Time & location: 11:00 - 12:00 on Thursday, Oct 26, at
Title: Iterative Network Pricing for Ridesharing Platforms
Abstract: Ridesharing platforms match riders and drivers, using dynamic pricing to balance supply and demand. The origin-based “surge pricing”, however, does not depend on the market condition of trip destinations, leading to inefficient trip flows in space and incentivizes drivers to strategize. In this work, we introduce the Iterative Network...
Abstract: A seller is pricing identical copies of a good to a stream of unit-demand buyers. Each buyer has a value on the good as his private information. The seller only knows the empirical value distribution of the buyer population and chooses the revenue-optimal price. We consider a widely studied third-degree price discrimination model where an information intermediary with perfect knowledge of the arriving buyer'...
Title: Ex-Post Group Fairness and Individual Fairness in Ranking
Abstract: Fair ranking tasks, which ask to rank a set of items to maximize utility subject to satisfying group-fairness constraints, have gained significant interest in algorithmic fairness, information retrieval, and machine learning literature. Recent works identify uncertainty in the utilities of items as a primary cause of unfairness and propose randomized rankings that achieve ex-ante fairer exposure and better robustness than...
Title: Learning to Leverage the Information Lever: Online Recommendation and Dynamic Pricing
Abstract: Modern customers' decisions are intricately shaped not only by their own preferences but also by the associated information with the products being offered. For online marketplaces that aim to maximize the revenue, it is important to learn how to effectively leverage the information as a lever to induce desired customers’ decisions.
In this talk, I will present an algorithmic framework, using a...
The EconCS Group holds an Economics & Computer Science research seminar each semester. Fall '23 meetings are at 1:30 - 2:30 PM on Fridays in SEC 1.413. Seminar Coordinators are Shirley Zhang and Tao Lin. SEC 1.413 is on ground level at the NW corner of SEC, which is open to the public. The seminar is in-person only. Speaker: Juan Perdomo (Harvard CRCS postdoc)
Practical algorithms and experimentally validated incentives for equilibrium-based fair division (A-CEEI)
Abstract:
Approximate Competitive Equilibrium from Equal Incomes (A-CEEI) is an equilibrium-based solution concept for fair division of discrete items to agents with combinatorial demands. We developed a new heuristic A-CEEI algorithm that significantly outperforms the (previous) commercial state-of-the-art and is now in production on real course allocation problems....
SEC 1.413, & streamed via Zoom at: https://harvard.zoom.us/j/95184948637?pwd=bXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09
This Friday, 1-2pm in SEC 1.413, Hannah Li will be speaking in person on:
Marketplace Experimentation and Interference Effects
Abstract:
Platforms often rely on experiments (A/B tests) to aid decision-making. However, in many marketplace experiments, interactions between users can create interference effects that lead to biased estimates. We develop mathematical models to capture these interference effects and study the biases that arise. In particular, we are able to highlight and formalize the relationship...
Zoom at the link: https://harvard.zoom.us/j/95184948637?pwd=bXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09
Scott Kominers (Harvard Business School)
A Simple Theory of Vampire Attacks
Abstract:
Firms often find it valuable to lock in repeat consumers, and they often do so via loyalty programs such as frequent-flyer miles or discounts for returning consumers. We introduce a model of loyalty programs in the presence of competition and show that, surprisingly, such programs result in higher prices for all consumers in equilibrium.
However, competitors may also find it valuable to identify repeat consumers of other firms and convince them to...
SEC 1.413, & streamed via Zoom at: https://harvard.zoom.us/j/95184948637?pwd=bXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09
This Friday, 1-2pm in SEC 1.413, we are very excited to have Sharad Goel (Harvard Kennedy School) speak in-person on:
Included-variable bias and everything but the kitchen sink
Abstract: When estimating the risk of an adverse outcome, common statistical guidance is to include all available factors to maximize predictive performance. Similarly, in observational studies of discrimination, general practice is to adjust for all potential confounds to...Read more about Included-variable bias and everything but the kitchen sink
