Often, the moment of a treatment and the moment at which the outcome of interest occurs are realizations of stochastic processes with dependent unobserved determinants. Notably, both treatment and outcome are characterized by the moment they occur. We compare different methods of inference of...

Using a proportional hazard model with multiple exits, this paper analyzes whether immigrants' unemployment spells differ from natives', and if so, how the difference vary with time spent in Sweden and across immigrant cohorts. A unique data set taken from the Swedish unemployment registers is...

Using a proportional hazard model with multiple exits, this paper analyzes whether immigrants' unemployment spells differ from natives', and if so, how the difference vary with time spent in Sweden and across immigrant cohorts. A unique data set taken from the Swedish unemployment registers is...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...

The vocational employment training program is the most expensive training program in Sweden and a cornerstone of labor market policy. We analyze its causal effects on the individual transition rate from unemployment to employment by exploiting variation in the timing of treatment and outcome,...

The vocational employment training program is the most expensive training program in Sweden and a cornerstone of labor market policy. We analyze its causal effects on the individual transition rate from unemployment to employment by exploiting variation in the timing of treatment and outcome,...

In a large class of hazard models with proportional unobserved heterogeneity, the distribution of the heterogeneity among survivors converges to a gamma distribution. This convergence is often rapid. We derive this result as a general result for exponential mixtures and explore its implications...

Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the...

We provide a new full-commitment intertemporal collective household model to estimate resource shares, defined as the fraction of household expenditure enjoyed by household members. Our model implies nonlinear time-varying household quantity demand functions that depend on fixed effects. We...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...