Inverse probability weighted M-estimators for sample selection, attrition, and stratification

Jeffrey Wooldridge

Portuguese Economic Journal, 2002, vol. 1, issue 2, No 3, 117-139

Abstract: Abstract. I provide an overview of inverse probability weighted (IPW) M-estimators for cross section and two-period panel data applications. Under an ignorability assumption, I show that population parameters are identified, and provide straightforward $\sqrt{N}$ -consistent and asymptotically normal estimation methods. I show that estimating a binary response selection model by conditional maximum likelihood leads to a more efficient estimator than using known probabilities, a result that unifies several disparate results in the literature. But IPW estimation is not a panacea: in some important cases of nonresponse, unweighted estimators will be consistent under weaker ignorability assumptions.

Keywords: Attrition; Inverse probability weighting; M-estimator; Nonresponse; Sample selection; Treatment effect (search for similar items in EconPapers)
Date: 2002
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DOI: 10.1007/s10258-002-0008-x

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