Hostname: page-component-77c89778f8-swr86 Total loading time: 0 Render date: 2024-07-16T10:46:46.704Z Has data issue: false hasContentIssue false
  • English
  • Français

Nonrobustness of Dynamic Dual Models of the U.S. Dairy Industry

Published online by Cambridge University Press:  10 May 2017

Wayne H. Howard  and
C. Richard Shumway
Wayne H. Howard
Affiliation:
Department of Agricultural Economics and Business, University of Guelph (and a former research associate, Texas A&M University)
C. Richard Shumway
Affiliation:
Department of Agricultural Economics, Texas A&M University
Get access

Abstract

The robustness of dynamic dual model results across functional forms is examined for the U.S. dairy industry. Modified generalized Leontief (GL) and normalized quadratic (NQ) functional forms are compared by examining their consistency with properties of the competitive firm, estimated rates of adjustment for cows and labor, tests of technological change, and elasticities. Homogeneity and symmetry are maintained in both models. Convexity is not rejected by the GL and is not seriously violated by the NQ. Absence of technological change is rejected by both models, but quality indexes on labor and cows fully embody technological change occurring within labor and cows in the NQ but not in the GL. Policy-relevant elasticities differ greatly between the functional forms. Dynamic dual models are found to be non-robust in important ways to choice of functional form.

Type
Research Article
Information
Northeastern Journal of Agricultural and Resource Economics , Volume 18 , Issue 1 , April 1989 , pp. 18 - 25
Copyright
Copyright © 1989 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Texas A&M Agricultural Experiment Station Technical Article No. 23573.

References

Baffes, J., and Vasavada, U. “A Comparison of Flexible Functional Forms in Production Analysis.” Paper presented at the Southern Agricultural Economics Association meetings, February, 1987.Google Scholar
Ball, V.E. “Output, Input, and Productivity Measurement in U.S. Agriculture, 1948–79.” American Journal of Agricultural Economics 67 (1985): 475–486.Google Scholar
Chambers, R.G. and Lopez, R. “A General Dynamic Supply-Response Model.” Northeastern Journal of Agricultural and Resource Economics 13 (1984): 142–154.Google Scholar
Chalfant, J.A. “Comparison of Alternative Functional Forms with Application to Agricultural Input Data.” American Journal of Agricultural Economics 66 (1984): 216–220.Google Scholar
Chavas, J.P., and Klemme, R.M. “Aggregate Milk Supply Response and Investment Behavior on U.S. Dairy Farms.” American Journal of Agricultural Economics 68 (1986): 55–66.Google Scholar
Epstein, L. “Duality Theory and Functional Forms for Dynamic Factor Demands.” Review of Economic Studies 48 (1981): 81–95.Google Scholar
Epstein, L., and Denny, M. S. “The Multivariate Flexible Accelerator Model: Its Empirical Restrictions and an Application to U.S. Manufacturing.” Econometrica 51 (1983): 647–674.Google Scholar
Gallant, A.R., and Jorgenson, D.W. “Statistical Inference for a System of Simultaneous, Non-linear, Implicit Equations in the Context of Instrumental Variable Estimation.” Journal of Econometrics 11 (1979): 275–302.Google Scholar
Gollop, F., and Jorgenson, D.W. “U.S. Productivity Growth by Industry, 1949–73.” New Developments in Productivity Measurement and Productivity Analysis, eds. Ken-dick, J. and Vaccara, B. National Bureau of Economic Research, Studies in Income and Wealth. Vol. 44, Chicago: University of Chicago Press, 1980.Google Scholar
Hillier, F.S., and Lieberman, G.J. Operations Research. 2nd ed., San Francisco, Holden-Day, Inc., 1974.Google Scholar
Howard, W.H., and Shumway, C.R. “Dynamic Adjustment in the U.S. Dairy Industry.” American Journal of Agricultural Economics 70 (1988): 837–847.Google Scholar
Karp, L.S., Fawson, C. and Shumway, C.R. “Impact of Expectation Formation on Dynamic Investment Decisions: An Application to U.S. Agriculture.” Giannini Working Paper No. 343, University of California Berkeley, March, 1985.Google Scholar
Kvalseth, T. O. “Cautionary Note About R2.” The American Satistician 39 (1985): 279–285.Google Scholar
LaFrance, J.T., and de Gorter, H. “Regulation in a Dynamic Market: The U.S. Dairy Industry.” American Journal of Agricultural Economics 67 (1985): 821–31.Google Scholar
Swamy, G. and Binswanger, H.P. “Flexible Demand Systems and Linear Estimation: Food in India.” American Journal of Agricultural Economics 65 (1983): 675–684.Google Scholar
Taylor, T.G. and Monson, M.J. “Dynamic Factor Demands for Aggregate Southeastern United States Agriculture.” Southern Journal of Agricultural Economics 17 No. 2 (1985): 1–9.Google Scholar
Treadway, A.B. “Adjustment Costs and Variable Inputs in the Theory of the Competitive Firm.” Journal of Economic Theory 2 (1970): 329–347.Google Scholar
Vasavada, U., and Chambers, R. G. “Testing Empirical Restrictions of the Multivariate Flexible Accelerator in a Model of U.S. Agricultural Investment.” Paper presented at the American Agricultural Economics Association meetings, Logan, Utah, August, 1982.Google Scholar
Vasavada, U., and Chambers, R. G. “Investment in U.S. Agriculture.” American Journal of Agricultural Economics 68 (1986): 950–960.Google Scholar