IPUMS CPS

Posts related to IPUMS CPS

A Missing Piece: The 2025 U.S. Government Shutdown and the Current Population Survey

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By Renae Rodgers

Current Population Survey (CPS) data collection and processing were among the many U.S. government programs and services interrupted by the October 1-November 12, 2025 U.S. government shutdown. This blog post gives an overview of the impacts of the 2025 government shutdown on CPS data collection and processing, explores how missed data collection in October and delayed data collection in November due to the shutdown impacted CPS response rates, and discusses implications for the CPS panel component.

Data Collection and Processing

The Current Population Survey is one of two surveys used to create the Employment Situation News Release published every month by the Bureau of Labor Statistics (BLS); the CPS is commonly referred to as the “household survey” in these releases. Each month they are in the CPS, household respondents are asked questions on work and job search activities for members of their households during the week that includes the 12th of the month – this is known as the “reference week” (Bureau of Labor Statistics, 2025a). CPS households are interviewed during the week immediately following the reference week – the week that contains the 19th. Data collection lasts for approximately 10 days. During November and December, reference weeks and subsequent data collection may be moved one week earlier if necessary to avoid coinciding with holiday periods. The Employment Situation news releases are typically published the first Friday of the month following data collection (e.g., the August Employment Situation news release is the first Friday of September) and the Public Use Microdata files are typically published the Wednesday following the Employment Situation news release.

The 2025 government shutdown impacted data release, collection, and processing in unique ways. Figure 1 shows the CPS reference weeks for September through December of 2025, the CPS interview weeks for this same period, and the days on which the federal government was shut down.

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Historical Supplemental Poverty Measure

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By Stephanie Richards, Kari Williams, and Sarah Flood

The Annual Social and Economic Supplement (ASEC) of the Current Population Survey is the official source of information about poverty in the United States. Since 1968, the ASEC has been used to create the Official Poverty Measure (OPM) and has included the variables needed to create that measure. The Supplemental Poverty Measure (SPM) and the variables needed to create it were first released by the Census Bureau in 2010, reporting the SPM for 20091. In contrast to the OPM, the SPM provides a more complete picture of the economic wellbeing of American households.

The value of the SPM is apparent – it is a comprehensive and nuanced measure that accounts for the diversity of living arrangements, variability in cost of living, and a wider array of available financial resources and demands. However, the temporal coverage of SPM is limited; the Census Bureau only has data back to 2010. Over the last ten years, researchers at Columbia University’s Center on Poverty and Social Policy (CPSP) have eliminated this constraint by compiling the data necessary to create SPM and make it available back to 1968, and have shared the data with the research community via the CPSP Historical SPM Data Portal.

CPSP researchers have also partnered with IPUMS to disseminate their historical SPM data via IPUMS CPS. This includes the poverty status variables (i.e., SPMPOV and SPMPOVANC12) as well as the inputs and thresholds for creating them. If you know IPUMS, you know that we loooooove the chance to extend a valuable measure back in time. We are incredibly grateful to CPSP for the important work they have done and are thrilled to make it even easier for IPUMS CPS users to access the historical SPM data.

In this blog post, we briefly describe differences between the components – family, resources, and needs – used to create OPM and (historical) SPM, preview CPSP’s “anchored” poverty variables that facilitate comparisons over time that reference a set cost-of-living standard, and share suggestions for further reading (because we know you are going to want to learn even more about this!).

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Multigenerational Households Across Multiple Data Collections

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By Etienne Breton

We recently updated a key IPUMS-constructed variable for understanding multigenerational households: MULTGEN, which identifies the number of generations in a household. This variable is needed to answer important questions in our era of rapid population aging. For example, do multigenerational households become more numerous during economic recessions, and if so for whom exactly? Can they buffer against physical and cognitive decline for older adults? Do young people living with their grandparents have distinct educational, professional or even health trajectories? All of these questions – and many more – can be investigated creatively and rigorously using MULTGEN.

MULTGEN has long been available for most IPUMS USA samples. We recently adapted our methodology to add this variable to IPUMS CPS for all samples from January 1994 to the present. This means that users can now research multigenerational households with another IPUMS data collection, tackling key research questions with added precision and contextual richness, in addition to analysis of topics in the CPS that are not covered in the ACS (e.g., tobacco use, volunteering, voting and registration).

The construction of MULTGEN in IPUMS CPS (as in IPUMS USA) relies on IPUMS family interrelationship variables (see this classic paper, or this more recent paper, or our user guide, for how these variables are constructed) and information from the variable RELATE (insufficient information in the RELATE variable before 1994 explains why MULTGEN is not available for older samples). At present, MULTGEN in IPUMS CPS only provides general codes about the number of generations per household, whereas MULTGEN in IPUMS USA also provides detailed codes identifying subtypes of 2-generations and 3+ generations households.

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New variables for augmenting IPUMS CPS data with external city-level data

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By David Van Riper, Etienne Breton, and Sarah Flood

Have you ever wanted to link external city-level data to CPS respondents but were stymied by the city coding system used by the CPS? With the release of two new variables (PLACECENSUS and PLACEFIPS), IPUMS CPS has simplified the task of making such linkages.

The CPS identifies a limited number of sub-state geographic units (e.g., cities, counties) because of the complex assignment of CPS geographic identifiers (see working paper) and required minimum population thresholds. An additional layer of complexity is a custom coding scheme for central/principal cities (INDIVIDCC) that is unique to the CPS and, therefore, unfamiliar to most data users. IPUMS CPS has addressed this issue through the creation of two new variables – PLACECENSUS and PLACEFIPS – which provide standard codes for identifying central cities. These new variables will dramatically simplify the process of using IPUMS CPS to study specific cities, and will be particularly beneficial to those who want to augment the CPS data with city-level characteristics.

While metropolitan areas have almost always been identified in CPS (see METFIPS), central or principal cities – defined as the largest or one of the largest cities in metropolitan areas – were not identified in the data until October of 1985 (see INDIVIDCC). The identification of cities is great for users – they can focus their analyses on these cities (paying close attention to sample size and applying weights of course!). If analyses are confined to the CPS only, INDIVIDCC is adequate for use. However, attaching city-level characteristics to CPS data quickly becomes a problem given the native coding scheme for INDIVIDCC that is not used in other data products.

The new IPUMS CPS variables PLACECENSUS and PLACEFIPS help mitigate the challenge associated with augmenting city-level data from other sources with CPS data.

  • PLACECENSUS (available October 1985 to May 1995) uses Census city codes developed by the Census Bureau. The Census Bureau developed standard Census codes for cities that they applied to the 1970 and 1980 decennial censuses. The codes are assigned to each place in alphabetical order within a state.
  • PLACEFIPS (available September 1995 forward) uses FIPS codes. were developed by the National Institute of Standards and Technology (NIST) in the 1980s and have been used by the Census Bureau for decennial censuses since 1990 and in many other datasets published by the United States government (e.g., American Community Survey). FIPS codes are assigned to each place in alphabetical order within a state.
  • Neither PLACECENSUS nor PLACEFIPS are available for the June to August 1995 data. During this period, there are no sub-state geographic identifiers in the data.
  • PLACECENSUS and PLACEFIPS codes are unique within states, so users must combine the PLACECENSUS or PLACEFIPS codes with a state identifier (STATEFIP or STATECENSUS) to uniquely identify each central city.

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Measuring Food Security with U.S. Federal Data

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By Kari Williams & Isabel Pastoor

The U.S. Department of Agriculture (USDA) defines a household as being food secure when all household members at all times have access to “enough food for an active, healthy life;” it sets a minimum threshold for food security of “ready availability of nutritionally adequate and safe foods” and the “assured ability to acquire acceptable foods in socially acceptable ways” (USDA Economic Research Service, 2025). The USDA provides survey modules for assessing food security in the U.S. (see Table 1), which are used in a number of federal surveys.

Following the recent announcement by the USDA that they plan to cease data collection for the Food Security supplement fielded as part of the December Current Population Survey, we are highlighting data sources for studying food security in the U.S. Table 2 provides an overview of a number of federal data sources that can be used to study aspects of food security in the U.S. This list of data sources is not exhaustive; we have prioritized data available through IPUMS and other long-running and large-scale population surveys. Additional sources covering shorter time periods or more specific focal populations can be found from the USDA’s Food Security in the United States Documentation page and the Food Access Research Atlas.

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What is going on with the weighted counts in the January 2025 CPS?

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By Kari Williams & Sarah Flood

The signature activity of IPUMS is data harmonization, or making variables interoperable across time, to facilitate pooling of multiple months or years of data, as well as comparative and trend analyses. It’s easy to get carried away in the magic of not needing to perform routine data cleaning and having documentation organized at the variable level, and perhaps miss some bigger picture considerations. The Current Population Survey (CPS) annual population controls adjustment is an excellent example.

Each January, the Census Bureau revises the CPS weights to incorporate new population controls, based on the Census Bureau’s updated population estimates. However, the Census Bureau doesn’t re-release previous weights for the CPS based on the new population controls. If you look at trendlines of weighted count estimates using CPS monthly data, you might notice a discontinuity between each December and January – these are the annual population control adjustments at work. In January 2025, the shift is particularly abrupt; this is because the 2024 vintage population estimates (i.e., the population controls for the 2025 CPS) reflect an improvement in the Census Bureau’s methodology for measuring net international migration.

Line chart showing a general upward trend from 2020-2025 with disruptions each January

Figure from Jed Kolko’s Population adjustments will cause the next jobs report to be misinterpreted and misconstrued.

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IPUMS CPS Checks on Basic Monthly Data

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By Sarah Flood, Renae Rodgers, and Kari Williams

Federal data are critical for understanding much about the US population from its size and composition to its health and employment. The Current Population Survey (CPS) is our nation’s official source of information about the labor force. At the beginning of each month, we eagerly await the first Friday when the Employment Situation Summary (aka the monthly jobs report) will be released (it isn’t just us, right??). The monthly snapshot of the US labor force serves as a bellwether for how our economy is faring.

The Wednesday after the jobs report is released, we at IPUMS clear the decks in preparation for the release of the CPS Basic Monthly Survey (BMS) by the Census Bureau. The CPS BMS is the individual-level data from which the jobs report is generated. Our goal is always to process these data as soon as they’re released by the Census Bureau so that we can deliver them to IPUMS CPS users as quickly as possible. Those who rely on CPS BMS data each month might be familiar with coping strategies while waiting for the data–obsessive page refreshing, some nervous pacing, maybe wondering why they haven’t yet been released (iykyk).

While quickly processing CPS Basic Monthly data is a priority, so, too, is ensuring data quality. Each month, we carefully inspect CPS BMS data at several points in our process. First, we review all of the variables for codes that are undocumented or have suspicious frequencies. Second, we rely on a suite of tools during our integration process that alert us to any codes in the data that we haven’t accounted for in our variable-level harmonizations. After harmonization, we compare univariate statistics from the newest month data to the previous month of data. Generally we expect very little change across months and we have built tools that are designed to flag variable-level differences above a certain threshold as well as new codes on either end of the distribution.

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