Applied Microeconomics
Applied Microeconomics
The Applied Microeconomics research group unites researchers working on a broad array of topics within such areas as labour economics, economics of education, health economics, family economics, urban economics, environmental economics, and the economics of science and innovation. The group operates in close collaboration with the CAGE Research Centre.
The group participates in the CAGE seminar on Applied Economics, which runs weekly on Tuesdays at 2:15pm. Students and faculty members of the group present their ongoing work in two brown bag seminars, held weekly on Tuesdays and Wednesdays at 1pm. Students, in collaboration with faculty members, also organise a bi-weekly reading group in applied econometrics on Thursdays at 1pm. The group organises numerous events throughout the year, including the Research Away Day and several thematic workshops.
Our activities
Work in Progress seminars
Tuesdays and Wednesdays 1-2pm
Students and faculty members of the group present their work in progress in two brown bag seminars. See below for a detailed scheduled of speakers.
Applied Econometrics reading group
Thursdays (bi-weekly) 1-2pm
Organised by students in collaboration with faculty members. See the Events calendar below for further details
People
Academics
Academics associated with the Applied Microeconomics Group are:
Research Students
Events
CRETA Seminar - Ian Ball (MIT)
Title: Quota Mechanisms: Limitations and Robustness (with Deniz Kattwinkel).
Abstract: Quota mechanisms are commonly used within organizations to elicit private information when agents face multiple decisions and monetary transfers are infeasible. As the number of decisions grows large, quotas asymptotically implement the same set of social choice rules as do monetary transfers. We analyze the robustness of quota mechanisms to misspecified beliefs. To set the correct quota, the designer must have precise knowledge of the environment. We show that only trivial social choice rules can be implemented by quota mechanisms in a prior-independent way. Next, we bound the error that results when the quota does not match the true type distribution. Finally, we show that in a multi-agent setting, quotas are robust to misspecification of the agents' beliefs about each other. Crucially, the quota makes the distribution of reports common knowledge.