Interest rate liberalization in China intensifies the exposure of commercial banks' interest rate risks and further increases the difficulty for commercial banks to effectively control interest rate risks, thus putting forward higher requirements for the normal operation and management of commercial banks. With the development of China's financial derivatives market, banking institutions begin to use basic interest rate derivatives to hedge interest rate risks. It is very important to give full play to the maturity transformation Function of commercial banks to enhance the ability of financial services to the real economy. Based on the semi annual unbalanced panel data of 37 listed banks in A-share stock markets from 2006 to 2020, this paper empirically tests the impact of the use of off balance sheet interest rate derivatives on the Maturity Transformation Function of banks in the case of interest rate fluctuations. The empirical results show that: (1) the use of interest rate derivatives helps to weaken the negative impact of interest rate fluctuations on the Maturity Transformation Function of banks. (2) The analysis of the mechanism shows that the use of interest rate derivatives improves the stability of the bank's asset side term structure and liability side term structure, so as to support the effective play of the bank's financial intermediary role. (3) Further analysis shows that the of interest rate derivatives significantly reduces the volatility of bank earnings. This study makes it clear that the use of interest rate derivatives has a positive impact on the commercial banks, which provides evidence for the further development of interest rate derivatives market in China.

Increasing greenhouse gas emissions, especially CO2, pose a serious challenge worldwide. Digital financial inclusion can help alleviate liquidity constraints and accelerate the green transformation of production, changing how and what households consume. This change can impact households’ indirect CO2 emissions. However, empirical research on the nexus between digital financial inclusion and households’ indirect CO2 emissions, especially from a microscopic perspective, has remained scant. This study investigates the impact of digital financial inclusion on households’ indirect CO2 emissions using a survey panel dataset of 13,624 Chinese households. The results show that digital financial inclusion promotes households’ indirect CO2 emissions.This finding is robust to the alternative model specifications and methods.Further analyses based on the mediation model show that digital financial inclusion increases households’ indirect CO2 emissions by promoting subsistence and development consumption upgrades. In addition, the effects of different services of digital financial inclusion are heterogeneous. Payment, credit, and credit investment services are positively and significantly related to households' indirect CO2 emissions, whereas other services are not. Overall, our findings provide evidence of the social benefits of digital financial inclusion policies and also have several implications for addressing environmental problems.

Using the sample of Chinese A-share listed firms from 2020 to 2021, this study investigates the impact of EPU on corporate ESG performance. We find that EPU improves corporate ESG performance, and the results largely hold after a series of robustness tests. Furthermore, EPU has a significantly positive effect on each dimension of corporate ESG performance (environment, society and governance). In addition, we document that the positive effect of EPU on corporate ESG performance is more pronounced for state-owned firms, and firms with better internal governance, better external governance, and firms that are more financially-constrained. This study provides large-sample empirical evidence for the effect of EPU on corporate ESG performance, which provides implications for management to make use of corporate ESG performance in the face with uncertain economic policy environment.

Taking the Stock Connect scheme as an exogenous shock based on data of China’s Ashare non-financial listed companies from 2009 to 2021, we identify the causal effect of stock market liberalization on green innovation. The baseline result based on a staggered difference-indifferences (DID) model suggests that stock market liberalization promotes corporate green innovation and this effect is similar to the green benefits of China’s mandatory environmental regulations. The results are robust to various checks, including the parallel trend tests, placebo tests, and the heterogenous time-varying treatment test based on Bacon decomposition and the DIDM approach. The enhanced continuity of corporate financing, improved corporate green governance and increased firm external technological collaboration are three plausible channels that allow stock market liberalization to promote corporate green innovation. Moreover, the effect is more significant for clean firms, non-SOEs, and firms in a good institutional environment. Further analysis suggests that the green innovation-enhancing effects of stock market liberalization are more likely to be high-quality innovation. Our paper provides new insights into understanding the green benefits of stock market liberalization and achieving sustainable economic development in developing countries.

In this paper, we investigate whether those enterprises adopting digital finance exhibit higher values. On the basis of the constructed fintech-related lexicon developed by the machine learning-based Word2Vec model, we employ the frequency of fintech-related words (phrases) in the management discussion sections of annual reports as a proxy variable for the degree to which enterprises apply digital finance. We utilize panel data regression and mediation models based on data of Chinese A-share listed companies from 2016 to 2022 and explore the impact of this degree of digital finance application on enterprise value. We find that the degree to which enterprises apply digital finance elevates their values. The in-depth integration of digital technology and finance directly enhances enterprise value by reducing financing costs. Additionally, the effects are more evident among small-scale firms and enterprises located in regions with lower marketization levels. However, in the face of the impact of the COVID-19 pandemic, the positive effects on enterprises are relatively low.

Digital economy promotes the modernization of industrial structure by influencing the rationalization and upgrading of industrial structure through technical level and factor level; while excessive credit expansion hinders the modernization of industrial structure. This paper uses panel data from 31 jurisdictions in China to conduct empirical analysis, and finds that digital economy development shows a year-on-year rising trend, and there is a large gap between different regions. The conclusion still holds after the robustness test and regional heterogeneity analysis, thus enriching the understanding of mechanisms and regional differentiation of digital economy, credit expansion on industrial structure modernization.

Purpose – Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whetherthe marketrewards meeting or beating analyst earnings expectations (MBE). Design/methodology/approach –The authors use an event study methodology to capture marketreactions to MBE. Findings – The authors document a stock return premium for beating analyst forecasts by a wide margin. However,there is no stock return premium forfirms that meet orjust beat analystforecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts. Research limitations/implications – The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market’s over-skepticism of earnings management being a plausible mechanism for this phenomenon. Practical implications – The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers’ earnings management. Originality/value – The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

Purpose – This study aims to examine whether and how gender diversity on corporate boards is associated with voluntary nonfinancial disclosures, particularly water disclosures. Design/methodology/approach – This study uses corporate water information disclosure data from Chinese listed firms between 2010 and 2018 to conductregression analyses to examine the association between female directors and water information disclosure. Findings – Empirical results show that female directors have a significantly positive association with corporate water information disclosure. Additionally, internal industry water sensitivity of firms moderates this significant relationship. Originality/value – This study determined that female directors can promote not only water disclosure but also positive corporate water performance, reflecting the consistency of words and deeds of female directors in voluntary nonfinancial disclosures.

把握新技术革命发展机遇,推动产业智能化升级,对于新形势下实现经济高质量发展具有重要作用。文章基于 2003—2019 年中国 283 个地级市数据和网络爬虫获得的企业微观数据构建城市产业智能化指数,采用社会网络分析方法考察产业智能化的空间关联网络特征；此外,运用机器学习中的极限梯度提升树算法（XGBoost）识别出产业智能化的核心驱动因素,在此基础上借助加权指数随机图模型（ERGM）探析产业智能化空间关联网络驱动机制。研究发现：（1）样本期间产业智能化空间关联强度不断提高,但整体处于较低水平,存在较大的提升空间；大部分城市位于网络边缘位置,主要依靠城市群或中心城市对周边城市产业智能化产生辐射带动作用。（2）XGBoost 算法测算结果表明,技术创新、产业结构升级和对外开放是产业智能化的核心影响因素,累积贡献率高达 92.72%。（3）技术创新、产业结构升级和对外开放有利于加强城市间的产业智能化合作。异质性分析发现,产业结构升级主要推动外围城市、高产业智能化水平城市形成紧密的产业智能化空间关联,而技术创新和对外开放对其驱动作用有限。据此,文章提出了推动产业智能化空间协调发展的相应政策建议。

在建设全国统一大市场的进程中,有效降低企业非生产性支出是提高市场运行效率的关键环节。文章基于 2016—2019 年中国 A 股上市公司数据,使用大数据发展“政用指数”刻画各地区数字政府建设水平,评估了数字政府建设对企业非生产性支出的影响及其机制。研究发现,数字政府建设显著降低了企业非生产性支出。上述结论在一系列稳健性检验之后依然成立。异质性效应分析表明,数字政府建设抑制企业非生产性活动的效应对非国有企业、政府管制行业、数字化转型程度较高的企业以及信息基础设施水平较高的地区更强。机制检验结果表明,数字政府建设降低企业非生产性支出的效应随着政务服务效能的提升而减弱,且数字政府建设会显著改善企业面临的税收环境。这意味着提升政务服务效能是数字政府建设降低企业非生产性支出的重要机制。文章证实了数字政府建设对于抑制企业非生产性活动的积极意义,在一定程度上可为激发市场主体活力、夯实经济发展效率的变革提供政策借鉴。