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  • The Impact of the First Secretary System on Rural Income Growth: Evidences from the National Rural Fxied Point Observation System
    YU Aizhi, KOU Mingzhu, CHONG Cong
    2025, 0(11): 5-20.
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    The First Secretary System represents a crucial institutional innovation in China's rural governance.Using panel data from National Rural Fixed Point Observation System, we provide a systematic evaluation of the system's impact on rural household income.Our empirical analysis reveals that this institutional arrangement enhances rural household income through two channels: improving agricultural operations and boosting local non-agricultural activities.Heterogeneity analysis shows that policy effects vary significantly across household and village characteristics.Further analysis confirms that the first secretary system effectively implements stratified assistance for low-income populations as required by targeted.These findings contribute to understanding the economic effects of grassroots governance institutions in rural development and provide implications for optimizing poverty alleviation mechanisms.
  • Research on the Relationship between Urban Planning and Government Expenditure from the Perspective of Fiscal Sustainability
    LI Shanshan, ZHANG Qingci, LI Guijun
    2025, 0(11): 21-35.
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    The government plays a leading role in balancing urban planning needs with fiscal sustainability.Urban planning and government expenditure are closely interconnected in national governance, economic development, and policy-making, but they often lack coordination in practice. Against the backdrop of high-quality urban development and increasing fiscal pressure, this study takes urban functions as an anchor to link urban planning with government expenditure, and systematically examines their behavioral characteristics and alignment.The findings are as follows: First, the focus of urban planning and government expenditure should adjust in parallel, emphasizing differentiated and high-quality development.Second, the weak alignment between long-term urban planning and annual fiscal budgeting calls for a dynamic coordination mechanism to enhance intertemporal consistency.Third, while there is strategic synergy between social and ecological functions in urban planning, differences remain in the allocation of corresponding government expenditures, highlighting the need for an incentive-constraint framework guided by the“people-oriented”principle.This study provides some insights for enhancing the quality of major cities, improving the efficiency of urban planning and financial resource allocation, and promoting urban fiscal sustainability.
  • Economic Growth Target Management and Local Budget Deviation: Theoretical Mechanisms and Empirical Evidence
    LIANG Fengbo, FU Minjie, GUAN Zhichao
    2025, 0(11): 36-55.
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    Reducing fiscal budget deviations is a critical manifestation of enhanced budget capacity and state capacity.This study investigates the impact effects and multi-layered mechanisms of local economic growth target management on budget revenue and expenditure deviations, utilizing panel data from 272 prefecture-level cities in China from 2010 to 2022.The results demonstrate that economic growth target management exerts a positive expansionary effect on both revenue and expenditure deviations, with findings robust across multiple sensitivity checks.Heterogeneity analysis reveals that this expansionary effect is significantly attenuated in less-developed regions and areas with higher fiscal transparency. Mechanism analysis further identifies that growth target management indirectly influences revenue deviations through land concession practices and exacerbates expenditure deviations by distorting fiscal prioritization away from essential public services.Consequently, China must urgently optimize its economic growth target framework, accelerate the statutory implementation of tax policies, strengthen budget legalization, foster an enabling state model, reform the existing performance evaluation system, and reconstruct government incentives around high-quality development objectives to establish a multi-target compatible incentive mechanism.
  • Integrative Early Warning Model for Bank Systemic Risk With Finance Public Opinion
    TU Yan, JIN Guanhao
    2025, 0(11): 56-73.
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    Financial public opinion as the crucial channel that reflects banks' risk conditions and amplifies risk contagion effects holds significant importance for the identification, early warning, and governance of systemic financial risks in the banking industry.Utilizing data from East Money Information, this paper constructs an inter-bank social network and sentiment indicator.This indicator, along with macroeconomic, meso-level banking system, and micro-level bank operation indicators, is integrated into the network to propose a systemic financial risk prediction model based on graph neural networks(GNNs), the efficacy and robustness of which are rigorously empirically validated.The empirical findings are threefold: First, incorporating sentiment indicator into the GNN-based model significantly enhances prediction accuracy. Second, compared to traditional machine learning models with XGBoost, the GNN model outperforms.Third, adjusting the window size for constructing the inter-bank social network reveals that the GraphSAGE model achieves the best prediction accuracy among all models when the window size is set to 2.This research provides valuable insights for financial regulators, offering a comprehensive understanding of banking system risks and supporting more precise governance.The findings contribute to the enhancement of regulatory tools and the effective identification methods of potential risks.
  • Data Asset Information Disclosure and Analyst Optimism Bias: “Halo Effect”or“Information Risk”?
    ZHANG Rao, ZHANG Yating
    2025, 0(11): 74-90.
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    With the development of the digital economy, data assets have become important strategic resources for promoting enterprises' high-quality development and driving economic growth.This study employs panel data from Chinese A-share listed companies from 2007 to 2022 to empirically examine the impact of data asset information disclosure on analysts' optimistic bias and the underlying mechanisms.The results show that data asset information disclosure can significantly enhance analysts' optimistic bias. Mechanism test reveals that data asset information disclosure improve analysts' optimism and stimulate the sentiment of individual stock investors, thereby strengthening analyst optimism bias.Heterogeneity analysis shows that the positive impact of data asset information disclosure on analyst optimism bias will be suppressed when the company's information environment is good and the tracking degree of star analysts is high.However, as media attention and online public opinion attention increase, the halo effect of data asset information disclosure will be further strengthened, intensifying analysts' irrational optimistic prediction behavior.In addition, the promoting effect of data asset information disclosure on analysts' optimistic bias is more significant in high-tech industries and mature enterprises.
  • Artificial Intelligence-driven Risk Reshaping: The Impact of Enterprise AI Applications on Stock Crash Risk
    ZHAO Jing, ZHANG Shaohua, XU Yuandeng
    2025, 0(11): 91-106.
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    In the context of accelerating the cultivation of new productive forces, artificial intelligence(AI) technology has become an inevitable choice for enterprises to achieve high-quality development.This paper selects data from Chinese A-share listed companies from 2010 to 2022, this study empirically analyzes the impact of corporate AI development levels on the risk of stock price crashes and further investigates the channels and cyclical differences of this effect using the ARDL-ECM model.The results show that the development of AI technology by enterprises can significantly suppress the risk of stock price crashes.There are structural differences in the impact effects among enterprises with different ownership attributes, geographical regions, and management structures.The effects are more pronounced in non-state-owned enterprises, enterprises in the eastern region, and enterprises where the CEO and chairman positions are not held by the same person.In terms of cyclical characteristics, the development of AI technology by enterprises has an initial increase followed by a decrease in the risk of stock price crashes.The application of AI has promoted the increase of stock liquidity of listed companies and increased the risk of stock price crash in the short term.However, in the long cycle, with the improvement of the quality of information disclosure of listed companies, the degree of information asymmetry is gradually reduced, and the application of AI can suppress the risk of stock price crash.The research conclusions can help investors better understand the laws of the capital market and improve investment efficiency.They also provide a theoretical basis and data support for the scientific decision-making and targeted policy-making of regulatory authorities.
  • Dynamic Analysis and Simulation Research on Evolutionary Game of Decision Behavior Risk of Financial Institutions: From the Perspective of Principal and Agent
    LIANG Lijun, ZHANG Mengwan, DAI Tongxin
    2025, 0(11): 107-123.
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    The operational performance of financial institutions directly reflects the decision-making preferences of their decision-makers.The selection of different decision-making behaviors results from a multi-party game and the balance of conflicting interests within these institutions.This paper seeks to move beyond the traditional assumption of complete rationality in classical game theory by considering organizational decision-makers as boundedly rational players.It applies evolutionary game theory to analyze the decision-making behaviors within financial institutions.Using MATLAB software, numerical simulations and model constructions are employed to simulate the strategy selection and evolutionary trajectory of decision-making processes between two organizational decision-making groups: the governance layer(principal) and the senior management layer(agent). The results indicate that:(1) the decision-making strategies of governance and senior management influence each other and eventually reach a dynamic equilibrium;(2) a more effective decision-making audit mechanism and a well-structured organizational context increase the additional costs associated with executives' improper behavior, thereby reducing the likelihood of such decisions;(3) enhancing the quality of governance decision-making effectively diminishes the additional benefits senior management gains from improper decisions and raises the costs of violations, which correspondingly lowers the probability of improper decision-making.This study aims to provide targeted measures and recommendations to improve supervision and mitigate behavioral risks arising from improper decision-making in financial institutions.
  • How Multimodal Data Shapes Marketing Research: A Review and Research Agenda
    WANG Yi, FAN Qingjunyue, ZENG Aoyu
    2025, 0(11): 124-142.
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    The field of marketing is undergoing a profound shift from traditional unimodal data to information-rich multimodal data.Reviewing and envisioning the process by which multimodal data shapes marketing research holds significant academic and practical value.Based on 407 core articles from the Web of Science and CNKI databases(2005-2025), this study employs a dual approach of bibliometric analysis(using CiteSpace) and content analysis to conduct a systematic review and in-depth deconstruction across research themes, theoretical foundations, and methodological paradigms.The findings reveal the shaping influence of multimodal data on marketing research: the evolutionary trajectory of research themes progresses from“static content presentation”to“dynamic interaction and engagement,”and ultimately to“long-term value conversion”; the theoretical underpinnings are characterized by an interdisciplinary integration of marketing with information science, communication studies, and psychology; the methodological landscape is dominated by AI-driven computation, complemented by qualitative interpretation. Furthermore, this study constructs an integrative theoretical framework that delineates the mechanisms of multimodal information's influence.A future research agenda covering theoretical deepening, methodological innovation, and application expansion is also outlined.The conclusions provide an integrative cognitive framework and forward-looking guidance for the field's theoretical advancement and practical innovation.
  • The Fluctuation of Housing Value and Resident's Subjective Well-being Under the Perspective of Real Estate Policy Uncertainty: An Empirical Study Based on the CHFS
    WU Yidong, QIN Lei, CHEN Jie, GUI Honghong
    2025, 0(11): 143-160.
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    The impact of housing asset value fluctuations on resident's subjective well-being has received more attention in the literature, but there is a lack of research on how real estate policy uncertainty affects the well-being effect of housing value fluctuations.Hence, we conduct an empirical study based on the 2011-2017 China Household Finance Survey(CHFS)and Real Estate Policy Uncertainty (REPU) data.We find that housing wealth appreciation has a significant subjective well-being-enhancing effect, but real estate policy uncertainty has a negative moderating effect, which is still significant after a variety of robustness tests.Heterogeneity analysis found that the negative moderating effect of real estate policy uncertainty on the well-being effect of housing appreciation is relatively greater for groups such as older, lower-educated, lower-middle-income, and non-multiple homeowners.Further research shows that the marginal effects of housing appreciation and depreciation on resident's subjective well-being are asymmetric, housing depreciation has a stronger negative effect on residents, and the negative effect of housing depreciation on residents is more obviously moderated by the weakening effect of real estate policy uncertainty.We provide a theoretical basis for enhancing the continuity and stability of real estate policy and promoting the precise implementation of real estate policy.