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Machine Learning the Macroeconomic Effects of Financial Shocks

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  • Niko Hauzenberger
  • Florian Huber
  • Karin Klieber
  • Massimiliano Marcellino

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.

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  • Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2024. "Machine Learning the Macroeconomic Effects of Financial Shocks," Papers 2412.07649, arXiv.org.
    • Handle: RePEc:arx:papers:2412.07649
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    References listed on IDEAS

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