Journal article
Detecting fuzzy relationships in regression models: The case of insurer solvency surveillance in Germany
Insurance, mathematics & economics, Vol.46(3), pp.554-567
06/01/2010
DOI: 10.1016/j.insmatheco.2010.02.003
Abstract
We develop a test for the fuzziness of regression coefficients based on the
Tanaka et al. (1982) and
He et al. (2007) possibilistic fuzzy regression models. We interpret the spread of the regression coefficients as a statistic measuring the fuzziness of the relationship between the corresponding independent variable and the dependent variable. We derive test distributions based on the null hypothesis that such spreads could have been obtained by estimating a possibilistic regression with data generated by a classical regression model with random errors. As an example, we show how our test detects a fuzzy regression coefficient in a solvency prediction model for German property–liability insurance companies.
Details
- Title: Subtitle
- Detecting fuzzy relationships in regression models: The case of insurer solvency surveillance in Germany
- Creators
- Thomas R. Berry-Stölzle - University of GeorgiaMarie-Claire Koissi - Western Illinois UniversityArnold F. Shapiro - Pennsylvania State University
- Resource Type
- Journal article
- Publication Details
- Insurance, mathematics & economics, Vol.46(3), pp.554-567
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.insmatheco.2010.02.003
- ISSN
- 0167-6687
- eISSN
- 1873-5959
- Language
- English
- Date published
- 06/01/2010
- Academic Unit
- Finance
- Record Identifier
- 9984380400302771
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