JOURNAL ARTICLE

Optimal Long-Term Health Insurance Contracts: Characterization, Computation, and Welfare Effects.

  • Published In: Review of Economic Studies, 2024, v. 91, n. 2. P. 1085 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Ghili, Soheil; Handel, Ben; Hendel, Igal; Whinston, Michael D 3 of 3

Abstract

This article focuses on the theoretical characterization, empirical computation, and welfare analysis of optimal long-term health insurance contracts with one-sided insurer commitment, aimed at mitigating reclassification risk—the risk of premium increases due to persistent health shocks under short-term contracts. Using detailed health and claims data from all privately insured men aged 25–64 in Utah, the study finds that dynamic long-term contracts effectively reduce reclassification risk for consumers entering the market in good health but perform poorly for those entering in poor health, especially when income rises steeply over the life cycle. The analysis highlights that government insurance of pre-age-25 health risks substantially enhances the welfare gains from dynamic contracts, and that consumer switching costs improve contract performance, while consumer myopia diminishes it moderately. Compared to managed competition-style insurance exchanges like those under the Affordable Care Act (ACA), dynamic contracts are preferred for consumers with flatter income profiles and adequate pre-market health risk insurance, whereas exchanges perform better for those with rising income profiles. The article also discusses practical challenges to implementing such contracts in the U.S. market, including short insurance durations and forecasting difficulties, suggesting that complementary policies and regulatory changes are crucial for their viability.

Additional Information

  • Source:Review of Economic Studies. 2024/03, Vol. 91, Issue 2, p1085
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:0034-6527
  • DOI:10.1093/restud/rdad054
  • Accession Number:175875941
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