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
CWIP (CAGE Work in Progress) Workshop - Ludovica Gazze
Title: People, places or houses? A decomposition of households' carbon emissions in the UK (with Lucie Gadenne, Peter Levell, Davide Sansone)
Abstract: Understanding the determinants of households' greenhouse gases (GHG) emissions is key to designing successful decarbonization policies. We examine the role of household, house, and place in explaining household GHG emissions from transport and energy in the UK. Using detailed household panel data on housing characteristics enables us to speak to the determinants of both household and place effects and investigate the effects of different policy scenarios (e.g., revenue recycling from carbon taxes). We exploit the panel dimension of our data using a "mover design" approach to disentangle contextual factors, such as place-based drivers of emissions and house characteristics, from household-level determinants.