Advanced analytics: new methods and applications for macroeconomic policy
Online event
Advanced analytics techniques, such as the analysis of novel large and unstructured data sources or the application of techniques from machine learning and artificial intelligence, offer new insights into problems in economics and finance. These approaches have now found their way into broad-based research programmes in academia and policy institutions. This conference is the latest in a series of events jointly organised by the Bank of England, the European Central Bank and the Data Analytics for Finance and Macro Research Centre (DAFM) at King’s College London.
Programme
Times are Coordinated Universal Time, UTC (CET-1)
* indicates the presenter
- 12:30
- Online registration
- 13:00
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Welcome
Paul Robinson, Head of Advanced Analytics, Bank of England
- 13:05
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Opening remarks
Cornelia Holthausen, Deputy Director General Economics, European Central Bank
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Session 1 chaired by Fotis Papailias, King’s College London
- 13:15
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Central bank communication with non-experts – a road to nowhere?
- Michael Ehrmann*, European Central Bank
- Alena Wabitsch, University of Oxford
Discussant: Conor Parle, Central Bank of Ireland
- 14:00
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The ECB’s tracker: nowcasting the press conferences of the ECB
Armando Marozzi, London School of Economics and Political Science
Discussant: Michael Ehrmann, European Central Bank
- 14:45
- Break
Session 2
- 15:15
Deep reinforcement learning in a monetary model
- Andreas Joseph*, Bank of England
- Mingli Chen, University of Warwick
- Michael Kumhof, Bank of England
- Xinlei Pan, University of California, Berkeley
- Rui Shi, University of Warwick
- Xuan Zhou, Deakin University
Discussant: Carlos Montes-Galdon, European Central Bank
- 16:00
Poster Session I (virtual booths)
- 16:45
- Break
Session 3 chaired by Francesca Monti, UCLouvain
- 17:00
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The voice of monetary policy
- Tho Pham*, University of Reading
- Yuriy Gorodnichenko, University of California, Berkeley
- Oleksandr Talavera, University of Birmingham
Discussant: Jonathan Benchimol, Bank of Israel
- 17:45
Whatever it takes to understand a central banker – Embedding their words using neural networks
- Martin Baumgärtner*, THM Business School
- Johannes Zahner, Philipps-Universität Marburg
Discussant: Linda Shuku, King’s College London
- End of day 1
- 12:30
- Online registration
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Session 4 chaired by Sholthana Begum, Bank of England
- 13:00
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Inequality and the zero lower bound
- Galo Nuño*, Banco de España
- Jesús Fernández-Villaverde, University of Pennsylvania, NBER and CEPR
- Joël Marbet, CEMFI
- Omar Rachedi, ESADE Business School
Discussant: Lilia Maliar, City University of New York
- 13:45
Poster Session II (virtual booths)
- 14:30
- Break
Keynote 1 chaired by Chiara Osbat, European Central Bank
- 15:00
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Almost matching exactly for observational causal inference
Cynthia Rudin, Duke University
- 16:00
- Break
Session 5 chaired by Christopher Kurz, Board of Governors of the Federal Reserve System
- 16:30
Forecasting social unrest: a machine learning approach
- Chris Redl*, International Monetary Fund
- Sandile Hlatshwayo, International Monetary Fund
Discussant: Martin Baumgärtner, THM Business School
- 17:15
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Credit shocks and populism
- Nicolò Fraccaroli*, Brown University
- Alessandro Pizzigolotto, Norwegian School of Economics
Discussant: Tho Pam, University of Reading
- End of day 2
- 12:30
- Online registration
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Keynote 2 chaired by Andreas Joseph, Bank of England
- 13:00
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Machine learning for macroeconomics
Jesús Fernández-Villaverde, University of Pennsylvania
- 14:00
- Break
Session 6 chaired by David Aikman, King’s College London
- 14:30
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Does regulation only bite the less profitable? Evidence from the too-big-to-fail reforms
- Aakriti Mathur*, Bank of England
- Tirupam Goel, Bank for International Settlements
- Ulf Lewrick, Bank for International Settlements
Discussant: Tim Munday, University of Oxford
- 15:15
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Inside the boardroom: evidence from the board structure and meeting minutes of community banks
- Paul Soto*, Federal Deposit Insurance Corporation
- Rosalind Bennett, Federal Deposit Insurance Corporation
- Manju Puri, Duke University and NBER
Discussant: Massimo Ferrari, European Central Bank
- 16:00
- Break
Session 7 chaired by Nick Bate, Bank of England
- 16:30
Macroeconomic predictions using payments data and machine learning
- Ajit Desai*, Bank of Canada
- James Chapman, Bank of Canada
Discussant: Nicolas Woloszko, Organisation for Economic Co-operation and Development
- 17:15
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Big data information and nowcasting: consumption and investment from bank transactions in Turkey
- Alvaro Ortiz*, BBVA Research
- Ali B. Barlas, BBVA Research
- Seda Guler Mert, BBVA Research
- Berk Orkun Isa, BBVA Research
- Tomasa Rodrigo, BBVA Research
- Baris Soybilgen, Bilgi University
- Ege Yazgan, Bilgi University
Discussant: Gianni Amisano, Board of Governors of the Federal Reserve System
- 18:00
Closing remarks
George Kapetanios, Director of Data Analytics for Finance and Macro (DAFM) Research Centre
Audiovisual notice: Images and video recordings may be published online
Please note that this programme may be subject to change without notice.
Poster Session I
3 November, 16:00-16:45
Mark my words: the transmission of central bank communication to the general public via the print media
Tim Munday*, University of Oxford, and James Brookes, Bank of England
The central bank crystal ball: temporal information in monetary policy communication
Conor Parle*, David Byrne and Robert Goodhead, all Central Bank of Ireland, and Michael McMahon, University of Oxford
Does central bank talk matter for forecasting? Evidence from untargeted speeches of the BoE, Fed, and ECB
Linda Shuku* and Fotis Papailias, both King’s College London
Five facts about the distributional income effects of monetary policy
Anna Rogantini Picco*, Niklas Amberg, Thomas Jansson and Mathias Klein, all Sveriges Riksbank
E pluribus pluribus. Shock dependency of the USD pass-through to real and financial variables
Massimo Ferrari* and Johannes Gräb, both European Central Bank
Poster Session II
4 November, 13:45-14:30
Learning to make consumption-saving decisions in a changing environment: an AI approach
Aruhan Rui Shi, University of Warwick
Can machine learning change our opinion on Euler’s consumption model?
Diana Gabrielyan, University of Tartu
Interpretability and explainability – nonlinear, non-parametric and time-varying equity risk premia
Felix Kempf* and Georg Kapetanios, both King’s College London
Decoupling shrinkage and selection for the Bayesian quantile regression
Tibor Szendrei* and David Kohns, both Heriot-Watt University
Heteroskedasticity as a complementary identification strategy
Tommaso Tornese* and Andrea Carriero, both Queen Mary University of London, and Massimiliano Marcellino, Bocconi University