The Journal of Human Resources · 2015 · 1.2K citations · 15 references
Public HealthBiostatisticsCausal InferencePopulation StudiesStatisticsBiasBias ControlCausal Effect EstimationHeterogeneity AssessmentTreatment Effect HeterogeneityAverage Treatment EffectsCausal Effects IdentificationHeterogeneityHeterogeneous Treatment Effect EstimationSample AnalysisSample WeightingStudy WeightsWeighting Estimation
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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Sample Selection Bias as a Specification Error
James J. Heckman · Econometrica · 1979 · 28.9K citations
Cluster-Sample Methods in Applied Econometrics
Jeffrey M. Wooldridge · American Economic Review · 2003 · 1.3K citations