Testing the Efficient Redistribution Hypothesis: An Application to Japanese Beef Policy
AbstractWe discuss and model the structure of the political economy of Japanese beef markets, and we apply Bullock's statistical test of the efficient redistribution hypothesis to our model to study the Pareto efficiency of Japanese beef policy in 1990 and 1991. We found that, under the hypothesis that our modeled political economy adequately reflects the true Japanese beef political economy, we could not reject at the 5% significance level that Japanese beef policy was inefficient in 1990 and in 1991; however, we could reject inefficiency in 1991 at a 7% level of significance. Copyright 1999, Oxford University Press.
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Bibliographic InfoArticle provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.
Volume (Year): 81 (1999)
Issue (Month): 2 ()
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- Earl L. Grinols & Peri Silva, 2012. "Intervention Efficiency, Incentive Symmetry, and Information," Development Working Papers 334, Centro Studi Luca d\'Agliano, University of Milano, revised 16 Jul 2012.
- Bullock, David S. & Rutstrom, Elisabet E., 2001. "The Size Of The Prize: Testing Rent-Dissipation When Transfer Quantity Is Endogenous," 2001 Annual meeting, August 5-8, Chicago, IL 20447, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Bullock, David S. & Salhofer, Klaus, 2003. "Judging agricultural policies: a survey," Agricultural Economics, Blackwell, vol. 28(3), pages 225-243, May.
- Bullock, David S., 2005. "Should We Expect Government Policy to Be Pareto Efficient?: The Consequences of an Arrow-Debreu Economy with Violable Property Rights," 2005 Annual meeting, July 24-27, Providence, RI 19444, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- David Bullock & E. RutstrÃ¶m, 2007. "Policy making and rent-dissipation: An experimental test," Experimental Economics, Springer, vol. 10(1), pages 21-36, March.
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