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A dynamic stochastic frontier production model with time-varying efficiency

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  • Evangelia Desli
  • Subhash Ray
  • Subal Kumbhakar

Abstract

In this paper technical efficiency is introduced via the intercept that evolve over time as a AR(1) process in a stochastic frontier (SF) framework in a panel data framework. Following are the distinguishing features of the model. First, the model is dynamic in nature. Second, it can separate technical inefficiency from fixed firm-specific effects which are not part of inefficiency. Third, the model allows estimation of technical change separate from change in technical efficiency. It is proposed that the ML method be used estimate the parameters of the model. Finally, expressions are derived to calculate/predict technical inefficiency (efficiency).

Suggested Citation

  • Evangelia Desli & Subhash Ray & Subal Kumbhakar, 2003. "A dynamic stochastic frontier production model with time-varying efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 623-626.
    • Handle: RePEc:taf:apeclt:v:10:y:2003:i:10:p:623-626
    DOI: 10.1080/1350485032000133291
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    2. Sauer, Johannes & Graversen, Jesper T. & Park, Timothy A., 2006. "Breathtaking or Stagnating? - Productivity, Technical Change and Structural Dynamics in Danish Organic Farming," 2006 Annual meeting, July 23-26, Long Beach, CA 21481, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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    5. Mundula, Luigi & Auci, Sabrina, 2013. "Smart Cities and a Stochastic Frontier Analysis: A Comparison among European Cities," MPRA Paper 51586, University Library of Munich, Germany.
    6. Shaik, Saleem & Allen, Albert J. & Myles, Albert E. & Yeboah, Osei-Agyeman, 2008. "Importance of Financial Variables on Efficiency of Class I Railroads in the United States," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6874, Southern Agricultural Economics Association.
    7. Kutlu, Levent, 2017. "A constrained state space approach for estimating firm efficiency," Economics Letters, Elsevier, vol. 152(C), pages 54-56.
    8. Auci, Sabrina & Castelli, Annalisa, 2011. "Pollution and economic growth: a maximum likelihood estimation of environmental Kuznets curve," MPRA Paper 53441, University Library of Munich, Germany.
    9. Assaf, A. George & Tsionas, Mike G., 2019. "A review of research into performance modeling in tourism research - Launching the Annals of Tourism Research curated collection on performance modeling in tourism research," Annals of Tourism Research, Elsevier, vol. 76(C), pages 266-277.
    10. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2013. "Does cutting back the public sector improve efficiency? Some evidence from 15 European countries," CEIS Research Paper 274, Tor Vergata University, CEIS, revised 30 Apr 2013.
    11. 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.
    12. A. Peyrache & A. N. Rambaldi, 2017. "Incorporating temporal and country heterogeneity in growth accounting—an application to EU-KLEMS," Journal of Productivity Analysis, Springer, vol. 47(2), pages 143-166, April.
    13. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    14. Weaver, Robert D. & Curtiss, Jarmila & Brümmer, Bernhard, 2005. "Technical Efficiency Effects of Technological Change: Another Perspective on GM Crops," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24528, European Association of Agricultural Economists.
    15. 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.
    16. A. Peyrache & A. N. Rambaldi, 2012. "A State-Space Stochastic Frontier Panel Data Model," CEPA Working Papers Series WP012012, School of Economics, University of Queensland, Australia.
    17. Merihun Fikru Meja & Bamlaku Alamirew Alemu & Maru Shete, 2021. "Total Factor Productivity of Major Crops in Southern Ethiopia: A Dis-Aggregated Analysis of the Growth Components," Sustainability, MDPI, vol. 13(6), pages 1-14, March.

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    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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