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This page provides information on the structure, uses, and considerations when using the Consumer Expenditure Surveys (CE) LABSTAT database.
Section 2. LABSTAT data availability
Section 3. CE LABSTAT Database Search Tools
Section 4. CE LABSTAT Database Data files
The Consumer Expenditure Surveys (CE) are nationwide household surveys conducted by the U.S. Bureau of Labor Statistics (BLS) to study how U.S. consumers spend their money. The surveys are the only federal government data collection effort to obtain information on the complete range of consumers’ expenditures, income, and demographic characteristics, directly from consumers. BLS publishes 12-month estimates of consumer expenditures annually, with the estimates summarized by various income levels and demographic characteristics. These estimates are stored as part of an online database (LABSTAT) enabling users a quick and efficient way to obtain information on consumer spending. This guide will describe how to work with the LABSTAT database as well as the LABSTAT text files. For more information on the program itself, see the Handbook of Methods Consumer Expenditures and Income page.
Data are grouped into one of four groups: expenditures, income and taxes, consumer characteristics, and assets and liabilities.
Mean estimates are available from 1984 onward. Standard errors for the mean and shares of expenditures are available from 2010 onward. Aggregate expenditures (for all consumer units in millions of dollars) and shares of aggregate expenditures (for all other characteristics) are available from 2011 onward.
Expenditures are organized into 14 categories. Each of these categories is broken out further into subcategories. Expenditures that could not be classified are included in the miscellaneous category. Table 1 below lists the expenditure categories and the subcategories available in the database.
Expenditure category | Expenditures categories |
---|---|
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 | |
Footwear | |
Other apparel products and services | |
Transportation |
Vehicle purchases (net outlay) |
Gasoline and other fuels | |
Electric vehicle charging | |
Other vehicle expenses | |
Public and other transportation | |
Healthcare |
Health insurance |
Medical services | |
Drugs | |
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 | |
The estimates contained with this database correspond to the Calendar year tables by demographic characteristics and the Calendar year aggregate shares tables by demographic characteristics available on the CE tables page.
The following estimates are available in the CE LABSTAT database:
Not all tabular data are in the CE LABSTAT database. Table 2 below lists the table types available on the CE tables page and indicates their availability in the database. The CE LABSTAT database only contains annual data and does not yet include cross-tabulations or data by metropolitan statistical areas. You can find these additional tabulations on the CE tables page.
Tabular Data Availability | Tables | LABSTAT Database |
---|---|---|
✔ | ✔ | |
✔ | ✔ | |
✔ | ✔ | |
Calendar year aggregate shares by demographic characteristics |
✔ | ✔ |
✔ | ||
✔ | ||
This section provides another view of the CE LABSTAT database search tools. These search tools allow users to dynamically retrieve CE estimates and their series IDs. Selected estimates are populated on a webpage, which can then be downloaded to Excel to develop further analysis and visualizations beyond the tool platform.
This section provides the necessary documentation for working with the underlying text files. The text files house the data and parameters used to populate the estimates in the tools described above. Data files are in American Standard Code for Information Interchange (ASCII) text format. The data files cx.data.1.All.Data and cx.aspect contain all the estimates in the database. These files, used in conjunction with the series and mapping files, enable users to create custom table output that may better suit their research and analysis needs, beyond the capability of the tools. Working with these files does require users to have a firm understanding of the underlying data available. Prior to working with these files, users should first peruse the available data using either one of the search tools listed above or the mapping files detailed below, in an effort to identify the data elements needed for their individual research purposes.
This section describes the various files and file types available to generate time series of most CE estimates found on the CE tables page. Table 3 below identifies the files that are available. All variables within these files are defined in Section 4 below. Highlighted variables in the file descriptions and field definition sections below denote key variables that can be used to merge with the series file in order to link and associate estimates with attributes and titles.
File Name | File Type | Description |
---|---|---|
Data | Contains means for expenditures, income and taxes, consumer characteristics, and assets and liabilities for 17 demographic groups. | |
Data | Contains standard errors, expenditure aggregates, and expenditure shares for associated means found on the cx.data.1.AllData. | |
Series | Contains a set of codes which, together, comprise a series identification code that serves to uniquely identify a single time series, such as "Women, 16 and over by Income Deciles: Ninth 10 percent." | |
Mapping | Contains text descriptions that link to the category_code variable within the cx.series file. | |
Mapping | Contains text descriptions that link to the subcategory_code variable within the cx.series. | |
Mapping | Contains text descriptions that link to the item_code variable within the cx.series. | |
Mapping | Contains text descriptions that link to the demographics_code variable within the cx.series. | |
Mapping | Contains text descriptions that link to the characteristics_code variable within the cx.series. | |
Mapping | Contains text descriptions that link to the footnote_code variable within the cx.series. | |
Mapping | Contains text descriptions that link to the process_code variable within the cx.series. | |
Contact | Contains CE program contact information. |
Data files are tab delimited text files that contain all the estimates that are available in the database. The first record of each file contains the column headers for the data elements stored in each field. The cx.data.1.AllData data file contains average annual means as well as percentages that describe the households within each demographic breakout. The cx.aspect data file contains associated estimates including the mean standard error, the expenditure aggregate or expenditure aggregate share, and the share of total expenditures. Associated estimates are identified by the aspect_type variable stored on file.
Below are the variables, their length, and possible values for the data file cx.data.1.AllData.
Variable | Length | Example value | Definition |
---|---|---|---|
series_id |
30 | CXUMENBOYSLB0104M | Identifies specific series. |
year |
4 | 1984 | Identifies year of observation. |
period |
3 | A01 | Identifies period for which data are observed. |
value |
12 | 93 | Lists the observation for the series. |
footnote_code |
10 | It varies | Identifies footnote for the data series. |
Below are the variables, their lengths, and their possible values for the data file cx.aspect.
Variable | Length | Example value | Definition |
---|---|---|---|
series_id |
30 | CXUMENBOYSLB0104M | Identifies the specific series. For a full list of possible series IDs, please see cx.series. |
year |
4 | 1984 | Identifies year of the estimate. |
period |
3 | A01 | Identifies the time period for which the estimate represents. The CE only develops annual estimates and therefore only has one begin and end period, A01. |
aspect_type |
2 | ES | Identifies the estimate type (see below of available estimates). |
value |
12 | 93 | Identifies the estimate. |
footnote_code |
10 | 1 | Identifies the footnote code for the data series. For a full list of possible footnote codes, please see cx.footnote. |
The cx.aspect data file can be merged with cx.data.1.Alldata, which allows the user to associate supporting estimates found on cx.aspect with the means found on cx.data.1.Alldata. Associated estimates include the mean standard error, the expenditure aggregate or expenditure aggregate share, and the share of total expenditures. Aspect_type options are defined as such:
AG (Aggregate or Aggregate Share):
Series defined with this aspect_type can represent two different estimates. First, the AG series can represent the aggregate (total) expenditure of an item for all consumer units (characteristic_code = 01). For example, if we use Series Report to look up the expenditures on eggs for all consumers (CXU080110LB0101M ), we can see that the expenditure aggregate (AG) in 2022 was $11,651.5, which is a total dollar aggregate presented in millions representing $11,651,500,000. In cases where the means represent all consumer units (characteristic_code = 01), the aggregate will represent the total dollars spent on a particular item.
Year | Period | Estimate Value | Standard Error | Expenditure Share | Aggregate |
---|---|---|---|---|---|
2022 |
Annual | 87 | 2.16 | 0.1 | 11651.5 |
The AG series can also represent the share (or portion) of aggregate expenditures that a particular demographic group (characteristic_code > 01) makes up of the total aggregate. For example, if we use the Series Report again, but this time look up expenditures on eggs for the lowest 20 percent income quintile (CXU080110LB0102M), we will see that in 2022 the aggregate field contains a percentage of 15.2. We can interpret this as the lowest income quintile contributing 15.2% to the total spending on eggs, or $1,771,028,000 (11,651,500,000 x 15.2%).
Year | Period | Estimate Value | Standard Error | Expenditure Share | Aggregate |
---|---|---|---|---|---|
2022 |
Annual | 66 | 3.98 | 0.2 | 15.2 |
ES (Expenditure Share):
Series defined with aspect_type of “ES” will provide an expenditure share, which represents an item’s expenditure expressed as a percent of total expenditures for a given demographic group. For example, if we utilize the Series Report here to look up the series ID for housing expenditures for reference person under age 25 in 2022 (CXUHOUSINGLB0402M), we will find an expenditure share of 36.3%, which implies that housing made up of 36.3% of all total expenditures for this demographic group ($16,837/$46,359 = 36.3%).
Year | Period | Estimate Value | Standard Error | Expenditure Share | Aggregate |
---|---|---|---|---|---|
2022 |
Annual | 16837 | 678.5 | 36.3 | 3.3 |
E (Standard Error):
Series defined with aspect_type of “E” will provide the standard error of the mean. For example, if we look up the same series ID used in the example above, housing expenditures for reference person under age 25 in 2022 (CXUHOUSINGLB0402M), we will find a standard error of $678.50, which implies that if the CE surveys could have been repeated with different samples of households, the mean expenditure could have varied by up to plus-or-minus $678.50. For more information on standard errors please visit the following link: https://www.bls.gov/cex/csxfaqs.htm#qc15.
Aspect type | Definition |
---|---|
AG |
Expenditure aggregate (all consumer units) or share of aggregate expenditure (subgroups) |
E |
Standard error |
ES |
Expenditure shares |
The series file (cx.series) enables users to associate coded values with text definitions by merging them with the mapping files discussed in section 5 below. The series file can also be merged with the data files to associate estimates with estimate titles. The series file is in ASCII text format, which is a common format for text files. Data elements are separated by tabs and the first record of each file contains the variable names for the data elements stored in each field.
Below are the types of fields, their length, and example values.
Variable | Length | Example value | Definition |
---|---|---|---|
series_id |
30 | CXUFRSHFRUTLB0201M | Series_id. For a full list of possible series IDs, please see cx.series. |
seasonal |
1 | U | Identifies whether the data are seasonally adjusted. All values are identified with a “U,” as all estimates are unadjusted/not seasonally adjusted. |
category_code |
10 | EXPEND | Identifies the category code for the data series. For a full list of possible category codes, please see cx.category. |
subcategory_code |
9 | FOOD | Identifies the subcategory code for the data series. For a full list of possible subcategory codes, please see cx.subcategory. |
item_code |
10 | FRSHFRUT | Identifies the item code for the data series. For a full list of possible item codes, please see cx.item. |
demographics_code |
4 | LB02 | Identifies the demographics code for the data series. For a full list of possible demographics codes, please see cx.demographics. |
characteristics_code |
2 | 01 | Identifies the characteristics code for the data series. For a full list of possible characteristics codes, please see cx.characteristics. |
process_code |
1 | M | Identifies the process code for the estimates found on cx.data.1.Alldata. (CE only provides Means on cx.data.1.Alldata so this will value will only be “M.”) |
series_title |
256 | Fresh fruits by Income Range: All Consumer Units | Title defining the unique series ID. |
footnote _code |
10 | It varies | Identifies the footnote code for the data series. For a full list of possible footnote codes, please see cx.footnote. |
begin_year |
4 | It varies | Identifies the first year the series is available. |
begin_period |
3 | AO1 | Identifies the starting period for which the estimate represents. The CE only develops annual estimates and therefore only has one begin and end period, A01. |
end_year |
4 | It varies | Identifies the last year the series is available. |
end_period |
3 | AO1 | Identifies the end period for which the estimate represents. The CE only develops annual estimates and therefore only has one begin and end period, A01. |
The series_id CXUFRSHFRUTLB0201M can be broken out into these segments:
Series ID elements | Example value |
---|---|
survey specific abbreviation |
CX |
item_code |
FRSHFRUT |
demographics_code |
LB02 |
characteristics _code |
01 |
process_code |
M |
Mapping files are in ASCII text format. Data elements are separated by tabs. The first record of each file contains the column headers for the data elements stored in each field.
cx.category: defines the available major category codes available in the CE database. For CE, categories are limited to the following:
Variable | Length | Example value | Definition |
---|---|---|---|
category_code |
10 | EXPEND | Identifies the category code for the data series. For a full list of possible category codes, please see cx.category. |
category_text |
60 | Expenditures | Title defining the unique category code. |
display_level |
2 | 0 | Identifies how columns should be grouped for display. |
selectable |
1 | T | Not applicable to CE. All series will be marked with “T.” |
sort_sequence |
5 | 100 | Sort sequence for how columns should be ordered. |
cx.subcategory: defines the available subcategory codes available in the CE database. cx.subcategory can be used to explore greater detail beyond what is available at the category level. For CE, subcategories include various expenditure types like food and transportation, as well as breakouts for income, like income before taxes.
Variable | Length | Example value | Definition |
---|---|---|---|
category_code |
10 | EXPEND | Identifies the category code for the data series. For a full list of possible category codes, please see cx.category. |
subcategory_code |
9 | PERSCARE | Identifies the subcategory code for the data series. For a full list of possible subcategory codes, please see cx.subcategory. |
subcategory_text |
50 | Personal care products and services | Title defining the unique subcategory code. |
display_level |
2 | 0 | Identifies how columns should be grouped for display. |
selectable |
1 | T | Not applicable to CE. All series will be marked with “T.” |
sort_sequence |
5 | 900 | Sort sequence for how columns should be ordered for display. |
cx.item: defines the available detailed items available in the CE database. For CE, items include various expenditure types like pets and major appliances, as well as breakouts for income, like self-employment.
Variable | Length | Example value | Definition |
---|---|---|---|
subcategory_code |
9 | ENTRTAIN | Identifies the subcategory code for the data series. For a full list of possible category codes, please see cx.subcategory. |
item_code |
10 | PETSPLAY | Identifies the item code for the data series. For a full list of possible item codes, please see cx.item. |
item_text |
50 | Pets, toys, and playground equipment | Title defining the unique item code. |
display_level |
2 | 1 | Identifies how columns should be grouped for display. |
selectable |
1 | T | Not applicable to CE. All series will be marked with “T.” |
sort_sequence |
5 | 11200 | Sort sequence for how columns should be ordered for display. |
cx.demographics: defines the available demographics available in the CE database. For CE, demographics include various breakouts like income quintiles, age, or race.
Variable | Length | Example value | Definition |
---|---|---|---|
demographics_code |
4 | LB01 | Identifies the demographics code for the data series. For a full list of possible demographics codes, please see cx.demographics. |
demographics_text |
150 | Quintiles before taxes | Title defining the unique item code. |
display_level |
2 | 0 | Identifies how columns are grouped for display. |
selectable |
1 | T | Not applicable to CE. All series will be marked with “T.” |
sort_sequence |
5 | 100 | Sort sequence for how columns should be ordered for display. |
cx.characteristics: defines the available detailed demographic characteristics available in the CE database. For CE, characteristics include various breakouts like “Lowest 20 percent income quintile,” or “Reference person under age 25.”
Variable | Length | Example value | Definition |
---|---|---|---|
demographics_code |
4 | LB01 | Identifies the demographics code for the data series. For a full list of possible demographics codes, please see cx.demographics. |
characteristics_code |
2 | 01 | Identifies the characteristics code for the data series. For a full list of possible characteristics codes, please see cx.characteristics. |
characteristics_text |
120 | All consumer units | Title defining the unique characteristics code. |
display_level |
2 | 1 | Identifies how columns should be grouped for display. |
selectable |
1 | T | Not applicable to CE. All series will be marked with “T.” |
sort_sequence |
5 | 1010 | Sort sequence for how columns should be ordered for display. |
cx.footnote: defines the available footnote codes utilized in the CE database. For CE, footnotes identify suppression and other key details users should be aware of when interpreting the estimate.
Variable | Length | Example value | Definition |
---|---|---|---|
footnote_code |
2 | 1 | Identifies the footnote code for the data series. For a full list of possible footnote codes, please see cx.footnote. |
footnote_text |
250 | No data provided | Title defining the unique footnote code. |
cx.process: is a place holder used on cx.data.1.AllData. All estimates stored on cx.data.1.AllData are marked with a process code of “M."
Variable | Length | Example value | Definition |
---|---|---|---|
process_code |
1 | M | Identifies the process code for the estimates found on cx.data.1.AllData. (CE only provides Means on cx.data.1.AllData so this will value will only be “M.”) |
process_text |
30 | Means | Title defining the unique process code. |
display_level |
2 | 0 | Identifies how columns should be grouped for display. |
selectable |
1 | T | Not applicable to CE. All series will be marked with “T.” |
sort_sequence |
5 | 100 | Sort sequence for how columns should be ordered for display. |
Last Modified Date: September 25, 2024