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Endogeneity in stochastic frontier models

Author

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  • Amsler, Christine
  • Prokhorov, Artem
  • Schmidt, Peter

Abstract

Stochastic frontier models are typically estimated by maximum likelihood (MLE) or corrected ordinary least squares. The consistency of either estimator depends on exogeneity of the explanatory variables (inputs, in the production frontier setting). We will investigate the case that one or more of the inputs is endogenous, in the simultaneous equation sense of endogeneity. That is, we worry that there is correlation between the inputs and statistical noise or inefficiency.

Suggested Citation

  • Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
  • Handle: RePEc:eee:econom:v:190:y:2016:i:2:p:280-288
    DOI: 10.1016/j.jeconom.2015.06.013
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    Citations

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    Cited by:

    1. Petrick, Martin & Kloss, Mathias, 2018. "Identifying factor productivity from micro-data: The case of EU agriculture," IAMO Discussion Papers 171, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    2. Graziella Bonanno & Domenico De Giovanni & Filippo Domma, 2017. "The ‘wrong skewness’ problem: a re-specification of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 47(1), pages 49-64, February.
    3. repec:eee:econom:v:199:y:2017:i:2:p:131-140 is not listed on IDEAS
    4. Bernini, Cristina & Cerqua, Augusto & Pellegrini, Guido, 2017. "Public subsidies, TFP and efficiency: A tale of complex relationships," Research Policy, Elsevier, vol. 46(4), pages 751-767.
    5. repec:eee:deveco:v:132:y:2018:i:c:p:18-31 is not listed on IDEAS
    6. Malikov, Emir, 2016. "Estimating Multi-Product Production Functions and Productivity using Control Functions," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 235108, Agricultural and Applied Economics Association.
    7. repec:ebl:ecbull:eb-16-00551 is not listed on IDEAS
    8. Orea, Luis & Zofío, José L., 2017. "A primer on the theory and practice of efficiency and productivity analysis," Efficiency Series Papers 2017/05, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    9. Tran, Kien C. & Tsionas, Mike G., 2016. "On the estimation of zero-inefficiency stochastic frontier models with endogenous regressors," Economics Letters, Elsevier, vol. 147(C), pages 19-22.
    10. repec:spr:soinre:v:132:y:2017:i:2:d:10.1007_s11205-016-1315-4 is not listed on IDEAS
    11. repec:bla:jageco:v:68:y:2017:i:2:p:494-517 is not listed on IDEAS
    12. Tran, Kien C. & Tsionas, Efthymios G., 2015. "Endogeneity in stochastic frontier models: Copula approach without external instruments," Economics Letters, Elsevier, vol. 133(C), pages 85-88.
    13. repec:gam:jijfss:v:6:y:2018:i:1:p:14-:d:128829 is not listed on IDEAS
    14. repec:eee:enepol:v:114:y:2018:i:c:p:145-152 is not listed on IDEAS
    15. repec:oup:ajagec:v:99:y:2017:i:3:p:783-799. is not listed on IDEAS
    16. Gale A. Boyd & Jonathan M. Lee, 2018. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," Working Papers 18-16, Center for Economic Studies, U.S. Census Bureau.
    17. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2017. "Endogenous environmental variables in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 199(2), pages 131-140.
    18. repec:psc:journl:v:9:y:2017:i:3:p:243-273 is not listed on IDEAS

    More about this item

    Keywords

    Endogeneity; Stochastic frontier; Efficiency measurement;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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