公共数据开放与企业投资效率——基于投资者信息生产与资本市场信息反馈机制

Journal of Financial Research

2026, Vol. 547

Issue (1): 132-150 DOI:

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Public Data Openness and Corporate Investment Efficiency: Based on Investor Information Production and Capital Market Information Feedback Mechanisms

ZHU Xiyu, CHEN Kang, JIANG Jiajun, LIU Qi

Guanghua School of Management, Peking University School of Finance, Southwestern University of Finance and Economics School of Economics, Fudan University

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Abstract Data, as a new factor of production, underpins digitalization, networking, and intelligent transformation. It has rapidly integrated into all facets of production, distribution, circulation, consumption, and social service management, profoundly reshaping how a nation produces, lives, and governs. To better leverage the value of public data, Chinese local governments have launched data openness platforms, piloting centralized and standardized provision of public data resources. Since 2012, these platforms have been progressively established, aggregating vast amounts of data from government and societal entities. By the end of 2022, 208 public data platforms had been launched, covering 23 provinces (excluding municipalities directly under the central government). A critical question remains: can—and how does—public data openness help market entities improve decision-making efficiency？ Clarifying this is essential to unlocking the potential of public data in China.
Using Chinese A-share listed firms from 2007 to 2022 as the sample, the paper employs provincial public data openness as a quasi-natural experiment and finds that such openness enhances firms' investment-price sensitivity. Mechanism analyses show that public data openness increases the idiosyncratic information content in stock prices by boosting analyst coverage and institutional investor research, thereby strengthening market feedback effects. Consistent with the “feedback effect” literature, the positive impact of public data openness on investment efficiency is more pronounced among firms with poorer ex-ante information environments (e.g., lower turnover, less informed trading) and stronger feedback channels (e.g., lower financing constraints, less insider information). Furthermore, heterogeneous effects are observed under types of data opened: when the data is more relevant to business operations, the enhancement effect is stronger, and the higher the quality of the data, the greater its role in improving investment efficiency. Finally, the study confirms that public data openness, as a policy tool, improves listed firms' profitability and long-term value through information feedback of the capital market.
This paper makes three contributions. First, it reveals an indirect mechanism through which public data affects corporate decisions via capital market feedback, offering a new perspective on how data openness improves investment efficiency and extending the literature on public data and investment decisions. Existing studies have mainly focused on the direct effects of data openness on investment levels. Few examine investment efficiency, and those that do overlook the role of capital markets. By opening this “black box,” this study provides a new theoretical lens for understanding how public data openness optimizes resource allocation.
Second, leveraging China's staggered public data platform launches as a quasi-natural experiment, this study provides empirical evidence that public data openness increases the private information content in stock prices in the A-share market. Theoretically, expanding public information supply may either “crowd in” or “crowd out” private information production (Goldstein & Yang, 2017), yet empirical evidence remains limited. This paper offers timely empirical insights from a unique institutional setting.
Third, the findings offer a capital-market-based perspective for evaluating the comprehensive effects of government information disclosure policies. The findings highlight the importance of considering both direct and indirect (capital market) effects when designing and evaluating public policies. This research suggests that public data openness not only has direct effects but also significantly shapes corporate behavior through information channels. This highlights the need for policymakers to adopt a more comprehensive approach that accounts for both direct policy impacts and indirect transmission through capital markets, thereby enabling a more accurate and complete understanding of policy outcomes.

Key words： Public Data Openness Feedback Effect Stock Price Informativeness Corporate Investment

Received: 24 February 2025 Published: 01 February 2026

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Cite this article:

ZHU Xiyu,CHEN Kang,JIANG Jiajun, et al. Public Data Openness and Corporate Investment Efficiency: Based on Investor Information Production and Capital Market Information Feedback Mechanisms[J]. Journal of Financial Research, 2026, 547(1): 132-150.

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http://www.jryj.org.cn/EN/ OR http://www.jryj.org.cn/EN/Y2026/V547/I1/132

[1]	蔡运坤、周京奎和袁旺平,2024,《数据要素共享与城市创业活力——来自公共数据开放的经验证据》,《数量经济技术经济研究》第8期,第5～25页。
[2]	陈国进、张润泽、谢沛霖和赵向琴,2019,《知情交易、信息不确定性与股票风险溢价》,《管理科学学报》第4期,第53～74页。
[3]	陈康和刘琦,2018,《股价信息含量与投资—股价敏感性——基于融资融券的准自然实验》,《金融研究》第9期,第126～142页。
[4]	陈兴述、董方芳和兰宗,2024,《公共数据开放与企业投资效率》,《财会月刊》第19期,第37～44页。
[5]	杜善重和连立帅,2025,《公共数据开放对企业技术创新的影响机理研究》,《科研管理》第10期,第40～49页。
[6]	方锦程、刘颖、高昊宇、董纪昌和吕本富,2023,《公共数据开放能否促进区域协调发展？——来自政府数据平台上线的准自然实验》,《管理世界》第9期,第124～142页。
[7]	郭家堂,2025,《公共数据开放与中国绿色全要素生产率:数据要素的视角》,《经济研究》第2期,第56～72页。
[8]	郭立祥、岳书敬和张鑫,2024,《数据开放对制造业与服务业融合的影响研究》,《科研管理》第12期,第1～14页。
[9]	黄群慧、余泳泽和张松林,2019,《互联网发展与制造业生产率提升:内在机制与中国经验》,《中国工业经济》第8期,第5～23页。
[10]	孔东民、石政和林爽,2025,《公共数据要素能提高企业劳动收入份额吗——基于建立公共数据开放平台的准自然实验》,《财贸经济》第4期,第77～94页。
[11]	蓝发钦、胡晓敏和徐卓琳,2024,《公共数据开放能否拓展资本跨区域流动距离——基于异地并购视角》,《中国工业经济》第9期,第156～174页。
[12]	刘志伟和张秋生,2024,《数据要素赋能企业投资效率研究——基于公共数据开放的准自然实验》,《经济学家》第9期,第42～52页。
[13]	陆蓉、朱思源和徐天丽,2024,《股指成分股调整与公司投资效率》,《南开管理评论》第2期,第225～235页。
[14]	欧阳伊玲、王愉靖、李平和高昊宇,2024,《数据要素与城投债定价:基于公共数据开放的准自然实验》,《世界经济》第2期,第174～203页。
[15]	沈坤荣和林剑威,2025,《链‘岛’成‘陆’:公共数据开放的技术创新效应研究》,《管理世界》第2期,第83～104页。
[16]	王海、叶帅和尹俊雅,2024,《公共数据开放如何提振企业有效投资——基于产能利用视角》,《中国工业经济》第8期,第137～153页。
[17]	王愉靖、李平、方锦程和高昊宇,2025,《公共数据开放对非正规金融风险的治理效应——基于中国法律裁判文书的微观证据》,《数量经济技术经济研究》第5期,第1～22页。
[18]	许年行、洪涛、吴世农和徐信忠,2011,《信息传递模式、投资者心理偏差与股价同涨同跌现象》,《经济研究》第4期,第135～146页。
[19]	叶永卫、余田田、陶云清和陈建兴,2025,《政府数据要素共享的稳投资效应:来自公共数据开放平台的证据》,《数量经济技术经济研究》第1期,第136～156页。
[20]	于丽峰、唐涯和徐建国,2014,《融资约束、股价信息含量与投资—股价敏感性》,《金融研究》第11期,第159～174页。
[21]	余华义,2015,《城市化、大城市化与中国地方政府规模的变动》,《经济研究》第10期,第104～118页。
[22]	张庆和朱迪星,2014,《投资者情绪、管理层持股与企业实际投资——来自中国上市公司的经验证据》,《南开管理评论》第4期,第120～127+139页。
[23]	Antoniou, C., F. Weikai Li, X. Liu, et al., 2023, “Exchange-Traded Funds and Real Investment”, The Review of Financial Studies, 36(3), pp.1043～1093.
[24]	Banerjee, S., S. Huang, V. Nanda, et al., 2023, “Managerial Overconfidence and Market Feedback Effects”, Management Science, 69(12), pp.7285～7305.
[25]	Bennett, B., R. Stulz, and Z. Wang. 2020. “Does the Stock Market Make Firms More Productive？,” Journal of Financial Economics, 136(2): pp.281～306.
[26]	Bird, A., S. A. Karolyi, T. G. Ruchti, and P. Truong, 2021, “More Is Less: Publicizing Information and Market Feedback”, Review of Finance, 25(3), pp.745～775.
[27]	Chen, Q., I. Goldstein, and W. Jiang, 2007, “Price Informativeness and Investment Sensitivity to Stock Price”, The Review of Financial Studies, 20(3), pp.619～650.
[28]	Edmans, A., S. Jayaraman, and J. Schneemeier, 2017, “The Source of Information in Prices and Investment-price Sensitivity”, Journal of Financial Economics, 126(1), pp.74～96.
[29]	Foucault, T., and L. Frésard, 2012, “Cross-Listing, Investment Sensitivity to Stock Price, and the Learning Hypothesis”, The Review of Financial Studies, 25(11), pp.3305～3350.
[30]	Furman, J. L., M. Nagler, and M. Watzinger, 2021, “Disclosure and Subsequent Innovation: Evidence from the Patent Depository Library Program”, American Economic Journal: Economic Policy, 13(4), pp.239～270.
[31]	Gao, M., and J. Huang, 2020, “Informing the Market: The Effect of Modern Information Technologies on Information Production”, The Review of Financial Studies, 33(4), pp.1367～1411.
[32]	Goldfarb, A., and C. Tucker, 2019, “Digital Economics”, Journal of Economic Literature, 57(1), pp.3～43.
[33]	Goldstein, I., 2023, “Information in Financial Markets and Its Real Effects”, Review of Finance, 27(1), pp.1～32.
[34]	Goldstein, I., and L.Yang,2017, “Information Disclosure in Financial Markets”, Annual Review of Financial Economics,9, pp.101~125.
[35]	Goldstein, I. , and L. Yang, 2019, “Good Disclosure, Bad Disclosure” , Journal of Financial Economics, 131( 1) ,pp. 118～138.
[36]	Hayek, F., 1945, “The Use of Knowledge in Society”, American Economic Review, 35, pp.519～530.
[37]	Kelly, B. and A. Ljungqvist. 2012. “Testing Asymmetric-Information Asset Pricing Models,” The Review of Financial Studies, 25(5): pp.1366～1413.
[38]	Kyle, A., 1985, “Continuous Auctions and Insider Trading”, Econometrica, 53, pp.1315～1335.
[39]	Luo, Y., 2005, “Do Insiders Learn from Outsiders？ Evidence from Mergers and Acquisitions”, The Journal of Finance, 60(4), pp.1951～1982.
[40]	Ma, R., F. Guo, and D. Li, 2024, “Can Public Data Availability Affect Stock Price Crash Risk? Evidence from China”, International Review of Financial Analysis, 94, 103270.
[41]	Magalhaes, G. and C. Roseira. 2020. “Open Government Data and the Private Sector: An Empirical View on BusinessModels and Value Creation, ” Government Information Quarterly, 37(3):101248.
[42]	Nagaraj, A., 2022, “The Private Impact of Public Data: Landsat Satellite Maps Increased Gold Discoveries and Encouraged Entry”, Management Science, 68(1), pp.564～582.
[43]	Nagaraj, A., E. Shears, and M. de Vaan, 2020, “Improving Data Access Democratizes and Diversifies Science”, Proceedings of the National Academy of Sciences, Vol.117,pp.23490～23498.
[44]	Rajan, R. and L. Zingales. 1998. “Financial Dependence and Growth,” American Economic Review, 88(3): pp.559～586.
[45]	Rhodes-Kropf, M., D. Robinson, and S. Viswanathan, 2005, “Valuation Waves and Merger Activity: The Empirical Evidence.”, Journal of Financial Economics, 77(3), pp.561～603.
[46]	Roll, R., 1988, “R2”, The Journal of Finance, 43(3), pp.541～566.
[47]	Sani, J., N. Shroff, and H. White, 2023, “Spillover Effects of Mandatory Portfolio Disclosures on Corporate Investment”, Journal of Accounting and Economics, 76(2), 101641.
[48]	Xu, C., and L. Jin, 2024, “Effects of Government Digitalization on Firm Investment Efficiency: Evidence from China.？”, International Review of Economics ＆ Finance, Vol. 92, pp.819～834.