Testing for asymmetric information in insurance markets has become a very important issue in the empirical literature in the last years. We analyze the (private) accident insurance, which has not been analyzed before in the literature, but covers one of the most important risks faced by...

Asymmetric information is an important phenomenon in insurance markets, but the empirical evidence on the extent of adverse selection and moral hazard is mixed. Because of its implications for pricing, contract design, and regulation, it is crucial to test for asymmetric information in specic...

Asymmetric information is an important phenomenon in many markets and in particular in insurance markets. Testing for asymmetric information has become a very important issue in the literature in the last two decades. Almost all testing procedures that are used in empirical studies are...

Since Chiappori and Salanié, testing for asymmetric information has become tantamount to testing for a positive relation between risk and coverage which is predicted by (equilibrium) models for adverse selection and moral hazard. In this paper we review parametric tests and a recently developed...

In this paper we analyze asymmetric information in the (private) disability insurance, which has not been analyzed before in the literature, but covers one of the most important risks faced by individuals in modern society, namely the loss of human capital. We show that there is asymmetric...

type="main" xml:lang="en" <title type="main">Abstract</title> <p>Asymmetric information is an important phenomenon in insurance markets, but the empirical evidence on the extent of adverse selection and moral hazard is mixed. Because of its implications for pricing, contract design, and regulation, it is crucial to test for...</p>

Quantile regression (QR) fits a linear model for conditional quantiles just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean-squared error linear approximation to the conditional expectation function even...

In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator handles censoring semi-parametrically in the tradition of Powell (1986), and it generalizes standard censored quantile regression (CQR) methods...