PUBLICATIONS
On the revealed preference analysis of stable aggregate matchings (with Thomas Demuynck)
Theoretical Economics, 17 (2022), 1651–1682
Echenique, Lee, Shum, and Yenmez (2013) established the testable revealed preference restrictions for stable aggregate matching with transferable (TU) and non-transferable utility (NTU) and for extremal stable matchings. In this paper, we rephrase their restrictions in terms of properties on a corresponding bipartite graph. From this, we obtain a simple condition that verifies whether a given aggregate matching is rationalisable. For matchings that are not rationalisable, we provide a simple greedy algorithm that computes the minimum number of matches that needs to be removed to obtain a rationalisable matching. We also show that the related problem of finding the minimum number of types that we need to remove in order to obtain a rationalisable matching is NP-complete.
Affirmative actions: The Boston mechanism case (with M. O. Afacan)
Economics Letters, 2016, 141, 95-97
We consider three popular affirmative action policies in school choice: quota-based, priority-based, and reserve-based affirmative actions. The Boston mechanism (BM) is responsive to the latter two policies in that a stronger priority-based or reserve-based affirmative action makes some minority student better off. However, a stronger quota-based affirmative action may yield a Pareto inferior outcome for the minority under the BM. These positive results disappear once we look for a stronger welfare consequence on the minority or focus on BM equilibrium outcomes.
WORK IN PROGRESS
Equal opportunities in school choice settings (with Domenico Moramarco)
We introduce a notion of fairness, inspired by the equality of opportunity literature, into the school choice setting, endowed with a measure of the match qualities between students and schools. In this framework, fairness considerations are made by a social evaluator based on the match quality distribution. We impose the standard notion of stability as minimal desideratum and study matchings that satisfy our notion of fairness, and an efficiency requirement based on aggregate match quality. To overcome some of the identified incompatibilities, we propose two alternative approaches. The first one is a linear programming solution to maximize fairness or efficiency under stability constraint. The second approach weakens fairness and efficiency to define a class of opportunity egalitarian social welfare functions and describe an algorithm to find the stable matching that maximizes social welfare. We conclude with an illustration on the allocation of Italian high school students in 2021/2022.
The Object Allocation Problem with Maximum and Minimum Number of Changes
This paper studies the object allocation problem, which involves assigning objects to agents while taking into account both object capacities and agents’ preferences. I focus on two classes of allocations: the Pareto efficient and Individual rational allocations and the Pareto efficient and Weak-core stable allocations. The goal is to look at two optimality criteria within these classes: one that maximizes the number of individuals improving upon their initial endowment (MAXDIST), and the one that minimizes the number of individuals who need to change from their initial allocation to the final one (MINDIST). I present an efficient algorithm for addressing the MAXDIST problem for the first class of allocations (Pareto efficient and Individual rational). Next, I study a special case of this problem where priority is given to the most disadvantaged individuals. I establish NP-completeness results for the other problems. I also look at how the results change when restricting individual preferences to be dichotomous. Finally, I present an integer programming formulation to solve small to moderately sized instances of the NP-hard problems.