A1678
Title: Real-time monitoring of global inflation heterogeneity
Authors: Yiren Wang - Hunan University (China) [presenting]
Hongqi Chen - Hunan University (China)
Liangjun Su - Tsinghua University (China)
Abstract: A real-time monitoring econometric framework for detecting structural changes in global inflation heterogeneity is developed. The framework detects changes in the inflation-macroeconomic relationship across quantiles in a timely manner as new data become available. A convolution-type smoothed panel quantile regression model with individual fixed effects is employed, and a gradient-based sequential detector with an associated boundary function is constructed. The proposed procedure preserves convexity and achieves $\sqrt{NT}$-consistent estimation through bias correction. Asymptotic size control is established under the null hypothesis of parameter stability, and non-trivial power is demonstrated under local alternatives. Simulation verifies the theoretical properties of the proposed method. Using global inflation data with the proposed framework, new empirical evidence on real-time monitoring of global inflation dynamics is provided, documenting timely detection of changes across quantiles in the inflation-macroeconomic relationship and identifying the macroeconomic drivers associated with these changes.
