When Historical Prices Becomes Transparent, Must Consumers Be Better Off?
Recent years have witnessed a growing number of online platforms disclosing the historical prices of products to consumers. While such transparency is typically viewed as consumer-friendly, this paper shows that it can raise prices and reduce consumer welfare. We develop a dynamic model in which a seller faces sequential consumers who are uncertain about product quality and rely on past consumer reviews....
Xi Li, HKU Business School
Wednesday, Oct 15, 2025 | 2:00pm-3:30pm | Room 335
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How Costly are Trading Biases?
We analyze a broad set of buy-side trading biases identified in leading finance journals over the past 75 years. Using 14.5 years of trade-level data for retail and institutional investors, we find that roughly 20 percent of documented biases are no more prevalent among retail investors than would be expected from random trading, while retail investors display about three times as many biases as institutions....
Daniel Weagley, University of Tennessee
Wednesday, Oct 15, 2025 | 10:30am-12:00pm | Room 339
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Quantity-Biased Technological Change
Skill-biased technological change has long been linked to rising wage inequality. New technologies also allow firms to expand their scope of their operation. We formalize such quantity-biased technological change in a model where heterogeneous firms with decreasing returns to scale choose the size and quality of their white and blue-collar worker pools. We characterize the equilibrium assignment and ...
Philipp Kircher, Cornell University
Friday, Oct 10, 2025 | 10:30am-12:00pm | Room 337
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Optimizing Drone Operations in Logistics, Emergency Relief, and Infrastructure Inspection
Recent advancements in drone technology have significantly broadened their applications in logistics, humanitarian relief, and infrastructure inspection. In this talk, I will present our recent research on optimizing drone operations across these diverse scenarios. Specifically, I will discuss methods for optimizing drone delivery routing under nonlinear energy consumption and uncertain weather conditions,...
Chun Cheng, Dalian University of Technology
Friday, Sep 26, 2025 | 10:30am-12:00pm | Room 335
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Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Allocation of goods and services often involves both stochastic supply and stochastic demand. Motivated by applications such as cloud computing, gig platforms, and blockchain auctions, we study the design of optimal selling mechanisms in an environment where buyers with private valuations arrive stochastically and are assigned goods that also arrive stochastically, and either buyers or goods can be ...
Yeon-Koo Che, Columbia University
Tuesday, Sep 23, 2025 | 12:30pm-2:00pm | Room 339
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Robust Benchmark Satisficing
We propose a robust benchmark satisficing framework for data-driven decision-making under uncertainty, designed to identify decisions whose expected revenue exceeds that of a comparator by a user-specified surplus—even when the true distribution is unknown. This framework generalizes the robust satisficing model of Long et al. (2023), by accommodating a broader range of benchmark-driven decision criteria ...
Melvyn Sim, National University of Singapore
Tuesday, Sep 23, 2025 | 11:30pm-2:00pm | Room 337
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Price-Cut Commitment under Strategic Inventory and Retailer Dominance
Problem definition: Dominant retailers often pressure manufacturers to commit to future wholesale price reductions, yet the implications of such price-cut commitments---particularly when retailers can also hold strategic inventory---are not fully understood. The decision is further complicated when multiple retailers compete for supply, as both commitments and inventory strategies influence upstream ...
Gangshu Cai, Santa Clara University
Thursday, Sep 18, 2025 | 10:30am-12:00pm | Room 337
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AI as Decision-Maker: Ethics and Risk Preferences of LLMs
Large Language Models (LLMs) exhibit surprisingly diverse risk preferences when acting as AI decision makers, a crucial characteristic whose origins remain poorly understood despite their expanding economic roles. We analyze 50 LLMs using behavioral tasks, finding stable but diverse risk profiles. Alignment tuning for harmlessness, helpfulness, and honesty significantly increases risk aversion, with ...
Shumiao Ouyang, University of Oxford
Wednesday, Sep 10, 2025 | 2:00pm-3:30pm | Room 339
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Range Anxiety
Range anxiety, the fear of depleting battery before reaching a charging station, is often cited as a major barrier to electric vehicle (EV) adoption, yet there has been limited formal economic analysis to quantify its importance and understand the policy implications. We develop a continuous-time dynamic model of EV usage and charging decisions to quantify range anxiety as the utility loss from feasible ...
Shanjun Li, Stanford University
Wednesday, Sep 10, 2025 | 2:00pm-3:30pm | Room 337
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Simulating Public Opinion with Large Language Models: An Evidence-Based Exploration
As a new medium of communication, large language models (LLMs) learn values and attitudes from human-generated data, giving them the potential to capture and reflect public opinion. This talk will examine the capacity of LLMs to simulate public opinion from two perspectives. First, we will investigate the extent to which LLMs can represent public opinion across different nations and social groups, ...
Baohua Zhou, Fudan University
Wednesday, June 25, 2025 | 10:30am - 12:00pm | Room 333
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