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Total Factor Productivity Growth, Technical Efficiency Change and Energy Input. An International Frontier Analysis

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Luis R Murillo-Zamorano
Abstract

The main objective of this paper is to clarify the controversial role of energy in productivity growth. This is done by reconciling conventional approaches to the measurement of aggregated productivity growth with the microeconomic foundations provided by the energy economics and frontier productivity measurement literature. The use of Malmquist productivity indices allows us to broaden previous research by decomposing productivity growth into technological progress and technical efficiency change as well as analysing the relationship between energy and both sources of productivity change. By doing so, our findings are that energy indeed matters and that the consideration of technical efficiency contributes to a better understanding of both the temporal evolution and cross-country variability of aggregated productivity growth.

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Paper provided by Department of Economics, University of York in its series Discussion Papers with number 03/09.

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Handle: RePEc:yor:yorken:03/09

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Keywords: Energy input Total factor productivity growth Technical efficiency change Malmquist productivity growth indices.

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Find related papers by JEL classification:
Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General
O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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  1. Balk, Bert M, 1993. "Malmquist Productivity Indexes and Fisher Ideal Indexes: Comment," Economic Journal, Royal Economic Society, vol. 103(418), pages 680-82, May. [Downloadable!] (restricted)
  2. Bernard, Andrew B & Jones, Charles I, 1996. "Technology and Convergence," Economic Journal, Royal Economic Society, vol. 106(437), pages 1037-44, July. [Downloadable!] (restricted)
  3. 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. [Downloadable!] (restricted)
  4. Bernard, Andrew B & Jones, Charles I, 1996. "Comparing Apples to Oranges: Productivity Convergence and Measurement across Industries and Countries," American Economic Review, American Economic Association, vol. 86(5), pages 1216-38, December. [Downloadable!] (restricted)
  5. 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. [Downloadable!] (restricted)
  6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November. [Downloadable!] (restricted)
  7. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200. [Downloadable!] (restricted)
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