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Registros recuperados: 4
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Determinants of Anomalous Prevented Planting Claims: Theory and Evidence from Crop Insurance AgEcon
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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USING DATA MINING TO DETECT ANOMALOUS PRODUCER BEHAVIOR: AN ANALYSIS OF SOYBEAN PRODUCTION AND THE FEDERAL CROP INSURANCE PROGRAM AgEcon
Olson, Stacey; Little, Bertis B.; Lovell, Ashley C..
The analysis was conducted on the USDA's Risk Management Agency insurance data and NRCS Land Resource Regions from 1994 - 2001 to assist RMA in improving program integrity. The objective is to develop a data-mining algorithm that identifies anomalous producers and counties within LRRs based upon the percentage of acres harvested.
Tipo: Conference Paper or Presentation Palavras-chave: Risk and Uncertainty.
Ano: 2003 URL: http://purl.umn.edu/35223
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Prediction of Weather Event Associated Crop Yield Losses in Kansas AgEcon
Wang, Erda; Williams, Jimmy R.; Little, Bertis B..
The Environmental Policy Integrated Climate (EPIC) model was modified to include hail weather events, completing modification needed to simulate the four most frequent causes of crop yield loss (hail, too wet, too cold, too dry) in the Kansas crop insurance program. Yields were simulated for corn, wheat, soybeans, and sorghum.
Tipo: Conference Paper or Presentation Palavras-chave: Crop Production/Industries.
Ano: 2006 URL: http://purl.umn.edu/35467
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Patterns of Collusion in the U.S. Crop Insurance Program: An Empirical Analysis AgEcon
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
Registros recuperados: 4
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