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A spatial stochastic frontier model with endogenous frontier and environmental variables

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  • Kutlu, Levent
  • Tran, Kien C.
  • Tsionas, Mike G.

Abstract

We propose a spatial autoregressive stochastic frontier model, which allows for the endogeneity in both the frontier and environmental variables (i.e., endogeneity due to correlation of inefficiency term and two-sided error term). The model parameters are estimated using a single-stage control function approach. Monte Carlo simulations show that our proposed model and approach perform well in finite samples. We employed our methodology to the Chinese chemicals firm data and found evidence for both spatial effects and endogeneity.

Suggested Citation

  • Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2020. "A spatial stochastic frontier model with endogenous frontier and environmental variables," European Journal of Operational Research, Elsevier, vol. 286(1), pages 389-399.
  • Handle: RePEc:eee:ejores:v:286:y:2020:i:1:p:389-399
    DOI: 10.1016/j.ejor.2020.03.020
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    Cited by:

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    2. Sadick Mohammed & Awudu Abdulai, 2022. "Do Egocentric information networks influence technical efficiency of farmers? Empirical evidence from Ghana," Journal of Productivity Analysis, Springer, vol. 58(2), pages 109-128, December.
    3. Hou, Zhezhi & Zhao, Shunan & Kumbhakar, Subal C., 2023. "The GMM estimation of semiparametric spatial stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1450-1464.
    4. Anthony J. Glass & Karligash Kenjegalieva, 2023. "Dynamic returns to scale and geography in U.S. banking," Papers in Regional Science, Wiley Blackwell, vol. 102(1), pages 53-85, February.
    5. Tran, Kien C. & Tsionas, Mike G. & Prokhorov, Artem B., 2023. "Semiparametric estimation of spatial autoregressive smooth-coefficient panel stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1189-1199.
    6. Mustafa U. Karakaplan & Levent Kutlu & Mike G. Tsionas, 2020. "A solution to log of dependent variables with negative observations," Journal of Productivity Analysis, Springer, vol. 54(2), pages 107-119, December.
    7. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
    8. Kutlu, Levent, 2023. "Calculating efficiency for spatial autoregressive stochastic frontier model," Economics Letters, Elsevier, vol. 225(C).
    9. Li, Mingyang & Jin, Man & Kumbhakar, Subal C., 2022. "Do subsidies increase firm productivity? Evidence from Chinese manufacturing enterprises," European Journal of Operational Research, Elsevier, vol. 303(1), pages 388-400.
    10. Vidoli, Francesco & Auteri, Monica & Marinuzzi, Giorgia & Tortorella, Walter, 2023. "Spatial interdependence in cost efficiency and local government optimal size: The case of Italian municipalities," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    11. D’Inverno, Giovanna & Vidoli, Francesco & De Witte, Kristof, 2023. "Sustainable budgeting and financial balance: Which lever will you pull?," European Journal of Operational Research, Elsevier, vol. 309(2), pages 857-871.
    12. Kerui Du & Luis Orea & Inmaculada C. Alvarez, 2023. "Fitting spatial stochastic frontier models in Stata," Efficiency Series Papers 2023/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    13. 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.
    14. M.V. Leonov, 2021. "Review of Modern Approaches for Assessing the Effectiveness of Banking," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 294-326.
    15. Lamees Al-Durgham & Mohammad Adeinat, 2020. "Efficiency of Listed Manufacturing Firms in Jordan: A Stochastic Frontier Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 5-9.
    16. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    17. Hung-pin Lai & Kien C. Tran, 2022. "Persistent and transient inefficiency in a spatial autoregressive panel stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 58(1), pages 1-13, August.
    18. E. Fusco & R. Benedetti & F. Vidoli, 2023. "Stochastic frontier estimation through parametric modelling of quantile regression coefficients," Empirical Economics, Springer, vol. 64(2), pages 869-896, February.
    19. Carmelo Algeri & Luc Anselin & Antonio Fabio Forgione & Carlo Migliardo, 2022. "Spatial dependence in the technical efficiency of local banks," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 685-716, June.
    20. Emir Malikov & Jingfang Zhang & Shunan Zhao & Subal C. Kumbhakar, 2023. "Accounting for Cross-Location Technological Heterogeneity in the Measurement of Operations Efficiency and Productivity," Papers 2302.13430, arXiv.org.

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    More about this item

    Keywords

    Productivity and competitiveness; Chinese chemical firms; Endogeneity; Spatial autoregressive spillover; Stochastic frontier;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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