Machine Learning for Economics and Econometrics
Increasingly large, complex and nonstandard datasets have become widely available. This trend has triggered the development and proliferation of an interdisciplinary body of applied and theoretical work, commonly coined as 'machine learning', in all fields of science. The fields of economics and econometrics are no exception.
This workshop explores how such methods perform and are used in a variety of economic environments characterized by multiple sources of heterogeneity, high-dimensionality of covariates, complex dependence structure and/or time instability.
|10:00-10:30||Registration and Refreshments|
Keynote Talk: Serena Ng (Columbia):
|11:30 - 12:15||Michael Mcmahon (Oxford):|
"Policymakers Uncertainty" (joint with Anna Cieslak and Stephen Hansen)
|12:15 - 13:30||Lunch|
|13:30 - 14:15|
Svetlana Bryzgalova (LBS):
Dimitris Korobilis (Essex):
Elena Manresa (NYU):
Anders Kock (Oxford):
Speakers’ Dinner at Euromast (by invitation only)
Deadline for the registration is 24 May 2019. The registration is closed.