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Bayesian inference in threshold stochastic frontier models

Author

Listed:
  • Efthymios G. Tsionas

    (Lancaster University Management School
    Athens University of Economics and Business)

  • Kien C. Tran

    (University of Lethbridge)

  • Panayotis G. Michaelides

    (London School of Economics
    National Technical University of Athens)

Abstract

In this paper, we generalize the stochastic frontier model to allow for heterogeneous technologies and inefficiencies in a structured way that allows for learning and adapting. We propose a general model and various special cases, organized around the idea that there is switching or transition from one technology to the other(s), and construct threshold stochastic frontier models. We suggest Bayesian inferences for the general model proposed here and its special cases using Gibbs sampling with data augmentation. The new techniques are applied, with very satisfactory results, to a panel of world production functions using, as switching or transition variables, human capital, age of capital stock (representing input quality), as well as a time trend to capture structural switching.

Suggested Citation

  • Efthymios G. Tsionas & Kien C. Tran & Panayotis G. Michaelides, 2019. "Bayesian inference in threshold stochastic frontier models," Empirical Economics, Springer, vol. 56(2), pages 399-422, February.
    • Handle: RePEc:spr:empeco:v:56:y:2019:i:2:d:10.1007_s00181-017-1364-9
    DOI: 10.1007/s00181-017-1364-9
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    More about this item

    Keywords

    Stochastic frontier; Regime switching; Efficiency measurement; Bayesian inference; Markov Chain Monte Carlo;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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