Three essays on agricultural risk and insurance

dc.contributor.advisor Bruce A. Babcock
dc.contributor.advisor David A. Hennessy
dc.contributor.advisor Dermot J. Hayes
dc.contributor.author Zhang, Li
dc.contributor.department Department of Economics (LAS)
dc.date 2018-08-22T19:25:07.000
dc.date.accessioned 2020-06-30T07:47:45Z
dc.date.available 2020-06-30T07:47:45Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2008
dc.date.issued 2008-01-01
dc.description.abstract <p>The general theme of this dissertation is agricultural risk and insurance in the United States. Chapter 2 examines welfare effects of the 2002 farm bill programs and yield insurance as well as their impacts on acreage decision of a representative Iowa farmer. Instead of measuring welfare using expected utility to capture farmers' preferences over risky alternatives, we apply recent advances in decision theory and use prospect theory to measure welfare changes due to government programs. The results indicate that there is no policy distortion to farmers' acreage decisions and farmers' willingness to pay per dollar of program cost is greatest for crop insurance. Given that farmers have crop insurance, the willingness to pay per dollar of program cost is much lower for loan deficiency payments, direct payments, and counter-cyclical payments. Chapter 3 develops a method for determining the aggregate risk of a book of business using hail insurance data. A spatial statistical approach is employed to measure the spatial correlation of hail loss cost. Monte Carlo simulation techniques are employed to simulate hail losses for a wide range of books of business. A regression model is estimated that captures the essence of the Monte Carlo simulation. This model can then be used to quickly estimate the degree of poolability of any given book of business. Chapter 4 turns to weather-based index contracts as alternative risk-management instruments in agriculture. A major concern associated with index contracts is basis risk. To address spatial basis risk, two spatial interpolation approaches, a geo-statistical approach and a Markov random field approach, are compared. The Markov random field approach is preferred because it has a smaller cross-validation prediction mean squared error. A temperature index insurance is presented based on interpolated data. The potential performance of the proposed index insurance is investigated through historical analysis in contract years 1980 to 2005.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/rtd/15858/
dc.identifier.articleid 16857
dc.identifier.contextkey 7051188
dc.identifier.doi https://doi.org/10.31274/rtd-180813-17059
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/15858
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/69532
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/rtd/15858/3296786.PDF|||Fri Jan 14 20:47:35 UTC 2022
dc.subject.disciplines Agricultural and Resource Economics
dc.subject.disciplines Agricultural Economics
dc.subject.keywords Economics;
dc.title Three essays on agricultural risk and insurance
dc.type dissertation
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 4c5aa914-a84a-4951-ab5f-3f60f4b65b3d
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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