The house price to income ratio in Germany stood at ***** points in the second quarter of 2025. This is higher than the observation from the second quarter one year earlier, when the ratio had been ***** points.

The Public Use Microdata Samples (PUMS) contain person- and household-level information from the "long-form" questionnaires distributed to a sample of the population enumerated in the 1980 Census. The A Sample identifies every state, county groups, and most individual counties with 100,000 or more inhabitants (350 in all). In many cases, individual cities or groups of places with 100,000 or more inhabitants are also identified. As a percentage of the 5-Percent Public Use Microdata Sample (A Sample) [CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE (A SAMPLE): 5-PERCENT SAMPLE (ICPSR 8101)], this file constitutes a 1-in-1000 sample, and contains all household- and person-level variables from the original A Sample. Household-level variables include housing tenure, year structure was built, number and types of rooms in dwelling, plumbing facilities, heating equipment, taxes and mortgage costs, number of children, and household and family income. Person-level variables include sex, age, marital status, race, Spanish origin, income, occupation, transportation to work, and education. (Source: retrieved from ICPSR 06/15/2011)

This data collection is a component of Summary Tape File 3, which consists of four sets of data containing detailed tabulations of the nation's population and housing characteristics produced from the 1980 Census. The STF 3 files contain sample data inflated to represent the total United States population. The files also contain 100-percent counts and unweighted sample counts of persons and housing units. All files in the STF 3 series are identical, containing 321 substantive data variables organized in the form of 150 "tables," as well as standard geographic identification variables. Population items tabulated for each person include demographic data and information on schooling, ethnicity, labor force status, and children, as well as details on occupation and income. Housing items include size and condition of the housing unit as well as information on value, age, water, sewage and heating, vehicles, and monthly owner costs. Each dataset provides different geographic coverage. STF 3A provides summaries for the states or state equivalents, counties or county equivalents, minor civil divisions (MCDs) or census county divisions (CCDs), places or place segments within MCD/CCDs and remainders of MCD/CCDs, census tracts or block numbering areas and block groups or, for areas that are not block numbered, enumeration districts, places, and congressional districts. There are 52 files, one for each state, the District of Columbia, and Puerto Rico. The information in the file for Puerto Rico is similar to but not identical to the data for the 50 states and the District of Columbia. Thus, this file is documented in a separate codebook. The Census Bureau's machine-readable data dictionary for STF 3 is also available through CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: CENSUS SOFTWARE PACKAGE (CENSPAC) VERSION 3.2 WITH STF4 DATA DICTIONARIES (ICPSR 7789), the software package designed specifically by the Census Bureau for use with the 1980 Census data files.

This extraction of data from 1980 decennial Census files (CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: SUMMARY TAPE FILES 3A AND 3B [ICPSR 8071, 8318]) was designed to provide a set of contextual variables to be matched to any survey dataset that has been coded for the geographic location of respondents, such as the PANEL STUDY OF INCOME DYNAMICS, 1968-1988 (ICPSR 7439). This geographic area data can also be analyzed independently with neighborhoods, labor market areas, etc., as the units of analysis. Over 120 variables were selected from the original Census sources, and more than 100 variables were derived from those component variables. The variables characterize geographic areas in terms of population counts, ethnicity, family structure, income and poverty, education, residential mobility, labor force activity, and housing. The geographic areas range from neighborhoods, through intermediate levels of geography, through large economic areas, and beyond to large regions. These variables were selected from the Census data for their relevance to problems associated with poverty and income determination, and 80 percent were present in comparable form in both the 1970 and 1980 Census datasets.

Australia Standardised Price-Income Ratio: sa data was reported at 149.268 Ratio in Dec 2024. This records a decrease from the previous number of 152.371 Ratio for Sep 2024. Australia Standardised Price-Income Ratio: sa data is updated quarterly, averaging 82.643 Ratio from Mar 1970 (Median) to Dec 2024, with 220 observations. The data reached an all-time high of 153.422 Ratio in Jun 2024 and a record low of 62.554 Ratio in Sep 1983. Australia Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Australia – Table AU.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

In 2024, the median household income in the United States was 83,730 U.S. dollars. This reflected an increase from the previous year. Household income The median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varied from state to state. In 2024, Massachusetts recorded the highest median household income in the country, at 113,900 U.S. dollars. On the other hand, Mississippi, recorded the lowest, at 55,980 U.S. dollars.Household income is also used to determine the poverty rate in the United States. In 2024, 10.6 percent of the U.S. population was living below the national poverty line. This was the lowest level since 2019. Similarly, the child poverty rate, which represents people under the age of 18 living in poverty, reached a three-decade low of 14.3 percent of the children. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.52 in 2024. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality, while a score of one indicates complete inequality.

VITAL SIGNS INDICATOR
Housing Affordability (EQ2)

FULL MEASURE NAME
Housing Affordability

LAST UPDATED
December 2022

DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Form STF3 – https://nhgis.org (1980-1990)
Form SF3a – https://nhgis.org (2000)

U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B25074 (2009-2021)
Form B25095 (2009-2021)

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The share of income brackets used for different Census and American Community Survey (ACS) forms vary over time. To allow for historical comparisons, the Census Bureau merges housing expenditure brackets into three consistent bins (less than 20 percent, 20 percent to 34 percent, and more than 35 percent) that work for all years. The highest income bracket for renters in the ACS data was $100,000 or more, while the homeowner dataset included brackets for $100,000 to $149,999 and $150,000 and above. These brackets were merged together to allow for uniform comparison across tenure. While some studies use 30 percent as the affordability threshold, Vital Signs uses 35 percent as this is the closest break point using the standardized affordability brackets above.

ACS 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

Income breakdown data is only provided for one year as it is not possible to compare consistent inflation-adjusted income brackets over time given Census data limitations. For the county breakdown, Napa was missing ACS 1-Year renter data for all years except 2012 and 2013, and Marin was missing ACS 1-Year renter data for 2019 — these counties used 5-Year data for those years.

Japan JP: Standardised Price-Income Ratio: sa data was reported at 87.580 Ratio in 2024. This records a decrease from the previous number of 89.402 Ratio for 2023. Japan JP: Standardised Price-Income Ratio: sa data is updated yearly, averaging 128.381 Ratio from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 163.402 Ratio in 1973 and a record low of 73.561 Ratio in 2009. Japan JP: Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

"MARF 2 contains the numeric codes and names for census geographic areas plus 100 percent and sample data for selected population and housing items. The file provides 100 percent counts for the total population, five race groups (White, Black, American Indian, Eskimo, and Aleut; Asian and Pacific Islander; and other races), persons of Spanish origin, families, persons in group quarters, one-person households, and total, occupied, and owner-occupied housing units."

In addition, total pop ulation and housing unit estimates and per capita income based on 1980 census sample returns are included. Latitude and longitude coordinates are given for the approximate population centroid of each geographic area down to the level of block group (BG) and enumeration district (ED). Land area in square miles is provided for geographic areas down to the level of places and minor civil divisions (MCDs), with a population of 2,500 or more.

MARF 2 provides summaries and codes for States or State equivalent, counties of county equivalents, minor civil divisions (MCDs) or census county divisions (CCDs), places or place segments within MCDs/CCDs, remainder of MCD/CCD, census tracts or block numbering areas (BNAs), and block groups (BGs) or, for areas that are not block-numbered, enumeration districts (EDs).

This is an extract prepared by Donald Treiman from the 1980 Census of Population and Housing, Public Use Microdata Sample (PUMS). It contains 11 variables: region/division, state, sex, age, highest grade attended, highest grade finished, 1980 industry, 1980 occupation, wage and salary earnings in 1979, earnings from self-employment, and earnings from farm self-employment.

Abstract (en): The Public Use Microdata Samples (PUMS) contain person- and household-level information from the "long-form" questionnaires distributed to a sample of the population enumerated in the 1980 Census. The B Sample containing 1-percent data, consists of a file for each state and an additional file for households and persons residing in metropolitan areas that are too small to be separately identified and/or that cross state boundaries. The B Sample defines Standard Metropolitan Statistical Areas (SMSAs) and county groups differently than in the A Sample [CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE (A SAMPLE): 5-PERCENT SAMPLE (ICPSR 8101)]. Most states cannot be identified in their entirety. Household-level variables include housing tenure, year structure was built, number and types of rooms in dwelling, plumbing facilities, heating equipment, taxes and mortgage costs, number of children, and household and family income. The person record, in addition to containing demographic items such as sex, age, marital status, race, Spanish origin, income, occupation, transportation to work, and education. All persons and housing units in the United States. The B Sample is a stratified sample of households that received the "long-form" questionnaire in the 1980 Census. It comprises 1 percent of all households enumerated in the Census. 2006-01-12 All files were removed from dataset 81 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 80 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 81 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 80 and flagged as study-level files, so that they will accompany all downloads. The household and person records in each data file have a logical record length of 193 characters, but the number of records varies with each file.

Graph and download economic data for Mortgage Debt Service Payments as a Percent of Disposable Personal Income (MDSP) from Q1 1980 to Q2 2025 about disposable, payments, mortgage, personal income, debt, percent, personal, income, services, and USA.

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Description:

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?

Acknowledgement:

Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the sales w.r.t a single & multiple feature.
• Also evaluate the models & compare thier respective scores like R2, RMSE, etc.

Following a period of stagnation over most of the 2010s, the number of owner-occupied housing units in the United States started to grow in 2017. In 2024, there were over 86.9 million owner-occupied homes. Owner-occupied housing is where the person who owns a property – either outright or through a mortgage – also resides in the property. Excluded are therefore rental properties, employer-provided housing, and social housing. Homeownership sentiment in the U.S. Though homeownership is still a cornerstone of the American dream, an increasing share of people see themselves as lifelong renters. Millennials have been notoriously late to enter the housing market, with one in four reporting that they would probably continue to always rent in the future, a 2022 survey found. In 2017, just five years before that, this share stood at about 13 percent. How many renter households are there? Renter households are roughly half as few as owner-occupied households in the U.S. In 2024, the number of renter-occupied housing units amounted to over 45 million. Climbing on the property ladder for renters is not always easy, as it requires prospective homebuyers to save up for a down payment and qualify for a mortgage. In many metros, the median household income is insufficient to qualify for the median-priced home.

These data, which correspond to tables provided in the documentation, summarize information on the United States population aged 60 years and over that was collected in the 1980 Census of Population and Housing. The tables were prepared by the Bureau of the Census at the request of the National Institute on Aging. Variables appearing in one or more of the tables are age (in single years or five-year intervals), sex, race (black/white), living arrangements (institutionalization status, household/group quarters, living in families/alone, relationship to householder, persons per room), income (source, personal level, family level, household level, poverty status), veteran status, educational attainment, urban/rural residence, marital status, nativity status, and Spanish origin. In some of the tables totals that exclude amounts allocated for missing data are provided for purposes of comparison. The variables for which non-allocated figures are included are age, race, institutionalization status, income, veterans status, educational attainment, marital status, and Spanish origin. The file contains a complete set of tables for the United States as a whole, for each of the four Census regions, and for each of the 50 States, the District of Columbia, and five territories. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08533.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Ireland IE: Standardised Price-Income Ratio: sa data was reported at 111.278 Ratio in Dec 2024. This records a decrease from the previous number of 112.020 Ratio for Sep 2024. Ireland IE: Standardised Price-Income Ratio: sa data is updated quarterly, averaging 96.617 Ratio from Mar 1977 (Median) to Dec 2024, with 192 observations. The data reached an all-time high of 156.979 Ratio in Mar 2007 and a record low of 73.179 Ratio in Sep 2012. Ireland IE: Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Ireland – Table IE.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

Graph and download economic data for Household Debt Service Payments as a Percent of Disposable Personal Income (TDSP) from Q1 1980 to Q2 2025 about disposable, payments, personal income, debt, percent, households, personal, income, services, and USA.

This supplement to Summary Tape File 3D (ICPSR 8157) contains census data for the ten states that were redistricted for the 99th Congress. Complete-count data are included for demographic data such as age, race, sex, marital status, and Spanish origin, and for housing information such as occupancy status, property value, rent, number of rooms, and plumbing facilities. Sample data inflated to represent the total population are provided for other topics: education, language, ancestry, employment, transportation, and income, plus detailed information on housing characteristics. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR08402.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

This file contains summary data from the 1980 census for school districts in New York State. The Summary Tape Files (STF) contain sample data inflated to represent the total United States population. All files in the STF 3 series contain 321 substantive data variables organized in the form of 150 "tables," as well as standard geographic identification variables. Population items tabulated for each person include demographic data and information on schooling, ethnicity, labor force status, and number of children, as well as details on occupation and income. Housing items include size and condition of the housing unit as well as information on value, age, water, sewage and heating, vehicles, and monthly owner costs. Each dataset provides different geographic coverage. STF 3F provides summaries, within State, for school districts by county or county equivalent.

France FR: Standardised Price-Income Ratio: sa data was reported at 106.566 Ratio in 2024. This records a decrease from the previous number of 116.544 Ratio for 2023. France FR: Standardised Price-Income Ratio: sa data is updated yearly, averaging 79.540 Ratio from Dec 1978 (Median) to 2024, with 47 observations. The data reached an all-time high of 126.727 Ratio in 2022 and a record low of 71.403 Ratio in 1998. France FR: Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s France – Table FR.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.