IDEAS home Printed from https://ideas.repec.org/p/gla/glaewp/2022_13.html
   My bibliography  Save this paper

Frequency-band estimation of the number of factors detecting the main business cycle shocks

Author

Listed:
  • Marco Avarucci
  • Maddalena Cavicchioli
  • Mario Forni

Abstract

We introduce consistent estimators for the number of shocks driving large-dimensional dynamic factor models. Our estimators are functions of the eigenvalues of the spectral density matrix of the observables and can be applied to single frequencies as well as to specific frequency bands, making them suitable for disentangling shocks affecting dynamic macroeconomic models with a factor model representation. Their small-sample performance in simulations is excellent, even in estimating the number of shocks that drive medium-sized DSGE models. We apply our estimators to the FRED-QD dataset, finding that the U.S. macroeconomyis driven by two shocks: an inflationary demand shock and a deflationary supply shock

Suggested Citation

  • Marco Avarucci & Maddalena Cavicchioli & Mario Forni, 2022. "Frequency-band estimation of the number of factors detecting the main business cycle shocks," Working Papers 2022_13, Business School - Economics, University of Glasgow.
    • Handle: RePEc:gla:glaewp:2022_13
    as

    Download full text from publisher

    File URL: https://www.gla.ac.uk/media/Media_899756_smxx.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Frequency Bands; Dynamic Eigenvalue Ratio; Generalized Dynamic Factor Models; Business Cycle; Permanent Component; DSGE.;
    All these keywords.

    JEL classification:

    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    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:gla:glaewp:2022_13. 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: Business School Research Team (email available below). General contact details of provider: https://edirc.repec.org/data/dpglauk.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.