This paper examines whether employees avoid firms that commit environmental, social and governance (ESG) misconduct in China where ESG norms are weak. We find that the number of employees grows slower when firms have more ESG incidents after accounting for performance, risk, corporate governance, and time-invariant firm characteristics. The result is mostly attributable to social incidents and incidents that affect China, better educated knowledge workers, and high tech and non-labor-intensive industries, and is unlikely to be caused by layoffs. Overall, workers with better job fluidity respond to incidents that affect them personally.

This paper conducts a regression analysis using data from Chinese listed companies between 2008 and 2023, and finds the following: First, financial support significantly increases firms’ customer dependence; second, financial support indirectly promotes the enhancement of customer dependence by reducing firms’ excess administrative expenses; third, further heterogeneity analysis reveals that the impact of financial support on customer dependence varies significantly depending on whether the firm is audited by a Big Four accounting firm, with the effect being more pronounced in firms not audited by a Big Four firm.

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.

Using comprehensive account-level data and 192 asset pricing anomaly signals, we investigate whether retail investors and institutions trade on anomalies in China. We find that retail investors tend to trade contrary to anomaly prescriptions, suggesting that they have a strong tendency to buy (sell) overvalued (undervalued) stocks. In contrast, institutions trade consistent with anomalies, indicating that they buy (sell) undervalued (overvalued) stocks. Regarding the information content of anomalies, we find that small retail investors trade contrary to trading-based anomalies, whereas institutions trade consistent with both trading- and accounting-based anomalies. Additionally, lottery stock preference and return extrapolation help explain investors’ trading behavior on anomalies.

This study identifies an incentive-compatible mechanism to foster individual environmental engagement. Utilizing a dataset comprising 100,000 randomly selected users of Ant Forest—a prominent personal carbon accounting platform embedded within Alipay, China's leading BigTech super-app—we provide causal evidence that individuals strategically engage in eco-friendly behaviors to enhance their credit limits, particularly when approaching borrowing constraints. These behaviors not only illustrate the green nudging effect of BigTech but also generate value for the platform by leveraging individual green actions as soft information, thereby improving the efficiency of credit allocation. Using a structural model, we estimate an annual green value of 427.52 million US dollars generated by linking personal carbon accounting with BigTech credit. We also show that the incentive-based mechanism surpasses green mandates and subsidies in improving consumer welfare and overall societal welfare. Our findings highlight the role of an incentive-aligned approach, such as integrating personal carbon accounts into credit reporting frameworks, in addressing environmental challenges.

We introduce a novel perspective on private information, specifically microstructure-based private information, to unravel how institutional investors predict stock returns. Using tick-by-tick transaction data from the Chinese stock market, we find that in retail-dominated markets, institutional investors positively predict stock returns, consistent with findings from institution-dominated markets. However, in contrast to the traditional view that institutional investors primarily rely on value-based private information, our results indicate that microstructure-based private information contributes almost as much to their predictive power as value-based private information does, with both components jointly accounting for approximately two-thirds of the total predictive power of institutional order flow. This finding reveals that retail investors’ trading activities significantly impact institutional investors, naturally forcing them to balance firm value information with microstructure information, thus profoundly influencing the price discovery process in the stock market.

With the increasing executive-employee pay disparity in recent years, research on executive compensation has grown exponentially. This paper reviews all articles on executive compensation published between 2000 and 2022 in the six accounting journals with the highest impact index in South Korea and China (five journals in China), and evaluates and analyzes the research in both countries. The analysis results are organized as follows: First, the research on executive compensation started earlier in South Korea than in China; second, the focus of the research on executive compensation differs between the two countries; then, the study on the determinants of executive compensation varies between the two countries; forth, the proxies for firm performance are mostly the same in the two countries; and finally, most of the studies in the two countries assert that executive compensation has a positive impact on firm performance. Based on the above research, this paper confirms that the agency theory, which has been widely validated in Western countries, is also valid in Asian countries. In addition, it provides an essential reference for future research on executive compensation in Asian countries.

Software and accounting advances have led to a rapid expansion in and proliferation of loyalty tokens, typically bundled as part of product price. Some tokens, such as in the airline industry, already account for tens of billions of dollars and are a major contributor to revenues. An open question is whether, as technology evolves, firms will have a strong incentive to make loyalty tokens tradable, raising regulation issues, including with monetary and banking authorities. This paper argues that for the vast majority of tokens, issuing firms have a strong incentive to make them non-tradable. The core incentive for token issuance here is that an issuer can earn a higher rate of return on the ``float'' (tokens issued but not yet used) than its retail customers can, much like a bank. Our main finding is that an issuer earns higher revenue by making tokens non-tradable even though the consumer would be willing to pay a higher price for tradable tokens. We further show that an issuer with stronger market power tends to allow more frequent token redemption, and its revenue is more token-dependent. We test the model's predictions with data on airline mileage and hotel reward programs and document consistent empirical results that align with our theory.

We examined reference point adaptation following gains or losses in security trading using participants from China, Korea, and the US. In both questionnaire studies and trading experiments with real money incentives, reference point adaptation was larger for Asians than for Americans. Subjects in all countries adapted their reference points more after a gain than after an equal-sized loss. When we introduced a forced sale intervention that is designed to close the mental account for a prior outcome, Americans showed greater adaptation toward the new price than their Asian counterparts. We offer possible explanations both for the cross-cultural similarities and the cross-cultural differences.

This paper provides new evidence on the predictive power of retail trading for future stock returns using tick data from the Chinese stock market. We explore sources of the predictive power from the novel perspective that sophisticated retail investors may exploit predictive information by observing limit order book and inferring institutional trading intentions. Employing a two-stage decomposition approach, we decompose the retail order imbalance into four components and find that the component related to retail investors’ perception of institutional trading intentions significantly contributes to the predictive power of the retail order imbalance for future returns, accounting for more than 15%.