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Approximation Properties and Estimation of the Translog Production Function with Panel Data

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  • Tzouvelekas, Evaggelos

Abstract

This paper provides a general theoretical and methodological framework for the estimation of the translog production function using panel data. The estimation is carried out using generalised least squares estimator (random-effects model) under different maintained hypotheses for the underlying production technology. Our empirical results indicate that imposing a priori restrictions such as homotheticity, homogeneity or separability on the production structure are not palatable and should rather remain a testable hypothesis within the estimation framework.

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File URL: http://purl.umn.edu/26412
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Bibliographic Info

Article provided by Greek Association of Agricultural Economists in its journal Agricultural Economics Review.

Volume (Year): 01 (2000)
Issue (Month): 1 (January)
Pages:

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Handle: RePEc:ags:aergaa:26412

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Keywords: Research Methods/ Statistical Methods;

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  1. 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.
  2. Shumway, C. Richard & Lim, Hongil, 1993. "Functional Form And U.S. Agricultural Production Elasticities," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(02), December.
  3. Baltagi, Badi H & Griffin, James M, 1988. "A General Index of Technical Change," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 20-41, February.
  4. Heshmati, Almas, 1994. "Estimating random effects production function models with selectivity bias: an application to Swedish crop producers," Agricultural Economics, Blackwell, vol. 11(2-3), pages 171-189, December.
  5. Kumbhakar, Subal C & Hjalmarsson, Lennart, 1995. " Decomposing Technical Change with Panel Data: An Application to the Public Sector," Scandinavian Journal of Economics, Wiley Blackwell, vol. 97(2), pages 309-23, June.
  6. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  7. Wales, Terence J., 1977. "On the flexibility of flexible functional forms : An empirical approach," Journal of Econometrics, Elsevier, vol. 5(2), pages 183-193, March.
  8. Greene, William H., 1980. "On the estimation of a flexible frontier production model," Journal of Econometrics, Elsevier, vol. 13(1), pages 101-115, May.
  9. Almas Heshmati, 1996. "On the single and multiple time trends representation of technical change," Applied Economics Letters, Taylor & Francis Journals, vol. 3(8), pages 495-499.
  10. Ornelas, Fermin S. & Shumway, C. Richard, 1993. "Multidimensional Evaluation Of Flexible Functional Forms For Production Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 25(02), December.
  11. Hatziprokopiou, Michalis & Karagiannis, Giannis & Velentzas, Kostas, 1996. "Production Structure, Technical Change, and Productivity Growth in Albanian Agriculture," Journal of Comparative Economics, Elsevier, vol. 22(3), pages 295-310, June.
  12. Thijssen, Geert, 1992. "A Comparison of Production Technology Using Primal and Dual Approaches: The Case of Dutch Dairy Farms," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 19(1), pages 49-65.
  13. Fuss, Melvyn & McFadden, Daniel & Mundlak, Yair, 1978. "A Survey of Functional Forms in the Economic Analysis of Production," Histoy of Economic Thought Chapters, in: Fuss, Melvyn & McFadden, Daniel (ed.), Production Economics: A Dual Approach to Theory and Applications, volume 1, chapter 4 McMaster University Archive for the History of Economic Thought.
  14. Denny, Michael & Fuss, Melvyn A, 1977. "The Use of Approximation Analysis to Test for Separability and the Existence of Consistent Aggregates," American Economic Review, American Economic Association, vol. 67(3), pages 404-18, June.
  15. Humphrey, David Burras & Moroney, John R, 1975. "Substitution among Capital, Labor, and Natural Resource Products in American Manufacturing," Journal of Political Economy, University of Chicago Press, vol. 83(1), pages 57-82, February.
  16. Kalirajan, K P, 1990. "On Measuring Economic Efficiency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 75-85, January-M.
  17. May, J D & Denny, M, 1979. "Factor-Augmenting Technical Progress and Productivity in U.S. Manufacturing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(3), pages 759-74, October.
  18. Griffin, Ronald C. & Montgomery, John M. & Rister, M. Edward, 1987. "Selecting Functional Form In Production Function Analysis," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 12(02), December.
  19. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
  20. Kim, H Youn, 1992. "The Translog Production Function and Variable Returns to Scale," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 546-52, August.
  21. Greene, William H, 1981. "Sample Selection Bias as a Specification Error: Comment," Econometrica, Econometric Society, vol. 49(3), pages 795-98, May.
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Cited by:
  1. Sauer, J.F., 2005. "“Efficiency Flooding”: Black-Box Frontiers and Policy Implications," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(1), pages 17-52.
  2. Eric Heyer & Florian Pelgrin & Arnaud Sylvain, 2004. "Translog ou Cobb-Douglas? Le rôle des durées d'utilisation des facteurs," Working Papers 04-19, Bank of Canada.
  3. Dewbre, Joshua, 2010. "Improving resource allocation and incomes in Vietnamese agriculture," IFPRI discussion papers 984, International Food Policy Research Institute (IFPRI).

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