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
CAGE-AMES Workshop - Adam Di Lizia (PGR)
Title: The Anatomy of Online Reviews: Evidence of Self-Selection from the Steam Store.
Abstract How good are reviews as signals of product quality for consumers? Using a data-set derived from the popular `Steam' gaming platform I investigate the self-selection of reviewers. A policy reform on Steam in 2019 both lowered the transaction cost of reviewing, with this randomly occurring within a game and reviewer's life cycle. I find that the new individuals elicited to review by the policy change are 4\% more likely to rate any game positively, leave 15\% shorter reviews and are less experienced both within and across games. This selection is heterogeneous across games, greatly affecting their rank order and while some sellers benefitted from the increase in selection, others did not. Overall, the policy reduced selection bias and improved the consumer's information set, but new reviewers were rated as less helpful by their peers, implying that more accurate review scores come at the cost of less helpful reviews.