West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for St. Louis city, MO (MWACL29510) from 2009 to 2023 about St. Louis City, MO; St. Louis; adjusted; MO; average; wages; real; and USA.

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for Franklin County, MO (MWACL29071) from 2009 to 2023 about Franklin County, MO; St. Louis; adjusted; MO; average; wages; real; and USA.

In 2023, the average U.S. consumer unit residing in the northeast U.S. spent about 87,445 U.S. dollars, almost twenty thousand dollars more than those living in the south. The average U.S. consumer spending amounted to 77,280 U.S. dollars.

This statistic shows the average increase in cost to live alone in one- to three- bedroom rental units in the United States in 2017, by state. Georgia was the most expensive state in which to rent alone, as it cost on average 136.2 percent more to live alone there than with roommates.

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for Lake County, FL (MWACL12069) from 2009 to 2023 about Lake County, FL; Orlando; adjusted; average; FL; wages; real; and USA.

In 2023, the average consumer unit in the United States spent about 9,985 U.S. dollars on food. Americans spent the most on housing, at 25,436 U.S. dollars, reflecting around one third of annual expenditure. The total average U.S. consumer spending amounted to 77,280 U.S. dollars.

This timeline depicts the average annual food at-home expenditure of households in the United States from 2000 to 2023. In 2023, the average food at-home expenditure of U.S. households amounted to ***** U.S. dollars.

In 2023, the average annual expenditure of consumer units in the United States increased by 5.9 percent when compared to 2022. The average annual expenditures of apparel and services increased by 4.9 percent during the same timeframe.

In 2024, the annual median cost for long-term care in the United States ranged from ****** to ******* U.S. dollars, depending on the type of service. This significant financial burden highlights the importance of planning for future healthcare needs, as many older adults may face substantial out-of-pocket costs for extended care services. Nursing homes and assisted living facilities Nursing homes represent the most expensive long-term care option, with private rooms costing an estimated ****** U.S. dollars per month in 2024. Semi-private rooms are slightly more affordable at ***** U.S. dollars monthly. Assisted living facilities offer a less costly alternative, with annual expenses for a private room averaging ****** U.S. dollars. However, these costs can vary dramatically by location, with states like Hawaii, Alaska, and Washington D.C. commanding the highest prices for assisted living accommodations. Home care services and future projections For those preferring to receive care at home, the hourly rates for long-term home care services in 2024 were ** U.S. dollars for homemaker services and ** U.S. dollars for home health aide services. These costs are expected to rise significantly in the coming decades, with projections suggesting home health aide services could approach *** U.S. dollars per hour by 2060. The increasing expense of long-term care is evident across all service types, with assisted living facilities experiencing a ** percent cost increase from 2023 to 2024, while nursing home rates for semi-private and private rooms rose by * and * percent, respectively.

In 2023, the average annual expenditures of consumer units in the United States totaled to 77,280 U.S. dollars. This is an increase from the previous year, when the average annual expenditures of consumer units totaled to 72,967 U.S. dollars.

From 2020 to 2023, the average annual household food expenditure in the United States increased by almost ** percent. The average household expenditure in 2020 was about ***** U.S. dollars and has since grown to nearly ******.

Key information about United States Household Expenditure per Capita

• United States Annual Household Expenditure per Capita reached 30,912.000 USD in Dec 2023, compared with the last update number of 30,402.917 USD in Dec 2022.
• US Annual Household Expenditure per Capita data is updated yearly, available from Dec 1984 to Dec 2023, with an averaged value of 16,842.400 USD.
• The data reached an all-time high of 30,912.000 USD in Dec 2023 and a record low of 8,451.923 USD in Dec 1984.
• In the latest reports, Retail Sales of US grew 0.967 % YoY in May 2023.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 36237). This data collection contains the Diary Survey component, which was designed to obtain data on frequently purchased smaller items, including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week. The 2013 Diary Survey release contains five sets of data files (FMLD, MEMD, EXPD, DTBD, DTID), and one processing file (DSTUB). The FMLD, MEMD, EXPD, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files. The FMLD files contain CU characteristics, income, and summary level expenditures; the MEMD files contain member characteristics and income data; the EXPD files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contain the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLD files permit the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. The DSTUB file provides the aggregation scheme used in the published consumer expenditure tables. The DSTUB file is further explained in Section III.F.6. "Processing Files" of the Diary Survey Users' Guide. A second documentation guide, the "Users' Guide to Income Imputation," includes information on how to appropriately use the imputed income data. Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over. The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Other" in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for Davidson County, TN (MWACL47037) from 2009 to 2023 about Davidson County, TN; Nashville; adjusted; TN; average; wages; real; and USA.

In 2023, the average annual expenditure of consumer units in the United States increased by 5.9 percent from the previous year. Since 2021, the annual consumer expenditure has continued to increase. This significant increase could be attributed to changes in consumer behavior as a result of the COVID-19 pandemic. Average annual consumer expenditure in the U.S. by type of expenditure can be found here.

In 2023, the average annual expenditures of households in the United States amounted to about 77,280 U.S. dollars per year. This was an increase from the previous year, reflecting an increase of around six percent between 2022 and 2023.

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]

United States US: Expenditure data was reported at 4,233.730 USD bn in 2016. This records an increase from the previous number of 4,109.428 USD bn for 2015. United States US: Expenditure data is updated yearly, averaging 1,510.750 USD bn from Sep 1972 (Median) to 2016, with 45 observations. The data reached an all-time high of 4,233.730 USD bn in 2016 and a record low of 227.660 USD bn in 1972. United States US: Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Government Revenue, Expenditure and Finance. Expense is cash payments for operating activities of the government in providing goods and services. It includes compensation of employees (such as wages and salaries), interest and subsidies, grants, social benefits, and other expenses such as rent and dividends.; ; International Monetary Fund, Government Finance Statistics Yearbook and data files.; ;

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for Clark County, NV (MWACL32003) from 2009 to 2023 about Clark County, NV; Las Vegas; NV; adjusted; average; wages; real; and USA.