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
MIEW (Macro/International Economics Workshop) - Anshumaan Tuteja (PGR)
Title: What explains the stock market’s response to QE policy?
Abstract: This paper analyses the effects of Quantitative easing (QE) on the US stock market by decomposing the S&P500 index into two components, its risk-neutral fundamental value, and the equity premium. The causal effects of QE are identified by using an instrumental variable (IV) that is based on high-frequency price revisions of the medium-long end of the yield curve, triggered by Federal Open Market Committee (FOMC) policy announcements. Stylized facts indicate that these price revisions are correlated with information and risk premia shocks, potentially biasing the dynamic effects of QE policy. The IV is constructed by controlling for such non-monetary shocks using a novel two step approach. Findings from a Structural Vector Autoregression (SVAR) model suggest that a QE policy shock increases the stock index, due to a rise in the risk-neutral fundamental component and a fall in the equity premium component. Both components display persistence, with the equity premium response declining gradually over a period of two years. This confirms QE’s ability to compress risk premium in stock markets.