When is growth at risk?

Mikkel Plagborg-Møller, Lucrezia Reichlin, Giovanni Ricco, Thomas Hasenzagl

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


This paper empirically evaluates the potentially nonlinear nexus between financial indicators and the distribution of future GDP growth, using a rich set of macroeconomic and financial variables covering thirteen advanced economies. We evaluate the out-of-sample forecast performance of financial variables for GDP growth, including a fully real-time exercise based on a flexible nonparametric model. We also use a parametric model to estimate the moments of the time-varying distribution of GDP and evaluate their in-sample estimation uncertainty. Our overall conclusion is pessimistic: moments other than the conditional mean are poorly estimated, and no predictors we consider provide robust and precise advance warnings of tail risks or indeed about any features of the GDP growth distribution other than the mean. In particular, financial variables contribute little to such distributional forecasts, beyond the information contained in real indicators.

Original languageEnglish (US)
Pages (from-to)167-229
Number of pages63
JournalBrookings Papers on Economic Activity
Issue numberSpring
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • General Business, Management and Accounting
  • Economics and Econometrics


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