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 Workshop - Ao Wang (Warwick)
Title: Identification and (Fast) Estimation of Nonlinear Panel Models with Additively Separable Two-Way Fixed Effects, with Martin Mugnier (CREST)
Abstract: In this paper, we study the identification and fast estimation of a class of nonlinear panel models with additively separable two-way fixed effects widely used in empirical research. We propose a novel identification strategy and show that all structural parameters of the model (heterogeneous slopes, individual/time fixed effects, and link function) can be nonparametrically identified when T is large. We propose a novel iterative procedure to implement the routinely used MLE. This procedure fully parallelizes the updates of the estimates of individual/time fixed effects. This feature largely alleviates computational burdens when the dataset is large and delivers precise estimates using only fractional running time in the presence of a large number of fixed effects. We revisit Aghion et al. (2013) and investigate the causal effect of institutional ownership on firm innovation in the US. Allowing firms to react differently to institutional ownership changes, the estimates obtained by using our method suggest non-negligible heterogeneity in the causal effect, partly explained by the “Superstar Firm Hypothesis”.