On Intercept Estimation in the Sample Selection Model
AbstractWe 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.
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Bibliographic InfoPaper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2000/380.
Date of creation: Jan 2000
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Asymptotic normality; sample selection model; semiparametric estimation;
Other versions of this item:
- Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2002. "On Intercept Estimation In The Sample Selection Model," Econometric Theory, Cambridge University Press, vol. 18(01), pages 40-50, February.
- Marcia M. A. Schafgans & Victoria Zinde-Walsh, 2000. "On intercept estimation in the sample selection model," LSE Research Online Documents on Economics 6868, London School of Economics and Political Science, LSE Library.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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