Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-26T15:14:33.489Z Has data issue: false hasContentIssue false
  • English
  • Français

Do Fine Wines Blend with Crude Oil? Seizing the Transmission of Mean and Volatility Between Two Commodity Prices*

Published online by Cambridge University Press:  28 June 2013

Elie I. Bouri
Elie I. Bouri*
Affiliation:
Faculty of Business Administration, Holy Spirit University of Kaslik, Lebanon. P.O. Box: 446 Jounieh, Lebanon. email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

This study applies a multivariate model to examine the dynamics of mean and volatility transmission between fine wine and crude oil prices using daily observations from January 2004 to December 2011. The results suggest that the crude oil mean determines the wine market. In each series, volatility persistence is high and significant; innovations in each market seem to include figures that are valuable to risk managers seeking to predict volatility in other markets. During the financial crisis of 2008, wine and oil conditional volatilities climbed but then returned to their overall pre-crisis levels. (JEL Classifications: G11, G15, Q14, Q40)

Keywords

Conditional correlationconditional volatilitycrude oilfine wines
Type
Research Article
Information
Journal of Wine Economics , Volume 8 , Issue 1 , May 2013 , pp. 49 - 68
Copyright
Copyright © American Association of Wine Economists 2013 

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

*

I thank the editor (Karl Storchmann) and an anonymous referee for their useful comments and suggestions.

References

Abbott, P. C., Hurt, C., and Tyner, W. E. (2008). What's driving food prices? Farm Foundation Issue Report, July.Google Scholar
Abbott, P. C., Hurt, C., and Tyner, W. E. (2009). What's driving food prices? March 2009 update. Farm Foundation Issue Report, March.Google Scholar
Baffes, J. (2007). Oil spills on other commodities. Resources Policy, 32(3), 126–134.Google Scholar
Baffes, J., and Haniotis, T. (2010). Placing the 2006/08 commodity price boom into perspective. World Bank Policy Research Paper 5371.Google Scholar
Bailey, M., Muth, R., and Nourse, H. (1963). A regression method for real estate price index construction. Journal of the American Statistical Association, 58, 933–942.CrossRefGoogle Scholar
Bala, L., and Premaratne, G. (2004). Volatility Spillover and Co-movement: Some New Evidence from Singapore. Paper presented at the Midwest Econometrics Group (MEG) Fall Meetings, Northwestern University, Evanston.Google Scholar
Berndt, E. K., Hall, B. H., Hall, R. E., and Hausman, J. A. (1974). Estimation and inference in nonlinear structural models. Annals of Economic and Social Measurement, 3(4), 653–665.Google Scholar
Black, F. (1976). Studies of stock market volatility changes. Proceedings of the 1976 Meetings of the American Statistical Association, Business and Economics Statistics Section, 177–181.Google Scholar
Burton, B., and Jacobsen, J. (2001). The rate of return on investment in wine. Economic Inquiry, 39, 337–350.Google Scholar
Case, K., and Shiller, R. (1987). Prices of single-family homes since 1970: New indexes for four cities. New England Economic Review, 87, 45–56.Google Scholar
Cevik, S., and Sedik, T. S. (2011). A barrel of oil or a bottle of wine: How do global growth dynamics affect commodity prices? IMF Working Paper 11/1, International Monetary Fund.CrossRefGoogle Scholar
Chang, T. H., and Su, H. M. (2010). The substitutive effect of bio-fuels on fossil fuels in the lower and higher crude oil price periods. Energy, 35, 2807–2813.Google Scholar
Chen, S. T., Kuo, H. I., and Chen, C. C. (2010). Modeling the relationship between the oil price and the global food prices. Applied Energy, 87, 2517–2525.Google Scholar
Dickey, D. A., and Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431.Google Scholar
Du, X., Yu, C. L., and Hayes, D. J. (2010). Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis. Energy Economics, 33(3), 497–503.CrossRefGoogle Scholar
Engle, R. F., and Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122–150.CrossRefGoogle Scholar
Esmaeili, A., and Shokoohi, Z. (2011). Assessing the effect of oil price on world food prices: Application of principal component analysis. Energy Policy, 39, 1022–1025.Google Scholar
Fogarty, J. (2010). Wine investment and portfolio diversification gains. Journal of Wine Economics, 5(1), 119–131.CrossRefGoogle Scholar
Forbes, K. J., and Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market comovements. Journal of Finance, 57, 2223–2261.Google Scholar
Gilbert, C. L. (2010). How to understand high food prices. Journal of Agricultural Economics, 61, 398–425.Google Scholar
Goetzmann, W. (1992). The accuracy of real estate indices: Repeat sales estimators. Journal of Real Estate Finance and Economics, 5, 5–53.CrossRefGoogle Scholar
Granger, C.W.J. (1969). Investigating causal relation by econometric and cross-sectional method. Econometrica, 37, 424–438.CrossRefGoogle Scholar
Hanson, K., Robinson, S., and Schluter, G. (1993). Sectoral effects of a world oil price shock: Economy wide linkages to the agricultural sector. Journal of Agricultural and Resource Economics, 18, 96–116.Google Scholar
Headey, D., and Fan, S. (2008). Anatomy of a crisis: The causes and consequences of surging food prices. Agricultural Economics, 39, 375–391.CrossRefGoogle Scholar
Janakiramanan, S., and Lamba, A. S. (1998). An empirical examination of linkages between Pacific basin stock markets. Journal of International Financial Markets, Institutions and Money, 8, 155–173.CrossRefGoogle Scholar
Jarque, C., and Bera, A. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259.Google Scholar
Johansen, S. (1995). Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Ljung, G., and Box, G. (1979). On a measure of lack of fit in time series models. Biometrika, 66, 265–270.CrossRefGoogle Scholar
McMillin, W. D., and Fackler, J. S. (1984). Monetary vs. credit aggregates: An evaluation of monetary policy targets. Southern Economic Journal, 50, 711–723.Google Scholar
Masset, P., and Henderson, C. (2010). Wine as an alternative asset class. Journal of Wine Economics, 5(1), 87–118.CrossRefGoogle Scholar
Masset, P., and Weisskopf, J.-P. (2010). Raise your glass: Wine investment and the financial crisis. American Association of Wine Economists, AAWE Working Paper 57.Google Scholar
Mitchell, D. (2008). A note on rising food prices. World Bank, Policy Research Working Paper Series No. 4682.Google Scholar
Nazlioglu, S., and Soytas, U. (2011). World oil prices and agricultural commodity prices: Evidence from an emerging market. Energy Economics, 33, 488–496.CrossRefGoogle Scholar
Phillips, P. C. B., and Perron, P. (1988). Testing for a unit root in time series regression, Biometrika, 75, 335–346.CrossRefGoogle Scholar
Radetzki, M. (2006). The anatomy of three commodity booms. Resources Policy, 31, 56–64.Google Scholar
Robles, M., Torero, M., and von Braun, J. (2009). When speculation matters. International Food Policy Research Institute, Issue Brief 57.Google Scholar
Rosegrant, M. W., Zhu, T., Msangi, S., and Sulser, T. (2008). Global scenarios for biofuels: Impacts and implications. Review of Agricultural Economics, 30, 495–505.CrossRefGoogle Scholar
Stock, J. H., and Watson, M.W. (2001). Vector autoregressions. Journal of Economic Perspectives, 15(4), 101–115.Google Scholar
Storchmann, K. (2012). Wine economics. Journal of Wine Economics, 7(1), 1–33.CrossRefGoogle Scholar
Tai, C.-S. (2007). Market integration and contagion: Evidence from Asian emerging stock and foreign exchange markets. Emerging Markets Review, 8, 264–283.Google Scholar
Yu, T. E., Bessler, D. A., and Fuller, S. (2006). Cointegration and causality analysis of world vegetable oil and crude oil prices. Paper presented at the American Agricultural Economics Association Annual Meeting, Long Beach, California, July 23–26.Google Scholar
Zhang, Q., and Reed, M. (2008). Examining the impact of the world crude oil prices on China's agricultural commodity prices: The case of corn, soybean and pork. Paper presented at the Southern Agricultural Economics Association Annual Meetings, Dallas, TX, February 2–5.Google Scholar
Zhang, Z., Lohr, L., Escalante, C., and Wetzstein, M. (2010). Food versus fuel: what do prices tell us?. Energy Policy, 38, 445–451.CrossRefGoogle Scholar