Modelling with Big Data & Machine Learning: Measuring Economic Instability - Call For Papers Extended Deadline
The confluence of access to large granular data sources (‘Big Data’) and the rapid advance of modelling techniques like those from machine learning promises 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 have recently initiated a series of annual scientific conferences to discuss these advances and how they pertain to Measuring Economic Instability.
The Coronavirus pandemic and the widespread economic downturn in the wake of the resulting ‘lockdown’ in many countries have spurred an unprecedented output of research in multiple disciplines. This research is serving as a vital guide to policymakers in governments, central banks and international institutions around the globe as events unfold. Crucial roles in this information gathering and evaluation process are played by novel high-frequency and low-latency data sources, as well as non-conventional modelling techniques like machine learning, artificial intelligence, and interdisciplinary approaches such as those from epidemiology and economics. The conference aims to provide an opportunity to discuss recent scientific advances, especially with a focus on aiming at quantifying potentially rapid economic fluctuations, and to connect policy makers and academia.
We invite you to submit empirical, methodological or theoretical work leveraging on new granular data sources or exploring recent analytical development relevant to decision making. We note that submissions do not have to be explicitly about Covid-19 but should be relevant for the assessment of large economic and financial shocks, ideally applicable in the current situation
Confirmed keynote speakers:
Kathy Yuan (LSE)
Rama Cont (Oxford)
Martin Weidner (UCL)
The event will be hosted virtually, including the presentation and discussion of accepted papers and posters, as well as chances to mingle (precise format TBD). The submission deadline is 21 September (please email to email@example.com). Preference will be given to full papers but extended abstracts will be considered in exceptional circumstances. Authors of accepted papers will be notified by 11 October. Full papers should be made available no later than two weeks before the conference. For questions regarding event logistics please contact firstname.lastname@example.org and email@example.com. Please note that we aim to record the event and share material externally.
· Andrew Blake (BoE) · Mingli Chen (University of Warwick) · Stephen Hansen (Imperial Business School) · Andreas Joseph (BoE & DAFM) · George Kapetanios (Committee Chair, King’s College London; DAFM) · Christopher Kurz (Federal Reserve Board) · Juri Marcucci (Bank of Italy) · Fotis Papailias (King’s College London, DAFM) · Galina Potjagailo (BoE) · Chris Redl (IMF & DAFM)
21 September: Submission deadline
11 October: Author notification
22 October: Final paper submission
4 - 6 November: Conference