Recent papers use regression discontinuity designs (RDDs) based on age discontinuity to evaluate social assistance (SA) and unemployment insurance (UI) extension policies. Job search theory predicts that such designs generate biased estimates of the policy-relevant treatment effect. Owing to market frictions, people below the age threshold modify their search behavior in expectation of future eligibility. We use a job search model to quantify the biases on various datasets in the literature. The impacts of SA benefits on employment are underestimated, whereas those of UI extensions on nonemployment duration are overestimated. The article provides insights for RDD evaluations of age-discontinuous policies.
History
Author affiliation
College of Social Sci Arts and Humanities
School of Business
The data and code that support the findings of this study are openly available athttps://doi.org/10.3886/E207842V1, or on the GitHub pagehttps://github.com/gwilemme/RDD_age_disc