讲座题目：Offline Policy Evaluation with Endogenous Network Effects with Applications for Live-Streaming Data
内容摘要：We study offline policy evaluation for assessing promotion effects in online livestreaming sessions with competing network interactions. To model such dependence, we adopt a partial linear spatial autoregression (PL-SAR) model, where promotional actions follow a behavior policy, network interference propagates through a spatial autoregressive term, and covariate effects are captured nonparametrically using machine learning methods. To estimate the average value of a target policy, we propose a Network-Directional Targeted Debiasing Estimation (NTDE) procedure that corrects the plug-in bias of an initial estimator by accounting for the propagation of perturbations through the network structure. We establish valid statistical inference under suitable initial estimation rates. For random covariates, we address a key theoretical challenge involving a network-dependent V-statistic of diverging order and reduce the asymptotic variance through exploiting the empirical distribution of the covariates. We apply the proposed method to a multimodal live-streaming dataset, estimate competing effects among sessions featuring automobiles from the same brand, and evaluate a holiday promotion policy. The results show stronger promotion effects near the holiday, followed by a cost-benefit analysis based on the estimated policy value.
主讲人简介：朱雪宁，复旦大学管理学院副教授，博士生导师。主要研究领域为网络数据分析、空间计量模型、高维数据建模等，研究成果发表于Journal of Econometrics, Annals of Statistics, Journal of the American Statistical Association等国际顶级期刊。2022年获国家自然科学基金优秀青年基金项目支持。担任全国工业统计学教学研究会青年统计学家协会副会长，中国现场统计研究会统计调查分会常务理事、STAT期刊副主编等职务。
报告时间：2026年9月15日(周二)，14:30-16:00
线下地点：厦门大学经济楼C108
线上地点：腾讯会议 ID：390 721 929
