The Term Structure of Growth-at-Risk
By Tobias Adrian, Federico Grinberg, Nellie Liang, Sheheryar Malik. Social Science Research Network, 2018
215 citations recorded by the source corpus.
We show that the conditional distribution of forecasted GDP growth depends on financial conditions in a panel of 11 advanced economies. Financial conditions have a larger effect on the lower fifth percentile of conditional growth—which we call growth-at-risk (GaR)—than the median. In addition, the term structure of GaR reflects that when initial financial conditions are loose, downside risks are lower in the near term but increase in later quarters. This intertemporal tradeoff for loose financial conditions is amplified when credit-to-GDP growth is rapid. Using granular instrumental variables, we also provide evidence that the relationship from loose financial conditions to future downside risks is causal. Our results suggest that models of macrofinancial linkages should incorporate the endogeneity of higher-order moments to systematically account for downside risks to growth in the medium run. (JEL E23, E27, E32, E44)
View Paper: https://www.semanticscholar.org/paper/684ca1522c1b6126ebb3f700d64fdf0d55df684d
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Citations in the corpus
- Predictable Financial Crises (2020, background): “Finally, Adrian et al. (2018) estimate quantile regressions which suggest that easy financial conditions and rapid credit growth raise the risk of a large decline in real growth over the next three years.”
- The benefits are at the tail: Uncovering the impact of macroprudential policy on growth-at-risk (2020, methodology): “Adrian et al. (2018) apply a panel quantile regression to a sample of 22 advanced and emerging economies, where the distribution of GDP growth up to 8 quarters ahead is estimated conditional on inflation, a dummy identifying credit boom periods, GDP growth, and a financial conditions index.”