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Measuring productivity growth under factor non-substitution: An application to US steam-electric power generation utilities

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  • Genius, Margarita
  • Stefanou, Spiro E.
  • Tzouvelekas, Vangelis

Abstract

A theoretical framework is developed for decomposing partial factor productivity and measuring technical inefficiency when the underlying technology is characterized by factor non-substitution. With Farrell’s (1957) radial index of technical inefficiency being inappropriate in this case, Russell non-radial indices are adapted to measure technical inefficiency in a Leontief-type model. A system of factor demand equations with a regime specific technical inefficiency term is proposed and estimated allowing for dependence across inputs using a copula approach. Then the paper presents a complete decomposition of partial factor productivity changes using a dataset of US steam-power electric generation utilities.

Suggested Citation

  • Genius, Margarita & Stefanou, Spiro E. & Tzouvelekas, Vangelis, 2012. "Measuring productivity growth under factor non-substitution: An application to US steam-electric power generation utilities," European Journal of Operational Research, Elsevier, vol. 220(3), pages 844-852.
    • Handle: RePEc:eee:ejores:v:220:y:2012:i:3:p:844-852
    DOI: 10.1016/j.ejor.2012.02.023
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    6. 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.
    7. Seifert, Stefan, 2015. "Productivity Growth and its Sources - A StoNED Metafrontier Analyis of the German Electricity Generating Sector," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112975, Verein für Socialpolitik / German Economic Association.
    8. Stefan Seifert, 2015. "Measuring Productivity When Technologies Are Heterogeneous: A Semi-Parametric Approach for Electricity Generation," Discussion Papers of DIW Berlin 1526, DIW Berlin, German Institute for Economic Research.
    9. Mamatzakis, E. & Tsionas, M., 2018. "Revisiting the returns of public infrastructure in Mexico: A limited information local likelihood estimation," Economic Modelling, Elsevier, vol. 75(C), pages 132-141.
    10. 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.
    11. Tsionas, Mike G. & Polemis, Michael L., 2019. "On the estimation of total factor productivity: A novel Bayesian non-parametric approach," European Journal of Operational Research, Elsevier, vol. 277(3), pages 886-902.

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