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December 2015 Evaluating the causal effect of university grants on student dropout: Evidence from a regression discontinuity design using principal stratification
Fan Li, Alessandra Mattei, Fabrizia Mealli
Ann. Appl. Stat. 9(4): 1906-1931 (December 2015). DOI: 10.1214/15-AOAS881

Abstract

Regression discontinuity (RD) designs are often interpreted as locally randomized experiments for units with a realized value of a pretreatment variable falling around a threshold. Motivated by the evaluation of Italian university grants, we consider a fuzzy RD design where the treatment status is based on both eligibility criteria and a voluntary application status. Resting on the fact that grant application and grant receipt statuses are post-assignment (post-eligibility) intermediate variables, we use the principal stratification framework to define causal estimands within the Rubin Causal Model. We propose a probabilistic formulation of the assignment mechanism underlying RD designs, by reformulating the Stable Unit Treatment Value Assumption (SUTVA) and making an explicit local overlap assumption for a subpopulation around the threshold. We invoke a local randomization assumption instead of the more standard continuity assumptions. We also develop a Bayesian approach to select the target subpopulation(s) with adjustment for multiple comparisons, and to draw inference for the target causal estimands within this framework. Applying the method to the data from two Italian universities, we find evidence that university grants are effective in preventing students from low-income families from dropping out of higher education.

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Fan Li. Alessandra Mattei. Fabrizia Mealli. "Evaluating the causal effect of university grants on student dropout: Evidence from a regression discontinuity design using principal stratification." Ann. Appl. Stat. 9 (4) 1906 - 1931, December 2015. https://doi.org/10.1214/15-AOAS881

Information

Received: 1 December 2014; Revised: 1 September 2015; Published: December 2015
First available in Project Euclid: 28 January 2016

zbMATH: 06560814
MathSciNet: MR3456358
Digital Object Identifier: 10.1214/15-AOAS881

Keywords: Bayesian , causal effects , intermediate variables , Principal stratification , Randomization , regression discontinuity , university grants

Rights: Copyright © 2015 Institute of Mathematical Statistics

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Vol.9 • No. 4 • December 2015
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