IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v163y2018icp152-154.html
   My bibliography  Save this article

A distribution-free stochastic frontier model with endogenous regressors

Author

Listed:
  • Kutlu, Levent

Abstract

We provide a guideline for estimating a distribution-free panel data stochastic frontier model in the presence of endogenous variables. In particular, we consider variations of the within estimator of Cornwell et al. (1990) to allow endogenous regressors.

Suggested Citation

  • Kutlu, Levent, 2018. "A distribution-free stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 163(C), pages 152-154.
    • Handle: RePEc:eee:ecolet:v:163:y:2018:i:c:p:152-154
    DOI: 10.1016/j.econlet.2017.12.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517305219
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2017.12.026?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. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2017. "Endogenous environmental variables in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 199(2), pages 131-140.
    2. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    3. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    4. Mustafa U. Karakaplan & Levent Kutlu, 2017. "Handling Endogeneity in Stochastic Frontier Analysis," Economics Bulletin, AccessEcon, vol. 37(2), pages 889-901.
    5. Mustafa U. Karakaplan & Levent Kutlu, 2017. "Endogeneity in panel stochastic frontier models: an application to the Japanese cotton spinning industry," Applied Economics, Taylor & Francis Journals, vol. 49(59), pages 5935-5939, December.
    6. 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.
    7. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    8. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    9. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    10. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    11. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    12. 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.
    13. Kutlu, Levent, 2010. "Battese-coelli estimator with endogenous regressors," Economics Letters, Elsevier, vol. 109(2), pages 79-81, November.
    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. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    2. 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.
    3. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    4. 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.
    5. Binlei Gong & Robin C. Sickles, 2020. "Non-structural and structural models in productivity analysis: study of the British Isles during the 2007–2009 financial crisis," Journal of Productivity Analysis, Springer, vol. 53(2), pages 243-263, April.
    6. 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.
    7. 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.

    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. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
    2. 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.
    3. Badunenko, Oleg & D’Inverno, Giovanna & De Witte, Kristof, 2023. "On distinguishing the direct causal effect of an intervention from its efficiency-enhancing effects," European Journal of Operational Research, Elsevier, vol. 310(1), pages 432-447.
    4. 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.
    5. 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.
    6. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    7. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    8. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.
    9. 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.
    10. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    11. 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.
    12. Kutlu, Levent & Nair-Reichert, Usha, 2022. "Executive compensation and the potential for additional efficiency gains: Evidence from the Indian manufacturing sector," Economic Modelling, Elsevier, vol. 114(C).
    13. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    14. Kutlu, Levent & Sickles, Robin C., 2012. "Estimation of market power in the presence of firm level inefficiencies," Journal of Econometrics, Elsevier, vol. 168(1), pages 141-155.
    15. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    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. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    18. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    19. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    20. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.

    More about this item

    Keywords

    Endogeneity; Time-varying efficiency; Panel data; 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

    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:163:y:2018:i:c:p:152-154. 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.