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Impact of Macroeconomic Policies on Agricultural Prices

Published online by Cambridge University Press:  15 September 2016

Titus O. Awokuse
Titus O. Awokuse*
Affiliation:
Department of Food and Resource Economics, University of Delaware
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Abstract

Existing empirical evidence on the impact of macroeconomic variables on agriculture remains mixed and inconclusive. This paper re-examines the dynamic relationship between monetary policy variables and agricultural prices using alternative vector autoregression (VAR) type model specifications. Directed acyclic graph theory is proposed as an alternative modeling approach to supplement existing modeling methods. Similar to results in other studies, this study's findings show that over the time period analyzed (1975–2000), changes to money supply as a monetary policy tool had little or no impact on agricultural prices. The primary macroeconomic policy instrument that affects agricultural prices is the exchange rate, which is shown to be directly linked to interest rate, a source of monetary policy shock.

Keywords

agricultural pricescointegrationdirected acyclic graphsmonetary policyVAR
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 34 , Issue 2 , October 2005 , pp. 226 - 237
Copyright
Copyright © 2005 Northeastern Agricultural and Resource Economics Association 

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References

Awokuse, T.O., and Bessler, D.A. 2003. “Vector Autoregression, Policy Analysis, and Directed Graphs: An Application to the U.S. Economy.” Journal of Applied Economics 6(1): 1–24.Google Scholar
Bernanke, B.S. 1986. “Alternative Explanations of the Money-Income Correlation.” Carnegie-Rochester Conference Series on Public Policy 25: 49–99.Google Scholar
Bessler, D.A. 1984. “Relative Prices and Money: A Vector Autoregression on Brazilian Data.” American Journal of Agricultural Economics 66(1): 25–30.Google Scholar
Bessler, D.A., and Yang, J. 2003. “The Structure of Interdependence in International Stock Markets.” Journal of International Money and Finance 22(2): 261–287.CrossRefGoogle Scholar
Blanchard, O.J., and Quah, D. 1989. “The Dynamic Effects of Aggregate Demand and Supply Disturbances.” American Economic Review 79(4): 655–673.Google Scholar
Bordo, M.D. 1980. “The Effect of Monetary Change on Relative Commodity Prices and the Role of Long-Term Contracts.” Journal of Political Economy 88(6): 1088–1109.Google Scholar
Chambers, R.G., and Just, R.E. 1982. “An Investigation of the Effect of Monetary Factors on Agriculture.” Journal of Monetary Economics 9(2): 235–247.CrossRefGoogle Scholar
Cooley, T.F., and Dwyer, M.D. 1998. “Business Cycle Analysis Without Much Theory: A Look at Structural VARs.” Journal of Econometrics 83(1–2): 57–88.CrossRefGoogle Scholar
Cooley, T.F., and LeRoy, S.F. 1985. “Atheoretical Macroeconomics: A Critique.” Journal of Monetary Economics 16(3): 283–308.Google Scholar
Devadoss, S., Meyers, W.H., and Starleaf, D.R. 1990. “Impacts of U.S. Monetary Policies on the Farm Sector: An Econometric Analysis.” Applied Economics 22(11): 1451–1470.CrossRefGoogle Scholar
Devadoss, S., and William, H.M. 1987. “Relative Prices and Money: Further Evidence for the United States.” American Journal of Agricultural Economics 69(4): 838–842.Google Scholar
Dickey, D.A., and Fuller, W.A. 1979. “Distribution of the Estimators for Autoregression Time Series with a Unit Root.” Journal of the American Statistical Association 74(366): 427–431.Google Scholar
Doan, T. 2004. RATS: User's Guide Version 6.0. Evanston, IL: Estima Press.Google Scholar
Dorfman, J.H., and Lastrapes, W.D. 1996. “The Dynamic Responses of Crop and Livestock Prices to Money-Supply Shocks: A Bayesian Analysis Using Long-Run Identifying Restrictions.” American Journal of Agricultural Economics 78(3): 530–541.CrossRefGoogle Scholar
Granger, C.W.J. 1969. “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods.” Econometrica 37: 424–438.Google Scholar
Hannan, E.J., and Quinn, B.G. 1979. “The Determination of the Order of an Autoregression.” Journal of the Royal Statistical Society Series B41(2): 190–195.Google Scholar
Johansen, S., and Juselius, K. 1990. “Maximum Likelihood and Inference on Cointegration: With Applications to the Demand for Money.” Oxford Bulletin of Economics and Statistics 52(2): 169–210.CrossRefGoogle Scholar
Lapp, J.S. 1990. “Relative Agricultural Prices and Monetary Policy.” American Journal of Agricultural Economics 72(3): 622–630.Google Scholar
Lutkepohl, H., and Reimers, H.E. 1992. “Impulse Response Analysis of Cointegrated Systems.” Journal of Economic Dynamics and Control 16(1): 53–78.Google Scholar
Orden, D., and Fackler, P.L. 1989. “Identifying Monetary Impacts on Agricultural Prices in VAR Models.” American Journal of Agricultural Economics 71(2): 495–502.Google Scholar
Osterwald-Lenum, M. 1992. “A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics: Four Cases.” Oxford Bulletin of Economics and Statistics 54(3): 461–472.CrossRefGoogle Scholar
Pearl, J. 1995. “Causal Diagrams for Empirical Research.” Biometrika 82(4): 669–710.CrossRefGoogle Scholar
Pearl, J. 2000. Causality. Cambridge, MA: Cambridge University Press.Google Scholar
Phillips, P. 1998. “Impulse Response and Forecast Error Variance Asymptotics in Nonstationary VARs.” Journal of Econometrics 83(1–2): 21–56.CrossRefGoogle Scholar
Phillips, P.C.B., and Perron, P. 1988. “Testing for a Unit Root in Time Series Regression.” Biometrika 75(2): 335–346.Google Scholar
Saghaian, S.H., Hasan, M.F., and Reed, M.R. 2002. “Overshooting of Agricultural Prices in Four Asian Economies.” Journal of Agricultural and Applied Economics 34(1): 95–109.CrossRefGoogle Scholar
Saghaian, S.H., Reed, M.R., and Marchant, M.A. 2002. “Monetary Impacts and Overshooting of Agricultural Prices in an Open Economy.” American Journal of Agricultural Economics 84(1): 90–103.Google Scholar
Scheines, R., Spirtes, P., Glymour, C., and Meek, C. 1994. Tetrad II: User's Manual and Software. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
Schuh, G.E. 1974. “The Exchange Rate and U.S. Agriculture.” American Journal of Agricultural Economics 56(1): 1–13.CrossRefGoogle Scholar
Schwarz, G. 1978. “Estimating the Dimension of a Model.” Annals of Statistics 6(2): 461–464.Google Scholar
Sims, C.A. 1980. “Macroeconomics and Reality.” Econometrica 48(1): 1–48.Google Scholar
Sims, C.A. 1986. “Are Forecasting Models Usable for Policy Analysis?” Federal Reserve Bank of Minneapolis Quarterly Review 10(1): 2–16.Google Scholar
Spirtes, P., Glymour, C., and Scheines, R. 2000. Causation, Prediction, and Search, Cambridge, MA: MIT Press.Google Scholar
Swanson, N.R., and Granger, C.W.J. 1997. “Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions.” Journal of the American Statistical Association 92(437): 357–367.CrossRefGoogle Scholar