Measuring Employment and Income for Low-Income Populations with Administrative and Survey Data

V. Joseph Hotz and John Scholz

Institute for Research on Poverty Discussion Papers from University of Wisconsin Institute for Research on Poverty

Abstract: We discuss the strengths and weaknesses of income and employment data in national surveys, in unemployment insurance (UI) wage records, and in tax returns. The CPS, SIPP, NLS, and PSID surveys provide valuable information on the behavior of the low-income population. They have broad and fairly accurate measures of income for national samples, and their focus on families as the unit of analysis and their ease of access greatly enhance their value.

The value of these data sets for evaluating welfare reform is severely limited, however. With the devolution of responsibility for TANF, the CPS and SIPP sampling frames and sample sizes mean that, at best, they can be only supplementary data sources for understanding the effects of welfare reform at the state and local levels. The apparent decline in program coverage in the CPS is also worrisome.

UI data are available at the state level and can be matched to individuals in existing samples at relatively low cost. It is straightforward to do follow-up analyses on income and employment for workers who remain in the state, and UI data are timely. However, earnings are available only for individuals, while changes in family composition upon exit from welfare have been shown to have a large bearing on economic well-being. UI data do not allow us to track these changes. There also appears to be a substantial problem with some workers being classified as independent contractors and hence not entering the UI system. Overall gaps in coverage appear to be at least 13 percent and may be significantly higher. Even when wages are reported, there is some evidence that they are understated by a significant amount.

We also present evidence on the degree to which tax data can be used to understand the incomes and employment of low-skilled workers. The paper concludes with brief recommendations for future research that might help fill some of the gaps we have identified.

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