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
Econometrics Seminar - Lorenzo Magnolfi (Wisconsin)
Title: Market Counterfactuals with Nonparametric Supply: An ML/AI Approach (with Harold Chiang, Jack Collison, and Chris Sullivan).
Abstract: This paper develops a flexible approach to perform market counterfactuals using machine learning methods and nonparametric structure from economics. While standard structural methods rely on restrictive assumptions about firm conduct and cost, we propose a data-driven framework that relaxes these constraints when rich market data are available. Building on the identification results of Berry and Haile (2014) we develop a nonparametric model of supply that nests traditional conduct specifications while allowing for more complex competitive interactions. We adapt the Variational Method of Moments (VMM) (Bennett and Kallus, 2023) to estimate this flexible model, addressing the endogeneity of market shares and the high dimensionality of the problem. Our approach enables a wide range of counterfactual exercises including tax policy analysis, product regulation, and merger simulation. Monte Carlo simulations demonstrate that our method substantially outperforms standard approaches; applied to the American Airlines-US Airways merger, our method produces more accurate post-merger price predictions.