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DTSTART;TZID=America/Los_Angeles:20231011T120000
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DTSTAMP:20260503T093654
CREATED:20230928T211314Z
LAST-MODIFIED:20231005T185613Z
UID:10000812-1697025600-1697030100@ccpr.ucla.edu
SUMMARY:Gary Solon\, University of Michigan\, "What Are We Weighting For?" (STC Workshop)
DESCRIPTION:Biography:\nGary Solon is Professor Emeritus of Economics at the University of Michigan. He was Eller Professor of Economics at the University of Arizona during 2015-2018 and Professor of Economics at Michigan State University during 2007-2015. He is a research associate at the National Bureau of Economic Research\, a fellow of the Society of Labor Economists\, and a member of the Conference on Research in Income and Wealth. His research includes studies of family and community background effects on socioeconomic status\, earnings dynamics over the life cycle\, cyclical fluctuations in the labor market\, and microeconometric methods. \nWhat Are We Weighting For?\nAbstract:\nThe purpose of this paper is to help empirical economists think through when and how to weight the data used in estimation. We start by distinguishing two purposes of estimation: to estimate population descriptive statistics and to estimate causal effects. In the former type of research\, weighting is called for when it is needed to make the analysis sample representative of the target population. In the latter type\, the weighting issue is more nuanced. We discuss three distinct potential motives for weighting when estimating causal effects: (1) to achieve precise estimates by correcting for heteroskedasticity\, (2) to achieve consistent estimates by correcting for endogenous sampling\, and (3) to identify average partial effects in the presence of unmodeled heterogeneity of effects. In each case\, we find that the motive sometimes does not apply in situations where practitioners often assume it does. We recommend diagnostics for assessing the advisability of weighting\, and we suggest methods for appropriate inference.
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CATEGORIES:CCPR Seminar,CCPR Workshop,Divisional Publish
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