讲座主题：Big Push Toward Big Data

主讲嘉宾：李金璞 清华大学社会科学学院 博士研究生

讲座时间：2026年10月8日（周四）18:40

讲座地点：中央财经大学沙河校区学院楼11号楼308

嘉宾简介：李金璞，清华大学社会科学学院经济学研究所博士生，主要研究方向为数据与人工智能经济、宏观金融，关注数据资产化如何影响企业决策与企业动态、资源配置和社会福利，以及智能经济背景下的政策设计。以第一作者或通讯作者在《管理世界》、《经济学（季刊）》、China & World Economy等中英文期刊发表多篇文章，同时有多篇文章在国内外一流期刊返修。工作论文入选AEA、INFORMS Annual Meeting、CICM等学术会议。

内容摘要：Economic activity generates data, those data improve forecasts, and better forecasts raise activity. Individual firms' data-processing decisions can also respond to economic activity and the behavior of other firms. This paper studies when these feedbacks become a macroeconomic data flywheel. Firms learn about persistent demand from raw data generated by economy-wide activity or by their own operations, and they choose how effectively to convert those data into usable signals. We show that multiple steady states can exist and that the economy can become stuck in a low-production, low-data trap. A Big Push policy supplies public signals at a labor cost and has state-dependent crowd-in and crowd-out effects. Provision crowds in private activity when endogenous information is scarce but crowds it out once information is abundant. A permanent push can eliminate the low-data state while drawing productive labor away from the surviving high-data state. A temporary push of sufficient strength and duration can lead the economy out of the low-data trap.