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Sastry's 10-year study of New Orleans Katrina evacuees shows demographic differences between returning and nonreturning

Stafford says less educated, smaller investors more likely to sell off stock and lock in losses during market downturn

Chen says job fit, job happiness can be achieved over time

Highlights

Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Next Brown Bag

Monday, Oct 12
Joe Grengs, Policy & Planning for Social Equity in Transportation

Attrition Bias in Economic Relationships Estimated with Matched CPS Panels

Archived Abstract of Former PSC Researcher

Neumark, David, and Genevieve Kenney. 2004. "Attrition Bias in Economic Relationships Estimated with Matched CPS Panels." Journal of Economic and Social Measurement, 29(4): 445-472.

Short panel data sets constructed by matching individuals across monthly files of the Current Population Survey (CPS) have been used to study a wide range of questions in labor economics. But because the CPS does not follow movers, these panels exhibit significant attrition, which may lead to bias in longitudinal estimates. The Survey of Income and Program Participation (SIPP) uses essentially the same sampling frame and design as the CPS, but makes substantial efforts to follow movers. We therefore use the SIPP to construct "data-based" rather than "model-based" corrections for bias from selective attrition. The approach is applied to two questions that have been studied with CPS data - union wage differentials and the male marriage wage premium. The evidence suggests that in many applications the advantages of using matched CPS panels to obtain longitudinal estimates are likely to far outweigh the disadvantages from attrition biases, although we should allow for the possibility that attrition bias leads the longitudinal estimates to be understated.

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