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

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  • Haroon Mumtaz
  • Sofia Velasco

Abstract

The tails of macroeconomic outcomes can respond differently from the centre of their distribution to aggregate shocks. We demonstrate this via a threshold stochastic-volatility-in-mean VAR with regime-dependent leverage. The model allows interactions between the endogenous variables and their volatility, contemporaneous level-volatility dependence, and regime-specific propagation. We estimate the model using a long-run U.S. data set, finding evidence for three inflation-based regimes. We identify business-cycle, financial, macroeconomic-uncertainty, and financial-uncertainty shocks and decompose their contributions to growth- and inflation-at-risk. Business-cycle shocks dominate the median response of GNP growth but account for a substantially smaller share of growth-at-risk. In contrast, uncertainty makes a material contribution to both growth- and inflation-at-risk.

Suggested Citation

  • Haroon Mumtaz & Sofia Velasco, 2026. "Nonlinear Drivers of Macroeconomic Tail Risk: A Threshold Stochastic Volatility-in-Mean VAR with Regime-Dependent Leverage," Papers 2609.26994, arXiv.org, revised Oct 2026.
    • Handle: RePEc:arx:papers:2609.26994
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    1. Andrea Carriero & Alessio Volpicella, 2025. "Max Share Identification of Multiple Shocks: An Application to Uncertainty and Financial Conditions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(1), pages 1-13, January.
    2. Rossi, Barbara & Sekhposyan, Tatevik, 2019. "Alternative tests for correct specification of conditional predictive densities," Journal of Econometrics, Elsevier, vol. 208(2), pages 638-657.
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