Abstract
ABSTRACT This paper studies the predictive power of a set of systemic risk measures for macroeconomic downside risks in China. The quantile single-index model (QSIM) is used to select and combine systemic risk measures to depict the lower tail of macroeconomy distribution. The out-of-sample results show that QSIM provides prominent and robust prediction, as it aggregates all relevant systemic risk measures information and captures parameter nonlinearity. Moreover, we uncover the risk drivers behind macroeconomic downturns using the variable selection technique. The results provide an early warning mechanism for regulators and a criterion for researchers to select systemic risk measures.
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