The Current Population Survey (CPS) has been the nation's primary source of information about employment and unemployment for decades. The data are widely used by social scientists and policy makers to study labor force participation, poverty, and other high-priority topics. An underutilized feature of the CPS is its short-run panel component. This paper discusses the unique challenges encountered when linking basic monthly data as well as when linking the March basic monthly data to the Annual Social and Economic (ASEC) Supplement in the 1976-1988 period. We describe strategies to address linking obstacles and document linkage rates.

Emerging evidence suggests that the COVID-19 pandemic has extracted a substantial toll on immigrant communities in the United States, due in part to increased potential risk of exposure for immigra...

Measuring change over time in areas such as family structure, employment, income, and poverty is of great interest to social scientists. The panel component of the Current Population Survey (CPS) affords the opportunity to observe short-term change in these areas. The Annual Social and Economic supplement (ASEC), with its wealth of information on income, health insurance coverage, benefits receipt, and many other topics, is a particularly popular resource for this purpose. However, commonly used methods for linking CPS ASEC files do not address how to link the ASEC oversample records across years, leading to smaller linked sample sizes and unreliable estimates for certain subpopulations. In this research note, we describe how to link individuals from the ASEC oversamples in the 2005-2020 data and the increase in sample size researchers can achieve by doing so. Finally, we illustrate the importance of including oversample records by examining poverty transitions over time.

Poverty is a key indicator of economic hardship. By providing a geographic adjustment for cost of living, the recently developed Supplemental Poverty Measure has upended long-held views that poverty is higher in rural compared to urban America. In this study, we unpack the geographic adjustment underlying the Supplemental Poverty Measure and find that most of the difference is explained by the median rent index component rather than the housing tenure component. Further, we find that six states (Alabama, Georgia, Kentucky, Mississippi, North Carolina, and Ohio) account for over a third of the nonmetro poverty drop due to the median rent adjustment. We demonstrate that the demographic composition of the rural poor remains relatively unaffected despite this large drop, but find that the prevalence of poverty within demographic groups varies considerably. As a result, while the SPM is largely considered a more complete measure of poverty, the use of the median rent adjustment has important implications for the demographic understanding of rural poverty.

The Annual Social and Economic Supplement (ASEC) is the most widely used type of Current Population Survey (CPS) data, but it is cumbersome to use the ASEC as part of a longitudinal CPS panel, especially linking to non-March months. In this paper, we detail the challenges associated with linking the ASEC to monthly CPS data, outline the creation of an identifier that links the ASEC and the March Basic Monthly data from 1989 through 2017, and provide substantive examples that illustrate the value of combining the ASEC with monthly data. The variable, MARBASECID, which we created to link ASEC and March monthly CPS data, represents a significant contribution to social and economic data infrastructure, saving individual researchers from having to duplicate the effort required to create linkages between ASEC and monthly CPS data.

Understanding poverty in terms of time use is not a new phenomenon. A 1977 article by Vickery theorizes a generalized definition of poverty using both income and time dimensions. She uses time diary data to identify families who are income poor, time poor, and both and highlights the importance of a time dimension to poverty, particularly as it relates to different household configurations. Under her generalized definition of poverty,"...the 1973 poverty population would have increased the number of poor female-headed families with children by 14 percent and increased the proportion of all families in poverty from .008 to .093 (35)." This paper uses the American Time Use Survey (ATUS-X) and the Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) from 2003 to 2011 to update Vickery's analysis. We estimate poverty rates from 2003-2011 by income, time, and a combination of both for diverse household configurations. We also estimate the effect of household configuration on changes to the definition of poverty, controlling for a variety of socio-demographic factors such as age, race, and education.