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Bank of England Modelling with Big Data and Machine Learning

Event Date: 26-11-2018
Duration: 08.30 - 18.00

The confluence of expanding access to data and the rapid advance of modelling techniques like those from machine learning promise new insights into the economy and a larger information set for policymakers. The Bank of England (BoE), the Data Analytics for Finance and Macro (DAFM) Research Centre at King’s College London and the Federal Reserve Board (FRB) are holding a two-day workshop to discuss recent advances in modelling the economy using big data and novel modelling approaches. 

We invite you to submit empirical, methodological or theoretical work leveraging on new granular data sources or exploring recent analytical development to analyse the macroeconomy in the near or medium term. The workshop aims to provide an opportunity to discuss recent scientific advances, as well as to connect with policy makers and academics. 

We invite submissions from a range of topics covering

  • Large granular structured or unstructured data sources (administrative data, web data, from the “digital exhaust”, text data)
  • Machine Learning for prediction and understanding the economy
  • Methods (matching, filtering or cleaning techniques)
  • Theory (modelling, estimation with many covariates or strong non-linearities)
  • Big data topics covering businesses, households, finance, labour markets or government.

Confirmed keynote speakers and panellists are

  • Domenico Giannone, Federal Reserve Bank of New York
  • Andrew Haldane, Chief Economist, Bank of England

The deadline for submissions is 19 August 2018. Upon submission, please indicate if you would be available to discuss another paper within your field of expertise. Please submit your full paper to Full papers are preferred but extended abstracts will be accepted in exceptional cases. Final decisions will be made by 21 September 2018. For questions regarding event logistics please contact and 

Bank of England Modelling with Big Data and Machine Learning

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