Asymmetric Information With Multiple Risks: The Case of the Chilean Private Health Insurance Market

Area of Science:

• Health Economics
• Insurance Markets
• Risk Theory

Background:

• The Rothschild and Stiglitz (1976) model is a cornerstone in analyzing insurance markets.
• Real-world health insurance involves multiple risk dimensions, such as inpatient and outpatient care.
• Previous models often simplify risk, potentially misrepresenting market dynamics.

Purpose of the Study:

• To extend the Rothschild and Stiglitz model to incorporate multiple risk dimensions (inpatient and outpatient).
• To theoretically explore the phenomenon of coverage reversal in multi-dimensional risk settings.
• To empirically test for adverse selection in the Chilean private health insurance market, accounting for multi-dimensional risk.

Main Methods:

• Theoretical extension of the Rothschild and Stiglitz model to include two distinct risk types.
• Development of a multi-dimensional adaptation of the Chiappori and Salanié (2000) positive correlation test.
• Empirical analysis using individual-level claims data from Chile's private health insurance sector.

Main Results:

• Identified a theoretical possibility of 'coverage reversal,' where individuals with higher overall risk may receive less coverage in a specific dimension.
• Demonstrated that failing to account for differences in one risk dimension when testing for adverse selection in another can lead to biased results.
• Empirical findings from Chile support the necessity of separating samples based on differing risk profiles.

Conclusions:

• Multi-dimensional risk is crucial for accurately modeling health insurance markets.
• The phenomenon of coverage reversal has significant implications for adverse selection testing.
• Methodological rigor in separating samples by risk dimension is essential to avoid erroneous conclusions in empirical studies of adverse selection.