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Estimating the Supply Elasticity of California Wine Grapes Using Regional Systems of Equations*

Published online by Cambridge University Press:  08 June 2012

Richard Volpe ,
Richard Green ,
Dale Heien  and
Richard Howitt
Richard Volpe
Affiliation:
USDA-Economic Research Service, 1800 M St. NW, Washington, DC 20036, e-mail:rvolpe@ers.usda.gov
Richard Green
Affiliation:
Department of Agricultural and Resource Economics, University of California, Davis. One Shields Ave., Davis, CA 95616, e-mail:green@primal.ucdavis.edu.
Dale Heien
Affiliation:
Department of Agricultural and Resource Economics, University of California, Davis. One Shields Ave., Davis, CA 95616, deceased.
Richard Howitt
Affiliation:
Department of Agricultural and Resource Economics, University of California, Davis. One Shields Ave., Davis, CA 95616, email: howitt@primal.ucdavis.edu.
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Abstract

This article is the first of its kind to estimate econometrically the supply elasticity of California wine grapes. Wine grapes constitute the single largest crop in the state of California in terms of total receipts. Allowing for the dynamic adjustments of quasi-fixed inputs, we estimate simultaneous systems of equations for California's four major wine grape growing regions and eight of the most widely grown varieties. We find that California wine grape production is, on the whole, inelastic with respect to prices received. The variety showing the most price responsiveness is Chardonnay. There appears to be no significant difference in price responsiveness between the coastal and inland growing regions, or between red and white grape varieties. (JEL Classification: Qll, Q13, R14)

Type
Articles
Information
Journal of Wine Economics , Volume 5 , Issue 2 , Spring 2010 , pp. 219 - 235
Copyright
Copyright © American Association of Wine Economists 2010

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References

Arnade, C. and Kelch, D. (2007). Estimation of area elasticities from a standard profit function. American Journal of Agricultural Economics, 89(3), 727–737.CrossRefGoogle Scholar
Bettiga, L.J., Golino, D.A., McGourty, G., Smith, R.J., Verdegaal, P.S. and Weber, E. (2003). Wine Grape Varieties in California. University of California, Davis.Google Scholar
Buccola, S.T. and Vander Zanden, L. (1997). Wine demand, price strategy, and tax policy. Review of Agricultural Economics, 19(2), 428–440.CrossRefGoogle Scholar
California Department of Food and Agriculture (1977a–2007a). Final Grape Crush Report. Sacramento.Google Scholar
California Department of Food and Agriculture (1977b–2007b). California Grape Acreage. Sacramento.Google Scholar
Choi, J. and Helmberger, P.G. (1993). Acreage response, expected price functions, and endogenous price expectations. Journal of Agricultural and Resource Economics, 18(1), 37–46.Google Scholar
Goodhue, R., Green, R., Martin, P. and Heien, D. (2008). California wine industry evolving to compete in the 21st century. California Agriculture, 62(1), 12–18.CrossRefGoogle Scholar
Heien, D. (2006). Price formation in the California winegrape economy. Journal of Wine Economics, 1(2), 162–172.Google Scholar
Howard, W.H. and Shumway, C.R. (1988). Dynamic adjustment in the U.S. dairy industry. American Journal of Agricultural Economics, 70(4), 837–847.CrossRefGoogle Scholar
Lave, L.B. (1963). The value of better weather information to the raisin industry. Econometrica, 31(5), 151–164.CrossRefGoogle Scholar
Li, H. and Maddala, G.S. (1999). Bootstrap variance estimation of nonlinear functions of parameters: an application to long-run elasticities of energy demand. The Review of Economics and Statistics, 81(4), 728–733.Google Scholar
Lobell, D.B., Cahill, K. and Field, C. (2006). Weather-based yield forecasts developed for 12 California crops. California Agriculture, 60(4), 211–215.CrossRefGoogle Scholar
Ruud, P.A. (2000). An Introduction to Classical Econometric Theory. New York City: Oxford University Press.Google Scholar
Sumner, D.A , Bombrun, H., Alston, J.M. and Heien, D. (2001). An Economic Survey of the Wine and Winegrape Industry in the United States and Canada. University of California, Davis. http://aic.ucdavis.edu/research1/Winegrape.pdfGoogle Scholar
Wine Institute (2007). Industry Background & Statistics, www.wineinstitute.org/communications/statistics/#econ_industryGoogle Scholar
Wohlgenant, M.K. (1982). Inventory adjustment and dynamic winery behavior. American Journal of Agricultural Economics, 64(2), 222–231.Google Scholar
Wooldridge, J.M. (2006). Introductory Econometrics: A Modern Approach. Mason, OH: Southwestern Cengage Learning.Google Scholar