We construct a text-based measure of war-related diplomatic sentiment from 154,185 foreignministry communications across the 15 largest world economies. The daily index tracks military escalations and ceasefires, varies across countries, and predicts newspaper-based geopolitical risk more than the reverse. Adverse Chinese rhetoric foreshadows stronger southbound reallocation into Hong Kong equities and weaker Stock Connect flows; a one-unit decline shifts daily flows by $42.4 million towards outflows, operating through a relative-price channel widening the AH premium rather than onshore declines. In monthly cross-country analyses, only the U.S. shows safe-haven behavior; adverse rhetoric raises Chinese and U.S. trading volume and U.S. volatility.

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.

The global AI inference market—reaching approximately $90–100 billion annually and growing at 18% CAGR—operates without organized exchange infrastructure. We document three market failures: resource misallocation (80% of China’s newly built compute capacity sits idle), price opacity (100-fold price dispersion across providers of equivalent quality), and unhedged risk exposure (85% of enterprises miss AI cost forecasts by more than 10%). Following the market design tradition of Roth [2002] and Budish et al. [2015], we propose the AI Service Right (ASR) as a transferable property right on AI compute and the AI Service Unit (ASU) as a quality-adjusted, cross-platform unit of account grounded in hedonic price theory [Rosen, 1974]. The ASU is modality-neutral: billing prices across text, image, video, and speech modalities are unified via eq-token conversion factors (κimg ≈ 2,667 eq-tokens per image; κvid ≈ 2,667 per second of video; κspc ≈ 7 per second of audio), and modality-appropriate benchmark sets (MMLU/HumanEval for language; FID/CLIP Score for image; FVD/CLIPSIM for video; MMBench for multimodal) supply the quality in dex via PCA. We design a hybrid secondary market architecture synthesizing mechanisms from four orthogonal market traditions: foreign exchange markets (cross-platform exchange rates and PPP-analog arbitrage via the ASU); equity markets (Central Limit Order Book, market making, clearing); electricity markets (Compute Locational Marginal Pricing for spatial scarcity signals); and decentralized finance (Automated Market Maker for long-tail liquidity). We establish nine formal propositions: bilateral trading is generically inefficient; Compute Locational Marginal Pricing decomposes nodal prices into system marginal cost, capacity congestion, and bandwidth premia; no-arbitrage equi librium holds with capital constraints (extending Shleifer and Vishny 1997); the ASR market Pareto-improves over bilateral trading; market prices are more in formative under ASR; the hybrid CLOB-AMM architecture weakly dominates either mechanism alone; platform adoption admits multiple equilibria with a coordination trap; financialization may improve or reduce price informativeness depending on speculator-hedger composition; and a hedonic micro-foundation justifies the ASU definition. Calibrated agent-based simulation (500 steps, 30 Monte Carlo runs) provides computational validation: the hybrid architecture reduces price dispersion by 90% relative to bilateral trading, and order-of-magnitude welfare estimates suggest enterprise procurement cost savings of 0.2–20% (net of ASR transaction costs; see Table 7) and potential TFP gains from compute reallocation of up to $29.9 billion annually. We propose a phased implementation roadmap from shadow ledger to full financialization, and we engage critically with the concern that financialization may not reduce intermediation costs [Philippon, 2015].

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.

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 identifies the marginal investors in China’s stock market and examines their impact on stock pricing. To clearly distinguish between the equity constraint channel and the debt constraint channel, we construct the capital ratio factor and the debt constraint factor for banks and securities companies, the two most critical financial intermediaries in China’s stock market. Our results demonstrate that banks indeed serve as marginal investors and influence stock market efficiency primarily through the equity capital constraint channel. Furthermore, we find that the bank capital ratio factor significantly explains stock mispricing in China, with the single-factor model based on bank equity capital producing substantially smaller pricing errors compared to traditional multi-factor models.

Against the backdrop of global green development and China’s sustainable economic transition, many firms exaggerate green-transition disclosures to cater to national strategies and capital market preferences, leading to a severe "Say–Do Gap". Based on signaling theory, this study uses the phased establishment of environmental courts in 208 prefecture-level cities as a quasi-natural experiment, adopting a staggered DID design with 2007–2023 panel data of Chinese A-share listed firms for empirical tests. Results show widespread corporate green pandering, with improved disclosure not translating into actual carbon reduction. Environmental courts effectively curb this behavior, with environmental litigation risk as the core mediating channel. Heterogeneity tests reveal stronger deterrence in regions with weaker regulation/heavier pollution and polluting firms with stronger environmental technology. This study enriches literature from a judicial deterrence perspective and provides implications for substantive corporate green transition.

The low-altitude economy (LAE) refers to economic activities conducted within airspace below 1,000 meters. Drawing on related theories on socio-technical transitions, LAE can be understood as a future regime challenging the dominant urban mobility paradigm. As an emerging field, it has yet to be systematically examined through an empirical study, especially about local response. In this paper, we construct an Integrated Local Support Index (ILSI) based on the number of relevant local policies and the level of public interest measured by the Baidu search index. Private sector readiness is measured by the LAE Development Scale (DS) based on the registered capital of relevant enterprises locally. Focusing on the top 50 cities in China’s LAE sector, we conduct a comprehensive empirical study to explore the relationships between DS, ILSI, and other natural and socio-economic factors between 2012 and 2023. The dynamic interactions of key stakeholders (local government, foreign capital, and talents) are analysed by game theory. The findings suggest that the ILSI, education level, and foreign investment have significant positive impacts. Wind speed is identified as a negative factor for LAE development. The game theory analysis further reveals that the three positive factors tend to foster efficient and stable growth when working synergistically. This implies that enhancing local government support could trigger chain reactions that attract more investment and talents, thereby accelerating LAE development. Projecting to the future, local LAE DS in 2026 is predicted via a panel time-series model with random effects. This study provides both empirical evidence and governance strategies for decision-makers navigating the socio-technical transition of the LAE.

Why do fertility subsidies consistently fail in China? Why do consumptionand fertility collapse globally despite intact household book wealth? This paper proposes the Family Long Cycle Hypothesis (FLCH), extending thedecision-making unit of the life cycle hypothesis from an individual to an intergenerational family network, and expanding the budget constraint from a singlelifetime resource constraint to a dual constraint of “total resources + liquiditystructure”. The core mechanism is: intergenerational “blood-transfusion” homepurchase locks in network liquidity without changing household net assets, completing a balance sheet morph of “book wealth unharmed, decision-making paralyzed” at the moment of purchase. This liquidity depletion spikes effective riskaversion, forming a multiplier effect with income uncertainty, causing fertility—the irreversible commitment with the longest duration—to enter the corner solution region first. Within this region, the elasticity of fertility decisions to costsubsidies is strictly zero, but they remain highly sensitive to liquidity repairand uncertainty reduction. Consequently, this paper proves the fundamentalmechanism difference between consumption subsidies (cash rewards, childcarefee waivers) and capital transfers (mortgage principal write-down, unconditionalcash transfers), and proposes three effective policy directions: reducing incomeuncertainty, repairing family liquidity, and raising the reference income of thebottom 90% of the population. The model nests the standard life cycle hypothesis as a special case and is distinguishable from the competitive saving hypothesis on six pairs of opposing predictions. The theory also explains theasymmetric “fast-falling, slow-rising” adjustment of housing prices: the drop isdriven by defensive behavior (business cycle scale), while the recovery is constrained by intergenerational liquidity reconstruction (intergenerational scale of10–20 years).

We find that firm-specific social media tone influences leveraged trading. A more positive tone predicts greater next-day net margin purchasing, driven predominantly by sentiment. High margin purchasing following positive social media tone consistently yields inferior performance over both short and long horizons. Short sellers are collectively more sophisticated. They capitalize on fluctuations in social media tone, both positive and negative, through strategies that adjust to different tone windows and holding periods. While experienced, rational short sellers can swiftly profit from temporary negative sentiment, high short selling following persistently high social media tone is highly profitable over longer horizons.