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Effect of Debt Position on the Choice of Marketing Strategies for Florida Orange Growers: A Risk Efficiency Approach

Published online by Cambridge University Press:  05 September 2016

Charles B. Moss ,
Stephen A. Ford  and
Mario Castejon
Charles B. Moss
Affiliation:
Department of Food and Resource Economics at theUniversity of Florida
Stephen A. Ford
Affiliation:
Agricultural Economics at Pennsylvania State University
Mario Castejon
Affiliation:
Department of Food and Resource Economics at theUniversity of Florida
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Abstract

This study examined the relationship between debt position and choice of marketing instrument. Specifically, this study employed first and second degree stochastic dominance, and stochastic dominance with respect to a function to determine whether the efficient marketing instrument changes between debt positions. The results indicate that the choice of marketing instrument does vary with debt position in some marketing periods if the decisionmaker is moderately risk averse.

Keywords

debt positionmarketing instrumentsstochastic dominance
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 23 , Issue 2 , December 1991 , pp. 103 - 112
Copyright
Copyright © Southern Agricultural Economics Association 1991

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References

Anderson, J. R., Dillon, J. L., and Hardaker, . Agricultural Decision Analysis. Ames: Iowa State University Press, 1977.Google Scholar
Boggess, W. G. and Ritchie, J. T.. “Economic and Risk Analysis of Irrigation Decisions in Humid Regions.” J. Production Agr., 1(1988): 116–122.Google Scholar
Collins, R. A. “Expected Utility, Debt-Equity Structure, and Risk Balancing.” Am. J. Agr. Econ., 67(1985):627–629.Google Scholar
Fishburn, P. C. “Expected Utility: An Anniversary and a New Era.” J. Risk and Uncertainty, 1(1988): 267–283.Google Scholar
Florida Agricultural Statistics. Citrus Summary 1987-88. Orlando, Florida, 1988.Google Scholar
Florida Citrus Processors Association. Statistical Summary 1986-87 Season. Winter Haven, Florida, 1988.Google Scholar
Florida Department of Citrus. Unpublished data on Frozen Concentrate Orange Juice Prices. Gainesville, Florida.Google Scholar
Gabriel, S. C. and Baker, C. B.. “Concepts of Business and Financial Risk.” Am. J. Agr. Econ., 62(1980): 560–564.Google Scholar
Kaylen, M. S., Preckel, P. V., and Loehman, E. T.. “Risk Modeling Via Direct Utility Maximization Using Numerical Quadrature.” Am. J. Agr. Econ. 69(1987): 701–706.Google Scholar
King, R.P. and Robison, L.J. “Risk Efficiency Models.” Risk Management in Agriculture. Barry, P.J., ed., pp. 68–81. Ames: Iowa State University Press, 1984.Google Scholar
Lintner, J. “The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets.” Rev. Econ. and Stat, 47(1965): 13–37.Google Scholar
Meyer, J. “Second Degree Stochastic Dominance with Respect to a Function.” Int. Econ. Rev., 18(1977): 477–486.Google Scholar
Meyer, J. “Two-Moment Decision Models and Expected Utility Maximization.” Am. Econ. Rev., 77(1987): 253–263.Google Scholar
Moss, C. B. and van Blokland., P. J. “Debt Choice and Marketing Instruments: The Case of Frozen Concentrated Orange Juice.” Department of Food and Resource Economics, University of Florida, Staff Paper 402, January 1990.Google Scholar
Moss, C.B., Ramirez, O.A., and Boggess, W.G.. “Modeling Nonnormality in Multivariate Distributions Using an Inverse Hyperbolic Sine Transformation to Normality.” Department of Food and Resource Economics, Staff Paper 91-16, University of Florida, March 1991.Google Scholar
Mossin, J. “Equilibrium in a Capital Asset Market.” Econometrica, 34(1966): 768–783.Google Scholar
Muraro, R.P., Hurner, G.T. and Oswald, T.W.. “Budgeting Costs and Returns: Central Florida Citrus Production 1988-89.” Food and Resource Economics Department, Economic Information Report No. 248, University of Florida, 1989.Google Scholar
Raskin, R. and Cochran, M. J.. “Interpretations and Transformation of Scale for the Pratt-Arrow Absolute Risk Aversion Coefficient: Implications for Generalized Stochastic Dominance.” West. J. Agr. Econ., 11(1986a): 204–210.Google Scholar
Raskin, R. and Cochran, M. J.. “A User's Guide to the Generalized Stochastic Dominance Program for the IBM PC.” University of Arkansas, Staff Paper 3786, (1986b).Google Scholar
Rausser, G. C, Chalfant, J. A., Love, H. A., and Stamoulis, K. G.. “Macroeconomic Linkages, Taxes, and Subsidies in the U. S. Agricultural Sector.” Am. J. Agr. Econ., 68(1986): 339–412.Google Scholar
Schuh, G. E. “The New Macroeconomics of Agriculture.” Am. J. Agr. Econ., 57(1976): 384–389.Google Scholar
Sharpe, W. F. “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk.” J. Finance, 19(1964): 425–442.Google Scholar
Tobin, J. “Liquidity Preferences as Behavior Towards Risk.” Rev. Econ. Studies, 15(1958): 65–85.Google Scholar
Tomek, W. G. and Robinson, K.. Agricultural Product Prices. Ithaca, New York: Cornell University Press, 1981.Google Scholar
Turvey, C. G. and Baker, T. G.. “Optimal Hedging Under Alternative Capital Structures and Risk Aversion.” Can. J. Agr. Econ., 37(1989): 135–143.Google Scholar
Tweeten, L. “Impact of Federal Fiscal-Monetary Policy on Farm Structure.” So. J. Agr. Econ., 15(1983): 61–71.Google Scholar
U.S. Department of Commerce. Business Statistics. Washington, D. C: various issues 1972 to 1986.Google Scholar