BIg Data, Machine Learning, and the Macroeconomy

Coming soon at Bank of Norway:

CALL FOR PAPERS 
Big data, machine learning and the macroeconomy 
Norges Bank, Oslo, 2-3 October 2017 

Data, in both structured and unstructured form, are becoming easily available on an ever increasing scale. To find patterns and make predictions using such big data, machine learning techniques have proven to be extremely valuable in a wide variety of fields. This conference aims to gather researchers using machine learning and big data to answer challenges relevant for central banking. 

Examples of questions, and topics, of interest are: 

Forecasting applications and methods
-Can better predictive performance of key economic aggregates (GDP, inflation, etc.) be achieved by using alternative data sources? 
- Does the machine learning tool-kit add value to already well-established forecasting frameworks used at central banks? 

 Causal effects
- How can new sources of data and methods be used learn about the causal mechanism underlying economic fluctuations? 

Text as data
- Communication is at the heart of modern central banking. How does this affect markets? 
- How can textual data be linked to economic concepts like uncertainty, news, and sentiment? 

Confirmed keynote speakers are: 
- Victor Chernozhukov (MIT) 
- Matt Taddy (Microsoft, Chicago Booth) 

The conference will feature 10-12 papers. If you would like to present a paper, please send a draft or an extended abstract to mlconference@norges-bank.no by 31 July 2017. Authors of accepted papers will be notified by 15 August. For other questions regarding this conference, please send an e-mail to mlconference@norges-bank.no. Conference organizers are Vegard H. Larsen and Leif Anders Thorsrud.