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
Applied Economics, Econometrics & Public Policy (CAGE) Seminar - Johannes Spinnewijn (LSE)
Title: Predicting Long-term Unemployment Risk - Andreas Mueller (UT Austin) & Johannes Spinnewijn (LSE)
Abstract: This paper uses rich administrative and survey data from Sweden to study the predictability and determinants of long-term unemployment (LTU) over the period 1992-2016. We use standard machine learning techniques to predict job seekers' LTU risk and find substantial predictable heterogeneity. Compared to a model using standard socio-demographic variables, a comprehensive model that uses data on income, employment and benefit histories more than doubles the predictive power. The estimated heterogeneity in LTU risk implies that at least two thirds of the observed duration dependence in job finding is driven by dynamic selection. We apply our prediction algorithm over the business cycle and find significant heterogeneity underlying the cyclicality in average LTU risk, while the role of composition effects is limited. We evaluate the implied value of targeting unemployment policies and how this changes over the business cycle.