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Eeva Mauring

I am an applied microeconomic theorist with main interests in theoretical industrial organisation and choice theory. My current research extends search theory in two directions. In my job market paper, I study decentralized search markets where agents learn about market conditions from data on frequency of trading. In two other projects, I revisit the standard sequential search model of individual choice, where decision-makers are restricted by either their own limitations or by having to account for others' preferences.

  • Microeconomic theory
  • Industrial organisation
  • Choice theory

"Learning from Trades"

Abstract

Buyers learn about the distribution of options on the market from many types of information. This paper analyses the efficiency of various information regimes in a dynamic market model with pairwise meetings where buyers face an unknown distribution of options. I show that, contrary to the intuition that more information leads to greater market efficiency, a market where buyers learn about the unknown distribution from a private signal with an equilibrium-determined precision ("trade signal") may be less efficient than a market where buyers do not receive this signal. The trade signal reveals to a buyer whether a randomly chosen seller traded in the previous period. In equilibrium, observing that the seller traded is good news about the unknown distribution. In contrast to the trade signal, a market where buyers learn from a private signal with a suitable exogenously given precision is more efficient than both a market where buyers do not receive a signal and a market where buyers know the distribution of options.

  • Prof Rani Spiegler (Tel Aviv University and University College London)
  • Prof Martin Cripps (University College London)
  • Prof Jan Eeckhout (University College London and Barcelona GSE-UPF)
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