Social experiments and instrumental variables with duration outcomes

Abstract

This paper examines the empirical analysis of treatment effects on duration outcomes from data that contain instrumental variation. We focus on social experiments in which an intention to treat is randomized and compliance may be imperfect. We distinguish between cases where the treatment starts at the moment of randomization and cases where it starts at a later point in time. We derive exclusion restrictions under various informational and behavioral assumptions and we analyze identifiability under these restrictions. It turns out that randomization (and by implication, instrumental variation) by itself is often insufficient for inference on interesting effects, and needs to be augmented by a semi-parametric structure. We develop corresponding non-and semi-parametric tests and estimation methods.

Regression Discontinuity Designs in Epidemiology

“… 36 – 39 Instrumental variables techniques that account for censoring in survival analysis are under development. 40 A simple approach is to use predicted survival probabilities for the numerator in the Wald estimator 40 ; under some assumptions, predicted hazards could also be estimated and plugged in (eAppendix, http://links.lww.com/EDE/A808 ). We note that the null hypothesis is equivalent to and the variance of is strictly larger than the variance of ; if a result is not statistically significant in the ITT framework, it will not be significant after scaling by take-up.…”

The Effect of Sanctions on Exit from Unemployment: Evidence from Denmark

“…In order to provide a first check of the possible effect of sanctions on the exit rate from unemployment, Figure 2 presents empirical sanction rate hazard functions for individuals who leave unemployment at selected elapsed durations. The figure is inspired by Abbring and van den Berg (2003b). The first sanction rate is estimated for a subsample of individuals who leave unemployment between four and six weeks of unemployment.…”

Does online search improve the match quality of new hires?

“…These figures are sufficiently high to rule out that results are strongly affected by selectivity due to interaction effects between internet availability and unobserved systematic determinants of the transition to work, on the occurrence of employment before the end of the observation window. Notice that the occurrence of subsequent events before the end of this window may be susceptible to such selection issues (see, e.g.,Abbring and van den Berg (2005), for details).17 The municipality identifier in the administrative data is based on individuals' place of residence. If the place of residence is missing, we use the municipality identifier of individual spells from the previous or subsequent five years or -in a final step -information on individuals' workplace (establishment) location.18 See for more details on why we concentrate on this DSL period.…”