Incorporating self-reported health measures in risk equalization through constrained regression

Anja Koster*, Richard van Kleef, Frank Eijkenaar

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)
26 Downloads (Pure)

Abstract

Most health insurance markets with premium-rate restrictions include a risk equalization system to compensate insurers for predictable variation in spending. Recent research has shown, however, that even the most sophisticated risk equalization systems tend to undercompensate (overcompensate) groups of people with poor (good) self-reported health, confronting insurers with incentives for risk selection. Self-reported health measures are generally considered infeasible for use as an explicit ‘risk adjuster’ in risk equalization models. This study examines an alternative way to exploit this information, namely through ‘constrained regression’ (CR). To do so, we use administrative data (N = 17 m) and health survey information (N = 380 k) from the Netherlands. We estimate five CR models and compare these models with the actual Dutch risk equalization model of 2016 which was estimated by ordinary least squares (OLS). In the CR models, the estimated coefficients are restricted, such that the under-/overcompensation for groups based on self-reported general health is reduced by 20, 40, 60, 80, or 100%. Our results show that CR can improve outcomes for groups that are not explicitly flagged by risk adjuster variables, but worsens outcomes for groups that are explicitly flagged by risk adjuster variables. Using a new standardized metric that summarizes under-/overcompensation for both types of groups, we find that the lighter constraints can lead to better outcomes than OLS.
Original languageEnglish
Pages (from-to)513–528
Number of pages16
JournalThe European Journal Of Health Economics
Volume21
DOIs
Publication statusPublished - 8 Jan 2020

Bibliographical note

JEL Classification: I10-Health, G22-Insurance, insurance companies, actuarial studies, H51-Government expenditures and health
Acknowledgements:
The authors are grateful for the thorough comments on a previous version of this article by two anonymous reviewers. They are also grateful to René van Vliet, Wynand van de Ven, Erik Schut, and Thomas McGuire for valuable feedback during this project. Furthermore, the authors would like to thank the participants of the HSI seminar series and the attendees of the RAN meeting 2018 for helpful discussions. The authors also gratefully acknowledge the Dutch Ministry of Health, the Dutch Association of Health Insurers and Statistics Netherlands for providing the administrative and survey data. Finally, the authors thank the members of the supervisory committee for their valuable comments. Remaining errors are the responsibility of the authors.

Research programs

  • EMC NIHES-05-63-03 Competition

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