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Technologies, Markets and Behaviour: Some Implications for Estimating Efficiency and Productivity Change

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  • O'Donnell, C.J.

Abstract

Most productivity indexes can be exhaustively decomposed into measures of technical change and efficiency change. Estimating these components usually involves the use of data envelopment analysis (DEA) or stochastic frontier analysis (SFA) models. This paper shows how assumptions concerning technologies, markets and firm behaviour can be used to frame these models. The paper explains that the assumptions underpinning common DEA models are rarely, if ever, true. On the other hand, the assumptions underpinning basic SFA models are almost always true. The parameters of basic SFA models can be estimated using ordinary least squares and two-stage least squares methods. More complex SFA models can be estimated using maximum likelihood methods. Unfortunately, the assumptions underpinning some of these more complex models are generally not true. This has important implications for estimating the drivers of productivity change. To illustrate, the paper uses common least squares and maximum likelihood methods to estimate the drivers of productivity change in U.S. agriculture. As expected, the different estimators lead to qualitatively different estimates of the efficiency change components productivity change.

Suggested Citation

  • O'Donnell, C.J., 2014. "Technologies, Markets and Behaviour: Some Implications for Estimating Efficiency and Productivity Change," 2014 Conference (58th), February 4-7, 2014, Port Macquarie, Australia 165867, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare14:165867
    DOI: 10.22004/ag.econ.165867
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    References listed on IDEAS

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    1. C. O’Donnell & K. Nguyen, 2013. "An econometric approach to estimating support prices and measures of productivity change in public hospitals," Journal of Productivity Analysis, Springer, vol. 40(3), pages 323-335, December.
    2. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    3. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    4. Geweke, John, 1986. "Exact Inference in the Inequality Constrained Normal Linear Regression Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 127-141, April.
    5. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521622448, November.
    6. Balk,Bert M., 2012. "Price and Quantity Index Numbers," Cambridge Books, Cambridge University Press, number 9781107404960, November.
    7. 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.
    8. D. W. Jorgenson & Z. Griliches, 1967. "The Explanation of Productivity Change," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 34(3), pages 249-283.
    9. 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.
    10. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
    11. Alois Kneip & Léopold Simar & Paul Wilson, 2011. "A Computationally Efficient, Consistent Bootstrap for Inference with Non-parametric DEA Estimators," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 483-515, November.
    12. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    13. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    14. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    15. 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.
    16. V. Eldon Ball & Charles Hallahan & Richard Nehring, 2004. "Convergence of Productivity: An Analysis of the Catch-up Hypothesis within a Panel of States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1315-1321.
    17. V. Eldon Ball & Jean-Christophe Bureau & Richard Nehring & Agapi Somwaru, 1997. "Agricultural Productivity Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1045-1063.
    18. Nadiri, M Ishaq, 1970. "Some Approaches to the Theory and Measurement of Total Factor Productivity: A Survey," Journal of Economic Literature, American Economic Association, vol. 8(4), pages 1137-1177, December.
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