Treatment evaluation in the case of interactions within markets
We extend the standard evaluation framework to allow for interactions between individuals within segmented markets. An individualâs outcome depends not only on the assigned treatment status but also on (features of) the distribution of the assigned treatments in his market. To evaluate how the distribution of treatments within a market causally aﬀects the average eﬀect within the market, averaged over the full population, we develop an identiﬁcation and estimation method in two steps. The ﬁrst one focuses on the distribution of the treatment within markets and between individuals and the second step addresses the distribution of the treatment between markets. We apply our method to data on training programs for unemployed workers in France. We use a rich administrative register of unemployment and training spells as well as the information on local labor demand that is used by unemployment agencies to allocate training programs. The results show that the average treatment eﬀect on the employment rate causally decreases with respect to the proportion of treated in the market. Our analysis accounts for unobserved heterogeneity between markets (using the longitudinal dimension of the data) and, in a robustness check, between individuals.
|Date of creation:||27 Jan 2010|
|Date of revision:|
|Publication status:||Published as Ferracci, Marc, Gregóry Jolivet and Gerard J. van den Berg, 'Evidence of Treatment Spillovers Within Markets' in The Review of Economics and Statistics, 2014, pages 812-823.|
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