This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: May 2025 (preliminary values at the county level) The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: July 18th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and County NationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS"s county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova. As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties. To better understand the different labor force statistics included in this map, see the diagram below from BLS:

United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-1st data was reported at -49.000 Person th in Feb 2025. This records a decrease from the previous number of -32.000 Person th for Jan 2025. United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-1st data is updated monthly, averaging 10.000 Person th from Jan 1979 (Median) to Feb 2025, with 552 observations. The data reached an all-time high of 437.000 Person th in Nov 2021 and a record low of -672.000 Person th in Mar 2020. United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-1st data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll: Seasonally Adjusted.

The seasonally-adjusted national unemployment rate is measured on a monthly basis in the United States. In February 2025, the national unemployment rate was at 4.1 percent. Seasonal adjustment is a statistical method of removing the seasonal component of a time series that is used when analyzing non-seasonal trends. U.S. monthly unemployment rate According to the Bureau of Labor Statistics - the principle fact-finding agency for the U.S. Federal Government in labor economics and statistics - unemployment decreased dramatically between 2010 and 2019. This trend of decreasing unemployment followed after a high in 2010 resulting from the 2008 financial crisis. However, after a smaller financial crisis due to the COVID-19 pandemic, unemployment reached 8.1 percent in 2020. As the economy recovered, the unemployment rate fell to 5.3 in 2021, and fell even further in 2022. Additional statistics from the BLS paint an interesting picture of unemployment in the United States. In November 2023, the states with the highest (seasonally adjusted) unemployment rate were the Nevada and the District of Columbia. Unemployment was the lowest in Maryland, at 1.8 percent. Workers in the agricultural and related industries suffered the highest unemployment rate of any industry at seven percent in December 2023.

In October 2024, the total nonfarm payroll employment increased by around 12,000 people in the United States. The data are seasonally adjusted. According to the BLS, the data is derived from the Current Employment Statistics (CES) program which surveys about 140,000 businesses and government agencies each month, representing approximately 440,000 individual worksites, in order to provide detailed industry data on employment.

United States Employment: NF: Over-the-Month Change: Revision: 3rd-2nd data was reported at -6.000 Person th in Feb 2025. This records a decrease from the previous number of 3.000 Person th for Jan 2025. United States Employment: NF: Over-the-Month Change: Revision: 3rd-2nd data is updated monthly, averaging 6.000 Person th from Jan 1979 (Median) to Feb 2025, with 552 observations. The data reached an all-time high of 796.000 Person th in Mar 1996 and a record low of -716.000 Person th in Mar 1992. United States Employment: NF: Over-the-Month Change: Revision: 3rd-2nd data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll.

United States Employment: NF: Over-the-Month Change: Revision: 2nd-1st data was reported at -89.000 Person th in Mar 2025. This records a decrease from the previous number of -36.000 Person th for Feb 2025. United States Employment: NF: Over-the-Month Change: Revision: 2nd-1st data is updated monthly, averaging 1.000 Person th from Jan 1979 (Median) to Mar 2025, with 554 observations. The data reached an all-time high of 283.000 Person th in Sep 1983 and a record low of -242.000 Person th in Mar 2020. United States Employment: NF: Over-the-Month Change: Revision: 2nd-1st data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll.

United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-2nd data was reported at -15.000 Person th in Feb 2025. This records a decrease from the previous number of -14.000 Person th for Jan 2025. United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-2nd data is updated monthly, averaging 11.500 Person th from Jan 1979 (Median) to Feb 2025, with 552 observations. The data reached an all-time high of 398.000 Person th in Nov 2021 and a record low of -492.000 Person th in Mar 2020. United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-2nd data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll: Seasonally Adjusted.

The Producer Price Index Revision-Current Series indexes reflect price movements for the net output of producers organized according to the North American Industry Classification System (NAICS). The PC dataset is compatible with a wide assortment of NAICS-based economic time series including: productivity, production, employment, wages, and earnings.

Non Farm Payrolls in the United States increased by 73 thousand in July of 2025. This dataset provides the latest reported value for - United States Non Farm Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States Employment: NF: sa: Over-the-Month Change: Revision: 2nd-1st data was reported at -43.000 Person th in Mar 2025. This records a decrease from the previous number of -34.000 Person th for Feb 2025. United States Employment: NF: sa: Over-the-Month Change: Revision: 2nd-1st data is updated monthly, averaging 2.000 Person th from Jan 1979 (Median) to Mar 2025, with 554 observations. The data reached an all-time high of 311.000 Person th in Dec 2021 and a record low of -186.000 Person th in Dec 1979. United States Employment: NF: sa: Over-the-Month Change: Revision: 2nd-1st data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll: Seasonally Adjusted.

This data set contains the veterans unemployment rate in Maryland. Figures come from the Bureau of Labor Statistics, and are subject to revision.

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 XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm. These microdata files present detailed expenditure and income data for the Diary component of the CE for 2002. They include weekly expenditure (EXPD) and annual income (DTBD) files. The data in EXPD and DTBD files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. Estimates of average expenditures in 2002 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2002. A list of recent publications containing data from the CE appears at the end of this documentation. The microdata files are in the public domain and with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2002".

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 noninstitutional persons. The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2002 sample is composed of 105 areas. The design classifies the PSUs into four categories: • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" 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 2002 survey is generated from the 1990 Population Census 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 (ED's) from the Census that fail to meet the criterion for good addresses for new construction, and all ED's in nonpermit-issuing areas are grouped into the area segment frame. To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance. Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year. During the last 6 weeks of the year, however, the Diary Survey sample is supplemented to twice its normal size to increase the reporting of types of expenditures unique to the holidays.

STATE IDENTIFIER Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data. To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

INTERPRETING THE DATA Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially. Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs. CUs with members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

Mode of data collection

Computer Assisted Personal Interview [capi]

This table provides information about labor supply and demand conditions in occupational labor markets in North Carolina’s eight regions (“Prosperity Zones”) and the statewide total.

A “Career Cluster” is a broad group of occupations. Each Career Cluster contains occupations that require similar knowledge and skills. A “Career Pathway” is a specific group of occupations falling under a broader “Career Cluster”. Specific occupations falling within a given Career Cluster, Career Pathway, and education level can be found on the Star Jobs table.

These data can be used to compare occupational labor markets within a given region. A low supply/demand rate indicates a “tight” labor market—with few jobseekers per job opening—while a high supply/demand rate indicates a “slack” labor market. A tight labor market presents opportunities for jobseekers, but can lead to challenges for employers looking to hire.

These data can also be used to assess the alignment between the labor market and our state’s talent pipeline. “Labor needed” is the amount of additional labor supply needed to attain the statewide or regional supply/demand rate. “Completers” is the average number of individuals completing higher education programs at the University of North Carolina system or the North Carolina Community College System.

Data are updated on an annual basis to accommodate methodology improvements and revisions to the underlying data inputs.

Technical details about methodology can be found here.

Data sources:

Labor supply: LEAD analysis of data from the U.S. Bureau of Labor Statistics and the U.S. Census Bureau (American Community Survey, 2014-2016 average)

Labor demand: LEAD analysis of data from the Conference Board^© and the U.S. Bureau of Labor Statistics (2014-2016 average)

Completers: LEAD analysis of data from the N.C. Common Follow-up System (2010-2015 average)

The ongoing Consumer Expenditure Survey (CES) provides a continuous flow of information on the buying habits of American consumers and also furnishes data to support periodic revisions of the Consumer Price Index. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR04415.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The ongoing Consumer Expenditure Survey (CES) provides a continuous flow of information on the buying habits of American consumers and also furnishes data to support periodic revisions of the Consumer Price Index. The survey consists of two separate components: (1) a quarterly Interview Survey in which each consumer unit in the sample is interviewed every three months over a 15-month period, and (2) a Diary Survey completed by the sample consumer units for two consecutive one-week periods. The Interview Survey was designed to collect data on major items of expense, household characteristics, and income. The expenditures covered by the survey are those that respondents can recall fairly accurately for three months or longer. In general, these expenditures include relatively large purchases, such as those for property, automobiles, and major appliances, or expenditures that occur on a fairly regular basis, such as rent, utilities, or insurance premiums. Expenditures incurred while on trips are also covered by the survey. Excluded are nonprescription drugs, household supplies, and personal care items. Including global estimates on spending for food, it is estimated that about 90 to 95 percent of expenditures are covered in the Interview Survey. The Consumer Unit Characteristics and Income (FMLY) files in this collection contain consumer unit characteristics, consumer unit income, and characteristics and earnings of both the reference person and the spouse. Summary expenditure data are also provided. The Member Characteristics and Income (MEMB) files present selected characteristics for each consumer unit member, including reference person and spouse. Each record in the FMLY and MEMB files consists of three months of data. Detailed Expenditures (MTAB) files provide monthly data at the Universal Classification Code (UCC) level. In these files expenditures for each consumer unit are classified according to UCC categories and are specified as gifts or nongifts. There may be more than one record for a UCC in a single month if that is what was xreported to the interviewer. The Income (ITAB) files supply monthly data at the UCC level for consumer unit characteristics and income. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09712.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The ongoing Consumer Expenditure Survey (CES) provides a continuous flow of information on the buying habits of American consumers and also furnishes data to support periodic revisions of the Consumer Price Index. These addendum files contain the variables NEWID, State Code (STATE), New Base Weight (NEWBASWT), corrected Household Identifier (HHID), and flags (HHID_) for use with the Consumer Unit Characteristics and Income (FMLY) files of the 1990-1993 Interview Surveys (ICPSR 9820, 6209, 6372, and 6580). (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR06713.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The ongoing Consumer Expenditure Survey (CES) provides a continuous flow of information on the buying habits of American consumers and also furnishes data to support periodic revisions of the Consumer Price Index. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08235.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

These files contain a collection of data from the Bureau of the Census and other Federal agencies, such as the Bureau of Economic Analysis, the Bureau of Labor Statistics, the Federal Bureau of Investigation, and the Social Security Administration, as well as several private organizations, such as the American Medical Association and the Elections Research Center. The universe varies from item to item within the file, e.g., all persons, all housing units, all local governments, etc. Demograph ic, economic, and governmental data are presented for 3,475 variables for the purpose of multi-county comparisons or single county profiles. Current estimates and benchmark census results are included. This CD-ROM contains 3,475 data items in 63 dBASE III (tm) files. Emphasis has been placed on extending time series in contrast to most other statistical files, which feature data for the most recent period. The 63 data files include all of the data published for counties in the last three editions of the County and City Data Book (1994, 1988 and 1983) and the last three editions of the State and Metropolitan Area Data Book (1991, 1986, and 1982), as well as a number of data items not previously published. Note: Some of the data on this CD-ROM differ from published figures due to later revisions made by the source agencies. The data files cover the following general topics: age, agriculture, ancestry, banking, building permits, business patterns, crime, earnings, education, elections, government, health, households, housing, income, labor force and employment, manufactures, population, poverty, retail trade, services industries, social programs, veterans, vital statistics, and wholesale trade. Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

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 XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm.

These microdata files present detailed expenditure and income data from the Interview component of the CE for 2003 and the first quarter of 2004. The Interview survey collects data on up to 95 percent of total household expenditures. In addition to the FMLI, MEMI, MTBI, and ITBI 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 FMLI or MTBI 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 2003 from the Interview Survey, integrated with data from the Diary Survey, will be published in the report Consumer Expenditures in 2003. 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, 2003."

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-institutionalized 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 2003 and 2004 samples is composed of 105 areas. The design classifies the PSUs into four categories: • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" 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 2003 and 2004 surveys is generated from the 1990 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 non-permit-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.

WEIGHTING Each CU included in the CE represents a given number of CUs in the U.S. population, which is considered to be the universe. The translation of sample families into the universe of families is known as weighting. However, since the unit of analysis for the CE is a CU, the weighting is performed at the CU level. Several factors are involved in determining the weight for each CU for which an interview is obtained. There are four steps in the weighting procedure: 1) The basic weight is assigned to an address and is the inverse of the probability of selection of the housing unit. 2) A weight control factor is applied to each interview if subsampling is performed in the field. 3) A noninterview adjustment is made for units where data could not be collected from occupied housing units. The adjustment is performed as a function of region, housing tenure, family size and race. 4) A final adjustment is performed to adjust the sample estimates to national population controls derived from the Current Population Survey. The adjustments are made based on both the CU's Member composition and the CU as a whole. The weight for the CU is adjusted for individuals within the CU to meet the controls for 14 age/race categories, 4 regions, and 4 region/urban categories. The CU weight is also adjusted to meet the control for total number of CUs and total number of CUs who own their living quarters. The weighting procedure uses an iterative process to ensure that the sample estimates meet all the population controls.

NOTE: The weight for a consumer unit (CU) can be different for each quarter in which the CU participates in the survey, as the CU may represent a different number of CUs with similar characteristics.

Mode of data collection

Computer Assisted Personal Interview [capi]