北大经院工作坊第1038场
Ridge Regression Under Dense Factor Augmented Models（密集因子增强模型下的岭回归）
计量、金融和大数据分析工作坊
主讲人：Yi He（University of Amsterdam, Netherlands）
主持老师：（北大经院）王法
参与老师：（北大经院）王一鸣、王熙、刘蕴霆
时间：2025年2月28日（周五） 10:00-11:30
地点：北京大学经济学院107会议室
主讲人简介：
Yi He is an Associate Professor in the Quantitative Economics Section at the University of Amsterdam. He earned his master's degree from the University of Cambridge and his PhD from Tilburg University in 2016. Before returning to the Netherlands, he served as a tenured Assistant Professor in the Department of Econometrics and Business Statistics at Monash University in Australia. His research focuses on high-dimensional econometrics, random matrix theory, extreme value statistics, bootstrapping, and machine learning. His work has been featured in prestigious journals, including the Journal of the American Statistical Association, The Annals of Statistics, Journal of the Royal Statistical Society - Series B, Journal of Business & Economic Statistics, and Journal of Econometrics. Yi's breakthroughs in extreme value statistics have earned him a nomination for the 2025 Van Dantzig Award in Statistics and Operations Research in the Netherlands. His current research explores dense time series models with complex network interactions in high-dimensional econometrics.
摘要：
This article establishes a comprehensive theory of the optimality, robustness, and cross-validation selection consistency for the ridge regression under factor-augmented models with possibly dense idiosyncratic information. Using spectral analysis for random matrices, we show that the ridge regression is asymptotically efficient in capturing both factor and idiosyncratic information by minimizing the limiting predictive loss among the entire class of spectral regularized estimators under large-dimensional factor models and mixed-effects hypothesis. We derive an asymptotically optimal ridge penalty in closed form and prove that a bias-corrected k-fold cross-validation procedure can adaptively select the best ridge penalty in large samples. We extend the theory to the autoregressive models with many exogenous variables and establish a consistent cross-validation procedure using the what-we-called double ridge regression method. Our results allow for nonparametric distributions for, possibly heavy-tailed, martingale difference errors and idiosyncratic random coefficients and adapt to the cross-sectional and temporal dependence structures of the large-dimensional predictors. We demonstrate the performance of our ridge estimators in simulated examples as well as an economic dataset. All the proofs are available in the supplementary materials, which also includes more technical discussions and remarks, extra simulation results, and useful lemmas that may be of independent interest.
北大经院工作坊第1039场
The Role of Weather Information in Climate Adaptation and Reducing Medical Costs in China
生态、环境与气候变化经济学工作坊
主讲人：刘庆丰（清华大学“水木学者”博士后）
主持老师：
（北大国发院）邢剑炜
（北大经院）季曦
时间：2025年2月28日（周五）10:30-12:00
地点： 北京大学国家发展研究院承泽园131教室
主讲人简介：
刘庆丰，清华大学“水木学者”博士后，全球与共同发展研究院助理研究员。博士毕业于清华大学经济管理学院，研究领域为公共经济学、环境与气候变化。曾获中国技术经济学会第二十七届年会一等奖。研究成果发表于《经济学（季刊）》等国内外学术期刊。
摘要：
Exploring cost-effective climate adaptation strategies is crucial for human well-being, yet little is known about whether and how information interventions promote climate adaptation. This paper provides the first analysis of the role of weather forecasts in reducing the health impacts of climate change, utilizing large-scale, fine-grained medical expenditure data from China’s largest medical insurance program. Our analysis reveals accurate forecasts significantly reduce weather-related medical cost: a one-degree Celsius deviation from the accurate forecast increases medical expenses over the next seven days by 13.7% when underestimating and 4.6% when overestimating the realized temperature. Moreover, the potential value of improving forecast accuracy will escalate with ongoing global warming, as the negative impacts of inaccurate forecasts are especially severe under extreme weather conditions. Our findings highlight the substantial potential of information interventions for climate adaptation and enhance understanding of health-related impacts of climate change.
第177次北大赛瑟（CCISSR）双周讨论会
国际经贸环境：巨变与思考
主讲人：傅梦孜（中国现代国际关系研究院研究员）
主持人：朱南军（北京大学经济学院教授）
时间：2025年2月28日（周五）10：00-11：30
地点：北京大学经济学院302会议室
主讲人简介：
傅梦孜博士，中国现代国际关系研究院研究员、博士生导师、原副院长、国务院政府津贴专家。历任中国改革开放论坛学术顾问，中国国际经济关系学会副会长，习近平外交思想研究中心研究员，中华美国学会、中美友协、外交学会，太平洋学会常务理事等，现代院美国研究所所长。国家社科基金重大专项首席专家。出席习近平总书记“一带一路”五周年建设座谈会。主要研究世界经济与政治、美国问题、“一带一路”等。出版专著多部，最新著作：《一带一路建设的持续性》。发表论文数百篇，最新论文包括《全球南方的崛起，一带一路未来可期》《世界进入动荡变革期与新时代的中国》等。
摘要：
在百年未有的大变局中，中国面临的国际经贸环境不同以往，大国竞争非良性化、世界经济增长趋缓和全球化进程变慢都反映了这一状况。由于美西方经济发展理念发生变化，加上特朗普式冲击震荡，国际经贸环境还有极大的形塑空间。中国争取和塑造良好外部环境的努力面临新的挑战，但仍然存在作为空间，需要冷静面对，寻求转圜，一切仍求其在我。
主办单位：
北京大学中国保险与社会保障研究中心
北京大学经济学院风险管理与保险学系
供稿：科研与博士后办公室
美编：初夏
责编：度量、雨禾、雨田
