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Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model

Author

Listed:
  • Kien C. Tran

    (University of Lethbridge)

  • Mike G. Tsionas

    (Lancaster University Management School)

Abstract

This paper proposes a semiparametric spatial autoregressive stochastic frontier model where the spatial lag on the dependent variable enters linearly whilst the functional form of the frontier is modeled nonparametrically. A three-step estimation procedure is considered where in the first two steps, a constrained (i.e., shape restrictions) semiparametric profile generalized method of moments that is based on the localized instruments of exogenous variables in the model and their spatial weighted version is used to obtain the estimates of the spatial parameter and the unknown smooth function of the frontier; whilst in the final step, the remaining parameters of the model can be estimated using maximum likelihood procedure. We derive the limiting distributions of the proposed estimators for both parametric and nonparametric components in the model. Monte Carlo simulations reveal that our proposed estimators perform well in finite samples. An empirical application of the Chinese Chemical firms is presented to illustrate the usefulness of the proposed approach in practice.

Suggested Citation

  • Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    • Handle: RePEc:spr:jospat:v:4:y:2023:i:1:d:10.1007_s43071-023-00036-z
    DOI: 10.1007/s43071-023-00036-z
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    More about this item

    Keywords

    Inefficiency spillovers; Maximum likelihood; Nonparametric frontier; Profile GMM; Shape restrictions; Spatial autoregressive;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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