Binary choice models for rare events data: a crop insurance fraud application
Y Jin, RM Rejesus*, BB Little - Applied Economics, 2005 - Taylor & Francis
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.
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.
Binary choice models for rare events data: a crop insurance fraud application.
JYF Jin YuFei, RM Rejesus, BB Little - 2005 - cabidigitallibrary.org
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.
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.
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