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Binary choice models for rare events data: a crop insurance fraud application

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This study implements a recently proposed score test that could help guide insurance fraud researchers in deciding whether to use a logit or a probit model in predicting insurance fraud probabilities, especially when the occurrence of ones in the dependent variable is much less than zeros. The test is easily implemented in a crop insurance fraud context and seems to be a promising method that could be applicable to analysing and detecting potentially fraudulent claims in various lines of insurance.

Document Type: Research Article


Affiliations: 1: AGRICORP, Ontario, Canada 2: Department of Agricultural and Applied Economics, Texas Tech University, Lubbock, TX 79409 3: Center for Agribusiness Excellence, Tarleton State University, Stephenville, TX 76402

Publication date: April 20, 2005

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