arXiv subjects

Eric Gao

Publications and source records attributed to Eric Gao.

9 recordsLinked to original sources

arXiv2026

Fair Commodity Taxation

We study optimal taxation in monopoly screening problems with a redistribution-minded regulator. When the regulator moves before the monopolist, any nondecreasing allocation can be implemented as the monopolist's optimum under an appropriate tax schedule. Despite this flexibility, we show that our redistribution-minded regulator never strictly benefits from randomization or nonlinear taxes. Under a strengthening of Myersonian regularity, which we call strong regularity, we characterize the tax rates on the fairness-efficiency frontier: it is enough for the regulator to consider policies which consist of a per-unit excise tax and a lump-sum rebate, with all (and only) tax rates between the consumer-surplus maximizing rate and the Laffer peak appearing on the frontier. Finally, we show subsidies are never used, and that every frontier threshold policy rations more than the unregulated monopolist.

econ.TH↗

arXiv2025

Multidimensional Sequential Screening

I study multidimensional sequential screening. A monopolist contracts with a buyer who privately observes information about the distribution of their eventual valuations for multiple goods. After initial private information is reported and the contract is signed, the buyer learns and reports realized valuations. In these settings, the monopolist frontloads surplus extraction: Any information rents given to the buyer to elicit their true valuations can be extracted in expectation before those valuations are drawn, transforming the multidimensional screening problem by distorting buyer information rents compared to static screening. If the buyer's distributions over valuations are commonly FOSD ordered, regular for each good, and satisfy invariant dependencies (valuations can be dependent across goods, but how valuations are coupled cannot vary), the optimal mechanism coincides with independently offering the optimal sequential screening mechanism for each good. This rationalizes membership payments followed by separate sales schemes commonly used in practice.

econ.TH↗

arXiv2025

Private From Whom? Minimal Information Leakage in Auctions

In many auctions, bidders may value keeping their private information hidden from the auctioneer or other bidders. Yet information must be conveyed to conduct an auction. Among deterministic bilateral communication protocols, revealing less information to bidders requires revealing more information to the auctioneer, and vice versa. A protocol implementing a given social choice rule is on the Privacy Frontier if no alternative protocol reveals less to both bidders and the auctioneer. For first-price auctions, the descending protocol and the sealed-bid protocol are on the Privacy Frontier. For second-price auctions, the ascending protocol and the ascending-join protocol are on the Privacy Frontier, but the sealed-bid protocol is not. We provide sufficient conditions for a protocol to be on the Privacy Frontier and devise alternative protocols allowing a designer to flexibly balance different dimensions of privacy.

econ.TH↗

arXiv2025

Artificial or Human Intelligence?

Artificial intelligence (AI) tools such as large language models (LLMs) are already altering student learning. Unlike previous technologies, LLMs can independently solve problems regardless of student understanding, yet are not always accurate (due to hallucination) and face sharp performance cutoffs (due to emergence). Access to these tools significantly alters a student's incentives to learn, potentially decreasing the sum knowledge of humans and AI. Additionally, the marginal benefit of learning changes depending on which side of the AI frontier a human is on, creating a discontinuous gap between those that know more than or less than AI. This contrasts with downstream models of AI's impact on the labor force which assume continuous ability. Finally, increasing the portion of assignments where AI cannot be used can counteract student mis-specification about AI accuracy, preventing underinvestment. A better understanding of how AI impacts learning and student incentives is crucial for educators to adapt to this new technology.

econ.TH↗

arXiv2025

Seeding an Uncertain Technology

I study how a startup with uncertainty over product quality and no knowledge of the underlying diffusion network optimally chooses initial seeds. To ensure widespread adoption when the product is good while minimizing negative perceptions when it is bad, the optimal number of initial seeds should grow logarithmically with network size. When there are agents of different types that govern their connectivity, it is asymptotically optimal to seed agents of a single type: the type that minimizes the marginal cost per probability of making the product go viral. These results rationalize startup behavior in practice.

econ.TH↗

arXiv2025

Simple Paired Combinatorial Assignment

Consider a university assigning students to courses and dorms. While many mechanisms are available, they each have their own drawbacks. Running serial dictatorship once for all goods is highly unfair, but running serial dictatorship separately for each matching problem is inefficient-Pareto improvements can be found via students jointly trading their allocated course and dorm. Alternatively, competitive equilibrium from equal incomes scales combinatorially in the number of items, making implementation and preference elicitation difficult. This paper considers paired serial dictatorship: a novel mechanism where agents signal relative preferences that determine their priority in each market. Any deterministic allocation that arises in equilibrium is Pareto efficient and envy-free, highlighting how seemingly innocuous tie-breaking is the key barrier to optimality and fairness. When agents differ only in relative preferences, paired serial dictatorship ex-ante Pareto dominates running random serial dictatorship independently in each market. Such gains exist even when agents behave simplistically.

econ.TH↗

arXiv2024

Quantity Limits on Addictive Goods

Addiction is a major societal issue leading to billions in healthcare losses per year. Policy makers often introduce ad hoc quantity limits-limits on the consumption or possession of a substance-something which current economic models of addiction have failed to address. This paper enriches Bernheim and Rangel (2004)'s model of addiction driven by cue-triggered decisions by incorporating endogenous choice of how much of the addictive good to consume, instead of just whether or not consumption happens. Stricter quality limits improve welfare as long as they do not preclude the myopically optimal level of consumption.

econ.TH↗

arXiv2023

Random Serial Dictatorship with Transfers

It is well known that Random Serial Dictatorship is strategy-proof and leads to a Pareto-Efficient outcome. We show that this result breaks down when individuals are allowed to make transfers, and adapt Random Serial Dictatorship to encompass trades between individuals. Strategic analysis of play under the new mechanisms we define is given, accompanied by simulations to quantify the gains from trade.

cs.GT↗

arXiv2023

(Robust) Information Acquisition Design

We study the design of information acquisition games-environments where a designer contracts their action on Sender's choice of experiment and the realized signals about some state. We develop a revelation-like principle for this setting and characterize the incentive properties of implementable allocations. We next turn to robust allocations-those that can be implemented regardless of the prior-and show that robustness is equivalent to experiment-neutrality of the mechanism. We conclude by considering two applications. First, for general good allocation problems, we show all efficient allocations are robust, even when agent preferences feature state-dependent outside options and allocation externalities. Second, we apply our model to school choice and uncover a novel informational justification for deferred acceptance when school preferences depend on students' unknown ability.

econ.TH↗