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 - Pascquale Schiraldi (LSE)
Title: Identification of Intertemporal Preferences From Choice Set Variation
Abstract: The paper provides conditions to identify the discount factor(s) and utility function in an infinite-horizon dynamic discrete choice model variation in choice sets over time. We show that if current choices or states are informative about the choice set the agent will face in the future, then the discount factor and utility are identified without any strong normalization. These identification results hold in both the exponential discounting model and, if the choice set provides a form of pre-commitment, the quasi-hyperbolic discounting model. Identifying the discount factor and utility allows us to identify the counterfactual policies which often are the objects of interest in dynamic discrete-choice analysis, but which are not generally identified. We conduct a data analyses to validate our approach.