Machine learning the macroeconomic effects of financial shocks

Tools

Hauzenberger, Niko and Huber, Florian and Klieber, Karin and Marcellino, Massimiliano (2025) Machine learning the macroeconomic effects of financial shocks. Economics Letters, 250. 112260. ISSN 0165-1765 (https://doi.org/10.1016/j.econlet.2025.112260)

[thumbnail of Hauzenberger-etal-EconLet-Machine-learning-the-macroeconomic-effects-of-financial-shocks]
Preview
 Text. Filename: Hauzenberger-etal-EconLet-Machine-learning-the-macroeconomic-effects-of-financial-shocks.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (1MB)| Preview

Abstract

We propose a method to learn the nonlinear impulse responses to structural shocks using neural networks, and apply it to uncover the effects of US financial shocks. The results reveal substantial asymmetries with respect to the sign of the shock. Adverse financial shocks have powerful effects on the US economy, while benign shocks trigger much smaller reactions. Instead, with respect to the size of the shocks, we find no discernible asymmetries.

ORCID iDs

Hauzenberger, Niko ORCID logoORCID: https://orcid.org/0000-0002-2683-8421, Huber, Florian, Klieber, Karin and Marcellino, Massimiliano;
  • Item type:Article
    ID code:92376
    Dates:
    Date
    Event
    April 2025
    Published
    14 March 2025
    Published Online
    1 March 2025
    Accepted
    10 December 2024
    Submitted
    Subjects:Social Sciences > Economic Theory
    Department:Strathclyde Business School > Economics
    Depositing user: Pure Administrator
    Date deposited:19 Mar 2025 11:22
    Last modified:26 Mar 2025 02:22
    URI:https://strathprints.strath.ac.uk/id/eprint/92376
CORE (COnnecting REpositories)