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Testing Multiple Non-nested Factor Demand Systems

  • Matteo Manera
  • Michael McAleer

Empirical factor demand analysis typically involves making a choice from among several competing non-nested functional forms. Each of the commonly used factor demand systems, such as Translog, Generalized Leontief, Quadratic, and Generalized McFadden, can provide a valid and useful empirical description of the underlying production structure of the firm. As there is no theoretical guidance on selecting the model which is best able to capture the relevant features of the data, formal testing procedures can provide additional information. Paired and joint univariate nonnested tests of a null model against both single and multiple alternatives have been discussed at length in the literature, whereas virtually no attention has been paid to either paired or joint multivariate non-nested tests. This paper shows how some multivariate non-nested tests can be derived from their univariate counterparts, and examines how to use these tests empirically to compare alternative factor demand systems. The empirical application involves the classical Berndt- Khaled annual data set for the U.S. manufacturing sector over the period 1947-1971. A statistically adequate empirical specification is determined for each competing factor demand system. The empirical results are interpreted for each system, and the models are compared on the basis of multivariate paired and joint non-nested procedures.

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Paper provided by Institute of Social and Economic Research, Osaka University in its series ISER Discussion Paper with number 0543.

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Date of creation: Jun 2001
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Handle: RePEc:dpr:wpaper:0543
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  1. Barten, A.P. & Mcaleer, M., 1991. "Comparing The Empirical Perfomance Of Alternative Demand Systems," Papers 9002a, Tilburg - Center for Economic Research.
  2. Russell Davidson & James G. MacKinnon, 1980. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Working Papers 378, Queen's University, Department of Economics.
  3. MacKinnon, James G. & White, Halbert & Davidson, Russell, 1983. "Tests for model specification in the presence of alternative hypotheses : Some further results," Journal of Econometrics, Elsevier, vol. 21(1), pages 53-70, January.
  4. Michael McAleer, 1981. "Exact Tests of a Model Against Non-Nested Alternatives," Working Papers 431, Queen's University, Department of Economics.
  5. Edward R. Morey, 1986. "An Introduction to Checking, Testing, and Imposing Curvature Properties: The True Function and the Estimated Function," Canadian Journal of Economics, Canadian Economics Association, vol. 19(2), pages 207-35, May.
  6. W. Erwin Diewert & T.J. Wales, 1989. "Flexible Functional Forms and Global Curvature Conditions," NBER Technical Working Papers 0040, National Bureau of Economic Research, Inc.
  7. Berndt, Ernst R & Wood, David O, 1975. "Technology, Prices, and the Derived Demand for Energy," The Review of Economics and Statistics, MIT Press, vol. 57(3), pages 259-68, August.
  8. Berndt, Ernst R & Khaled, Mohammed S, 1979. "Parametric Productivity Measurement and Choice among Flexible Functional Forms," Journal of Political Economy, University of Chicago Press, vol. 87(6), pages 1220-45, December.
  9. Berndt, Ernst R. & Christensen, Laurits R., 1973. "The translog function and the substitution of equipment, structures, and labor in U.S. manufacturing 1929-68," Journal of Econometrics, Elsevier, vol. 1(1), pages 81-113, March.
  10. McFadden, Daniel, 1978. "The General Linear Profit Function," Histoy of Economic Thought Chapters, in: Fuss, Melvyn & McFadden, Daniel (ed.), Production Economics: A Dual Approach to Theory and Applications, volume 1, chapter 5 McMaster University Archive for the History of Economic Thought.
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