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 - Patrick Gagliardini (Lugano)
Title: Eigenvalue tests for the number of latent factorsin short panels
Alain-Philippe Fortin, Patrick Gagliardini, Olivier Scaillet
This paper studies new tests for the number of latent factors in a large cross-sectionalfactor model with small time dimension. These tests are based on the eigenvalues ofvariance-covariance matrices. We establish the asymptotic distributional results usingexpansion theorems based on perturbation theory for symmetric matrices. Our frame-work accommodates semi-strong factors in the systematic components. We propose anovel statistical test for weak factors against strong or semi-strong factors. We providean empirical application to US equity data. Evidence for a dierent number of latentfactors according to market downturns and market upturns, is statistically ambiguous.In particular, our results contradicts the common wisdom of a single factor model inbear markets