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Technical and allocative efficiency in a panel stochastic production frontier system model

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  • Lai, Hung-pin
  • Kumbhakar, Subal C.

Abstract

In this paper, we consider a state-of-the-art panel stochastic production frontier model and estimate it using a system that includes both technical and allocative inefficiency. The system consists of the optimal input choice rule (the first-order conditions (FOCs)) under cost minimization together with the production function. The FOCs are used to take care of endogeneity of inputs. Allocative inefficiency is modeled as non-fulfillment of the FOCs. We use distributional assumptions on the noise and inefficiency components and estimate the model parameters using the maximum likelihood method. In estimating technical and allocative inefficiency components and costs therefrom we control for fixed firm-effects in each equation of the system. We also correct for the incidental parameter bias by using the half-panel jackknife estimator.

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  • Lai, Hung-pin & Kumbhakar, Subal C., 2019. "Technical and allocative efficiency in a panel stochastic production frontier system model," European Journal of Operational Research, Elsevier, vol. 278(1), pages 255-265.
    • Handle: RePEc:eee:ejores:v:278:y:2019:i:1:p:255-265
    DOI: 10.1016/j.ejor.2019.04.001
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    1. F. Bartolucci & R. Bellio & A. Salvan & N. Sartori, 2016. "Modified Profile Likelihood for Fixed-Effects Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1271-1289, August.
    2. Kumbhakar, Subal C. & Wang, Hung-Jen, 2006. "Estimation of technical and allocative inefficiency: A primal system approach," Journal of Econometrics, Elsevier, vol. 134(2), pages 419-440, October.
    3. Geert Dhaene & Koen Jochmans, 2015. "Split-panel Jackknife Estimation of Fixed-effect Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 991-1030.
    4. Brissimis, Sophocles N. & Delis, Manthos D. & Tsionas, Efthymios G., 2010. "Technical and allocative efficiency in European banking," European Journal of Operational Research, Elsevier, vol. 204(1), pages 153-163, July.
    5. Banker, Rajiv D. & Janakiraman, Surya & Natarajan, Ram, 2004. "Analysis of trends in technical and allocative efficiency: An application to Texas public school districts," European Journal of Operational Research, Elsevier, vol. 154(2), pages 477-491, April.
    6. 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.
    7. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    8. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    9. Manuel Arellano & Jinyong Hahn, 2016. "A likelihood-Based Approximate Solution to the Incidental Parameter Problem in Dynamic Nonlinear Models with Multiple Effects," Global Economic Review, Taylor & Francis Journals, vol. 45(3), pages 251-274, July.
    10. Kumbhakar, Subal C., 1997. "Modeling allocative inefficiency in a translog cost function and cost share equations: An exact relationship," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 351-356.
    11. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "The Joint Measurement of Technical and Allocative Inefficiencies: An Application of Bayesian Inference in Nonlinear Random-Effects Models," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 736-747, September.
    12. Laurits R. Christensen & Dale W. Jorgenson, 1970. "U.S. Real Product And Real Factor Input, 1929–1967," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 16(1), pages 19-50, March.
    13. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 355-384, June.
    14. Haelermans, Carla & Ruggiero, John, 2013. "Estimating technical and allocative efficiency in the public sector: A nonparametric analysis of Dutch schools," European Journal of Operational Research, Elsevier, vol. 227(1), pages 174-181.
    15. Schmidt, Peter, 1988. "Estimation of a fixed-effect Cobb-Douglas system using panel data," Journal of Econometrics, Elsevier, vol. 37(3), pages 361-380, March.
    16. Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, July.
    17. Banker, Rajiv D & Maindiratta, Ajay, 1988. "Nonparametric Analysis of Technical and Allocative Efficiencies in Production," Econometrica, Econometric Society, vol. 56(6), pages 1315-1332, November.
    18. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    19. Athanassopoulos, Antreas & Gounaris, Chrysostomos, 2001. "Assessing the technical and allocative efficiency of hospital operations in Greece and its resource allocation implications," European Journal of Operational Research, Elsevier, vol. 133(2), pages 416-431, January.
    20. 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.
    21. 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.
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    8. Dibyendu Maiti & Chiranjib Neogi, 2024. "Endogeneity-corrected stochastic frontier with market imperfections," Empirical Economics, Springer, vol. 67(3), pages 1149-1183, September.
    9. Musau, Andrew & Kumbhakar, Subal C. & Mydland, Ørjan & Lien, Gudbrand, 2021. "Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms," European Journal of Operational Research, Elsevier, vol. 288(3), pages 983-991.
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    12. Hou, Zheng & Roseta-Palma, Catarina & Ramalho, Joaquim J.S., 2024. "Can operational efficiency in the Portuguese electricity sector be improved? Yes, but..," Energy Policy, Elsevier, vol. 190(C).

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