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)

I propose an equilibrium framework based on sequential sampling where players face strategic uncertainty — uncertainty with respect to the distribution of gameplay of the opponents. Players sequentially accumulate empirical information on their opponents’ distribution of actions at a cost and equilibrium imposes a consistency condition on the overall distribution of gameplay. The solution concept can account for stochastic choice without relying on indifference conditions or choice mistakes and makes predictions on the joint distribution of players’ choices, beliefs and response times. It rationalizes well-known deviations of gameplay from Nash equilibrium as well as patterns in process data as decision times.



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

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.



Statistical Mechanism Design: Robust Pricing and Reliable Projections
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
with Jonathan Libgober and Jack Willis


Fact-Checking
with Jonathan Libgober and Jack Willis


The Dynamics of Conflict


Learning and Strategic Uncertainty




Notes


Diagonal Games: A Tool for Experiments
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. In particular, it allows for a systematic way to the number of steps of iterated elimination of dominated strategies required to reach the dominance solution as well as the number of strategies, it identifies level-k actions only using ordinal payoff information and it pins down specific predictions made by quantal response equilibrium. The results generalize to games with interval strategy sets.