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Modeling the Demand for Durable Inputs: Distributed Lags and Causality

Published online by Cambridge University Press:  05 September 2016

H. W. Mui ,
G. L. Bradford  and
M. M. Ali
H. W. Mui
Affiliation:
China State Farm Agribusiness Corporation, Xisi, Beijing
G. L. Bradford
Affiliation:
Agricultural Economics
M. M. Ali
Affiliation:
Economics, University of Kentucky
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Abstract

Vector-autoregressive-moving-average (VARMA) modeling was used to identify distributed lag relationships among farm tractor derived demand variables and to provide a basis for formally testing the hypothesis that the price of new tractor horsepower is exogeneous to its quantity demanded. Similar causality tests were used for a number of other explanatory variables, including the interest rate, price of diesel fuel, and price of used tractors. Results indicate that several lagged variables are significant causal factors and that the dynamic nature of the demand structure cannot be ignored when explaining tractor demand.

Keywords

distributed lagscausalityfarm tractors
Type
Notes
Information
Journal of Agricultural and Applied Economics , Volume 18 , Issue 2 , December 1986 , pp. 273 - 280
Copyright
Copyright © Southern Agricultural Economics Association 1986

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References

Barnett, R.C, Bessler, D. A., and Thompson, R. L.. “The Money Supply and Nominal Agricultural Prices.” Amer. J. Agr. Econ., 65,2(1983):303–307.CrossRefGoogle Scholar
Bessler, D. A..“Aggregated Personalistic Beliefs on Yields of Selected Crops Estimated Using ARIMA Processes.” Amer. J. Agr. Econ., 62,4(1980):666–674.CrossRefGoogle Scholar
Bessler, D. A.. “Relative Prices and Money: A Vector Autoregression on Brazilian Data.” Amer.J. Agr. Econ., 66,1(1984):25–30.CrossRefGoogle Scholar
Bessler, D. A..and Brandt, J. A.. “Causality Tests in Livestock Markets.” Amer. J. Agr. Econ., 64,1(1982):140–144.CrossRefGoogle Scholar
Bessler, D. A. and Schrader, L. F.. “Relationship Between Two Price Quotes for Eggs.” Amer. J. Agr. Econ., 62,4(1980):766–771.CrossRefGoogle Scholar
Board of Governors, Federal Reserve System. Federal Reserve Bulletin, Volumes 59-68, (1973–1982) various issues; Washington, D.C. Google Scholar
Conley, D. M. and Lambert, D. A.. “U. S. Demand for Farm Tractor Horsepower.” Contributed Paper, AAFA Meetings; Clemson, South Carolina; August, 1981.Google Scholar
Farm and Industrial Equipment Institute (FIEI). Unpublished monthly data, 1973-1982; Chicago, Illinois.Google Scholar
Geweke, J. “Measurement of Linear Dependence and Feedback Between Multiple Time Series.”J. Amer. Stat. Assoc., 77(1982):304–314.CrossRefGoogle Scholar
Granger, C. W. J. “Investigating Causal Relations by Econometric Models and Cross-spectral Methods.” Econometrica, 37(1969):424–438.CrossRefGoogle Scholar
Griliches, Z. “The Demand for a Durable Input: Farm Tractors in the United States, 1921-57.” in Harberger, A. (ed.), The Demand for Durable Goods, Chicago: University of Chicago Press, 1960.Google Scholar
Heady, E. O. and Tweeten, L. G.. Resource Demand and Structure of the Agricultural Industry, Ames, Iowa: Iowa State University Press, 1963.CrossRefGoogle Scholar
Hughes, D. W..and Penson, J. B. Jr. “The Demand for Farm Tractors in the United States.” Contributed Paper, AAEA Meetings; San Diego, California; August, 1977.Google Scholar
Intertec Publishing Corporation. Implement and Tractor, January 1973 - December 1982.Google Scholar
Jorgenson, D. W..“Capital Theory and Investment Behavior.” Amer. Econ. Review, 53(1963):247–259.Google Scholar
Kang, H. “Necessary and Sufficient Conditions for Causality Testing in Multivariate ARMA Models.” J. Time Series Anal, 2(1981):95–101.CrossRefGoogle Scholar
Mui, H. W.. The U.S. Demand for New Farm Wheel Tractors: A Mixed Multiple Time Series Analysis-Econometrics Approach, Unpublished Ph.D. dissertation. University of Kentucky; Lexington, Kentucky, 1983.Google Scholar
Pierce, D. A..“Forecasting in Dynamic Models with Stochastic Regressors.” J. of Econometrics, 3(1975):349–374.CrossRefGoogle Scholar
Pierce, D. A..and Haugh, L. D.. “Causality in Temporal Systems: Characterizations and A Survey.” J. of Econometrics, 5(1977):265–293.CrossRefGoogle Scholar
Silvey, S. D.. Statistical Inference, Baltimore: Penguin Books, Inc., 1970.Google Scholar
Sims, C. A..“Macroeconomics and Reality.” Econometrica, 48(1980):1–48.CrossRefGoogle Scholar
Sims, C. A. “Money, Income, and Causality.” Amer. Econ. Review, 62(1972):540–552.Google Scholar
Sims, C. A. “Distributed Lags.” in Intriligator, M. D..and Kendrick, D. A..(eds.) Frontiers of Quantitative Economics, Volume II, Amsterdam: North-Holland, 1974.Google Scholar
Tiao, G. C..and Box, G. E. P. “Modeling Multiple Time Series with Applications.” J. Amer. Stat. Assoc., 76(1981):802–816.Google Scholar
U. S. Bureau of the Census. Current Industrial Reports, Series M359, U.S. Government Printing Office, Washington, D.C., various years.Google Scholar
U. S. Department of Agriculture, Agricultural Prices, Crop Reporting Board, ESS, U.S. Government Printing Office, Washington, D.C., various issues.Google Scholar
Weaver, R. D..“The Causal Linkage of Control Policy and Its Targets: The Case of Wheat.” Amer. J. Agr. Econ., 62,3(1980):512–516.CrossRefGoogle Scholar
Zellner, A. “Causality and Econometrics.” in Brumer, K. and Meltzer, A. H..(eds.), Three Aspects of Policy and Policymaking, Carnegie-Rochester Conference Series on Public Policy, 10(1978):9–54.Google Scholar