The 2022 Denis Sargan Econometrics Prize
提出一种基于协整的非平稳动态因子模型永久-暂时分解方法，通过先利用观测序列的协整性质进行分解，再对平稳序列进行动态因子分析，模拟表明该方法比直接对一阶差分进行因子分析更有效，并应用于商品价格联动分析。
for her article "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices" with Riccardo (Jack) Lucchetti in the May 2022 issue of The Econometrics Journal. 1 Chiara and Jack's prize winning article develops a cointegration-based Permanent-Transitory decomposition for nonstationary dynamic factor models.Its novel idea is to first leverage the cointegration properties of the observed series in their Permanent-Transitory decomposition and then apply dynamic factor analysis to the resulting stationary series.The paper shows by simulation that this method extracts the factor structure better than a common alternative that does not use the cointegration properties of the observed series, but applies dynamic factor analysis to their first differences.It then demonstrates the empirical usefulness of the proposed method with an empirical analysis of the comovement of commodity prices.