Advanced analytics: new methods and applications for macroeconomic policy

The Bank of England is hosting a virtual conference

About the conference

Date: 3 - 5 November 2021

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 was the latest in a series of events jointly organised by the Bank of England (BoE), the European Central Bank (ECB) and the Data Analytics for Finance and Macro Research Centre (DAFM) at King’s College London.

The conference aimed to connect leading researchers in academia and policy institutions to present and discuss the latest advances in the interdisciplinary field of advanced analytics. For example, how do these techniques best address pressing policy questions, and how do the resulting answers compare with conventional approaches? Could these novel approaches become the norm and how? We particularly focused on areas that apply advanced analytics techniques to the following topics:

  • monetary policy transmission, policy interactions, heterogeneous effects, communication
  • trade and capital flows networks, exchange rates
  • macroprudential and supervisory analysis and policy
  • assessing and addressing risks from shocks and structural economic change

Keynote speakers

  • Jesús Fernández-Villaverde (University of Pennsylvania)
  • Cynthia Rudin (Duke University)

Scientific Committee

  • Andrew Blake (BoE)
  • Mingli Chen (University of Warwick)
  • Lukas Henkel (ECB)
  • Andreas Joseph (BoE)
  • George Kapetanios (DAFM)
  • Christopher Kurz (Federal Reserve Board)
  • Michele Lenza (ECB)
  • Juri Marcucci (Banca d’Italia)
  • Chiara Osbat (ECB)
  • Fotis Papailias (DAFM)
  • Galina Potjagailo (BoE)
  • Diego Rodriguez Palenzuela (ECB)
  • Arthur Turrell (Office for National Statistics)
  • Session title/speaker Course presentation/recording of the day
    Vimeo links to Day 1 recordings Session 1
    Session 2
    Session 3
    Opening remarks
    Cornelia Holthausen, Deputy Director General Economics, European Central Bank

    Central bank communication with non-experts – a road to nowhere?
    Michael Ehrmann, European Central Bank
    Discussant: Conor Parle, Central Bank of Ireland
    Michael - slides
    Michael - paper
    Conor - slides
    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
    Michael - slides
    Armando - slides
    Armando - paper
    Deep reinforcement learning in a monetary model
    Andreas Joseph, Bank of England
    Discussant: Carlos Montes-Galdon, European Central Bank

    Andreas - slides
    Andreas - paper
    Carlos - slides

    The voice of monetary policy
    Tho Pham, University of Reading
    Discussant: Jonathan Benchimol, Bank of Israel
    Jonathan - slides
    Tho - slides
    Tho - paper
    Whatever it takes to understand a central banker – Embedding their words using neural networks
    Martin Baumgartner, THM Business School
    Discussant: Linda Shuku, King’s College London
    Linda - slides
    Martin - slides
    Martin - paper
    Poster session: Five facts about the distributional income effects of monetary policy
    Mathias Klein, Sveriges Riksbank
    Mathias - paper
    Poster session: The central bank crystal ball: temporal information in monetary policy communication
    Conor Parle, Central Bank of Ireland
    Conor - paper
    Poster session: Mark my words: the transmission of central bank communication to the general public via the print media
    Tim Munday, University of Oxford
    Tim - paper

  • Session title/speaker Course presentation/recording of the day

    Vimeo links to Day 2 recordings

    Keynote session 1
    Session 4
    Session 5

    Inequality and the zero lower bound
    Galo Nuno, Banco de Espania
    Discussant: Lilia Maliar, City University of New York

    Galo - slides
    Galo - paper
    Lilia - slides

    Keynote session 1: Don’t use black box machine learning models for high-stakes
    Cynthia Rudin, Duke University

    Cynthia - slides

    Forecasting social unrest: a machine learning approach
    Chris Redl, International Monetary Fund (covered by Sandile Hlatshwayo)
    Discussant: Martin Baumgartner, THM Business School

    Sandile and Chris - slides
    Sandile and Chris - paper
    Martin - slides

    Credit shocks and populism
    Nicolo Fraccaroli, Brown University
    Discussant: Tho Pham, University of Reading

    Nicolo - slides
    Nicolo - paper

    Poster session: Heteroskedasticity as a complementary identification strategy
    Tommaso Tornese, Queen Mary University of London

    Tommaso - paper

    Poster session: Learning to make consumption-saving decisions in a changing environment: an Al approach
    Aruhan Rui Shi, University of Warwick

    Aruhan - paper

    Poster session: Can machine learning change our opinion on Euler’s consumption model?
    Diana Gabrielyan, University of Tartu

    Diana - paper

    Poster session: Decoupling shrinkage and selection for the Bayesian quantile regression
    Tibor Szendrei, Heriot-Watt University

    Tibor - paper

  • Session title/speaker Course presentation/recording of the day

    Vimeo links to Day 3 recordings

    Keynote session 2
    Session 6
    Session 7

    Keynote session 2: Machine learning for macroeconomics
    Jesús Fernández-Villaverde, University of Pennsylvania

    Jesús - slides

    Does regulation only bite the less profitable? Evidence from the too-big-to-fail reforms
    Aakriti Mathur, Bank of England
    Discussant: Tim Munday, University of Oxford

    Aakriti – paper

    Inside the boardroom: evidence from the board structure and meeting minutes of community banks
    Paul Soto, Federal Deposit Insurance Corporation
    Discussant: Massimo Ferrari, European Central Bank

    Massimo - slides

    Macroeconomic predictions using payments data and machine learning
    Ajit Desai, Bank of Canada
    Discussant: Nicolas Woloszko, Organisation for Economic Co-ordination and Development

    Ajit - slides
    Ajit - paper
    Nicolas - slides

    Big data information and nowcasting: consumption and investment from bank transactions in Turkey
    Alvaro Ortiz, BBVA
    Discussant: Gianni Amisano, Federal Reserve Bank

    Alvaro - slides
    Alvaro - paper
    Gianni - slides

    Closing remarks
    Fotis Papailias, Deputy Director of Data Analytics for Finance and Macro (DAFM) Research Centre

    Fotis - slides

This page was last updated 10 January 2022

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