现代产业经济学系列讲座第212期

时间：2021年12月1日（周三）13:30-15:00

地点：复旦大学管理学院史带楼303室

题目：Self-fulfilling Bandits: Dynamic Selection in Algorithmic Decision-making

主讲人：罗晔 香港大学经济与工商管理学院 副教授

主持人：李玲芳复旦大学管理学院 教授

腾讯会议链接：https://meeting.tencent.com/dm/rspMqGVecLMi

会议号：189 720 504

会议密码：086309

摘要：This paper identifies and addresses dynamic selection problems that arise in online learning algorithms with endogenous data. In a contextual multi-armed bandit model,we show that a novel bias (self-fulfilling bias) arises because the endogeneity of the data influences the choices of decisions, affecting the distribution of future data to be collected and analyzed. We propose a class of algorithms to correct for the bias by incorporating instrumental variables into leading online learning algorithms. These algorithms lead to the true parameter values and meanwhile attain low (logarithmic-like) regret levels.We further prove a central limit theorem for statistical inference of the parameters of interest. To establish the theoretical properties, we develop a general technique that untangles the interdependence between data and actions.

主讲人简介：罗晔，2015年于美国麻省理工学院获得经济学博士学位，2010年同样于美国麻省理工学院获得数学与经济学学士学位。现任香港大学经济与工商管理学院终身副教授，加入香港大学之前曾于2015-2018在美国佛罗里达大学经济系任助理教授。罗晔博士的主要研究方向包括:高维计量经济学与统计学，机器学习理论与经济金融中的应用，如量化交易，风险管理等等。罗晔博士在不同国际杂志上发表/接受十余篇论文，包括Econometrica，Journal of the Royal Statistical Society: Series B, Journal of Machine Learning Research，等等。此外，罗晔博士有多项在大数据和人工智能算法方面与业界的实践与合作经验，包括滴滴出行，京东，顺丰，建设银行，华为，Novartis, BMW, Alianz等等。

现代产业经济学系列讲座第213期

时间：2021年12月7日10:00-11:30

地点：在线讲座

题目：Adaptation to Temperature Extremes in Chinese Agriculture, 1981 to 2010

主讲人：王 迪中国农业大学助理教授

主持人：沈煌南复旦大学管理学院 助理教授

会议链接：https://meeting.tencent.com/dm/3edF4IzYyhib

腾讯会议号：638 932 104会议密码：366720

摘要：Temporal evolution of extreme temperature effects on agriculture is important for understanding adaptation to climate change but has not been sufficiently studied. This study examines the time-varying impacts of extreme temperatures on Chinese agriculture over 1981 to 2010. We estimate a period-specific panel regression model using nationwide county-level agriculture production data combined with fine-scale meteorological data. There are two primary findings. First, crop yields have become more heat-resilient over time. The impact of a daily exposure to extreme temperatures on corn and soybean yields in the post-1996 period is 40% to 50% less than that in the pre-1996 period. Second, estimation of marginal adaptation effects of inputs points to irrigation as the central input for adaptation among the inputs that can be observed in our data. The expansion of irrigation coverage over time accounts for 25% to 30% of the decline in the extreme temperature impacts.

主讲人简介：Di Wang is an Assistant Professor of Economics at China Agricultural University. His main research areas are environmental, agricultural and development economics. He is currently interested in adaptation to climate change and economic drivers of pollution in China. He completed his Ph.D. in economics at the University of California, Santa Barbara in 2021.