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Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach

Author

Listed:
  • Guohua Feng

    (University of North Texas)

  • Chuan Wang

    (Zhongnan University of Economics and Law)

  • Xibin Zhang

    (Monash University)

Abstract

We propose a kernel-based Bayesian framework for the analysis of stochastic frontiers and efficiency measurement. The primary feature of this framework is that the unknown distribution of inefficiency is approximated by a transformed Rosenblatt-Parzen kernel density estimator. To justify the kernel-based model, we conduct a Monte Carlo study and also apply the model to a panel of U.S. large banks. Simulation results show that the kernel-based model is capable of providing more precise estimation and prediction results than the commonly-used exponential stochastic frontier model. The Bayes factor also favors the kernel-based model over the exponential model in the empirical application.

Suggested Citation

  • Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    • Handle: RePEc:kap:jproda:v:51:y:2019:i:1:d:10.1007_s11123-018-0542-x
    DOI: 10.1007/s11123-018-0542-x
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    Cited by:

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    3. Li, Huijuan & Cai, Weihong & Li, Wenxiu, 2021. "Does global value chains participation improve skill premium? Mediating role of skill-biased technological change," Economic Modelling, Elsevier, vol. 99(C).
    4. Guohua Feng & Chuan Wang, 2021. "Determinants of profitability of community banks in the USA: a cost-frontier-based decomposition approach," Empirical Economics, Springer, vol. 60(6), pages 2969-2992, June.

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    More about this item

    Keywords

    Kernel density estimation; Efficiency measurement; Stochastic distance frontier; Markov Chain Monte Carlo;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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