This paper quantifies the impact of rural–urban migration on agricultural fires, a major source of air pollution in China. Using satellite records and census data, we exploit an exogenous trade shock that raised manufacturing labor demand in destination prefec-tures, drawing workers from origin counties through established migration networks. A one-percentage-point increase in rural labor emigration in 2010 led to a 5% rise in agricultural fires from 2011 to 2017. The effect stems from reduced agricultural labor, which incentivizes fire use as a labor-saving clearing method. Consistent with this mech-anism, we find no effect from non-agricultural emigration or from migration to nearby areas where return farming remains feasible, with the strongest impact during harvest seasons. Institutional reforms, particularly land titling programs, significantly mitigate the problem by enhancing tenure security, enabling farmland reallocation, and reducing reliance on fire—proving more effective than nationwide administrative bans.

Cultural tightness measures the extent to which individuals behave according to the broader values shared by other members in society. While cultural tightness has been studied extensively in the context of individuals’ behavior and (cross) country-level outcomes, much less is known about the explanatory power it holds in the setting of organizational structures. Motivated by the ambiguous relationship between cultural tightness and population-level gender equality documented by prior literature, we investigate whether cultural tightness helps explain board gender diversity levels in China. Rooting our hypotheses in institutional theory and the contextual governmental reforms of China, we leverage a large sample of Chinese A-share listed firms and document that firms located in culturally tight provinces have higher levels of board gender diversity. Further analyses reveal that cultural tightness in China partially offsets the impact of more traditional Confucian values, and the relationship becomes more pronounced in settings where firms can realize higher legitimacy gains from adopting women on their boards. Finally, we counter potential critiques of window dressing, by demonstrating that in culturally tighter areas women are more likely to be higher educated, have more experience abroad, hold more board positions, and are less likely to be independent directors.

This study examines the mean-reversion behavior of trading volume in China’s A-share market, with a focus on the speed at which abnormal surges dissipate. We compare two competing hypotheses: the stealth-trading hypothesis, where persistent volume reflects order-splitting by informed traders, and the informational-efficiency hypothesis, which interprets faster reversion as a sign of efficient information absorption. Using the Ornstein–Uhlenbeck (OU) model, we estimate the reversion speed for over 3,000 stocks and link it to firm- and industry-level characteristics. We find that trading volume is strongly mean-reverting, with over 98% of stocks classified as stationary. The OU model forecasts reversion speed with less than 7% error. Faster reversion is associated with larger size, higher analyst coverage, lower volatility, and greater liquidity. Notably, reversion speed increased after the 2006 IFRS reform but declined following Stock Connect, suggesting that stock market policies can influence informational efficiency. Our OU-based methodology offers a simple, observable proxy for monitoring how quickly markets process information. These results position trading volume as a core variable in market microstructure research and policy evaluation.

This study investigates the mean-reversion behavior of trading volume, using China’s A-share market as a representative setting characterized by dispersed retail investors, frequent public disclosures, and active policy interventions. We compare two competing interpretations:the stealth-trading hypothesis, in which persistent volume reflects order-splitting by informed investors, and the informational efficiency hypothesis, which links faster volume reversion to more effective information processing. Using the Ornstein–Uhlenbeck (OU) model, we estimate reversion speeds for over 3,000 stocks and relate these to firm- and industry-level characteristics. We find that trading volume is broadly mean-reverting, with over 98% of stocks exhibiting stationarity. The OU model forecasts reversion speed with less than 7% error. Faster reversion is associated with larger firm size, greater analyst coverage, lower volatility, and higher liquidity. Notably, reversion speed increased after accounting reforms but declined following capital access liberalization, suggesting that regulatory policy can both enhance and impair informational efficiency. These findings position reversion speed as an observable proxy for market responsiveness and highlight trading volume as a central variable in empirical market microstructure research.

This paper studies the economic impact of introducing a personal bankruptcy regime, using China’s recent pilot reforms as a natural experiment. We exploit the staggered rollout of personal bankruptcy frameworks across Chinese cities and construct a novel dataset of bankruptcy case filings, combined with survey-based measures of credit access and official firm registration records. Our difference-in-differences estimates show that the reforms significantly improve small business credit access - business loan take-up increases by 1.3 % (21% relative to pre-reform mean), with no offsetting rise in interest rates. Effects are concentrated among non-corporate firms, firms with less employees and female entrepreneurs. Moreover, the reform is also associated with a 9.7% increase in new firm registrations. To interpret these findings, we develop a simple but novel theoretical model in which personal bankruptcy reduces the downside risk of entrepreneurial failure while preserving creditor recoveries. These findings underscore how debtor protection policies, when designed to reduce enforcement costs without expanding exemption rights, can enhance credit supply and entrepreneurial activity.

This paper examines why tax incentives fail to stimulate participation in China's third-pillar commercial pension insurance, emphasizing the role of rational inattention. Using household survey data from China Family Panel Studies (CFPS) spanning 2014-2022 and a difference-in-differences-in-differences (DDD) design, we find that pilot policy generated a statistically insignificant average effect on participation, with rational inattention - proxied by financial literacy - explaining much of its ineffectiveness. We develop a dynamic consumption-portfolio model featuring costly information acquisition, and then resolve limitations of standard models through a dynamic framework with distinct savings channels and policy-focused rational inattention. The models show that rational inattention distorts perceptions of tax benefits and wage growth, raising participation costs, while multiple savings channels dilute incentives. Only households with higher financial literacy substantially respond to the policy. Our results reveal how cognitive frictions undermine pension reform and offer implications for designing behaviorally-informed retirement schemes.

We combine a new collection of microdata from China with a natural policy experiment to investigate the extent to which reductions in rural-urban migration barriers affect flows of trade and investments between cities and the countryside. We find that increases in worker eligibility for urban residence registration (Hukou) across origin-destination pairs increase rural-urban exports, imports, capital inflows and outflows, both in terms of bilateral transaction values and the number of unique buyer-seller matches. To quantify the implications at the regional level, we interpret these estimates through the lens of a spatial equilibrium model in which migrants can reduce buyer- seller matching frictions. We find that a 10% increase in a rural county’s migration market access on average leads to a 1.5% increase in the county’s trade market access and a 2% increase in investment market access. In the context of China’s recent Hukou reforms, we find that these knock-on effects on market integration were on average larger among the urban destinations compared to the rural origins, reinforcing incentives for rural-urban migration.

The reform of the IPO registration system is a crucial step toward the maturity, improvement, and marketization of the securities market. In recent years, the trend of corporate financialization has become increasingly evident. Based on data from firms listed on the ChiNext Market and the Main Board, this paper constructs a Propensity Score Matching-Difference-in-Differences (PSM-DID) model and an RDD-DID model to examine the impact of IPO registration system reform on corporate financialization and analyze its underlying mechanisms from multiple perspectives. The estimation results of both models indicate that the IPO registration system reform has significantly increased firms’ financialization levels. Furthermore, a series of robustness checks confirm the reliability of the findings. The mechanism analysis reveals that the reform has promoted corporate financialization by lowering listing thresholds, alleviating financing constraints, and intensifying market competition. Meanwhile, its information disclosure mechanism has to some extent curbed financialization. Further heterogeneity analysis shows that the reform’s promoting effect is more pronounced in non-state-owned enterprises, firms with lower growth potential, and those with weaker corporate social responsibility (CSR) performance. This study enriches the literature on the policy impact of IPO registration system reform, provides a new perspective on how such reforms influence corporate financialization, and offers important implications for curbing excessive financialization in real-sector enterprises, deepening IPO registration system reform, and further improving capital markets.

We construct a daily Chinese Housing Market Sentiment Index by applying GPT-4o to Chinese news articles. Our method outperforms traditional models in several validation tests, including a test based on a suite of machine learning models. Applying this index to household-level data, we find that after monetary easing, an important group of homebuyers (who have a college degree and are aged between 30 and 50) in cities with more optimistic housing sentiment have lower responses in non-housing consumption, whereas for homebuyers in other age-education groups, such a pattern does not exist. This suggests that current monetary easing might be more effective in boosting non-housing consumption than in the past for China due to weaker crowding-out effects from pessimistic housing sentiment. The paper also highlights the need for complementary structural reforms to enhance monetary policy transmission in China, a lesson relevant for other similar countries. Methodologically, it offers a tool for monitoring housing sentiment and lays out some principles for applying generative AI models, adaptable to other studies globally.

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.