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Productivity and efficiency estimation: A semiparametric stochastic cost frontier approach

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  • Sun, Kai
  • Kumbhakar, Subal C.
  • Tveterås, Ragnar

Abstract

This paper proposes a flexible stochastic cost frontier panel data model where the technology parameters are unknown smooth functions of firm- and time-effects, which non-neutrally shift the cost frontier. The model decomposes inefficiency into firm and time-specific components and productivity change into inefficiency change, technical change and scale change. We then apply the proposed methodology to the Norwegian salmon production data and analyze technical efficiency as well as productivity changes.

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  • Sun, Kai & Kumbhakar, Subal C. & Tveterås, Ragnar, 2015. "Productivity and efficiency estimation: A semiparametric stochastic cost frontier approach," European Journal of Operational Research, Elsevier, vol. 245(1), pages 194-202.
    • Handle: RePEc:eee:ejores:v:245:y:2015:i:1:p:194-202
    DOI: 10.1016/j.ejor.2015.03.003
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    1. Subal Kumbhakar & M. Denny & M. Fuss, 2000. "Estimation and decomposition of productivity change when production is not efficient: a paneldata approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 312-320.
    2. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    3. Ragnar Tveteras & George E. Battese, 2006. "Agglomeration Externalities, Productivity, And Technical Inefficiency," Journal of Regional Science, Wiley Blackwell, vol. 46(4), pages 605-625, October.
    4. 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.
    5. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    6. Luis Orea, 2002. "Parametric Decomposition of a Generalized Malmquist Productivity Index," Journal of Productivity Analysis, Springer, vol. 18(1), pages 5-22, July.
    7. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    8. 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.
    9. Li, Qi, et al, 2002. "Semiparametric Smooth Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 412-422, July.
    10. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    11. Li, Qi & Racine, Jeffrey S., 2010. "Smooth Varying-Coefficient Estimation And Inference For Qualitative And Quantitative Data," Econometric Theory, Cambridge University Press, vol. 26(6), pages 1607-1637, December.
    12. Subal kumbhakar & Ana Lozano-Vivas, 2005. "Deregulation and Productivity: The Case of Spanish Banks," Journal of Regulatory Economics, Springer, vol. 27(3), pages 331-351, January.
    13. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    14. Kai Sun, 2015. "Constrained nonparametric estimation of input distance function," Journal of Productivity Analysis, Springer, vol. 43(1), pages 85-97, February.
    15. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-468, October.
    16. Kumbhakar, Subal C. & Park, Byeong U. & Simar, Leopold & Tsionas, Efthymios G., 2007. "Nonparametric stochastic frontiers: A local maximum likelihood approach," Journal of Econometrics, Elsevier, vol. 137(1), pages 1-27, March.
    17. Subal Kumbhakar & Kai Sun, 2012. "Estimation of TFP growth: a semiparametric smooth coefficient approach," Empirical Economics, Springer, vol. 43(1), pages 1-24, August.
    18. Sun, Kai & Kumbhakar, Subal C., 2013. "Semiparametric smooth-coefficient stochastic frontier model," Economics Letters, Elsevier, vol. 120(2), pages 305-309.
    19. 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.
    20. Christopher Parmeter & Kai Sun & Daniel Henderson & Subal Kumbhakar, 2014. "Estimation and inference under economic restrictions," Journal of Productivity Analysis, Springer, vol. 41(1), pages 111-129, February.
    21. 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.
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    Cited by:

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    2. Tsionas, Mike G. & Mallick, Sushanta K., 2019. "A Bayesian semiparametric approach to stochastic frontiers and productivity," European Journal of Operational Research, Elsevier, vol. 274(1), pages 391-402.
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    10. Kai Sun & Ruhul Salim, 2020. "A semiparametric stochastic input distance frontier model with application to the Indonesian banking industry," Journal of Productivity Analysis, Springer, vol. 54(2), pages 139-156, December.
    11. Pontus Mattsson & Jonas Månsson & William H. Greene, 2020. "TFP change and its components for Swedish manufacturing firms during the 2008–2009 financial crisis," Journal of Productivity Analysis, Springer, vol. 53(1), pages 79-93, February.
    12. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
    13. Pontus Mattsson & Jonas Mansson & William H. Greene, 2018. "TFP Change and its Components for Swedish Manufacturing Firms During the 2008-2009 Financial Crisis," Working Papers 18-27, New York University, Leonard N. Stern School of Business, Department of Economics.
    14. Baležentis, Tomas & Sun, Kai, 2020. "Measurement of technical inefficiency and total factor productivity growth: A semiparametric stochastic input distance frontier approach and the case of Lithuanian dairy farms," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1174-1188.
    15. Astrid Cullmann & Maria Nieswand & Julia Rechlitz, 2017. "Productive Efficiency and Ownership When Market Restructuring Affects Production Technologies," Discussion Papers of DIW Berlin 1641, DIW Berlin, German Institute for Economic Research.
    16. Michael L. Polemis & Mike G. Tsionas, 2022. "Endogenous productivity: a new Bayesian perspective," Annals of Operations Research, Springer, vol. 318(1), pages 425-451, November.
    17. Mamatzakis, Emmanuel & matousek, roman & vu, anh, 2019. "The interplay between problem loans and Japanese bank productivity," MPRA Paper 92960, University Library of Munich, Germany.
    18. Tsionas, Mike G., 2017. "Microfoundations for stochastic frontiers," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1165-1170.
    19. Glass, Anthony J. & Kenjegalieva, Karligash & Douch, Mustapha, 2020. "Uncovering spatial productivity centers using asymmetric bidirectional spillovers," European Journal of Operational Research, Elsevier, vol. 285(2), pages 767-788.
    20. Anaya, Karim L. & Pollitt, Michael G., 2017. "Using stochastic frontier analysis to measure the impact of weather on the efficiency of electricity distribution businesses in developing economies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1078-1094.
    21. Bolt, Wilko & Humphrey, David, 2015. "A frontier measure of U.S. banking competition," European Journal of Operational Research, Elsevier, vol. 246(2), pages 450-461.
    22. Chaudhuri, Kausik & Kumbhakar, Subal C. & Sundaram, Lavanya, 2016. "Estimation of firm performance from a MIMIC model," European Journal of Operational Research, Elsevier, vol. 255(1), pages 298-307.
    23. Glass, Anthony J. & Kenjegalieva, Karligash, 2019. "A spatial productivity index in the presence of efficiency spillovers: Evidence for U.S. banks, 1992–2015," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1165-1179.

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