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On the econometric estimation of the distance function representation of a production technology

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  • COELLI, Tim

Abstract

Recent developments in the econometric estimation of multi-output, multi-input distance functions have provided a promising new solution to the single-output restriction implicit in the standard production function. However, a suspicion that regressor endogeneity may introduce possible simultaneous equations bias has concerned some econometricians. In this paper we show that, under profit maximising behaviour, distance functions face no greater danger from such bias than their production function cousins. Furthermore, we prove that ordinary least squares (OLS) provides consistent estimates of an input distance function under an assumption of cost minimising behaviour. We also prove that OLS provides consistent estimates of an output distance function under an assumption of revenue maximising behaviour. These results are established for the Cobb-Douglas and translog functional forms, which are the two most commonly used functional forms in applied analyses. Our results provide strong support for the direct estimation of distance functions, and indicate that the instrumental variables (IV) methods, proposed by some authors, may not be required in many cases.

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Bibliographic Info

Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2000042.

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Date of creation: 00 Sep 2000
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Handle: RePEc:cor:louvco:2000042

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Related research

Keywords: distance function; endogeneity; simultaneous equations bias.;

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Cited by:
  1. Bolli, Thomas & Somogyi, Frank, 2011. "Do competitively acquired funds induce universities to increase productivity?," Research Policy, Elsevier, vol. 40(1), pages 136-147, February.
  2. Angelo Zago, 2005. "Tecnhnology estimation for quality pricing in supply-chain relationships," Working Papers 27, University of Verona, Department of Economics.
  3. Kumbhakar, Subal C., 2012. "Specification and estimation of primal production models," European Journal of Operational Research, Elsevier, vol. 217(3), pages 509-518.
  4. Hess, Borge & Cullmann, Astrid, 2007. "Efficiency analysis of East and West German electricity distribution companies - Do the "Ossis" really beat the "Wessis"?," Utilities Policy, Elsevier, vol. 15(3), pages 206-214, September.
  5. Kumbhakar, Subal C., 2011. "Estimation of production technology when the objective is to maximize return to the outlay," European Journal of Operational Research, Elsevier, vol. 208(2), pages 170-176, January.
  6. Aiken, Deborah Vaughn & Pasurka, Carl Jr., 2003. "Adjusting the measurement of US manufacturing productivity for air pollution emissions control," Resource and Energy Economics, Elsevier, vol. 25(4), pages 329-351, October.
  7. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
  8. Yuxin Li & Karen Mumford, . "Aspirations, Expectations and Education Outcomes for Children in Britain: Considering Relative Measures of Family Efficiency," Discussion Papers 09/26, Department of Economics, University of York.
  9. Sauer, Johannes & Wossink, Ada, 2010. "The Marginal Cost Of Agri-Environmental Services," 50st Annual Conference, Braunschweig, Germany, September 29-October 1, 2010 93939, German Association of Agricultural Economists (GEWISOLA).

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