Estimating SUR system with random coefficients: the unbalanced panel data case
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A system of regression equations for analyzing panel data with random heterogeneity in intercepts and coefficients, and unbalanced panel data is considered. A maximum likelihood (ML) procedure for joint estimation of all parameters is described. Since its implementation for numerical computation is complicated, simplified procedures are presented. The simplifications essentially concern the estimation of the covariance matrices of the random coefficients. The application and ‘anatomy’ of the proposed algorithm for modified ML estimation are illustrated by using panel data for output, inputs and costs for 111 manufacturing firms observed up to 22 years.
KeywordsPanel data Unbalanced data Random coefficients Heterogeneity Regression systems Iterated maximum likelihood
JEL ClassificationC33 C51 C63 D24
An earlier version of the paper was presented at the Sixteenth International Conference on Panel Data, Amsterdam, July 2010. I am grateful to Xuehui Han for excellent programming assistance and Terje Skjerpen and a referee for comments.
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