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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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Kulyakwave,Peter David; Shiwei,Xu; Yu,Wen. |
ABSTRACT: Rice farming is characterized by various factors including environmental and non-environmental factors. The current paper analyses the influence of households’ characteristics, and perceptions of weather variability on rice yield. Authors used primary data collected from small-scale rice farmers in the Mbeya region of Tanzania. Garret technique and Stata software were used for data analyses. Results confirmed that farmer’s education, marital status, gender, and land ownership have a positive influence on rice yield. Thus, for every 1% increase in each variable increases rice yield by 14%, 98%, 26%, and 21% respectively. Owing to empirical results on farmers’ perceptions, it is confirmed that if the drought period increased by 1%, would on... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Rice yield; Weather; Perceptions; Empirical analysis; Tanzania. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019001100200 |
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