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SIES Tackles Behavioral Economics

The two presenters on the second day of the SIES were Dr. Jean-Pierre Benoît (London Business School) and Dr. Roberto Sarkisian (Toulouse School of Economics), who presented respectively “The Role of Theory in Understanding Behavioural Experiments” and “Introduction to Market Design and Two-sided Matching Theory.

The first lecture examined the statistical modeling of “Overconfidence.”  The lecture opened with a brief overview of the pioneering article entitled “Are we all less risky and more skillful than our fellow drivers?”, authored by psychologist Ola Svenson (1981). After establishing Svenson’s thesis that people tend to rank themselves as “Better Than Average” (BTA), Dr. Jean Pierre Benoît questioned Svenson’s findings and broke down the idea of overconfidence into three categories: “Overestimation,” “Overprecision” and “Overplacement”. Employing an accurate and more precise experimental game, Benoît discovered a Bayesian equilibrium, indicating that BTA does not imply that people are overconfident—rather, because people are over-ranking themselves, a more accurate term is “Overplacement.”

The second lecturer, Dr. Roberto Sarkisian, covered many topics within matching with non-transferable utility. He worked with the DA Algorithm, an algorithim that allows suppliers’ preferences to be efficiently matched to more suitable candidates who are willing to apply. He began with a simple model, employing the example of student matching with colleges. Continuing with this example, Sarkisian generalized the model to be employed for the example of an applicant matching with employment options in the job market. He also discussed how a stable matching exists both in one-to-one and in many-to-one matching markets. This unified framework highlighted the connection between two important views of market design, namely auction and matching theories. Both lectures were followed by lively Q&A sessions.

Pictured Above: Jean-Pierre Benoît’s lecture. Below, Roberto Sarkisian responds to questions.