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Empirical Calibration of a Least-Cost Conservation Reserve Program

  • Sheriff, Glenn

Mechanism design models typically conclude by characterizing an optimal allocation schedule based on the principal's beliefs regarding agent value functions and the distribution of agent types. This article addresses the question of how a principal can develop these beliefs given a standard cross-sectional data set in which agents' input-output choices are observable, but their underlying heterogeneity is not. I employ the methodology to evaluate strategies for reducing the cost of a voluntary program that reduces cultivation on environmentally-sensitive farmland.

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File URL: http://purl.umn.edu/21420
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Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2006 Annual meeting, July 23-26, Long Beach, CA with number 21420.

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Date of creation: 2006
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Handle: RePEc:ags:aaea06:21420
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  1. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
  2. Christopher R. Knittel, 2002. "Alternative Regulatory Methods And Firm Efficiency: Stochastic Frontier Evidence From The U.S. Electricity Industry," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 530-540, August.
  3. Guesnerie, Roger & Laffont, Jean-Jacques, 1984. "A complete solution to a class of principal-agent problems with an application to the control of a self-managed firm," Journal of Public Economics, Elsevier, vol. 25(3), pages 329-369, December.
  4. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
  5. Thomas Alban, 1995. "Regulating Pollution under Asymmetric Information: The Case of Industrial Wastewater Treatment," Journal of Environmental Economics and Management, Elsevier, vol. 28(3), pages 357-373, May.
  6. Roger B. Myerson, 1977. "Incentive Compatability and the Bargaining Problem," Discussion Papers 284, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  7. Pascal Lavergne & Alban Thomas, 2005. "Semiparametric estimation and testing in a model of environmental regulation with adverse selection," Empirical Economics, Springer, vol. 30(1), pages 171-192, January.
  8. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  9. Pepper, John V., 2002. "Robust inferences from random clustered samples: an application using data from the panel study of income dynamics," Economics Letters, Elsevier, vol. 75(3), pages 341-345, May.
  10. Kopp, Raymond J. & Mullahy, John, 1990. "Moment-based estimation and testing of stochastic frontier models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 165-183.
  11. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
  12. Diewert, W.E., 1993. "Duality approaches to microeconomic theory," Handbook of Mathematical Economics, in: K. J. Arrow & M.D. Intriligator (ed.), Handbook of Mathematical Economics, edition 4, volume 2, chapter 12, pages 535-599 Elsevier.
  13. Jean Tirole & Jean-Jaques Laffont, 1985. "Using Cost Observation to Regulate Firms," Working papers 368, Massachusetts Institute of Technology (MIT), Department of Economics.
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