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
Summary:
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.
朱茜俣, 陈康, 江嘉骏, 刘琦. 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[J]. 金融研究, 2026, 547(1): 132-150.
ZHU Xiyu, CHEN Kang, JIANG Jiajun, LIU Qi. Public Data Openness and Corporate Investment Efficiency: Based on Investor Information Production and Capital Market Information Feedback Mechanisms. Journal of Financial Research, 2026, 547(1): 132-150.
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.
