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

Yufei Jin, Roderick Rejesus and Bertis Little

Applied Economics, 2005, vol. 37, issue 7, 841-848

Abstract: 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.

Date: 2005
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DOI: 10.1080/0003684042000337433

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