Mohit Karnani

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We study the efficiency of a centralized college admissions platform that operates jointly with a decentralized “off-platform” aftermarket. We exploit a policy change in 2012 in which a significant number of off-platform higher education options joined a centralized assignment system for higher-education programs in Chile. We show evidence that this policy change had impacts on real outcomes finding that the share of students declining their placed spot de-creased by 8% and dropout rates at the end of the first year of college dropped by 2 percentage points (a 16% drop) following this event. To quantify the welfare impacts of the aftermarket on the efficiency of the match, we develop and estimate an empirical model of college applications, aftermarket waitlists and matriculation choices, using individual-level administrative data from Chile on almost half a million applications, including test scores and enrollment decisions at all on- and off-platform higher education options. According to model estimates, welfare increases substantially, students begin their studies sooner, and fewer students drop out by the end of the first year of study when top off-platform programs join the platform. These benefits are greater for less advantaged students and for women. Counterfactual analysis suggests that more desirable options generate larger negative externalities when not on the platform. These externalities are mostly driven by students admitted on on-platform options that decline their spots to pursue off-platform programs; and are amplified by frictions in waitlists that yield socially inefficient allocations. Our results indicate that platform design can have real impact on outcomes of interest. Specifically, our findings suggest policymakers need to consider the implications of off platform options and their characteristics when designing regulation surrounding centralized assignment systems.
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Kapor, A., Neilson, C., & Karnani, M. (2019). Negative Externalities of Off Platform Options and the Efficiency of Centralized Assignment Mechanisms. Retrieved from (Original work published 12/2019AD)
Working Papers