Financial Variables as Predictors of Real Growth Vulnerability

Working Paper: CEPR ID: DP14322

Authors: Lucrezia Reichlin; Giovanni Ricco; Thomas Hasenzagl

Abstract: We evaluate the role of financial conditions as predictors of macroeconomic risk first in the quantile regression framework of Adrian et al. (2019b), which allows for non-linearities, and then in a novel linear semi-structural model as proposed by Hasenzagl et al. (2018). We distinguish between price variables such as credit spreads and stock variables such as leverage. We find that (i) although the spreads correlate with the left tail of the conditional distribution of GDP growth, they provide limited advanced information on growth vulnerability; (ii) nonfinancial leverage provides a leading signal for the left quantile of the GDP growth distribution in the 2008 recession; (iii) measures of excess leverage conceptually similar to the Basel gap, but cleaned from business cycle dynamics via the lenses of the semi-structural model, point to two peaks of accumulation of risks – the eighties and the first eight years of the new millennium, with an unstable relationship with business cycle chronology.

Keywords: financial cycle; business cycle; credit; financial crises; downside risk; entropy; quantile regressions

JEL Codes: E32; E44; C32; C53


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
excess leverage (G32)risk accumulation (D81)
credit spreads (G12)left tail of GDP growth distribution (D39)
non-financial leverage (G32)left quantile of GDP growth distribution (D39)
financial conditions (E66)GDP growth (O49)

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