Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/279812 
Year of Publication: 
2023
Series/Report no.: 
ZEW Discussion Papers No. 23-045
Publisher: 
ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung, Mannheim
Abstract: 
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.
Subjects: 
heavy tails
health expenditures
claims data
nonlinear model
JEL: 
C10
C13
I10
I13
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.