As digital transformation strategies have emerged as a primary approach for enterprises to enhance their Total Factor Productivity (TFP), it is crucial to empirically examine the impact of these strategies on TFP. For this purpose, this study considers these transformation strategies as a quasi-natural experiment and employees a propensity score-weighted difference-indifferences methodology on data from Chinese firms listed on the A-share market between 2007 and 2020. The key findings include: (1) digital transformation has a significant positive influence on TFP; (2) Generalized boosted regression trees analysis reinforces this finding after controlling for other TFP determinants; (3) notably, non-state-owned and technology-intensive enterprises exhibit a more distinct enhancement in TFP following digital transformation. These results underscore the need for firms to increase investment in research and development capabilities and digital competencies.

Using data from Chinese A-share listed firms from 2015 to 2022, we employ a difference-in-differences model to empirically examine the impact of bankruptcy regimes, marked by the establishment of bankruptcy courts, on firms’ total factor productivity (TFP). The results show a significant decline in TFP among firms in regions following the establishment of bankruptcy courts. This finding remains valid after a series of robustness tests. Mechanism tests reveal that establishing bankruptcy courts increases firms’ risk aversion incentives by endowing creditors with excessive rights. Consequently, firms tend to reduce liabilities, curtail R&D investment, and accumulate liquid assets as coping measures, ultimately contributing to a decline in TFP. Furthermore, this effect is more pronounced for firms with high financial risk. However, the improvement of the market mechanism can alleviate the negative impact of bankruptcy courts excessively strengthening creditor protection. Specifically, when firms are located in regions with weak government intervention and strong financial development, as well as in market environments with low uncertainty and strong competition, this negative impact can be mitigated. These findings provide fresh insights into the dual nature of creditor protection and offer valuable references for governments to improve the bankruptcy legal system.

This study examines how localized carbon reduction policies affect corporate environmental productivity. Leveraging a quasi-experiment from China’s low-carbon pilot policy rollout across cities, we implement a difference-in-differences approach to estimate the causal impact of these interventions. Pilot policies significantly increased regulated polluting corporate environmental productivity by around 3 percentage points. The productivity gains persisted over time and were greater for financially constrained firms, firms facing less market competition and with lower capital intensity. Additional analysis reveals the pilots enhanced executive environmental awareness. Overall, our results demonstrate appropriately designed local regulations can improve environmental productivity.

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The level of corporate risk-taking impacts debt default as a crucial investment decision. Hence, this must be examined considering resource allocation. This study uses A-share listed companies from 2007 to 2021 as samples to empirically explore the impact and mechanism of corporate risk-taking level on debt default risk. The results show that corporate risk-taking can significantly inhibit debt default and the risk of debt default by promoting total factor productivity. Further, the higher the level of enterprise financialization of the firm, the higher the stock liquidity, and the higher the level of managerial confidence, the stronger the inhibitory effect of corporate risktaking on debt default. The heterogeneity analysis reveals that the inhibitory effect of corporate risk-taking on debt default is more significant in large-scale enterprises, enterprises with lower regulatory shareholdings, and enterprises with standard unqualified audit opinions. The study provides guidance for enterprises to improve the level of risk-taking and resource allocation efficiency effectively. Moreover, it provides empirical support for regulators to effectively prevent "waves of defaults" and even "waves of bankruptcies" in the real economy.

This research study primarily examines the digital transformation’s internal mechanism promoting enterprises’ total factor productivity (TFP) based on the matching and learning mechanism. Afterward, this research article empirically examines the digital transformation’s influential mechanism on enterprises’ TFP, using the Chinese listed companies’ data on the “A” stock market for the time period ranging from 2007 to 2019. The major study findings are as follows: (1) the improvement of the digital transformation significantly increases enterprises’ TFP. The proposed conclusion remains robust after a series of robustness- and the endogeneity test. (2) Furthermore, mechanism analysis reveals that digital transformation effectively enhances enterprises’ TFP by eliminating resource misallocation in the industry. In addition to this, digital transformation relies on the mechanism of “learning by doing” to promote the technological innovation’s spillover effect; hence, effectively enhancing enterprises’ TFP. (3) Heterogeneity analysis demonstrates that the digital transformation’s impact on enterprises’ TFP is heterogeneous in the context of enterprise size, enterprise type, and enterprise ownership. Lastly, this study puts forward that government bodies should intensify the construction and investment in digital infrastructure, promote a series of institutional reforms, and support digital technological R&D practices.

This paper examines the relationship between population aging and corporate digital transformation from the perspective of demographic changes. Generally, the findings indicate that population aging notably contributes to corporate digital transformation, mainly through increasing labor costs, including expected and actual labor costs. Further analysis suggests that the above effects are significantly weakened in samples of firms with lower levels of regional intellectual property protection, higher corporate financial constraints, and shorter-sighted managerial decision-making. Moreover, the economic consequences test implies aforementioned favorable effects can enhance corporate total factor productivity.

We study the role of firm heterogeneity and imperfect competition for global production networks and the gains from trade. We develop a quantifiable trade model with two-sided firm heterogeneity, matching frictions, and oligopolistic competition upstream. More productive buyers endogenously match with more suppliers, thereby inducing tougher competition among them to enjoy lower input costs and superior performance. Transaction-level customs data confirms that downstream French and Chilean firms import higher values and quantities at lower prices as upstream Chinese markets become more competitive over time, with stronger responses by larger firms. Moreover, suppliers charge more diversified buyers lower mark-ups. Counterfactual analysis indicates that entry upstream benefits high-productivity buyers, while lower matching or trade costs benefit all buyers, with the biggest boost to mid-productivity buyers. All three shocks generate sizeable welfare gains, especially under package reforms. Global production networks thus mediate bigger effects and cross-border spillovers from industrial and trade policies.

Green finance has drawn increased worldwide attention from policymakers as a financial mechanism that could potentially encourage corporations to actively engage in sustainable activities. However, despite a growing body of studies investigating the economic outcomes of green financial policies, there is still a lack of research that systematically quantifies the social welfare implications of green finance. Hence, this study aims to fill this research gap by establishing the causal effect of green finance on corporate environmental responsibility. Exploiting the "bottom-up" enforcement of the green finance pilots in 2017 in China as a quasi-natural experiment and the difference-in-difference-in-difference identification strategy, we find that green finance significantly enhances corporate environmental responsibility performance in high-polluting industries relative to their counterparts, and this evidence continues to survive a battery of robustness checks. Moreover, we explore three underlying mechanisms that possibly explain this beneficial effect: risk-taking, external governance and financing channels. Furthermore, we uncover that corporate environmental responsibility serves as a plausible non-economic channel that combines green finance with economic benefits by stimulating green innovation, promoting total factor productivity and expanding market share. Overall, our study offers new insights on both the economic and non-economic consequences of green finance on business performance.

As digital transformation strategies have emerged as a primary approach for enterprises to enhance their Total Factor Productivity (TFP), it is crucial to empirically examine the impact of these strategies on TFP. For this purpose, this study considers these transformation strategies as a quasi-natural experiment and employees a propensity score-weighted difference-indifferences methodology on data from Chinese firms listed on the A-share market between 2007 and 2020. The key findings include: (1) digital transformation has a significant positive influence on TFP; (2) Generalized boosted regression trees analysis reinforces this finding after controlling for other TFP determinants; (3) notably, non-state-owned and technology-intensive enterprises exhibit a more distinct enhancement in TFP following digital transformation. These results underscore the need for firms to increase investment in research and development capabilities and digital competencies.