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Estimation of a panel stochastic frontier model with unobserved common shocks

  • Hsu, Chih-Chiang
  • Lin, Chang-Ching
  • Yin, Shou-Yung
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    This paper develops panel stochastic frontier models with unobserved common correlated effects. The common correlated effects provide a way of modeling cross-sectional dependence and represent heterogeneous impacts on individuals resulting from unobserved common shocks. Traditional panel stochastic frontier models do not distinguish between common correlated effects and technical inefficiency. In this paper, we propose a modified maximum likelihood estimator (MLE) that does not require estimating unobserved common correlated effects. We show that the proposed method can control the common correlated effects and obtain consistent estimates of parameters and technical efficiency for the panel stochastic frontier model. Our Monte Carlo simulations show that the modified MLE has satisfactory finite sample properties under a significant degree of cross-sectional dependence for relatively small T. The proposed method is also illustrated in applications based on a cross country comparison of the efficiency of banking industries.

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    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 37313.

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    Date of creation: Mar 2012
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    Handle: RePEc:pra:mprapa:37313
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    1. William Greene, 2002. "Fixed and Random Effects in Stochastic Frontier Models," Working Papers 02-16, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    3. Wang, Hung-jen & Schmidt, Peter, 2001. "One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels," MPRA Paper 31075, University Library of Munich, Germany, revised Mar 2002.
    4. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-97, November.
    5. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1989. "Production Frontiers With Cross-Sectinal And Time-Series Variation In Efficiency Levels," Working Papers 89-18, C.V. Starr Center for Applied Economics, New York University.
    6. M. Hashem Pesaran, 2004. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," CESifo Working Paper Series 1331, CESifo Group Munich.
    7. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, 07.
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    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.
    12. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
    13. William Greene, 2003. "Distinguishing Between Heterogeneity and Inefficiency: Stochastic Frontier Analysis of the World Health Organization’s Panel Data on National Health Care Systems," Working Papers 03-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    14. Manthos D. Delis & Nikolaos I. Papanikolaou, 2009. "Determinants of bank efficiency: evidence from a semi-parametric methodology," Managerial Finance, Emerald Group Publishing, vol. 35(3), pages 260-275.
    15. Berger, Allen N. & Hasan, Iftekhar & Zhou, Mingming, 2009. "Bank ownership and efficiency in China: What will happen in the world's largest nation?," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 113-130, January.
    16. Lensink, Robert & Meesters, Aljar & Naaborg, Ilko, 2008. "Bank efficiency and foreign ownership: Do good institutions matter?," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 834-844, May.
    17. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.
    18. 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.
    19. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    20. Kiviet, Jan F. & Phillips, Garry D. A., 1994. "Bias assessment and reduction in linear error-correction models," Journal of Econometrics, Elsevier, vol. 63(1), pages 215-243, July.
    21. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
    22. Lee, Young Hoon, 2006. "A stochastic production frontier model with group-specific temporal variation in technical efficiency," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1616-1630, November.
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