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Valuing State-Level Funding for Research: Results for Florida

Published online by Cambridge University Press:  28 April 2015

Charles B. Moss
Charles B. Moss*
Affiliation:
Department at the University of Florida, Gainesville, FL
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Abstract

This study analyzes the value of agricultural research to Florida by examining the effect of research spending on agricultural productivity, as measured by a total factor productivity index, and profitability, as measured by net farm income. Results suggest that research expenditures do increase agricultural productivity in the state. However, agricultural productivity does not affect net cash income. Further, the economic rents to the productivity gains do not accrue to land values. Instead, the economic value of research innovations accrues more to consumers than to producers. Thus, consumers are the ultimate beneficiaries of agricultural research in Florida, thereby justifying public funding for agricultural research.

Keywords

cointegrationresearch and developmentstate expenditurestotal factor productivityH40H72Q16
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 38 , Issue 1 , April 2006 , pp. 169 - 183
Copyright
Copyright © Southern Agricultural Economics Association 2006

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References

Abramovitz, M. “Catching Up, Forging Ahead, and Falling Behind.” Journal of Economic History 46(1986):385–406.CrossRefGoogle Scholar
Alston, J.M., Norton, G.W., and Pardey, P.G.. Science Under Scarcity: Principles and Practice for Agricultural Research Evaluation and Priority Setting. New York: CAB International, 1998.CrossRefGoogle Scholar
Baker, J.B., and Bresnahan, T.F.. “The Gains from Merger or Collusion in Product-Differentiated Industries.” Journal of Industrial Economics 33,4(1985):427-44.CrossRefGoogle Scholar
Ball, V.E., Butault, J.P., and Nehring, R.F.. “United States Agriculture, 1960-96: A Multilateral Comparison of Total Factor Productivity.” Agricultural Productivity: Measurement and Sources of Growth. Ball, V.E. and Norton, G.W.. eds., pp. 251-76. Boston: Kluwer Academic Publishers, 2002.CrossRefGoogle Scholar
Ball, V.E., Hallahan, C., and Nehring, R.. “Convergence of Productivity: An Analysis of the Catch-Up Hypothesis within a Panel of States.” American Journal of Agricultural Economics 86,5(2004):1315-21.CrossRefGoogle Scholar
Engle, R.F., and Granger, C.W.J. “Cointegration and Error Correction: Representation, Estimation and Testing.” Econometrica 55,2(1987): 251-76.CrossRefGoogle Scholar
Granger, C.W.J., and Newbold, P.. “Spurious Regressions in Econometrics.” Journal of Econometrics 26,2(1974):1045-66.Google Scholar
Griliches, Z. “Measuring Inputs in Agriculture: A Critical Survey.” Journal of Farm Economics 42,5(1960):1411-26.CrossRefGoogle Scholar
Hamilton, J.D.Time Series Analysis. Princeton, NJ: Princeton University Press, 1994.CrossRefGoogle Scholar
Huang, K.S., and Lin, B.H.. “Estimation of Food Demand and Nutrient Elasticity from Household Survey Data.” Washington, DC: U.S. Department of Agriculture, Economic Research Service, Technical Bulletin 1887, 2000.Google Scholar
Huffman, W.E., and Evenson, R.E.. “New Econometric Evidence on Agricultural Total Factor Productivity Determinants: Impact of Funding Sources.” Working Paper 03029, Department of Economics Working Paper Series, Iowa State University, Ames, IA, December 2003.Google Scholar
Huffman, W.E., McCunn, A., and Xu, J.. “Public Agricultural Research Expenditures with an Agricultural Productivity Emphasis: Data for 48 States, 1927-95.” Iowa State University Department of Economics Staff Paper, Ames, IA, 2001.Google Scholar
Johansen, S. “Statistical Analysis of Cointegrating Vectors.” Journal of Economic Dynamics and Control 12,2/3(1988):231-54.CrossRefGoogle Scholar
Just, R.E., Hueth, D.L., and Schmitz, A.. The Welfare Economics of Public Policy. Northampton, MA: Edward Elgar Publishing, 2004.Google Scholar
Krätzig, M. “The Software J Multi.” Applied Time Series Econometrics. Lütkepohl, H. and Krätzig, M., eds. New York: Cambridge University Press, 2004.Google Scholar
Moss, C.B. “The Cost Price Squeeze in Agriculture: An Application of Cointegration.” Review of Agricultural Economics 14,2(1992):209-17.CrossRefGoogle Scholar
Ouliaris, S., and Philips, P.C.B.. COINT 2.0a: Gauss Procedures for Cointegrated Regressions. 1997.Google Scholar
Scheffman, D.T., and Spiller, P.T.. “Geographic Market Definition under the U.S. Department of Justice Merger Guidelines.” Journal of Law and Economics 30,1(1987):123-47.CrossRefGoogle Scholar
U.S. Department of Agriculture—Economic Research Service [USDA/ERS]. Farm Income Data. Internet site: http://www.ers.usda.gov/farmincome/ (Accessed March 17, 2004a).Google Scholar
U.S. Department of Agriculture—Economic Research Service [USDA/ERS]. Farm Balance Sheet Data. Internet site: http://www.ers.usda.gov/data/farmbalancesheet/ (Accessed March 17, 2004b).Google Scholar