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| Rejesus, Roderick M.; Little, Bertis B.; Lovell, Ashley C.; Cross, Mike H.; Shucking, Michael. |
| This article analyzes anomalous patterns of agent, adjuster, and producer claim outcomes and determines the most likely pattern of collusion that is suggestive of fraud, waste, and abuse in the federal crop insurance program. Log-linear analysis of Poisson-distributed counts of anomalous entities is used to examine potential patterns of collusion. The most likely pattern of collusion present in the crop insurance program is where agents, adjusters, and producers nonrecursively interact with each other to coordinate their behavior. However, if a priori an intermediary is known to initiate and coordinate the collusion, a pattern where the producer acts as the intermediary is the most likely pattern of collusion evidenced in the data. These results have... |
| Tipo: Journal Article |
Palavras-chave: Abuse; Collusion; Crop insurance; Empirical analysis; Fraud; Waste; G22; Q12; Q18; Q19. |
| Ano: 2004 |
URL: http://purl.umn.edu/43393 |
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| Knight, Thomas O.; Lovell, Ashley C.; Rister, M. Edward; Coble, Keith H.. |
| Agricultural lenders have a stake in and are in a position to influence their borrowers' management decisions. Risk management practice adoption is an area in which lenders might want to exercise this influence. This study employs logistic statistical models to estimate lenders' influence on crop producers' decisions regarding use of three alternative risk management practices: federal multiple-peril crop insurance, crop hail and fire insurance, and forward contracting. Results suggest lenders can exert significant influence on these decisions but that poor communication between lenders and borrowers likely reduces this influence. |
| Tipo: Journal Article |
Palavras-chave: Agricultural Finance; Risk and Uncertainty. |
| Ano: 1989 |
URL: http://purl.umn.edu/30092 |
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| Rejesus, Roderick M.; Lovell, Ashley C.; Little, Bertis B.; Cross, Mike H.. |
| This study examines the factors that determine the likelihood of submitting a potentially fraudulent prevented planting claim. A theoretical model is developed and the theoretical predictions are empirically verified by utilizing a binary choice model and crop insurance data from the southern United States. The empirical results show that insured producers with higher prevented planting coverage, lower dollar value of expected yield, and a history of submitting prevented planting claims are more likely to submit an anomalous prevented planting claim. The empirical model also suggests revenue insurance plans may be more vulnerable to prevented planting fraud than the traditional yield-based insurance plan. Results of this study can be valuable to compliance... |
| Tipo: Journal Article |
Palavras-chave: Crop Production/Industries. |
| Ano: 2003 |
URL: http://purl.umn.edu/31632 |
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