The “big data” revolution has already major implications for businesses and policymakers around the globe. The rapid advances in data quality and computing power will also have profound effects on economic research. Large-scale datasets by governments and the private sector offer countless new opportunities to measure and analyze economic activity. At the same time, this strand of research remains in its infancy. How can economists take full advantage of the new resources this field has to offer?
This summer school invites leading researchers that use big data and machine learning methods in macroeconomics and finance and has two main aims. First, to teach participants state of the art methods in big data analysis and machine learning and, second, to present how these methods can be applied to address big and relevant economic questions.
Stephen Hansen (Oxford)
Theresa Kuchler (New York University)
Michele Modugno (Fed)
Johannes Stroebel (New York University)
Adam Storeygard (Tufts)
The Summer School is targeted at graduate (MA or PhD) students and Post-docs with a strong academic record and a keen interest in policy issues, as well as staff members of policy institutions. The size of the group is limited to approx. 25 participants. The schedule will allow for plenty of opportunities to engage in debates and discuss research ideas with faculty and fellow participants.
The registration fee to attend the summer school is € 720 for graduate students and post-docs and € 1,680 for staff members of policy institutions and all other participants. The fee includes full board (breakfast-lunch-dinner included) and accommodation at the guest house of the Kiel Institute. Participants need to make their own travel arrangements and cover their travel costs. Accepted participants are required to stay for the entire week.
Please visit our webpage for additional information.https://www.ifw-kiel.de/events-1/kiel-institute-summer-school-on-economic-policy
Kiellinie 66, 24105 Kiel
Kiel , Germany