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"


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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