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Setting Efficient Incentives for Agricultural Research: Lessons from Principal-Agent Theory

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Author Info
Huffman, Wallace
Just, R.

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Abstract

A conceptual analysis of important issues in the organization and management of academic research is presented. Principal-agent theory is applied to derive optimal compensation schemes for scientists when they differ in ability, risk aversion, cost of effort, and reservation utility, and to show the optimal trade-off between institutional risk and scientists' abilities. Implications for an efficient organization of research are derived, including how scientists' incentives should be structured to elicit optimal research efforts and direction, whether research direction should be centralized or decentralized, and whether the organization of research should be through external competitive grants or program and institutional funding.

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Publisher Info
Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 5040.

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Date of creation: 01 Mar 2002
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Publication status: Published in American Journal of Agricultural Economics, November 2000, Vol. 82, pp. 828-841.
Handle: RePEc:isu:genres:5040

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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
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  1. Dana G. Dalrymple, 2008. "International agricultural research as a global public good: concepts, the CGIAR experience and policy issues," Journal of International Development, John Wiley & Sons, Ltd., vol. 20(3), pages 347-379. [Downloadable!]
  2. Oscar Alfranca, 2005. "Private R&D and Spillovers in European Agriculture," International Advances in Economic Research, Springer, vol. 11(2), pages 201-213, May. [Downloadable!] (restricted)
  3. Ekboir, Javier & Garcia, Jose Antonio Espinosa & Espinoza, Jose De Jesus Arellano & Lopez, Georgel Moctezuma & Naranjo, Alfredo Tapia, 2003. "Analisis del sistema Mexicano de investigacion agropecuaria," Economics Working Papers 7684, CIMMYT: International Maize and Wheat Improvement Center. [Downloadable!]
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