Analyzing the Anticipation of Treatments Using Data on Notification Dates

Abstract

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, subjects may receive private signals about the date when a treatment may start. We provide a methodological and empirical analysis of this issue in a setting where the outcome of interest as well as the moment of information arrival (notification) and the start of the treatment can all be characterized by duration variables. Building on the "Timing of Events" approach, we show that the causal effects of notification and of the treatment on the outcome are identified. We estimate the model on an administrative data set of unemployed workers in France which provides the date when job seekers receive information from caseworkers about their future treatment status. We find that notification has a significant and positive effect on unemployment duration. This result violates the standard "no anticipation" assumption and rules out a "threat effect" of training programs in France.

Keywords: evaluation of labor market programs, training, duration model, timing of events, anticipation

JEL Classification: C31, C41, J64, J68