Working Papers

• Leading by Example Among Equals (Link to paper) 

Abstract. I examine the factors that determine whether a grassroots social movement reaches the necessary size to achieve its goal. I study a collective action problem where identical individuals who value the common goal sequentially decide whether to join the movement. The model has two key ingredients: (i) The movement is facing a freeriding problem (i.e., while individuals want the movement to succeed, they would rather have others bear the cost of participation) and (ii) The necessary number of members to achieve success is ex-ante unknown but it can be revealed as the movement grows in size. The central insight is that an increase in cost of participation, such as harsher and more likely punishment for members of the movement, can lead to a drastic surge in membership.

• Tacit Collusion and Dynamic Reference Prices (Link to paper) 

   Abstract. This paper examines the extent of tacit collusion in an oligopoly market where consumers are affected by past prices. In particular, we study an infinite horizon Bertrand competition between two identical firms where today’s demand for the good at a given price is higher if it is a discount relative to past prices and lower if the price has been raised. First, we find that history dependent demand leads to overpricing (relative to the myopic profit maximizing price), as the firms consider it an investment in future demand which they can take advantage of through discounts. Second, the firms are able to coordinate on monopoly behavior as long as an upper bound is not crossed. Prices that are too high are followed by very large discounts, after which the firms gradually raise it until a steady state is reached. Above this upper bound, a higher price today leads to a larger discount tomorrow and lower lifetime profits for the firms.

• Volunteer's Dilemma with Social Learning (Link to paper)

Abstract. We study a volunteer's dilemma game with sequential moves. If one individual exerts costly effort, a public good that benefits everyone equally is produced. The value of the public good is uncertain, and each individual receives a private signal about it. The central mechanism of the model is that individuals make inferences about each other's private signal by observing their action. We focus on the behavior of the equilibrium probability of public good provision with respect to population size and show that it is not monotonic. If the population is small, increasing it beyond a certain threshold leads to an upward jump in provision probability. Above this threshold, provision probability gradually decreases as population grows. This allows two observations in the presence of social learning:  (i) There is a unique and finite population level that maximizes provision probability and (ii) The ``bystander effect" hinders provision only if the population is already large. A second result shows that the effect of effort cost on provision is ambiguous: A rise in cost can increase or decrease provision probability. 

Work in Progress

• Review versus Recommendation by an Influence Motivated Expert

Abstract. I investigate communication between an expert and consumers regarding the quality of a good. The expert is influence motivated: She prefers that the good is purchased if she gave it a positive review. I compare two cases: One where the expert can send both a positive or negative evaluation for the good (review), and one where she can either give a positive evaluation or say nothing (recommendation). I find that an expert who is allowed to send negative evaluations in addition to positive ones is followed with higher probability by the consumers if she is sufficiently unbiased (towards a particular action by the consumer). If she is sufficiently biased in favor of the product being purchased, this result is reversed: Allowing negative reviews decreases the influence of the expert on the action of the consumer.   

Economics Department, EUI

• TA: Decision and Game Theory (PhD Core Course-2018) (Student Evaluations: TA Section) (Student Evaluations: Complete)

School of Transnational Governance, EUI

• Instructor: Mathematics Boot Camp (MTnG-2020)

 Course Slides: (Calculus), (Probability), (Statistics)

• TA: Microeconomics 1 (MTnG-2020)