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Recent Applications of Nonparametric Programming Methods

Published online by Cambridge University Press:  10 May 2017

Hyunok Lee
Hyunok Lee*
Affiliation:
Office of Energy, U.S. Department of Agriculture, Washington, DC
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Nonparametric techniques have recently come into vogue in agricultural economics: Applications abound in both consumer and producer models of the agricultural economy. Moreover, several distinct approaches to nonparametric analysis exist. There are nonparametric statistical techniques, semiparametric estimation techniques, nonparametric revealed-preference analysis of consumption data, and nonparametric analysis of production data. Both revealed-preference analysis and nonparametric analysis of production data rely on the basic fact, which provides the foundation for much of modern duality theory, that convex sets can be completely characterized by their supporting hyperplanes. This observation allows one to apply simple mathematical programming (in particular, linear programming) methods to analyze production and consumption data. My task today is to provide an overview of nonparametric programming approaches to production data. Thus, I will not address any of the other topics cited above. However, I would be remiss if I did not mention the close connection between these subject areas and what I intend to survey today. Moreover, one should also recognize that very closely related to the literature on nonparametric programming analysis of production data are the fields of estimation of efficiency frontier via statistical methods. (A useful survey here is Lovell and Schmidt).

Type
Invited Presentation
Information
Northeastern Journal of Agricultural and Resource Economics , Volume 21 , Issue 2 , October 1992 , pp. 113 - 120
Copyright
Copyright © 1992 Northeastern Agricultural and Resource Economics Association 

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References

Afriat, S.N. “Efficiency Estimation of Production Functions.” International Economic Review 13 (1972):568–98.Google Scholar
Aigner, D.J., and Chu, S.F. “On Estimating the Industry Production Function.” American Economic Review 58, no. 4(September 1968):826–39.Google Scholar
Chambers, R.G. “Recent Developments in Production Economics.” Paper presented at the Australian Economics Congress, Canberra, August 1988.Google Scholar
Chames, A., Cooper, W.W., and Rhodes, E. “Measuring Efficiency of Decision Making Units.” European Journal of Operational Research 2 (1978):429–44.Google Scholar
Cheung, S.N.S. The Theory of Share Tenancy. Chicago: University of Chicago Press, 1969.Google Scholar
Färe, R., Grosskopf, S., and Lovell, C.A.K. The Measurement of Efficiency of Production. Boston: Kluwer-Nijhoff, 1985.Google Scholar
Färe, R., Grosskopf, S., Lovell, C.A.K., and Pasurka, C. “Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach.” Review of Economics and Statistics 71, no. 1 (1989):90–98.Google Scholar
Färe, R., Grosskopf, S., Lovell, C.A.K., and Yaisawarng, S. “Derivation of Virtual Prices for Undesirable Outputs: A Distance Function Approach.” Review of Economic and Statistics Forthcoming.Google Scholar
Färe, R., Grosskopf, S., and Lee, H. “A Nonparametric Approach to Expenditure-Constrained Profit Maximization.” American Journal of Agricultural Economics 12, no. 3 (August 1990):574–81.Google Scholar
Farrell, M.J. “Measurement of Productive Efficiency.” Journal of the Royal Statistical Society, Series A, General (1957):253–81.Google Scholar
Farrell, M.J., and Fieldhouse, M. “Estimating Efficient Production Functions under Increasing Returns to Scale.” Journal of the Royal Statistical Society Series A-125, no. 2 (1962):252–67.Google Scholar
Ferguson, C.E. The Neoclassical Theory of Production and Distribution. Cambridge: Cambridge University Press, 1971.Google Scholar
Hanoch, H., and Rothschild, M. “Testing the Assumptions of Production Theory: A Nonparametric Approach.” Journal of Political Economy 80 (1972):256–75.Google Scholar
Helpman, E. “Increasing Returns, Imperfect Markets and Trade Theory.” In Handbook of International Economics, edited by Jones, R. and Kenen, P. Amsterdam: North-Holland.Google Scholar
Johnson, D.G. “Resource Allocation Under Share Contracts.” Journal of Political Economy 58, no. 2 (April 1950):111–23.Google Scholar
Lee, H., and Chambers, R. “Expenditure Constraints and Profit Maximization in U.S. Agriculture.” American Journal of Agricultural Economics 68, no. 4 (November 1986):857–65.Google Scholar
Lee, Hyunok, and Somwaru, Agapi. “The Efficiency of Share Tenancy.” In The Measurement of Productive Efficiency: Techniques and Applications, edited by Lovell, K., Schmidt, S., and Fried, H. Oxford University Press. Forthcoming.Google Scholar
Lovell, C.A.K., and Schmidt, P. “A Comparison of Alternative Approaches to the Measurement of Productive Efficiency.” In Applications of Modern Production Theory: Efficiency and Productivity, edited by Dogramaci, A. and Färe, R., 3–32. Boston: Kluwer Academic Publishers, 1988.Google Scholar
Markusen, J.R., and Schweinberger, A.G. “The Positive Theory of Production Externalities Under Perfect Competition.” Journal of International Economics 29(1990).Google Scholar
Schultz, Theodore W. The Economic Organization of Agriculture. New York: McGraw-Hill Book Co., 1953.Google Scholar
Shephard, Ronald W. Indirect Production Functions. Meisenheim Am Glan: Verlag Anton Hain, 1974.Google Scholar
Timmer, C.P. “Using a Probabilistic Frontier Production Function to Measure Technical Efficiency.” Journal of Political Economy 79 (1971):776–94.Google Scholar
Varian, H.R. “The Nonparametric Approach to Production Analysis.” Econometrica 52 (1984):579–97.Google Scholar