The study examines the impact of Government-Backed Financing Guarantee (GFG) programs on employment in small and medium-sized enterprises (SMEs) using data from the Zhejiang Guarantee Group and non-listed SMEs in China. The findings demonstrate that these programs have a significant positive effect on employment in SMEs, particularly in private firms, and non-ZhuanJingTeXin firms. Furthermore, the study demonstrates that GFGs can enhance firm employment rates by mitigating financing constraints. It also contributing to firm revenue growth.

We study the effect of China’s inland-favoring land policy on firm-level productivity by employing a research design combining difference-in-differences and regression discontinuity at the policy border. We find that the inland-favoring land policy decreased the firm productivity gap between developed (eastern) regions and underdeveloped (inland) regions. The relative changes are mainly due to slower eastern firm productivity growth rather than faster inland firm productivity growth. Eastern firms reduced their R&D expenditure and capital usage as a response to the policy.

This paper develops an SOE (small open economy) dynamic general equilibrium model to study the impact of climate change on the current account. By calibrating the model to Chinese economy, we find the following results. First, the current account-output ratio improves in the first decade following an increase in global temperature caused by climate change. It then deteriorates in the following next three decades. Second, the overall current account-output ratio dynamics in response to climate change is neither affected by the types and stringency of climate policies, nor by the levels and growth rates of temperature increases. Third, the impact of an increase in temperature from 1.28 ℃ to 1.5 ℃ relative to the pre-industrial periods (1850-1900) on the current account-output ratio is equivalent to that of an approximate 0.14% permanent decline in TFP. Finally, although the current account-output ratio is likely to deteriorate in the first year when temperature increases instantly, it might not be true if the coefficient of relative risk aversion, or interest rate premium is larger, or debt sensitivity to interest rate is smaller.

In this study, we investigate the impact of the development of the digital economy on corporate innovation and value using data of listed firms in China spanning the years 2011 to 2018. Our findings reveal a positive correlation between the development of the digital economy and corporate innovative activities, with a more pronounced effect observed in growth-stage firms, labor-intensive enterprises, and companies situated in underdeveloped regions. To establish a causal relationship, we employ a quasi-experimental approach utilizing the "Broadband China" pilot program. Using a difference-in-difference framework, we establish a causal link between the advancement of the digital economy and the increased innovative activities. Furthermore, our research underscores that digital economy development enhances firm value by promoting innovative activities. These results support the view that the digital economy plays a pivotal role in increasing firm value and fostering sustainable development in the overall economy.

Digital transformation provides enterprises a catalyst for new growth. This study delves into the correlation between digital transformation and corporate innovation from 2016 to 2020 based on a sample of Chinese A-share listed companies. It seeks to understand the underlying mechanisms and pathways of this relationship. Our research suggests that digital transformation significantly bolsters a company’s innovation capabilities. The mediating mechanisms indicate that the degree of digital transformation in enterprises supports this enhancement in various ways. Firstly, it lowers production costs. Secondly, it strengthens positive market expectations. Thirdly, it aids in managing operational risks effectively. All these factors collectively augment the innovation capacities of enterprises. Further analysis shows that digital transformation can successfully counterbalance the negative influences of economic policy uncertainty on corporate innovation. These insights offer a theoretical basis for elevating the level of digital transformation in enterprises and achieving superior-quality development more effectively.

This paper examines the impact of asset bubbles on innovation and long-run economic growth within a semi-endogenous growth framework, incorporating idiosyncratic productivity shocks and endogenous credit constraints in the R&D sector. It demonstrates that pure bubbles tied to intrinsically useless assets and equity bubbles linked to intermediate goods firms can coexist, relaxing credit constraints and boosting entrepreneurs’ total factor productivity (TFP), which stimulates R&D and enhances growth along the transitional path. However, these bubbles generally do not influence the long-run economic growth rate. The model’s mechanisms and predictions are supported by aggregate and firm-level evidence, showing a positive correlation between equity bubbles and R&D investment, with stronger effects during periods of tightened financial constraints.

With fintech growth and smartphone adoption, e-wallets, which enable instant transactions while offering cash management products with financial returns, have become increasingly prevalent. Using a unique dataset from Alipay, the world’s largest e-wallet provider, we find that holdings in Yu’EBao—an investment product usable for payments—are less affected by interest rate changes than similar assets without payment functions. This effect is stronger for users who depend on Yu’EBao for daily spending, during peak payment periods, or among less experienced investors. Our findings show that Yu’EBao reduces retail fund flow to riskier assets by 7.7% for every one-percentage-point interest rate cut, dampening monetary policy transmission through the portfolio rebalancing channel.

The economic institutionalist literature often suggests that sub-optimal institutional arrangements impart unique distortions in China, and excessive corporate debt is a symptom of this condition. However, lax monetary policies after the global financial crisis, and specifically, quantitative easing have led to concerns about debt bubbles under a wide range of institutional regimes. This study draws on data from Chinese listed firms, supplemented by numerous macroeconomic control variables, to isolate the effect of international capital flows from other drivers of firm leverage. We conclude that the rise in, and distribution of, Chinese corporate debt can partly be as-cribed to the effects of monetary policy outside of China and that Chinese institutional features amplify these effects. Whilst Chinese firms are affected by developments in the global financial ecosystem, domestic institutional realities and distortions may unevenly add their own particular effects, providing further support for and extending the variegated capitalism literature.

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.

To specify the peer effects that affect influencers’ sponsored content strategies, the current research addresses three questions: how influencers respond to peers, what mechanisms drive these effects, and the implications for social media platforms. By using a linear-in-means model and data from a leading Chinese social media platform, the authors address the issues of endogenous peer group formation, correlated unobservables, and simultaneity in decision-making and thereby offer evidence of strong peer effects on the quantity of sponsored content but not its quality. These effects are driven by two mechanisms: a social learning motive, such that following influencers emulate leading influencers, and a competition motive among following influencers within peer groups. No evidence of competition motive among leading influencers or defensive strategies by leading influencers arises. Moreover, peer effects increase influencers’ spending on in-feed advertising services, leading to greater platform revenues, without affecting the pricing of sponsored content. This dynamic may reduce influencers’ profitability, because their rising costs are not offset by higher prices. These findings emphasize the need for balanced strategies that prioritize both platform growth and influencer sustainability. By revealing how peer effects influence competition and revenue generation, this study provides valuable insights for optimizing content volume, quality, and financial outcomes for social media platforms and influencers.