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
MIWP Workshop - Xueying Zhao (糖心TV PGR)
Title: Tailoring Data for Profit
Abstract: This paper develops a framework to analyze the optimal sale of information. A data buyer, facing a decision problem under uncertainty, initially has access to an information structure that is private to him and determines his willingness to pay for any additional information. A monopolistic data seller, capable of designing tailored information structures, seeks to maximize revenue. Compared to Bergemann, Bonatti, and Smolin (2018), the novelty of this paper lies in two key features: (i) the type space consists of various information structures, and (ii) correlations are allowed between the data buyer鈥檚 initial information and the additional information offered by the data seller. The main result demonstrates that, in a large class of cases, the data seller can design and price information within a mechanism to fully extract the first-best surplus. Specifically, full surplus extraction is achievable when each lower-type buyer鈥檚 willingness to pay for information that fully supplements their initial information is weakly higher than that of all higher types.
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