讲座嘉宾：朱 丹 教授

讲座时间：2025年10月16日（星期四） 下午15：00

讲座形式：腾讯会议（详询院学科与科研办公室65105261）

主讲人简介：朱丹现任澳大利亚莫纳什大学（Monash University）经济计量与商业统计系教授、澳大利亚精算师协会资深会员。她的主要研究领域包括精算科学、贝叶斯经济计量学、运筹学以及宏观时间序列分析。近年来，她的研究重点集中在高维贝叶斯模型的高效计算方法及其在保险、宏观经济与金融风险管理中的应用。

 朱丹教授在多家国际顶级学术期刊上发表了论文，包括《Journal of Econometrics》《Journal of Applied Econometrics》《European Journal of Operational Research》《Insurance: Mathematics and Economics》《Journal of Business & Economic Statistics》等。目前，她主持和参与多项科研项目，其中包括澳大利亚社会服务部资助的“照护者评估改革项目”，以及英国学术院资助的访问学者项目。朱丹教授多次受邀在国际学术会议上作特邀报告，以其严谨的研究方法和跨领域的创新成果在学术界广受认可。

论文摘要：Recent evidence of a flattened Phillips curve calls for methods that capture more than average relationships. We propose a semiparametric time-varying parameter distributional regression (TVPDR) model that estimates full conditional distributions, allowing asymmetric and dynamic effects of macroeconomic drivers on inflation. Applied to U.S. inflation from 1982–2024, the model delivers superior point and density forecasts compared to mean- and quantile-based alternatives, especially during recessions. It identifies sharp spikes in deflation risk during downturns and surges in excessive inflation risk during the post-pandemic recovery. Shapley decompositions show that deflation risk is mainly driven by demand-side weakness and inflation persistence, while excessive inflation risk reflects supply-side shocks, particularly energy and food prices. Scenario analyses further reveal that unemployment fluctuations mainly affect the lower tail of the distribution, whereas energy prices dominate the upper tail. Taken together, the results show that the lower end of the inflation distribution remains sensitive to unemployment, while the upper end is less responsive and instead shaped by supply shocks. This asymmetric and time-varying sensitivity explains why the aggregate Phillips curve relationship appears flattened.