What Are We Weighting For?
2015/01/01 by Gary Solon, Steven J. Haider, Jeffrey M. Wooldridge · 1,244 citations
Economics, Econometrics and Finance · Mathematics · Social Sciences · #Computer science #Descriptive statistics #Econometrics #Health Systems, Economic Evaluations, Quality of Life #Heteroscedasticity #Income, Poverty, and Inequality #Mathematics #Population #Sample (material) #Sampling (signal processing) #Statistics #Weighting
paper · doi:10.3368/jhr.50.2.301
published in The Journal of Human Resources 50(2), 301-316 (University of Wisconsin Press)
openalex publication_date 2015/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Abstract
When estimating population descriptive statistics, weighting is called for if needed to make the analysis sample representative of the target population. With regard to research directed instead at estimating causal effects, we discuss three distinct weighting motives: (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.
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