A Least-Cost Mechanism to Achieve Agricultural Income and Conservation Targets under Asymmetric Information
| dc.contributor.advisor | Chambers, Robert G | en_US |
| dc.contributor.author | Sheriff, Glenn David | en_US |
| dc.contributor.department | Agricultural and Resource Economics | en_US |
| dc.contributor.publisher | Digital Repository at the University of Maryland | en_US |
| dc.contributor.publisher | University of Maryland (College Park, Md.) | en_US |
| dc.date.accessioned | 2005-02-02T06:36:27Z | |
| dc.date.available | 2005-02-02T06:36:27Z | |
| dc.date.issued | 2004-11-23 | en_US |
| dc.description.abstract | Two policy goals dominate United States' agricultural programs: voluntary land retirement for environmental purposes and countercyclical income support. Traditionally, these goals have been pursued with separate policies. This policy separation is efficient with perfect information regarding farm productivity. A more realistic assumption, however, is that farmers have better information regarding their own productivity than the government. The focus of the dissertation is to analyze least cost agricultural policy with this type of asymmetric information. I first use a mechanism design framework to show that it is optimal to have a combined income support-land retirement program rather than separate programs. For land retirement, farmers have an incentive to overstate productivity in order to receive a higher rental payment. For income support, farmers have an incentive to understate productivity to receive a higher income support payment. With high output prices, the first effect dominates. With low prices, the second dominates. Farmers' ability to use private information to their advantage increases the cost to the government of reaching its targets. If contract commitment takes place when output prices are uncertain, the two incentives can countervail each other, reducing the cost of the policy to the government. In the second part of the dissertation, I extend the literature by showing how one can implement the policy using actual data. I conduct a numerical simulation to determine the exact payment and land set aside for each farmer. To calibrate the simulation, I apply stochastic frontier analysis to a data set of US farmers. I thus obtain consistent estimates of the key determinants of the contracts: the farm profit function and the probability distribution of profitability levels across the sector. Simulation results show that unlike current programs, the least cost contract is likely to involve pooling. Farmers with different profitability levels receive identical expected payments for idling identical acreage. The countervailing incentives created by the least-cost policy almost eliminate the information advantage of farmers, significantly reducing cost relative to current programs. | en_US |
| dc.format.extent | 1451103 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1903/2053 | |
| dc.language.iso | en_US | |
| dc.subject.pqcontrolled | Economics, Agricultural | en_US |
| dc.subject.pquncontrolled | mechanism design | en_US |
| dc.subject.pquncontrolled | stochastic frontier analysis | en_US |
| dc.subject.pquncontrolled | environment | en_US |
| dc.subject.pquncontrolled | simulation | en_US |
| dc.title | A Least-Cost Mechanism to Achieve Agricultural Income and Conservation Targets under Asymmetric Information | en_US |
| dc.type | Dissertation | en_US |
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