Research Summary

Microeconomics is about modeling the agents’ behavior. I strongly believe that models can help us to understand better human behavior, which has immense applications in the real world. I am interested in particular in the interaction of agents facing information asymmetries, in particular, Moral Hazard. I focus my research on finding new economic models that allow us to better understand the misbehavior of some Agents. In particular, I am working on finding new ways of understanding fraud.

I am also very interested in developing solutions for real-life problems using the Microeconomic Theory. Is in this part for example that I studied optimal bidding, and developed software to assist in the analysis of how the auction environment affects the bidding strategy adopted by the bidders. I am convinced that incorporating the economic techniques on modeling situations into daily basis applications can make a big difference in the performance of individuals, institutions, and companies.

Interests

  • Corporate Finance Theory
  • Contract Theory
  • Industrial Organization
  • Auctions

Work in Progress

  • Wealth and the Principal-Agent Matching (Job Market Paper)

    I study the problem of matching agents with principals, considering the moral hazard problem to study the effects the agent's wealth has in the market outcome.

    I study the role that the agent’s wealth plays in the principal-agent matching with moral hazard and limited liability. I consider wealth and talent as the agent’s type, and size as the firm’s (principal’s) type. Since utility is not perfectly transferable in this setup I use generalized increasing differences and find that wealthier agents indeed match with bigger firms, when talent is homogeneous among them, while for equally wealthy agents, more talented agents will match with bigger firms. I describe economic conditions over types such that pairs of higher types will write contracts in which the agent obtains more than the information rents, through a higher bonus, increasing the expected surplus. Finally, I provide an example in which wealth is distributed among agents in such a way that it reverses the standard result of positive assortative matching between talent and firm size.

  • Bidding in First Price Sealed Bid Auctions: A Computational Approach

    Joint with Prof. Ingemar Dierickx, we quantify the effects of different dimensions of heterogeneity among bidders in a First Price Sealed Bid auction, by using computer simulations.

    Computational methods are used to analyze bidding in first price sealed bid auctions for a broad range of realistic scenarios. Bidders valuations may have both common value and firm-specific components, and the accuracy of their estimates of the common value component may differ. In addition, we allow for a subset of “naive” bidders, defined as bidders who do not account for the Winners Curse. We find that, when estimates are independently distributed, bids can be determined by applying a constant Shading Factor that can be computed ex-ante of receiving a signal. Our computations confirm that these bids are very sensitive to asymmetries in the bidding population and, in particular, to the presence of naive bidders. Assuming that a rival is rational when in fact he is naive results in underbidding when facing that rival only and in overbidding in all other cases.
  • Hunting with two bullets

    In a standard Moral Hazard setup, I study what happens if the Agent can fix the outcome privately before reveal it to the Principal.

    I study the moral hazard problem where an agent can create an extra instance to exert effort, and potentially improve bad realizations of the outcome before the principal observes it. Here the agent cannot hide the outcome of his effort, but just the way he achieved it. I find that both, principal and agent, value the option of improving the outcome in case of a bad realization if doing so is cheap. I also find that, under asymmetric information, that contracted effort is not always decreasing in its cost, and that the principal will demand higher returns in order to contract high effort in every period when compared to the first best. Finally, I let the principal to eliminate, by using deadlines, the agent’s extra chance. I find that, under a broad range of scenarios, the principal will shorten deadlines if preventing an agent’s deviation from the first bests strategy is too expensive.