Consumer Spending in Brazil decreased to 225777.09 BRL Million in the first quarter of 2025 from 236836.06 BRL Million in the fourth quarter of 2024. This dataset provides - Brazil Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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 European Union increased to 1886.15 EUR Billion in the first quarter of 2025 from 1880.81 EUR Billion in the fourth quarter of 2024. This dataset provides - European Union Consumer Spending- actual values, historical data, forecast, chart, statistics, economic calendar and news.

When asked about spending intentions in August, about ** percent of consumers in the United States said the intended to spend less on items such as furniture, jewelry, home decorations, and accessories over the course of the next three months. For most categories, a significant share of shoppers expected to spend about the same as they usually do.

The global total consumer spending on clothing and footwear in was forecast to continuously increase between 2024 and 2029 by in total ***** billion U.S. dollars (+***** percent). After the ninth consecutive increasing year, the fashion-related spending is estimated to reach *** trillion U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case footwear-related spending, 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). The shown data adheres broadly to group **. 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 on clothing and footwear in countries like North America and Australia & Oceania.

Consumer Spending in Vietnam increased to 5579533 VND Billion in 2023 from 5231354 VND Billion in 2022. This dataset provides - Vietnam Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Consumer trends time series dataset up to Quarter 1 (January to March) 2025.

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.

Consumer Spending in Netherlands decreased to 104242 EUR Million in the second quarter of 2025 from 104626 EUR Million in the first quarter of 2025. This dataset provides - Netherlands Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

Consumer spending on traditional and emerging technologies is forecast to amount to *** billion U.S. dollars, marking a year-on-year growth of *** percent. Emerging consumer technologies include AR/VR headsets, drones, on-demand devices, robotic systems, and similar.

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.

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...

Consumer Spending in Poland increased to 538662.30 PLN Million in the first quarter of 2025 from 485739.50 PLN Million in the fourth quarter of 2024. This dataset provides - Poland Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The statistic depicts the results of a survey about the average U.S. consumer spending during Christmas season, i.e. in the last 5 weeks of the year from 2008 to 2010, by week. Even though the trend seems to indicate that people spent the most of their money in the first three weeks of December, in 2010 data differs slightly: spending has increased even more over the weeks with Christmas approaching more and more and consumers getting more eager - and maybe a little desperate - to find presents for their loved ones. While the respondents reported to have spent an average of 79 U.S. dollars in the last week of November 2010, they spent an average of 85 U.S. dollars in the 4th week of December in 2010.

Consumer Spending in Austria increased to 46028.87 EUR Million in the first quarter of 2025 from 45993.08 EUR Million in the fourth quarter of 2024. This dataset provides - Austria Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This statistic shows total domestic consumption expenditure in the United Kingdom (UK) from 2005 to 2023. In 2023, consumer spending in the UK increased compared to the previous year, and amounted to approximately 1.6 trillion British pounds. Household consumption expenditure looks at the overall spending on consumer goods and services of a wide variety. Some examples are government licenses and permits, such as a passport renewal or the price of train tickets to get to work. Housing may also be accounted for in these figures. This figure is measured by how much the consumer actually pays at the point of sale. All fast moving consumer goods such a beer, or cigarettes are also accounted for in this data. One part of the United Kingdom, Scotland, has seen as increase in its overall household expenditure year over year since 2009, with figures reaching over 100 billion British pounds in 2018. There was a small decrease in expenditure in 2009, which was possibly a result of the economic recession which hit all of the United Kingdom hard at this time. This drop can also be seen when looking at the whole of the United Kingdom in this statistic.

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 XVI. APPENDIX 5). The microdata are available on CD-ROMs. These microdata files present detailed expenditure and income data from the Interview component of the CE for 2008 and the first quarter of 2009. The Interview survey collects data on up to 95 percent of total household expenditures. In addition to the FMLY, MEMB, MTAB, and ITAB_IMPUTE files, the microdata include files created directly from the expenditure sections of the Interview survey (EXPN files). The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLY or MTAB files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure. Estimates of average expenditures in 2008 from the Interview Survey, integrated with data from the Diary Survey, will be published in the report Consumer Expenditures in 2008 (due out in 2010). 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, Interview Survey, 2008."

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 non-institutional 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 2008 and 2009 samples 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 MSA's. 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 2008 survey is generated from the 2000 Census of Population 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 (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. Interviewers are then assigned to list these areas before a sample is drawn. 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. The Interview Survey is a panel rotation survey. Each panel is interviewed for five consecutive quarters and then dropped from the survey. As one panel leaves the survey, a new panel is introduced. Approximately 20 percent of the addresses are new to the survey each month.

Mode of data collection

Computer Assisted Personal Interview [capi]

Graph and download economic data for Shares of gross domestic product: Personal consumption expenditures (DPCERE1Q156NBEA) from Q1 1947 to Q2 2025 about Shares of GDP, PCE, consumption expenditures, consumption, personal, GDP, and USA.

Consumer Spending in Kazakhstan decreased to 15660654.20 KZT Million in the first quarter of 2025 from 70979758.50 KZT Million in the fourth quarter of 2024. This dataset provides - Kazakhstan Consumer Spending - actual values, historical data, forecast, chart, statistics, economic calendar and news.