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

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Detalhes bibliográficos
Resumo:I provide an overviewof 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 √ 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.
Autores principais:Wooldridge, Jeffrey M.
Assunto:Attrition Inverse probability weighting M-estimator Nonresponse Sample selection Treatment effect
Ano:2002
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso restrito
Instituição associada:Universidade de Lisboa
Idioma:português
Origem:Repositório da Universidade de Lisboa

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