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
Monday, May 22, 2023
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Economic History Seminar - Martin Fiszbein (Boston U)S2.79 |
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Econometrics - Jasmin Fliegner (Manchester)S2.79The title of the talk is: How Biased are Observational Methods in Practice? Accumulating Evidence Using Randomised Controlled Trials with Imperfect Compliance, joint with David Rhys Bernard, Gharad Bryan, Sylvain Chabé-Ferret, Jon de Quidt and Roland Rathelot. The abstract: Consider a policy maker choosing between programs of unknown impact. She can inform her decision using observational methods, or by running a randomised controlled trial (RCT). The proponents of RCTs would argue that observational approaches suffer from bias of an unknown size and direction, and so are uninformative. Our study treats this as an empirical claim that can be studied. By doing so we hope to increase the value of observational data and studies, as well as better inform the choice to undertake RCTs. We propose a large-scale, standardised, hands-off approach to assessing the performance of observational methods. First, we collect and categorise data from a large number of RCTs in the past 20 years. Second, we implement new methods to understand the size and direction of expected bias in observational studies, and how bias depends on measurable characteristics of programmes and settings. We find that the difference between observational estimators and the experimental benchmark is on average zero, but the resulting observational bias distribution has high variance. |