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,...

We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi-parametric MLE that is shown to be consistent and asymptotically normally distributed. In a...

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,...

Public programs often use statistical profiling to assess the risk that applicants will become long-term dependent on the program. The literature uses linear probability models and (Cox) proportional hazard models to predict duration outcomes. These either focus on one threshold duration or...

We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker or covariate effects. A number of well-known models are special cases. In a counting process...

We consider a dependent competing risks model with many risks and many covariates. We show identifiability of the marginal distributions of latent variables for a given dependence structure. Instead of directly estimating these distributions, we suggest a plug-in regression framework for the...

We propose two simple semiparametric estimation methods for ordered response models with an unknown error distribution. The proposed methods do not require users to choose any tuning parameter and they automatically incorporate the monotonicity restriction of the unknown distribution function....