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Axinn says data show incidents of sexual assault start at 'very young age'

Miech on 'generational forgetting' about drug-use dangers

Impacts of H-1B visas: Lower prices and higher production - or lower wages and higher profits?

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Highlights

Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

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Next Brown Bag

Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

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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