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Markov switching stochastic frontier model

Author

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  • Efthymios G. Tsionas
  • Subal C. Kumbhakar

Abstract

In this paper, we propose a new approach to stochastic frontier models, viz., a Markov switching structure to accommodate cross-sectional parameter heterogeneity and temporal variation in the parameters and technical inefficiency distributions. The Markov Chain Monte Carlo techniques are developed and implemented for Bayesian inferences on parameters and technical efficiency. We illustrate new methods by estimating world production frontiers using international panel data on 59 countries observed for 26 years. Copyright Royal Economic Socciety 2004

Suggested Citation

  • Efthymios G. Tsionas & Subal C. Kumbhakar, 2004. "Markov switching stochastic frontier model," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 398-425, December.
    • Handle: RePEc:ect:emjrnl:v:7:y:2004:i:2:p:398-425
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    Cited by:

    1. Walheer, Barnabé, 2023. "Meta-frontier and technology switchers: A nonparametric approach," European Journal of Operational Research, Elsevier, vol. 305(1), pages 463-474.
    2. Guanchun Liu & Shichang Ma & Chien‐Chiang Lee & Ming Xu, 2020. "Growth decomposition bias when accounting for heterogeneous regimes: Evidence from China," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 691-711, May.
    3. Vouldis, Angelos T. & Michaelides, Panayotis G. & Tsionas, Efthymios G., 2010. "Estimating semi-parametric output distance functions with neural-based reduced form equations using LIML," Economic Modelling, Elsevier, vol. 27(3), pages 697-704, May.
    4. Bos, J.W.B. & Economidou, C. & Koetter, M., 2010. "Technology clubs, R&D and growth patterns: Evidence from EU manufacturing," European Economic Review, Elsevier, vol. 54(1), pages 60-79, January.
    5. Yélou, Clément & Larue, Bruno & Tran, Kien C., 2010. "Threshold effects in panel data stochastic frontier models of dairy production in Canada," Economic Modelling, Elsevier, vol. 27(3), pages 641-647, May.
    6. Lu, Zeng-Hua, 2009. "Covariate selection in mixture models with the censored response variable," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2710-2723, May.
    7. Iordanis Parikoglou & Grigorios Emvalomatis & Fiona Thorne, 2022. "Precision livestock agriculture and productive efficiency: The case of milk recording in Ireland," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 109-120, November.
    8. Guangjie Li, 2015. "A stochastic frontier model with structural breaks in efficiency and technology," Empirical Economics, Springer, vol. 49(1), pages 131-159, August.
    9. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    10. Hung-pin Lai, 2013. "Estimation of the threshold stochastic frontier model in the presence of an endogenous sample split variable," Journal of Productivity Analysis, Springer, vol. 40(2), pages 227-237, October.
    11. Xiangfei Xin & Yi Zhang & Jimin Wang & John Alexander Nuetah, 2016. "Effects of Farm Size on Technical Efficiency in China's Broiler Sector: A Stochastic Meta-Frontier Approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 493-516, September.
    12. Efthymios G. Tsionas & Kien C. Tran & Panayotis G. Michaelides, 2019. "Bayesian inference in threshold stochastic frontier models," Empirical Economics, Springer, vol. 56(2), pages 399-422, February.
    13. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
    14. Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.
    15. Drivas, Kyriakos & Economidou, Claire & Tsionas, Efthymios G., 2014. "A Poisson Stochastic Frontier Model with Finite Mixture Structure," MPRA Paper 57485, University Library of Munich, Germany.
    16. Pavlos Almanidis, 2013. "Accounting for heterogeneous technologies in the banking industry: a time-varying stochastic frontier model with threshold effects," Journal of Productivity Analysis, Springer, vol. 39(2), pages 191-205, April.
    17. Fabrice Murtin, 2007. "The Structural Change and the Endogeneity Bias of the College Premium in the United States 1968-2001"," Working Papers 2007-14, Center for Research in Economics and Statistics.
    18. Mike G. Tsionas & Konstantinos N. Baltas, 2022. "On identifying risk-adjusted efficiency gains or losses of prospective mergers and acquisitions," Annals of Operations Research, Springer, vol. 318(1), pages 619-683, November.
    19. Drake, Leigh & Hall, Maximilian J.B. & Simper, Richard, 2009. "Bank modelling methodologies: A comparative non-parametric analysis of efficiency in the Japanese banking sector," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 1-15, February.
    20. Aivazian, Sergei & Afanasiev, Mikhail & Kudrov, Alexander, 2016. "Clustering methodology of the Russian Federation regions with account of sectoral structure of GRP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 41, pages 24-46.

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