Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-03T02:11:38.268Z Has data issue: false hasContentIssue false
  • English
  • Français

Rational Expectations Estimation of Georgia Soybean Acreage Response

Published online by Cambridge University Press:  28 April 2015

Nicolas B. C. Ahouissoussi ,
Christopher S. McIntosh  and
Michael E. Wetzstein
Nicolas B. C. Ahouissoussi
Affiliation:
Department of Agricultural and Applied Economics, University of Georgia
Christopher S. McIntosh
Affiliation:
Department of Agricultural and Applied Economics, University of Georgia
Michael E. Wetzstein
Affiliation:
Department of Agricultural and Applied Economics, University of Georgia
Get access Rights & Permissions [Opens in a new window]

Abstract

The general method of moments procedure is used for estimating a soybean acreage response function assuming that producers hold rational expectations. Results indicate that soybean, corn, and wheat futures prices, lagged acreage, and government programs are significant factors for determining soybean plantings. Implications of the results are that crop acreage selection by Georgia producers is not very responsive to demand shocks. Thus, producers in other regions are more likely to absorb impacts from these shocks on crop acreage selection.

Keywords

soybeansrational expectationsGMMelasticities
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 27 , Issue 2 , December 1995 , pp. 500 - 509
Copyright
Copyright © Southern Agricultural Economics Association 1995

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.)

References

Arnade, C.A. and Davison, C.. “Testing for Aggregation and Simultaneous Bias in U.S. Soybean Export Export Equations.” S. J. Agr. Econ. 21(1989): 129–137.Google Scholar
Bailey, K.W., and Womack, A.W.. “Wheat Acreage Response: A Regional Econometric Investigation.” S.J. Agr. Econ., 17,2(1985): 171-80.Google Scholar
Bessler, D. “Foresight and Inductive Reasoning of Economic Variables with California Field Crop Farmers.” Ph.D. thesis, University of California, Davis, 1977.Google Scholar
Bowden, R.J. and Turkington, D.A.. Instrumental Variables. Economic Society Monograph in Quantitative Economics, Cambridge University Press, 1990.Google Scholar
Chicago Board of Trade. Statistical Annual: Chicago Board of Trade, selected annual series.Google Scholar
Cho, D. G. “Estimation of A Wheat Acreage Response Function For Kansas.” Selected Paper, American Association of Agricultural Economics Annual Meeting Baltimore, Maryland August 1992.Google Scholar
Cumby, R.E., Huzinga, J., and Obstfed, M.. “Two-Step Two-Stage Least Squares Estimation with rational Expectations.” J. Econometrics, 21(1983): 333-55CrossRefGoogle Scholar
Duffy, P.A., Richardson, J. W., and Wohlgenant, M.K.. “Regional Cotton Acreage Response”. S. J. Agr. Econ, 19(1987): 99–109Google Scholar
Fisher, B. S. “Rational Expectations in Agricultural Economics Research and Policy Analysis’. Amer. J. Agr. Econ, 64(1982):260–265.CrossRefGoogle Scholar
Fomby, T.B., Hill, R.C. and Johnson, S.R.. Advanced Econometric Methods. Springer-Verlag, New York, 1984.CrossRefGoogle Scholar
Gardner, L.B. “Futures Prices in Supply Analysis’. Amer. J. Agr. Econ., 58(1976): 81–84.CrossRefGoogle Scholar
Georgia Agricultural Statistics Service. Agricultural Facts. Selected Issues.Google Scholar
Hansen, L.P. “Large Sample Properties of Generalized Method of Moments Estimators.” Econometrica, 50(1982): 1269-86.CrossRefGoogle Scholar
Hansen, L.P., and Sargent, T.J.. “Instrumental Variables Procedures for Estimating Linear Rational Expectations Models.”. Monetary Econ., 9(1982): 263-96CrossRefGoogle Scholar
Hansen, L.P., and Singleton, KJ.. “Instrumental Variables Estimators of Non-linear Rational Expectations Models.” Econometrica, 50(1982): 1269-86.CrossRefGoogle Scholar
Hocking, R.R., and Pendleton, O.J.. “The Regression Dilemma.” Communications in Statistics: Theory and Methods 12(1985):497–527.Google Scholar
Houck, J.P. and Subotnick, A.. “The U.S. Supply of Soybeans: Regional Acreage Functions.” Agricultural Economics Research, Vol. 21, Number 4, Oct. 1969: 99–108.Google Scholar
Lee, D.R., and Helmberger, P.. “Estimating Supply Response in the Presence of Farm Programs.” Amer. J. Agr. Econ., 67(1985): 193–202.CrossRefGoogle Scholar
Marra, M.C. and Carlson, G.. “Double-Cropping Wheat and Soybeans in the Southeast: Input Use and Patterns of Adoption.” Economic Research Service, Agricultural Economic Report, 552(1986):1–18.Google Scholar
McIntosh, C.S. and William, A.. “Multiproduct Production Choices and Pesticide Regulation in Georgia.” S. J. Agr. Econ., 24(1992): 135–141.Google Scholar
Merrill, N. “Biodiesel Alert.” Publication Vol 1, No. 8, July-August 1993.Google Scholar
Morzuch, B.J., Weaver, R.D., and Helmbergher, P.D.. “Wheat Acreage Supply Response Under Changing Farms Programs.” Amer. J. Agr. Econ. 62(1980):29–37.CrossRefGoogle Scholar
Muth, J.F. “Rational Expectations and the Theory of Price Movement.” Econometrica, 29(1961):315-35.CrossRefGoogle Scholar
Nerlove, M. “Estimates of the Elasticities of Supply of Selected Agricultural Commodities.” Amer. J. Agr. Econ., 38(1956):496–509.Google Scholar
Nerlove, M. “Adaptive Expectations and Cobweb Phenomena.” Quart. J. Econ., 72(1958):227-40.CrossRefGoogle Scholar
Penn, J.B. and Irwin, G.D.. “A Simultaneous Equation Approach to Production Response: Delta Region.” S. J. Agr. Econ. 3(1971): 115–121Google Scholar
Pindyck, R.S. and Rubinfeld, D.L.. Econometric Models & Economic Forecasts. McGraw-Hill, Inc, third ed., 1991Google Scholar
Pope, R. D. “Supply Response and the Dispersion of Price Expectations.” Amer. J. Agr. Econ. 63(1981):161–163.Google Scholar
Reed, M.R. and K.S., Riggins “A Disaggregated Analysis of Corn Acreage Response in Kentucky.” Amer. J. Agr. Econ. 63(1981):708–711.Google Scholar
Shapiro, B.I., Brorsen, B.W., and Doster, D.H.. “Adoption of Double-Cropping Soybeans and Wheat.” S. J. Agr. Econ., 24(1992):33–40Google Scholar
Shideed, K. H., Fred C. White. “Alternative Forms of Price Expectations in Supply Analysis for U.S. Corn and Soybean Acreages.” W. J. Agr. Econ, 14(1989):281–292.Google Scholar
Shumway, C. Richard and Chang, A.A “Supply Response of Texas Field Crops: An Evaluation of the CET Linear Supply Model.” W. J. Agr. Econ. 5(1980): 149-64.Google Scholar
Shumway, C. R. “Supply, Demand, And Technology in a Multiproduct Industry: Texas Field Crops.” Amer. J. Agr. Econ. 65(1983):748-60.CrossRefGoogle Scholar
Tomek, W.G. and W.R., Gray “Temporal Relationships Among Prices on Commodity Futures Markets: Their Allocative and Stabilizing Roles.” Amer. J. Agr. Econ. 54(1970):372-80.CrossRefGoogle Scholar
Tegene, A., W.E., Huffman, and A.J., Miranowski “Dynamic Corn Supply Functions: A Model With Explicit Optimization.” Amer. J. Agr. Econ. 70(1988): 103–111.CrossRefGoogle Scholar
Whittaker, J.K. and L.R., Brancroft “Corn Acreage Response-Function Estimation with Pooled Time-Series and Cross-Sectional Data.” Amer. J. Agr. Econ. 61(1979):551-3.CrossRefGoogle Scholar