This study develops an intertemporal model to investigate the causal relationship between government subsidies and employment and employs firm-level panel data to procure an estimation of the elasticities of government subsidies concerning employment, which is approximately 0.7 percent. To address endogeneity issues, we construct a novel Bartik shift-share instrumental variable for government subsidies. In heterogeneity analysis, our study discloses that government subsidies create a plethora of jobs, most predominately for individuals with advanced degrees, such as masters or doctorate. Additionally, our article identifies the top five industries that are most influenced by the effects of government subsidies.

Through a unique database on daily activities of municipal party secretaries, we find that they spend a significant part of their work time on political and propaganda activities, including organizing various meetings to promote the central government's spirit ideology. We find that officials engage in these behaviors more often before a government reshuffle, plausibly tend to leave a loyal and obedient impression on the superior government and increase their promotion probability. This is on contrary to economic behaviors, which are more common in the early stages of officials' terms, possibly because investment projects require time. This is more evident among younger, well-educated politicians due to age-based promotion restrictions. Our study may shed light on how the Communist Party of China balancing economic development and political loyalty when selecting officials.

The side effect of automation on the economy has been discussed frequently, but little is known regarding its political consequences. This paper examines the causal effect that automation induces political costs for the local government. By combining the national individual-level panel data of political trust with the prefecture-level robot exposure rate in China biennially during the period 2012– 2018, we find that the development of automation would incur lower political trust in the Chinese local government. Furthermore, the impact may result from the risk of unemployment, intensified pessimism about local government, higher downside risk, and declining group participation, providing a few channels for the automation process to affect citizens’political trust. This paper provides empirical evidence for the impact of automation and the source of political legitimacy, contributing to the literature about automation by emphasizing the crucial role of government in coping with the technological progress and making good use of endogenous creative destruction.

Volatility in the financial markets is commonplace and it comes with a cost. One of these costs is abrupt and huge drop in stock price that is known as stock price crash. To model this, we propose a new machine-learning based stock crash risk measure using minimum covariance determinant (MCD) to detect stock price crash. Using this proposed dependent variable, we try to predict stock price crash using cross-sectional regression. The findings confirm that the method properly capture the stock price crash and our proposed model performs well in terms of statistical significance and financial impact. Moreover, using newly introduced firm-specific investor sentiment index, it is identified that stock price crash and firm-specific investor sentiment are positively correlated. That is, higher sentiment leads to an increase with stock price crash risk, a relation that remains robust even when different firm sizes and detoned firm-specific investor sentiment index are considered.

Establishing a comprehensive risk management system and establishing a sound and effective internal control mechanism are important conditions for the survival and healthy development of financial enterprises. This paper analyzes the lessons of Société Générale's financial shock in Europe in 2008 due to the serious lack of internal control mechanism; Elaborated on the influencing factors and implementation paths of internal control in the digital intelligence era, pointed out the key points of constructing an internal control system under risk management in the digital intelligence era, and proposed the main methods and six major technologies of internal control in the digital intelligence era; This paper expounds that the audit Digital transformation is conducive to the realization of internal audit objectives and the improvement of internal audit efficiency. This paper introduces the main paths and key points of audit Digital transformation, and points out that intelligent audit is the major trend of future audit development; Introduced the application of digital twins in commercial bank auditing. It points out that the Digital transformation of audit is also the upgrading and transformation of organizations and talents, and it needs to vigorously cultivate and introduce audit professionals to support the smooth completion of the Digital transformation of audit. Financial enterprises should continue to innovate their internal control mechanisms, continuously improve and strengthen their internal control and risk management functions, continuously improve the effectiveness of internal control, and assist in the high-quality development of enterprises.

The past decade has witnessed a phenomenal rise of digital wallets, and the COVID-19 pandemic further accelerated their adoption globally. Such e-wallets provide not only a conduit to external bank accounts but also internal payment options, including the ever-popular Buy-Now-Pay-Later (BNPL). We examine, for the first time, e-wallet transactions matched with merchant and consumer information from a world-leading provider based in China, with around one billion users globally and a business model that other e-wallet providers quickly converge to. We document that internal payment options, especially BNPL, dominate both online and on-site transactions. BNPL has greatly expanded credit access at the extensive margin through its adoption in two-sided payment markets. While BNPL crowds out other e-wallet payment options, it expands FinTech credit to underserved consumers. Exploiting a randomized experiment, we also find that e-wallet credit through BNPL substantially boosts consumer spending. Nevertheless, users, especially those relying on e-wallets as their sole credit source, carefully moderate borrowing when incurring interest charges. The insights likely prove informative for economies transitioning from cash-heavy to cashless societies where digital payments and FinTech credit see the largest growth and market potential.

This paper provides a first systematic analysis of urban vibrancy in human capital supply in explaining persistent geographic firm valuation dispersion in China. We find persistent, significant city-to-city differences in Tobin’s q, especially among large, mature, or high labor-intensive firms. To explain such geographic differences in firm valuations, we identify several factors of the endowed city competitive advantages in creating human capital that play important roles in explaining the persistent geographic firm valuation premia. Our evidence suggests that city geographic location and initial cumulated human capital supply have created long-lasting, and growing, shareholder wealth by attracting and retaining talents and human resources in local firms.

We study the relationship between common factor betas and the expected overnight versus intraday stock returns. Using data from the Chinese A-share markets, we find that the Fama-French five-factor betas and expected returns exhibit contrasting relationships overnight versus intraday. The market, value, and profitability factors earn positive beta premiums overnight and negative premiums intraday, while the size and investment factors’ beta premiums behave oppositely. The night and day factor beta premium differentials are more muted among stocks with higher investor sophistication and vary across macroeconomic conditions. The contrasting day and night beta premiums extend to some other common factors and Chinese B shares, and vary their signs for some factors in the U.S. market.

本文基于Jurado et al.(2015)提出的大数据分析方法，提出了基于中国整体经济和金融市场不确定性的个股不确定性的度量方法，并检验了在存在卖空限制的中国A股市场中的不确定性的定价，着重研究了融资融券的不对称性对个股不确定性定价的影响。股票特质性波动率刻画了股票收益率中不能被市场风险因子解释的波动，通常被用于度量不确定性，本文提出其中与宏观金融不确定性的相关部分才会在市场中被定价。本文提出利用股票收益率与宏观金融不确定性指数的绝对相关系数来刻画在市场中被定价的个股不确定性，并发现不确定性越高的股票预期收益越低，即不确定性溢价在A股为负，这与Miller(1977)的理论相一致，即在存在卖空限制的市场上，不确定性越大的股票其价值被高估程度越大，因此预期收益率越低。本文进一步发现融资融券限制放开之后，不确定性的负溢价略有降低，市场的定价效率有所改善但并不明显，反映了市场中存在的卖空限制和隐性卖空成本较高，及其对市场定价效率的负面影响。因此，在中国A股市场合理地放开融资融券限制，特别是有效降低融券成本、引入长期投资者提供优质券源，能够降低融资融券的不对称性，改善市场的定价效率，从而更好地发挥金融市场的资源配置作用。

China’s emissions trading system applies a two-stage emissions intensity-based compliance quota allocation scheme different from the cap-and-trade systems prevalent in developed economies. It was designed to accommodate the country’s socioeconomic complexities and implemented following a learning-by-doing approach. Compliance firms significantly expanded green investment and production workforce. Their climate decisions are influenced by state ownership and regional heterogeneity. State-owned enterprises (SOEs) and less liberal market firms increased hiring, but not investment; non-SOEs and more liberal market firms grew investment. There are mixed welfare effects: compliance firms maintained productivity and efficiency; however, ordinary workers’ real wages were reduced, more prominent in SOEs.