北大经院工作坊第848场
Learning with Uncertain Signal Structure
微观理论经济学工作坊
主讲人：闵炜程（上海交通大学安泰经济与管理学院助理教授）
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：2024年4月11日（周四）10:30-12:00
地点：北京大学经济学院302会议室
主讲人简介：
Weicheng received his Ph.D. in Economics from Yale University in 2022 and is currently an Assistant Professor at Antai College of Economics and Management. Prior to this, he received a Bachelor’s degree from Fudan University and a Master’s degree from London School of Economics and Political Science. He is primarily interested in microeconomic theory and behavioral economics, with special emphasis on information economics and bounded rationality.
摘要：
A decision-maker repeatedly chooses between a familiar source and an unfamiliar source to learn a persistent fundamental. When the signal structure of the unfamiliar source is also uncertain, the learning problem is two-dimensional. Moreover, the two dimensions become naturally correlated as the decision-maker chooses the unfamiliar source over time. This paper makes a novel observation that it is the correlation, instead of the marginal belief over the uncertain signal structure, that determines the expected informativeness of the unfamiliar source. Based on this observation, this paper characterizes the decision-maker's asymptotic choice of source and obtains a counterintuitive result: for any (full-support) joint prior, the decision-maker may settle on the familiar source almost surely, even if the true signal structure of the unfamiliar source Blackwell dominates that of the familiar source. As an implication, this result explains the well-documented preference towards familiarity or status quo from a rational perspective.
北大经院工作坊第849场
The Spillover Effect of China's Outpatient Cost-sharing Policy on the Hospitalization Sector
风险、保险与不确定性经济学工作坊
主讲人：郭淼（湖南大学金融与统计学院助理教授）
主持老师：
（人大财金）陈泽
（北大经院）贾若
（清华经管）冯润桓
参与老师：
（人大财金）魏丽
（北大经院）郑伟
时间：2024年4月11日（周四）15：00-16：30
线上形式：腾讯会议
会议号：629 467 969
线下地点：中国人民大学明德主楼515A
主讲人简介：
郭淼，湖南大学金融与统计学院助理教授，研究方向为卫生经济学、保险经济学、以及社会保障。曾在European Journal of Health Economics、SSM – Population Health等期刊发表数篇研究论文。
摘要：
China has encountered a rapid growth in inpatient utilization and expenditure in the past decade, primarily attributed to an insufficient reimbursement scheme for outpatient services. This study investigates the impact of China's outpatient cost-sharing policy on inpatient expenditures. Leveraging a quasi-experimental design centered on the outpatient mutual-aid mechanism, we employ a difference-in-difference methodology to analyze the policy effect. Using hospital inpatient records, our evaluation indicates a notable decrement in both total and out-of-pocket inpatient expenditures. This effect is pronounced in cases involving Ambulatory Care Sensitive Conditions, underscoring the potential for primary care to preempt unnecessary hospital admissions. Furthermore, our findings suggest that the reductions in expenditure are larger for patients aged over 60, alongside an elevated responsiveness within tertiary hospital cohorts.
北大经院工作坊第850场
Data-driven Policy Learning for a Continuous Treatment
数字经济学工作坊
主讲人：张勋（北京师范大学统计学院金融统计系教授）
主持老师：（北大经院）李博
时间：2024年4月11日（周四）13:30-14:50
地点： 北京大学经济学院302会议室
主讲人简介：
张勋，北京师范大学统计学院金融统计系教授，博士生导师，北京大学数字金融研究中心特约高级研究员，入选2022年度教育部长江学者特聘教授。目前担任北京师范大学财经处副处长（挂职）。主要研究领域为数字经济与数字金融、区域经济和发展经济学，在《中国社会科学》、《经济研究》、《管理世界》、《统计研究》、《经济学（季刊）》以及Journal of Banking & Finance、Journal of Population Economics、World Development等期刊发表论文70余篇，全球经济学与商学领域前1% ESI高被引论文作者。主持承担国家社科基金重点项目，国家自然科学基金面上和青年项目，青年项目在绩效评估中被评为“特优”。曾获霍英东教育基金会高等院校青年科学奖、教育部高等学校科学研究优秀成果奖、张培刚发展经济学青年学者奖、洪银兴经济学奖（青年）和商务部商务发展研究成果奖等多项学术奖项。
北大经院工作坊第851场
Data-driven Policy Learning for a Continuous Treatment
计量、金融和大数据分析工作坊
主讲人：解海天（北京大学光华管理学院助理教授）
主持老师：（北大经院）王熙
参与老师：
（北大经院）王一鸣、王法、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：2024年4月12日（周五） 10:00-11:30
地点： 北京大学经济学院606会议室
主讲人简介：
解海天，2023年毕业于美国加州大学圣地亚哥分校。主要研究方向为因果推断理论，包括工具变量、断点回归等因果推断方法的非参数/半参数识别与估计，以及基于因果模型的政策分析评估、策略学习与统计决策等。研究成果发表于Journal of Business and Economic Statistics, Oxford Bulletin of Economics and Statistics等国际期刊。
摘要：
This paper studies policy learning under the condition of unconfoundedness with a continuous treatment variable. Our research begins by employing kernel-based inverse propensity-weighted (IPW) methods to estimate policy welfare. We aim to approximate the optimal policy within a global policy class characterized by infinite Vapnik-Chervonenkis (VC) dimension. This is achieved through the utilization of a sequence of sieve policy classes, each with finite VC dimension. Preliminary analysis reveals that welfare regret comprises of three components: global welfare deficiency, variance, and bias. This leads to the necessity of simultaneously selecting the optimal bandwidth for estimation and the optimal policy class for welfare approximation. To tackle this challenge, we introduce a semi-data-driven strategy that employs penalization techniques. This approach yields oracle inequalities that adeptly balance the three components of welfare regret without prior knowledge of the welfare deficiency. By utilizing precise maximal and concentration inequalities, we derive sharper regret bounds than those currently available in the literature. In instances where the propensity score is unknown, we adopt the doubly robust (DR) moment condition tailored to the continuous treatment setting. In alignment with the binary-treatment case, the DR welfare regret closely parallels the IPW welfare regret, given the fast convergence of nuisance estimators.
北大经院工作坊第852场
Paving the Green Tracks:The Environmental Impact of Heavy-haul Railways in China
生态、环境与气候变化经济学工作坊
主讲人：谭娅（对外经济贸易大学国际经济贸易学院助理教授）
时间：2024年4月12日（周五）10:00-12:00
地点：北京大学经济学院101会议室
主讲人简介：
谭娅，对外经济贸易大学国际经济贸易学院助理教授，2016年于北京大学光华管理学院获经济学博士学位，2018-2020年作为博雅博士后在北京大学进行科研工作。主要研究领域为区域与城市经济学、公共经济学。在Journal of Urban Economics，iScience，Journal of Cleaner Production,《金融研究》，《经济学(季刊)》，《世界经济》等国内外期刊发表论文20余篇。
摘要：
This paper studies how heavy-haul railways affect the environmental outcomes of air pollution. We exploit the large-scale progressive expansion of three heavy-haul railways in China as a quasi-natural experiment and construct a difference-in-difference model to identify its effect on air pollutants both along the heavy-haul railway itself and along the road transportation routes for coal that have been partly replaced by the heavy-haul railways. The results show that heavy-haul railway transportation is an environmentally clean mode of transportation. The substitution of road transport with heavy-haul railways leads to a decrease in air pollution within the counties traversed by key roads previously used for coal transportation. This shift results in a 1.5 percent reduction in PM2.5 in the area along these roads. The concentrations of other air pollutants, such as PM1, PM10, and NO2, which are mainly emitted by heavy-duty trucks transporting coal, have also been significantly reduced. In addition, “road-to-rail” has promoted the clustering of clean industries such as services and high-tech industries along the original transportation roads. The back-of-envelope calculations suggest significant economic benefits resulting from the health outcomes brought by the reduction of pollutant concentration. Our findings shed light on the contribution of freight railways to the reduction of air pollution and reveal the importance of the “road-to-rail” transportation transformation.
北大经院工作坊第853场
Judicial Transparency and Economic Development: Evidence from China
国际经济学与实证产业组织工作坊
主讲人：刘政文（北京大学经济学院助理教授）
主持老师：（北大经院）莫家伟
参与老师：
（北大经院）刘冲、田巍、袁野、吴群锋、曹光宇、庄晨
（北大新结构）王歆、徐铭梽
时间：2024年4月12日（周五）10：00-11：30
地点：北京大学经济学院305会议室
主讲人简介：
刘政文，北京大学经济学院助理教授，主要研究领域为公共经济学、国际经济学和实证产业组织。研究成果发表于Economic Inquiry，Structural Change and Economics Dynamics，Review of Policy Review，《经济评论》，《经济学报》等国内外期刊。
摘要：
This paper investigates the role of judicial transparency in driving economic development using a transparency reform in China. Starting from mid-2013, China has mandated that all courts upload judicial documents online; however, there are significant disparities in compliance levels among different regions. We find that provinces with greater improvements in judicial transparency have experienced more substantial growth in industrial outputs, the registration of new firms, and exports. This growth in outputs is mainly driven by output per worker rather than a surge in the workforce. Exploring industry heterogeneity strengthens the identification. Industries with higher judicial dependence exhibit larger growth in output and exports after the improvement in judicial transparency.
北大经院工作坊第854场
中国投入产出核算简介及国民经济核算新趋势
宏观经济学工作坊
主讲人：陈杰（国家统计局国民经济核算司副司长）
主持老师：（北大经院）李博
参与老师：
（北大经院）陈仪、韩晗、李伦
（北大国发院）赵波、余昌华、李明浩
时间：2024年4月12日（周五）10:00-11:30
地点：北京大学国家发展研究院承泽园246教室
主讲人简介：
陈杰，国家统计局国民经济核算司副司长，中国投入产出学会副理事长，高级统计师。长期从事国民经济核算有关工作，特别是GDP核算和投入产出核算。参与了多个年份中国投入产出表的编制，及APEC贸易增加值核算等有关工作。主要研究领域包括国民经济核算理论、投入产出分析、全要素生产率测算等。
摘要：
结合中国核算工作实践，介绍中国投入产出表特别是非竞争型表的编制情况及其意义；结合目前国际上对2008年SNA开展修订的情况，简介国民经济核算理论新趋势和新发展。
供稿：科研与博士后办公室
美编：薏米
责编：度量、雨禾、雨田
