数据简介 在中国推进制造业与互联网融合、促高质量发展的政策背景下，评估政策对企业影响成重要课题。本数据基于 国家试点政策，构建适用于双重差分法的准自然实验数据集，以2007 – 2024年中国制造业非ST上市公司为样 本，识别试点企业，生成核心处理变量"treat"（企业被认定试点当年及之后取1，否则取0），为评估政策因果效 应提供数据支撑。该变量可构建政策交互项，识别政策对企业关键指标影响。数据集整理了试点企业基本信 息，具结构化与标准化特征。利用该数据集，可评估政策影响、分析效应异质性、检验中介机制有效性，为政 府和企业提供经验依据。 数据名称：上市公司-制造业与互联网融合DID 数据年份：2007-2024年 数据范围：制造业上市公司 参考文献：[1]周科选,罗学强."虚实融合"如何赋能中国制造企业高质量发展—来自制造业与互联网融合发展试点 的证据[J].企业经济 数据指标 股票代码 股票简称 年份 行业名称 中文名称 treat 数据截图 获取见 | 股票代码 ▼ | 股票简称 ▼ | 年份 | ▼ 行业名称 | ▼ 中文名称 | ▼ P treat | | --- | --- | --- | --- ...

Core Insights - The article discusses the importance of evaluating the impact of policies promoting the integration of manufacturing and the internet on the development of enterprises in China, particularly in the context of high-quality growth [1][2]. Group 1: Policy Impact Assessment - A dataset has been constructed to assess the causal effects of the pilot policies on enterprises' high-quality development, focusing on non-ST listed manufacturing companies in China from 2007 to 2024 [1]. - The core variable "treat" is defined as 1 if a company is recognized as a pilot unit for the integration of manufacturing and the internet in a given year, and 0 otherwise, allowing for the construction of a Difference-in-Differences (DID) model [1][2]. Group 2: Research Applications - Researchers can utilize this dataset to evaluate the effects of the pilot policy on high-quality development, analyze heterogeneity across different regions, company sizes, and ownership types, and test the effectiveness of various mediating mechanisms such as information, funding, and human capital channels [2]. Group 3: Data Characteristics - The dataset includes essential information such as stock codes, abbreviations, full names, industry classifications, and the treatment variable, ensuring a structured and standardized format for analysis [3][4].