Hostname: page-component-8448b6f56d-m8qmq Total loading time: 0 Render date: 2024-04-19T20:55:18.925Z Has data issue: false hasContentIssue false
  • English
  • Français

The Relationship between Oil, Exchange Rates, and Commodity Prices

Published online by Cambridge University Press:  26 January 2015

Ardian Harri ,
Lanier Nalley  and
Darren Hudson
Ardian Harri
Affiliation:
Mississippi State University, Starkville, MS
Lanier Nalley
Affiliation:
University of Arkansas, Fayetteville, AR
Darren Hudson
Affiliation:
Texas Tech University, Lubbock, TX
Get access

Abstract

Exchange rates have long been thought to have an important impact on the export and import of goods and services, and, thus, exchange rates are expected to influence the price of those products that are traded. At the same time, energy impacts commodity production in some very important ways. The use of chemical and petroleum derived inputs has increased in agriculture over time; the prices of these critical inputs, then, would be expected to alter supply, and, therefore, the prices of commodities using these inputs. Also, agricultural commodities have been increasingly used to produce energy, thereby leading to an expectation of a linkage between energy and commodity markets. In this paper, we examine the price relationship through time of the primary agricultural commodities, exchange rates, and oil prices. Using overlapping time periods, we examine the cointegration relationship between prices to determine changes in the strength of the linkage between markets through time. In general, we find that commodity prices are linked to oil for corn, cotton, and soybeans, but not for wheat, and that exchange rates do play a role in the linkage of prices over time.

Keywords

cointegrationcommodity pricescrude oilexchange ratesC32L71Q11Q40
Type
Invited Paper Sessions
Information
Journal of Agricultural and Applied Economics , Volume 41 , Issue 2 , August 2009 , pp. 501 - 510
Copyright
Copyright © Southern Agricultural Economics Association 2009

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

Abbott, P., Hurt, C., and Tyner, W. “What's Driving Food Prices?” Farm Foundation Issue Report July 2008.Google Scholar
Akaike, H. “Markovian Representation of Stochastic Processes and Its Application to the Analysis of Autoregressive Moving Average Processes.” Annals of the Institute of Statistical Mathematics 26(1974:363-87.CrossRefGoogle Scholar
Akaike, H. “Factor Analysis and AIC.” Psychometrika 52(1987:317-32.CrossRefGoogle Scholar
Anderson, J.D., and Coble, K.H. “Impact of Renewable Fuels Standard Ethanol Mandates on the Corn Market.” Agribusiness: An International Journal (Forthcoming).Google Scholar
Bozdogan, H. “Model Selection and Akaike's Information Criterion (AIC): The General Theory and Its Analytical Extensions.” Psychometrika 52(1987:345–70.Google Scholar
Campiche, J., Bryant, H., Richardson, J., and Outlaw, J. “Examining the Evolving Correspondence between Petroleum Prices and Agricultural Commodity Prices.” Paper presented at the American Agricultural Economics Association Annual Meeting, Portland, OR, July 29-August 1, 2007.Google Scholar
Dickey, D.A., and Fuller, W.A. “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association 74(1979): 427–31.Google Scholar
Dickey, D.A., and Fuller, W.A. “Likelihood Ratio Statistics for Autoregressive Processes.” Econometrica 49(1981): 1057–72.CrossRefGoogle Scholar
Engle, R.F., and Granger, C.W.J. “Cointegration and Error Correction: Representation, Estimation and Testing.” Econometrica 55(1987):251–76.Google Scholar
Federal Reserve Economic Data. Internet site: http://research.stlouisfed.org/fred2/categories/95/downloaddata (Accessed October 2008).Google Scholar
Johansen, S. “A Representation of Vector Auto-regressive Processes Integrated of Order 2.” Econometric Theory 8(1992): 188–202.Google Scholar
Johansen, S., Likelihood-based Inference in Cointegrated Vector Autoregressive Models. Oxford: Oxford University Press, 1995:11–20.Google Scholar
Johansen, S., and Juselius, K. “Maximum Likelihood Estimation and Inference on Cointegration—With Application to the Demand for Money.” Oxford Bulletin of Economics and Statistics 52(1990): 169–210.Google Scholar
Johansen, S., and Juselius, K. “Testing Structural Hypotheses in a Multivariate Cointegration Analysis of the PPP and the UIP for UK. Journal of Econometrics 53(1992):211-44.CrossRefGoogle Scholar
Hanson, K., Robinson, S., and Schluter, G. “Sectoral Effects of a World Oil Price Shock: Economywide Linkages to the Agricultural Sector.” Journal of Agricultural and Resource Economics. 18,1(1993:96–116.Google Scholar
Reed, A., Hanson, K., Elitzak, H., and Schluter, G. “Changing Consumer Food Prices: A User's Guide to ERS Analysis.” Economic Research Service, Food and Consumer Economics Division. U.S. Department of Agriculture. Technical Bulletin No. 1862, 1997.Google Scholar
Schnept, R. “High Agricultural Commodity Prices: What Are the Issues?” Congressional Research Service May 2008.Google Scholar
Schwarz, G. “Estimating the Dimension of a Model.” Annals of Statistics 6(1978:461-64.CrossRefGoogle Scholar
Trostle, R. “Global Agricultural Supply and Demand: Factors Contributing to the Recent Increase in Food Commodity Prices.” Economic Research Service. United States Department of Agriculture, 2008.Google Scholar
Urbanchuk, J.M “The Relative Impact of Corn and Energy Prices in the Grocery Aisle.” LECG, LLC, 2007.Google Scholar
Yu, Tun-Hsiang, Bessler, D.A., and Fuller, S. “Cointegration and Causality Analysis of World Vegetable Oil and Crude Oil Prices.” Paper presented at the American Agricultural Economics Association Annual Meeting, Long Beach, CA, July 23-26, 2006.Google Scholar
Zhang, Q., and Reed, M. “Examining the Impact of the World Crude Oil Price on China's Agricultural Commodity Prices: The Case of Com, Soybean, and Pork.” Paper presented at the South Agricultural Economics Association Annual Meeting, Dallas, TX, February 2-5, 2008.Google Scholar