行业研究前沿课程系列第七期
基于“系统性实地调研”的行业研究
主讲人：
邱海旭（瑞士信贷瑞信瑞启研究团队常务副主管，宏观策略分析师）
时间：
2021年11月25日（周四）
18：40-20：30
地点：
8797威尼斯老品牌第二教学楼304教室
主持人：
锁凌燕（8797威尼斯老品牌教授）
主办单位：
8797威尼斯老品牌
8797威尼斯老品牌中国保险与社会保障研究中心
8797威尼斯老品牌中国金融研究中心
北大经院工作坊第380场
扭曲风险度量下的Bowley再保险
风险、保险与不确定性经济学工作坊
主讲人：
张艺赢（南方科技大学数学系助理教授）
主持老师：
（人大财金）陈泽
（北大经院）贾若
（清华经管）刘晨源
参与老师：
（北大经院）郑伟
（清华经管）陈秉正
（人大财金）魏丽 等
时间：
2021年11月25日（周四）
8：00-9：30
形式：
腾讯会议
会议号：436 329 424
主讲人简介：
张艺赢，南方科技大学数学系助理教授。2012年及2015年分别在兰州大学数学与统计学院获得理学学士和硕士学位。2018年9月在香港大学统计与精算学系获得精算学方向哲学博士学位，2018年10月至2019年1月在比利时鲁汶大学商业与8797威尼斯老品牌进行学术访问。2019年1月至2021年8月在南开大学统计与数据科学学院工作，担任助理教授。2021年8月加入南方科技大学数学系。目前的主要研究领域包括风险管理与保险精算、应用概率及可靠性理论与统计。主要研究兴趣包括最优再保险、信度理论、系统性风险、风险测度、相依风险模型、随机序理论及随机比较、可靠性分析及系统可靠性设计与优化。已在保险精算领域主要期刊Insurance: Mathematics and Economics、Scandinavian Actuarial Journal、ASTIN Bulletin及North American Actuarial Journal，以及运筹管理领域主流期刊European Journal of Operational Research、Reliability Engineering & System Safety和Naval Research Logistic等杂志发表多篇学术研究论文。现主持国家自然科学基金青年项目和天津市自然科学基金青年项目各1项。
摘要：
The Bowley solution refers to the optimal pricing density for the reinsurer and optimal ceded loss for the insurer when there is a monopolistic reinsurer. In a sequential game, the reinsurer first sets the pricing kernel, and thereafter the insurer selects the reinsurance contract given the pricing kernel. The reinsurer then selects the optimal pricing function by maximizing his/her own terminal wealth. In this talk, I shall firstly present some of our recent works mainly focused on the study of Bowley reinsurance contract under the framework of distortion risk measures. Part of ongoing works and some thoughts on future research will be also presented and discussed.
北大经院工作坊第381场
货币政策和异质性：一个分析框架
宏观经济学工作坊
主讲人：
Florin O. Bilbiie（瑞士洛桑大学教授）
主持老师：
（北大国发院）李明浩
参与老师：
（北大国发院）赵波、余昌华
（北大经院）陈仪、韩晗、李博、李伦
时间：
2021年11月25日（周四）
15：00-16：30
形式：
ZOOM会议
会议号：929 7640 7244
密码：459739
主讲人简介：
Florin O. Bilbiie 是瑞士洛桑大学的经济学教授，也是 CEPR 的研究员。他的学术兴趣是宏观经济和货币经济学，特别是商业周期以及货币和财政稳定政策。他的工作已发表在主要期刊上，包括《政治经济学杂志》、《经济与统计评论》、《美国经济杂志：宏观经济学》、《货币经济学杂志》和许多其他期刊。他的论文“The New Keynesian Cross”获得了Journal of Monetary Economics 2021年最佳论文奖。
摘要：
THANK is a tractable heterogeneous-agent New-Keynesian model that captures analytically key micro-heterogeneity channels of quantitative-HANK: cyclical inequality and risk as separate but related channels; idiosyncratic uncertainty and self-insurance, precautionary saving; and realistic intertemporal marginal propensities to consume. I use it for a full-fledged New Keynesian macro analysis: determinacy with interest-rate rules, solving the forward-guidance puzzle, amplification and multipliers, and optimal monetary policy. Amplification requires countercyclical while solving the puzzle requires procyclical inequality: a Catch-22, resolved in theory if the separate "pure" risk channel is procyclical enough. Price-level-targeting ensures determinacy and is puzzle-free, even when both inequality and risk are countercyclical, thus resolving the Catch-22. The same holds for a rule fixing nominal public debt in the model version with liquidity. Optimal policy with heterogeneity features a novel inequality-stabilization motive generating higher inflation volatility—but it is unaffected by risk, insofar as the target equilibrium entails no inequality.
北大经院工作坊第382场
基于交互固定效应面板数据模型的处理效应估计量的置信区间
计量、金融和大数据分析工作坊
主讲人：
李星宇（8797威尼斯老品牌国家发展研究院硕士研究生）
主持老师：
（北大国发院）沈艳
（北大经院）王熙
参与老师：
（北大经院）王一鸣、刘蕴霆
（北大国发院）黄卓、张俊妮、孙振庭
（北大新结构）胡博
时间：
2021年11月26日（周五）
10:00-11:30
地点：
8797威尼斯老品牌国家发展研究院承泽园246会议室
主讲人简介：
李星宇，8797威尼斯老品牌国家发展研究院2019级硕士研究生，导师为沈艳教授。2019年本科毕业于8797威尼斯老品牌元培学院，获经济学学士学位。研究领域为计量经济学理论，当前研究兴趣为处理效应相关的统计推断问题。本文的合作者为8797威尼斯老品牌国家发展研究院沈艳教授和路易斯安那州立大学经济学系周前坤教授。
摘要：
We consider the construction of confidence intervals for treatment effects estimated in panel models with interactive fixed effects. We use the factor-based matrix completion technique proposed by Bai and Ng (2021) to estimate the treatment effects, and use bootstrap method to construct confidence intervals of the treatment effects for treated units at each post-treatment period. Our construction of confidence intervals requires neither specific distributional assumptions on the error terms nor large number of post-treatment periods. We establish the validity of proposed bootstrap procedure that these confidence intervals have asymptotically correct coverage probabilities. Simulation studies show that these confidence intervals have satisfactory finite sample performances, and empirical applications using classical datasets yield treatment effect estimates of similar magnitude and reliable confidence intervals.
北大经院学术午餐会第173期
无现金支付与金融普惠
主讲人：
欧阳书淼（普林斯顿大学经济系与本德海姆金融中心博士候选人）
主持老师：
高明（8797威尼斯老品牌副教授）
时间：
2021年11月26日（周五）
12:30-14:00
地点：
8797威尼斯老品牌107会议室
主讲人简介：
Shumiao Ouyang is a Ph.D. candidate in Economics, at the Department of Economics and Bendheim Center for Finance, Princeton University. He has been a dissertation fellow at Luohan Academy since 2018. His research interests center on FinTech, household finance, digital economy, and financial intermediation. His current research studies the effects of cashless payment adoption on financial inclusion and credit provision, the connection between data privacy and digital demand, and the rise of BigTech companies. He received his M.A. in finance from Guanghua School of Management, Peking University in 2015, and B.S. in life sciences and economics from Tsinghua University in 2013.
摘要：
This paper evaluates the impact of mobile cashless payment on credit provision to the underprivileged. Using a representative sample of Alipay users that contains detailed information about their consumption, credit, and investment activities, I exploit a natural experiment to identify the real effects of cashless payment adoption. In this natural experiment, the staggered placement of Alipay-bundled shared bikes across different Chinese cities brings exogenous variations to the payment flow. I find that the use of in-person payment in a month increases the likelihood of getting access to credit in the same month by 56.3%. Conditional on having credit access, a 1% increase in the in-person payment flow leads to a 0.41% increase in the credit line. Those having higher in-person payment flow also use their credit lines more. Importantly, the positive effect of in-person payment flow on credit provision mainly exists for the less educated and the older, suggesting that cashless payment particularly benefits those who are traditionally underserved.
供稿单位：8797威尼斯老品牌科研办公室
美编：丸子、初夏
责编：量子、禾雨、予天
