微观经济与数字经济教研室学术讲座

报告题目：Decoding China's Industrial Policies
报  告 人：李明（香港中文大学（深圳）经管学院 助理教授）
主  持 人：沙文彪（中山大学岭南学院 助理教授）
时      间：2025年11月28日（周五）下午14:30
地      点：MBA大楼601
语      言：中英文

摘要：

      We decode China’s industrial policies from 2000 to 2022 by employing large language models (LLMs) to extract and analyze rich information from a comprehensive dataset of 3 million documents issued by central, provincial, and municipal governments. Through careful prompt engineering, multistage extraction and refinement, and rigorous verification, LLMs allow us to extract structured information on detailed policy dimensions, including context and scope, targeted industries, tools, implementation mechanisms, and intergovernmental relationships, etc. Combining these newly constructed industrial policy data with microlevel firm data, we document a set of key facts about China's industrial policy that explore the following critical questions. What are the economic and political foundations of the targeted industries? What policy tools are deployed? How do policy tools vary between different levels of government and between regions, as well as over the development phases of an industry? What is the impact of these policies on firm behavior, including entry, production, and productivity growth? In addition, we explore the political economy of industrial policy, focusing on top-down transmission mechanisms, policy diffusion, and persistence across regions. Finally, we document spatial inefficiencies and industry-wide overcapacity as potential downsides of industrial policies.

报告人简介：

      Ming Li is an Assistant Professor of Economics at the Chinese University of Hong Kong, Shenzhen. Her research interests cover topics of the Chinese economy, political economy, and urban economics. Her current research focuses on industrial policy, internal migration and trade, and the political economy of firm dynamics in China. She received the Bachelor's degree in Finance from Peking University and Ph.D. in Economics from the University of Pennsylvania.

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