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The Behavior of the Maximum Likelihood Estimator of Dynamic Panel Data Sample Selection Models

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Author Info
Wladimir Raymond
Pierre Mohnen ()
Franz Palm
Sybrand Schim van der Loeff

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Abstract

This paper proposes a method to implement maximum likelihood estimation of the dynamic panel data type 2 and 3 tobit models. The likelihood function involves a two-dimensional indefinite integral evaluated using “two-step” Gauss-Hermite quadrature. A Monte Carlo study shows that the quadrature works well infinite sample for a number of evaluation points as small as two. Incorrectly ignoring the individual effects, or the dependence between the initial conditions and the individual effects results in an overestimation of the coefficients of the lagged dependent variables. An application to incremental and radical product innovations by Dutch business firms illustrates the method.

Cette étude propose une façon d’utiliser l’estimateur du maximum de vraisemblance pour des données panel et des modèles dynamiques de type tobit 2 ou tobit 3. La fonction de vraisemblance inclut une intégrale double qui est évaluée en utilisant une quadrature Gauss-Hermite à deux étapes. Une étude de Monte Carlo montre que la quadrature donne de bons résultats dans un échantillon fini même avec uniquement deux points d’évaluation. Si on ignore les effets individuels ou la dépendance entre ceux-ci et les conditions initiales, on obtient une estimation biaisée vers le haut des coefficients des variables endogènes retardées. Une application à l’étude des innovations de produit radicales et incrémentales avec des données panel d’entreprises néerlandaises illustre la méthode proposée.

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Paper provided by CIRANO in its series CIRANO Working Papers with number 2007s-06.

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Date of creation: 01 Mar 2007
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Handle: RePEc:cir:cirwor:2007s-06

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Related research
Keywords: panel data; maximum likelihood estimator; dynamic models; sample selection; données panel; maximum de vraisemblance; modéles dynamiques avec sélection;

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    Other versions:
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  19. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-64, May. [Downloadable!] (restricted)
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