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2004•UvA-DARE (University of Amsterdam)Open access

A two-step first-difference estimator for a panel data Tobit model

Adriaan Kalwij

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Abstract

This study formulates an easy-to-use two-step first-difference estimator for a panel data Tobit model. In the first step a bivariate Probit is estimated, using all observations. These estimates are used to construct correction terms that are added to the first-difference equation. This equation is estimated by Least Squares on a sub-sample of observations for which the dependent variable is positive in both periods. Most of this study is concerned with the derivation of the corrections terms.

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This study formulates an easy-to-use two-step first-difference estimator for a panel data Tobit model. In the first step a bivariate Probit is estimated, using all observations. These estimates are used to construct correction terms that are added to the first-difference equation. This equation is estimated by Least Squares on a sub-sample of observations for which the dependent variable is positive in both periods. Most of this study is concerned with the derivation of the corrections terms.

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Available abstract

This study formulates an easy-to-use two-step first-difference estimator for a panel data Tobit model. In the first step a bivariate Probit is estimated, using all observations. These estimates are used to construct correction terms that are added to the first-difference equation. This equation is estimated by Least Squares on a sub-sample of observations for which the dependent variable is positive in both periods. Most of this study is concerned with the derivation of the corrections terms.

Key concepts: Tobit model, Mathematics, Estimator, Panel data, Statistics, Bivariate analysis, Econometrics, Multivariate probit model

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