A time-varying skewness model for Growth-at-Risk
Download PDF: Working Paper 49
This paper develops a new empirical model to study macro-financial risks and shows that changing financial conditions can signal risks to the path of future economic growth.
Author: Martin Iseringhausen (ESM)
Abstract:
This paper studies macroeconomic risks in a panel of advanced economies based on a stochastic volatility model in which macro-financial conditions shape the predictive growth distribution. We find sizable time variation in the skewness of these distributions, conditional on the macro-financial environment. Tightening financial conditions signal increasing downside risk in the short term, but this link reverses at longer horizons. When forecasting downside risk, the proposed model, on average, outperforms existing approaches based on quantile regression and a GARCH model, especially at short horizons. In forecasting upside risk, it improves the average accuracy across all horizons up to four quarters ahead. The suggested approach can inform policy makers' assessment of macro-financial vulnerabilities by providing a timely signal of shifting risks and a quantification of their magnitude.
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Keywords: Bayesian analysis, downside risk, macro-financial linkages, time variation
JEL codes: C11, C23, C53, E44