The frequent occurrence of extreme weather events not only poses serious challenges to global economic growth and financial stability but also affects firms negatively across multiple dimensions. Using a sample of Chinese A-share listed firms from 2006-2016, this study aims to explore the effect of climate risk on firm export sophistication. The findings show that climate risk inhibits firm export sophistication, with the results varying depending on firm and industry types. Specifically, climate risk (i) inhibits export sophistication for firms with low government subsidies more than for firms with high government subsidies; (ii) restraints export sophistication for firms in high-tech industries rather than for low-and medium-tech industries; and (iii) reduces export sophistication for firms in low-marketization regions more than for firms in high-marketization regions. In addition, channel analysis shows that climate risk inhibits firm export sophistication by increasing financial constraints and reducing human capital.

The corporate maturity mismatch is highly likely to trigger systemic financial risks, which is a realistic issue commonly faced by businesses. In the context of the intelligent era, the impact of artificial intelligence on maturity mismatch has emerged as a focal point of academic inquiry. Leveraging data from Chinese A-share companies over the 2011–2023 timeframe, this research employs a double machine learning approach to systematically examine the influence and underlying mechanisms of artificial intelligence on maturity mismatch. The findings reveal that artificial intelligence significantly exacerbates maturity mismatch. However, this effect is notably mitigated by government subsidies, media attention, and collectivist cultural. Further analysis indicates that in high-climate-risk scenarios, collectivist culture exerts a notably strong moderating influence. By contrast, government subsidies and media attention exhibit stronger moderating influences in low-climate-risk environments. This study constructs a multi-stakeholder collaborative governance framework, which helps to reveal the 'black box' between artificial intelligence and maturity mismatch, thereby offering a theoretical basis for monitoring maturity mismatch.

We use a sample of China’s listed firms and employ a naïve Bayesian machine learning algorithm to reveal that environmental information intangibility superficially promotes green innovation. We demonstrate that this effect is channelled through the acquisition of institutional resources, including bank loans and government subsidies. The impact of environmental information intangibility on green innovation is most pronounced within state-owned enterprises, large firms, and politically connected firms. Furthermore, we confirm that environmental information intangibility does not lead to improvements in innovation efficiency or quality. This implies that green innovation may serve as a symbolic environmental activity. Our findings contribute to the understanding of the consequences of environmental information intangibility, greenwashing behaviour, and their relationship to green innovation.

We study how politicians' activities affect the stock market and firm performance. Using hand-collected data on China's national leaders' corporate visits, we investigate the industry-wide implications of these visits. We find that over the six days surrounding a visit, an average industry peer's value increases by 2\% of its total assets. This result reflects investors' favourable interpretation of leaders' visits as a signal of more government support for the entire industry. However, the industry peer's profitability plummets by more than 15\% in the next three years. Further analysis reveals that after the visits, industry peers increase their investments, presumably in anticipation of additional government subsidies and credits. However, these resources are insufficient, and the profitability of these firms suffers. Our findings suggest that national leaders' visits do not help boost the targeted industries, and firms should carefully interpret the politicians' activities.

ESG is emerging as a new benchmark for measuring a company's sustainable development capabilities and social impact. As a measure of ESG performance, ESG ratings are increasingly receiving attention from companies, the general public, and government institutions, and are becoming an important reference factor influencing their decision-making. This paper investigates the impact of corporate ESG ratings on Total Factor Productivity (TFP) and its mechanisms of action. Focusing on listed companies in China, we find that higher ESG ratings contribute to improving a company's TFP, and this conclusion remains valid after robustness tests and addressing endogeneity issues. Further exploration into the reasons behind this result reveals that ESG ratings can be seen as a signal that a company sends to the outside world, representing its overall performance. Higher ESG ratings enhance a company's TFP by reducing market financing constraints and obtaining government subsidies. Heterogeneity analysis shows that the positive impact of ESG ratings on TFP is more pronounced for companies with higher levels of attention, reputation, and audit quality. Additionally, we explore whether ESG ratings can serve as a predictive indicator for measuring a company's TFP. This hypothesis was tested using machine learning algorithms, and the results indicate that models incorporating ESG rating indicators significantly improve the accuracy of predicting a company's TFP capabilities.

This paper examines the spillover effect of environmental regulations on firms’ green technological innovation, from the perspective of supply chain relationships. Analyzing data from Chinese listed companies, we find that the average environmental regulatory pressure faced by the client firms of a supplier firm enhances the green patent applications filed by the supplier firm, indicating that environmental regulatory pressure from clients spills over to suppliers. When the industries of suppliers are more competitive or the proportion of their sales from the largest client is higher, suppliers feel more pressured to engage in green innovation, resulting in more green patent applications. Thus, via their negotiation power, client firms can prompt supplier firms to innovate to meet their demand for green technologies. Finally, we show that this effect is particularly pronounced when supplier firms are located in highly marketized regions, receive low R&D government subsidies, or have high ESG ratings.

This paper investigates the varying impact of government subsidies on corporate investment efficiency using micro-level data from Chinese listed firms. Through meticulous compilation of information on government subsidies revealed in financial statements, and the implementation of an innovative categorization methodology based on the nature and timing of funds (ex-ante versus ex-post), we shed light on the divergent effects of these subsidies. Our findings are as follows: (1) Government subsidies enhance corporate investment efficiency, yet their effects exhibit asymmetry by alleviating underinvestment while exacerbating overinvestment. (2) Functional subsidies exert a stronger influence on investment efficiency compared to selective subsidies. Specifically, functional subsidies prove more effective in addressing underinvestment, but also possess a higher likelihood of exacerbating overinvestment. (3) State ownership, firm size and dividend payments lead to heterogeneity in the effects of subsidies. (4) Corporate financial constraints serve as one of the mechanisms through which subsidies affect investment efficiency. This suggests that firms with easier access to financing may not effectively utilize subsidies, while those facing severe financial constraints are less prone to misusing them.

We estimate the financial and real effects of a subsidy program on imported capital goods recently implemented in China. We identify ffrms that have access to the subsidy program by combining data on catalogues of eligible products periodically released by the government and product-level import data. Our findings demonstrate that following the implementation of the program, eligible firms experience an increase in borrowing and gain access to loans at lower interest rates compared to non-eligible firms. This improved financial situation enables them to expand their fixed-asset investments, increase total output, and enhance their export performance. The expansion of production capacity also leads to improved investment efffciency and greater profitability. Further analysis reveals that the effects of the policy are particularly pronounced for non-state-owned enterprises and small firms in relatively competitive industries. This finding suggests that these firms face ex-ante financial constraints, and their marginal rate of return to capital is large.

This paper investigates the free cash flow productivity of SOEs compared with non-SOEs and examines its possible determinants. We find that SOEs have slightly weak free cash flow productivity but significantly stronger than non-SOEs. Similar performance exists among commercial class I and II SOEs and public-benefit SOEs. Further analyses suggest that firm size, age, sales growth, ownership concentration, government subsidies, and industry monopoly factors cannot explain this phenomenon. The common driver for all types of SOEs to generate stronger free cash flows than nonSOEs is their stronger expense control capability.

Research has argued that state-owned enterprises (SOEs) should bear more social responsibility than other listed firms, because their own goals include maintaining social stability and promoting social welfare. In contrast with the privatization of SOEs observed in other countries, in China, some listed firms’ major shareholders have become SOEs in recent years. This transition offers a good opportunity to investigate the impact of ownership change on firms’ corporate social responsibility (CSR). Using the propensity score matching difference-in-differences method, we document that the CSR performance of these firms does not improve when their ownership structure changes, and it can even worsen. Our results remain robust to a series of tests. Further investigating the underlying economic mechanism, we uncover those political connections, bank financing, and government subsidies play critical roles in determining the negative effect of ownership structure change on public firms, which is consistent with the soft budget constraint framework. In an additional analysis, we find that CSR performance is poor for manufacturing industry firms after ownership structure change. After calculating the frequency of keywords appearing in the annual reports of such firms, we find them to be satisfied with their new SOE background after ownership structure change. Our paper provides a possible explanation for the phenomenon of SOEs becoming major shareholder of listed firms.