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 provides asymptotically valid tests for the null hypothesis of no treatment effect heterogeneity. Importantly, I consider the presence of heterogeneity that is not explained by observed characteristics, or so-called idiosyncratic heterogeneity. When examining this heterogeneity,...

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...

In this paper we simultaneously analyze transitions from unemployment to employment and to nonparticipation. We estimate a dependent competing risks model with nonparametric specifications of the destination-specific duration dependence and unobserved heterogeneity terms. We use a unique...

We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas (1994) type estimator which adapts the nonparametric conditional hazard rate estimator...

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...

In the practice of program evaluation, choosing the covariates and the functional form of the propensity score is an important choice that the researchers make when estimating treatment effects. This paper proposes a data-driven way of averaging the estimators over the candidate specifications...

We consider the problem of assessing the effects of a treatment on duration outcomes using data from a randomized evaluation with noncompliance. For such settings, we derive nonparametric sharp bounds for average and quantile treatment effects addressing three pervasive problems simultaneously:...