Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution...

Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution...

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...

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...

When treatments may occur at different points in time, most evaluation methods assume - implicitly or explicitly - that all the information used by subjects about the occurrence of a future treatment is available to the researcher. This is often called the no anticipation assumption. In reality,...

When treatments may occur at different points in time, most evaluation methods assume – implicitly or explicitly – that all the information used by subjects about the occurrence of a future treatment is available to the researcher. This is often called the “no anticipation” assumption....

This note describes how the (single-spell) identification result of the timing-of-events model by Abbring and Van den Berg (2003b) can be extended to a model that accommodates several competing exit risks. The extended model can be used for example to distinguish between the different effects of...

We introduce a dynamic treatment to the mixed proportional hazard competing risks model and allow for selection on unobservables. Our model can e.g. be used to evaluate the effect of benefit sanctions on the transition rate out of unemployment when more than one exit risk is of interest....

Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution...

A general formulation of Mixed Proportional Hazard models with K random effects is provided. It enables to account for a population stratified at K different levels. We then show how to approximate the partial maximum likelihood estimator using an EM algorithm. In a Monte Carlo study, the...