Application of Artificial Intelligence and Machine Learning in the Conduct of Monetary Policy by Central Banks
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Azqueta-Gavaldon, Andres & Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2019. "Sources of economic policy uncertainty in the euro area: a machine learning approach," Economic Bulletin Boxes, European Central Bank, vol. 5.
- Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2021.
"Deep Neural Networks for Estimation and Inference,"
Econometrica, Econometric Society, vol. 89(1), pages 181-213, January.
- Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
- Sebastian Doerr & Leonardo Gambacorta & José María Serena Garralda, 2021. "Big data and machine learning in central banking," BIS Working Papers 930, Bank for International Settlements.
- Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022.
"Making text count: Economic forecasting using newspaper text,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
- Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
- Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020.
"Empirical Asset Pricing via Machine Learning,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
- Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
- Carlo Altavilla & Miguel Boucinha & José-Luis Peydró & Frank Smets, 2019.
"Banking Supervision, Monetary Policy and Risk-Taking: Big Data Evidence from 15 Credit Registers,"
Working Papers
1137, Barcelona School of Economics.
- Carlos Altavilla & Miguel Boucinha & José-Luis Peydró & Frank Smets, 2019. "Banking supervision, monetary policy and risk-taking: Big data evidence from 15 credit registers," Economics Working Papers 1684, Department of Economics and Business, Universitat Pompeu Fabra, revised Dec 2020.
- Altavilla, Carlo & Boucinha, Miguel & Peydró, José-Luis & Smets, Frank, 2020. "Banking supervision, monetary policy and risk-taking: big data evidence from 15 credit registers," Working Paper Series 2349, European Central Bank.
- Altavilla, Carlo & Boucinha, Miguel & Peydró, José-Luis & Smets, Frank, 2020. "Banking Supervision, Monetary Policy and Risk-Taking: Big Data Evidence from 15 Credit Registers," EconStor Preprints 216793, ZBW - Leibniz Information Centre for Economics, revised 2020.
- Altavilla, Carlo & Boucinha, Miguel & Peydró, José-Luis & Smets, Frank, 2020. "Banking Supervision, Monetary Policy and Risk-Taking: Big Data Evidence from 15 Credit Registers," CEPR Discussion Papers 14288, C.E.P.R. Discussion Papers.
- Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
- Leif Anders Thorsrud, 2020.
"Words are the New Numbers: A Newsy Coincident Index of the Business Cycle,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 393-409, April.
- Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Paper 2016/21, Norges Bank.
- Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Papers No 4/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016.
"Measuring Economic Policy Uncertainty,"
The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2015. "Measuring Economic Policy Uncertainty," NBER Working Papers 21633, National Bureau of Economic Research, Inc.
- Baker, Scott R. & Bloom, Nicholas & Davis, Steven J., 2015. "Measuring economic policy uncertainty," LSE Research Online Documents on Economics 64986, London School of Economics and Political Science, LSE Library.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2015. "Measuring Economic Policy Uncertainty," CEP Discussion Papers dp1379, Centre for Economic Performance, LSE.
- Davis, Steven & Bloom, Nicholas & Baker, Scott, 2015. "Measuring Economic Policy Uncertainty," CEPR Discussion Papers 10900, C.E.P.R. Discussion Papers.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2015. "Measuring Economic Policy Uncertainty," Economics Working Papers 15111, Hoover Institution, Stanford University.
- Cai, Jian & Eidam, Frederik & Saunders, Anthony & Steffen, Sascha, 2018. "Syndication, interconnectedness, and systemic risk," Journal of Financial Stability, Elsevier, vol. 34(C), pages 105-120.
- Jeremy Fouliard & Michael Howell & Hélène Rey & Vania Stavrakeva, 2020.
"Answering the Queen: Machine Learning and Financial Crises,"
NBER Working Papers
28302, National Bureau of Economic Research, Inc.
- Jérémy Fouliard & Michael Howell & Hélène Rey, 2021. "Answering the Queen: Machine learning and financial crises," BIS Working Papers 926, Bank for International Settlements.
- Fouliard, Jeremy & Howell, Michael & Rey, Hélène & Stavrakeva, Vania, 2022. "Answering the Queen: Machine Learning and Financial Crises," CEPR Discussion Papers 15618, C.E.P.R. Discussion Papers.
- Ehrmann, Michael & Talmi, Jonathan, 2020.
"Starting from a blank page? Semantic similarity in central bank communication and market volatility,"
Journal of Monetary Economics, Elsevier, vol. 111(C), pages 48-62.
- Michael Ehrmann & Jonathan Talmi, 2016. "Starting from a Blank Page? Semantic Similarity in Central Bank Communication and Market Volatility," Staff Working Papers 16-37, Bank of Canada.
- Ehrmann, Michael & Talmi, Jonathan, 2017. "Starting from a blank page? Semantic similarity in central bank communication and market volatility," Working Paper Series 2023, European Central Bank.
- Meinen, Philipp & Roehe, Oke, 2017.
"On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area,"
European Economic Review, Elsevier, vol. 92(C), pages 161-179.
- Meinen, Philipp & Röhe, Oke, 2016. "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," Discussion Papers 48/2016, Deutsche Bundesbank.
- Husted, Lucas & Rogers, John & Sun, Bo, 2020.
"Monetary policy uncertainty,"
Journal of Monetary Economics, Elsevier, vol. 115(C), pages 20-36.
- Lucas F. Husted & John H. Rogers & Bo Sun, 2017. "Monetary Policy Uncertainty," International Finance Discussion Papers 1215, Board of Governors of the Federal Reserve System (U.S.).
- Martin, Ian W.R. & Nagel, Stefan, 2022.
"Market efficiency in the age of big data,"
Journal of Financial Economics, Elsevier, vol. 145(1), pages 154-177.
- Ian Martin & Stefan Nagel, 2019. "Market Efficiency in the Age of Big Data," NBER Working Papers 26586, National Bureau of Economic Research, Inc.
- Martin, Ian W.R. & Nagel, Stefan, 2022. "Market efficiency in the age of big data," LSE Research Online Documents on Economics 112960, London School of Economics and Political Science, LSE Library.
- Ian Martin & Stefan Nagel, 2019. "Market Efficiency in the Age of Big Data," CESifo Working Paper Series 8015, CESifo.
- Martin, Ian & Nagel, Stefan, 2019. "Market Efficiency in the Age of Big Data," CEPR Discussion Papers 14235, C.E.P.R. Discussion Papers.
- Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2021. "Using machine learning and big data to analyse the business cycle," Economic Bulletin Articles, European Central Bank, vol. 5.
- Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
- Born, Benjamin & Pfeifer, Johannes, 2014.
"Policy risk and the business cycle,"
Journal of Monetary Economics, Elsevier, vol. 68(C), pages 68-85.
- Born, Benjamin & Peifer, Johannes, 2011. "Policy Risk and the Business Cycle," Bonn Econ Discussion Papers 06/2011, University of Bonn, Bonn Graduate School of Economics (BGSE).
- Benjamin Born & Johannes Pfeifer, 2013. "Policy Risk and the Business Cycle," CESifo Working Paper Series 4336, CESifo.
- Andrew Haldane & Michael McMahon, 2018. "Central Bank Communications and the General Public," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 578-583, May.
- Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2022.
"Measuring real activity using a weekly economic index,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 667-687, June.
- Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2020. "Measuring Real Activity Using a Weekly Economic Index," Staff Reports 920, Federal Reserve Bank of New York.
- Daniel J. Lewis & Karel Mertens & James H. Stock, 2020. "Measuring Real Activity Using a Weekly Economic Index," Working Papers 2011, Federal Reserve Bank of Dallas, revised 02 Mar 2021.
- Lang, Jan Hannes & Peltonen, Tuomas A. & Sarlin, Peter, 2018. "A framework for early-warning modeling with an application to banks," Working Paper Series 2182, European Central Bank.
- Hans Genberg & Özer Karagedikli, 2021. "Machine Learning and Central Banks: Ready for Prime Time?," Working Papers wp43, South East Asian Central Banks (SEACEN) Research and Training Centre.
- Ricardo Correa & Keshav Garud & Juan M. Londono & Nathan Mislang, 2017. "Constructing a Dictionary for Financial Stability," IFDP Notes 2017-06-28, Board of Governors of the Federal Reserve System (U.S.).
- Huseyin Gulen & Mihai Ion, 2016. "Editor's Choice Policy Uncertainty and Corporate Investment," The Review of Financial Studies, Society for Financial Studies, vol. 29(3), pages 523-564.
- Larsen, Vegard H. & Thorsrud, Leif A., 2019. "The value of news for economic developments," Journal of Econometrics, Elsevier, vol. 210(1), pages 203-218.
- Jean-Marc Israel & Bruno Tissot, 2021. "Incorporating micro data into macro policy decision-making," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Micro data for the macro world, volume 53, Bank for International Settlements.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Martin Baumgaertner & Johannes Zahner, 2021.
"Whatever it takes to understand a central banker - Embedding their words using neural networks,"
MAGKS Papers on Economics
202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Zahner, Johannes & Baumgärtner, Martin, 2022. "Whatever it Takes to Understand a Central Banker – Embedding their Words Using Neural Networks," VfS Annual Conference 2022 (Basel): Big Data in Economics 264019, Verein für Socialpolitik / German Economic Association.
- Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
- Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"How is machine learning useful for macroeconomic forecasting?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Tobias Götze & Marc Gürtler & Eileen Witowski, 2020. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 428-446, September.
- Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2022. "Uncertainty in an emerging market economy: evidence from Thailand," Empirical Economics, Springer, vol. 62(3), pages 933-989, March.
- Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
- Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
- Paul Geertsema & Helen Lu, 2023. "Relative Valuation with Machine Learning," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 329-376, March.
- Pan, Shuiyang & Long, Suwan(Cheng) & Wang, Yiming & Xie, Ying, 2023. "Nonlinear asset pricing in Chinese stock market: A deep learning approach," International Review of Financial Analysis, Elsevier, vol. 87(C).
- Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
- Daniel Stempel & Johannes Zahner, 2022. "DSGE Models and Machine Learning: An Application to Monetary Policy in the Euro Area," MAGKS Papers on Economics 202232, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Emanuel Kohlscheen, 2022.
"Quantifying the Role of Interest Rates, the Dollar and Covid in Oil Prices,"
Papers
2208.14254, arXiv.org, revised Oct 2022.
- Emanuel Kohlscheen, 2022. "Quantifying the role of interest rates, the Dollar and Covid in oil prices," BIS Working Papers 1040, Bank for International Settlements.
- Danilo Cascaldi-Garcia & Cisil Sarisoy & Juan M. Londono & Bo Sun & Deepa D. Datta & Thiago Ferreira & Olesya Grishchenko & Mohammad R. Jahan-Parvar & Francesca Loria & Sai Ma & Marius Rodriguez & Ilk, 2023.
"What Is Certain about Uncertainty?,"
Journal of Economic Literature, American Economic Association, vol. 61(2), pages 624-654, June.
- Danilo Cascaldi-Garcia & Deepa Dhume Datta & Thiago Revil T. Ferreira & Olesya V. Grishchenko & Mohammad R. Jahan-Parvar & Juan M. Londono & Francesca Loria & Sai Ma & Marius del Giudice Rodriguez & J, 2020. "What is Certain about Uncertainty?," International Finance Discussion Papers 1294, Board of Governors of the Federal Reserve System (U.S.).
- Sebastian Doerr & Leonardo Gambacorta & José María Serena Garralda, 2021. "Big data and machine learning in central banking," BIS Working Papers 930, Bank for International Settlements.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Julian Ashwin & Eleni Kalamara & Lorena Saiz, 2024. "Nowcasting Euro area GDP with news sentiment: A tale of two crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 887-905, August.
- Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.
- Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.
- Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
More about this item
JEL classification:
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
- E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bas:econst:y:2023:i:8:p:177-199. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Diana Dimitrova (email available below). General contact details of provider: https://edirc.repec.org/data/ikbasbg.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.