Assistant Professor: University of Notre Dame
Email: pingandrew[at]gmail[dot]com
My CV
Research Interests: Matching, Incomplete Information
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Working Papers
Working Papers
I introduce a framework for studying transient matching in decentralized markets where workers learn about their preferences through experience. Limits on the number of available positions force workers to compete over matches. Each capacity-constrained firm employs workers whose match value exceeds a threshold. Since employment offers both payoff and information benefits, workers face a multi-armed bandit problem. Each firm acts as a bandit where the probability of "success" at the firm is driven by market competition. Equilibria are inefficient because competition depresses the level of search. Interventions designed to improve efficiency are effective in uncongested markets, but can fail when congestion is severe. Reducing congestion through unemployment benefits, depresses search in vertical markets. Headhunters have differential effects depending on workers’ quality, conclusively improving outcomes for low-quality workers.
Build to Order: Endogenous Supply in Centralized Mechanisms, 2026, with Kwok Hao Lee and Luther Yap (under review)
How should a planner choose the composition of scarce goods when an application both claims a good and reports the applicant's private type? We study a dynamic matching model in which agents prefer one of several good types, choose queues, and receive goods by lottery within queues. The planner controls supply over time, minimizing mismatch and unassignment. In Markovian lottery mechanisms, responsive supply creates an incentive problem: supplying only the currently over-demanded good encourages agents to join the popular queue to avoid waiting. The optimal mechanism in this class therefore sometimes supplies the under-demanded type, despite risking temporary unassignment. Batching applications increases market thickness, helping the planner equalize expected waiting times across queues.
We study strategic interactions in decentralized matching markets, where firms make directed offers to workers and agents' preferences are aligned. We show that stable outcomes can be achieved through decentralized interactions if either information frictions or time frictions are absent. When both frictions are present, stable outcomes are attainable with sufficient richness of plausible preference profiles. However, unique implementation requires more stringent conditions on market interactions. Additionally, simulations demonstrate that strategic decentralized interactions lead to stability much faster than the naïve best-response dynamics that the literature has focused on.
(In)Stability in Networked Markets, 2026, with Zeky Murra-Anton [Online Appendix] (under review)
Networked markets rely on infrastructure whose operational availability is controlled by market participants. We study a two-sided transferable-utility matching market in which coalitions can profit by withholding links before settlement, changing outsiders' feasible trades and the settlement environment, a network disruption externality. A settlement rule assigning a self-enforcing payoff after each withholding event prices the externality and induces a characteristic-function game. Network-stable payoffs are exactly its core; existence is equivalent to Bondareva-Shapley balancedness, and nonexistence occurs when disruption rents create infeasible overlapping claims. Simple local ownership patterns generate nonexistence for an open set of surplus vectors under every settlement rule, and the probability of structural instability converges exponentially to one in large random markets. Finally, the punishment rule characterizes when disruption-neutral settlement is feasible. When it is, balanced-budget transfers convert any settlement rule into one under which the entire fixed-network core is network-stable.
Public Housing at Scale, 2023, with Kwok Hao Lee and Luther Yap
We consider the design of a large-scale public housing program where consumers face dynamic tradeoffs over apartments rationed via lotteries and prices. We show, theoretically and empirically, that changing rules complements increasing supply. First, we present a motivating example in which supplying more housing leads households to strategically delay their applications. By waiting for “better” developments arriving tomorrow, households forgo mediocre developments available today, resulting in more vacancies. Turning to the data from the mechanism, we formulate a dynamic choice model over housing lotteries and estimate it. Under the existing mechanism, we find that increasing supply fails to lower wait times. However, when a strategyproof mechanism is implemented, vacancies and wait times fall, but prices on the secondary market rise. Under this new mechanism, building more apartments lowers wait times and reduces the upward pricing pressure on the secondary market.
Works in Progress
Works in Progress
Racing to Interview, 2026, with Stephen Nei
We study a setting where two agents inspect two potential projects. Each project might be achievable or not with independent probability for each agent. Agents must decide how to allocate attention across the two projects in continuous time, and receive perfectly revealing signals according to a Poisson process, while unable to observe each others' attention decisions. While in the absence of a signal agents' beliefs about project achievability does not change over time, their beliefs about the other agent's action is time-dependent in equilibrium. Equilibrium inefficiency is increasing in the gap in priors regarding the projects' qualities.
Coordinated Matching, 2026, with Alejandro Robinson-Cortés
In many matching markets agents have private information regarding their preferences and can only make a limited number of offers. We study the incentives of agents to share their private information with other agents on the same side of the market in order to coordinate match offers. Our focus is on whether information can be transmitted through cheap talk under a natural refinement. We find that, even in settings in which communication has the potential to be efficiency-enhancing, cheap talk results in fragile information transmission when agents might have dominant actions. To contrast, we prove that information can be credibly communicated when the preference uncertainty is limited. Our results highlight the limits of cheap-talk communication in two-sided matching markets. They also highlight the role for alternative means to establish credibility, such as commitment devices, costly forms of communication, or reputational considerations arising through repeated interaction.
Evident Competition, 2024, with Clara Nguyen, and Erez Yoeli
United States civil courts rely on an adversarial system where two parties in a lawsuit obtain and present evidence according to a process known as discovery. Two discovery regimes are predominantly used: voluntary disclosure, which does not require parties to reveal all evidence in their possession, and formal discovery, which does. How do these regimes influence the extent of the parties' search for evidence and the information available to the judge? We find that each regime has its advantages: Voluntary disclosure tends to provide a stronger incentive to search relative to formal discovery, but formal discovery ensures the judge is better informed conditional on the evidence found. Furthermore, the quality of evidence plays an important role, when evidence is decisive for the judge, parties are encouraged to search more and present more evidence. Our results can help explain the legal literature's inconclusive findings on the relationship between disclosure and settlement.
Completed Papers
DyPy, 2020, with Anjalika Nande, Eric Lubin, Erez Yoeli, and Martin Nowak
We've developed a python library for simulating matrix form games! DyPy is an open source Python software library that is hosted on Github at https://github.com/anjalika-nande/dynamics_sim. The package is designed to make it simple to run evolutionary game theory simulations to model populations undergoing biological and cultural evolution in a range of fields, from biology to economics to linguistics. Detailed documentation for each command in the library, sample code for exemplary simulations and a Wiki is provided in the Github repository. Improvements through pull requests and suggestions for additional functionality are encouraged.
Geometric Invariants of Numerical Semigroups, 2016, with Maksym Fedorchuk and Jian Zhou
A natural invariant of a unibranch curve singularity is the numerical semigroup of its valuations. In the case when the curve singularity admits a GGm-action, this semigroup also determines the singularity uniquely. A rational-valued function on curve singularities with GGm-action that leads to an ordering of singularities according to their geometric complexity was proposed. We explore this function and give a classification of those numerical semigroups for which the values of this function are above a certain threshold.
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