IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v147y2016icp19-22.html
   My bibliography  Save this article

On the estimation of zero-inefficiency stochastic frontier models with endogenous regressors

Author

Listed:
  • Tran, Kien C.
  • Tsionas, Mike G.

Abstract

In this paper, we investigate endogeneity issues in the zero-inefficiency stochastic frontier (ZISF) models by mean of simultaneous equation setting. Specifically, we allow for one or more regressors to be correlated with the statistical noise. A modified limited information maximum likelihood (LIML) approach is used to estimate the parameters of the model. Moreover, the firm specific inefficiency score is also provided. Limited Monte Carlo simulations show that the proposed estimators perform well in finite sample.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecolet:v:147:y:2016:i:c:p:19-22
    DOI: 10.1016/j.econlet.2016.08.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016517651630307X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2016.08.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    2. Seunghwa Rho & Peter Schmidt, 2015. "Are all firms inefficient?," Journal of Productivity Analysis, Springer, vol. 43(3), pages 327-349, June.
    3. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    4. Tran, Kien C. & Tsionas, Efthymios G., 2013. "GMM estimation of stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 118(1), pages 233-236.
    5. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    6. Kumbhakar, Subal C. & Parmeter, Christopher F. & Tsionas, Efthymios G., 2013. "A zero inefficiency stochastic frontier model," Journal of Econometrics, Elsevier, vol. 172(1), pages 66-76.
    7. Christine Amsler & Artem Prokhorov & Peter Schmidt, 2014. "Using Copulas to Model Time Dependence in Stochastic Frontier Models," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 497-522, August.
    8. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    9. Kutlu, Levent, 2010. "Battese-coelli estimator with endogenous regressors," Economics Letters, Elsevier, vol. 109(2), pages 79-81, November.
    10. 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.
    11. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    2. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Centorrino, Samuele & Pérez-Urdiales, María, 2023. "Maximum likelihood estimation of stochastic frontier models with endogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 82-105.
    2. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    3. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    4. William C. Horrace & Hyunseok Jung, 2018. "Stochastic frontier models with network selectivity," Journal of Productivity Analysis, Springer, vol. 50(3), pages 101-116, December.
    5. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2017. "Endogenous environmental variables in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 199(2), pages 131-140.
    6. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    7. Mustafa U. Karakaplan & Levent Kutlu, 2019. "School district consolidation policies: endogenous cost inefficiency and saving reversals," Empirical Economics, Springer, vol. 56(5), pages 1729-1768, May.
    8. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    9. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    10. Mustafa U. Karakaplan & Levent Kutlu, 2017. "Handling Endogeneity in Stochastic Frontier Analysis," Economics Bulletin, AccessEcon, vol. 37(2), pages 889-901.
    11. 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.
    12. Yang Yu & Edward C. Jaenicke, 2020. "Estimating Food Waste as Household Production Inefficiency," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 525-547, March.
    13. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    14. 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).
    15. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.
    16. Mustafa U. Karakaplan & Levent Kutlu, 2019. "Estimating market power using a composed error model," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(4), pages 489-510, September.
    17. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C. & Weyman-Jones, Thomas, 2018. "The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model," Working Papers 18-003, Rice University, Department of Economics.
    18. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    19. Mike G. Tsionas, 2017. "“When, Where, and How” of Efficiency Estimation: Improved Procedures for Stochastic Frontier Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 948-965, July.
    20. Wondmagegn Tirkaso & Atakelty Hailu, 2022. "Does neighborhood matter? Spatial proximity and farmers’ technical efficiency," Agricultural Economics, International Association of Agricultural Economists, vol. 53(3), pages 374-386, May.

    More about this item

    Keywords

    Endogeneity; Fully efficient firm; Limited information maximum likelihood; Firm specific inefficiency score; Zero-inefficiency stochastic frontier;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:147:y:2016:i:c:p:19-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.