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.

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.

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.

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]

Media and entertainment spending patterns in the United States reveal intriguing age-related disparities. A late-2024 study found that Americans spent an average of 1,399 U.S. dollars annually on digital media and entertainment, a slight decrease from two years prior. Notably, consumers aged 35 to 54 outspent other age groups, allocating 1,610 U.S. dollars per year to digital media consumption. Generational differences in media spending The rise of digital platforms has transformed how different age groups consume media. While 66 percent of the general population spent less than 1,000 U.S. dollars on media and entertainment annually, this figure rose to 77 percent for those aged 55 and older. Interestingly, it is not the youngest age group that was ready to spend more on media subscriptions, services and products, but millennials - their annual expenses were more likely to reach up to five thousand U.S. dollars. This disparity suggests that younger and older generations may be more frugal with their entertainment choices. Consumption follows similar age patterns The spending behavior is a direct result of how different generations consume media. Data on time spent with media types in the United States clearly suggest that millennials favor the more expensive ones - they devote more of their weekly hours to TV connected devices and video on a computer, as well as apps on tablets and internet on a computer. These media are the ones hosting the majority of subscription services - hence the increased spending outcomes. Younger and older generations in this case seem to spend more of their time with free entertainment sources.

The survey studied the lifestyle and consumer habits of Finnish people. The respondents were asked to compare their lifestyle and consumer habits to the average consumer, and to give their opinions on consumption-related issues. The respondents were asked to evaluate their life situation at the time of the survey, in the past, and in the future on several aspects of life, such as financial situation and general welfare. They were also asked to compare their expenditure and consumer behaviour (concerning e.g. food, housing, leisure activities, alcohol, travel) to those of the average consumer. Furthermore, the respondents were asked which things and household items they considered necessary and what they would have done had they had more money. The survey carried a set of attitudinal statements about consumption and lifestyle (e.g. "I often buy things that are on sale" or "Quality is more important to me than price"). Some questions covered on what grounds respondents make decisions on economical, family or work matters. Questions on social integration measured how closely the respondents felt that they were a part of their family, workplace, Internet communities, Finnish society, European Union etc. The respondents were also asked which generation and social class they most closely identified with. Opinions on values were measured by asking the respondents to rate the importance of various things (e.g. self-respect, world peace, prosperity, independence). Furthermore, the respondents were asked about the safety and security of their own life, relationships, European integration, Finnish society, and the world. The respondents feelings of insecurity were measured by asking them about risks at the personal level (unemployment, gambling, casual sexual encounters, etc.), and at the level of society (immigration, different types of crime, terrorism, environmental problems, etc.). The survey contained questions about the income, expenditure, savings and debts of the respondents and the household. Quickie loan use and possible bad credit were charted. Respondents were asked about their methods of coping when short of money (borrowing, reducing expenditure, gambling, etc.) Background variables included the respondent's gender, year of birth, marital status, household size, basic and vocational education, economic activity, occupation, party preference, experiences of unemployment, and financial circumstances as well as the number of children, occupations of the spouse and parents, and voting in elections.

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

This statistic shows average annual expenditure on jewelry and valuables per consumer unit in the United States from 2018 to 2023, by category. In 2023, the country's average annual expenditure on jewelry amounted to 108.82 U.S. dollars per consumer unit.

In 2023, the lowest 20 percent of income consumer units spent about 41.3 percent of their total expenditure on housing. Consumer units belonging to the highest 20 percent of income spent only 29.2 percent on housing. Additionally, those in the highest income quintile spent 17.7 percent of their total expenditure on personal insurance and pensions, while the lowest 20 percent spent only 2.1 percent.

The total consumer spending in Spain was forecast to continuously increase between 2024 and 2029 by in total 210.7 billion U.S. dollars (+22.49 percent). After the seventh consecutive increasing year, the consumer spending is estimated to reach 1.1 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.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Surveys related to the family budget are considered one of the most important surveys types carried out by the Department Of Statistics, since it provides data on household expenditure and income and their relationship with different indicators. Therefore, most of the countries undertake periodic surveys on household income and expenditures. The Department Of Statistics, since established, conducted a series of Expenditure and Income Surveys during the years 1966, 1980, 1986/1987, 1992, 1997, 2002/2003, 2006/2007, and 2008/2009 and because of continuous changes in spending patterns, income levels and prices, as well as in the population internal and external migration, it was necessary to update data for household income and expenditure over time. Hence, the need to implement the Household Expenditure and Income Survey for the year 2010 arises. The survey was then conducted to achieve the following objectives: 1. Provide data on income and expenditure to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. 2. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index. 3. Provide the necessary data for the national accounts related to overall consumption and income of the household sector. 4. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty. 5. Identify consumer spending patterns prevailing in the society, and the impact of demographic, social and economic variables on those patterns. 6. Calculate the average annual income of the household and the individual, and identify the relationship between income and different socio-economic factors, such as profession and educational level of the head of the household and other indicators. 7. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

The General Census of Population and Housing in 2004 provided a detailed framework for housing and households for different administrative levels in the Kingdom. Where the Kingdom is administratively divided into 12 governorates, each governorate is composed of a number of districts, each district (Liwa) includes one or more sub-district (Qada). In each sub-district, there are a number of communities (cities and villages). Each community was divided into a number of blocks. Where in each block, the number of houses ranged between 60 and 100 houses. Nomads, persons living in collective dwellings such as hotels, hospitals and prison were excluded from the survey framework.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Household Expenditure and Income survey sample, for the year 2010, was designed to serve the basic objectives of the survey through providing a relatively large sample in each sub-district to enable drawing a poverty map in Jordan. A two stage stratified cluster sampling technique was used. In the first stage, a cluster sample proportional to the size was uniformly selected, where the number of households in each cluster was considered the weight of the cluster. At the second stage, a sample of 8 households was selected from each cluster, in addition to another 4 households selected as a backup for the basic sample, using a systematic sampling technique. Those 4 households were sampled to be used during the first visit to the block in case the visit to the original household selected is not possible for any reason. For the purposes of this survey, each sub-district was considered a separate stratum to ensure the possibility of producing results on the sub-district level. In this respect, the survey framework adopted that provided by the General Census of Population and Housing Census in dividing the sample strata. To estimate the sample size, the coefficient of variation and the design effect of the expenditure variable provided in the Household Expenditure and Income Survey for the year 2008 was calculated for each sub-district. These results were used to estimate the sample size on the sub-district level so that the coefficient of variation for the expenditure variable in each sub-district is less than 10%, at a minimum, of the number of clusters in the same sub-district (6 clusters). This is to ensure adequate presentation of clusters in different administrative areas to enable drawing an indicative poverty map. It should be noted that in addition to the standard non response rate assumed, higher rates were expected in areas where poor households are concentrated in major cities. Therefore, those were taken into consideration during the sampling design phase, and a higher number of households were selected from those areas, aiming at well covering all regions where poverty spreads.

Mode of data collection

Face-to-face [f2f]

Research instrument

To reach the survey objectives, 3 forms have been developed. Those forms were finalized after being tested and reviewed by specialists taking into account making the data entry, and validation, process on the computer as simple as possible.

(1) General Form/Questionnaire This form includes: - Housing characteristics such as geographic location variables, household area, building material predominant for external walls, type of tenure, monthly rent or lease, main source of water, lighting, heating and fuel cooking, sanitation type and water cycle, the number of rooms in the dwelling, in addition to providing ownership status of some home appliances and car. - Characteristics of household members: This form focused on the social characteristics of the family members such as relation to the head of the family, gender, age and educational status and marital status. It also included economic characteristics such as economic activity, and the main occupation, employment status, and the labor sector. to the additions of questions about individual continued to stay with the family, in order to update the information at the beginning of the second, third and fourth rounds. - Income section which included three parts · Family ownership of assets · Productive activities for the family · Current income sources

(2) Expenditure on food commodities form/Questionnaire This form indicates expenditure data on 17 consumption groups. Each group includes a number of food commodities, with the exception of the latter group, which was confined to some of the non-food goods and services because of their frequent spending pattern on daily basis like food commodities. For the purposes of the efficient use of results, expenditure data of the latter group was moved with the non-food commodities expenditure. The form also includes estimated amounts of own-produced food items and those received as gifts or in an in-kind form, as well as servants living with the family spending on themselves from their own wages to buy food.

(3) Expenditure on non-food commodities form/Questionnaire This form indicates expenditure data on 11 groups of non-food items, and 5 sets of spending on services, in addition to a group of consumption expenditure. It also includes an estimate of self-consumption, and non-food gifts or other items in an in-kind form received or sent by the household, as well as servants living with the family spending on themselves from their own wages to buy non-food items.

Cleaning operations

Raw Data

The data collection phase was then followed by the data processing stage accomplished through the following procedures: 1- Organizing forms/questionnaires A compatible archive system, with the nature of the subsequent operations, was used to classify the forms according to different round throughout the year. This is to effectively enable extracting the forms when required for processing. A registry was prepared to indicate different stages of the process of data checking, coding and entry till forms are back to the archive system. 2- Data office checking This phase is achieved concurrently with the data collection phase in the field, where questionnaires completed in the fieldwork are immediately sent to data office checking phase. 3- Data coding A team was trained to work on the data coding phase, which in this survey is only limited to education specialization, profession and economic activity. In this respect, international classifications were use, while for the rest of the questions, all coding were predefined during

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.

This dataset presents a comprehensive overview of household and per-capita income and expenditure patterns in various demographic, geographic, and socioeconomic contexts. It encompasses three main categories:Disposable IncomeConsumption ExpenditureFinal Monetary Consumption ExpenditureWithin each category, indicators detail averages, medians, and percentages across dimensions such as administrative region, nationality of the household head, age group, educational level, marital status, type of dwelling, type of ownership, household size, and income sources. The dataset thus enables in-depth analysis of how different factors influence income and expenditure.esearchers, policymakers, and analysts can employ these indicators to:Understand how household and per-capita incomes vary by social and economic factors.Examine consumption patterns and their drivers, including demographic variables.Analyze the final monetary consumption expenditure in more detail using COICOP divisions for targeted economic and social policy insights.In doing so, users can identify disparities, assess living standards, and formulate data-driven strategies to address economic and social challenges at both the household and regional levels.Notes:For the first time the methodology for calculating household disposable income and consumption expenditure is used in Household Income and Consumption Expenditure Survey of 2023

Amazon's shopping app has seen a significant increase in monthly downloads worldwide since January 2015, reaching a peak of approximately 55 million downloads in December 2020. However, the company faces stiff competition from emerging players in the global market. Rising competition in mobile shopping While Amazon remains a major player, Chinese retailers are making significant inroads in the mobile shopping space. In 2024, Temu became the most downloaded shopping app worldwide with nearly 550 million downloads, followed by Shein with about 235 million. Despite this competition, Amazon continues to maintain a strong presence, particularly in the United States, where it ranks as the second-most used shopping app among millennials. Generational differences Amazon's influence on consumer spending varies significantly across generations, with Generation X leading the pack in overall expenditure. In 2023, a study of iOS users in the United States revealed that Gen X shoppers spend an average of 124.2 U.S. dollars across all departments on Amazon, outpacing both Millennials and Gen Z. This generational divide in spending habits reflects broader trends in online shopping preferences and brand loyalty.

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The survey's main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To measure mean household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To define mean household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income and expenditure for commodities and services. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its sources and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to sources, either from household production or not, in addition to household expenditure for non-food commodities and services. - To identify distribution of households according to the possession of some appliances and equipment such as (cars, satellites, mobiles ...) in urban and rural areas. - To identify the percentage distribution of income recipients according to some background variables such as housing conditions, size of household and characteristics of head of household.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

• Household/families
• Individuals

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008/2009 HIECS is a two-stage stratified cluster sample, approximately self-weighted, of nearly 48000 household in urban and rural areas. The main elements of the sampling design are described below.

• Sample Size: It has been deemed important to retain the same sample size of the previous two HIECS rounds. Thus, a sample of about 48000 households has been considered. The justification of maintaining the sample size at this level is to have estimates with levels of precision similar to those of the previous two rounds: therefore trend analysis with the previous two surveys will not be distorted by substantial changes in sampling errors from round to another. In addition, this relatively large national sample implies proportional samples of reasonable sizes for smaller governorates. Nonetheless, oversampling has been introduced to raise the sample size of small governorates to about 1000 households. As a result, reasonably precise estimates could be extracted for those governorates. The oversampling has resulted in a slight increase in the national sample to 48658 households.

• Cluster size: An important lesson learned from the previous two HIECS rounds is that the cluster size applied in both surveys is found to be too large to yield an accepted design effect estimates. The cluster size was 40 households in the 2004-2005 round, descending from 80 households in the 1999-2000 round. The estimates of the design effect (deft) for most survey measures of the latest round were extraordinary large. As a result, the cluster size was decreased to only 19 households (20 households in urban governorates to account for anticipated non-response in those governorate. In view of past experience non-response is almost nil in rural governorates).

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document that is provided as an external resources in both Arabic and English.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires were used: 1- Expenditure and consumption questionnaire 2- Diary questionnaire for expenditure and consumption 3- Income questionnaire

Cleaning operations

Harmonized Data - The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets. - The harmonization process starts with cleaning all raw data files received from the Statistical Office. - Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization. - A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables. - A post-harmonization cleaning process is run on the data. - Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

For the total sample, the response rate was 96.3% (93.95% in urban areas and 98.4% in rural areas).

Sampling error estimates

The sampling error of major survey estimates has been derived using the Ultimate Cluster Method as applied in the CENVAR Module of the Integrated Microcomputer Processing System (IMPS) Package. In addition to the estimate of sampling error, the output includes estimates of coefficient of variation, design effect (DEFF) and 95% confidence intervals.

Data appraisal

The precision of survey results depends to a large extent on how the survey has been prepared for. As such, it was deemed crucial to exert much effort and to take necessary actions towards rigorous preparation for the present survey. The preparatory activities, extended over 3 months, included forming Technical Committee. The Committee has set up the general framework of survey implementation such as:

1- Applying the recent international recommendations of different concepts and definitions of income and expenditure considering maintaining the consistency with the previous surveys in order to compare and study the changes in pertinent indicators.

2- Evaluating the quality of data in all different Implementation stages to avoid or minimize errors to the lowest extent possible through: - Implementing field editing after finishing data collection for households in governorates to avoid any errors in suitable time. - Setting up a program for the Survey Technical Committee Members and survey staff for visiting field work in all governorates (each 15 days) to solve any problem in the proper time. - Re-interviewing a sample of households by Quality Control Department and examining the differences with the original responses. - For the purpose of quality assurance, tables were generated for each survey round where internal consistency checks were performed to study the plausibility of mean household expenditure on major expenditure commodity groups and its variability over major geographic regions.

In 2023, housing required the highest amount of consumer expenditure across all races, with Asian individuals spending the most. Additionally, Asian individuals spent more on personal insurance and pensions, as well as education than any other race.

The global total consumer spending on clothing and footwear in was forecast to continuously increase between 2024 and 2029 by in total 517.2 billion U.S. dollars (+22.47 percent). After the ninth consecutive increasing year, the fashion-related spending is estimated to reach 2.8 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 03. 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.

Consumption and consumer behavior of the population.

Topics: Drinking habits with non-alcoholic refreshments and alcoholic drinks as well as preferred brand; preferred type of wine and preferred area of origin; average amount of expenditure for a bottle of wine or champagne; spirits preference; type of one´s own forms of savings and investment; type of bank account and financial institute; possession of a Euro-check card; possession or planned acquisition of a credit card; detailed information on building loan contracts and insurance policies; short trips, vacation trips and tour operator; vacation destination and means of transport used on the short trip and vacation trips; frequency of mail-order purchases and amount of expenditure; mail-order company preference; department store purchase due to magazine ads; shopping place preference for clothing and durable economic goods; trips to fast-food restaurants; personal camera equipment or available in household; brand of one´s own camera; most important characteristics of a camera as well as planned acquisition and amount of expenditure; number and type of films purchased; frequency of use of diet foods; used tonics as well as frequency of consumption; frequency of use of pain-killers and type of complaints; self-treatment or decision of the doctor in choice of pain-killers; purchase of preparations against colds and headcolds; frequency of use of selected health preparations; preferred acne medicine; type of toys purchased; preferred brand of soap; frequency of use of bathing or shower salts, deodorants or body sprays, tooth paste, denture and hair care products as well as preferred brand; frequency of use of sun screens and preferred brand; frequency of use of selected body care products as well as preferred brand; last purchased brand of toilet water or perfume; consumption and frequency of use of foods from the areas of ready-to-eat products, breakfast drinks, milk products, cereal products, side-dishes as well as preferred brand; having a pet and frequency of use of pet food; possession of drivers license; number of cars in household; frequency of use of car and annual distance driven; new or used car; personal or company car; year of manufacture, displacement, manufacturer and model of car; type of tires and preferred brand of tires; type of vehicle fuel and preferred brand; preferred brand of motor oil; age and features of car radio; desired features of a car radio; brands of car considered in purchase considerations and preferred engine displacement; most important criteria in choice of a car brand; planned acquisition of a new car; consumer habits regarding selected confectioneries and snacks as well as preferred brand; smoking habits, use of tobacco products and preferred brand; possession, age and brand of selected products from the area of entertainment electronics and home computers; most important features of a television set; value of hifi equipment; planned acquisition of video camera, video recorder, CD player and home computer; preferred supplement equipment for a new television set; frequency and point in time of use of video recorder; cable connection in household or interest in cable connection; possibility of reception of teletext; use of Btx and presence of a Btx keyboard; preferred leisure activities; interest in information about selected products and services; dealing with money and need to prepare for the future, health consciousness, pleasure orientation, attitude to healthful nutrition, environmental consciousness, attitude to household as well as to residence and furnishing, cooking and baking as hobby, understanding of one´s role in marriage and partnership, attitude to external appearance, brand awareness, attitude to advertising, dealing with technology, consumption orientation, pioneering consumer behavior (scales); preferred living room style of furnishing; brand or price consciousness in purchase of selected products; number of pairs of glasses purchased in the last few years; media usage; housing conditions; planned measures to save energy; type of maintenance work conducted in household; planned purchase of one´s own home or condominium; having a garden and type of garden.

The following additional questions were posed to those in charge of household or heads of household: possession, age and brand of selected electrical appliances and planned acquisitions; type, age and brand of vacuum cleaner as well as of refrigeration equipment; preferred brand and frequency of use of detergent and mild detergents, fabric conditioners, dishwashing liquids as well as household cleansers; possession, age and planned acquisitions of selected electrical appliances for dental hygiene; consumption and frequency of use of ready-to-use products, instant soups and sauces, frozen products, ice cream, cornflakes, muesli, spices, cooking fats and oils as well as sauces.

The following questions were posed only to women: frequency of use...

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.