Summary:
Information asymmetry remains a key obstacle to financing for small and medium-sized enterprises (SMEs), especially those in the technology sector. It also presents a major challenge to improving the efficiency of credit allocation. In recent years, government-led information empowerment has emerged as an important tool to reduce the information asymmetry between banks and firms. By enhancing the disclosure of firm-related information, such as business registrations and tax records, government agencies help banks better assess the operational performance of loan-seeking enterprises. While prior research has recognized the benefits of information empowerment in credit markets, it has largely focused on mirror-type information — that is, data directly reflecting observable facts about firms. In contrast, certification-type information—which reflects government assessments based on objective data—has received far less attention. This paper explores whether certification-type information can guide credit allocation and investigates the mechanisms behind its effects. Drawing on the theory of information asymmetry, this paper first explains how certification-type information helps bridge information gaps between banks and firms. According to signaling theory, third parties with informational advantages can send credible signals to less-informed parties, thereby reducing asymmetries and improving the efficiency of resource allocation. When banks lack direct insights into firm quality, they may rely on government endorsements to identify high-quality borrowers. In this context, certification-type information serves as a quality signal to the market, helping banks distinguish high-quality firms, reducing information asymmetry, and increasing firms' attractiveness as loan recipients. Specifically, when information asymmetry is severe and credit rationing occurs, certification-type signals can ease the rationing and improve firms' access to credit. In less asymmetric situations, such signals may prompt banks to expand credit scale and lower interest rates for certified firms. This study uses the specialized, high-end and innovation-driven SMEs whitelist issued by a province in eastern China as a proxy for certification-type information. Leveraging 1.8 million bank-firm matched loan records from the province, a difference-in-differences model is employed to evaluate the credit-guiding effect of the whitelist and its underlying mechanism. Results show that following the release of the whitelist, banks increased lending to listed firms by 6% relative to non-listed firms—demonstrating a notable guiding effect. This effect appears on both the extensive margin—encouraging new credit relationships between previously unconnected banks and firms—and the intensive margin—leading banks to increase credit to existing clients. Further analysis reveals that the primary channel through which the whitelist operates is by improving banks' ability to assess pre-loan risk and reducing adverse selection. However, its effectiveness in curbing moral hazard is limited due to weak punishing consequences for firms that fail to meet ongoing criteria. These findings offer important policy implications for improving the efficiency of credit allocation. First, government-driven information empowerment can help correct market failures and reduce friction, with certification-type information effectively channeling financial resources toward sectors aligned with high-quality development goals. Second, the success of such whitelists depends on the government's capacity for evaluation and access to reliable data—making it essential to enhance the rigor, professionalism, and credibility of the certification process. Third, dynamic management of the whitelist should be strengthened. A dual-track system combining a “whitelist” with a “negative list”, supported by annual reviews and real-time adjustments, would improve post-certification constraining function and governance. This paper makes three key contributions. First, by utilizing large-scale, firm-level loan data, it provides a novel analysis of the economic impact of certification-type information from both the extensive and intensive margins, thereby enriching the literature on the role of government information in credit markets. Second, by examining the government whitelist as a representative form of certification-type information, it offers empirical evidence for a mechanism distinct from that of mirror-type information, helping to address a notable gap in existing research. Finally, the paper generates practical policy implications for strengthening macroeconomic governance and enhancing the efficiency of credit resource allocation.
曹廷求, 庞念伟. 政府白名单的信贷引导效应研究[J]. 金融研究, 2025, 540(6): 114-132.
CAO Tingqiu, PANG Nianwei. The Credit Guidance Effect of Government Whitelist. Journal of Financial Research, 2025, 540(6): 114-132.
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