Partially convertible economies face a market-design problem: trade integration, cross-border investment, and domestic balance-sheet exposure increase the demand for currency hedging before full financial integration is complete. China adopted a distinctive architecture for this problem by fostering a deliverable offshore Renminbi market (CNH) alongside the segmented onshore market (CNY), rather than relying only on non-deliverable forwards. This creates two venues for closely related claims on the same currency. Spot prices are tightly linked, yet CNY and CNH forwards display a persistent and economically large discrepancy. We study that discrepancy in a joint equilibrium model for spot and forward trading with transaction costs and segmented supply. In the benchmark case with common constant supply and deterministic costs, spot parity implies a forward differential with the wrong sign relative to the data. Random offshore stress, modeled as a jump in trading costs, overturns this benchmark while preserving tight spot parity. The model yields a semi-explicit representation in the CNY/CNH application and a calibration of the observed forward discrepancy in terms of the market-implied likelihood and severity of offshore liquidity stress.

With the development of China's economy, more and more Chinese enterprises are active on the world stage, and cross-border M&A is the most effective and fastest way for enterprises to go abroad and make overseas investments, and it is also an important path for globalization after the enterprises have reached a certain stage of growth. Compared to domestic M&A, cross-border M&A is a more complex economic activity, requiring more factors to be considered and greater risks to be taken, with the slightest misstep often leading to operational difficulties for the acquiring company. It is important to consider whether cross-border M&A can improve business performance, the factors that influence the performance of cross-border M&A, and how to improve the performance of enterprises in cross-border M&A. This study takes 100 cross-border M&A events of Chinese listed companies in Shanghai and Shenzhen during the period of 2017-2020 as a sample, and on the basis of reviewing the research results of cross-border M&A at home and abroad, combined with the characteristics of cross-border M&A of Chinese enterprises, from different perspectives, a number of financial indicators are selected to construct comprehensive performance evaluation indicators using factor analysis, and the preliminary analysis shows that after cross-border M&A, the companies with increased performance The preliminary analysis showed that the number of companies whose performance increased after cross-border M&A increased year by year. The impact of industry relevance and transaction equity on M&A performance is not significant; the ratio ofM&A amount to current assets negatively affects firm performance in the year of M&A. Finally, based on the empirical results, relevant policy recommendations are made to encourage better development of private enterprises and improving cross-border M&A performance.

This study examines the role of artificial intelligence (AI) adoption in the market for corporate control using a sample of Chinese listed firms from 2011 to 2021. We construct a novel firm-level AI Index through textual analysis of annual reports and find that AI adoption significantly enhances both the likelihood of becoming an acquisition target and the valuation premiums commanded in M&A transactions. Specifically, a one-standard-deviation increase in the AI Index is associated with a significant increase in the probability of being acquired and higher deal premiums measured by price-to-earnings multiples. We identify two channels through which AI adoption creates value recognized by the M&A market: an efficiency channel, whereby AI reduces agency costs and improves profitability, and an innovation channel, evidenced by increased high-quality patent output. The persistence of these effects over time further suggests that AI adoption generates substantive improvements in firm fundamentals rather than serving as a transitory informational signal. Importantly, we document significant heterogeneity across ownership structures: the positive effects of AI adoption are substantially weaker for State-Owned Enterprises (SOEs) than for non-SOEs. Our findings contribute to the literature on digital transformation and corporate finance by demonstrating that AI adoption serves as a value-relevant firm attribute that shapes outcomes in the market for corporate control.

This paper studies whether financial technology (FinTech) changes loan contract design by reducing banks’ reliance on collateral in corporate lending. Using loan-level data on Chinese listed firms from 2007 to 2023 and exploiting the People’s Bank of China’s 2019 FinTech Development Plan as a quasi-natural experiment, we find that banks with stronger pre-policy FinTech capability significantly reduce secured lending after the policy shock. In the benchmark specification, the probability that a loan is secured falls by 1.64 percentage points, or about 2.7% relative to the baseline secured-loan share. The result is robust to alternative loan classifications, matching procedures, alternative measures of FinTech adoption, aggregated lending outcomes, and alternative inference procedures. The pattern is more pronounced among small and medium-sized enterprises, lower-tier branches, and branches located outside bank headquarters’ cities, where borrower information is likely to be more limited. Supplementary analyses are consistent with FinTech reducing banks’ information-production costs and suggest that technological proximity to FinTech-active peers may amplify the collateral-reducing effect. Overall, the evidence indicates that FinTech can enhance banks’ screening capacity and shift lending decisions away from reliance on asset-based guarantees toward information-based credit assessment.

Technology firms are often financed on narratives about products, contracts, customers, and technological progress well before these developments appear in accounting statements. We ask when such narratives become economically informative. Our central idea is that narratives should matter more once they can be linked to later verifiable outcomes rather than treated as stand-alone text.Using listed Chinese technology firms, we develop a validated corporate narrative framework for bank-affiliated investment, a setting in which investors must screen with soft information ex ante and then monitor hard realization and downside risk ex post. We use GPT-5.1 to extract business claims from management discussion, investor-relations records, exchange Q&A, and earnings-roadshow materials, and to label later claim–evidence pairs as support, partial support, conflict, duplicate, or irrelevant. We then connect these labels to official announcements, procurement awards, permits, project updates, and negative-event disclosures to construct a validated firm-month signal. The broad merged panel contains 592 firms and 30,169 firm-month observations; the main return tests use 576 firms and 18,230 firm-month observations over 2022–2024. A simple production rule that combines a low-narrative-premium component with hard-narrative and hard-event anchors, together with a separate downside-risk gate, delivers an implementable annualized long-short return of 8.93% in bank-invested firms after trading costs. The signal is much weaker in non-bank firms, predicts future gross-margin improvement more strongly than future ROE, and improves downside screening.

Breaking away from being “large but not strong” and accelerating the internal “dual circulation” reform to integrate the manufacturing and service industries is a daunting challenge. This study examines how environmental regulations and financial instruments can simultaneously drive servitization evolution and green transformation. Utilizing the Green Credit Guidelines (GCG) policy rollout by China in 2012 as a quasi-natural experiment, we analyze 2007-2021 data from A-share listed manufacturing corporations through DID model to evaluate the policy ramifications and investigate servitization direction. The results show that: (1) While GCG generally promotes overall servitization, it biases firms toward traditional rather than modern servitization pathways. (2) Contrary to typical innovation compensation effects, GCG induces short-sight in managerial decisions, favoring quick wins over innovation-driven progress. These results highlight why firms have tended to advance traditional servitization while constraining modern servitization efforts. (3) Heterogeneity analysis shows stronger policy impacts in firms with domestically-oriented executives and domestic ownership, where both overall and traditional servitization are significantly enhanced.

The parking reservation systems (PRS), as an intelligent system, was adopted to address urban parking difficulties. However, the parking reservation system has not been widely adopted in China due to the reasons such as the imperfect system and the uncontrollable parking behaviour of users. This study examines the impact of users' non-compliant behaviour on intentions to reuse PRS. Non-compliant behaviours include not arriving or leaving parking spaces not as scheduled, negatively affecting subsequent users. The Technology Acceptance Model (TAM) was expanded by adding perceived risk, social influence, and behavioral attitude. A survey involving 702 PRS users from multiple Chinese cities was conducted. Structural Equation Modelling (SEM) was used for analysis Results show that perceived risk—such as occupied reserved spaces and extra fees from time deviations—significantly reduces behavioral attitudes and reuse intentions. Conversely, perceived usefulness, ease of use, and social influence positively influence both attitudes and reuse intentions. Importantly, the findings highlight that behavioral uncertainty, particularly users’ deviations from scheduled parking times, is a critical source of perceived risk that undermines trust and long-term engagement. Effectively managing this uncertainty through improved system flexibility and reliability is therefore essential to promoting the sustained adoption of PRS.

This study challenges democratic citizenship theory by examining altruistic behaviour in authoritarian China. We find that financial resources influence prosocial engagement primarily through psychological mediators such as long-term planning and self-discovery, rather than directly providing material means for participation. Communist Party membership shapes specific domestic ideological orientations, but not attitudes toward market regulation or income equality, while cultural tradition emerges as a stronger predictor of certain political attitudes than party affiliation. Cluster analysis identifies three distinct citizen profiles: (1) future-oriented altruists; (2) status-driven contributors; and, (3) short-termpragmatists, revealing motivational heterogeneity within authoritarian publics. These findings suggest that authoritarian citizenship operates through psychological mediation and plural motivational pathways fundamentally different from democratic societies, with potential applicability to other single-party regimes where states actively structure prosocial behaviour. The study contributes to comparative authoritarianism literature by theorizing how regime type moderates the relationship between socio-economic resources, political identity, and civic engagement.

Bankruptcy abuse prevention has been criticized for increasing foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention reduces household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results. 预防破产滥用的政策被认为推高止赎率、对住房市场造成负面影响以及加剧金融危机而饱受批评。与之相反，本文证明破产滥用预防能够缓解家庭债务积压（debt overhang）—— 而债务积压恰恰是一种损害房屋价值与住房市场的现象。采用双重差分（DID）分析，我们发现：在《破产滥用预防与消费者保护法案》（BAPCPA）实施后，**追索权州（recourse states）**的家庭增加了住房改善与维护支出；该时期家庭对住房市场的下行风险高度关注，且上述效应因房屋净值水平的不同而存在异质性。在多种替代设定下结果依然稳健，且不能被信贷变化、司法与非司法止赎、宅基地豁免、房屋销售或异质性预期所解释。最后，我们使用熵平衡（entropy balancing）方法消除处理组与控制组之间的差异，同样得到了一致的结果。

How do market-design reforms affect secondary-market liquidity in an emerging equity market? We examine China’s ChiNext reform, which combined registration-based IPO issuance with changes in secondary-market trading rules. Using firm-month observations and high-frequency order-book data, we compare incumbent ChiNext firms with Main Board firms in a difference-in-differences framework. The results show that the reform significantly improves secondary-market liquidity, with consistent evidence across alternative DID estimators and liquidity measures. Dynamic estimates show comparable pre-reform movements and increasingly favorable liquidity outcomes after implementation. Cross-sectional analysis indicates stronger liquidity improvements among larger and more profitable firms. Microstructure results show narrower quoted spreads, broadly stable displayed depth, and a shift in order flow toward buyer-initiated trading. Overall, the findings demonstrate that the integrated ChiNext reform package improved secondary-market liquidity and reshaped the cross-sectional distribution of liquidity gains, highlighting the market-quality consequences of institutional reform in emerging equity markets.