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

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Author Info
Mohnen, Pierre () (UNU-MERIT and University of Maastricht)
Raymond, Wladimir () (University of Maastricht)
Palm, Franz () (University of Maastricht)
Schim van der Loeff, Sybrand () (University of Maastricht)

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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 in finite 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.

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Publisher Info
Paper provided by United Nations University, Maastricht Economic and social Research and training centre on Innovation and Technology in its series UNU-MERIT Working Paper Series with number 007.

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Date of creation: 2007
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Handle: RePEc:dgr:unumer:2007007

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Related research
Keywords: panel data; maximum likelihood estimator; dynamic models; sample selection;

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Find related papers by JEL classification:
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models
O31 - Economic Development, Technological Change, and Growth - - Technological Change - - - Innovation and Invention: Processes and Incentives

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    Other versions:
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