-3.089223278520148,-2.2942780672737584,4.755918640966961,-0.1009192512320567,0.6275206322801097
		2011-10-01,-0.6896579059060493,-1.0374732825551902,1.1023043480204997,5.8268908123976,0.5037794029957077,0.2936859673310366,-0.3374466555172262,-3.3074670048204524,-4.660377357449619,-0.5774097212157159,-0.6108429950224981,-0.7215257929720664,0.48939738788624787,1.1358794035606357,0.8109148749258832,2.1150213681891517,10.72798050999677,11.476424400246898,12.742091532750631,10.062341537355701,-1.1773778239888344,1.3474365978956016,0.332265226946582,0.35579936982461646,-7.675179927984832,4.371953730563671,7.926503937315665,10.236315730806744,5.641427451249292,0.6236073547034593
		2012-01-01,-0.7986351632649935,-0.6857169726137258,-1.915058663321556,2.23532457807476,-0.3025720916537189,-0,-0.32464255229003314,-1.629762278809821,-5.346018477285774,0.3735771682688238,-0.8827152088495716,-0.7877771388107746,3.409893772112871,2.2213263410731265,1.1913767125848906,4.0783271602091276,7.8863760168562225,5.677330118974022,1.6060808150184291,4.445176257083383,-2.6714712964595932,1.6357655912049296,0.5105108695790506,0.5307066680932948,-2.6526754333429103,-2.868165994109617,-5.9715894582279105,-13.078616096471762,-7.258987751707124,0.6197425819355118
		2012-04-01,-1.2422519998557036,-1.3574869091068642,-0.2867381205659214,1.3001266557373548,-1.4000228673389792,-1.3632148790057919,-0.23837497970982113,-0.09694620245479513,4.238243083197535,-1.241922453592359,-0.7663229835155327,-0.33043781648034454,6.014884669049869,3.10243860174102,1.5855371789794015,8.692337593356015,5.741588037072209,6.757944368980451,4.47981428998947,6.216978730202061,1.112098087226876,0.8384910448659966,0.21511859087901541,0.23622301075381102,-0.9667405402136175,-5.564308077493241,4.5998708163018875,7.759291870734941,3.293589346891501,0.3740078426259785
		2012-07-01,-1.448493292136721,-1.5607897665991466,-0.1220663409454481,3.5519827248536195,0.09935420588780275,-0.38610086574593083,-0.29313446646144214,-0.32247689990150263,-3.643666823959535,-1.490697588572143,-0.6296925031441525,-0.32543179004065337,5.636595797788968,2.7244522106565583,1.456522491091783,4.979383557774031,7.5802963415500635,8.624125758306533,10.270799420869503,8.10070701732073,2.9881495692475113,0.7018899992582206,0.3766607608183037,0.3949558177719581,3.5505027325961613,0.6830302148076228,9.574529620482508,14.400986744311872,9.126360531290523,0.3726142345476191
		2012-10-01,-1.318700428195374,-1.318700428195374,-1.5633558768200828,-0,-1.185784645078325,-0,-0.25993101529149243,-0.7058097956568865,-0.7426695850823783,-0.7825767494422209,-0.47952138948774703,-0.7156814177251114,4.769760533571965,3.686159330415828,1.7920230233570589,7.0103365770978865,6.054649986803373,3.286680808035225,2.458224340533599,4.072697812985626,1.0303897326570777,0.7155947075094815,0.821069284376108,0.8217917080395765,-2.315305655315658,-3.004966196844272,-7.295089163444857,-9.855645337782981,-6.876772549289534,0.37123097350271195
		2013-01-01,0.3280484079161816,0.21857932199802477,-0.027906332335447814,-0.22573373016507858,-0.8802012818090788,0.28943580263645075,-0.4687689517449023,-0.28731065254765653,4.309056652491083,-8.076504741904511,-0.7464094465198023,-0.36762324694077364,4.069737616381008,2.6027495244775434,1.6647233433156217,3.636764417087468,1.2024192966801683,1.8061899805013049,-0.22598879674375905,1.4354313451683032,0.5143311105870296,0.37938703774518245,0.8007337113930646,0.7912485281970305,9.367974814913271,-3.925986563261752,1.7646732752412575,-9.759236848069719,-1.396305640187201,0.3698579446831829
		2013-04-01,-1.9523396682098237,-1.950224323144134,-0.818452248328061,1.3621095951965145,-0,-1.3435902696827817,-0.235113723339353,-0,5.497961540193508,-1.2204078653369699,0.1821069521461105,-0.18916705108242837,0.7295498746724194,2.568194563234294,1.5304366373446232,-2.318590746881033,3.9758492139084223,3.965823290941606,3.5615481668320736,2.6863642269548293,1.5151340294801585,-0.19061207123911572,0.5343664470672138,0.5167921019237909,-0.0899800819113672,4.754518636163407,5.964494154923372,11.68622578883145,6.612233846762017,0.8791787482405056
		2013-07-01,0.21505384632281022,0.10735374085246718,1.4212385342293743,-1.5873349156289684,-0.38872740884015045,1.4402553327922618,-0.3621725884579874,-0.28648754275453214,-3.0542860382361425,-1.0213142099583017,-0.5815988984781306,-0.5843455571385547,1.9007964045176573,2.7427879681605427,1.967276559870479,1.5805800171187823,-1.6643934839511765,-3.844242728852587,-2.768342874841667,-2.2032714999882685,2.114345547026275,-0.36496793050631027,0.5001093696186842,0.4785929385235477,5.321403089613597,5.783229555877956,8.71939087050233,0.1321877257915105,5.161075836381279,0.8715165113610368
		2013-10-01,-0.10758473334631091,-0.21459235702767643,0.08086010105001762,-1.894207052907504,-0,-0.6747013546594793,-0.3299997390916687,-0.2539683904760004,2.5860917987564846,-0.460828224903409,-0.28186741064768484,-0.7107689215619217,0.2134472528632525,2.381064869371863,1.6694878572169891,2.4815169119724034,-2.7138707599297818,-4.867429602724815,-4.232257457128785,-2.9817355052396133,1.9829507807051172,-0.4652651913335859,0.5516224131230985,0.5329916877535368,-3.171329806559431,-6.432477088865429,-17.775089027958657,-17.072646262775493,-13.696445875932106,0.8639866775617122
		2014-01-01,-0.8565362858922398,-0.7474674416705795,-2.212060419488715,1.1098893068049343,-0,0.8683122573461155,-0.49895864116740185,0.15865464219588787,3.0517832231906183,0.5225267779898068,-0.3178803177688927,-0.4855786199859047,-0.8510689667908578,1.879546762003792,1.6122538450521917,-2.9705154413915746,2.7138707599297818,3.1786077998726237,2.6520891379965716,1.7783515488672519,-0.5860650895314734,-1.1166088394878315,0.5766836856290425,0.52712316896244,7.245237243059499,5.98867805912997,-1.1126145851241276,4.315325502259704,2.9324714512657835,0.856585844341673
		2014-04-01,-2.0053442446729797,-2.0011199619388798,-1.7592994748278024,1.4615212370969743,-0.8691508118458202,1.071612787684284,-0.41240193261211644,0.19071843034570435,0.37759642095354096,-0.8025444781100788,-0.46462354721690247,-0.18143656004632192,0.10598835120432248,2.257432203853904,1.7256683623312563,7.073655109177812,4.78964783436161,6.549591709389857,5.288588622444479,5.786229223882744,1.4993134458586965,-0.7234704071109377,0.6120787962693441,0.5780871461604775,-9.7818591326714,0.7182731270273912,7.1151034803421,7.765955919502687,3.577272098243256,0.7533884209193431
		2014-07-01,-0.5211059212752112,-0.4162336914687259,-1.0145345762105684,2.5230696176230083,-0.6708218735118621,0.6879634013536418,-0.24768118179974152,0.09549578952681159,0.5056900788972918,-0.9830185133933078,-0.30812453533304307,-0.44518304757197313,2.795881037699277,2.660654344471225,1.6674366142369612,3.869728995368382,8.740500029721165,9.78677259554419,12.16274881216981,9.569048024625381,-0.9366251316075491,-0.4141520596061099,0.5798756830222018,0.5382304997393561,-0.985996571339598,-3.5178338759701333,5.28345554747478,10.444758170274149,4.826631285721916,0.7477548956716262
		2014-10-01,-0,0.20790028278332429,-0.6629166559383393,3.0662779576874577,-0.19083975257601082,-0.6879634013536418,-0.3616247667311612,0.3189795368100157,11.683291682006303,-0.5712044996823984,-0.6941161439885768,-0.8346510617893266,4.80270966009293,3.5803346814609505,1.8758924356019113,6.753620699048746,8.715455116125382,10.536051565782644,9.504354868689402,9.044060496436856,-3.7457116361185427,-0.052698907145476426,1.0800395125217577,1.0253396373954615,0.3384097984240775,-4.335543230083694,1.5220258543889642,6.620127309553148,2.3505581935939546,0.7422049958117682
		2015-01-01,-1.6495219369111247,-1.7535261064525187,-2.0440729425227566,0.8418570465596353,-2.6342068760091486,0.19607849419402967,-0.42027817168763804,0.7697279825566561,14.953173397096453,2.3933238798217182,-0.4271317835536692,-0.725311622948599,3.6113417653679925,3.4614086022737856,2.1878721375807153,2.5056579837337556,2.0834086902842053,12.30787232310938,17.93932970148664,12.16071320947868,-7.665040977539483,-0.26681313493135406,1.312376511773472,1.2294620860602734,-1.7168366123086365,-3.247690851778362,1.2295822833621628,26.574219044959335,9.768050419027752,0.7367368730175627
		2015-04-01,-2.1245108613736186,-2.3245109280402687,-1.2433009949814,2.697904090169434,1.2144007254798694,0.09818361122571062,-0.29921977378997155,0.1933613235395093,-1.069528911674844,0.03809774053769033,-0.33925313039802063,-0.2996938113192016,4.116804094336379,3.5855313287075696,2.4254920373153466,4.268940869505055,3.936107388058019,11.623556104670163,0.8810629682154847,5.492966203093442,-0.9611027835946473,-0.48547118373143405,0.8380700965469501,0.7924722628978031,2.4547517996502677,0.1530222180766927,11.774093127962715,13.059401440797735,10.00662024504777,0.7643741813966543
		2015-07-01,-0.4992521603121247,-0.29925209364547456,-0.7253577813845169,-2.8186041651729887,-1.121507082013995,-0.2942621054197403,-0.20829343309269888,0.3878479328570883,8.805343141961597,-0.8000719329399608,-0.4150227850370669,-0.4363627320929986,2.25009492908379,3.7188880419054327,2.679586158444658,-2.9165536161725014,-6.362569588021138,-12.504619072885648,-11.994392442572256,-10.207644045663622,1.6466406755190732,-0.43939487297492974,0.8898181992202936,0.8528161428850822,-2.666476107933402,6.6702335384750455,4.8770113843113805,-4.6957704395154565,0.258837248653343,0.758575795849481
		2015-10-01,-1.384789685879273,-1.2865095796884773,-2.214179140068584,-0.24096397201534003,-0.27842245364047,-1.1684650954973286,-0.21548652621969921,0.1620483258516714,8.644284905553423,-0.350922462820602,-0.46103310429144173,-0.4483015792848377,0.7614249985245403,3.3015378254194205,2.3553591298397736,1.0646488394487452,0.5150225976315759,0.7042282625412843,2.061928720273576,0.991743665734568,-2.203819086989789,-0.542059596611999,1.002580945485576,0.9497398266347545,-0.9182312171101437,-4.021294078553783,-12.83146999857454,-12.883631158471331,-10.490036933701852,0.7528647191344717
		2016-01-01,-2.0418793988759454,-2.043866767727387,-2.463137215111999,0.7246408520767744,-1.0143009965054794,-0.28999536997895703,-0.41580260965421445,1.010603548180189,16.143055116935745,1.369166244495812,-0.31143819335230916,-0.7060573412182691,0.12746974320005933,1.5504186535965192,2.615843315319899,-3.456392145507625,4.578264310547664,6.007265403733841,5.942342047080085,4.588740451147066,-1.7310059858338889,-0.6497975684679247,0.9753417328553837,0.9269398450452826,1.7887194360739045,4.211830814508488,-0.2327864665794266,6.559160415609533,3.1661680295037797,0.7472389940073043
		2016-04-01,-2.846491992581779,-3.0362863730117873,-1.5167926106244956,0.3642991278500318,-1.6378892084039975,-0.9606221805440462,-0.15439082574451035,0.42685994875553135,-4.988008253345733,-0.8767911340209267,-0.4403628034577167,-0.6621896534067417,1.8018505502678472,2.2989518224698746,2.5814546513961867,5.776681853474031,0.9049835519917893,8.61589346909724,5.0577474743527695,5.726072086341505,-1.789054204099294,-0.5533567051713817,1.0163749943281175,0.9626801312650812,-9.772938737932435,-14.575224695461664,-8.434370750113906,3.6553085806641405,-4.183064074280729,0.9620390326155359
		2016-07-01,-1.7617516390843413,-1.8519047767237673,-0.34039581851494916,0.8552281815317642,-0.6297816586990024,0.38314223115563095,-0.2410594528995169,0.6934153588998626,0.8752791109595037,-0.6912066435737607,-0.482121730275864,-0.5511632787730925,2.7651531330509904,2.6511125548331904,2.7573326904099638,3.0184976338397562,3.704127168034921,6.986967996048598,9.173874743672773,7.255089065857556,-3.270485100717302,-0.6573658849323039,0.928589404358604,0.8653350444642882,-2.864262779169824,-3.359151437381236,4.229855513820979,4.329954301581651,2.7400862999456876,0.9528719623782322
		2016-10-01,-1.459879942115272,-1.36676387286645,-2.090917587952834,0.8626054719766962,-0,-2.558168871173283,-0.42442038059231635,0.6315460578784737,-6.899287148695166,-0.5348474732866038,-0.45481050317999205,-0.6943041633711289,2.159328163056795,4.113298814739252,2.72496424473756,5.810763080728066,6.8319243977477235,4.255961441879602,0.5899722127188256,3.0153038170687596,-4.491783931362647,-1.2697382764477183,0.9770515354841081,0.9021778297526595,4.942147956080056,-5.2802758814388895,1.8744204508976736,0.938974034983886,1.1997237560320784,0.9438779466560021
		2017-01-01,-0.45187605133261144,-0.6314860858673832,-0.8303205692303806,-3.0471583645747202,-0.6258402188422885,0.6569709223160913,-0.3410922485476142,1.2751850647418017,-4.903433460160578,0.7556557515730589,-0.48986519239280213,-1.0445868310811512,0.2732242136872953,2.6794353137520877,2.687731776374669,-7.885857491231962,-1.0050335853501458,-11.44721960090822,-10.831472755525773,-9.716374845364783,-3.6472445448442414,-1.6105106865474283,1.0933840202905998,1.0165458738651267,-8.213680061434037,5.469885342871894,1.116342585405583,1.2825323744971584,0.5059739043518974,0.9350521308910231
		2017-04-01,-1.9643488765753503,-2.047245510497575,-0.7075072392987991,-1.311885242911437,-0.621947806702039,-1.8657257604543176,-0.3964674188769557,0.7117467768863683,2.2717026284232666,-0.6898757099643937,-0.4994841958457563,-0.6369839567859081,-0.2732242136872953,2.2618088587772256,2.8787249794437253,0.6339165443735584,-3.922071315328135,-3.0153038170687596,-0.7054702979889971,-1.834913866819654,-1.5879527258624293,-0.3443562800473643,1.2641311058134264,1.2142871291667134,0.904290015405973,-6.556196568608907,-6.113067055538934,-1.5817385511468274,-3.352819934774409,0.8724859410293107
		2017-07-01,-1.6659745241175195,-1.573459035355551,-1.272416962307954,-1.8779894651595797,-1.9298844572220197,-0.36900410874531886,-0.2023930494173598,0.6141268022083146,0.9367750003599795,-1.306019930216351,-0.6170231862042463,-0.5369523410641897,-0,1.8137347977118523,2.8437935320533514,2.5766320764229134,-1.5267472130788495,0.1982161203991306,-2.943935545068177,-0.9049835519917893,-5.648940176124562,-1.3895443852156575,1.1044967374813197,1.017374011651384,3.0059371686753877,4.759512152610057,1.1343200879089466,-2.1041965838781707,0.2261331350906559,0.864939418744548
		2017-10-01,-1.9802627296179764,-2.1450843942472986,-1.567408198077036,-0,-0.08684325339540777,-1.9152432214756487,-0.4191900035119822,-0.10261673553122463,-6.946334903032714,-0.6066349853430353,-0.7322841090853238,-1.282136071000206,0.9595687061855429,1.17156151725627,2.433210065953073,-0.48820275973082694,3.272669350255708,0.5970166986503767,1.7212128881121447,1.2692826798418988,-0.7332755129391799,-0.6370926233890017,1.0183086624788729,0.9773254013069277,-4.543482833360635,-7.154468500313449,-6.653380126031827,-6.566910350785804,-6.4120188989541305,0.857522324293214
		2018-01-01,-0.8489015324911087,-0.676821534613925,-2.832155382642476,-1.2709587604949668,-1.0362787035546717,1.455894687556647,-0.5092266984254579,0.5828921012546395,-1.7716081064479638,1.094964384979047,-0.5523272677981694,-1.4659989464778533,4.363816926000386,1.5267472130788384,2.3677118526829855,0.1624695727001857,-0.7797310460031626,-1.190490250631837,-1.0362787035546606,-1.2692826798418988,-1.678302095737827,-0.6481525101657226,1.2785334543176319,1.2325198492588285,3.7407432767150084,7.347146787283432,5.391132447364022,11.839733774478312,8.253704163392861,0.8502313563067077
		2018-04-01,-1.9255513308744199,-2.0860163995421566,-0.9796396815233699,-1.9329766139667193,-0.7702220362092227,0.18348629001101457,-0.28716316819643595,0.3444715772782381,-6.615458982589573,-0.6850211097352954,-0.7973929091614984,-1.0659810858760999,0.7220247973487304,1.203797855947908,2.4251348045120857,-1.6129381929883557,-1.350068721890263,-4.247742826711621,-1.8723951266287564,-2.66682470821612,2.83409594571129,0.4105515595696829,1.3204323638730031,1.3040677364285713,15.047656111303276,5.9230909160167045,3.507264451774894,4.1018491515377065,5.363591175802718,0.43165135179084047
		2018-07-01,-2.051774889732272,-1.9624505508985202,-1.5496041818695794,-1.7857617400006909,-2.6084777215290345,-1.368010390408081,-0.3016906161992239,0.24183808642819216,-5.906291720434176,-0.8036739027479811,-0.7062476301932463,-1.3152133354009443,1.1661939747842798,1.745244995122608,2.3530497410194195,-2.371652661731616,1.350068721890263,3.0712586687529853,1.1874609420712723,1.5915455305899329,5.17148325119976,0.19890660953318928,1.1070065822709196,1.095178249974893,-10.881909480102792,-4.092026978936314,-2.2741911387717195,-1.070258743492758,-2.9221616399064843,0.42979612812565904
		2018-10-01,-1.2111573162944644,-1.5267472130788384,0.5823328624005697,-0.11055833077495691,-0.08302200559890949,0.1813237124181022,-0.34524354164462423,-0.10371651750826771,-8.988393474788925,-0.6414383520942479,-0.81839761893443,-1.3532851312765715,0.7358384931187123,1.4184634991956435,2.409755157906046,4.473589384139142,0.3891055492966533,-0,-0.5106394074574028,0.35714323675972715,0.8909789304437865,1.241231571580137,1.114642862951598,1.118390713142503,-1.6746457477180954,-2.081618178207645,-0.3312390383079844,-3.5989254621677347,-2.1236899500252093,0.4279567836203313
		2019-01-01,-0,-0.07971303730185397,-0.5955988355886177,-0.22075064152105028,-1.2371291802547368,0.18165309263977747,-0.43438109484403853,-1.406782507076798,8.689845281809117,-0.5760588397182076,-1.0893612114620588,-0.9334139458122337,-0.7358384931187123,0.8968669982760358,2.1918685707646213,-0.8136741393061642,2.967576814611661,4.179712867846147,5.227671049648752,3.8290912993314663,1.9341770368836109,-0.4288586919487969,1.2951108555467883,1.2673690106941748,2.6150915505159134,5.33560053659583,-0.9166056871153572,7.400102142582021,3.859617204408572,0.4261331152747516
		2019-04-01,-2.535793559008148,-2.7506645789832973,-1.1930453871505264,1.331873184028165,-1.0599365437041541,-0.7246408520766856,-0.3168319900467509,-0.7805911008547994,-1.4795158916747653,-1.1248415906690568,-1.2015448789147065,-0.34671110018873463,1.0316966970932318,3.4833952675632607,2.382733608055765,2.4611578596566597,11.929019494695476,11.170398958000128,11.154137473290737,9.959443707919474,3.1846476484608033,1.205855013426671,1.6256627734223983,1.6206388753271739,4.966098857109191,5.91384013884273,5.764250648340052,8.038490974719714,6.754362883613396,-0.27107508524650825
		2019-07-01,-1.3986241974739855,-1.3857034661426404,-0.6766750970171209,2.2599831917240465,-0.8881770134780531,-1.3447087431214477,-0.3306827839979043,-0.33749610165267896,1.4795158916747653,-1.3566174539442422,-0.6814865251250524,-0.7188590265867489,3.1605339415331057,1.503787736454043,2.5863510589919314,5.1118453929023255,5.343896215556054,17.05726643048717,20.089294237939008,15.998560285189145,2.9859486030316518,1.0620298720803945,1.1769153575176716,1.1744788182385335,0.592036174907129,-7.054606879635106,2.4337687605653358,11.832461622972978,6.031571889252341,-0.271811900038621
		2019-10-01,-2.3638157419988204,-2.1929045084799093,-3.3615714926413354,1.0338977795179893,-0.9600073729019165,0.6252811797187618,-0.3745227620320257,-1.0390574461737856,1.0077710239290383,-0.774368545882087,-0.5248233970216454,-0.8868987736103229,4.535570172079739,2.4929383042525455,3.1044621681960094,2.8370697129215583,5.141891463769993,10.207153078236859,9.213673639898609,8.285791162412304,1.488472447642586,-0.18941063948840764,1.442863012560558,1.4109125551849289,-5.515596924320576,-8.694408903078443,-5.905222985645864,-7.173024546156448,-6.712203984879039,-0.27255273125348367
		2020-01-01,-0.8255206355966216,-1.1896051068845281,-0.06526158118225212,-1.8307147444356353,-1.7364287909336085,-0.4470280130903781,-0.42848545048963516,-0.7309002637662765,5.7174516769876504,-1.08678146099912,-0.6257448598526061,-0.8986014036946877,2.429269256904454,1.7630231376270622,2.7398974188114433,1.4493007302566752,0.2515724597247193,-0.2980628138137667,-1.5957785438610816,-0.5221943981151611,1.2434738183928928,-0.009421731414782641,1.6037719387165694,1.5764287980040592,0.18412298948566885,4.22904354131326,4.364585870608018,3.560743033370173,3.5068665070829397,-0.2732976118211994
		2020-04-01,-1.7778246021283195,-1.6129381929883557,-2.0461337518791645,-4.000533461369926,-3.762439939472806,-1.2411506843343467,-0.34532756075451587,0.16564522588256025,11.344463405778527,-1.0596988950098307,-0.5343279263701817,-0.008061313476037668,2.6579637804711953,1.794664319083683,2.658483381106158,-3.055044419842534,-9.82826296892556,-1.1834457647002916,0.5291017634415696,-2.0619287202735648,-1.9030740679120584,0.7234957160042299,1.590272550688887,1.558535375755099,9.354627248641023,4.613294382824051,4.142256969034008,0.15056464575877726,2.7758143033022264,0.7832716344521984
		2020-07-01,-2.9658593393003585,-3.2203140494634575,-0.7372798082662335,0.9852296443011888,0.3018870217252001,-2.006172821743757,-0.19216687352860973,1.133723380316276,9.960510408720591,0.8526280373574835,2.0542100157998178,2.3445270718779554,0.3372684478639143,1.2145898302107994,2.731093439407084,4.896717098465642,4.67374778516898,4.20482362434994,4.336722911512977,5.505977718302746,0.7020060738877731,0.08713499727939222,1.2446727650662126,1.212947782286733,-11.168055967641433,-10.163092671203255,-2.683311789192011,-1.008073052835634,-3.3320369832258834,0.7771841406500002
		2020-10-01,-2.811147867141006,-2.7094397927479363,-3.3985958158876173,-0.43907864174901334,-1.276772883000099,-1.5424470325631212,-0.33686132624737297,0.033540164661260974,3.913463364445491,-0.4005291186398807,-0.29172576923892635,-0.9992671603817449,2.7398974188114544,1.8500013743920296,2.975426108179269,2.22722169749634,6.6773872539390435,5.410641767579989,4.440643496555902,4.786606298060378,-1.3301757460345343,0.5788942871637559,1.8231669196755007,1.7893898616382131,-0.15862718734691583,1.4417957140327786,3.1287468241300687,1.1201112754820386,1.6755196658733595,0.7711905401418306
		2021-01-01,-1.3764842246253295,-1.9009397937368888,0.5499773527144924,-3.7618621660053364,-3.807194794940827,-2.3530497410193973,-0.3902201594982557,-2.9092960941665247,-11.275570720440786,0.1438694334405355,-2.5474366686470518,-3.5820817519653936,0.9612020031172674,2.0965128465044836,2.8938189492354494,-0.1614205354541154,0.1740644477784159,-0.05503132068377381,-0.19672516904023218,-0.09609135069431063,-0.8268966763791852,0.1442762046346857,1.9207885212940923,1.8841578632994072,-0.3324903677443203,3.486882565082361,9.015640785610834,4.632310155911945,5.54022734895625,0.7652886772319789
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00_original_index/04_literature/Baur_Dimpfl_Pena-2024.pdf

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00_original_index/05_output/.DS_Store

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00_original_index/05_output/.Rapp.history

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		load("/Users/severinrenaud/Main/Uni/Master/S3/git/mlw_project_tw_sr/05_output/pca_analysis_complete.RData")

00_original_index/05_output/01_Plot_hai_cumulative.pdf

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00_original_index/05_output/02_Plot_hai_returns.pdf

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00_original_index/05_output/03_Plot_pc1_variance.pdf

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00_original_index/05_output/04_Plot_avg_loadings.pdf

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00_original_index/05_output/05_Plot_loadings_heatmap.pdf

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00_original_index/05_output/07_Plot_cumulative_contributions.pdf

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00_original_index/05_output/affordability_index_pca_returns.csv

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Original line number	Diff line number	Diff line
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00_original_index/05_output/avg_loadings_pca.csv

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+10 −0

Original line number	Diff line number	Diff line
		variable,avg_loading
		r_actual_rent_d,-0.43244715459424626
		r_maintenance_repair_aprtm_d,-0.4037657409640241
		r_construction_price_index_bw,-0.3912533417133141
		r_disp_income_bw,0.39065406594864344
		r_volume_existing_overall_d,0.3666826126583123
		r_index_house_price_d,-0.2586459986965647
		r_houseprice_income_ratio_d,-0.14308481265897946
		r_interest_new_avg_d,0.09108317833700706
		r_volume_new_overall_d,0.05349718195536953

00_original_index/05_output/contributions_rolling_pca.csv

0 → 100644

+65 −0

Original line number	Diff line number	Diff line
		date,r_index_house_price_d,r_interest_new_avg_d,r_actual_rent_d,r_maintenance_repair_aprtm_d,r_disp_income_bw,r_volume_new_overall_d,r_volume_existing_overall_d,r_houseprice_income_ratio_d,r_construction_price_index_bw
		2009-01-01,-0,-0.18343048441260423,0.1597087935404254,1.180817653858318,-0.21805148443494315,0.9729913789155742,-0.030933012899552338,0.01137584334469535,0.13121548866854393
		2009-04-01,-0.01181257728196498,0.681877044378849,0.13450665512715956,0.46669451593283967,0.2547681308014777,1.7193025208137471,0.013514330086881965,0.22247456152524772,-0.2592046036668755
		2009-07-01,-0.004291650879956665,0.15628927994348815,0.08287475304110543,-0.06416680826662513,0.24358235423788138,-0.8945931199628674,-0.003136560641217872,-0.026223761864068836,0.13651904565177345
		2009-10-01,0.13511953357453746,0.3356909473329271,0.12855690129831543,0.22263610116336907,0.2548965342910104,-1.5834206829083688,0.0548528949067276,0.006434812884646085,0.06483219896403562
		2010-01-01,0.073047392862299207,0.26815483375049903,0.20180782920973223,0.1916467597549883,0.26315922114138185,-0.5124521188632584,0.035964643341105156,0.0646730043743181,-0.0647681255676651
		2010-04-01,0.1421837161808007,0.6755329344906493,0.21698975323166306,0.11890712866636824,0.4303370699540623,0.5718158161670481,0.024270048052820813,0.027971418361423292,0.25530908002652336
		2010-07-01,0,1.1798750613336175,0.10145774120452367,0.186236638790943,0.41867370617267324,1.5590561560096419,0.0019507763976619609,-0.014371573827145495,0.19283140494774523
		2010-10-01,-0.055885887034182624,0.22558518319670318,0.16278161502127408,0.4723926516169581,0.42316868539132824,0.38881842158852625,0.048096542060826517,0.051547817973988136,0.22847926855900602
		2011-01-01,0.4459583239668597,-0.361808982091381,0.21219493840940343,0.34128305639426065,0.4607149670533709,-0.03373486532158637,0.10273663725357565,-0,0.4000938161837625
		2011-04-01,0.23036413702686398,0.23393049650964703,0.1595062674301886,0.28953162202121235,0.3020094220464605,0.09344775283501434,0.08207786899053118,0.13452402638201985,0.36835865684198915
		2011-07-01,-0.09588610629740524,0.19681801902594445,0.11274347337620191,0.40959387003192926,0.29701543673108494,-0.002977014066131486,0.025559036609976778,-0.0902874785262738,0.24448996078072704
		2011-10-01,0.13938680566906475,1.6274865245564776,0.1722953293832918,0.26849874839248006,0.2914341532735716,0.5189576350281352,0.10837618053676497,0.060620748960620814,0.27471138867631023
		2012-01-01,0.2693735172943285,0.7400270890329771,0.15650905980592214,0.35268151528985653,0.2720643603313579,0.15020798622715242,0.1692510376029288,-0.023784781322599407,0.32041876159963417
		2012-04-01,0.41489656986162893,1.3468751957989045,0.11347074735033491,0.3112769065068755,0.1577077638427508,-0.022680639810624313,0.08024296264470894,0.023330214672214567,0.13068343916898983
		2012-07-01,0.49157234402302763,2.156265275310308,0.1357625700050868,0.25123757665889773,0.14923103385129446,0.6890417297486672,0.1457381060238876,-4.2561960816998526e-4,0.12089753626029302
		2012-10-01,0.4603600795497411,1.1041980499517297,0.11901046596652343,0.188538436992607,0.1420093715503772,-0.21370203353845255,0.3105085389414036,0.0976294240820168,0.2711627333234296
		2013-01-01,-0.10283802119879007,0.391736528323878,0.21742270208141165,0.3002733739205332,0.14145312814414976,-0.048063729282552634,0.3085808117403273,0.07519977577229207,0.13923134956979027
		2013-04-01,0.6301718990945461,0.7448646311210959,0.10827422835432507,-0.06809389733966978,0.35170279636398283,0.37463404847173093,0.20470410562911953,0,0.07107658867092725
		2013-07-01,-0.06680366920546156,-0.5374129081173916,0.16474113157690018,0.21465985921495243,0.34994647810413054,0.3977542072276962,0.18985344172952445,0.033724405162655506,0.24009245150716554
		2013-10-01,0.03196223745158228,-0.5974390799826257,0.15051404901574628,0.10424653578323627,0.35410425889320835,0.18647909828736306,0.22168046241247694,0,0.298361900014084
		2014-01-01,0.25370757241235514,0.33962045028049426,0.2196503873504742,0.12733323031116056,0.35964965006687233,-0.03262154805463758,0.21818821368006205,0,0.19724098552871697
		2014-04-01,0.6081228027894812,1.2293527001521578,0.1747929986469282,0.18263381620040825,0.30330385559287465,0.006141574486526576,0.2349863153021052,0.1788164848670272,0.0723715885801493
		2014-07-01,0.1570573323124032,2.267512228280469,0.10320889783214933,0.11933367182887736,0.2998633290642845,0.1594144830782574,0.217404736347764,0.14896390571917761,0.1752713331486909
		2014-10-01,0,2.413107361229599,0.14930100334814875,0.2689839858849124,0.2961350716109456,0.19444375838758607,0.4087432449770371,0.0426260547719775,0.3292809421185711
		2015-01-01,0.5008046925988677,3.5899329840831293,0.1670681492502772,0.15303745655333367,0.2803227255606541,1.5440050367977907,0.4754104623618402,0.7087600208316656,0.2739022806188458
		2015-04-01,0.6526601724452357,1.644184099702682,0.12014125605794654,0.12329938912018526,0.2959115721246776,1.7580387111538176,0.31109660858244553,-0.2560757725308398,0.11349544036773176
		2015-07-01,0.15815809748947424,-2.387805154757126,0.08515255705025494,0.15395799664910712,0.3002808572917459,0.04136067023441382,0.3397430420715158,0.24985142059473442,0.16878720369336409
		2015-10-01,0.4582583160425073,0.22313662471346637,0.08793726542739043,0.1743399291208585,0.2997782241530354,-0.9275901420439452,0.3770165696826143,0.06469549167076791,0.17500344467745174
		2016-01-01,0.6809302912271811,1.2431392695492582,0.1657632345010139,0.11258572256929232,0.28959008550722776,0.37723259258737707,0.362495455711724,0.2534712868062803,0.2697972691592642
		2016-04-01,0.9428568996617974,1.6732563688818336,0.05911450260028395,0.1577976304635009,0.36818719305334,-0.38676015836889016,0.3723670210446228,0.4574278503906862,0.25410497407988153
		2016-07-01,0.6001066281666497,2.1476103927286676,0.09081853226334437,0.17416825501365524,0.36089513022087855,0.2795850284697972,0.3338870346372242,0.17475032507828056,0.20927728992206268
		2016-10-01,0.5023570303428073,0.881743729537846,0.15962365156355574,0.1643770549435327,0.35696028271546876,0.11265443045622035,0.34915102763503414,0,0.2637681817305144
		2017-01-01,0.15611051513692487,-2.165514216414335,0.13088014279715598,0.1825223987085709,0.36052130076883765,0.058722663759081375,0.40030309599145847,0.18107652328156462,0.39639959612795417
		2017-04-01,0.6850325908306781,-0.3571166893847557,0.15306954041840748,0.18883097277365085,0.3397626776352943,-0.2770220332789774,0.4832369376770785,0.18049210548551856,0.2446046301719755
		2017-07-01,0.5845836286105853,-0.1544201862696873,0.07731025253227151,0.23503703487747346,0.3382843746317905,0.01412482993187416,0.40607378562103186,0.5873511801969709,0.20652890002644855
		2017-10-01,0.707893995428579,0.20726744810168232,0.1616835579104921,0.2816104140369857,0.33898918708853093,-0.22275471066403169,0.3923236680543451,0.02509155778812185,0.49122219043205484
		2018-01-01,0.3038728775301882,-0.18656368764448436,0.19703161464789432,0.2129154191675153,0.33446895162064366,0.7374029464846423,0.4922526595569067,0.30577552697762306,0.553671778252306
		2018-04-01,0.6973429323607467,-0.3219819924656799,0.11048819529217371,0.31092452106324237,0.16749024413258326,0.5664932180649842,0.518729244669268,0.23183342224937192,0.404013382421273
		2018-07-01,0.7607990707120177,0.20522021229839812,0.11556110836931932,0.2762324615334555,0.1637822181164843,-0.20542267308234594,0.43463229893954325,0.8015500404902322,0.49925827547359253
		2018-10-01,0.45158996934634005,0.04815653822618971,0.13314839284172836,0.3176102896603116,0.16320292702758346,-0.19172910810643726,0.443664749312209,0.024925054256663772,0.510603771570343
		2019-01-01,0,0.5695618661667696,0.16923249300330387,0.4167126283270676,0.16136098737439816,0.4086110149869905,0.5030208313716722,0.38499486705140085,0.35298187217568927
		2019-04-01,0.9168094458132909,1.760978731349752,0.12408208873660366,0.45786431023759605,-0.09433955095219206,0.9072507238170343,0.6462860183581207,0.335705713368547,0.1301583461658761
		2019-07-01,0.5092698936317547,3.0905469020502303,0.12965641116260027,0.26099906154945773,-0.08761396712765314,0.9034797333694977,0.4693262714115153,0.28371467447842147,0.2705339518880051
		2019-10-01,0.8836984003335717,1.6634560204748847,0.14791413076104756,0.20265141450563248,-0.08199785764464973,-0.6605886805124692,0.5666264399746321,0.3161009424435147,0.33767381496750215
		2020-01-01,0.3107401913034678,-0.09124275191340893,0.17116263348854746,0.24766902627659054,-0.07560536183856922,0.2870389859802828,0.639849430970442,0.5818403152930246,0.3495369157394469
		2020-04-01,0.6785394437814125,-0.3067771904277886,0.13897991504197196,0.21198391180206366,0.22753220175233665,0.2253806392140626,0.6359681559975154,1.275848181906521,0.003020042857615753
		2020-07-01,1.1287510386654402,1.0392500686911363,0.08280641917062806,-0.6781968404856091,0.2331352877343615,-0.29734094878692036,0.5202316043115323,-0.11189146587767143,-0.7617876638354939
		2020-10-01,1.0609804381898846,0.9670177066599874,0.14256153178139622,0.09358740148940185,0.233768166907282,0.2366506008462887,0.7564290030289376,0.47157078647319517,0.32804239730453855
		2021-01-01,0.4895310714707987,-0.015841225942592314,0.15892286909074718,0.8744909175897255,0.23567514585121452,0.9926290215042242,0.7823524984217046,1.4437915182325822,1.2381364163659472
		2021-04-01,1.343916125138135,-0.44654702587815115,0.14938278221901657,0.443265736856515,0.6553130959312551,0.008160541135456148,0.7588276013827304,0.6696838919145707,1.5919768887204375
		2021-07-01,1.5484674350100789,-0.037734125019406484,0.12396021682813377,0.7514996408332991,0.6831904939595305,-0.34036852964286873,0.6486097666556866,1.7130373356181208,1.1613453201872046
		2021-10-01,1.019770567893063,-0.014495378652875916,0.14272588311582685,0.8110300643348525,0.6829824757334656,-0.12079978434843484,0.6662229636777341,-0.12125118663296065,0.8613277228474897
		2022-01-01,0.3564973096828724,0.9017412415346696,0.18886414231181403,1.0038373924052169,0.6861147616618053,1.7687962720949892,0.6972023429150419,-0.13101425547038914,1.256959185176387
		2022-04-01,0.5051945761626284,7.8611820479375645,0.1803025758538415,1.2496838563488195,0.6511936337997608,-0.21354315988252923,0.722817024736067,0.2510826537764099,2.0588959653429693
		2022-07-01,-0.0386230196421494,5.56454803841646,0.16255050108736768,1.3241108838290303,0.6636191810255738,1.651448202576545,0.48592017852485103,-0.4544605686917542,0.8062329194547565
		2022-10-01,-1.0822848040602904,4.9628886988103185,0.1987531920354759,1.0536644540774176,0.6818847784185652,3.354916897782436,0.36525767841723,-0.49357910341969835,1.0942409606144394
		2023-01-01,-0.45398924722256623,2.705915669836387,0.24661528316566464,0.9726520331971963,0.6874766397633975,0.7909467631815984,0.29924994242264247,-0.32318033563056525,0.7455051532621131
		2023-04-01,-0.15388921278872997,1.6445639172987354,0.21252449296075546,0.7711347248374688,0.6815790089798672,-0.2634443331525068,0.18411382614428426,-0.11720740004545788,0.18699309120100374
		2023-07-01,-0.12305638015697949,0.9507981346886201,0.1780563454813104,0.5362388972481087,0.6713022342528534,-0.16580829058527552,-9.592243121152197e-4,0.008789150139028038,0.3640171626301107
		2023-10-01,-0.09027396544050659,0.46002579149331496,0.19631253945674154,0.4544159869099396,0.6619889105535738,0.7532683576065102,0.03699868022070626,0.06728956724843607,0.38900860411162874
		2024-01-01,-0.018898768145621928,-2.4230939391753283,0.27673250350431094,0.38276473086112606,0.6559026248462332,-1.9992825610299618,0.17899150279209233,0.061160025617813446,0.3154140181514455
		2024-04-01,0.07522368423511633,0.45614170967309947,0.22858439239949885,0.37705825792374326,0.6457326952903624,-1.3483706074573103,0.12799104181236462,0.040195049926630456,0.38280244013380293
		2024-07-01,0.04907838025414933,-0.7049140829678403,0.15734181142397327,0.283837515212928,0.6297443942400627,-1.1959901641637918,0.04931598889463506,-0,0.35790555190434575
		2024-10-01,0.0072120278800220285,-2.104102046438755,0.03409067931089298,0.06641174026440126,0.10641670949913555,0.08714223848922951,0.015680062098917258,-0,0.060429555312476166

00_original_index/05_output/loadings_rolling_pca.csv

0 → 100644

+65 −0

Original line number	Diff line number	Diff line
		date,r_index_house_price_d,r_interest_new_avg_d,r_actual_rent_d,r_maintenance_repair_aprtm_d,r_disp_income_bw,r_volume_new_overall_d,r_volume_existing_overall_d,r_houseprice_income_ratio_d,r_construction_price_index_bw
		2009-01-01,0.08811382145348208,-0.014166805240012792,-0.5385720631195884,-0.4906475031838792,0.39626296315946874,0.11579753581707836,0.24387838431017503,0.03896223577711581,-0.47938741026540066
		2009-04-01,0.00749174476484913,0.09845816374442329,-0.543179336486518,-0.5047424330578846,0.401367115896068,0.2044488690837828,0.2470002946137233,0.10263765415389678,-0.4074341824828657
		2009-07-01,-0.017810342534042616,0.13143773577261295,-0.5477834743907887,-0.5110537457824074,0.38618063796064006,0.2351910930902258,0.2249861801260583,0.08789324331357337,-0.3979571692372923
		2009-10-01,-0.08683853282030696,0.11858689737828593,-0.5595319559381535,-0.5221433336394825,0.40666735306436874,0.11889297265459613,0.22354756682510826,0.06476638635623232,-0.3987536482310639
		2010-01-01,0.050888809909423655,0.09204721375959836,-0.5445990339390331,-0.5070560392401758,0.42248142020596285,0.06888543685826863,0.22472203370022056,0.16232902626148965,-0.4185179156739481
		2010-04-01,-0.09148791133720593,0.1632304956031571,-0.5460421193943248,-0.4919252986367507,0.4320836064425117,0.1062370025004701,0.22549438347740636,0.13999690232650958,-0.39547930223372557
		2010-07-01,-0.04506097493101837,0.1971233030531716,-0.5422761604346307,-0.4961518529137591,0.42455967786221527,0.139668072219077,0.19486796772835394,0.1437875841703813,-0.400593724282093
		2010-10-01,-0.09394389905697224,0.21830299152028937,-0.536678471958457,-0.4930689200396523,0.43334957106724825,0.13401008357072314,0.19925857310972497,0.12874050339179574,-0.38774857335190216
		2011-01-01,-0.16470367514905676,0.04128321283396774,-0.5252146901960946,-0.46002506901774826,0.47640635313629653,0.008204185795471709,0.2518810549291545,0.142203688340494,-0.41593098468962314
		2011-04-01,-0.199493125900584,-0.03673930048787499,-0.5035021153719366,-0.42768671470654457,0.4782539870647908,-0.01996744486662216,0.29799583024518195,0.1909272390120247,-0.40992939631044095
		2011-07-01,-0.20831219812813107,0.03811708641771849,-0.5081234540901397,-0.4403373524227681,0.47331581059235134,0.02949897100688998,0.2886099899144305,0.17922026583338319,-0.4034265874826639
		2011-10-01,-0.20211006714400392,0.16174033832130963,-0.5105853816189219,-0.43955443637786323,0.4673359784413635,0.09199048281888518,0.304599135715689,0.12033193219123593,-0.38073675446131355
		2012-01-01,-0.33729233282575644,0.16647868301144297,-0.4820965665218716,-0.39954167749018465,0.4389957512386456,-0.020692690408773237,0.3189163577141555,0.07860864229943618,-0.4067378269993175
		2012-04-01,-0.33398744369888084,0.2166446523704174,-0.47601785845337136,-0.4061954465712122,0.42166967070918965,-0.006886298631014933,0.3396915583653163,-0.016664166862187232,-0.39548572424598166
		2012-07-01,-0.3393680500224428,0.2661823555277133,-0.4631409320232376,-0.3989845446855878,0.40049740459451805,0.07550016541492388,0.3689985043036756,-0.004283861003837348,-0.3714988515571584
		2012-10-01,-0.3491013346979332,0.2711220180468682,-0.4578540419005498,-0.3931804526884919,0.38253643064979814,0.03107591999106193,0.37784335848573675,-0.08233318291583044,-0.37888748625800067
		2013-01-01,-0.3134842868222845,0.27290509549096353,-0.4638163454983472,-0.4022904256110147,0.38245258802083404,0.0344220691367463,0.3899922726472193,-0.08543474921751293,-0.3787338007822485
		2013-04-01,-0.32277779802137363,0.27727611306283995,-0.4605185389286985,-0.3739225578001864,0.4000355980713174,0.05665771313505309,0.39610532913931096,-0.07564799156474683,-0.37573450695679594
		2013-07-01,-0.3106369420855871,0.2439158805985795,-0.45486913374177246,-0.36908573894595176,0.401537404675929,0.0770680803455475,0.39669085447691643,-0.0867559230342911,-0.41087409423091925
		2013-10-01,-0.2970889684570498,0.2003662226018318,-0.4561035394453323,-0.36984245728761234,0.40984921190282547,-0.013615145124258179,0.415917297597679,-0.09705137662674797,-0.41977341856539085
		2014-01-01,-0.29620177987914675,0.19097486686297804,-0.4402176237224058,-0.4005697213494519,0.4198641063736936,-0.011124250856920256,0.41392263995819345,-0.09384666125958582,-0.4061978378175762
		2014-04-01,-0.30325107741720947,0.21246180415355598,-0.4238413664548204,-0.39307912243016047,0.4025862983436349,0.0017168317974868646,0.40648943133025967,-0.20573700493620167,-0.39888095630600784
		2014-07-01,-0.3013923386786017,0.2369631986844627,-0.41670060309869306,-0.3872903912046244,0.40101820904154717,0.03302810462233472,0.40392496607502654,-0.22206178957660883,-0.39370621613877743
		2014-10-01,-0.2787424183335459,0.26681680890793524,-0.4128616651390528,-0.3875201408502885,0.39899363825630846,0.08272237586693636,0.39864180615831357,-0.2233604592156432,-0.3945132968652289
		2015-01-01,-0.3036059608498864,0.29520743744577027,-0.3975180261668376,-0.35829095947879624,0.3804923247732866,0.15806685782355645,0.38668167790782415,-0.26906012101275983,-0.3776339327161955
		2015-04-01,-0.30720491211010015,0.2993253624565788,-0.40151509553067216,-0.36344362976261174,0.38712920886991753,0.17568756164438865,0.39256466522231376,-0.21086595812897896,-0.37870465148460686
		2015-07-01,-0.3167900112652417,0.23392323870967124,-0.40881056971373003,-0.37096275722634525,0.39584819201287647,0.15979411946928693,0.3983778272795857,-0.22278184828405442,-0.38680481003449163
		2015-10-01,-0.33092268141175235,0.22499425246965687,-0.40808707147533685,-0.37815056554084153,0.39818338744532267,0.08842582232135249,0.3969682634227418,-0.23236449081190091,-0.3903699044661622
		2016-01-01,-0.33348213004256433,0.2709107832059897,-0.39865847556576,-0.36150261905074577,0.3875468060816925,0.1191448429369995,0.3910668611877564,-0.24989750348225256,-0.38211807088322536
		2016-04-01,-0.33123469242807274,0.29221713308029773,-0.38288870025287675,-0.3583355115928916,0.3827154414435078,0.09245857856848462,0.3868024372283308,-0.27927887188194855,-0.38373443736639107
		2016-07-01,-0.3406306626049465,0.2960143387950013,-0.3767474420561351,-0.3612536919130327,0.37874462096684625,0.10203511782652211,0.38584711987936077,-0.27747763477151477,-0.3797010758552725
		2016-10-01,-0.34410845429859416,0.2924228479221731,-0.37609798884018425,-0.3614187750595553,0.37818478965433816,0.09390030820829073,0.38700909745338913,-0.27939532104573356,-0.3799029238854232
		2017-01-01,-0.3454719821432115,0.2228726506416534,-0.3837089331535659,-0.37259719927643664,0.38556278185826093,0.11605868060389263,0.3937875370733834,-0.2893334717550261,-0.37947979462624387
		2017-04-01,-0.34873265080333654,0.1946231350922889,-0.3860835295167416,-0.3780519470769461,0.38941908592184427,0.08262359406951465,0.3979593673274728,-0.29020458556257633,-0.384004381218957
		2017-07-01,-0.3508958991556273,0.1706331412651888,-0.38198076838522305,-0.38092091210276136,0.3911075935500862,0.062462451273280095,0.39913913759395114,-0.3043452565250647,-0.3846317153904711
		2017-10-01,-0.3574747859669827,0.1632949471330527,-0.3857047080223861,-0.3845644204798294,0.3953123755325346,0.034740183111494786,0.4014258378322211,-0.2889292697715615,-0.38312797022304185
		2018-01-01,-0.3579601000818914,0.14698356056329598,-0.38692318226267625,-0.3854877924392437,0.39338581097918157,0.08934206168367405,0.39938720650456155,-0.29507074296590624,-0.3776754271089582
		2018-04-01,-0.3621523462810381,0.12073609168000343,-0.38475754389432526,-0.38992636815669235,0.38802205399727735,0.10561826945734777,0.3977778378981319,-0.30099557186182196,-0.3790061453944332
		2018-07-01,-0.3708004589193951,0.12894397826138837,-0.38304508713326235,-0.39112692166892177,0.38106955227991135,0.07029818962681336,0.39685987093836755,-0.3072865195951838,-0.37960250404653406
		2018-10-01,-0.37285822681398606,0.13483816371017454,-0.38566512267674624,-0.38808799330800414,0.3813537564399763,0.09028112041692402,0.39669924302713533,-0.3002222612770893,-0.3773068659142687
		2019-01-01,-0.3574701488086401,0.14874596128491668,-0.3895945173766496,-0.3825293428318301,0.37866333685510406,0.10586827484349033,0.3969016341153498,-0.3112002151401252,-0.3781622009820447
		2019-04-01,-0.361547351737849,0.17681496908802952,-0.39163371324434265,-0.3810630116880539,0.34801999920576343,0.13432069603753366,0.3987847189137979,-0.31672246358763917,-0.375408650299986
		2019-07-01,-0.36412203832275475,0.19317656382564252,-0.3920869710695975,-0.3829849188897236,0.322333080763588,0.14979175411627083,0.3996038618349917,-0.31943483131522415,-0.3763379771031618
		2019-10-01,-0.37384402880163775,0.20076007080904879,-0.39494029670858644,-0.38613258413339085,0.3008513518376333,0.0984160615500683,0.4016028051436286,-0.3292692862222535,-0.3807354627326005
		2020-01-01,-0.37641723041712843,0.17472947286057805,-0.3994596159401865,-0.3957987386982753,0.2766411361400144,0.08185055958090798,0.40588539855435607,-0.33507870770801507,-0.3889788223146455
		2020-04-01,-0.38166838447904267,0.1487816661223319,-0.40245821891050587,-0.3967299879722204,0.290489520805215,0.08119442246044349,0.4080550020812928,-0.33910127535093443,-0.37463409239609186
		2020-07-01,-0.38058144690425905,0.18874941415699953,-0.43090891603801773,-0.3301497097518286,0.29997432466825447,0.08923698935029593,0.42889859885868764,-0.3706401992316295,-0.32492167523802806
		2020-10-01,-0.3774189364392714,0.20202574568370935,-0.42320539840393145,-0.32080608351315315,0.303126341337498,0.14124012129868693,0.422730126757517,-0.369345866247661,-0.32828297607540535
		2021-01-01,-0.3556387081762931,0.16485589835225656,-0.4072646305487904,-0.3432826921087577,0.307955877125535,0.17916756100112574,0.4152266185656561,-0.3792271202280372,-0.3456471689085863
		2021-04-01,-0.36415994032626864,0.06543840258690903,-0.39978396859893006,-0.34932809239915213,0.3321183674674496,0.17921413535683842,0.41071262083074506,-0.37621847666311514,-0.3586119075368025
		2021-07-01,-0.3749661702593969,0.028790725260524397,-0.38672746940234565,-0.3601088373773712,0.35307899716895147,0.10109124908845343,0.40195053287955795,-0.3819433024106402,-0.37014297093116266
		2021-10-01,-0.3802567695918295,0.007030009578096741,-0.3906413243520568,-0.36579235138469335,0.35980152528454784,0.07699859487337969,0.4042409253952231,-0.35878191977104174,-0.3760712254258543
		2022-01-01,-0.3638471559002858,-0.07110826229989164,-0.39124972034887534,-0.3727460805566629,0.36831299246697036,0.15454594141377728,0.4015350283474248,-0.3218579098543553,-0.3823363393392115
		2022-04-01,-0.3498279365619959,-0.18801312361613953,-0.3878560018764241,-0.3757644156788176,0.372638976506514,0.12715070693257152,0.3956601855212563,-0.3042418601770879,-0.3827572401547308
		2022-07-01,-0.3436694514659544,-0.22570895580636285,-0.3950116953336399,-0.3779210727497415,0.3863857281365544,-0.052847378666858486,0.4008974232633641,-0.25509069843218846,-0.3926976113676012
		2022-10-01,-0.225293921670547,-0.27365194107004726,-0.4070268281224685,-0.4027352540765563,0.403839704785105,-0.11912598306355436,0.40592406078566234,-0.1867698541006768,-0.41177167434400574
		2023-01-01,-0.14762945241441597,-0.3056252251806224,-0.4095437329826149,-0.41877804041073674,0.4140263579322298,-0.16662204906350153,0.39864098348400623,-0.09196502126431486,-0.4185029498241721
		2023-04-01,-0.11186103735314158,-0.3187005898979141,-0.4095396868277895,-0.4258505722816099,0.4172905092456644,-0.18044721760793678,0.3938068337815884,-0.033575263648289645,-0.4170634114979852
		2023-07-01,-0.08049335574640439,-0.32881741579916135,-0.4101895405510436,-0.43113632789238976,0.41771181717774386,-0.1839333154718405,0.385402695867733,0.004428234121684736,-0.417608022374911
		2023-10-01,-0.046022682296379014,-0.33459584184572727,-0.4096582404319908,-0.43450605217159427,0.4185367140528945,-0.1952382772231402,0.3759654729757047,0.033229558480796784,-0.4166136647738386
		2024-01-01,-0.04601843575700209,-0.32669567085981127,-0.40433162965365804,-0.4403497735104893,0.42124787386567725,-0.17091613965824418,0.3824843536782932,0.04541962685022975,-0.4227776378888422
		2024-04-01,-0.05521333017980999,-0.33183786873041654,-0.40116784086274726,-0.4398963695892874,0.42117377864819433,-0.15105495606202587,0.38779529311637584,0.05020334917566837,-0.4234148643153994
		2024-07-01,-0.06069326619601114,-0.34069631939651457,-0.4003796645668202,-0.4390392143421229,0.41704310773316605,-0.1364847344056858,0.39058982233471606,0.04791087829134557,-0.42399780642793344
		2024-10-01,-0.05376565978381687,-0.3445943659664044,-0.3996395553665474,-0.437560457621737,0.41822023292451127,-0.1332652664171993,0.3920624543215065,0.05212590577781768,-0.4220132413586874

00_original_index/05_output/reduced/00_summary.pdf

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00_original_index/05_output/reduced/01_housing_cost_index.pdf

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00_original_index/05_output/reduced/02_affordability_index.pdf

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00_original_index/05_output/reduced/03_quarterly_changes.pdf

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00_original_index/05_output/reduced/04_PC1_variance.pdf

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00_original_index/05_output/reduced/05_loadings_overtime.pdf

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00_original_index/05_output/reduced/06_cumulative_contributions.pdf

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00_original_index/05_output/reduced/contributions_reduced.csv

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Original line number	Diff line number	Diff line
		date,r_index_house_price_d,r_interest_new_avg_d,r_actual_rent_d,r_maintenance_repair_aprtm_d,r_disp_income_bw,r_volume_new_overall_d,r_volume_existing_overall_d,r_houseprice_income_ratio_d
		2009-01-01,0,1.5222976361174583,0.17805745431610023,1.2941373326273924,-0.24167354771796398,1.7175381336561033,-0.03892194721247302,-0.01417371688697703
		2009-04-01,0.21994579387597976,1.7363020838108765,0.1361109234903266,0.4730731177800112,0.26147350429031707,2.6573152747041933,0.014832494908883142,0.2248134573576523
		2009-07-01,-0.03910402979227275,0.3304497949017899,0.0825091168661036,-0.06390711083179966,0.24628654598252084,-1.296465302360688,-0.0035116069008476855,-0.02644251225599373
		2009-10-01,0.3822533223508743,0.7255117102428043,0.12979658202774558,0.22222541808556348,0.26833309904328384,-2.374082711932518,0.06291211255908663,0.0048688478803428645
		2010-01-01,-0.10572988009974582,0.6631131536436362,0.20976884727938666,0.1969525401048705,0.28867619760154845,-0.9985016993936445,0.04253137273841299,0.08669461178802175
		2010-04-01,0.3620821578546915,1.1940749865505418,0.21819241691146554,0.11655375499350532,0.45368213505792937,0.8947423843806199,0.027115106763200204,0.03454085029150314
		2010-07-01,0,1.9234742867669825,0.10279642059749212,0.1848787270232977,0.4446402828375988,2.212900036432913,0.0021418317138326465,-0.017963291564631386
		2010-10-01,-0.14020205531426586,0.34288386684773253,0.16235006083334966,0.46107109218663056,0.44225754272641055,0.5551614679472525,0.052822861537147936,0.06534465225100224
		2011-01-01,0.7867764571761512,-1.0305921194543264,0.21857004238892183,0.3386379740284419,0.5110337362430113,-0.1303550307669124,0.11909451892781947,-0
		2011-04-01,0.3639187735899562,-0.04759106326355418,0.16359068270279573,0.2828118055436354,0.3360963308650716,0.07628292985566439,0.09555596020397683,0.16604645845776334
		2011-07-01,-0.1436429388013495,0.4125451826527933,0.11597355304523933,0.40813800663143307,0.32922336788095874,-0.0025303105514151852,0.029257805311143262,-0.1074486224312544
		2011-10-01,0.20189619827198366,2.1955474061576683,0.17502334663336866,0.26630152737096435,0.3149236861384456,0.5996971908216956,0.12073021473281823,0.08145870095703321
		2012-01-01,0.30722221484378776,0.966163730210429,0.16261191382093862,0.3771132362369964,0.29834112924878503,0.03045239280159274,0.19013183984429008,-0.032097863841227293
		2012-04-01,0.46912413311264956,1.6919118219140041,0.11789077945001705,0.3335381571736324,0.1706363399772851,0.039134899824163676,0.08864816550203442,0.018477818737991904
		2012-07-01,0.5435905987192815,2.5761211649917026,0.14015463236845552,0.26691546714919545,0.15848301947539112,0.9470776125079956,0.15703267567847293,-1.53122507118047e-5
		2012-10-01,0.5068703371161764,1.3161058527628111,0.12452067560495,0.20391046058334766,0.1519174213553436,-0.345161219578575,0.32898472823746444,0.10107699287125968
		2013-01-01,-0.11316191852222807,0.4675228530666352,0.22809758778820086,0.3252647274175244,0.15072019857004218,-0.07497251788948772,0.3268941633668047,0.08176818581900036
		2013-04-01,0.6971816875286742,0.8863104396655369,0.11386721654066846,-0.07315983533256933,0.3712906789171108,0.6359988167810688,0.21526964660916695,0
		2013-07-01,-0.07322206618969143,-0.6642091258378119,0.1797380506834417,0.23942831168301526,0.370762073451806,0.5882044941565796,0.20083487438745587,0.033344411611964275
		2013-10-01,0.035808049247325856,-0.7632541406031219,0.1648608769517887,0.11655616392816244,0.3818415027184676,-0.23685220843450136,0.2389738836806121,0
		2014-01-01,0.2820858035536831,0.42385490032522444,0.23917888120017547,0.13925742073219374,0.38928002926693106,0.04045751548877701,0.23560115451499886,0
		2014-04-01,0.6671575476941325,1.4768952026527613,0.1885715688419312,0.19455789549368482,0.3226372956773175,0.06700762242353342,0.25606781052116057,0.21251568580654548
		2014-07-01,0.17113854808201556,2.677200660654131,0.11090350650118797,0.1263778913511608,0.31896385931867766,0.2573357819798596,0.23594730786195323,0.17515720703087428
		2014-10-01,0,2.7942860647936687,0.16034332730489165,0.2850170328436782,0.3152731830108364,0.2633815300325484,0.4414502323905804,0.04990916980774159
		2015-01-01,0.5450065317307053,4.0649144938821475,0.1767196588230057,0.15908657256243897,0.2942124593134035,1.9050923007471494,0.5100691961535108,0.8073747417475078
		2015-04-01,0.7166038282174749,1.8614938174995503,0.12738671749323377,0.1282176967830805,0.31215413793485375,2.1623495266118278,0.33429104138903454,-0.28708499492424183
		2015-07-01,0.17488478004448035,-2.75945806376154,0.09081745993261865,0.16092817696759362,0.31843594484535426,0.05249228223825083,0.3662918728683849,0.2791057247096147
		2015-10-01,0.5055881246429127,0.25770065524605995,0.09440902249348046,0.18409003903391358,0.320319834279455,-1.2736706598066654,0.4079477920085464,0.07234999208771845
		2016-01-01,0.7527646480573129,1.3929474470899708,0.17729077119150635,0.1185199739902681,0.3085305347082361,0.47843995148255036,0.389239458369534,0.2790116546521629
		2016-04-01,1.0428195548873975,1.8441358407765882,0.06353903362815923,0.16784479963122184,0.3946046142929822,-0.48965893037091535,0.40048139327201404,0.4978989970391481
		2016-07-01,0.6589828777147522,2.362216306473968,0.09742373770524564,0.1856675940707963,0.3865467937874265,0.3459276491802219,0.3580387478048024,0.18970515254113335
		2016-10-01,0.5504648368187535,0.9754905749653159,0.1711908625587772,0.17550413656195382,0.38206796365451245,0.14191642786401684,0.37397628888500056,0
		2017-01-01,0.17172573656471257,-2.5061367351692128,0.14000559661311693,0.1949275260074484,0.3838725978919895,0.07152893486511362,0.4261228515261272,0.19590673221437604
		2017-04-01,0.7542940593325772,-0.4168112978973665,0.16443474448251655,0.20208352140418773,0.36373412761927104,-0.3486694529983476,0.5175501357236983,0.19566002029111426
		2017-07-01,0.6433210971756894,-0.18024812952957567,0.08303449351636692,0.25182178799274807,0.3630585685154427,0.018124048129685804,0.4360918101272868,0.6400260078209139
		2017-10-01,0.7744780680525685,0.24327199362995164,0.17338622800726114,0.30060280808800605,0.36392449438651264,-0.34463227738974217,0.42157521866423636,0.027687874775867007
		2018-01-01,0.333276440144065,-0.22155384964640384,0.2101504351321969,0.22677100475905793,0.3590967171709549,0.8671964021140086,0.5270511240851204,0.33457490978516463
		2018-04-01,0.7622245736516572,-0.38945303687480015,0.11813438228486937,0.33208267042636636,0.18022551331047937,0.6453937723416107,0.5558395580754206,0.2540785115168227
		2018-07-01,0.8299088312384035,0.24525455951135375,0.12400790144046045,0.2954959603455593,0.1770690788991345,-0.24205561010538437,0.4665672612259953,0.8672730796056572
		2018-10-01,0.49119183541560363,0.057147794361657095,0.1428019952471704,0.3378519100349323,0.17691091421747931,-0.22228601663434563,0.47491965002706266,0.02706120882771702
		2019-01-01,0,0.6699528850606491,0.1813741858159843,0.44372710326751114,0.17480270574839565,0.46950940212531506,0.538629663875729,0.4180540588166592
		2019-04-01,0.996584824652341,2.0757220696564787,0.13212934994086845,0.4905134257082373,-0.10013882242456035,1.0546728075161804,0.6936370890522053,0.3633289849536809
		2019-07-01,0.5536669223648679,3.5879774056877927,0.13817623286329786,0.279995813124465,-0.09241066571700937,1.044276744840269,0.5043527303034712,0.30718398975411654
		2019-10-01,0.9616264879638019,1.9253095114796936,0.15802280702933078,0.2180439990816725,-0.08677997043369585,-0.7856532314078559,0.6102766701187035,0.34307314348257173
		2020-01-01,0.34040000436476653,-0.10696374704913374,0.18363923630455653,0.26833358414834413,-0.08021170685273198,0.33956432301252587,0.6925332901210182,0.6307357200069441
		2020-04-01,0.7347652225734084,-0.3456839786127396,0.14764460474781216,0.22674600430133404,0.24203331076859905,0.2650031882350244,0.6840438222181476,1.412651027556985
		2020-07-01,1.2497122302313424,1.1922538140660333,0.08668037808756068,-0.631732757919135,0.2535914650652614,-0.2861345503528797,0.5569824592362046,-0.1180139318638307
		2020-10-01,1.169521200134576,1.100060678557509,0.1495911172745453,0.08781616723582078,0.2537115197167051,0.23957419405285366,0.8101921782042701,0.49876402686181365
		2021-01-01,0.5488388619685003,-0.018791496988945475,0.1698748406135786,0.8442584656008617,0.2565665315202348,0.9987982992296525,0.8450199909402701,1.5104011428932242
		2021-04-01,1.4751028253557732,-0.6629259652677132,0.1619760865949255,0.4453450296830081,0.6891086169196209,0.008775880743413206,0.825127842451486,0.7145522137206619
		2021-07-01,1.6989150194047573,-0.07219978117407069,0.13549928458299648,0.768880902846779,0.72406715132773,-0.36985389183766404,0.7098840566078215,1.8363851520449501
		2021-10-01,1.1199696585297167,-0.06346103989110126,0.1562049763150588,0.8364640322181591,0.7253836969563182,-0.13201695792927956,0.7303031734445046,-0.13091679386525393
		2022-01-01,-0.39485905283148354,-0.6828346261185131,-0.2070742347663663,-1.0437139119147534,-0.7318560028650748,-1.8665491990272172,-0.7665977786472554,0.14369162206383954
		2022-04-01,-0.5628054292955026,-7.471353472607112,-0.19752902433820468,-1.3040290770371215,-0.696552237629075,0.2356128109501428,-0.7948986048768506,-0.27864902434947414
		2022-07-01,0.04334355654050857,-5.560044345186919,-0.1786873240887461,-1.3943501402720617,-0.7156750569456019,-1.8882149935618548,-0.5362016936799283,0.5054024800055781
		2022-10-01,1.256977406899335,-5.151388001732106,-0.22033924883611017,-1.1274816214824006,-0.7440103754134147,-3.707224287641734,-0.40758195246587314,0.5597628708384156
		2023-01-01,0.4903179344457756,-2.9349418994697003,-0.27391415453443563,-1.0568938282879188,-0.758090907098234,-0.9511750511847223,-0.33071078472144916,0.3149197327115482
		2023-04-01,0.14403202166145293,-1.8049422448311145,-0.23596820360137938,-0.8399624784136454,-0.7539521846832965,0.32340125125892666,-0.19975496184993172,0.027679979323228434
		2023-07-01,0.09318825218047365,-1.047624722983869,-0.1974601213579928,-0.5836466976771568,-0.742977919107403,0.20636477822986307,0.001025962635848865,-0.08507767737292712
		2023-10-01,0.027020274209961972,-0.5064585442334927,-0.21723047118109853,-0.49265175900546476,-0.7316895214239965,-0.9444914776050035,-0.03886614463385468,-0.16714254418181065
		2024-01-01,0.005147738704139734,2.662463106243684,-0.3088228717913128,-0.4164391516415362,-0.7292604227422058,2.5184903807720804,-0.18862429807690168,-0.13246118580272334
		2024-04-01,-0.03533299976572585,-0.5004504196587324,-0.2559779444891214,-0.4108905401167262,-0.7194309600755744,1.6949396788102253,-0.13553467703361416,-0.08121074058978393
		2024-07-01,-0.02857162937928465,0.7705573447750855,-0.17671437436278056,-0.3099185527822589,-0.7017591368291197,1.5006156226707952,-0.0525923815754595,0
		2024-10-01,-0.0036636177987597607,2.295394664834318,-0.03826716874984516,-0.07241944079262183,-0.1183349261075038,-0.10976865138895497,-0.016704662496054457,0

00_original_index/05_output/reduced/cumulative_contributions_reduced.csv

0 → 100644

+9 −0

Original line number	Diff line number	Diff line
		variable,cumulative_contribution
		r_index_house_price_d,26.97342227110162
		r_interest_new_avg_d,19.997465914684017
		r_volume_existing_overall_d,15.140391597236277
		r_houseprice_income_ratio_d,14.111619591136991
		r_volume_new_overall_d,9.749772501665955
		r_disp_income_bw,6.955998088438982
		r_maintenance_repair_aprtm_d,5.363141863336933
		r_actual_rent_d,5.27103946277205

00_original_index/05_output/reduced/housing_index_reduced.csv

0 → 100644

+65 −0

Original line number	Diff line number	Diff line
		date,r_HCI,pc1_variance,pc2_variance,HCI,HAI
		2009-01-01,4.41726134489964,28.559572369717834,21.748837552058728,104.41726134489964,95.58273865510036
		2009-04-01,5.72386665021824,30.898542135492757,20.344816123027684,110.14112799511788,89.85887200488212
		2009-07-01,-0.7701851043911875,30.848271266221776,19.198138945219153,109.3709428907267,90.6290571092733
		2009-10-01,-0.5781816197428169,30.349263933610278,19.01628983429061,108.79276127098387,91.20723872901613
		2010-01-01,0.3835051436624862,29.753683961154962,19.37385430490119,109.17626641464636,90.82373358535364
		2010-04-01,3.3009837928034567,30.985830032295773,18.632763088021584,112.47725020744981,87.52274979255019
		2010-07-01,4.852868293807485,31.077709281697825,17.934500084263625,117.3301185012573,82.6698814987427
		2010-10-01,1.94168948901526,32.29413785179325,17.940788773525036,119.27180799027256,80.72819200972744
		2011-01-01,0.8131655785431069,31.797307358086762,21.162052356800057,120.08497356881567,79.91502643118433
		2011-04-01,1.4367118779553094,33.26788114654843,21.476754916612812,121.52168544677099,78.47831455322901
		2011-07-01,1.0415160437375486,33.68300437713894,21.850899589721397,122.56320149050853,77.43679850949147
		2011-10-01,3.9555782710839775,34.924660224401826,20.29969504011614,126.5187797615925,73.4812202384075
		2012-01-01,2.2999385931655922,38.58259347506271,19.394429815020313,128.8187183547581,71.18128164524191
		2012-04-01,2.929362115691778,40.410106599766195,19.425505457678895,131.74808047044988,68.25191952955012
		2012-07-01,4.7893598586397825,44.24531769255408,18.62339944256595,136.53744032908966,63.46255967091034
		2012-10-01,2.3882252489527778,45.34485466946527,18.626755081327957,138.92566557804244,61.07433442195756
		2013-01-01,1.392133279616492,44.58244013970057,18.348613217057082,140.31779885765894,59.68220114234106
		2013-04-01,2.8467586507096567,45.845728106247975,17.64038143392921,143.1645575083686,56.8354424916314
		2013-07-01,0.8748810239467594,46.207667973707025,17.342049352824567,144.03943853231533,55.96056146768467
		2013-10-01,-0.06206587251126657,46.8358580899148,19.774265915484797,143.97737265980408,56.022627340195925
		2014-01-01,1.7497157050819836,50.63146879076139,17.92812442551519,145.72708836488607,54.27291163511393
		2014-04-01,3.3854106291110666,54.476792004386695,16.406215590344573,149.11249899399712,50.88750100600288
		2014-07-01,4.07302476277986,56.18554770814808,16.348325946370394,153.185523756777,46.814476243223
		2014-10-01,4.309660540183946,56.86320174062889,15.593064337462643,157.49518429696093,42.50481570303907
		2015-01-01,8.462475954959869,62.53084402835213,15.123572897772855,165.9576602519208,34.0423397480792
		2015-04-01,5.355411771004814,61.832785438023386,14.007537713202844,171.3130720229256,28.68692797707439
		2015-07-01,-1.3165018221552427,59.885603816789704,15.182233404323888,169.99657020077038,30.00342979922962
		2015-10-01,0.5687347999854211,59.96322881019027,16.13855266076564,170.5653050007558,29.434694999244186
		2016-01-01,3.8967444395415414,63.11050699530247,14.779545418642922,174.46204944029733,25.537950559702665
		2016-04-01,3.921665303156596,65.08366057924633,14.234217683906428,178.38371474345394,21.616285256546064
		2016-07-01,4.584508859278347,67.006173626974,13.96182353911207,182.96822360273228,17.03177639726772
		2016-10-01,2.7706110913083304,67.34947584942424,13.857166264977769,185.7388346940406,14.261165305959395
		2017-01-01,-0.9220467594863284,65.34457675306831,14.619760113762483,184.81678793455427,15.18321206544573
		2017-04-01,1.4322758579576511,64.83072907502353,15.717742058285012,186.24906379251195,13.750936207488053
		2017-07-01,2.255229683748558,65.05286456293265,15.908605624400243,188.5042934762605,11.4957065237395
		2017-10-01,1.9602944082146612,64.49701842224822,16.47372812973149,190.46458788447515,9.53541211552485
		2018-01-01,2.6365631835441645,65.54950706681645,15.320318753014966,193.1011510680193,6.8988489319806945
		2018-04-01,2.458525944732426,65.96762898990582,14.779262279821554,195.55967701275176,4.440322987248237
		2018-07-01,2.7635210621611797,66.35238127228071,15.150334723937082,198.3231980749129,1.6768019250870907
		2018-10-01,1.4855992914972769,66.47822614710473,14.66720524838567,199.8087973664102,0.19120263358979628
		2019-01-01,2.8960500047102435,66.39224320040454,14.354663048513574,202.70484737112042,-2.7048473711204224
		2019-04-01,5.706449729055432,65.86889003962283,14.45787361907223,208.4112971001759,-8.4112971001758865
		2019-07-01,6.323219173221271,65.819248145981,15.614087735373772,214.73451627339716,-14.734516273397162
		2019-10-01,3.3439194173142224,64.638407098376,14.793559469694568,218.0784356907114,-18.078435690711387
		2020-01-01,2.2680307040562897,62.49491956640999,15.187277230427545,220.34646639476767,-20.346466394767674
		2020-04-01,3.367203201788571,62.82013468468462,15.506349678714724,223.71366959655623,-23.71366959655623
		2020-07-01,2.303339106550557,56.22417209757621,15.996444911619312,226.0170087031068,-26.017008703106796
		2020-10-01,4.309231082038094,57.864267318860726,15.349112537985473,230.32623978514488,-30.326239785144878
		2021-01-01,5.1549666357773765,59.34308396654768,15.524370344023117,235.48120642092226,-35.48120642092226
		2021-04-01,3.6570625302011757,59.710858115669495,15.28894246084412,239.13826895112342,-39.13826895112342
		2021-07-01,5.4315778938033,60.331596958917835,16.38822377387154,244.56984684492673,-44.56984684492673
		2021-10-01,3.241930745778123,59.82466322884036,16.6903160694095,247.81177759070485,-47.81177759070485
		2022-01-01,-5.549793184106824,60.07425461387934,17.095257263555112,242.26198440659803,-42.26198440659803
		2022-04-01,-11.070204059183197,61.620228571291214,14.931329391162912,231.19178034741483,-31.191780347414834
		2022-07-01,-9.724427517189024,58.8064824631553,22.035473516375472,221.46735283022582,-21.46735283022582
		2022-10-01,-9.541285209833887,53.9767359717352,28.59056266074792,211.9260676203919,-11.926067620391905
		2023-01-01,-5.500488958139137,52.16796372513566,29.523605774620815,206.4255786622528,-6.4255786622528035
		2023-04-01,-3.3394668211357597,51.471844657671284,28.866503648985724,203.08611184111703,-3.086111841117031
		2023-07-01,-2.3562081454531634,50.86942322984028,28.672307527780937,200.72990369566386,-0.7299036956638645
		2023-10-01,-3.0715101880547593,50.59659235291846,28.58143284479845,197.6583935076091,2.341606492390895
		2024-01-01,3.410493295665224,49.037226567411246,27.963919268596793,201.06888680327432,-1.0688868032743244
		2024-04-01,-0.443888602919053,49.113326002376105,27.175076689192597,200.62499820035526,-0.6249982003552645
		2024-07-01,1.0016168925169775,49.25053558895199,26.818731003221657,201.62661509287227,-1.626615092872271
		2024-10-01,1.9362361975005782,49.690263370491415,26.864092450039106,203.56285129037283,-3.5628512903728335

00_original_index/05_output/reduced/loadings_reduced.csv

0 → 100644

+65 −0

Original line number	Diff line number	Diff line
		date,r_index_house_price_d,r_interest_new_avg_d,r_actual_rent_d,r_maintenance_repair_aprtm_d,r_disp_income_bw,r_volume_new_overall_d,r_volume_existing_overall_d,r_houseprice_income_ratio_d
		2009-01-01,-0.07272612952132511,0.11757093809825866,-0.6004476547534037,-0.5377335348569091,0.4391911221524111,0.20440744682743772,0.30686379083756216,-0.04854494585194871
		2009-04-01,-0.13949350006257527,0.25070959095471995,-0.5496578666694861,-0.5116410592596807,0.4119309034850211,0.3159915699159196,0.27109228417521675,0.10371669339282158
		2009-07-01,-0.16228164511574097,0.27790500310783006,-0.5453667015262454,-0.5089853968895317,0.3904679209880998,0.3408444406865288,0.2518883302760756,0.08862642116662345
		2009-10-01,-0.24566631337819433,0.2562958084299495,-0.5649275510113989,-0.5211801680513581,0.4281043342978862,0.1782607452310742,0.2563921140411178,0.04900494988446774
		2010-01-01,-0.07365721840729864,0.22762117447798413,-0.566082654108195,-0.5210939910048135,0.46344691785220166,0.1342217608915937,0.26575368723077086,0.21760318775689813
		2010-04-01,-0.23298125301825034,0.2885269420490053,-0.549068552739022,-0.4821892629607467,0.45552341822491493,0.16623315801910515,0.2519279842044334,0.17287689819845448
		2010-07-01,-0.17772315708713385,0.32135741924808814,-0.5494311977206325,-0.4925342487517397,0.45089130858444304,0.19824268735333406,0.21395296446631998,0.17972271714235455
		2010-10-01,-0.23567895994864152,0.3318151166499065,-0.5352556709737617,-0.4812518245315647,0.452897681369106,0.19134184643542634,0.21883918399275867,0.16319805096310677
		2011-01-01,-0.29057642172701403,0.11759286230682109,-0.5409940404797028,-0.4564596878038397,0.5284389178199757,0.031701827814971384,0.29198593477202106,0.18761338328603364
		2011-04-01,-0.31515015598500506,0.0074742814633622645,-0.5163950992210835,-0.4177604199113072,0.5322330978446752,-0.01629975199988607,0.3469300317622118,0.23566639145215867
		2011-07-01,-0.31206373355577016,0.07989624352594016,-0.5226810971116653,-0.4387722141671254,0.524641503315546,0.025072625099020154,0.33037610237904425,0.21328506443954376
		2011-10-01,-0.2927483271677126,0.21819448266657027,-0.5186696734780172,-0.43595740565242325,0.5050031622673847,0.1063023846365148,0.3393210471180136,0.16169517942306041
		2012-01-01,-0.38468405722056714,0.21735105074199212,-0.5008952544078769,-0.42721959750583877,0.4813952404513482,-0.004195129382114074,0.3582616373134888,0.10608335906261293
		2012-04-01,-0.37764007074823924,0.27214373658618174,-0.4945602075919544,-0.43524488283453894,0.45623733122603977,0.011882143067137165,0.37527320145124443,-0.013198226378339561
		2012-07-01,-0.3752800248853157,0.3180118919846755,-0.47812402976806195,-0.42388223746740683,0.4253273353010818,0.10377385478700488,0.397595550217066,-1.5411779073647158e-4
		2012-10-01,-0.3843711022448233,0.3231533281370552,-0.47905278046680866,-0.4252374660516746,0.4092261481361382,0.05019232744788614,0.40032617148483196,-0.08524059852755406
		2013-01-01,-0.3449549389404189,0.32570199518098064,-0.4865885143185176,-0.4357725226202574,0.4075083440458412,0.05369348639130059,0.4131371518777778,-0.0928971446746159
		2013-04-01,-0.35710061055510245,0.32992936355105806,-0.48430697674043227,-0.4017410344327258,0.42231534788593594,0.09618516699806598,0.41654979982823315,-0.08100053946749924
		2013-07-01,-0.34048247655975517,0.30146494693974324,-0.4962773451428437,-0.4116725673131898,0.4254217431552632,0.11396935693334102,0.4196361003717033,-0.08577839085608678
		2013-10-01,-0.33283578565056426,0.255976473856217,-0.4995788099880678,-0.4135141542625861,0.4419529983912208,0.017292968597839437,0.44836324687884654,-0.08045085926362144
		2014-01-01,-0.3293331621786915,0.2383414576241718,-0.47935612587162385,-0.43808129332951506,0.4544553611741171,0.013796388527947567,0.44695655282757363,-0.08090319610025742
		2014-04-01,-0.3326897860386703,0.25524312043443687,-0.4572519038587815,-0.41874308062750515,0.4282482803274444,0.01873148605509764,0.4429571081486664,-0.2445095637145236
		2014-07-01,-0.3284141305921418,0.27977711615246503,-0.4477671888325256,-0.4101519900535104,0.42656204749042453,0.05331581526459402,0.4383759522662005,-0.2611083716067541
		2014-10-01,-0.30427020612168815,0.3089636635993922,-0.4433969740355034,-0.4106186483516925,0.4247791173461642,0.11205063152673686,0.43054049242838177,-0.2615239704204864
		2015-01-01,-0.3304027182271235,0.33426612599610905,-0.42048260111483604,-0.3724531366850383,0.3993453702247233,0.19503301263024908,0.4148718386168315,-0.30649633067949816
		2015-04-01,-0.33730297229647926,0.33888681427736145,-0.42572960964354284,-0.3779410867414905,0.40837870447755037,0.21609189453171906,0.4218331127030809,-0.23640054629479937
		2015-07-01,-0.3502934868326761,0.2703325127147046,-0.4360073123006296,-0.38775745036075704,0.41978131465262214,0.2028003407985262,0.429508606191737,-0.24886666271281896
		2015-10-01,-0.36510101844229814,0.25984603093500513,-0.4381203045485349,-0.3992989599235832,0.4254679840060902,0.12141717592191517,0.429536364136736,-0.25985688704957965
		2016-01-01,-0.36866263917041814,0.3035576890695071,-0.4263820550307346,-0.38055696610143896,0.41289405020694114,0.15111009492365263,0.41991879025387996,-0.2750777684468691
		2016-04-01,-0.36635253413854024,0.32205948737100887,-0.4115466921156646,-0.3811511742438486,0.41017526411600375,0.11705747788601861,0.416006709046474,-0.3039882029165538
		2016-07-01,-0.3740498167251623,0.3255943910586234,-0.4041481739604532,-0.3851052180629976,0.4056649886335841,0.12624699053715158,0.4137573649596695,-0.3012236858930199
		2016-10-01,-0.3770617164731816,0.3235131960644718,-0.40335212536180554,-0.3858840887245248,0.4047853485804111,0.1182909208478008,0.41452613503873137,-0.30313094524853723
		2017-01-01,-0.380028408361723,0.2579291942781283,-0.4104625572972324,-0.3979207525550096,0.41053603880480155,0.14136882208724802,0.41918703570741594,-0.3130299496839216
		2017-04-01,-0.3839919009944989,0.22715578394957603,-0.41474970364096714,-0.40458441545284113,0.41689396987893884,0.10399289546750069,0.4262172622045821,-0.31459234711129147
		2017-07-01,-0.38615302206764646,0.19917282378543277,-0.4102635626836147,-0.4081237036518597,0.4197502861442239,0.08014768876051687,0.4286445349822039,-0.3316395473448199
		2017-10-01,-0.39109864386630017,0.1916610046709638,-0.41362204860475643,-0.41050024759308357,0.4243906940690624,0.05374785739417509,0.4313560438524214,-0.31882585800650265
		2018-01-01,-0.39259728883521094,0.1745504395238423,-0.41268542239043526,-0.4105736181794382,0.42235176873601027,0.10506754118474838,0.4276208001048104,-0.3228618986740696
		2018-04-01,-0.3958474445371032,0.146036233905794,-0.41138417237428837,-0.41646052606057055,0.4175256548201634,0.1203286662214744,0.4262351889769847,-0.3298769699803875
		2018-07-01,-0.40448337456098565,0.1540983621250509,-0.4110432833567843,-0.41840276372283824,0.4119838856420899,0.08283443557664753,0.42601947330189527,-0.33248245612666383
		2018-10-01,-0.4055557678654041,0.16001365412976876,-0.41362684024995716,-0.4128212279928456,0.41338499817876156,0.10466971255936253,0.42464555941511056,-0.3259522416075248
		2019-01-01,-0.3889010112225675,0.17496393600685844,-0.41754622373956074,-0.4073277977944285,0.41020680975636137,0.12164662381259654,0.42499829120857696,-0.3379227209971539
		2019-04-01,-0.3930070810031341,0.20841747094829421,-0.41703285681907243,-0.40823562591460827,0.3694135974669042,0.1561468973002469,0.4280022524525546,-0.3427837139041902
		2019-07-01,-0.39586539641229546,0.22426876804717266,-0.4178513050869124,-0.41086038065548824,0.3399802058110002,0.1731350904896062,0.42942684233325906,-0.3458589730342161
		2019-10-01,-0.4068111024384073,0.23236278512710717,-0.4219311162076128,-0.41546165875809776,0.31839699435258056,0.11704847367239453,0.43254039229859587,-0.3573651131923373
		2020-01-01,-0.41234584538126307,0.2048351101337259,-0.4285775306832703,-0.4288226741671517,0.2934958206118874,0.0968284142914183,0.4393051503485887,-0.3632373082617587
		2020-04-01,-0.41329455205748955,0.16765078987157045,-0.42754943864086414,-0.42435739011747764,0.3090030330766049,0.09546862984305735,0.43890169761897985,-0.3754614160711164
		2020-07-01,-0.4213659810738521,0.216538074628016,-0.4510682642430343,-0.307530755404854,0.32629521345246376,0.08587376184398199,0.4591973928062615,-0.3909208524083414
		2020-10-01,-0.4160297698334889,0.22982058896368274,-0.44407328956691683,-0.3010230034354574,0.3289868152039892,0.14298500873039668,0.4527756614550879,-0.3906442825523065
		2021-01-01,-0.3987251376730386,0.19555867258777204,-0.4353307651557606,-0.33141489874574537,0.33525457667585845,0.18028110334097044,0.44848683191573424,-0.39672284299724137
		2021-04-01,-0.39970750168761837,0.09714725143492764,-0.4334866559259989,-0.35096673788023336,0.349246230969731,0.19272764554695349,0.4465973800585853,-0.4014248342956076
		2021-07-01,-0.41139751732539626,0.055087644475222186,-0.4227267164695504,-0.3684377116917824,0.3742044216571289,0.10984855722509236,0.4399228773680916,-0.409445255445543
		2021-10-01,-0.41761947030229785,0.030777513920404398,-0.42753365742761856,-0.37726362887020504,0.38213888328707374,0.0841484967447652,0.4431225681903663,-0.387382424350453
		2022-01-01,0.4029997967783217,0.05384602751322298,0.42897362862050425,0.38755307665570937,-0.3928673299744817,-0.1630869578988471,-0.4415014721453794,0.3530019307822731
		2022-04-01,0.3897212505958381,0.17868973081391626,0.4249124965162534,0.392105348622082,-0.398594979190529,-0.1402917119478852,-0.4351166598365667,0.33764458129436786
		2022-07-01,0.38567301155822303,0.22552627719722984,0.43422556282979324,0.3979684082624086,-0.41669474887652463,0.06042406453530773,-0.4423810470236343,0.28368461533442224
		2022-10-01,0.2616588243586302,0.2840457264771758,0.45123293188992575,0.43094990586158577,-0.44063299236689357,0.13163567121269593,-0.4529605564072695,0.2118137275122221
		2023-01-01,0.1594429132717118,0.3314930649600427,0.454877832082501,0.45504857978627433,-0.4565531380898177,0.20037598410411778,-0.4405510370455824,0.08961436301148143
		2023-04-01,0.1046959111893008,0.34978035946708036,0.4547162675601354,0.46385993342852244,-0.46160032358430114,0.22151494117285128,-0.42726214921326106,0.007929214394280185
		2023-07-01,0.06095608471970047,0.3623032498393385,0.45489014299403385,0.4692522219376108,-0.46231137165617575,0.22892316012936798,-0.41221720584186183,-0.04286465334840031
		2023-10-01,0.013775239510727589,0.36836830912822754,0.4533090593118763,0.4710665493009615,-0.46260431726514695,0.24480105539739888,-0.39494188340889935,-0.08253988208919152
		2024-01-01,0.012534726127383359,0.3589688193969932,0.4512186080221655,0.4790903427640619,-0.4683612947067526,0.21530256004745624,-0.4030685346095255,-0.09837042366356252
		2024-04-01,0.025934020676395733,0.36407194769321055,0.44924379228706324,0.4793669230087099,-0.46924285875795313,0.1898803172469545,-0.41065147266116075,-0.10143167315591206
		2024-07-01,0.03533338913368246,0.3724227641240071,0.44967603519483423,0.4793813031427399,-0.46473428581532533,0.17124816812222315,-0.41653933006609606,-0.09606748125028781
		2024-10-01,0.02731226659448961,0.37592286482017473,0.4485998699192295,0.47714279926670705,-0.46505911141884243,0.16786748682630837,-0.4176814438297265,-0.10055688364550787

00_original_index/05_output/reduced/variable_summary_reduced.csv

0 → 100644

+9 −0

Original line number	Diff line number	Diff line
		variable,avg_loading
		r_actual_rent_d,-0.2931026863785579
		r_maintenance_repair_aprtm_d,-0.25556079525221564
		r_disp_income_bw,0.2529199336706797
		r_index_house_price_d,-0.24604404456252868
		r_interest_new_avg_d,0.24332124217496137
		r_volume_existing_overall_d,0.23893102790324755
		r_houseprice_income_ratio_d,-0.12527862857180042
		r_volume_new_overall_d,0.1194054407225627

00_original_index/05_output/robustness/lambda_sensitivity.csv

0 → 100644

+5 −0

Original line number	Diff line number	Diff line
		lambda,mean_pc1_var,final_HCI,correlation
		0.9,54.80127764084113,193.99175805604273,0.9863932120416629
		0.95,53.01883130088331,200.94420993404466,0.9991421662427576
		0.97,52.460843967170874,203.56285129037286,1
		0.99,52.00384243815898,204.06038140436834,0.9991485715349177

00_original_index/05_output/robustness/variable_sensitivity.csv

0 → 100644

+5 −0

Original line number	Diff line number	Diff line
		specification,n_vars,mean_pc1_var,final_HCI,correlation
		baseline,8,52.460843967170874,203.56285129037286,1
		no_maintenance,7,50.56239632489925,206.14958503598012,0.9936615234001475
		existing_interest,8,60.033599555094305,254.6727777236975,0.9178990269717562
		construction_cost,8,52.142045497227905,186.54678414021078,0.993835527827103

00_original_index/05_output/robustness/window_sensitivity.csv

0 → 100644

+4 −0

Original line number	Diff line number	Diff line
		W,mean_pc1_var,final_HCI,correlation
		16,52.79200500876648,200.46332944746257,0.9989788766181912
		20,52.460843967170874,203.56285129037286,1
		24,52.78987310784444,188.63888456985808,0.9993013048088826

00_original_index/05_output/variable_selection/.DS_Store

0 → 100644

+6 KiB

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00_original_index/05_output/variable_selection/correlation_heatmap.pdf

0 → 100644

+12.8 KiB

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00_original_index/05_output/variable_selection/correlation_matrix.csv

0 → 100644

+31 −0

Original line number	Diff line number	Diff line
		variable,r_index_house_price_d,r_index_existing_buildings_d,r_index_new_buildings_d,r_annuity_income_ratio_d,r_houseprice_income_ratio_d,r_houseprice_rent_ratio_d,r_actual_rent_d,r_cost_gas_d,r_cost_oil_d,r_electricity_cost_d,r_maintenance_repair_aprtm_d,r_construction_price_index_bw,r_interest_existing_1_d,r_interest_existing_1_5_d,r_interest_existing_5_d,r_interest_new_1_d,r_interest_new_1_5_d,r_interest_new_5_10_d,r_interest_new_10_d,r_interest_new_avg_d,r_volume_existing_1_d,r_volume_existing_1_5_d,r_volume_existing_5_d,r_volume_existing_overall_d,r_volume_new_1_d,r_volume_new_1_5_d,r_volume_new_5_10_d,r_volume_new_10_d,r_volume_new_overall_d,r_disp_income_bw
		r_index_house_price_d,1,0.9933002232976441,0.5768924608339042,0.09602313441596955,0.5591174998417934,0.5996330839028217,-0.09056275846998756,-0.17861732204165098,0.07115468515420971,-0.18632367619338758,-0.18519635880743307,-0.03846692482087182,-0.45164700857485607,-0.5498516405701246,-0.5984176604882204,-0.3607738713556043,-0.25732011299744606,-0.19227900863391273,-0.14246514255738574,-0.20838699749776166,0.043493717800631236,-0.2799949822964256,-0.4348173328237917,-0.44112496692607395,0.022135650817401997,0.05354675661881366,-0.19495788662597466,-0.19350729063114724,-0.20328270058197384,0.002596805192002209
		r_index_existing_buildings_d,0.9933002232976441,1,0.5023029077382506,0.08761835133642351,0.5544298184969364,0.5918394474235686,-0.07783962792370558,-0.16310153038602554,0.0862991485094706,-0.18909758580667824,-0.19028925609979536,-0.05697624892105195,-0.44425718704935424,-0.5417577597338858,-0.5894604804470105,-0.3522765247962884,-0.26664188102348174,-0.1995382060373382,-0.1495739718359398,-0.21399367904618075,0.06082376282315152,-0.2683887763938448,-0.43118993042051146,-0.4362751137923976,0.02645865581434872,0.04056711507874016,-0.19509566838851958,-0.19701626639228273,-0.20599919275285025,0.010335744027829868
		r_index_new_buildings_d,0.5768924608339042,0.5023029077382506,1,0.09736826283365226,0.30909658788434263,0.3049415978933066,0.013326782393071512,-0.14672580803334553,-0.08836843081039951,-0.07913197653063005,0.014724955852360031,0.07769875060937388,-0.2443964534000465,-0.3045108990784379,-0.36651995402990817,-0.23000664984443922,-0.10822477304069333,-0.05623563401930575,-0.018939658258186085,-0.07513962995905063,0.04462083344874567,-0.17823524451986233,-0.27697238629400966,-0.2850394269432267,-0.03017630282852268,0.05758232338125593,-0.04196958339969859,-0.023578589711587696,-0.05472824118923243,0.009784515192440528
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		r_disp_income_bw,0.002596805192002209,0.010335744027829868,0.009784515192440528,-0.2681432496776581,0.25887280593903017,0.1169680107055843,-0.42522589378199044,-0.20331083952497878,-0.2493749380094791,-0.0768669914660621,-0.36600693853634125,-0.42996592550360363,-0.4545632624609801,-0.4121478771884276,-0.18801282710189549,-0.4838379299372856,-0.4612224119282815,-0.4538440146872552,-0.43499654644555963,-0.48333367837809127,-0.306578494636992,-0.09447125022508016,0.3036242644311109,0.2959561455358548,-0.14034560558596945,-0.0871424001597898,-0.07235205716439767,-0.10958002551998554,-0.14405505191675783,1

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		var1,var2,correlation
		r_volume_existing_5_d,r_volume_existing_overall_d,0.9971895092019284
		r_index_house_price_d,r_index_existing_buildings_d,0.9933002232976441
		r_interest_new_5_10_d,r_interest_new_avg_d,0.9872765300462886
		r_interest_new_10_d,r_interest_new_avg_d,0.9705298634112776
		r_interest_new_5_10_d,r_interest_new_10_d,0.9678682984656979
		r_volume_new_5_10_d,r_volume_new_overall_d,0.9319669385807033
		r_interest_new_1_5_d,r_interest_new_avg_d,0.9288466496416348
		r_interest_new_1_5_d,r_interest_new_5_10_d,0.9004503511720852

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		Capacity: max_strings=200000, hash_size=200000, hash_prime=170003
		The top-level auxiliary file: HAI_Poster_tw_sr.aux
		I found no \bibdata command---while reading file HAI_Poster_tw_sr.aux
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		%==============================================================================
		% Beamer style for the poster template with Darker Orange/Red theme
		% Modified from Nathaniel Johnston / Jacobs University (2009)
		%==============================================================================

		\ProvidesPackage{beamerthemeconfposter}
		\RequirePackage{tikz}
		\usetikzlibrary{arrows,backgrounds}
		\RequirePackage[T1]{fontenc}
		\RequirePackage{textcomp}
		\RequirePackage{amsmath,amssymb}
		\usepackage{exscale}
		\usepackage{ragged2e}
		\usepackage{changepage}
		\usepackage{xcolor}

		%-----------------------------
		% Define new darker colors
		%-----------------------------
		\definecolor{DarkOrangeRed}{RGB}{180,50,20} % dark orange/red for titles
		\definecolor{OrangeRedAccent}{RGB}{220,80,40} % lighter accent
		\definecolor{RedAccent}{RGB}{150,20,20} % deep red for alert blocks
		\definecolor{GrayText}{RGB}{80,80,80} % gray text

		% Spacing for list environments
		\makeatletter
		\def\@listi{\leftmargin\leftmarginii
		\topsep 1ex
		\parsep 0\p@ \@plus\p@
		\itemsep 6pt}
		\makeatother

		\usecaptiontemplate{\small\structure{\insertcaptionname~\insertcaptionnumber: }\insertcaption}

		%-----------------------------
		% Fonts and block colors
		%-----------------------------
		\setbeamercolor{cboxb}{bg=DarkOrangeRed!80}

		% ALERT BLOCKS
		\setbeamercolor{block title alerted}{fg=white,bg=RedAccent}
		\setbeamercolor{block body alerted}{bg=RedAccent!15,fg=black}

		% NORMAL BLOCKS
		\setbeamercolor{block title}{fg=DarkOrangeRed,bg=white}
		\setbeamercolor{block body}{bg=white,fg=black}

		% SUBBLOCKS
		\setbeamercolor{subblock title}{fg=DarkOrangeRed,bg=white}

		% Headline / poster title
		\setbeamercolor{title in headline}{fg=DarkOrangeRed}
		\setbeamercolor{author in headline}{fg=GrayText}
		\setbeamercolor{institute in headline}{fg=GrayText}

		% Bullet points
		\setbeamercolor{item}{fg=DarkOrangeRed}

		% Fonts
		\setbeamerfont{section in head/foot}{series=\bfseries}
		\setbeamerfont{block title}{series=\bfseries,size=\huge}
		\setbeamerfont{frametitle}{series=\bfseries,size=\HUGE}

		% Beamer templates
		\setbeamertemplate{title page}[default][colsep=-4bp,rounded=true]
		\setbeamertemplate{sections/subsections in toc}[square]
		\setbeamertemplate{items}[circle]
		\beamertemplatenavigationsymbolsempty
		\setbeamertemplate{sidebar left}{}
		\setbeamersize{sidebar width left=0pt}

		% Bibliography colors
		\setbeamertemplate{bibliography item}[text]
		\setbeamercolor{bibliography item}{fg=DarkOrangeRed,bg=white}
		\setbeamercolor{bibliography entry author}{fg=DarkOrangeRed,bg=white}

		% Poster headline (colored)
		\setbeamertemplate{headline}{
		\leavevmode
		\begin{columns}
		\begin{column}{\linewidth}
		\vskip1cm
		\centering
		\color{DarkOrangeRed} % <- force the color
		\usebeamercolor[fg]{title in headline}{\Huge{\textbf{\inserttitle}}\\[0.5ex]}
		\color{GrayText} % authors & institute in gray
		\usebeamercolor[fg]{author in headline}{\Large{\insertauthor}\\[1ex]}
		\usebeamercolor[fg]{institute in headline}{\large{\insertinstitute}\\[1ex]}
		\vskip1cm
		\end{column}
		\vspace{1cm}
		\end{columns}
		\vspace{0.5in}
		\hspace{0.5in}\begin{beamercolorbox}[wd=47in,colsep=0.15cm]{cboxb}\end{beamercolorbox}
		\vspace{0.1in}
		}

		% Block environments
		\let\oldblock\block
		\let\endoldblock\endblock
		\renewenvironment{block}[1]{\begin{oldblock}{#1}\smallskip}{\end{oldblock}\vspace*{0.25cm}}

		\newenvironment{subblock}[1]{
		\setbeamercolor{block title}{fg=DarkOrangeRed,bg=white}
		\setbeamerfont{block title}{size=\LARGE}
		\medskip
		\begin{block}{#1}\smallskip
		}{\end{block}\medskip}

		\addtobeamertemplate{block end}{}{\vspace*{2ex}}
		\addtobeamertemplate{block alerted begin}{}{
		\setlength{\parskip}{1em plus 0.5em minus 0.5em}%
		\begin{adjustwidth}{1em}{1em}
		}
		\addtobeamertemplate{block alerted end}{\end{adjustwidth}\vspace{2ex plus 0.5ex minus 0.5ex}}{\vspace*{2ex}}

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		\headcommand {\slideentry {0}{0}{1}{1/1}{}{0}}
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		\headcommand {\gdef \inserttotalframenumber {1}}