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Consumer Expenditure Surveys

Consumer Expenditure Surveys Tables: Getting Started Guide

This page provides information about concepts, types, structure, uses, and considerations related to the Consumer Expenditure Surveys (CE) tables.

If users have comments or questions about this page and its contents, contact us.

Table of Contents

Section 1. CE program
Section 2. Table concepts
Section 3. Table types and structure
Section 4. Table uses
Section 5. Table considerations

Section 1. CE program

The CE program provides data on expenditures, income, and demographic characteristics of consumers in the United States. The CE program provides these data in tables, public-use microdata files (PUMD), publications, and LABSTAT databases.

The Census Bureau collects CE data for the Bureau of Labor Statistics (BLS) in two surveys, the Interview Survey for major or recurring items and the Diary Survey for more minor or frequently purchased items. CE data are primarily used to revise the relative importance of goods and services in the market basket of the Consumer Price Index (CPI). While the CE data are most notably associated with the CPI, the CE data have a long list of stakeholders in both federal and private-sector organizations. The CE program conducts the only Federal household survey that provides information on the complete range of consumers' expenditures and income. For more information on the program, see the overview section in the BLS Handbook of Methods.

The CE program publishes calendar year tables once a year in September. The CE tables are aggregated expenditure data, organized to show patterns and relationships among various socioeconomic groups. Vertical columns within each table define and distinguish those socioeconomic groups. Horizontal rows stored in the Item column define and organize each item into either consumer unit characteristics, expenditures, income, assets, or liabilities. Each group and item intersection represents one of several different statistics used to analyze and interpret consumer spending.

All published tables use data from both CE surveys: the weekly (Diary Survey) and quarterly (Interview Survey). Each year, items listed in the tables may be adjusted to account for additions, deletions, or survey source changes. These adjustments are performed to account for survey enhancements, which are aimed at improving the accuracy of the data and reducing respondent burden. For more information on where an estimate is sourced from and how this designation is determined, see How does the CE program select a survey to source an item?

The Interview Survey generally adds or deletes items at the start of data collection in April. To identify these expenditures in any given year, users can view the integrated hierarchical grouping files (e.g., CE-HG-Integ-2013.txt) located in the Hierarchical Groupings zip folder on the Public-Use Microdata documentation page. The items that were end dated in a particular year will have their titles annotated with a "from" or "thru" quarter remark, such as in the 2013 tables with Residential telephone/payphones (thru Q20131). While this series only contributed 1/12th of a yearly expenditure to the 2013 annual estimate, the remaining 11/12ths contribution came from the new series "Residential telephone including VOIP (new UCC Q20132)," which was annotated with a "new," along with the quarter for which it was introduced.

Diary Survey data are collected for a week of expenditures and multiplied by 13 to create quarterly estimates for use in the annual tables. New items begin in January and will have a full year of data, while the ending items have data through December and do not appear in the next year's annual tables. For the processing of two-year data, the ending items may be kept depending on the change type.

Tables present estimates that utilize income and expenditure data incurred during 12 or 24 month periods. A table's scope is particularly important for estimates sourced from the Interview Survey, which collects data that respondents recall from up to 12 months prior to the interview. Some CUs, depending on when they are interviewed, may only have a portion of their data contribute to the overall estimate, as some of their income or expenditures may have been recalled from a point in time outside of the scope of the table. For example, respondents interviewed in January 2022, would have reported expenditures recalled from the previous 3 months: October, November and December of 2021. These expenditures were not included in the 2022 annual tables, but instead, were included as part of the 2021 annual tables.

Section 2. Table concepts

  • What is a consumer unit (CU)?
    Most CUs consist of persons who are related by blood, marriage, or adoption. However, CUs may also consist of individuals living with others but are financially independent, or persons living together and making joint financial decisions. For more information on CUs, see the complete definition of a CU in the CE Glossary.

  • Who is the reference person?
    The reference person is identified as the first CU member mentioned by the respondent, who is considered to either own or rent the home. It is with respect to this person that the relationship of the other CU members is determined.

  • How are estimates presented in the table?
    Table columns are defined using characteristics based on either the CU or the reference person. Table 1 below presents these characteristics and identifies whether they are presented at the CU level or by the reference person. While several tables are indeed defined utilizing a characteristic of the reference person, all table estimates reflect income and expenditure data at the CU level. Some characteristics can be considered to be defined at either the CU level or by the reference person and are designated as such below.

    Table 1: Demographic characteristics by CU and reference person
    Unit Characteristics

    Consumer unit

    CU composition, income before taxes by selected groups, quintiles, and deciles, number of earners, size of CU, and highest education level of any CU member
    Reference person Age ranges, age splits , generation, Hispanic, race, and occupation

    Both units

    Population size of area, region, type of area, Metropolitan Statistical Areas (MSA), division, and housing tenure
  • What statistics do the tables present?
    The tables provide the following statistics:
    • Average expenditures (mean) are the average dollar amount per item for all CUs. This figure provides users a sense of how much money a CU spends on average for a particular item or group of items. Averages are provided using all CUs rather than only those that purchased the item. For information on the difference between the average expenditure and the average purchase price, see why do reported averages appear lower than expected?
    • Aggregate expenditures are the total amount spent by all CUs as a whole. These values are expressed in millions of dollars and provide users a sense of the total dollars spent on a particular item.
    • Aggregate expenditure shares are the portions of aggregate expenditures (as percentages) allotted to distinct expenditure groups. This figure provides users a sense of how spending is allocated within and across various groups.
    • Standard errors (SE) are a measure of the uncertainty in a survey's estimates caused by the use of data from a representative sample of households rather than a complete universe of households. Standard errors are the most common measure of sampling variability of a survey's estimates. Defined as the square root of the survey estimate's variance, they measure how much the estimates would vary if the survey could be repeated using a different sample of households every time. SE's provide a general measure of an estimate's precision and are used to determine whether differences between various expenditure estimates are statistically significant.
    • Relative standard error (RSE) is the ratio of the SE to the mean of the expenditure.
    • Percent reporting is the percent of CUs that actually reported an expenditure. This figure allows users to assess how prevalent an item is purchased and to estimate weekly or quarterly expenditure means for CUs that actually reported an expenditure. 
  • What time periods do the tables cover?
    The tables can cover one of two time periods:

    • Calendar year tables include purchases from January to December of a given year, e.g., January 2019 through December 2019.
    • Two year tables include purchases from January of a given year to December two years later, e.g., January 2018 through December 2019.

  • How does the CE program select a survey to source an item?
    The CE program selects an item from one of the two surveys to use in table estimation if both surveys collect the same item. The CE program chooses the source with the higher mean of the two estimates if that higher mean is statistically significant. For more information, see CE source selection for publication tables. For a complete list of the source selection from 1996 forward, see the source selection file.

  • How does the CE program estimate income tax?
    The CE program has estimated income taxes since 2014 using a program called TAXSIM. TAXSIM is a FORTRAN program created and supported by NBER that calculates liabilities under the U.S. Federal and State income tax laws. The program is updated annually for both current year tax code changes and improvements to previous years' code. For more information on income tax estimation, see New CE income tax estimates.

Section 3. Table types and structure

  • What table types does the CE program publish?
    Tables present estimates in a multitude of different ways, with varying levels of detail. Table 2 below presents an overview of these table types and includes additional details about what is included on each table, specifically the statistics, the number of socioeconomic table breakouts, the number of detailed items, and the number of years' of data used to develop the estimates.

    Table 2: Types, detail, statistic, number of months, and access
    Table type Statistic included in table Table breakouts Items per table Years used in estimation
    Means, share, and variances calendar year Means, shares, SE, and RSE 17 ~200 1
    Multiyear all CU Means 1 ~200 1
    Aggregate calendar year Aggregates and shares 17 ~200 1
    Cross-tabulated, region, and population size of area Means 38 ~200 or fewer 2
    Region and division Means, SE, and RSE 2 ~200 or fewer 2
    State Means 5 ~200 or fewer 2
    Metropolitan statistical area (MSA) Means 4 ~50 2
    Detailed integrated all CU calendar year Percent reporting, means, SE, and RSE 1 ~1000 1
    Detailed integrated year  (Available upon request) Means, SE, and RSE 17 ~1000 1
    Detailed Interview Survey (Available upon request) Means, SE, RSE, and percent reporting 17 ~650 1
    Detailed Diary Survey (Available upon request) Means, SE, RSE, and percent reporting 17 ~400 1
  • What items are included in the tables?
    The item column within each table distinguishes the number of CUs in the sample, CU characteristics, expenditures, income, income taxes, and an addenda, which contains information on holdings of assets and liabilities, as well as expenditure estimates for items identified as gifts.

    Beginning with the 2020 midyear tables, gift expenditures will not be included in the table addenda and will only be available upon request as part of the detailed Interview Survey tables described in Table 2 above. Particular tables may provide more or less detail, depending on the table type. Table 3 below presents items found on the CE tables using six broad categories and defines the statistics associated with each.

    Table 3: Basic structure of CE tables
    Type of information Item Statistic
    Number of CUs
    • Number of CUs in thousands
    Sum total
    CU characteristics
    • Income by CU before taxes
    • Income by CU after taxes
    Mean, SE, and RSE (%)
    • Age of reference person
    • People, children under 18, adults 65 and over, earners, and vehicles
    Average number in CU
    • Sex, race, ethnicity, and education of reference person Housing tenure of and at least one vehicle in CU
    Percent distribution among characteristics
    • Food, housing, apparel and services, transportation, healthcare, entertainment, and other items
    Mean, SE, share, and RSE (%)
    • Wages and salaries, self-employment income, retirement income, interest, public assistance, unemployment payments, and other income
    Mean, SE, and RSE (%)
    Income taxes
    • Personal taxes, Federal taxes, State and local taxes, and other taxes
    Mean, SE, and RSE (%)
    • Liabilities, including net change in total assets, change in loan principals, and other financial information
    Mean, SE, and RSE (%)
  • What expenditures do the tables list?
    The tables list and organize expenditures into 14 broad categories. Each of these categories is broken out into more detailed expenditure classifications. Expenditures that could not be initially classified are included in the miscellaneous category of expenditures.

    Tables provide varying levels of detail, depending on the statistical validity and availability of data for a given characteristic. Table 4 below lists the broad expenditure types and the components that most CE tables include.

    Table 4: Expenditure types
    Expenditure types Detailed expenditures
    Food Food at home
    Food away from home
    Alcoholic beverages Alcoholic beverages at home
    Alcoholic beverages away from home
    Housing Shelter
    Utilities, fuel, and public services
    Household operations
    Housekeeping supplies
    Household furnishings and equipment
    Apparel and services Men and boys
    Women and girls
    Children under 2
    Other apparel products and services
    Transportation Vehicle purchases (net outlay)
    Gasoline, other fuels, and motor oils
    Electric vehicle charging
    Other vehicle expenses
    Public and other transportation
    Healthcare Health insurance
    Medical services
    Medical supplies
    Entertainment Fees and admission
    Audio and visual equipment and services
    Pets, toys, hobbies, and playground equipment
    Other entertainment supplies, equipment and services
    Personal care products and services Personal care products
    Personal care services
    Reading Newspapers, magazines, newsletters, books, encyclopedia and other sets of reference books, and digital book readers
    Education Tuition, student loans, test preparation and tutoring services, and school supplies
    Tobacco products and smoking supplies Cigarettes, other tobacco products, smoking accessories, and marijuana
    Miscellaneous Miscellaneous fees, lotteries, ad pari-mutuel losses, and miscellaneous personal services
    Cash contributions Cash contributions
    Personal insurance and pensions Life and other personal insurance
    Pensions and social security
  • What do total expenditures exclude?
    Total expenditures exclude business expenses and outlays on the principal of loans. While outlays on the principal of loans are excluded from total expenditures, they are included in the net change in total liabilities within the addenda. Interest charges associated with a loan are included as part of total expenditures.

  • Are expenditure items missing from the table?
    Some items may seem to be missing from the tables because of two main reasons:
    • Items are only listed once to avoid double counting in the aggregation of total expenditures. Items could presumably feed other categories, and users are free to customize and or manipulate categories as they see fit.
    • Some expenditures are combined with others into a single item to allow an estimate to be developed. For example, instead of presenting "Toys", "Games", "Arts and Crafts" and "Tricycles" separately, the CE tables group them into one item "Toys, games, arts and crafts, and tricycles."
  • Does the CE program prepare tables with additional detail?
    The CE program prepares calendar year with additional detail. Users interested in obtaining additional expenditure detail can access the All CU Prepublication means, variances, and percent reporting (MVP) tables, which contain the most detailed set of expenditure estimates calculated by the CE. Detailed tables produced by varying demographics are available upon request by contacting the CE program.

    Guidance to the user: Caution should be taken when analyzing expenditure subcategories on these tables. Users need to consider that some estimates on these tables are subject to high variance. For more information on variability, see How does the variability of Consumer Expenditures data impact your analysis.

  • How does the survey treat gifts?
    Beginning with the 2020 midyear tables, gifts will be excluded from the tables. For years prior, gifts that the surveyed CU gives to others outside the CU are considered expenditures. Financial gifts received by the surveyed CU are considered income. Any non-financial gift received by the CU is not included in either income or expenditures.

Section 4. Table uses

This section discusses selected uses and considerations for working with the tables.

Users can investigate many topics with the CE tables, including comparisons of mean expenditures and expenditure shares for different demographic groups. Such comparisons can be made within a single time period (e.g., calendar year) or over time (e.g., trend analysis).

In addition, users may investigate table estimates further with either the LABSTAT databases, CE publications, or CE PUMD. To learn more about these products, see the introduction to the CE data products.

  • What calculations do tables enable data users to perform?
    The data associated with item characteristics listed first within each table can be used in tandem with either the income or expenditure estimates to create additional analysis figures. In order to perform these calculations correctly, the components of the calculation need to be sourced from the same survey. The survey source for a particular estimate can be identified in the source selection file. Users may also request Interview only or Diary only tables to perform these calculations by contacting the CE program.

    The combined calendar year, multiyear, geographic, and cross tab tables can be used to develop these estimates:

    • Total number of people in a demographic group: Multiply the number of CUs in a demographic group by the average number of people in a CU for that group. For example, in 2019, the tables estimated 132,242,000 CUs in the United States. This value multiplied by the average number of people per CU (2.5) produces an estimate of 330.6 million persons.

    • Average income per earner in CU: Divide the average CU income by the number of earners in the CU. For example, in 2019, the tables estimated an average income for all CUs of $82,852. Dividing this estimate of income by the average number of earners (1.3) produces an estimated average income per CU earner of $63,732.

    • Average annual expenditure per CU member: Divide the average expenditures of the CU by the respective number of CU members. For example, in 2019, the average total expenditures for all CUs was $63,036. Dividing this total by the number of CU members (2.5) produces a total expenditure estimate of $25,214 per CU member. Users can calculate similar estimates with the other averages provided as well (Number of children under 18, Adults 65 and older, and Number of vehicles).

    • Aggregate annual expenditures by demographic group: Multiply the average annual expenditures for the demographic group by the total number of CUs in that demographic group. For example, in 2019, the average food expenditure for CUs with a reference person under the age of 25 was $5,835. Multiplying this average food expenditure by the number of CUs in that category (7,328,000) produces an estimated $43 billion.

    • Detailed level aggregate expenditure shares: Divide the component expenditure by the total expenditure for the category it feeds and multiply the result by 100. For example, in 2019, the average Food at home expenditure was $4,643. Dividing the average Food at home expenditure by the total food expenditure ($8,169) produces an estimate of about 57 percent of Food at home, as a percent of total food.

    • Savings rate: Divide average annual expenditures by the Income after taxes for a particular demographic group, multiply the result by 100, and subtract the result from 100. For example, in 2019, the average annual expenditures for all CUs were $63,035. Dividing this average expenditure by the Income after taxes ($71,487) produces an estimate of about 88 percent spending rate or 12 percent savings rate.

    The aggregate calendar year tables can be used for these estimates:

    • Aggregate annual expenditures by demographic group: Multiply the total expenditures for all CUs by the share of the expenditures for the group of interest. For example, in 2019, the total expenditure on Food for all CUs was $1,078,750. Multiplying this figure by the share of the CUs with reference persons 25 years or younger (0.041%) produces an estimated $44,229.

    • Average rent expenditures by renters: Divide the aggregate annual rent expenditure of all CUs by the number of CUs that pay rent and multiply the result by 1,000 to adjust the units into billions. For example, in 2019, 47,607,000 CUs paid rent. This figure is calculated by taking the total number of CUs (132,242,000) and multiplying it by the percent of renters (36%). To calculate the average rent, divide the aggregate ($586,042,000) rent by the number of rent-paying CUs (47,607,000) to obtain an annual estimate of $12,310.

    The detailed calendar year tables can be used for this estimate:

    • Reported values only: In calculating the mean expenditure only for those reporting that expenditure, both the mean expenditure for the group as a whole and the percent reporting must cover the same time period (quarterly or weekly). The integrated mean expenditures found in the CE tables are annualized figures, whereas the percent reporting figures are either quarterly (Interview Survey estimates) or weekly (Diary Survey estimates). Thus, mean expenditure figures from the Interview Survey must be divided by four, and mean expenditure figures from the Diary Survey must be divided by 52, before dividing by the percent reporting to obtain the mean of those reporting. For example, in 2021 the mean annual expenditure for "Furniture" was $715.60, with a quarterly percent reporting of 15.22. The mean for the group as a whole includes both purchasers and non-purchasers. To calculate the mean only for those reporting this expenditure, first convert $715.60 from an annual number to a quarterly number: 715.60/4=$178.90. Next, divide the quarterly figure by the percent reporting: $178.90/0.1522=$1,175.43. That is, the average amount spent in a quarter by those actually purchasing Furniture is $1,175.43. IMPORTANT: This number cannot be annualized by multiplying by 4 (in the Interview Survey, or by 52 in the Diary Survey) in most cases. The less frequent the purchase, the more apparent this becomes. Consider expenditures for new cars in 2021. According to the Interview Survey, the average annual mean expenditure for all consumer units was $498.59, with an average quarterly percent reporting of 0.38. Applying the formula above, the average of the quarterly mean expenditures for those purchasing a new car was $32,801.97. (Note that the denominator is 0.0038.) Presumably, nearly all of these consumer units bought one car in the typical quarter of 2021. However, annualizing the figure would yield a mean of over $130,000, implying that those who purchased bought four cars in 2021, which is not likely to have occurred. NOTE: Percent reporting figures for tables prior to 2008 were found to be low and should be used with caution. The improved methodological formula used to adjust collection quarter percent reporting to expenditure year tables first applies for the 2008 tables and continues to apply for all subsequent years. Note: Percent reporting is not available for summary categories on the tables. For more information on why percent reporting is not available for all summary categories, please see Why is percent reporting not available for summary categories on the tables?

  • What does the number of CUs on each table represent?
    The number of CUs represents the estimated number of households in a particular socioeconomic group. However, CUs do not match households exactly. For the exact definition of a CU see the CE Glossary. It is expressed in thousands and listed in the first row of the tables. For example, in 2019, the tables list 132,242 CUs in the United States. This number, being expressed in thousands, represents 132,242,000 CUs in the United States.

    While this figure applies to the expenditures and income statistics, which all come from the Interview Survey, it cannot be used in conjunction with items that come from the Diary Survey. For the All consumer units column, the number of CUs in each survey is close, but for the columns with subsets of the total population, this figure's disparity can be significant. For example, using the Income prepublication table from 2016, the CE program has an All consumer unit column Diary Survey weight that is 99.9 percent of the Interview Survey weight (129,461,459 of 129,549,180). The Less than $15,000 income column on the other hand, has a Diary Survey weight that is only 92.5 percent (16,074,138 of 17,367,961) of the Interview Survey weight. The full Interview and Diary Survey column weights can be found at the very last rows of the integrated prepublication tables, available on request.

Section 5. Table considerations

    • How does variability affect estimates?
      Variability limits the ability to use the data with certainty. Measures of variability inform users about the range of possible values for a particular data point. The tables utilize standard errors to quantify variability. Generally, the larger that range of possible values is, the lower the data point's reliability. For more information on variability, see How does the variability of CE data affect the estimates?

      Care should be taken when analyzing detailed expenditure subcategories in the tables, as a small number of CUs reporting an expenditure can cause the mean dollar estimate to be imprecise. Users should consider the coefficient of variation (CV) for tables with annual data prior to 2022 and the Relative Standard Error (RSE) for tables with annual data for 2022 and later that are published with the dollar amounts. For further information on the standard error and variance in the CE data, see Standard Errors in the 2016 Consumer Expenditure Survey.

    • Why are some data suppressed in the published tables?
      Beginning with the 2022 tables publication, BLS includes data suppressions for estimates with a Relative Standard Error (RSE) of 25 percent or more. RSE is defined as the ratio of the mean to its standard error (SE). For any estimate with an RSE that equals or exceeds the 25 percent threshold, the mean expenditure, SE, expenditure share, and RSE will be suppressed. The BLS CE program determined that estimates with RSEs of 25 percent or more were considered unreliable. RSEs tend to be smaller for the nationwide estimates than for smaller demographic groups. This is primarily due to their different sample sizes. In general, RSEs decrease as the sample size “n” increases. RSEs often decrease as the frequency of purchases increases. Infrequently purchased items are more susceptible to large RSEs while frequently purchased items tend to have smaller RSEs. While data are suppressed in the tables estimates, users can still use the CE Public Use Microdata to obtain estimates suppressed in published tables.

    • What can data users discern from the average number of members in a consumer unit?
      The average number of members in a CU can shed light on per capita expenditures as opposed to average expenditures by the CU as a whole. For example, the 2016 income by quintile table lists the mean food expenditures by the lowest quintile as $3,862 and by the highest as $12,513. Although the two columns each represent an equal number of weighted CUs, they are not similar in size. Taking into account that the lowest quintile has an average of 1.6 people per CU while the highest quintile has 3.1 people, the apparent difference per person changes considerably as seen in Table 5. Per-capita food spending by the top quintile was almost two times higher than the lowest quintile: $4,036 compared to $2,414.

    • What can the average number of earners in a consumer unit tell us about components of wages and salaries?
      Users may want to consider the average number of earners in a CU when looking at the wages and salaries subcomponent of money income before taxes. In the published version of the 2016 Quintile table, users can see that the lowest quintile has on average one half an earner per CU while the highest quintile has on average two earners per CU. In addition, users see that for the first quintile, wages and salaries ($3,472) make up 30 percent of their total income. In the highest quintile, the wages and salaries ($159,681) make up 80 percent of their income. If one is interested in a CU's earnings, they can use our Number of Earners in the consumer unit table where they can easily compare a one earner to a two earner CU.

      Table 5: Difference between average CU spending and per capita spending on food for Adults 65 and older
      Item description Per CU spending Per capita spending Average CU size
      Highest quintile $12,513 $4,036 3.1
      Lowest quintile $3,862 $2,414 1.6
    • What can CE data tell us about older adults?
      Data users interested in analyzing seniors can access the Age table, which contains a column where the CU's reference person is 65 or older. Looking at the 2016 data, the Adults 65 and older row shows that they make up about three-quarters of the population in the column: 1.4 of the 1.7 average number of people. Users can use the data from the 65 or older column in conjunction with the other age brackets to make inferences about spending behavior as it related to age.

    • What can the average number of vehicles in a consumer unit tell us about transportation expenditures?
      The average number of vehicles in consumer units includes both owned and leased vehicles and can be used to compare transportation expenditures. It would be a factor to consider when looking at expenditures for items such as Vehicle insurance, Gasoline, other fuels, and motor oil, and Other vehicle expenses.

    • Why is percent reporting not available for summary categories on the table?
      The percent of consumer units making an expenditure can only be reported covering the time period for which the data were collected. For example, the percent reporting for Vehicle insurance is per quarter, and all CUs do not pay car insurance premiums every three months. The percent reporting will be weekly or quarterly, depending on the survey used as the source of that expenditure item. Aggregated rows that have data from both surveys do not have a percent reporting calculation because expenditure amounts from each survey represent different time periods (quarterly vs. weekly), which disallows the development of a percent reporting figure at the aggregate level. To see the percent reporting numbers for disaggregated rows, users can request the Interview or Diary Survey prepublication tables. With these tables, one can answer such questions as: "What was the average expenditure per week on rice for consumer units actually purchasing rice?" or "What was the average quarterly expenditure on Cellular phone service of those in the middle quintile who actually reported such an expenditure?"

    • Do the CE tables provide consumption data?
      No, the tables do not provide data on consumption. The tables only provide data on expenditures. While the two concepts may be similar at times, they have important conceptual differences that do not allow users to use them interchangeably.

    • What specific products and services does an estimate include?
      The CE tables do not include details about specific products and services that would allude to particular brands or businesses. However, users can consult the Information Booklet to indicate where specific products and services may have been collected. The Information Booklet and other survey material are on the CE Survey Materials page.

    • Is the reference person representative of the CU?
      The reference person may not be representative of all other CU members. For example, the reference person may have a different age, race, or ethnicity from the other CU members. This concept is important to consider when interpreting table estimates derived using characteristics of the reference person.

    • Do the tables provide expenditures by sex?
      Yes, users can find expenditures by sex for single-person households. However, within multi-member CUs, CE data do not allow users to identify which person(s) made an expenditure. For example, one CU member could have bought groceries for all CU members, or two members might have shared the expenses of a single expenditure.

    • Why do reported averages appear lower than expected?
      The published estimates may appear lower than the expected expenditures because the published estimates are the share for all CUs in the sample, including those that did not make the expenditure in question. Table 6 shows the difference between the published average expenditure of all CUs in the sample versus the average by only those CUs that purchased an item.

      Table 6: Difference between published averages and average purchase expenditure
      Item description Published average Average expenditure
      CUs included All sampled CUs Sampled CUs that bought the item
      Number of CUs considered 10 2
      Aggregate expenditure $100 $100
      Average expense $10 $50

      Data users may notice lower average mortgage, rent, or healthcare payments. While the same principle applies, there may be additional factors in play.

      • Mortgage payments may seem low because they exclude principal payments. In addition, many CUs do not pay mortgages because they rent or because they paid their mortgage off. In these cases, the data include all CUs in the denominator, but only those with mortgages in the numerator, similar to the situation described in table 6.

      • Healthcare expenditure estimates only include out-of-pocket expenses, rather than the total cost of health care also covered by insurance. Thus the healthcare expenditures may seem lower than expected. Similarly, only the out-of-pocket part of the health insurance premiums are shown in these tables.

      • Rent may seem low on certain tables if the table estimates were developed using all CUs because the rent item represents the share for all households, including those who own their home. In the United States, about 60 percent of households own their home and do not pay rent. To obtain a better estimate for rent and renter expenditures, users should access the CE Housing tenure and type area table and look at just the subset of renters in the Renters column. The same can be said for Homeowners for those interested in looking at expenditures specifically for those with a mortgage and those without.

    • Are negative values for items possible?
      Negative values are possible. Negative expenditure values are associated with reimbursements, mostly for medical expenditures. Negative income values can be due to business losses, among other reasons.

    • Why do total expenditures outweigh income after tax from some groups?
      Some groups may spend more money than they earn because they live off retirement or savings, or borrow through loans or credit. In addition, CUs may consist of students who are supported by their parents. For more information, see Use with caution: interpreting Consumer Expenditure income data.

    • Why are there differences between the estimates in the tables and the LABSTAT database?
      Rounding may create slight differences between the estimates in the tables and those found on the LABSTAT database. For more information on the LABSTAT database, see the LABSTAT Getting Started Guide.

    • How does the CE data compare to data from other organizations?
      Other organizations' data may differ from the CE program's data even though they may seem to cover the same concept. The differences may be due to different sources, methods, and presentation. For more information, see the CE data comparisons page.



Last Modified Date: September 11, 2023

  • Why are some data suppressed in the published tables?
    Beginning with 2022 tabular publication, BLS will include data suppressions for estimates with a Relative Standard Error (RSE) of 25 percent or more. For any estimate that equals or exceeds the 25 percent threshold, the mean expenditure, standard error, expenditure share, and RSE will be suppressed. The BLS CE program determined that estimates with RSE's of less than 25 percent were considered reliable for publication purposes. While data are suppressed in the tables estimates, users can still use the CE Public Use Microdata to obtain estimates suppressed in published tables.
  • Why are some data suppressed in the published tables?
    Beginning with 2022 tabular publication, BLS will include data suppressions for estimates with a Relative Standard Error (RSE) of 25 percent or more. For any estimate that equals or exceeds the 25 percent threshold, the mean expenditure, standard error, expenditure share, and RSE will be suppressed. The BLS CE program determined that estimates with RSE's of less than 25 percent were considered reliable for publication purposes. While data are suppressed in the tables estimates, users can still use the CE Public Use Microdata to obtain estimates suppressed in published tables.