Abstract：This paper aims to detect structural break points in latent networks in a panel data setting. We consider panel models where the outcome of a unit depends on the outcomes and characteristics of other units. The latent network structure induces high-dimensional parameters and interactive outcomes generate endogeneity. Our goal is to detect breaks in high-dimensional network parameters associated with endogenous variables. We propose a two-step penalized nonlinear least squares approach to estimate the break points based on reduced forms, and show that the resulting estimator achieves superconsistency. This property allows us to estimate, and make inferences on, network and slope parameters as if the true break points were known

主讲人Speaker:赵山 副教授 香港城市大学时间Date & Time:2025年3月25日（周二），下午14:00--15:30地点Venue:粤海校区汇星楼565会议室内容简介/ Abstract:We examine the impact of investment banking business ties on mutual fund proxy voting decisions in shareholder meetings. Controlling for a comprehensive set of saturated fixed effects, we find robust evidence that fund families are more likely to vote ...

主讲人Speaker:易君健 特聘教授 北京大学时间Date & Time:2025年1月14日（周二），上午10:30--12:00地点Venue:粤海校区汇星楼565会议室内容简介/ Abstract:A marked feature of health insurance plan choice is inconsistent choices through the overweighting of premiums relative to out-of-pocket spending. We show that this source of inconsistency disappears when both types of spending come from the same sourc...

主讲人Speaker:于涵 副教授 南洋理工大学计算与数据科学学院时间Date & Time:2025年1月8日（周三），下午15:00--16:30地点Venue:粤海校区汇星楼565会议室内容简介/ Abstract:大型模型的兴起突显了联邦学习作为关键研究方向的重要性和相关性。随着大型模型成为机器学习开发的主流，研究重点从模型架构设计转向解决与隐私保护和分布式学习相关的问题。联邦学习方法的进步有潜力释放大型模型的价值，实现高效且可扩展的训练，同时...

Abstract:  This study provides the first in-depth analysis of concentrated liquidity provision (CLP) strategies in decentralized finance (DeFi). We compile a comprehensive dataset of all CLP positions and trades on the Ethereum blockchain, ...