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...

We analyse pricing, e¤ort and tipping decisions in the online service GoogleAnswers. While users set a price for the answer to their question ex ante, theycan additionally give a tip to the researcher ex post.In line with the related experimental literature we …nd evidence that tippingis...

We consider guilt averse agents and principals and study the effects ofguilt on optimal behavior of the principal and the agent in a moral hazardmodel.The principal’s contract proposal contains a target effort in addition tothe monetary incentive scheme. By accepting the agreement, the...

Amidst a sharp increase in household debt levels, many countries have substantially reformedtheir consumer bankruptcy regulations. I first classify the mechanisms triggered by current U.S.and European bankruptcy regulations and then evaluate these mechanisms within a hidden actionmodel. I...

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...

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...

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...