We develop a nonparametric instrumental variable approach for the estimation of average treatment effects on hazard rates and conditional survival probabilities, without model structure. We derive constructive identification proofs for average treatment effects under noncompliance and dynamic...

We develop a nonparametric instrumental variable approach for the estimation of average treatment effects on hazard rates and conditional survival probabilities, without model structure.We derive constructive identification proofs for average treatment effects under noncompliance and dynamic...

This paper implements a method to identify and estimate treatment effects in a dynamic setting where treatments may occur at any point in time. By relating the standard matching approach to the timing-of-events approach, it demonstrates that effects of the treatment on the treated at a given...

In this paper, I consider the identification of lagged durationdependence in multiple spells without using the assumtion that there are additionalregressors orthogonal to the individual effects. The non-parametricidentification strategy is applied to the multiple non-employment spells of 2066...

In this paper, I consider the identification of lagged durationdependence in multiple spells without using the assumtion that there are additionalregressors orthogonal to the individual effects. The non-parametricidentification strategy is applied to the multiple non-employment spells of 2066...

Our survey covers the recent developments of the microeconometric literature on evaluation methods. In this field, the canonical model is Rubin's causal model, which is close to Roy's selectivity model. This model is the relevant framework for defining and for examining the identifiability...

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...

We propose and implement a new method to estimate treatment effects in settings where individuals need to be in a certain state (e.g. unemployment) to be eligible for a treatment, treatments may commence at different points in time, and the outcome of interest is realized after the individual...

In this paper, we specify and estimate a structurally dependent competing risks model for the transitions out of unemployment into either new job or recall. The recall probability is allowed to affect the search intensity for new jobs.

In this paper, we specify and estimate a structurally dependent competing risks model for the transitions out of unemployment into either new job or recall. The recall probability is allowed to affect the search intensity for new jobs.