A significant fraction of the labor force consists of employed workers who are part-time unemployed (underemployed) in the sense that they are unable to work as much as they prefer. This paper develops a search and matching model to study the design of optimal unemployment insurance in an...

Firms select not only how many, but also which workers to hire. Yet, in standard search models of the labor market, all workers have the same probability of being hired. We argue that selective hiring crucially affects welfare analysis. Our model is isomorphic to a search model under random...

We develop and estimate a non-stationary job search model to evaluate a scheme that monitors job search effort and sanctions insured unemployed whose effort is deemed insufficient. The model reveals that such schemes provide incentives to the unemployed to front-load search effort prior to...

The distribution of unemployment duration in our equilibrium matching model with spell-dependent unemployment benefits displays a time-varying exit rate. Building on Semi-Markov processes, we translate these exit rates into an expression for the aggregate unemployment rate. Structural estimation...

Rare and randomly occurring events are important features of the economic world. In continuous time they can easily be modeled by Poisson processes. Analyzing optimal behavior in such a setup requires the appropriate version of the change of variables formula and the Hamilton-Jacobi-Bellman...

Rare and randomly occurring events are important features of the economic world. In continuous time they can easily be modeled by Poisson processes. Analyzing optimal behavior in such a setup requires the appropriate version of the change of variables formula and the Hamilton-Jacobi-Bellman...

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is...

Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from characteristic single-stage and multi-stage versions of such...

We consider a portfolio optimization problem in a Black-Scholes model with n stocks, in which an investor faces both fixed and proportional transaction costs. The performance of an investment strategy is measured by the average return of the corresponding portfolio over an infinite time horizon....

The aim of the paper is to study empirically the influence of higher moments of the return distribution on conditional value at risk (CVaR). To be more exact, we attempt to reveal the extent to which the risk given by CVaR can be estimated when relying on the mean, standard deviation, skewness...