Abstract: Based on the monthly data from January 2007 to December 2017, this paper first selects 14 representative indicators from four respects—the extreme value risks of financial institutions, the contagion effects between financial systems, the volatility and instability of financial markets, and the liquidity and credit risks of financial markets—to measure the systemic financial risk. Secondly, the quantile regression is used to measure the impact of individual systemic risk indicators on the macro economy. Finally, a partial least squares quantile regression method is used to construct a systemic risk comprehensive indicator and empirically analyze the impact of systemic financial risk on the macro economy. The results show that: ① The indicators under the institutional extreme risk category of the individual systemic financial risk index have the greatest impact on the macro economy, among which the CATFIN has the most significant effect; ② The systemic risk comprehensive index constructed by partial least squares quantile regression can more stably reflect the impact of systemic financial risks on the macro economy than individual systemic risk indicators; ③ From the measurement effect, the individual systemic risk index and the comprehensive systemic risk index in the lower tail distribution (0.2 quantile) are significantly better than the middle distribution (0.5 quantile) and the upper tail distribution (0.8 quantile).

Key words: Systemic Financial Risk, Quantile Regression, Partial Least Squares Quantile Regression, Macroeconomy