Getting the Right Tail Right: Modeling Tails of Health Expenditure Distributions

Martin Karlsson, Yulong Wang and Nicolas Ziebarth ()

No 31444, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: C10 C13 I10 I13 (search for similar items in EconPapers)
Date: 2023-07
New Economics Papers: this item is included in nep-ecm and nep-hea
Note: EH
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Citations: View citations in EconPapers (1)

Published as Martin Karlsson & Yulong Wang & Nicolas R. Ziebarth, 2024. "Getting the right tail right: Modeling tails of health expenditure distributions," Journal of Health Economics, .

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Journal Article: Getting the right tail right: Modeling tails of health expenditure distributions (2024)
Working Paper: Getting the Right Tail Right: Modeling tails of health expenditure distributions (2023)
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