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Consistent inference in fixed-effects stochastic frontier models

Author

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  • Federico Belotti

    () (University of Rome Tor Vergata)

  • Giuseppe Ilardi

    () (Bank of Italy)

Abstract

The classical stochastic frontier panel data models provide no mechanism for disentangling individual time-invariant unobserved heterogeneity from inefficiency. Greene (2005a, b) proposed the ‘true’ fixed-effects specification, which distinguishes these two latent components while allowing for time-variant inefficiency. However, due to the incidental parameters problem, the maximum likelihood estimator proposed by Greene may lead to biased variance estimates. We propose two alternative estimation procedures that, by relying on a first-difference data transformation, achieve consistency when n goes to infinity with fixed T. Furthermore, we extend the approach of Chen et al. (2014) by providing a computationally feasible solution for estimating models in which inefficiency can be heteroskedastic and may follow a first-order autoregressive process. We investigate the finite sample behavior of the proposed estimators through a set of Monte Carlo experiments. Our results show good finite sample properties, especially in small samples. We illustrate the usefulness of the new approach by applying it to the technical efficiency of hospitals.

Suggested Citation

  • Federico Belotti & Giuseppe Ilardi, 2017. "Consistent inference in fixed-effects stochastic frontier models," Temi di discussione (Economic working papers) 1147, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_1147_17
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    References listed on IDEAS

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    More about this item

    Keywords

    stochastic frontiers; fixed-effects; panel data; pairwise differencing;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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