Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-26T11:11:33.804Z Has data issue: false hasContentIssue false
  • English
  • Français

Do Farmers Hedge Optimally or by Habit? A Bayesian Partial-Adjustment Model of Farmer Hedging

Published online by Cambridge University Press:  26 January 2015

Jeffrey H. Dorfman  and
Berna Karali
Jeffrey H. Dorfman
Affiliation:
Department of Agricultural and Applied Economics, The University of Georgia, Athens, GA
Berna Karali
Affiliation:
Department of Agricultural and Applied Economics, The University of Georgia, Athens, GA
Get access Rights & Permissions [Opens in a new window]

Abstract

Hedging is one of the most important risk management decisions that farmers make and has a potentially large role in the level of profit eventually earned from farming. Using panel data from a survey of Georgia farmers that recorded their hedging decisions for 4 years on four crops, we examine the role of habit, demographics, farm characteristics, and information sources on the hedging decisions made by 57 different farmers. We find that the role of habit varies widely and that estimation of a single habit effect suffers from aggregation bias. Thus, modeling farmer-level heterogeneity in the examination of habit and hedging is crucial.

Keywords

Bayesian econometricshabit formationhedging decisionsinformation sourcesC11Q12Q14
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 42 , Issue 4 , November 2010 , pp. 791 - 803
Copyright
Copyright © Southern Agricultural Economics Association 2010

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

Blanciforti, L., and Green, R. “An Almost Ideal Demand System Incorporating Habits: An Analysis of Expenditures on Food and Aggregate Commodity Groups.” The Review of Economics and Statistics 65(1983):511–15.Google Scholar
Dorfman, J.H., and Lastrapes, W.D. “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(1996):530–41.Google Scholar
Dorfman, J.H., Pennings, J.M., and Garcia, P. “Is Hedging a Habit? Hedging Ratio Determination of Cotton Producers.” NCR 134 Conference Proceedings, 2005.Google Scholar
Holt, M.T., and Goodwin, B.K. “Generalized Habit Formation in an Inverse Almost Ideal Demand System: An Application to Meat Expenditures in the U.S.” Empirical Economics 22(1997):293–320.Google Scholar
Koop, G. Bayesian Econometrics. Chichester, UK: Wiley, 2003.Google Scholar
Koop, G., and Poirier, D.J. “Bayesian Variants of Some Classical Semiparametric Regression Techniques.” Journal of Econometrics 123(2004): 259–82.CrossRefGoogle Scholar
Koop, G., and Tobias, J.L. “Semiparametric Bayesian Inference in Smooth Coefficient Models.” Journal of Econometrics 134(2006):283–315.Google Scholar
Pannell, D.J., Hailu, G., Weersink, A., and Burt, A. “More Reasons Why Farmers Have So Little Interest in Futures Markets.” Agricultural Economics 39(2008):41–50.Google Scholar
Pennings, J.M.E. and Garcia, P. “Hedging Behavior in Small and Medium-Sized Enterprises: The Role of Unobserved Heterogeneity.” Journal of Banking & Finance 28(2004):951–78.Google Scholar
Pennings, J.M.E. and Leuthold, R.M. “The Role of Farmers' Behavioral Attitudes and Heterogeneity in Futures Contracts Usage.” American Journal of Agricultural Economics 82(2000): 908–19.Google Scholar
Pope, R., Green, R., and Eales, J. “Testing for Homogeneity and Habit Formation in a Flexible Demand Specification of U.S. Meat Consumption.” American Journal of Agricultural Economics 62(1980):778–84.Google Scholar