Supply chain standardization significantly promotes cross-regional investment by increasing subsidiaries outside headquarters cities, mainly by reducing transaction and information costs and alleviating “outsider disadvantage.” This effect is stronger for non-state-owned firms, firms with lower financing constraints, and those in highly marketized regions. Our findings show that standardization helps overcomeinstitutional and information barriers, optimizing resource allocation. This study expands supply chain governance literature and offers insights for building a unified national market.

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.

A central premise of mandatory disclosure regulation is that greater transparency reduces information asymmetry and lowers borrowing costs. We challenge this premise by examining industry-level operational disclosure - a regulatory form that reveals horizontally comparable information across peer firms rather than refining individual firm fundamentals. Exploiting the staggered introduction of mandatory industry-specific disclosure guidelines by Chinese stock exchanges between 2013 and 2019, we find that enhanced industry disclosure significantly widens bond credit spreads by approximately 54 basis points - the opposite of what standard disclosure theory predicts. This counterintuitive effect is more pronounced in non-homogeneous industries, among smaller firms, and for bonds restricted to institutional investors. Mechanism tests confirm two opposing channels: disclosure reduces information asymmetry while simultaneously intensifying product market competition by exposing strategically sensitive operational metrics. Our evidence challenges the one-size-fits-all approach to disclosure regulation and highlights that the competitive implications of disclosed information - not merely its quantity - shape credit risk pricing.

We examine the unintended consequences of bankruptcy court establishment on corporate behavior. Using data on Chinese listed firms from 2009 to 2019 and a staggered difference-in-differences model, we find that the establishment of bankruptcy courts increases accrual earnings management by about 17% among high bankruptcy risk firms relative to low-risk firms. While bankruptcy courts improve bankruptcy efficiency and justice, reduce local government intervention, and accelerate the exit of zombie firms, they also induce greater earnings management. This effect is driven mainly by survival pressure and managerial reputation concerns, rather than by efforts to correct external evaluations. Consistent with this interpretation, we do not observe improvements in long-term operations, governance, performance, or real earnings management. Overall, this paper enriches the literature on earnings management from the perspective of judicial governance and on the economic consequences of creditor-friendly bankruptcy institutions.

Hyman Minsky (1919–1996), a prominent post-Keynesian economist, argued that capitalist financial systems are inherently unstable. During prolonged prosperity, firms and financial institutions increase leverage and adopt more fragile forms of financing, shifting from hedge to speculative and Ponzi finance. This gradual buildup of financial fragility can eventually trigger a sudden collapse of asset values—later termed a “Minsky moment.” After the 2007–2009 global financial crisis, Minsky’s ideas gained renewed attention, and current financial developments once again bring his insights to the forefront.

This paper examines the use of finance leases in China’s local government debt. Using a unique dataset of government finance lease transactions, we document that local government financing vehicles (LGFVs) rapidly adopted finance leases, with the outstanding amount growing from virtually nothing in 2013 to a cumulative total of 1.02 trillion RMB by 2018. Our difference-in-differences (DID) analysis reveals that the central government’s restrictive financial policies account for a substantial portion of this surge. Because these restrictive policies confined LGFVs’access to conventional borrowing channels, finance leases emerged as a key alternative, particularly through bank-affiliated leasing firms. While LGFVs' use of finance leases offers low-cost financing for local governments, the low quality of the underlying assets poses significant risks to the leasing firms.

The China Securities Regulatory Commission is allowing firms to use externally financed funds for share repurchases, a recent measure to enable listed companies address valuation pressures and protect investors; however, its implications for corporate marketing decisions remain unclear. Using an event sample of Chinese listed firms that conducted open-market repurchases between 2009 and 2024, this study empirically examines how this market activity financed by different sources influence marketing decisions and explores the underlying mechanisms. The findings show that compared with firms using internal cash for repurchases, those relying on debt financing are inclined to resist myopic marketing decisions, and this negative relationship is pronounced under high analyst coverage and when privately owned listed firms are controlled by family entrepreneurs. These results remain robust after replacing the dependent variables and applying propensity score matching. Overall, this study shows that debt financing to support share repurchases has a long-term beneficial governance impact as it improves earnings quality and protects investor interests, and offers a new perspective on the relationship between financing-based repurchases and marketing myopia, and provides useful policy insights for evaluating the effectiveness of China’s refinancing regulations related to share repurchases, while guiding further refinement.

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.

This paper examines the spillover effects of China’s Carbon Emissions Trading Scheme (CETS) on non-regulated firms’ bank loans. Using a sample of Chinese A-share listed firms and a staggered difference-in-differences design, we find that suppliers experience a significant decline in bank loans when their customers are included in the CETS. This effect is driven by reductions in firms’ cash flow and customer concentration. The negative effect of downstream CETS on suppliers’ bank loans is attenuated for suppliers with better environmental performance, more comprehensive carbon disclosure, and closer geographic proximity to customers. We also find that, in response to reduced bank credit, firms rely more heavily on trade credit. Overall, this study sheds new light on the unintended financial consequences of CETS policy on non-regulated firms.