北大经院 | 讲座预告（5.7-5.8）

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第188次北大赛瑟（CCISSR）双周讨论会

追古抚今看文化对保险发展的影响力

主讲人：

范娟娟（对外经济贸易大学中国保险历史文化研究中心研究员、正高级经济师）

主持人：

郑伟（北京大学经济学院教授）

时间：

2026年5月7日（周四）

10：30-12：00

地点：

北京大学第三教学楼108室

主讲人简介：

范娟娟，对外经济贸易大学中国保险历史文化研究中心研究员，正高级经济师，中央财经大学经济学博士、对外经济贸易大学经济学博士后；保险行业工作20余年；中国保险保障基金保险行业风险评估专家委员会委员，中国保险学会智库专家库专家；国际金融理财规划师（CFP）资深培训专家；央视网财经频道学术顾问；出版《健康保险经营与管理》、《医保经办的博弈与制衡》等，译作《简明健康保险学》；参编多部学术著作和教材，发表学术论文40余篇。

摘要：

商业保险不仅是经济层面上的安排，更是文化融合进步的产物。讲座以“追古抚今看文化对保险发展的影响力”为主题，跳出单纯的经济发展思维框架，从信仰与行为习惯、价值观、技术发展、行业规则确立等非经济角度，系统梳理文化如何塑造保险思想萌芽、推动实践探索和现代保险制度的演进；并探讨中国保险市场“由大变强”的发展进程中，中国特色保险文化应当具有的时代内涵。

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

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北大经院工作坊第1277场

Standoffs with Intertwined Resolve and Public Information

 微观理论经济学工作坊 

主讲人：

Hulya Eraslan（Ralph O'Connor Professor of Economics at Rice University, Research Associate at the National Bureau of Economic Research，Specially Appointed Professor at the Institute of Social and Economic Studies, University of Osaka）

主持老师：

（北大经院）吴泽南、石凡奇

（北大国发院）胡岠

参与老师：

（北大经院）胡涛

（北大国发院）汪浩、邢亦青

（北大光华）翁翕、刘烁

时间：

2026年5月7日（周四）

10:30-12:00

地点：

北京大学经济学院305会议室

主讲人简介：

Hulya Eraslan is the Ralph O'Connor Professor of Economics at Rice University, a Research Associate at the National Bureau of Economic Research and a Specially Appointed Professor at the Institute of Social and Economic Studies, University of Osaka. She received her PhD in 2001 from the University of Minnesota. Previously she held positions at the Wharton School, University of Pennsylvania and Johns Hopkins University. Her areas of research interest include political economy, bargaining and voting theory and their application. She has published numerous articles in leading economics journals, including the American Economic Review, Econometrica, and the Review of Economic Studies. She is an elected fellow of the Game Theory Society and an elected fellow of the Society for the Advancement of Economic Theory. She holds editorial positions at Econometrica, International Economic Review, International Journal of Game Theory, Review of Economic Design and Social Choice and Welfare.

摘要：

Conventional wisdom, dating back to Schelling and formalized by Crawford (1982),regards commitment as a valuable bargaining tool despite the risk of impasse. More recently, Kambe (1999) showed that the delays caused by reputation-building discourage negotiators from making incompatible demands. We highlight two factors that influence the tradeoff between the costs and benefits of commitment attempts: a correlation in their successes and public signals about the resolve of negotiators. We show that negotiators make incompatible demands when the correlation is sufficiently negative or the public signals are sufficiently precise, helping to explain common behavior in political negotiations and collective bargaining.

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北大经济史学名家系列讲座

第245讲

性别不平等的地方病起源：来自新中国血吸虫病防治的证据

主讲人：

李楠（复旦大学经济学院教授）

时间：

2026年5月8日（周五）

10:10-12:00

地点：

北京大学经济学院302会议室

主持人：

周建波（北京大学经济学院经济史学系主任、教授）

评论人：

李晓（中国政法大学商学院教授）

兰日旭（中央财经大学经济学院经济史学系主任、教授）

管汉晖（北京大学经济学院长聘副教授）

郝煜（北京大学经济学院经济史学系副主任、长聘副教授）

赵一泠（北京大学经济学院助理教授）

主讲人简介：

李楠，复旦大学经济学院教授、经济史专业博士生导师、香港科技大学社会科学部博士后、伦敦政治经济学院（LSE）访问学者、北京大学人文社会科学高等研究院访问教授、中国商业史学会常务理事、中国经济史学会外国经济史专业委员会理事。主要研究兴趣包括：长期经济增长与发展、历史经济分析、历史计量方法与应用、中国传统社会政治经济、艺术品金融等。先后在Explorations in Economic History、Australian Economic History Review、China Economic Review、《经济研究》、《历史研究》、《经济学（季刊）》、《世界经济》、《中国经济史研究》等国内外核心期刊发表论文50余篇。部分研究成果已分别被《中国社会科学文摘》等全文转载，并获得教育部高等学校科学研究优秀成果奖、上海市哲学社会科学优秀成果奖等省部级优秀研究成果奖多项。

主办单位：

北京大学经济学院经济史学系

北京大学社会经济史研究所

北京大学外国经济学说研究中心

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北大经院工作坊第1278场

How does Smart Technology Impact Firms? Evidence from a Field Experiment

 行为和实验经济学工作坊 

主讲人：

施新政（北京大学经济学院教授）

主持老师：

（北大经院）陆方文

时间：

2026年5月8日（周五）

10:10-11:30

地点：

北京大学经济学院305会议室

主讲人简介：

施新政，北京大学经济学院教授。他的主要研究领域为劳动经济学、发展经济学。他的研究论文发表于JEEA、RESTAT、JPubE、JDE、JEEM、《经济研究》、《管理世界》、《经济学（季刊）》、《世界经济》等国内外期刊。

摘要：

We conduct a randomized controlled trial investigating Smart Voice Assistants (SVAs) in a full-service Shanghai hotel. Although intended to enhance productivity, SVA adoption increased front-desk calls by 19%, driven by frictions in voice-controlled amenities. This effect is most pronounced among older guests and those in premium rooms. Sentiment analysis of call transcripts reveals a decline in guest satisfaction, concentrated among younger rather than older guests, alongside negative spillovers into housekeeping and repair requests. Our results provide empirical evidence that adjustment costs, specifically user learning and interface frictions, can diminish the short-run productivity gains of general-purpose technologies in the service sector.

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北大经院工作坊第1279场

Offline and Online Classification Learning under Selective Labels

 计量、金融和大数据分析工作坊 

主讲人：

Xiaojie Mao(Associate Professor in Management Science and Engineering at Tsinghua University)

主持老师：

（北大国发院）沈艳

参与老师：

（北大经院）王一鸣、王熙、刘蕴霆、王法、李少然、巩爱博

（北大国发院）黄卓、张俊妮

时间：

2026年5月8日（周五）

10：00-11:30

地点：

北京大学国家发展研究院承泽园131教室

主讲人简介：

Xiaojie Mao is an associate professor in Management Science and Engineering at Tsinghua University. He did his undergraduate in Mathematical Economics at Wuhan University and Ph.D. in Statistics and Data Science at Cornell University. His research interest lies in causal inference and data-driven decision-making. His research has appeared in top journals and conferences across multiple fields, such as Operations Research, Information Systems Research, Management Science, Journal of Machine Learning Research, Journal of the Royal Statistical Society Series B, NeurIPS, ICML, COLT, etc.

摘要：

The problem of selective label observations is common in many decision-making applications involving human subjects. In these applications, whether an individual’s outcome label can be observed depends on a certain decision. For example, in lending, the default status of a loan applicant cannot be observed if the loan is not approved, creating selection bias in labeled data. The selective label problem presents significant challenges for developing effective machine learning algorithms. In this talk, I will present our research on learning classifiers from selectively labeled data in both offline and online settings. In the offline setting, we follow the existing literature and consider selective labels arising from the decisions of multiple heterogeneous decision-makers. We formalize this setup through an instrumental variable framework, provide principled identification analysis, and propose a cost-sensitive learning algorithm to tackle the selective label problem. In the online setting, we additionally consider individuals’ strategic behaviors of manipulating their features to achieve favorable classification (e.g., get loan approval). We propose an online optimization algorithm to learn linear classifiers under both selective labels and strategic manipulation. We further prove that the expected regret of this algorithm is sublinear.

供稿：科研与博士后办公室

美编：初夏

责编：度量、雨禾、雨田