Project description:The panel data of 50 new energy vehicle enterprises in Shanghai and Shenzhen A-shares from 2012 to 2021 are selected to empirically analyze the impact of government subsidies on the innovation of new energy vehicle enterprises and to further discuss the differences between such an impact in different forms and regions. The study finds that, first, government subsidies have a certain promotion effect on the innovation of new energy vehicle enterprises, and an inverted U-shaped relationship exists thereof. Second, at the enterprise level, government subsidies have a significant effect on the innovation of non-state enterprises, downstream vehicle enterprises, and enterprises with lower establishment years, and the inverted-U trend is evident. Third, at the regional level, government subsidies have a more significant effect on the innovation of enterprises in non-eastern regions and low-environmental regulation regions, and the inverted-U-shaped relationship trend is more apparent. The study establishes the nonlinear relationship between government subsidies and the innovation of new energy vehicle enterprises through empirical research, which expands the theory of enterprise innovation and has a certain guiding significance for improving the innovation capability of new energy vehicle enterprises in the future.
Project description:Innovation holds paramount importance for both nations and businesses. This article presents a panel regression model designed to assess the fixed effects of industry-university-research (IUR) cooperation projects on innovation performance. Furthermore, it examines the moderating impact of government innovation subsidies by utilizing data spanning from 2007 to 2021, encompassing 326 listed Chinese biopharmaceutical firms. Our findings reveal that industry-university-research-cooperation projects have the potential to significantly enhance innovation performance across three key metrics: input, output, and quality for firms. The presence of government innovation subsidies as a moderator is found to have a positive influence on IUR-cooperation projects and their innovative inputs. However, it can yield adverse effects on IUR-cooperation projects with respect to innovation outputs and quality. The insights presented in this paper introduce innovative recommendations for elevating corporate innovation quality and refining the policies governing IUR cooperation.
Project description:Environmental, Social and Governance (ESG) is closely related to the "dual carbon" objective and the concept of sustainable development. The impact of ESG performance on audit efficiency, especially on audit delays, is still an issue to be studied in depth. Drawing on stakeholder theory, sustainable development theory, shared value concept and corporate social responsibility theory, this study adopts regression analysis and structural equation modeling (SEM) to investigate the impact of ESG on audit efficiency based on the data of A-share listed companies in the period of 2015-2022, with a focus on audit delay. The results of regression analysis show that ESG performance has a significant effect on reducing audit delay, and audit delay is reduced by 0.007 on average for each unit increase in ESG performance. In structural equation modeling, the effect of ESG performance on audit delay is more significant, with an estimated value of -0.555 and a standard error of 0.097. In addition, the study shows that the corporate ESG performance on audit efficiency has a positive impact is more pronounced among firms with stronger ESG practices, especially among non-state-owned firms with lower institutional investor ownership and firms audited by "Big Four" firms. These results not only demonstrate the importance of ESG performance in improving audit efficiency, but also provide important guidance for corporate management and policy making. This study enriches the existing literature on corporate ESG performance and audit efficiency and provides new perspectives and directions for future research.
Project description:Environmental, Social, and Governance (ESG) is closely related to commercial banks' promotion of "dual-carbon" goals and the concept of sustainable development. The impact of ESG performance on commercial banks' support for green innovation remains an issue for in-depth study. This paper studies 36 Chinese commercial banks in China from 2010 to 2021 and finds that the ESG performance of commercial banks can promote green innovation, and this promotion is more obvious when bank remuneration incentives are effective. Meanwhile, this paper verifies the mediating role of the non-performing loan ratio and the Lerner index in it, which provides channel support for ESG to effectively promote green innovation development. This study enriches the existing literature on environmental, social, and governance performance and green innovation in commercial banks and provides new perspectives and directions for future research.
Project description:Under the global wave of intelligence, intelligent manufacturing has become a crucial means of transforming and upgrading China's manufacturing industry. Accurate evaluation of the implementation effects of intelligent manufacturing industry policies is an urgent issue. This study uses the introduction of the "Made in China 2025" policy as a quasi-natural experiment and employs the difference-in-differences method to investigate the impact of intelligent manufacturing policies on firms' total factor productivity (TFP) and its mechanisms. These results indicate that implementing intelligent manufacturing policies significantly enhances firms' TFP. Mechanism analysis reveals that intelligent manufacturing policies can improve firms' ESG performance by enhancing green technology innovation capabilities, increasing capital market attention, and reducing internal control costs, thereby enhancing firms' TFP. Heterogeneity analysis finds that intelligent manufacturing policies have a more pronounced effect on promoting TFP in large-scale enterprises, labor-intensive enterprises, firms with higher technical employee levels, companies in highly competitive industries, and enterprises in regions with higher levels of digital infrastructure development and lower economic development as compared to their counterparts. This study provides evidence of how intelligent manufacturing policies drive the high-quality and sustainable development of enterprises and offers insights for future policy formulation and implementation.
Project description:This paper aims to investigate the effect of political turnover on corporate ESG performance in China. By analyzing data from Chinese A-share-listed companies between 2010 and 2020, we have discovered that changes in the municipal party committee secretary or the mayor of the prefecture-level city where a firm is located have a detrimental effect on corporate ESG performance. Compared with the change of the party committee, the change of mayor has a more pronounced negative impact on ESG performance. The reason behind this negative effect is primarily attributed to policy uncertainty, which leads to a decrease in governmental subsidies and an increase in ineffective under-investment by companies, consequently resulting in decreased corporate ESG performance. Furthermore, we have also observed that the adverse influence of political turnover on corporate ESG performance is relatively mitigated in SOEs, politically connected firms, and tertiary industries. These findings contribute to a deeper understanding of the relationship between political uncertainty and corporate behavior, particularly in emerging markets.
Project description:Digital transformation is crucial for sustainable development of enterprises and for addressing the conundrum of "efficiency and environment". Utilizing a dataset from A-share listed companies in China from 2007 to 2021, this paper investigates the direct impact, underlying mechanism and driving effect of enterprise digital transformation on carbon emission intensity. The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. Furthermore, the carbon emission reduction effect of digital transformation is more potent in capital-intensive and technology-intensive enterprises compared to labor-intensive enterprises. This paper offers valuable insights for fostering enterprise digital transformation and promoting green, low-carbon development aligned with the "dual-carbon" strategy.
Project description:Goodwill has been a controversial issue in China since 2007 when the new accounting standards changed the subsequent measurement of goodwill from periodic amortization to impairment testing. Using the change in subsequent measurement of goodwill, this paper examines the impact of goodwill accounting on corporate M&A and industry development. The paper finds that adopting the goodwill impairment test significantly increases firms’ M&A incentives, as evidenced by a significant increase in the frequency and probability of M&A and a significant reduction in the time interval between successive M&A at the industry level. From an industrial perspective, the impairment policy has significantly improved industry concentration, total factor productivity, and competitive advantage in international trade across Chinese industries. The positive impact of goodwill impairment policy on M&A is more pronounced among firms with asset-light characteristics or high P/E ratios, and its contribution to industry competitiveness is more pronounced in asset-light or high P/E ratios industries. From the perspective of promoting capital market mergers and acquisitions and industry competitiveness, the article finds that the current goodwill impairment policy can have positive economic consequences. Our study breaks through existing perspectives to provide compelling empirical evidence for the current theoretical and practical controversy over goodwill measurement standards.
Project description:Private enterprises play an increasingly important role in China. They can improve the total-factor productivity (TFP) and help transform and upgrade industrial structures. This study uses data for private listed manufacturing companies from 2009 to 2017 to examine the effects of different types of subsidies on TFP. We also analyze the heterogeneity and specific mechanism of subsidy effects. We find that R&D subsidies and production subsidies positively affect private enterprises' TFP. Moreover, R&D subsidies and production subsidies lagged by one period can also significantly increase private enterprises' TFP. In terms of industry, R&D subsidies have more obvious effects on technology-intensive industries, while production subsidies have more significant effects on labor-intensive and capital-intensive industries. In terms of scale, R&D subsidies' effects on the TFP of medium-sized enterprises are the largest, while production subsidies have the greatest effect on small enterprises' TFP. Government subsidies increase private enterprises' TFP through two mechanisms: improving technological innovation capability and alleviating financing constraints. Our results suggest that governments should formulate different subsidy policies according to industry and enterprise scale.
Project description:Small and medium-sized enterprises (SMEs) were an important part of China's economy, but they faced challenges to growth due to financing difficulties. Government subsidies are considered as a potential way to address this problem. This study aims to assess the effectiveness of the Chinese government's subsidy program aimed at improving the accessibility of financing for SMEs. We analyze a comprehensive dataset of Chinese firms' subsidy programs from 2011 to 2020. We classify subsidies into unconditional and conditional categories and use fixed-effects regression models to control for the effects of time and between-group variation to more accurately assess the effectiveness of government subsidies. In addition, we use a PSM-DID model to reduce the effect of selectivity bias to more accurately estimate the causal effect of subsidies on financing strategies. We also use a mediated effects model to help understand the mechanisms by which different types of subsidies affect financing strategies. The results show that government subsidies can significantly improve SMEs' financing ability, but different types of subsidies produce subtle differences. Conditional subsidies support debt financing mainly through incentives, while unconditional subsidies help SMEs improve their equity financing ability through information effects. Furthermore, we find that over-reliance on a single subsidy type may reduce its effectiveness, suggesting a complex relationship between government intervention and SME financing. Thus, well-designed policies are crucial for promoting SMEs and fostering economic growth.