Study reveals pervasive asymmetric tail risk in US economy

The paper introduces a dynamic factor model with stochastic volatility to characterize asymmetric tail risk across over one hundred U.S. macroeconomic and financial variables.

This framework unifies growth-at-risk, inflation-at-risk, and sectoral heterogeneity through common factors whose volatility responds endogenously to shocks.

The core mechanism extends the leverage effect, where shocks affect factor levels and volatility responds, amplifying downside risk for real activity and generating upside risk for prices and financial conditions.

The study establishes four empirical findings, starting with the construction of three directional indices for growth, financial conditions, and inflation.

These indices synthesize tail risk information across many variables, revealing significant time variation consistent with regime shifts.

For instance, growth risk tilts towards adverse events during financial crises, while inflation risk shifts direction across supply-shock periods (1970s, 2021-22) and demand-driven downturns (2008-09).

The methodological contribution is a dynamic factor model that formalizes interactions between factor levels and volatilities.

This allows past volatility to affect current factor dynamics, factor movements to influence volatility evolution, and contemporaneous correlation between factor levels and volatilities.

The model produces full predictive distributions for all variables, characterizing time-varying asymmetries.

The study estimates the model using 116 monthly U.S. macroeconomic and financial time series from 1973 to 2023.

It finds that cyclical, capital-intensive industries like construction materials exhibit extreme downside asymmetry, while regulated utilities show modest, nearly symmetric risk.