In recent years, despite China’s sustained expansion of public investment in education, pronounced regional disparities in educational development persist, revealing the practical constraints of the existing fiscal sharing structure in advancing equity objectives. In particular, the mechanism through which the allocation of fiscal responsibilities between central and local governments influences educational equity performance remains insufficiently examined in a systematic and empirical manner. From the perspective of fiscal structure, this study seeks to identify and explicate the evolutionary trajectory of educational fiscal equity in China, as well as its underlying institutional determinants. To this end, the study constructs a fiscal performance evaluation framework comprising seven core indicators. Objective weights are assigned using the entropy method, and the TOPSIS model is subsequently employed to conduct a comparative ranking analysis of national education fiscal performance over the period from 2013 to 2023. The results indicate that educational fiscal equity has exhibited an overall upward trend during the study period; however, its evolution displays clear stage-specific characteristics. In the initial phase, improvements in equity were primarily driven by fiscal expansion, leading to rapid gains. In the subsequent period, progress became increasingly constrained by structural optimization bottlenecks, with fiscal performance gradually stabilizing at a plateau in more recent years. Further analysis reveals that the persistently heavy fiscal burden borne by local governments, coupled with the relatively limited regulatory and equalization capacity of the central government, constitutes a key structural impediment to the sustained improvement of educational equity. By elucidating the internal mechanism through which the allocation of fiscal responsibilities shapes educational equity performance, this study provides both theoretical grounding and quantitative support for deepening fiscal system reform and optimizing policies related to the allocation of educational resources.

This paper investigates the outstanding economic and scientific-technological achievements of the Soviet Union during the 1945–1953 period and analyzes how these successes influenced New China’s decision to adopt the Soviet development model. Drawing upon a review of the key Chinese studies and the influential Western works, this study synthesizes diverse research methods,including historical institutional analysis, archival research, and econometric modeling, to examine the driving forces behind Soviet economic development, its quantitative achievements, and its evolving international status relative to the United States. Moreover, the paper reviews the development of Sino-Soviet relations during both the Kuomintang era and the early years of the People’s Republic of China, and it provides a comprehensive factor analysis of why New China chose to introduce the “Soviet model.” The paper also discusses recent quantitative research that employs statistical models to assess the impact of Soviet achievements on China’s economic planning. The findings underscore that the rapid reconstruction and modernization of the Soviet economy not only set new benchmarks in industrial output and scientific progress but also provided a persuasive example that shaped China’s early development strategy.

This paper asks whether a personally experienced bubble crash leaves a lasting imprint on investment style. We study this in China’s stock market, where two technology-growth booms —the 2014–2015 Internet boom and the 2025–2026 AI hardware boom—share a similar narrative but are separated by a decade of generational turnover. Following managers across the mutual funds they run from 2013Q1 to 2026Q1, we compare those who lived through the 2015 crash with otherwise similar managers who entered afterwards. We find that the caution of veteran managers reflects a scar rather than a symptom of ageing. Conditional on age and career length, managers who lived through the 2015 crash hold more value exposure and chase technology stocks less when prices have been rising, and this reluctance deepens with how much the crash hurt them—crash-window tenure, performance shortfalls, redemption pressure—rather than with age. These demand differences reach asset prices as well: stocks held disproportionately by managers without bubble memories carry significantly higher subsequent left-tail risk, whereas crash-experienced ownership stabilises the stock, particularly when ownership is broad. Heterogeneous institutional beliefs rooted in career experience therefore shape not only how managers invest but also the crash risk of the assets they hold.

This paper examines the intricate relationship between China’s First Five-Year Plan (1953–1957) and the extensive Soviet aid that played a pivotal role in shaping early industrialization and economic policy in New China. Drawing upon both Chinese and Western literature, the study reviews the evolution of planned economy practices and Soviet economic assistance, analyzes the process of plan formulation and the formulation of key industrial targets, and assesses the quantitative and qualitative impact of Soviet aid on the successful implementation of the plan. By employing a multi-perspective literature review, archival research, and statistical data analysis, the paper identifies that Soviet technology, machinery, and planning expertise contributed significantly, estimates suggest that Soviet aid accounted for 30-40% of the capital inputs in key sectors and that this collaboration was instrumental in achieving heavy industry targets before the advent of reform and opening-up policies. Furthermore, the paper explores the subsequent divergence in the economic models of China and the Soviet Union, offering lessons on dependency, technology transfer, and the political dimensions of foreign aid. The findings not only contribute to our understanding of the early stages of China’s economic development but also shed light on the broader dynamics of Cold War-era international economic cooperation.

The global financial system is currently navigating a profound transformation driven by digitalization and the rise of decentralized financial innovations. In response, central banks are increasingly exploring or implementing Central Bank Digital Currencies (CBDCs) as a sovereign digital evolution of fiat money. This study investigates the dual nature of CBDCs, evaluating whether they represent a strategic opportunity to modernize the economy or a systemic threat to existing financial stability. Employing a qualitative methodology, the research analyzes official policy frameworks from the IMF and BIS alongside diverse real-world case studies, including China’s e-CNY, the Bahamas’ Sand Dollar, Nigeria’s eNaira, and the European Central Bank’s Digital Euro. The findings suggest that while CBDCs offer significant benefits—such as enhanced payment efficiency, reduced transaction costs, and improved financial inclusion—they also introduce critical risks. These include the potential disintermediation of commercial banks, heightened cybersecurity vulnerabilities, and concerns regarding individual data privacy and government surveillance. The study concludes that the successful integration of CBDCs is not merely a technical challenge but a social and strategic one. Adoption is heavily dependent on infrastructure, digital literacy, and public trust. Ultimately, the research highlights that there is no "one-size-fits-all" model; the future of money will be shaped by how effectively individual nations balance technological innovation with the preservation of financial architecture.

This paper studies whether and how policies that promote a currency’s use in trade invoicing can also strengthen its role as an anchor currency in other economies’ exchange rate baskets. We exploit the establishment of RMB swap lines by the People’s Bank of China as a natural setting to examine this mechanism. We first estimate countries’ implicit currency baskets and the weights assigned to the RMB, and then use a staggered difference-in-differences design to assess the effect of initiating swap line agreements on the RMB’s weights in these baskets. Our results indicate that RMB weights increase by approximately 5% about nine months after a swap line is introduced and remain persistently higher thereafter. Finally, we develop a three-country DSGE model to interpret these findings, showing that by promoting RMB invoicing, swap lines reinforce the RMB’s role as an anchor currency for exchange rate stabilization.

This paper develops a delegation-based framework to explain how institutional design shapes pricing incentives under risk. Using China’s 2016 IPO reform—which abolished prefunding requirements and transferred payment obligations from investors to underwriters—as a natural experiment, we show that introducing subscription-payment risk (SPR) renders underwriter’s partial residual claimants with respect to unpaid allocations. Building on Baron’s (1982) delegation model, we argue that the reform amplifies information asymmetry and induces underwriters to adopt more conservative pricing strategies to manage perceived payment risk. Empirically, IPOs exposed to SPR exhibit greater underpricing and lower offer prices, particularly when investor bids reflect stronger valuation pessimism. The effect tends to be less pronounced for reputable underwriters and when foreign institutional investors participate. Overall, the evidence demonstrates how risk redistribution and institutional frictions jointly shape underwriter behavior and pricing efficiency in primary equity markets.

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 study investigates how the interaction of political accountability and local officials’ career incentives shapes the market for Municipal Corporate Bonds (MCBs) in China, taking the 2017 local government debt personal responsibility rule as a quasinatural experiment. We develop a stylized incomplete-information bargaining model to analyze how the rule reshapes the bargaining equilibrium by rendering officials’ observable characteristics credible signals of bailout incentives. Using a dataset of prefecture-level MCBs from 2008 to 2020, we empirically test the model’s predictions and focus on separating officials’ incentive effects from their inherent ability. Our core findings show that post-announcement of the rule, each additional year of a local party secretary’s remaining time to retirement, a proxy for bailout incentives, reduces MCB spreads by approximately 2.5 basis points and increases issuance volume by about 2.0%. These effects are significantly amplified in fiscally stressed cities. Notably, under the 2017 rule, cities led by party secretaries with stronger bailout incentives can expand MCB issuance, which is contrary to the rule’s original intent to rein in local borrowing.

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.