On Intercept Estimation in the Sample Selection Model

Marcia M Schafgans and Victoria Zinde-Walsh

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990) for the intercept of a semiparametrically estimated sample selection model. The estimator is based on 'identification at infinity' which leads to non-standard convergence rate. Andrews and Schafgans (1998) derived asymptotic results for a smoothed version of the estimator. We examine the optimal bandwidth selection for the estimators and derive asymptotic MSE rates under a wide class of distributional assumptions. We also provide some comparisons of the estimators and practical guidelines.

Keywords: Asymptotic normality; sample selection model; semiparametric estimation (search for similar items in EconPapers)
Date: 2000-01
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Citations: View citations in EconPapers (3)

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https://sticerd.lse.ac.uk/dps/em/em380.pdf (application/pdf)

Related works:
Journal Article: ON INTERCEPT ESTIMATION IN THE SAMPLE SELECTION MODEL (2002)
Working Paper: On intercept estimation in the sample selection model (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:380

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