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I am an Associate Professor of Economics at IESE Business School. My main area of research is information economics. I focus mainly on three different areas:

  1. Social learning and learning dynamics. “Social learning” refers to the inferences we draw from the information of others based on observing their opinions and behavior. There are two ways of modeling how inferences are made:

          In a fully rational, Bayesian manner

          In a boundedly rational manner relying on simple heuristics or algorithms

 

My research addresses the following questions for both rational and boundedly rational social learning:

  • How do behavior and opinions evolve when individuals interact in dynamic environments?
  • When does herding behavior — in which individuals eventually exhibit a uniformity of behavior or opinions — arise?
  • When are herds correct given the aggregate private information?
  • To what extent is the evolutionary trajectory of collective, social learning-based societal behavior vulnerable to misinformation and manipulation?

I also work on questions related to the design of optimal boundedly rational learning algorithms in dynamic environments where Bayesian learning is not applicable either due to its inherent computational complexity or the lack of sufficient knowledge of the underlying information structure.

 

  1. Information elicitation. Regarding information elicitation, I focus on two types of questions: 

          To what extent does the nature of an individual’s decision problem — a situation in which an individual must make a choice under uncertainty – impact the inferences we make about her underlying information based on her choice?

         How are mechanisms which incentivize individuals or groups to truthfully reveal their private information designed?

 

  1. Information aggregation. “The wisdom of the crowd” is a long-held philosophical principle dating back at least to Aristotle (if not even earlier). This boils down to the idea that even though some event may be uncertain, and though the information each individual has may be noisy, the aggregate of individual beliefs is accurate.

         But absent knowledge of how individual beliefs are generated, how can we aggregate the beliefs to achieve “the wisdom of the crowd”?

         I study the design of simple mechanisms that achieve aggregation in unspecified information environments where the mechanism designer has  no knowledge of the information’s structure.

 

I teach Global Economics — a class on the global economy with a macroeconomic focus — in IESE’s MBA, Executive MBA, Executive Education, and custom programs. I also teach Managerial Economics in the Master in Management program, a course concerned with the application of economic principles to key management decisions.