Daleng Xin

This study examines whether China’s high-tech enterprise identification policy promotes corporate sustainable innovation. Using panel data from Chinese listed firms on the Shanghai and Shenzhen stock exchanges between 2008 and 2022, we adopt a time-varying difference-in-differences (DID) model to evaluate the policy’s effectiveness and explore its underlying mechanisms. The results reveal that this certification policy significantly facilitates green innovation, and the findings remain robust across various checks, including alternative measurements, placebo tests, propensity score matching DID (PSM-DID), and the exclusion of digital transformation trend and confounding macro-level policies. Mechanism analysis shows that the policy influences green innovation by alleviating financing constraints, increasing access to government subsidies, facilitating the agglomeration of scientific and technological talent, and encouraging greater R&D investment. Heterogeneity analysis further indicates that the policy effect is more pronounced among non-state-owned enterprises, small-scale firms, capital-intensive businesses, those located in high-institutional-quality regions, and firms in China’s eastern provinces. Moreover, the positive impact is strongest for growth-stage firms. The policy has also been found to improve green innovation efficiency. These findings offer empirical insights for optimizing selective industrial policies to enhance sustainable innovation and support China’s dual-carbon goals.

It is essential for achieving green and sustainable economic development by using tax incentives to promote green investment. Using the data from the seventh, eighth, ninth, and tenth Chinese Private Enterprise Surveys (CPESs) conducted by the Private Enterprise Research Group and using China’s corporate income tax reform in 2008 as a quasi-natural experiment, this paper empirically analyses the effect of tax incentives on corporate green investment based on the difference-in-difference models. The research results show that tax incentives can significantly increase corporate green investment. The mechanism test shows that easing financing constraints is an important channel for tax incentives to promote corporate green investment. In addition, the role of tax incentives in promoting green investment varies depending on the type and location of the enterprise. Relatively speaking, tax incentives have a stronger effect in promoting green investment for corporates with low sales revenue, located in the eastern region, heavy pollution, and high innovation capability. By doing placebo tests and changing measurement methods of indicators for robustness tests, the conclusions of this paper are still valid. Therefore, the government should increase tax incentives to better promote corporate green investment.

It is crucial to achieve sustainable development using digital finance to promote the fulfillment of corporate social responsibility. In this paper, we study the impact of digital finance on corporate social responsibility performance of pollution-intensive industry. From the perspective of theoretical mechanism, digital finance could influence corporate social responsibility performance through financing effect. Then, we use the data of Chinese listed companies and the Peking University Digital Financial Inclusion Index of China (PKU_DFIIC) to empirically test the influence of digital finance on corporate social responsibility of pollution-intensive industry. The results show that digital finance is positively related to the fulfillment of corporate social responsibility of pollution-intensive industry. The mechanism test shows that by reducing the information asymmetry in the financial market and making them easier for enterprises to access the financial market, digital finance effectively alleviates the financing constraints of enterprises and then enables enterprises to invest more capital in corporate social responsibility. Furthermore, we find that there are heterogeneous influences of digital finance on the corporate social responsibility performance of different types of enterprises. Specially, enterprises with small scale, located in high informatization and marketization areas and eastern regions of China, and enterprises with high ownership concentration will enjoy more positive impact. By using different indicators to measure digital finance and changing samples for robustness checks, the research conclusions of the paper are still valid. Therefore, government should make more effort to support the development of digital finance, so as to promote corporate social responsibility of pollution-intensive industry and the green and sustainable development of the economy.

We conduct theoretical and empirical study on the impact of economic policy uncertainty on PM2.5 pollution. Economic policy uncertainty has important impact on PM2.5 pollution through investment channel and innovation channel. Specifically, according to real option theory, increase in economic policy uncertainty can reduce investment, thereby reducing PM2.5 pollution. However, increase in economic policy uncertainty can hinder corporate’s innovation activities, which in turn make PM2.5 pollution increase. Therefore, the impact of economic policy uncertainty on PM2.5 pollution depends on the combination effect of these two different effects. Furthermore, using 25 countries’ unbalanced panel data and fixed effects estimation methods, we empirically test the impact of economic policy uncertainty on PM2.5 pollution. The results show that, with the increase of economic policy uncertainty, countries’ PM2.5 pollution has significantly decreased. In addition, economic policy uncertainty has heterogeneous effect on countries’ PM2.5 pollution. Compared with countries who have higher R&D input, increase in economic policy uncertainty makes the reduction of PM2.5 pollution in countries with relatively lower R&D input higher. By changing the measurement methods of economic policy uncertainty and PM2.5 pollution indicators, and using 2SLS methods to estimate the models, the conclusions of the paper are robust. Finally, we put forward corresponding policy implications.