Please wait a minute...
金融研究  2026, Vol. 554 Issue (8): 114-131    
  本期目录 | 过刊浏览 | 高级检索 |
监管一体化对上市公司绩效的影响——来自中央法规文本分析的证据
何青, 姚天宇, 蒋东明
The Impact of Regulatory Integration on Listed Firm Performance: Evidence from Textual Analysis of Central Laws and Regulations
HE Qing, YAO Tianyu, JIANG Dongming
School of Finance/Center for Financial Policy Studies, Renmin University of China
下载:  PDF (1075KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 基于我国2007年至2023年颁布的33万多条中央法规文件,本文运用潜在狄利克雷分配算法(LDA),同时结合大语言模型,提取并定义了99个监管议题,进而在中国上市公司年报文本基础上构建了企业层面的监管一体化程度指标。总体而言,上市公司的监管一体化程度在2013年后呈现出稳步提升的态势。实证结果表明,监管一体化显著提高了企业的经营绩效;在数字化转型水平较高的地区和非国有企业中,监管一体化的积极效应更为显著;机制分析表明,监管一体化降低了企业的经营成本和合规成本、减少了监管不一致性、提高了研发创新能力,从而提升了企业的经营绩效。本文研究对提高监管效率、推进全国统一大市场建设具有参考价值。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
()
作者相关文章
何青
姚天宇
蒋东明
关键词:  监管一体化  经营绩效  LDA算法  企业创新    
Summary:  Market regulation is a key instrument through which governments shape the institutional environment for firms. In China, recent reforms have emphasized a unified national market, integrated regulatory standards, and cross-departmental supervision. This paper examines whether regulatory integration improves the performance of listed firms. Regulatory integration is defined as the coordination and unification of rule-making, agency responsibilities, enforcement standards, administrative procedures, and information sharing within a specific regulatory topic. It differs from deregulation: it does not imply weaker oversight, but captures whether regulation is organized in a more coherent, predictable, and less duplicative manner.
  This paper constructs a novel firm-year measure of regulatory integration using large-scale regulatory and corporate texts. First, it manually collects 338,403 central regulatory documents issued between 2007 and 2023 from the PKUlaw database. These documents represent the common institutional baseline faced by firms nationwide and reveal how regulatory authority is allocated among central agencies. Second, annual reports of listed firms are used to measure each firm's exposure to various regulatory topics. The paper applies the Latent Dirichlet Allocation (LDA) topic model to regulatory texts and uses large language models to annotate and label the topics, identifying 99 regulatory topics.
  For each topic, integration is measured by the distribution of that topic across drafting agencies. A topic concentrated in a small number of agencies indicates more integrated authority and lower coordination costs, whereas a topic associated with many agencies suggests fragmented oversight and greater potential for duplication or inconsistency. The firm-year regulatory integration index is constructed by weighting topic-level integration scores by each firm's topic exposure derived from annual reports. After merging this measure with CSMAR financial data and excluding ST and *ST firms, the final sample contains 45805 firm-year observations of 5,323 listed firms from 2007 to 2023. Descriptive evidence shows that regulatory integration increased steadily after 2013, declined temporarily during the COVID-19 pandemic shock, and then recovered quickly.
  The baseline regressions examine the effect of lagged regulatory integration on firm performance, measured by return on assets (ROA) and sales growth. The models control for firm-level characteristics and include firm fixed effects and industry-by-year fixed effects, with standard errors clustered at the firm level. The results show that regulatory integration significantly improves firm performance. A one-standard-deviation increase in regulatory integration is associated with an approximately 16.74% increase in ROA and a 34.03% increase in sales growth. These findings remain robust after excluding the COVID-19 pandemic period, replacing key variables, changing LDA topic numbers and model specifications, and adding controls.
  The paper further addresses potential endogeneity concerns. It constructs an instrumental variable by fixing each firm's topic weights at the values observed in its first sample year and combining these baseline weights with time-varying topic-level integration. The instrumental-variable results are consistent with the baseline estimates. The paper also uses the 2018 State Council policy on accelerating the construction of a national integrated online government-service platform as a policy shock, showing that firms initially exposed to lower regulatory integration experience significant performance improvements after the policy.
  Heterogeneity tests show that the effect of regulatory integration is stronger in cities with better digital infrastructure, as measured by the Broadband China pilot program, and stronger for non-state-owned enterprises. Digital infrastructure facilitates information sharing and coordinated supervision, while non-state-owned firms benefit more from reductions in fragmented supervision, repeated reporting, and inconsistent standards.
  Mechanism tests indicate that regulatory integration improves performance by reducing operational and compliance costs, increasing regulatory consistency, and promoting innovation. It lowers administrative expense ratios and compliance-related hiring, increases the semantic similarity of regulatory texts issued by different agencies within the same topic, and raises R&D intensity and patent applications. Additional analysis shows that regulatory integration reduces regulatory penalties and litigation and increases firms' distance to default.
  This paper contributes by developing a firm-level measure of regulatory integration tailored to China's institutional setting, showing that an integrated regulatory framework can enhance firm performance, and providing evidence for reforms aimed at streamlining administration and strengthening cross-departmental supervision. The findings suggest that China should continue to unify regulatory items, data standards, reporting requirements, and enforcement discretion, while investing in digital regulatory infrastructure and providing targeted compliance guidance for non-state-owned firms.
Keywords:  Regulatory Integration    Firm Performance    LDA Algorithm    Corporate Innovation
JEL分类号:  G38   L51   D78  
基金资助: * 本文感谢国家自然科学基金资助项目(72473146)、中央高校基本科研业务费专项资金资助项目(24XNN005)的资助。感谢匿名审稿人的宝贵意见,文责自负。
通讯作者:  姚天宇,博士研究生,中国人民大学财政金融学院,E-mail:tianyuyao@ruc.edu.cn.   
作者简介:  何 青,经济学博士,教授,中国人民大学财政金融学院/中国财政金融政策研究中心,E-mail:qinghe@ruc.edu.cn
蒋东明,博士研究生,中国人民大学财政金融学院,E-mail:jiangdongming@ruc.edu.cn.
引用本文:    
何青, 姚天宇, 蒋东明. 监管一体化对上市公司绩效的影响——来自中央法规文本分析的证据[J]. 金融研究, 2026, 554(8): 114-131.
HE Qing, YAO Tianyu, JIANG Dongming. The Impact of Regulatory Integration on Listed Firm Performance: Evidence from Textual Analysis of Central Laws and Regulations. Journal of Financial Research, 2026, 554(8): 114-131.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2026/V554/I8/114
[1] 蔡庆丰、陈熠辉和林海涵,2021,《开发区层级与域内企业创新:激励效应还是挤出效应?——基于国家级和省级开发区的对比研究》,《金融研究》第5期,第153~170页。
[2] 戴静雯、许荣、祝天琪和陆超,2024,《共同机构所有权与企业诉讼风险》,《金融研究》第4期,第94~112页。
[3] 周广肃和于磊,2025,《地方人才引进政策与家庭教育投资》,《世界经济》第4期,第117~143页。
[4] 何青和刘尔卓,2022,《汇率敏感性会影响企业贷款利率吗?——基于中国上市公司的分析》,《金融研究》第8期,第132~151页。
[5] 江小涓和黄颖轩,2021,《数字时代的市场秩序、市场监管与平台治理》,《经济研究》第12期,第20~41页。
[6] 刘鹏,2017,《中国市场经济监管体系改革:发展脉络与现实挑战》,《中国行政管理》第11期,第26~32页。
[7] 刘淑春,2018,《数字政府战略意蕴,技术构架与路径设计——基于浙江改革的实践与探索》,《中国行政管理》,第9期,第37~45页。
[8] 刘亚平和苏娇妮,2019,《中国市场监管改革70年的变迁经验与演进逻辑》,《中国行政管理》第5期,第15~21页。
[9] 孙森和王玲,2014,《基于KMV-Logit模型的上市公司违约风险实证研究》,《财会月刊》第18期,第64~68页。
[10] 王健和王鹏,2018,《新一轮市场监管机构改革的特点、影响、挑战和建议》,《行政管理改革》第7期,第24~29页。
[11] 杨鹏,孙伟增,田轩和左祥太,2026,《网络安全风险治理与企业创新——基于大语言模型的识别与发现》,《金融研究》第1期,第76~94页。
[12] 于永生,2017,《商业银行会计监管与资本监管冲突根源及化解策略》,《会计研究》第8期,第12~18页。
[13] 赵静梅和何宝露,2025,《企业声誉与违规行为——基于数字经济视角的新考证》,《金融研究》第7期,第76~94页。
[14] Agarwal, S., D. Lucca, A. Seru and F. Trebbi, 2014, “Inconsistent Regulators: Evidence from Banking”,The Quarterly Journal of Economics, 129(2), pp.889~938.
[15] Bharath, S. T. and T. Shumway, 2008, “Forecasting Default with the Merton Distance to Default Model”,The Review of Financial Studies, 21(3), pp.1339~1369.
[16] Bhattacharya, U., P. H. Hsu, X. Tian and Y. Xu, 2017, “What Affects Innovation More: Policy or Policy Uncertainty?”,Journal of Financial and Quantitative Analysis, 52(5), pp.1869~1901.
[17] Bloom, N., S. Bond and J. Van Reenen, 2007, “Uncertainty and Investment Dynamics”,The Review of Economic Studies, 74(2), pp.391~415.
[18] Cejudo, G. M. and C. L. Michel, 2017, “Addressing Fragmented Government Action: Coordination, Coherence, and Integration”,Policy Sciences, 50(4), pp.745~767.
[19] Goldfarb, A., and C. Tucker, 2019, “Digital economics”,Journal of Economic Literature, 57, pp. 3~43.
[20] Houston, J. F., C. Lin, P. Lin and Y. Ma, 2010, “Creditor Rights, Information Sharing, and Bank Risk Taking”, Journal of Financial Economics, 96(3), pp.485~512.
[21] Kalmenovitz, J., 2021, “Incentivizing Financial Regulators”,The Review of Financial Studies, 34(10), pp.4745~4784.
[22] Kalmenovitz, J., M. Lowry and E. Volkova, 2025, “Regulatory Fragmentation”,The Journal of Finance, 80(2), pp.1081~1126.
[23] Kim, S. and S. Kim, 2024, “Fragmented Securities Regulation, Information-Processing Costs, and Insider Trading”,Management Science, 70, pp. 4407-4428.
[24] Nou, J., and J. Nyarko, 2022, “Regulatory diffusion”,Stanford Law Review, 74, pp.897~968.
[25] Pástor, L'. and P. Veronesi, 2013, “Political Uncertainty and Risk Premia”,Journal of Financial Economics, 110(3), pp.520~545.
[26] Rijcken, E., F. Scheepers, K. Zervanou, M. Spruit, P. Mosteiro and U. Kaymak, 2023, “Towards Interpreting Topic Models with ChatGPT”, The 20th World Congress of the International Fuzzy Systems Association.
[27] Rubashkina, Y., M. Galeotti, and E. Verdolini, 2015, “Environmental Regulation and Competitiveness: Empirical Evidence on the Porter Hypothesis From European Manufacturing Sectors”,Energy Policy, 83, pp.288~300.
[28] Trebbi, F. and M. B. Zhang, 2022, “The Cost of Regulatory Compliance in the United States”, NBER Working Paper, No.w30691.
[29] Zhou, K. Z., G. Y. Gao, and H. Zhao, 2017, “State Ownership and Firm Innovation in China: An Integrated View of Institutional and Efficiency Logics”,Administrative Science Quarterly, 62, pp.375~404.
[1] 何青内容精粹 Download
[2] 何青附录 Download
[1] 王修华, 梁中旗, 刘锦华. 保险资金入市的创新驱动效应:发展“耐心资本”的视角[J]. 金融研究, 2026, 553(7): 58-76.
[2] 罗知, 汪洋子, 王怡静, 丁宇澄. 并购数字企业如何影响创新——基于专利结构演化的视角[J]. 金融研究, 2026, 553(7): 189-206.
[3] 诸竹君, 施逸帆, 刘乐易. 赋能型自主开放与中国式创新——基于自由贸易试验区政策的准自然实验[J]. 金融研究, 2026, 549(3): 75-94.
[4] 程晨, 司登奎, 刘贯春. 政府研发补助的创新效应再评估——基于外部投资者关注的新解释[J]. 金融研究, 2026, 548(2): 77-94.
[5] 杨鹏, 孙伟增, 田轩, 左祥太. 网络安全风险治理与企业创新——基于大语言模型的识别与发现[J]. 金融研究, 2026, 547(1): 76-94.
[6] 潘玉坤, 杜茜茜, 龚强, 叶奎成. 供应链不确定性与中国企业创新——基于中美供应链微观企业数据的分析[J]. 金融研究, 2025, 542(8): 75-92.
[7] 刘阳, 肖淇泳, 韩立岩, 秦萍. 关键金属价格波动、绿色激励与新能源企业创新[J]. 金融研究, 2025, 540(6): 152-170.
[8] 蔡庆丰, 陈熠辉, 严佳佳. “强省会”的创新外部性——基于省域知识交流与产业分工的研究视角[J]. 金融研究, 2025, 536(2): 132-149.
[9] 张美扬, 龙小宁. 专利丛林:科技创新中的绿荫还是荆棘?[J]. 金融研究, 2024, 527(5): 169-187.
[10] 蔡庆丰, 刘昊, 舒少文. 政府产业引导基金与域内企业创新:引导效应还是挤出效应?[J]. 金融研究, 2024, 525(3): 75-93.
[11] 魏浩, 封起扬帆. 进口竞争、创新风险与创新质量——基于单一企业和企业集团的再考察[J]. 金融研究, 2024, 533(11): 57-75.
[12] 许锐, 王艳艳, 于李胜. 专利质押贷款的创新激励效应[J]. 金融研究, 2024, 532(10): 58-75.
[13] 袁凯彬, 李万利, 张伟俊. 人民币参与国际结算能否激励出口企业创新? ——基于跨境贸易人民币结算试点的研究[J]. 金融研究, 2023, 516(6): 94-112.
[14] 许年行, 王崇骏, 章纪超. 破产审判改革、债权人司法保护与企业创新 ——基于清算与破产审判庭设立的准自然实验[J]. 金融研究, 2023, 516(6): 150-168.
[15] 冀云阳, 周鑫, 张谦. 数字化转型与企业创新——基于研发投入和研发效率视角的分析[J]. 金融研究, 2023, 514(4): 111-129.
No Suggested Reading articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 《金融研究》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn
京ICP备11029882号-1