Information Disclosure and Smart Financing: A Quasi-Natural Experiment from China’s New Securities Law
- 1 School of Accounting, Southwestern University of Finance and Economics, Chengdu, China
- 2 School of International Business, Beijing Foreign Studies University, Beijing, China
- 3 Department of Psychology, Capital Normal University, Beijing, China
- 4 School of Design, Beijing City University, Beijing, China
Abstract
Against the backdrop of smart city construction and digital transformation of urban business, information disclosure has become a core link balancing corporate privacy protection with urban financial development, while smart financing drives high-quality urban business growth. In this study, we define smart financing operationally as the process by which firms utilize information embedded in stock prices to guide and optimize investment decisions, captured empirically by investment-stock price sensitivity. The 2020 new Securities Law marks a historic reform in China’s disclosure regulation, offering a rare quasi-natural experiment to examine how disclosure data empowers smart financing efficiency. Using Chinese A-share listed firms from 2017 to 2024 and continuous disclosure ratings, this paper employs a difference-in-differences model to investigate the impact, mechanism, and heterogeneity of strengthened disclosure on investment-stock price sensitivity. We find that post-reform, investment-stock price sensitivity—a key smart financing metric—rose significantly among firms with poor prior disclosure. A one-level deterioration in disclosure rating is associated with a 0.0089 unit increase in sensitivity; relative to the sample mean sensitivity of 0.0327, this corresponds to a 27.2% increase, confirming the decision-empowering value of disclosure data. Mechanism tests reveal increased institutional ownership and analyst coverage for treated firms, with institutional shareholding partially mediating the effect, uncovering a “disclosure → information acquisition → price feedback” pathway. Heterogeneity analysis shows stronger effects in high-tech industries and low-financing-constraint firms, highlighting data value and transformability as key boundary conditions. Robustness tests (alternative measures, placebo tests, etc.) support these findings. This study is the first to assess enhanced disclosure’s impact on market feedback within China’s capital market using a quasi-natural experiment. It reveals asymmetry between disclosure quality and market efficiency in smart financing contexts and clarifies the role of institutional investors and analysts as information processors. Findings offer empirical evidence for regulators evaluating the new law’s effects and optimizing disclosure systems, while guiding firms on disclosure’s strategic value and investors on enhancing information processing capabilities.
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