Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/279812 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
ZEW Discussion Papers No. 23-045
Verlag: 
ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung, Mannheim
Zusammenfassung: 
Health expenditure data almost always include extreme values, implying that the underlying distribution has heavy tails. This may result in infinite variances as well as higher-order moments and bias the commonly used least squares methods. To accommodate extreme values, we propose an estimation method that recovers the right tail of health expenditure distributions. It extends the popular two-part model to develop a novel three-part model. We apply the proposed method to claims data from one of the biggest German private health insurers. Our findings show that the estimated age gradient in health care spending differs substantially from the standard least squares method.
Schlagwörter: 
heavy tails
health expenditures
claims data
nonlinear model
JEL: 
C10
C13
I10
I13
Dokumentart: 
Working Paper

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