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Some models for stochastic frontiers with endogeneity

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  • Griffiths, William E.
  • Hajargasht, Gholamreza

Abstract

We consider mostly Bayesian estimation of stochastic frontier models where one-sided inefficiencies and/or the idiosyncratic error term are correlated with the regressors. We begin with a model where a Chamberlain–Mundlak device is used to relate a transformation of time-invariant effects to the regressors. This basic model is then extended in two directions: first an extra one-sided error term is added to allow for time-varying efficiencies. Second, a model with an equation for instrumental variables and a more general error covariance structure is introduced to accommodate correlations between both error terms and the regressors. An application of the first and second models to Philippines rice data is provided.

Suggested Citation

  • Griffiths, William E. & Hajargasht, Gholamreza, 2016. "Some models for stochastic frontiers with endogeneity," Journal of Econometrics, Elsevier, vol. 190(2), pages 341-348.
    • Handle: RePEc:eee:econom:v:190:y:2016:i:2:p:341-348
    DOI: 10.1016/j.jeconom.2015.06.012
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    4. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2020. "Socio-institutional determinants of educational resource efficiency according to the capability approach: An endogenous stochastic frontier analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    5. Paul, Satya & Shankar, Sriram, 2018. "On estimating efficiency effects in a stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 271(2), pages 769-774.
    6. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    7. Liu, Xiao-Yan & Pollitt, Michael G. & Xie, Bai-Chen & Liu, Li-Qiu, 2019. "Does environmental heterogeneity affect the productive efficiency of grid utilities in China?," Energy Economics, Elsevier, vol. 83(C), pages 333-344.
    8. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    9. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2017. "Endogenous environmental variables in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 199(2), pages 131-140.
    10. 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.
    11. Heesun Jang & Hyunhee Kim & Hojeong Park, 2020. "Spatiotemporal analysis of Korean ginseng farm productivity," Journal of Productivity Analysis, Springer, vol. 53(1), pages 69-78, February.
    12. Sun, Sunny Li & Chen, Victor Z. & Sunny, Sanwar A. & Chen, Jie, 2019. "Venture capital as an innovation ecosystem engineer in an emerging market," International Business Review, Elsevier, vol. 28(5), pages 1-1.
    13. Massimiliano Giacalone & Demetrio Panarello & Raffaele Mattera, 2018. "Multicollinearity in regression: an efficiency comparison between Lp-norm and least squares estimators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1831-1859, July.
    14. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.
    15. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2019. "A time-varying true individual effects model with endogenous regressors," Journal of Econometrics, Elsevier, vol. 211(2), pages 539-559.
    16. Yang, Zhenbing & Shao, Shuai & Yang, Lili & Miao, Zhuang, 2018. "Improvement pathway of energy consumption structure in China's industrial sector: From the perspective of directed technical change," Energy Economics, Elsevier, vol. 72(C), pages 166-176.
    17. Mustafa U. Karakaplan & Levent Kutlu, 2017. "Handling Endogeneity in Stochastic Frontier Analysis," Economics Bulletin, AccessEcon, vol. 37(2), pages 889-901.
    18. Levent Kutlu & Kien C. Tran & Mike G. Tsionas, 2020. "Unknown latent structure and inefficiency in panel stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 54(1), pages 75-86, August.
    19. Kutlu, Levent & Liu, Shasha & Sickles, Robin C., 2018. "Cost, Revenue, and Profit Function Estimates," Working Papers 18-006, Rice University, Department of Economics.
    20. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.

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    More about this item

    Keywords

    Technical efficiency; Instrumental variables; Gibbs sampling;
    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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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