The welfare cost of unpriced heterogeneity in insurance markets

We consider the welfare loss of unpriced heterogeneity in insurance markets, which results when private information or regulatory constraints prevent insurance companies to set premiums reflecting expected costs. We propose a methodology which uses survey data to measure this welfare loss. After identifying some \u201ctypes\u201d which determine expected risk and insurance demand, we derive the key factors defining the demand and cost functions in each market induced by these unobservable types. These are used to quantify the efficiency costs of unpriced heterogeneity. We apply our methods to the US Long-Term Care and Medigap insurance markets, where we find that unpriced heterogeneity causes substantial inefficiency

Testing For Asymmetric Information In Insurance Markets With Unobservable Types

In two important recent papers, Finkelstein and McGarry [25] and Finkelstein and Poterba [28] propose a new test for asymmetric information in insurance markets that considers explicitly unobserved heterogeneity in insurance demand. In this paper we propose an alternative implementation of the Finkelstein-McGarry-Poterba test based on the identification of unobservable types by use of finite mixture models. The actual implementation of our test follows some recent advances on marginal modelling as applied to latent class analysis; formal testing procedures for the null of asymmetric information and for the hypothesis that private information is indeed multidimensional can be performed by imposing restrictions on the behavior of these unobservable types. To show the potential applicability of our approach, we look at the long term insurance market as analyzed in Finkelstein and McGarry [25], where we also find strong evidence for both asymmetric information and multidimensional unobserved heterogeneity.Asymmetric Information, Unobservable Types, Latent Class Analysis, Long Term Insurance Market.

The Effect Of Supplemental Insurance On Health Care Demand With Multiple Information: A Latent Class Analysis

The Medicare program, which provides insurance coverage to the elderly in the United States, does not protect them fully against high out-of-pocket costs. For this reason private supplementary insurance, named Medigap, has been available to cover Medicare gaps. This paper studies how Medigap affects the utilization of health care services. The decision to take out supplemental insurance is likely to be infuenced by unobservable attributes such as actual risk type and insurance preferences. Empirical appraisals to this problem typically rely on the recursive bivariate probit. We exploit the Health and Retirement Study data and some recent advances on latent class analysis to jointly model the insurance and health care decisions. Results show the presence of unobserved `types' representing different preferences and risk levels. We compare our results to those obtained by the probit and the bivariate probit and find the residual effect of insurance on health care not significant.Health Care Demand; Latent Class Models; Health Insurance; Asymmetric Information; Medigap.

BEHIND THE ATKINSON INDEX: MEASURING EQUALITY OF OPPORTUNITY IN HEALTH

This paper proposes a new approach to the measurement of equality of opportunity in health, based on the path independent Atkinson index of equality. The proposed decomposition is applied both to the ex-ante and the ex-post methodologies recently adopted by the literature. The approach is applied to the measurement of equality of opportunity in health using ten waves of the British Household Panel Survey. Results confirm that socioeconomic background is an important factor determining individual health in adulthood while the incidence of equality of opportunity is around one third of the overall equality according to a substantial stable pattern over years. Our findings also depict that differences in education, in social conditions and in the life style are crucial determinants of the shape of the observed health equalities in adulthood, explaining how potential differences can be derived by the combination of different circumstances

Testing for Asymmetric Information in Insurance Markets: A Multivariate Ordered Regression Approach

The positive correlation (PC) test is the standard procedure used in the empirical literature to detect the existence of asymmetric information in insurance markets. This article describes a new tool to implement an extension of the PC test based on a new family of regression models, the multivariate ordered logit, designed to study how the joint distribution of two or more ordered response variables depends on exogenous covariates. We present an application of our proposed extension of the PC test to the Medigap health insurance market in the United States. Results reveal that the risk\u2013coverage association is not homogeneous across coverage and risk categories, and depends on individual socioeconomic and risk preference characteristics

Measuring equity in health: a normative decomposition

This paper proposes a new approach to the measurement of equality of opportunity in health, based on the path independent Atkinson index of equality. The proposed decomposition is applied both to the ex-ante and the ex-post methodologies recently adopted by the literature. The approach is applied to the measurement of equality of opportunity in health using ten waves of the British Household Panel Survey. Results confirm that socioeconomic background is an important factor determining individual health in adulthood while the incidence of equality of opportunity is around one third of the overall equality according to a substantial stable pattern over years. Our findings also depict that differences in education, in social conditions and in the life style are crucial determinants of the shape of the observed health equalities in adulthood, explaining how potential differences can be derived by the combination of different circumstances.Equality of opportunity; health inequalities; Atkinson index; responsibility;