IDEAS home Printed from https://ideas.repec.org/p/bis/biswps/980.html
   My bibliography  Save this paper

What does machine learning say about the drivers of inflation?

Author

Listed:
  • Emanuel Kohlscheen

Abstract

This paper examines the drivers of CPI inflation through the lens of a simple, but computationally intensive machine learning technique. More specifically, it predicts inflation across 20 advanced countries between 2000 and 2021, relying on 1,000 regression trees that are constructed based on six key macroeconomic variables. This agnostic, purely data driven method delivers (relatively) good outcome prediction performance. Out of sample root mean square errors (RMSE) systematically beat even the in-sample benchmark econometric models, with a 28% RMSE reduction relative to a naïve AR(1) model and a 8% RMSE reduction relative to OLS. Overall, the results highlight the role of expectations for inflation outcomes in advanced economies, even though their importance appears to have declined somewhat during the last 10 years.

Suggested Citation

  • Emanuel Kohlscheen, 2021. "What does machine learning say about the drivers of inflation?," BIS Working Papers 980, Bank for International Settlements.
    • Handle: RePEc:bis:biswps:980
    as

    Download full text from publisher

    File URL: https://www.bis.org/publ/work980.pdf
    File Function: Full PDF document
    Download Restriction: no
    File URL: https://www.bis.org/publ/work980.htm
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kristin Forbes, 2019. "Has globalization changed the inflation process?," BIS Working Papers 791, Bank for International Settlements.
    2. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    3. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    4. Christian Gillitzer & Martin McCarthy, 2019. "Does global inflation help forecast inflation in industrialized countries?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 850-857, August.
    5. Martina Jašová & Richhild Moessner & Elöd Takáts, 2019. "Exchange Rate Pass-Through: What Has Changed Since the Crisis?," International Journal of Central Banking, International Journal of Central Banking, vol. 15(3), pages 27-58, September.
    6. Jeremy B. Rudd, 2021. "Why Do We Think That Inflation Expectations Matter for Inflation? (And Should We?)," Finance and Economics Discussion Series 2021-062, Board of Governors of the Federal Reserve System (U.S.).
    7. Haroon Mumtaz & Paolo Surico, 2012. "Evolving International Inflation Dynamics: World And Country-Specific Factors," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 716-734, August.
    8. Jon Kleinberg & Jens Ludwig & Sendhil Mullainathan & Ziad Obermeyer, 2015. "Prediction Policy Problems," American Economic Review, American Economic Association, vol. 105(5), pages 491-495, May.
    9. Tommaso Monacelli & Luca Sala, 2009. "The International Dimension of Inflation: Evidence from Disaggregated Consumer Price Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(s1), pages 101-120, February.
    10. Claudio E. V. Borio & Andrew Filardo, 2007. "Globalisation and inflation: New cross-country evidence on the global determinants of domestic inflation," BIS Working Papers 227, Bank for International Settlements.
    11. 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.
    12. Marcelo C. Medeiros & Gabriel F. R. Vasconcelos & Álvaro Veiga & Eduardo Zilberman, 2021. "Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 98-119, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Douglas Kiarelly Godoy de Araujo, 2023. "gingado: a machine learning library focused on economics and finance," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Data science in central banking: applications and tools, volume 59, Bank for International Settlements.
    2. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).

    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.
    1. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    2. Günes Kamber & Madhusudan Mohanty & James Morley, 2020. "What drives inflation in advanced and emerging market economies?," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation dynamics in Asia and the Pacific, volume 111, pages 21-36, Bank for International Settlements.
    3. Güneş Kamber & Madhusudan Mohanty & James Morley, 2020. "Have the driving forces of inflation changed in advanced and emerging market economies?," BIS Working Papers 896, Bank for International Settlements.
    4. Emanuel Kohlscheen, 2022. "Quantifying the Role of Interest Rates, the Dollar and Covid in Oil Prices," Papers 2208.14254, arXiv.org, revised Oct 2022.
    5. Auer, Raphael A. & Mehrotra, Aaron, 2014. "Trade linkages and the globalisation of inflation in Asia and the Pacific," Journal of International Money and Finance, Elsevier, vol. 49(PA), pages 129-151.
    6. Kohlscheen, Emanuel & Moessner, Richhild, 2022. "Globalisation and the slope of the Phillips curve," Economics Letters, Elsevier, vol. 216(C).
    7. Fabio Busetti & Michele Caivano & Davide Delle Monache, 2021. "Domestic and Global Determinants of Inflation: Evidence from Expectile Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 982-1001, August.
    8. Karol Szafranek & Aleksandra Hałka, 2019. "Determinants of Low Inflation in an Emerging, Small Open Economy through the Lens of Aggregated and Disaggregated Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(13), pages 3094-3111, October.
    9. Szafranek, Karol, 2021. "Disentangling the sources of inflation synchronization. Evidence from a large panel dataset," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 229-245.
    10. Guido Ascari & Luca Fosso, 2021. "The Inflation Rate Disconnect Puzzle: On the International Component of Trend Inflation and the Flattening of the Phillips Curve," Working Paper 2021/17, Norges Bank.
    11. Silvio Contessi & Pierangelo De Pace & Li Li, 2014. "An international perspective on the recent behavior of inflation," Review, Federal Reserve Bank of St. Louis, vol. 96(3), pages 267-294.
    12. Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1145-1162.
    13. Raphael Auer & Aaron Mehrotra, 2014. "Real globalisation and price spillovers in Asia and the Pacific," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation, inflation and monetary policy in Asia and the Pacific, volume 77, pages 81-89, Bank for International Settlements.
    14. Gert Peersman, 2022. "International Food Commodity Prices and Missing (Dis)Inflation in the Euro Area," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 85-100, March.
    15. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    16. Chon, Sora, 2020. "International Inflation Synchronization and Implications," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 42(2), pages 57-84.
    17. Chatterjee, Arpita, 2016. "Globalization and monetary policy comovement: International evidence," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 181-202.
    18. Felipe Leal & Carlos Molina & Eduardo Zilberman, 2020. "Proyección de la Inflación en Chile con Métodos de Machine Learning," Working Papers Central Bank of Chile 860, Central Bank of Chile.
    19. Ergemen, Yunus Emre, 2022. "Forecasting inflation rates with multi-level international dependence," Economics Letters, Elsevier, vol. 214(C).
    20. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).

    More about this item

    Keywords

    expectations; forecast; inflation; machine learning; oil price; output gap; Phillips curve;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:bis:biswps:980. 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: Christian Beslmeisl (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.