The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants. More information and details about the data provided can be found at http://www.bls.gov/cpi

The Chained Consumer Price Index for All Urban Consumers, was introduced with the release of July data in August 2002. Designated the C-CPI-U, the index supplements the existing Consumer Price Indexes already produced by the BLS: the CPI for All Urban Consumers (CPI-U) and the CPI for Urban Wage Earners and Clerical Workers (CPI-W).

The Consumer Price Indexes (CPI) program produces monthly data on changes in the prices paid by urban consumers for a representative basket of goods and services. More information and details about the data provided can be found at http://www.bls.gov/cpi

This dataset contains the consumer price index (CPI) over time for the Atlanta Metropolitan Statistical Area (MSA). The CPI is given for all goods and services combined as well for individual classes such as energy, housing, transportation and food. The 2-month change and year-over-year change in CPI is also included. This dataset is in a wide format with the metrics for each category of consumer item in a separate column.

Analysis of ‘🚊 Consumer Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/consumer-price-indexe on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

9The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a measure of the average monthly change in the price for goods and services paid by urban consumers between any two time periods.(1) It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force.(1)

The CPIs are based on prices for food, clothing, shelter, and fuels; transportation fares; service fees (e.g., water and sewer service); and sales taxes. Prices are collected monthly from about 4,000 housing units and approximately 26,000 retail establishments across 87 urban areas.(1) To calculate the index, price changes are averaged with weights representing their importance in the spending of the particular group. The index measures price changes (as a percent change) from a predetermined reference date.(1) In addition to the original unadjusted index distributed, the Bureau of Labor Statistics also releases a seasonally adjusted index. The unadjusted series reflects all factors that may influence a change in prices. However, it can be very useful to look at the seasonally adjusted CPI, which removes the effects of seasonal changes, such as weather, school year, production cycles, and holidays.(1)

The CPI can be used to recognize periods of inflation and deflation. Significant increases in the CPI within a short time frame might indicate a period of inflation, and significant decreases in CPI within a short time frame might indicate a period of deflation. However, because the CPI includes volatile food and oil prices, it might not be a reliable measure of inflationary and deflationary periods. For a more accurate detection, the core CPI (Consumer Price Index for All Urban Consumers: All Items Less Food & Energy [CPILFESL]) is often used. When using the CPI, please note that it is not applicable to all consumers and should not be used to determine relative living costs.(1) Additionally, the CPI is a statistical measure vulnerable to sampling error since it is based on a sample of prices and not the complete average.(1)

Attribution: US. Bureau of Labor Statistics from The Federal Reserve Bank of St. Louis

For more information on the consumer price indexes, see:

• (1) Bureau of Economic Analysis. “CPI Detailed Report.” 2013
• (2) Handbook of Methods
• (3) Understanding the CPI: Frequently Asked Questions

This dataset was created by Finance and contains around 900 samples along with Consumer Price Index For All Urban Consumers: All Items, Title:, technical information and other features such as: - Consumer Price Index For All Urban Consumers: All Items - Title: - and more.

How to use this dataset

• Analyze Consumer Price Index For All Urban Consumers: All Items in relation to Title:
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Acknowledgements

If you use this dataset in your research, please credit Finance

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In 2023, the U.S. Consumer Price Index was 309.42, and is projected to increase to 352.27 by 2029. The base period was 1982-84. The monthly CPI for all urban consumers in the U.S. can be accessed here. After a time of high inflation, the U.S. inflation rateis projected fall to two percent by 2027. United States Consumer Price Index ForecastIt is projected that the CPI will continue to rise year over year, reaching 325.6 in 2027. The Consumer Price Index of all urban consumers in previous years was lower, and has risen every year since 1992, except in 2009, when the CPI went from 215.30 in 2008 to 214.54 in 2009. The monthly unadjusted Consumer Price Index was 296.17 for the month of August in 2022. The U.S. CPI measures changes in the price of consumer goods and services purchased by households and is thought to reflect inflation in the U.S. as well as the health of the economy. The U.S. Bureau of Labor Statistics calculates the CPI and defines it as, "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." The BLS records the price of thousands of goods and services month by month. They consider goods and services within eight main categories: food and beverage, housing, apparel, transportation, medical care, recreation, education, and other goods and services. They aggregate the data collected in order to compare how much it would cost a consumer to buy the same market basket of goods and services within one month or one year compared with the previous month or year. Given that the CPI is used to calculate U.S. inflation, the CPI influences the annual adjustments of many financial institutions in the United States, both private and public. Wages, social security payments, and pensions are all affected by the CPI.

Context:

The Consumer Price Indexes (CPI) program produces monthly data on changes in the prices paid by urban consumers for a representative basket of goods and services. It is a useful way to compare changes in the economy across time.

Content:

This data covers Jan 1913-May 2017, and is normalized to “CPI-U all items 1982-84=100, not seasonally adjusted”. Fields include time of measurement and CPI score.

Acknowledgements:

This dataset was compiled on behalf of the Bureau of Labor Statistics (BLS) via Colorado Department of Labor & Employment (CDLE) and hosted on data.colorado.gov.

Inspiration:

• What periods of time have seen the highest/lowest CPI?
• When has inflation been the worse?
• Can you predict present CPI?

Graph and download economic data for Consumer Price Index for All Urban Consumers: All Items Less Food and Energy in U.S. City Average (CPILFESL) from Jan 1957 to Apr 2025 about core, headline figure, all items, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

The Consumer Price Index (CPI) measures over time the prices of goods and services in major expenditure categories typically purchased by urban consumers. The expenditure categories include food, housing, apparel, transportation, and medical care. Essentially, the Index measures consumer purchasing power by comparing the cost of a fixed set of goods and services (called a market basket) in a specific month relative to the cost of the same market basket in an earlier reference period, designated as the base period. The CPI is calculated for two population groups: urban wage earners and clerical workers (CPI-W) and all urban consumers (CPI-U). The CPI-W population includes those urban families with clerical workers, sales workers, craft workers, operatives, service workers, or laborers in the family unit and is representative of the prices paid by about 40 percent of the United States population. The CPI-U population consists of all urban households (including professional and salaried workers, part-time workers, the self-employed, the unemployed, and retired persons) and is representative of the prices paid by about 80 percent of the United States population. Both populations specifically exclude persons in the military, in institutions, and all persons living outside of urban areas (such as farm families). National indexes for both populations are available for about 350 consumer items and groups of items. In addition, over 100 of the indexes have been adjusted for seasonality. The indexes are monthly with some beginning in 1913. Area indexes are available for 27 urban places. For each area, indexes are presented for about 65 items and groups. The area indexes are produced monthly for 5 areas, bimonthly for 10 areas, and semiannually for 12 urban areas. Regional indexes are available for four regions with about 95 items and groups per region. Beginning with January 1987, regional indexes are monthly, with some beginning as early as 1966. City-size indexes are available for four size classes with about 95 items and groups per class. Beginning with January 1987, these indexes are monthly and most begin in 1977. Regional and city-size indexes are available cross-classified by region and city-size class. For each of the 13 cross-classifications, about 60 items and groups are available. Beginning with January 1987, these indexes are monthly and most begin in 1977. Each index record includes a series identification code that specifies the sample (either all urban consumers or urban wage earners and clerical workers), seasonality (either seasonally adjusted or unadjusted), periodicity (either semiannual or regular), geographic area, index base period, and item number of the index. (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/ICPSR08166.v3. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future and includes additional years of data.

VITAL SIGNS INDICATOR
Rent Payments (EC8)

FULL MEASURE NAME
Median rent payment

LAST UPDATED
January 2023

DESCRIPTION
Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time.

DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Count 2 (1970)
Form STF1 (1980-1990)
Form SF3a (2000)

U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B25058 (2005-2021; median contract rent)

Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Rent data reflects median rent payments rather than list rents (refer to measure definition above). American Community Survey 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.

1970 Census data for median rent payments has been imputed from quintiles using methodology from California Department of Finance as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

Graph and download economic data for Producer Price Index by Industry: Medical Equipment and Supplies Manufacturing (PCU33913391) from Dec 2003 to Apr 2025 about medical, supplies, equipment, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

VITAL SIGNS INDICATOR
Income (EC4)

FULL MEASURE NAME
Household income by place of residence

LAST UPDATED
January 2023

DESCRIPTION
Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Count 4Pb (1970)
Form STF3 (1980-1990)
Form SF3a (2000)

U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B19001 (2005-2021; household income by place of residence)
Form B19013 (2005-2021; median household income by place of residence)
Form B08521 (2005-2021; median worker earnings by place of employment)

Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Income derived from the decennial Census data reflects the income earned in the prior calendar year, whereas income derived from the American Community Survey (ACS) data reflects the prior 12 month period; note that this inconsistency has a minor effect on historical comparisons (see Income and Earnings Data section of the ACS General Handbook - https://www.census.gov/content/dam/Census/library/publications/2020/acs/acs_general_handbook_2020_ch09.pdf). 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.

Quintile income for 1970-2000 is imputed from decennial Census data using methodology from the California Department of Finance. Bay Area income is the population weighted average of county-level income.

Income has been inflated using the Consumer Price Index (CPI) for 2021 specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data uses national CPI for 1970. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

These data present detailed income and expenditure data for the Diary component of the ongoing Consumer Expenditure Survey (CEX). The Consumer Expenditure Survey program provides a continuous and comprehensive flow of data on the buying habits of American consumers. The primary purpose of the Diary component of the Survey is to provide the Bureau of Labor Statistics (BLS) with a data base for the maintenance and review of the Consumer Price Index (CPI). The Diary Survey collects expenditure data for items purchased on a daily or weekly basis. The actual information is obtained by asking participants to maintain records of all purchases made each day for a two-week period. This survey is suited to collect expenditure data for small, frequently purchased items such as food, beverages, food consumed away from home, gasoline, housekeeping supplies, nonprescription drugs and medical supplies, and personal care products and services.

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/ICPSR09333.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Abstract

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, issues, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (See Section XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm. These microdata files present detailed expenditure and income data for the Diary component of the CE for 2002. They include weekly expenditure (EXPD) and annual income (DTBD) files. The data in EXPD and DTBD files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. Estimates of average expenditures in 2002 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2002. A list of recent publications containing data from the CE appears at the end of this documentation. The microdata files are in the public domain and with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2002".

Analysis unit

Consumer Units

Kind of data

Sample survey data [ssd]

Sampling procedure

Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons. The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2002 sample is composed of 105 areas. The design classifies the PSUs into four categories: • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

The sampling frame (that is, the list from which housing units were chosen) for the 2002 survey is generated from the 1990 Population Census 100-percent-detail file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (ED's) from the Census that fail to meet the criterion for good addresses for new construction, and all ED's in nonpermit-issuing areas are grouped into the area segment frame. To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance. Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year. During the last 6 weeks of the year, however, the Diary Survey sample is supplemented to twice its normal size to increase the reporting of types of expenditures unique to the holidays.

STATE IDENTIFIER Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data. To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

INTERPRETING THE DATA Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially. Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs. CUs with members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

Mode of data collection

Computer Assisted Personal Interview [capi]

VITAL SIGNS INDICATOR
Economic Output (EC13)

FULL MEASURE NAME
Gross regional product

LAST UPDATED
August 2022

DESCRIPTION
Economic output is measured by the total and per-capita gross regional product (GRP) and refers to the value of goods and services generated by workers and companies in a region.

DATA SOURCE
Bureau of Economic Analysis: Regional Economic Accounts - http://www.bea.gov/regional/
2001-2020

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
1970-2021

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2001-2020

Bureau of Labor Statistics: Consumer Price Index - https://download.bls.gov/pub/time.series/cu
2012, 2020

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Data is inflation-adjusted by using both nominal and real data developed by Bureau of Economic Analysis (BEA) and appropriately escalating real GRP data in 2012 chained dollars to 2020 dollars using metropolitan statistical area (MSA)-specific Consumer Price Index data from Bureau of Labor Statistics. Economic output per capita is calculated using CA Department of Finance historical population estimates and Census historical population estimates for Metro areas.

VITAL SIGNS INDICATOR
Economic Output (EC13)

FULL MEASURE NAME
Gross regional product

LAST UPDATED
August 2022

DESCRIPTION
Economic output is measured by the total and per-capita gross regional product (GRP) and refers to the value of goods and services generated by workers and companies in a region.

DATA SOURCE
Bureau of Economic Analysis: Regional Economic Accounts - http://www.bea.gov/regional/
2001-2020

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
1970-2021

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2001-2020

Bureau of Labor Statistics: Consumer Price Index - https://download.bls.gov/pub/time.series/cu
2012, 2020

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Data is inflation-adjusted by using both nominal and real data developed by Bureau of Economic Analysis (BEA) and appropriately escalating real GRP data in 2012 chained dollars to 2020 dollars using metropolitan statistical area (MSA)-specific Consumer Price Index data from Bureau of Labor Statistics. Economic output per capita is calculated using CA Department of Finance historical population estimates and Census historical population estimates for Metro areas.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Cereals and Bakery Products in U.S. City Average (CUUR0000SAF111) from Jan 1935 to Apr 2025 about bakeries, urban, production, consumer, CPI, inflation, price index, indexes, price, and USA.

VITAL SIGNS INDICATOR Income (EC5)

FULL MEASURE NAME Worker income by workplace (earnings)

LAST UPDATED May 2019

DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.

DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org

U.S. Census Bureau: American Community Survey Form B08521 (2006-2017; place of employment) http://api.census.gov

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION Vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.

Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.

VITAL SIGNS INDICATOR Home Prices (EC7)

FULL MEASURE NAME Home Prices

LAST UPDATED August 2019

DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/

Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/

Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Gasoline, Unleaded Premium in Size Class A (CUUSA000SS47016) from H1 1987 to H2 2024 about unleaded premium, gas, urban, consumer, CPI, inflation, price index, indexes, price, and USA.