Nonlinear Drivers of Macroeconomic Tail Risk: A Threshold Stochastic Volatility-in-Mean VAR with Regime-Dependent Leverage

2026-09-22

AI Summary

本文通过构建一个带有机制依赖杠杆的阈值随机波动率在均值向量自回归模型，研究宏观经济尾部风险的不同驱动因素。

Abstract

The tails of macroeconomic outcomes can respond differently from the centre of their distribution: shocks with modest effects on median growth or inflation can shift downside growth or upside inflation risk. We develop a threshold stochastic-volatility-in-mean VAR with regime-dependent leverage to study their structural drivers. The model allows endogenous interactions between outcomes and volatility, contemporaneous level-volatility dependence, and regime-specific propagation. In nearly 150 years of U.S. data, predictive model selection supports three inflation-defined regimes. We identify business-cycle, financial, macroeconomic-uncertainty, and financial-uncertainty shocks and decompose their contributions to growth- and inflation-at-risk. The structural composition of tail risk differs from that of the predictive median. Business-cycle shocks dominate the median response of GNP growth but account for a substantially smaller share of growth-at-risk. Macroeconomic uncertainty makes a material contribution to both growth- and inflation-at-risk, with its share of growth-at-risk increasing with the magnitude of a positive macroeconomic-uncertainty impulse, despite its limited role at the median. In high-inflation states, the contribution of financial uncertainty to inflation-at-risk rises with the magnitude of positive financial-uncertainty impulses.

Problem

• Macroeconomic Tail Risk
• Threshold Stochastic Volatility
• Regime-Dependent Leverage

Innovation

• Threshold Stochastic Volatility-in-Mean VAR
• regime-dependent leverage
• endogenous interactions
• macroeconomic uncertainty
• financial uncertainty