Estimation of a panel data model with parametric temporal variation in individual effects
This paper is an extension of Ahn, Lee and Schmidt (2001) to allow a parametric function for time-varying coefficients on the individual effects. It is shown that the main results of Ahn, Lee and Schmidt (2001) hold for our model too. Least squares is consistent, given white noise errors, but less efficient than a GMM estimator. An application of the GMM estimators to the measurement of cost efficiency of Spanish banks is also included. The empirical study shows the consequences of increasing the number of assumptions made regarding the error term. The GMM estimates, especially for private banks, cast doubt on the normality assumption supporting the traditional MLE frontier models.
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