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.

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.

CEIC calculates Annual Household Expenditure per Capita from annual Average Household Expenditure and annual Average Household Size. U.S. Bureau of Labor Statistics provides Average Household Expenditure in USD and Average Household Size.

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.

Consumer Spending in the United States increased to 16291.80 USD Billion in the first quarter of 2025 from 16273.20 USD Billion in the fourth quarter of 2024. This dataset provides the latest reported value for - United States Consumer Spending - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This statistic shows the average annual expenditure on household furnishings and equipment per consumer unit in the United States from 2007 to 2023. In 2023, the country's average expenditure on household furnishings and equipment amounted to about 2.5 thousand U.S. dollars per consumer unit, a decrease compared to the previous year.

Survey of Household Spending (SHS), average household spending by age of reference person.

Household Budget Survey (HBS): Average expenditure by household, average expenditure by person and expenditure distribution (vertical and horizontal percentages) by expenditure group and expenditure quintile. Annual. National.

analyze the consumer expenditure survey (ce) with r the consumer expenditure survey (ce) is the primo data source to understand how americans spend money. participating households keep a running diary about every little purchase over the year. those diaries are then summed up into precise expenditure categories. how else are you gonna know that the average american household spent $34 (±2) on bacon, $826 (±17) on cellular phones, and $13 (±2) on digital e-readers in 2011? an integral component of the market basket calculation in the consumer price index, this survey recently became available as public-use microdata and they're slowly releasing historical files back to 1996. hooray! for a t aste of what's possible with ce data, look at the quick tables listed on their main page - these tables contain approximately a bazillion different expenditure categories broken down by demographic groups. guess what? i just learned that americans living in households with $5,000 to $9,999 of annual income spent an average of $283 (±90) on pets, toys, hobbies, and playground equipment (pdf page 3). you can often get close to your statistic of interest from these web tables. but say you wanted to look at domestic pet expenditure among only households with children between 12 and 17 years old. another one of the thirteen web tables - the consumer unit composition table - shows a few different breakouts of households with kids, but none matching that exact population of interest. the bureau of labor statistics (bls) (the survey's designers) and the census bureau (the survey's administrators) have provided plenty of the major statistics and breakouts for you, but they're not psychic. if you want to comb through this data for specific expenditure categories broken out by a you-defined segment of the united states' population, then let a little r into your life. fun starts now. fair warning: only analyze t he consumer expenditure survey if you are nerd to the core. the microdata ship with two different survey types (interview and diary), each containing five or six quarterly table formats that need to be stacked, merged, and manipulated prior to a methodologically-correct analysis. the scripts in this repository contain examples to prepare 'em all, just be advised that magnificent data like this will never be no-assembly-required. the folks at bls have posted an excellent summary of what's av ailable - read it before anything else. after that, read the getting started guide. don't skim. a few of the descriptions below refer to sas programs provided by the bureau of labor statistics. you'll find these in the C:\My Directory\CES\2011\docs directory after you run the download program. this new github repository contains three scripts: 2010-2011 - download all microdata.R lo op through every year and download every file hosted on the bls's ce ftp site import each of the comma-separated value files into r with read.csv depending on user-settings, save each table as an r data file (.rda) or stat a-readable file (.dta) 2011 fmly intrvw - analysis examples.R load the r data files (.rda) necessary to create the 'fmly' table shown in the ce macros program documentation.doc file construct that 'fmly' table, using five quarters of interviews (q1 2011 thru q1 2012) initiate a replicate-weighted survey design object perform some lovely li'l analysis examples replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using unimputed variables replicate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t -tests using unimputed variables create an rsqlite database (to minimize ram usage) containing the five imputed variable files, after identifying which variables were imputed based on pdf page 3 of the user's guide to income imputation initiate a replicate-weighted, database-backed, multiply-imputed survey design object perform a few additional analyses that highlight the modified syntax required for multiply-imputed survey designs replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using imputed variables repl icate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t-tests using imputed variables replicate the %proc_reg() and %proc_logistic() macros found in "ce macros.sas" and provide some examples of regressions and logistic regressions using both unimputed and imputed variables replicate integrated mean and se.R match each step in the bls-provided sas program "integr ated mean and se.sas" but with r instead of sas create an rsqlite database when the expenditure table gets too large for older computers to handle in ram export a table "2011 integrated mean and se.csv" that exactly matches the contents of the sas-produced "2011 integrated mean and se.lst" text file click here to view these three scripts for...

This statistic shows the average food away-from-home household expenditure in the United States in 20223, by income. In that year, households with an income range of ****** to ****** U.S. dollars spent on average ***** U.S. dollars for food away-from-home.

Graph and download economic data for Expenditures: Total Average Annual Expenditures by Age: from Age 65 to 74 (CXUTOTALEXPLB0408M) from 1984 to 2023 about 65-years +, age, average, expenditures, and USA.

Survey of Household Spending (SHS), average household spending, Canada, regions and provinces.

The average planned back-to-school spending per household in the United States gradually increased year-on-year, reaching about *** U.S. dollars in 2023. While this was an increase of over *** dollars since the beginning of the survey period in 2004, the numbers had begun to fall back down by 2024. That year, U.S. consumers planned to spend an average of *** U.S. dollars on back-to-school purchases. Spending breakdown In 2024, parents planned to spend the most on electronics or computer-related equipment, with average household spending expected to reach just over *** U.S. dollars. Although parents relied on several kinds of outlets for back-to-school supplies, the leading location for such items was online. More than **** of respondents planned to undertake their shopping there. Department stores stood in second place. Back-to-school vs. back-to-college spending While parents planned to spend hundreds of dollars to send their children back to school, college students and their families were willing to spend even more. In 2024, the average household spend for back-to-college was expected to equal more than ***** U.S. dollars.

Graph and download economic data for Expenditures: Total Average Annual Expenditures by Deciles of Income Before Taxes: Second 10 Percent (11st to 20th Percentile) (CXUTOTALEXPLB1503M) from 2014 to 2023 about percentile, tax, average, expenditures, income, and USA.

Personal Spending in the United States decreased 0.10 percent in May of 2025 over the previous month. This dataset provides the latest reported value for - United States Personal Spending - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States US: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data was reported at 0.781 % in 2013. This records a decrease from the previous number of 0.856 % for 2012. United States US: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data is updated yearly, averaging 0.880 % from Dec 1995 (Median) to 2013, with 18 observations. The data reached an all-time high of 1.078 % in 2000 and a record low of 0.724 % in 2008. United States US: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Poverty. Proportion of population spending more than 25% of household consumption or income on out-of-pocket health care expenditure, expressed as a percentage of a total population of a country; ; Wagstaff et al. Progress on catastrophic health spending: results for 133 countries. A retrospective observational study, Lancet Global Health 2017.; Weighted Average;

Key information about Japan Household Expenditure per Capita

• Japan Annual Household Expenditure per Capita reached 8,258.473 USD in Dec 2024, compared with the last update number of 8,691.523 USD in Dec 2023.
• Japan Annual Household Expenditure per Capita data is updated yearly, available from Dec 2000 to Dec 2024, with an averaged value of 10,419.370 USD.
• The data reached an all-time high of 14,023.726 USD in Dec 2012 and a record low of 8,258.473 USD in Dec 2024.
• In the latest reports, Retail Sales of Japan grew 5.854 % YoY in May 2023.

CEIC calculates Annual Household Expenditure per Capita from monthly Household Expenditure and monthly Average Household Size and converts it into USD. Statistical Bureau provides Household Expenditure in local currency and Average Household Size. Federal Reserve Board average market exchange rate is used for currency conversions. Household Expenditure do not cover single person households.

The average annual expenditure on renting, streaming, and downloading video per consumer unit in the United States reached over *** U.S. dollars in 2023, more than **** times the figure recorded for 2017. Average consumer expenditure has continued to grow, and with many U.S. consumers exhibiting an ever-increasing and almost insatiable need for streamed and downloaded video content, it can be expected that growth will continue in years to come.

Average weekly household expenditure on goods and services in the UK. Data are shown by region, age, income (including equivalised) group (deciles and quintiles), economic status, socio-economic class, housing tenure, output area classification, urban and rural areas (Great Britain only), place of purchase and household composition.

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]

Key information about South Korea Household Expenditure per Capita

• South Korea Annual Household Expenditure per Capita reached 15,353.591 USD in Dec 2024, compared with the last update number of 15,398.973 USD in Dec 2023.
• South Korea Annual Household Expenditure per Capita data is updated yearly, available from Dec 2003 to Dec 2024, with an averaged value of 11,051.919 USD.
• The data reached an all-time high of 15,398.973 USD in Dec 2023 and a record low of 6,271.386 USD in Dec 2003.
• In the latest reports, Retail Sales of South Korea dropped 0.473 % YoY in May 2023.

CEIC calculates Annual Household Expenditure per Capita from annual Monthly Household Expenditure multiplied by 12 and annual Average Household Size and converts it into USD. Statistics Korea provides Household Expenditure in local currency and Average Household Size. Federal Reserve Board average market exchange rate is used for currency conversions. Household Expenditure prior to 2017 excludes single person and farm households. Household Expenditure per Capita prior to 2019 is based on old methodology.