This paper utilizes data from Chinese A-share listed companies and, based on the limited attention theory, reexamines the impact of data asset disclosure on capital market pricing efficiency. The study finds that the economic consequences of data asset disclosure are not static but exhibit a significant marginal decreasing feature as the overall market disclosure level rises. Specifically, when the overall market disclosure level is low, corporate disclosure of data asset information can significantly reduce stock price synchronization and enhance capital market pricing efficiency by increasing the supply of idiosyncratic information, enhancing information diffusion, and accelerating information integration. However, with the recent widespread disclosure behavior, there is no evidence that the above mechanisms remain effective. Further analysis indicates that disclosure behavior can maintain its positive effect only when the overall market disclosure level of data assets is low, and the firm's disclosed idiosyncratic information is relatively limited, the information dissemination environment is favorable, or institutional investor attention is not excessively diffused. This paper expands the boundaries of the limited attention theory, extending the research perspective to the dimension of the dispersion of investor attention by homogenized information, and reveals the value dilution problem faced by data asset information disclosure in the context of universalization.

We investigate whether China's 2021 mining ban transformed Bitcoin from a speculative vehicle into a macro-sensitive asset. Using daily data from 2017-2025, we document a decisive structural break. Pre-2021, volatility was endogenous, driven by raw trading volume rather than fundamentals. Post-ban, however, internal microstructure noise loses predictive power. Instead, volatility is now driven by macroeconomic anxiety: Wikipedia searches for "Inflation" improve forecast accuracy by over 7%. We further uncover a "dual narrative" where inflation attention predicts crash risk, while "Recession" queries (pivot speculation) drive rallies. These findings suggest the regulatory shock successfully curtailed noise trading, allowing macro-fundamentals to dominate price discovery.

Purpose-This study explores how inconsistency in environmental, social and governance (ESG) ratings affects the information environment of publicly traded companies in emerging markets. Design/methodology/approach-Drawing on data from six ESG rating agencies covering listed Chinese firms from 2010 to 2022, we construct measures of pairwise ESG rating divergence and average them across 15 unique rater pairs. We then employ a battery of econometric methods to examine how inconsistencies in ESG ratings affect stock return synchronicity in the Chinese capital market. Findings-Our findings indicate that greater ESG rating divergence correlates with increased stock return synchronicity, suggesting a decline in the dissemination of firm-specific information. Supporting evidence for this relationship includes reduced private information flow, heightened opportunistic executive sales and decreased stock turnover for firms associated with higher ESG rating divergence. Our analysis suggests that such divergence hinders informed trading by institutional investors and the effect is more pronounced for firms with lower transparency, such as those with fewer analysts, limited investor oversight and sparse ESG disclosure, as well as for firms in non-polluting industries. These findings emphasize that ESG rating divergence exacerbates uncertainty about firms' future performance, discourages informed trading and ultimately restricts the integration of firm-specific information into stock prices. Originality/value-This study adds to the literature on ESG ratings and market efficiency by highlighting the importance of standardizing rating methodologies and improving corporate disclosure to counteract the adverse impacts of rating divergence.

We develop a theoretical model in which investors evaluate dual-listed stocks through the prospect theory value of their historical return distributions. When the prospect theory value (PTV) of A shares exceeds that of H-shares, the A-share price will be higher than the H-share price, generating a persistent equilibrium price premium despite identical fundamentals. Using Chinese A–H dual-listed firms, we find that the PTV difference positively explains the AH premium. A gain–loss decomposition shows that A-shares have higher PTV because their less negative loss contribution more than offsets their smaller gain contribution. Consistent with this result, loss aversion and value-function curvature exhibit stronger pricing relationships than probability weighting. Investor composition shapes the pricing influence of PTV. Our results also explain why the AH premium increased following deeper market integration, like the Shanghai–Hong Kong Stock Connect.

This paper develops a theoretical and empirical framework to analyze China's interest rate corridor, focusing on the Standing Lending Facility (SLF). We construct a general equilibrium model featuring an explicit corridor and a novel accessibility cost friction (α), which captures implicit costs during SLF application. The theoretical properties of the model explain key stylized facts associated with the corridor operation. The study highlights several fundamental properties of the corridor as a policy framework: 1) Both the width and the midpoint of the corridor are active policy tools, implying that SLF and Interest on Excess Reserves (IOER) policies should be designed cohesively within the unified corridor framework; 2) The policy's efficiency varies with the level of market liquidity; and 3) The corridor framework allows for a separation between price-based and quantity-based monetary policy instruments. Empirically, we employ the Joint Power Prior (JPP) Bayesian estimation to quantify the α time series, identifying structural breakpoints that align with major policy and market events. This study provides a quantitative tool for monitoring SLF transmission efficiency.

Firms’ export and import participation are positively correlated, a pattern known as two-way complementarity. In this paper, we refine its concept, develop empirical measures, identify its micro-foundations, and explore associated welfare implications. In a general equilibrium trade model with heterogeneous firms, we show that twoway complementarity emerges endogenously from the way trade costs align firms’ joint import and export decisions. We then derive an ACR-style gains-from-trade formula that incorporates this channel. Two-way complementarity amplifies aggregate trade elasticities, leading to smaller inferred welfare gains from a given decline in domestic trade shares after a trade reform. Using Chinese micro data, we document empirical support for the model predictions and find that failing to account for the complementarity overstates China’s gains from WTO accession by around 40%.

This paper focuses on China's green financial development context, selects carbon taxes and green credit policies as adjustable fiscal instruments, constructs a four-sector dynamic stochastic general equilibrium (DSGE) model, and innovatively divides the production sector into traditional and clean firms. We then separately investigate the impacts of these two structural policies on green economic development. The impact of structural policies on the development of green economy and emission reduction is investigated individually in terms of each policy. The results of the study show that the positive impacts of green credit and pollution tax rate have a significant inhibiting effect on pollution emissions; for total output, the policy of adjusting the carbon tax rate has a negative impact on economic development, while the negative impacts of targeted subsidy on economic development in the long run are not obvious. Based on this, this paper combines the green development practice to put forward the corresponding policy recommendations for the construction of a green low-carbon development policy system to provide references.

In this paper, we investigate the availability of external finance for state-owned enterprises (SOEs) and private enterprises (PEs) across all manufacturing industries in China. Employing a disequilibrium model, we find that SOEs are generally less financially constrained than PEs, but the difference is of small magnitude and has been steadily declining over time. We also reveal a positive relation between the advantage of SOEs in accessing external funds and the level of SOE monopoly at the industry level. In general, while SOEs and PEs are equally constrained in competitive downstream industries, we find a significant comparative advantage in accessing external finance for SOEs in monopolized mid- and upstream industries. The policy implication is straightforward: to finance PEs better, the Chinese government should consider breaking the existing monopolies or near monopolies of SOEs in certain industries further, rather than encouraging banks to favor PEs in their lending.

We study how alternative data influences investors’information acquisition and market efficiency from both short-term and long-term perspectives. Using the exogenous introduction of online sales data on a major Chinese financial information platform, we find that such disclosure enhances investors’information processing capacity. In the short term, firms covered by online sales data exhibit weaker market reactions to unexpected earnings, reflecting more accurate earnings expectations. In the long term, online sales disclosure strengthens the link between earnings and stock returns, indicating higher earnings value relevance. These results are robust to a series of endogeneity tests and robustness checks. Cross-sectional analyses indicate that these effects are more pronounced for firms with lower institutional ownership, higher earnings volatility, and greater reliance on online sales. Mechanism analyses show that short-term effects operate through improved analyst forecast accuracy, while long-term effects are jointly driven by higher firms' earnings quality and enhanced analyst performance. These findings offer new perspectives on market efficiency and fresh evidence on investor information processing.

In automobile markets where consumers attach social recognition to car ownership, how does the introduction of a lower-cost alternative influence the market outcomes of traditional internal combustion engine vehicles (ICEVs)? Leveraging high-frequency sales data covering China's entire automobile market from 2018 to 2022, we examine heterogeneous market responses to the emergence of electric vehicles (EVs) across different price segments. Overall, the rise of EVs is associated with lower ICEV sales but higher total automobile sales. More importantly, while EV penetration is negatively correlated with ICEV sales in the lowand mid-end segments, it is positively correlated with ICEV sales in the high-end segment. Further evidence suggests that the rise of EVs amplifies the symbolic value of high-end ICEVs, boosting sales of ICEV models with strong social recognition.