We embed learning (without experimentation) in optimal growth. We extend the Mirman-Zilcha results of stochastic optimal growth to the learning case. We use recursive methods to study the effect of learning on the dynamic program by considering the case of iso-elastic utility and linear...

This paper assesses the merits of countercyclical bank balance sheet regulation for the stabilization of financial and economic cycles and examines its interaction with monetary policy. The framework used is a dynamic stochastic general equilibrium model with banks and bank capital, in which...

Risk classification refers to the use of observable characteristics by insurers to group individuals with similar expected claims, compute the corresponding premiums, and thereby reduce asymmetric information. With perfect risk classification, premiums fully reflect the expected cost associated...

This paper uses longitudinal data to perform tests of asymmetric information in the French automobile insurance market for the 1995-1997 period. This market is characterized by the presence of a regulated experience-rating scheme (bonus-malus). We demonstrate that the result of the test depends...

The identification of information problems in different markets is a challenging issue in the economic literature. In this paper, we study the identification of moral hazard from adverse selection and learning within the context of a multi-period dynamic model. We extend the model of Abbring et...

In this paper we compare the welfare effects of unemployment insurance (UI) with an universal basic income (UBI) system in an economy with idiosyncratic shocks to employment. Both policies provide a safety net in the face of idiosyncratic shocks. While the unemployment insurance program should...

We discuss the difficult question of measuring the effects of asymmetric information problems on resource allocation. Three problems are examined: moral hazard, adverse selection, and asymmetric learning. One theoretical conclusion, drawn by many authors, is that information problems may...