Duarte Gonçalves

Duarte Gonçalves

Hi, I’m Duarte.

I’m a PhD Candidate at Columbia University
and I work mainly on Microeconomic theory and Behavioral Economics



Reach out: duarte.goncalves.ds@gmail.com




Research

Working Papers


Sequential Sampling and Equilibrium
(draft coming soon)

Understanding how agents form beliefs is crucial to understand choices. I propose an equilibrium framework where players best-respond to their beliefs and where beliefs are formed through sequentially sampling from the population distribution of opponents’ actions at a cost. In equilibrium, beliefs are random, but closely tied to the primitives of the model: payoffs, sampling costs and priors. Relying on properties I establish for the sequential sampling problem in individual decision-making settings – collapsing bounds, speed-accuracy complementarity and comparative statics results – we illustrate the ability of our solution concept to rationalize well-known deviations from Nash equilibrium as the own-payoff effect (Goeree and Holt, 2001) as well as recent experimental evidence that relate gameplay and response times.



The Effect of Incentives on Choices and Beliefs in Games. An Experiment
with Teresa Esteban-Casanelles ; March 2020

Do incentive levels matter in strategic environments? Existing models disagree not only on whether gameplay is affected by incentive levels, the overall stakes players face, but also on why. In this paper, we present experimental evidence establishing that the level of incentives affects both gameplay and beliefs. Holding fixed the actions of the other player, we find that, in the context of dominance-solvable games, higher incentives make subjects more likely to best-respond to their beliefs. Moreover, higher incentives result in more responsive beliefs but not necessarily less biased. We provide evidence that incentives affect effort and that it is effort, and not incentives directly, that accounts for the changes in belief formation. The results support models where, in addition to choice mistakes, players exhibit costly attention.



Robust Pricing and Reliable Projections: Statistical Mechanism Design
with Bruno Furtado; May 2020

This paper studies the robustness of pricing strategies when a firm is uncertain about the distribution of consumers’ willingness-to-pay. When the firm has access to data to estimate this distribution, a simple strategy is to implement the mechanism that is optimal for the estimated distribution. We find that such empirically optimal mechanism boasts strong profit and regret guarantees. Moreover, we provide a toolkit to evaluate the robustness properties of different mechanisms, showing how to consistently estimate and conduct valid inference on the profit generated by any one mechanism, which enables one to evaluate and compare their probabilistic revenue guarantees.



Recommenders’ Originals: Integrated Recommender Systems and Vertical Foreclosure
with Guy Aridor ; revised April 2020

We study a model of strategic interaction between producers and a monopolist platform that employs a recommendation system. We characterize the consumer welfare implications of the platform’s entry into the production market. The platform’s entry induces the platform to bias recommendations to steer consumers towards its own goods, which leads to equilibrium investment adjustments by the producers and lower consumer welfare. Further, we find that a policy separating recommendation and production is not always welfare improving. Our results highlight the ability of integrated recommender systems to serve as tools of vertical foreclosure.



Work in Progress


Random Belief Updating
with Arthur Prat-Carrabin


Retractions. An Experiment [Working Title]
with Jonathan Libgober and Jack Willis


Fact-Checking. An Experiment [Working Title]
with Jonathan Libgober and Jack Willis




Notes


Diagonal Games
January 2020

This note introduces a new class of dominance-solvable games called diagonal games with several theoretical interesting properties that make them particularly well-suited for experimental applications.