Measuring Macroeconomic Risk in the Euro Area: A Quantile Regression Approach.

This thesis uses a distribution-based framework to measure macrofinancial tail risks in the euro area. Using conditional quantiles, it constructs two indicators, expected skewness (ES) and interquartile range (IQR), to capture downside risk and uncertainty, respectively. Quantile factors from a panel of macroeconomic variables (2000–2024) are incorporated into a quantile factor-augmented VAR to assess asymmetric shock dynamics. Results show stronger and more persistent effects in the lower tail, with systematic cross-country heterogeneity. The framework highlights the role of left-tail risks in periods of elevated uncertainty and supports more tailored policy responses in a heterogenous monetary union.