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Frey's Scenario F simulation mentioned in account of the Democratic Party's tribulations

U-M Poverty Solutions funds nine projects

Dynarski says NY's Excelsior Scholarship Program could crowd out low-income and minority students

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Workshops on EndNote, NIH reporting, and publication altmetrics, Jan 26 through Feb 7, ISR

2017 PAA Annual Meeting, April 27-29, Chicago

NIH funding opportunity: Etiology of Health Disparities and Health Advantages among Immigrant Populations (R01 and R21), open Jan 2017

Russell Sage 2017 Summer Institute in Computational Social Science, June 18-July 1. Application deadline Feb 17.

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Next Brown Bag

Mon, Jan 23, 2017 at noon:
Decline of cash assistance and child well-being, Luke Shaefer

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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