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Computation and Inference in Semiparametric Efficient Estimation

  • Robert M. Adams
  • Allen N. Berger
  • Robin C. Sickles
Part of the Advances in Computational Economics book series (AICE, volume 6)

Abstract

This paper examines computational issues in semiparametric efficient estimation of stochastic panel distance functions. Our basic model is an extension of Hausman and Taylor (1981), Park and Simar (1995), Park et al. (1996), and allows for a subset of the regressors to be correlated with the random effects. We motivate issues of computation and inference by analyzing the productive efficiency of U.S. banks.

Keywords

Banking Industry Kernel Estimate Stochastic Frontier Kernel Estimator Stochastic Frontier Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Robert M. Adams
  • Allen N. Berger
  • Robin C. Sickles

There are no affiliations available

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