In the third quarter of 2024, consumer spending reached over 16.1 trillion U.S. dollars in the United States. In the same quarter of the previous year, consumer spending was around 15.6 trillion U.S. dollars.

Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Data are in current U.S. dollars.

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.

Graph and download economic data for Real Personal Consumption Expenditures (PCEC96) from Jan 2007 to Jan 2025 about headline figure, PCE, consumption expenditures, consumption, personal, real, and USA.

Graph and download economic data for Personal Consumption Expenditures: Goods (DGDSRC1) from Jan 1959 to Jan 2025 about PCE, consumption expenditures, consumption, personal, goods, and USA.

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.

The global total consumer spending in was forecast to continuously increase between 2024 and 2029 by in total 16.2 trillion U.S. dollars (+26.61 percent). After the ninth consecutive increasing year, the consumer spending is estimated to reach 77.1 trillion U.S. dollars and therefore a new peak in 2029. Consumer spending here refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data is shown in nominal terms which means that monetary data is valued at prices of the respective year and has not been adjusted for inflation. For future years the price level has been projected as well. The data has been converted from local currencies to US$ using the average exchange rate of the respective year. For forecast years, the exchange rate has been projected as well. The timelines therefore incorporate currency effects.Find more key insights for the total consumer spending in countries like North America and Europe.

Key information about United States Private Consumption: % of GDP

• United States Private Consumption accounted for 68.8 % of its Nominal GDP in Dec 2024, compared with a ratio of 67.7 % in the previous quarter.
• US Private Consumption contribution to Nominal GDP ratio is updated quarterly, available from Mar 1947 to Dec 2024, with an average share of 63.5 %.
• The data reached an all-time high of 68.8 % in Dec 2024 and a record low of 57.7 % in Mar 1952.

• In the latest reports, US GDP expanded 1.8 % YoY in Mar 2023.
• Its Nominal GDP reached 6,632.4 USD bn in Mar 2023.
• US GDP Per Capita reached 59,484.0 USD in Dec 2017.
• Its Gross Savings Rate was measured at 16.0 % in Mar 2023.

In September 2024, personal consumption expenditure in the United States increased by 0.5 percent when compared to the previous month. The data are in 2017 chained U.S. dollars, seasonally adjusted at monthly rates. According to the BEA, personal consumption expenditure is the value of the goods and services purchased by an individual living in the United States.

Graph and download economic data for Personal Consumption Expenditures: Services (PCESV) from Q1 1947 to Q4 2024 about PCE, consumption expenditures, consumption, personal, services, GDP, and USA.

Consumer spending on home entertainment in the United States reached a record 57.17 billion U.S. dollars in 2024, up by over 21 percent from the previous year. Spending on physical rentals continued to decrease, whilst digital formats saw an increase. SVOD subscription expenditure grew by around 10 billion U.S. dollars year-on-year.

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 or CUs) of average expenditures in news releases, reports, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (see Section XVI. Appendix 5). The microdata are available on CD-ROM as SAS data sets or ASCII text files.

These microdata files present detailed expenditure and income data for the Diary component of the CE for 2006. They include weekly expenditure (EXPN), annual income (DTAB) files, and imputed income files (DTAB_IMPUTE). The data in EXPN, DTAB, and DTAB_IMPUTE files are categorized by a Universal Classification Code (UCC). The advantage of the EXPN and DTAB files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLY and MEMB files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLY 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 2006 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2006. 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, 2006”.

The Diary survey PUMD are organized into five major data files for each quarter: 1. FMLD - a file with characteristics, income, and summary level expenditures for the household 2. MEMD - a file with characteristics and income for each member in the household
3. EXPD - a detailed weekly expenditure file categorized by UCC 4. DTBD - a detailed annual income file categorized by UCC
5. DTID - a household imputed income file categorized by UCC

Analysis unit

Consumer Unit

Kind of data

Sample survey data [ssd]

Sampling procedure

A. SURVEY SAMPLE DESIGN

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 2006 sample is composed of 91 areas. The design classifies the PSUs into four categories:

• 21 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 38 "X" PSUs, are medium-sized MSAs. • 16 "Y" PSUs are nonmetropolitan areas that are included in the CPI. • 16 "Z" 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 2006 survey is generated from the 2000 Population Census file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (EDs) from the Census that fail to meet the criterion for good addresses for new construction, and all EDs 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.

B. COOPERATION LEVELS

The annual target sample size at the United States level for the Diary Survey is 7,200 participating sample units. To achieve this target the total estimated work load is 12,200 sample units. This allows for refusals, vacancies, or nonexistent sample unit addresses.

Each participating sample unit selected is asked to keep two 1-week diaries. Each diary is treated independently, so response rates are based on twice the number of housing units sampled.

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

The response rate for the 2006 Diary Survey is 74.2%. This response rate refers to all diaries in the year.

Aggregated and anonymized purchase data from consumer credit and debit card spending. Spending is reported based on the ZIP code where the cardholder lives, not the ZIP code where transactions occurred. Data from Affinity Solutions, compiled by Opportunity Insights. Update Frequency: Weekly Date Range: January 13th until the most recent date available. Data Frequency: Data is daily until the final two weeks of the series, and the daily data is presented as a 7 day lookback moving average. For the final two weeks of the series, the data is weekly and presented as weekly data points. Index Period: January 4th - January 31st Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division.

Graph and download economic data for Personal Consumption Expenditures: Total for United States (USPCE) from 1997 to 2023 about PCE, consumption expenditures, consumption, personal, and USA.

Envestnet®| Yodlee®'s Consumer Spending Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: Analytics B2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis.

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

The Consumer Expenditure Data contains annual household expenditure estimates for nearly 400 different products and is for use with GIS mapping software, databases, and web applications

Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Data are in current U.S. dollars.

This dataset provides annual estimates developed by the U.S. Bureau of Economic Analysis on consumer spending in the State of Iowa beginning in 1998. Personal consumption expenditures (PCE) is the value of the goods and services purchased by, or on the behalf of, Iowa residents. PCE is reported in millions of current dollars. Also provided is per capita PCE which is reported in current dollars. The Census Bureau’s annual midyear (July 1) population estimates are used for per capita variables.

Consumption category indicates the goods or services associated with personal consumption. All includes both goods and services.

Goods include both durable goods and non durable goods. Durable goods include: motor vehicles and parts, furnishings and durable household equipment, recreational goods and vehicles, and other durable goods. Non durable goods include: food and beverages purchased for off-premises consumption, clothing and footwear, gasoline and other energy goods, and other non durable goods.

Services include household consumption expenditures (for services) and final consumption expenditures of nonprofit institutions serving households (NPISHs). Household consumption expenditures include: housing and utilities, health care, transportation services, recreation services, food services and accommodations, financial services and insurance, and other services. NPISH is the gross output of nonprofit institutions less receipts from sales of goods and services by nonprofit institutions.

The Consumer Expenditure Survey (CE) program consists of two surveys: the quarterly Interview survey and the annual Diary survey. Combined, these two surveys provide information on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. The survey data are collected for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The CE collects all on all spending components including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. The CE features several arts-related spending categories, including the following items: Spending on Admissions Plays, theater, opera, and concerts Movies, parks, and museums Spending on Reading Newspapers and magazines Books Digital book readers Spending on Other Arts-Related Items Musical instruments Photographic equipment Audio-visual equipment Toys, games, arts and crafts The CE is important because it is the only Federal survey to provide information on the complete range of consumers' expenditures and incomes, as well as the characteristics of those consumers. It is used by economic policymakers examining the impact of policy changes on economic groups, by the Census Bureau as the source of thresholds for the Supplemental Poverty Measure, by businesses and academic researchers studying consumers' spending habits and trends, by other Federal agencies, and, perhaps most importantly, to regularly revise the Consumer Price Index market basket of goods and services and their relative importance. The most recent data tables are for 2019, and were made available on September 9, 2020. The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Excel" in the Dataset(s) section). Also, see Featured CE Tables and Economic News Releases sections on the CE home page for current data tables and news release. The 1980 through 2019 CE public-use microdata, including Interview Survey data, Diary Survey data, and paradata (information about the data collection process), are available on the CE website.

This data collection includes detailed information on the purchasing habits of Americans in 1960-1961, with over 200 types of expenditures coded. For the first time since 1941, the Consumer Expenditure Survey sampled both urban, non-farm and rural, farm households in an attempt to provide a complete picture of consumer expenditures in the United States. Personal interviews were conducted in 1960 and 1961 (and a small number in 1959) with 9,476 urban families, 2,285 rural non-farm families, and 1,967 rural farm families, for a total of 13,728 consumer units interviewed. A complete account of family income and outlays was compiled for a calendar year, as well as household characteristics. The expenditures covered by the survey were those which respondents could recall fairly accurately for three months or longer. In general, these expenditures included relatively large purchases, such as those for property, automobiles, and major appliances, or expenditures that occurred on a fairly regular basis, such as rent, utilities, or insurance premiums. Expenditures incurred while on trips were also covered by the survey. Information to determine net changes in the family's assets and liabilities during the year was also gathered. The estimated value of goods and services received, as gifts or otherwise, without direct expenditures by the family, was requested also. In addition, farm families provided farm receipts, disbursements, changes in farm assets, and value of home-produced food. To supplement the annual data, non-farm families who prepared meals at home provided a detailed seven-day record, during the week prior to the interview, of expenditures for food and related items purchased frequently (e.g., tobacco, personal care, and household supplies). For selected items of clothing, house furnishings, and food, the record of expenditures was supplemented by information on quantities purchased and prices paid. Characteristics of the housing occupied by homeowners and renters and an inventory of the major items of house furnishing they owned also were recorded. Demographic information includes sex, age, years of school completed, occupation, race, and marital status of each family member.