How does labor risk affect corporate’s bond financing? Using the unique institutional feature of government regulations in China, we provide robust evidence that firms with a larger employment size have significantly better access to bond credit. This effect is more pronounced in times of local labor market deterioration or economic slowdown, for low-skill intensive industries, or in places with career-driven government officials. Our results are not driven by differential financial constraints or information frictions. We further show that the employment bias allocates bond credit towards under-performing large employers and the performance-enhancing benefits from bond issuance diminishes with employment size.

This article aims to provide an in-depth and comprehensive analysis of PRC Securities Law 2020 which overhauls China’s securities regulatory framework to construct more efficient and transparent capital markets with enhanced investor protection and market integrity. The law constrains regulators’ administrative powers in deciding the outcome of IPOs as well as streamline the securities offering procedure. This article pays attention to key reform initiatives proposed by PRC Securities Law 2020, such as the registration-based IPO system, the enhanced investor protection and compensation regime, the cross-border supervision, and the harsher punishments for securities frauds. It also discusses the latest enforcement cases relating to high-profile financial frauds like the Luckin Coffee scandal which resulted in Luckin Coffee being delisted from NASDAQ in 2020. The analysis in the article is accompanied by relevant US securities law in the same area to offer a comparative angle, which is of interest to practitioners, academics and policymakers in major financial centres.

Subjective performance evaluation is widely used by firms and governments to provide work incentives. However, delegating evaluation power to local leadership could induce influence activities: employees might devote too much effort to impressing/pleasing their evaluator, relative to working toward the goals of the organization itself. We conduct a large-scale randomized field experiment among Chinese local civil servants to study the existence and implications of influence activities. We find that civil servants do engage in evaluator-specific influence to affect evaluation outcomes, partly in the form of reallocating work efforts toward job tasks that are more important and observable to the evaluator. Importantly, we show that introducing uncertainty about the evaluator’s identity discourages evaluator-specific influence activities and improves bureaucratic work performance.

We identify negative spillovers exerted by large, successful manufacturing plants on other local production facilities in China. A short-lived alliance between the U.S.S.R. and China led to the construction of 150 "Million-Rouble plants" in the 1950s. Our identification strategy exploits the ephemeral geopolitical context and the relative position of allied and enemy airbases to isolate exogenous variation in plant location decisions. We find a boom-and-bust pattern in hosting counties: treated counties are twice as productive as control counties in 1982, but 30% less productive in 2010. The average other establishment in treated counties is unproductive, does not innovate, and charges high markups. We find that (over)specialization limits technological spillovers. This prevents the emergence of new industrial clusters and leads to a flight of entrepreneurs.

We analyze the effects of exposure to industrial robots on labor markets and household behaviors,exploring longitudinal household data from China. We find that a one standard deviation increase in robot exposure led to a decline in labor force participation (-1%), employment (-7.5%), and hourly wages (-9%) of Chinese workers. At the same time, among those who kept working, robot exposure increased the number of hours worked by 14%. These effects were concentrated among the less educated and larger among men, prime-age, and older workers. We then explore how individuals and families responded to increased exposure to robots. We find that more exposed workers increased their participation in technical training and were significantly more likely to retire earlier. Despite the negative impact on wages and employment, we find no evidence of an effect on consumption or savings, which is explained by an increase in borrowing (+10%). While there is no evidence of an effect on marital behavior, we document that robot exposure led to a small decline in the number of children (-1%). Finally, we find that robot exposure increased family time investment in the education of children (+10%) as well as the investment in children’s after-school academic and extra-curricular activities (+24%).

Rising concern over the impact of Chinese industrial policy has led to severe trade tensions between China and some of its major trading partners. In recent years, foreign criticism has increasingly focused on the so-called "Made in China 2025" initiative. In this paper, we use information extracted from Chinese listed firms' financial reports and a difference-in-differences approach to examine how the "Made in China 2025" policy initiative has impacted firms' receipt of subsidies, R&D expenditure, patenting, productivity, and profitability. We find that while more innovation promotion subsidies seem to flow into the listed firms targeted by the policy, we see little statistical evidence of productivity improvement or increases in R&D expenditure, patenting and profitability. This paper suggests that the “Made in China 2025” initiative may have not yet achieved its target goals.

This paper examines the impact and mechanism of digital finance on financial fraud by constructing a theoretical framework of digital finance affecting corporate financial fraud. We use panel data of Chinese A-share listed companies from 2011 to 2018. The results that digital finance can significantly inhibit corporate financial fraud and improve the ability of financial institutions to identify financial statements. Thus, the incentive and opportunity for corporations to engage in financial fraud is directly reduced. The internal mechanism shows that digital finance can restrain corporate financial fraud by alleviating the financing constraints faced by enterprises, as well as reducing corporate financial fraud by reducing corporate leverage. These effects will reduce debt pressure, thus easing the motivation of corporate financial fraud. The results of heterogeneity analysis that digital finance has a significant inhibitory effect on financial fraud of enterprises with different scales and different property rights.

This paper examines return spillovers within and between different DeFi, cryptocurrency, stock and safe-haven assets. The results show that DeFi and cryptocurrency asset markets exhibit strong within-market and between-market return spillovers, that stock and safe-haven markets show weak connectedness, and that safe-haven assets are minor receivers and transmitters of between-market spillover effects. The connectedness between markets is time varying and reveals structural changes in early 2020. Furthermore, we document that financial conditions shape the dynamics of return spillover effects between markets.

We explore whether Management Discussion and Analysis (MD&A) can provide incremental information to peers. Using Chinese stock market data, we find that positive peers' MD&A tone encourages firms to hold more cash, particularly for industries with fewer institutional investors' site visits. Moreover, this association is moderated by predation risk and decision-making environment. Specifically, this effect is more pronounced for firms which are market followers or financial constrained, and it is also stronger for firms operating under higher economic policy uncertainty or solely in domestic market. Overall, our findings enrich the information channels of peer effects in cash policy.

Regional carbon emission efficiency has differentiated characteristics under different economic development stages and patterns, and it is significant to identify such characteristics and formulate corresponding policies for high-quality regional development. Based on input-output data related to economic development and energy consumption, a comprehensive evaluation model of Super-SBM and Malmquist-Luenberger (ML) index was constructed to evaluate the spatial and temporal changes and driving forces of CEE, on the basis of which a proposal for collaborative carbon emission reduction zoning is proposed. The results indicated that the carbon emission efficiency (CEE) of the YRD shows a fluctuating upward trend with obvious spatial agglomeration characteristics, and the changes in CEE were closely related to the stage of economic development. The annual average CEE value during each period exhibited positive changes, indicating that economic development gradually shifted toward low carbonization. Moreover, the improvement of CEE gradually shifted from being driven by efficiency change to being driven by technological change. Finally, based on the carbon emissions and CEE characteristics of different cities, a carbon-neutral synergistic path is proposed in terms of industrial transformation, green development and technological support.