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- W2952725725 abstract "This paper presents a new approach to deal with spatial inequalities in risk adjustment between health insurances. The shortcomings of non-spatial and spatial fixed effects in risk adjustment models are analysed and opposed against spatial kernel estimators. Theoretical and empirical evidence suggests that a reasonable choice of the spatial kernel could limit the spatial uncertainty of the modifiable area unit problem under heavy-tailed claims data, leading to more precise predictions and economically positive incentives on the healthcare market. A case study of the German risk adjustment shows a spatial risk spread of 86 Euro p.c., leading to incentives for spatial risk selection. The proposed estimator eliminates this issue and conserves incentives for services optimisation." @default.
- W2952725725 created "2019-06-27" @default.
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- W2952725725 date "2019-06-13" @default.
- W2952725725 modified "2023-09-23" @default.
- W2952725725 title "Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for service optimisation and reduce MAUP" @default.
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- W2952725725 doi "https://doi.org/10.1007/s10198-019-01079-6" @default.
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