IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/17800.html

Advances in Nowcasting Economic Activity: The Role of Heterogeneous Dynamics and Fat Tails

Author

Listed:
  • Antolin-Diaz, Juan
  • Drechsel, Thomas
  • Petrella, Ivan

Abstract

A key question for households, firms, and policy makers is: how is the economy doing now? This paper develops a Bayesian dynamic factor model that allows for nonlinearities, heterogeneous lead-lag patterns and fat tails in macroeconomic data. Explicitly modeling these features changes the way that different indicators contribute to the real-time assessment of the state of the economy, and substantially improves the out-of-sample performance of this class of models. In a formal evaluation, our nowcasting framework beats benchmark econometric models and professional forecasters at predicting US GDP growth in real time.

Suggested Citation

  • Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2023. "Advances in Nowcasting Economic Activity: The Role of Heterogeneous Dynamics and Fat Tails," CEPR Discussion Papers 17800, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:17800
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP17800
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. Florian Eckert & Philipp Kronenberg & Heiner Mikosch & Stefan Neuwirth, 2025. "Tracking Economic Activity With Alternative High‐Frequency Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 270-290, April.
    3. ., Kaustubh & Gopalakrishnan, Pawan Gopalakrishnan & Ranjan, Abhishek Ranjan, 2025. "Estimating the New Keynesian Phillips Curve (NKPC) with Fat-tailed Events," MPRA Paper 126329, University Library of Munich, Germany.
    4. Freddy Garc'ia-Alb'an & Juan Jarr'in, 2025. "Tracking the economy at high frequency," Papers 2507.07450, arXiv.org.
    5. Maximo Camacho & Salvador Ramallo & Manuel Ruiz, 2024. "A New Approach to Forecasting the Probability of Recessions after the COVID‐19 Pandemic," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 833-855, August.
    6. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    7. De Polis, Andrea & Melosi, Leonardo & Petrella, Ivan, 2024. "The Taming of the Skew : Asymmetric Inflation Risk and Monetary Policy," The Warwick Economics Research Paper Series (TWERPS) 1530, University of Warwick, Department of Economics.
    8. Nicolò Maffei‐Faccioli, 2025. "Identifying the Sources of the Slowdown in Growth: Demand Versus Supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(2), pages 181-194, March.
    9. Kronenberg, Philipp, 2024. "A High-Frequency GDP Indicator for Switzerland," EconStor Preprints 330303, ZBW - Leibniz Information Centre for Economics.
    10. Kaustubh, Kaustubh & Ranjan, Abhishek, 2025. "A multi-factor GDP nowcast model for India," Economic Modelling, Elsevier, vol. 147(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

    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:cpr:ceprdp:17800. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    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.