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Estimation of a smooth coefficient zero-inefficiency panel stochastic frontier model: A semiparametric approach

Author

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  • Yao, Feng
  • Wang, Taining
  • Tian, Jinjing
  • Kumbhakar, Subal C.

Abstract

In this paper we propose a zero-inefficiency stochastic frontier model with a simple semiparametric approach using panel data. We model the frontier with a smooth coefficient function and specify a nonzero conditional probability for firms being fully efficient to be a known function of environment variables. Following (Yao et al., 2017) we propose a three step semiparametric estimator which is computationally efficient. The simulation results reveal encouraging finite sample properties. We illustrate the applicability of our model using country level data from the Penn World Table.

Suggested Citation

  • Yao, Feng & Wang, Taining & Tian, Jinjing & Kumbhakar, Subal C., 2018. "Estimation of a smooth coefficient zero-inefficiency panel stochastic frontier model: A semiparametric approach," Economics Letters, Elsevier, vol. 166(C), pages 25-30.
    • Handle: RePEc:eee:ecolet:v:166:y:2018:i:c:p:25-30
    DOI: 10.1016/j.econlet.2018.02.015
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    Cited by:

    1. Taining Wang & Jinjing Tian & Feng Yao, 2021. "Does high debt ratio influence Chinese firms’ performance? A semiparametric stochastic frontier approach with zero inefficiency," Empirical Economics, Springer, vol. 61(2), pages 587-636, August.
    2. Wang, Taining & Henderson, Daniel J., 2022. "Estimation of a varying coefficient, fixed-effects Cobb–Douglas production function in levels," Economics Letters, Elsevier, vol. 213(C).

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    More about this item

    Keywords

    Zero inefficiency; Semiparametric smooth coefficient model; Stochastic frontier;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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