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
CAGE-AMES Workshop - Jian Xie
Title: Investments, Connections, and Innovation: Evidence from Chinese Artificial Intelligence Startups
Author: Jian Xie and Kang Zhou
Abstract: Large technology firms have advantages in new technologies such as Artificial Intelligence, due in part to data and network effects. For Artificial Intelligence (AI) startups, investments by these large technology firms could be more effective at increasing innovation than investments by firms without the same data and network advantages. We use a staggered difference-in-difference approach to show that Chinese AI startups innovate more after they receive direct investments from large technology firms. These startups increase their AI technology output, as measured by both AI-related patent applications and registered software. Using a triple-difference approach, we show that the impacts of investments from large technology firms are more pronounced than those from venture capital firms and other investors. We confirm these findings using an instrumental variables approach based on previous investments by large technology firms in peer startups. Our evidence suggests that investments by data-rich technology firms shape AI innovation by startups and contribute to the rise of AI industry.
This workshop is via MS Teams, click here to join the meeting.