中国科学院数学与系统科学研究院期刊网
CJE

21 July 2025, Volume 5 Issue 4
    

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  • Theoretical Framework and Research Prospects of Innovametrics of Innovation Inputs
    Yujie ZHANG, Kaihua CHEN, Yanping ZHANG
    China Journal of Econometrics. 2025, 5(4): 941-959. https://doi.org/10.12012/CJoE2025-0124
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    As the scope, actors, forms, approaches, trends, and influencing factors of innovation inputs continue to evolve, the research objects, domains, and methodological perspectives of innovation inputs analysis are continuously expanding and becoming more refined. The optimal allocation, efficient management, and strategic decision-making of innovation inputs necessitate a systematic and scientific measurement framework. This study develops a theoretical framework for the innovametrics of innovation inputs, emphasizing their role throughout the innovation process. The framework aims to provide analytical perspectives and methodological tools for addressing key measurement issues related to the level, structure, and influencing factors of innovation inputs. Based on a review of the evolution of research on innovation input measurement, this study categorizes key measurement issues into three dimensions: development, structure, and dynamics. It further proposes the key issues and analytical approaches associated with each dimension. Additionally, considering advancements in innovation input management and practical demands, this study outlines future research directions in innovametrics. The development of this theoretical framework not only advances the theoretical and methodological foundations for optimizing innovation input allocation, management, and decision-making but also provides a systematic framework to guide academia, policymakers, and industry practitioners in understanding and effectively applying relevant measurement theories and methodologies.
  • A Preliminary Exploration of the Automated Market Maker Mechanism in Cross-Border Transactions of Central Bank Digital Currency
    Xingjian JIANG, Kunyan WU, Ke TANG
    China Journal of Econometrics. 2025, 5(4): 960-975. https://doi.org/10.12012/CJoE2025-0048
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    This paper preliminarily explores the potential application of the automated market maker (AMM) mechanism in China's Central Bank Digital Currency (CBDC) for cross-border transactions. The study focuses on two primary approaches to managing exchange rate volatility risks through AMM: one relies on direct regulation via central bank reserves, while the other achieves reserve-free regulation through market incentives. The research indicates that the reserve-free regulation mechanism, by setting target ranges and providing economic incentives, can effectively guide liquidity concentration and reduce exchange rate volatility risks, while simultaneously decreasing reliance on foreign exchange reserves. However, this mechanism may also exert certain influences on market liquidity distribution and price discovery. Future research could further investigate dynamic market behaviors, policy coordination, and international cooperation to refine the exchange rate regulation mechanisms in CBDC cross-border transactions, manage risks associated with the cross-border use of the digital yuan, and provide theoretical support and practical references for the internationalization of the digital yuan.
  • Measurement and Spatial Characteristics of China's Provincial New Quality Productive Forces Based on Multi-Indicators and Multi-Source Data
    Yinggang ZHOU, Zengguang ZHONG, Qiuping ZHONG, Guobin HONG
    China Journal of Econometrics. 2025, 5(4): 976-992. https://doi.org/10.12012/CJoE2025-0165
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    As an innovation and development of Marxist productive forces theory, new quality productive forces have received widespread attention since its proposal. In accordance with the connotation and characteristics of new quality productive forces, this study constructs an indicator system based on TEI@I methodology. With the comprehensive consideration of industrial development status and government's catalytic role, we collect basic data from four aspects: Industry, workers, infrastructure, and policy basis, and explore relevant policy texts to measure new quality productive forces of 31 provinces in China. The results show that the development level of China's new quality productive forces is at the early stage, and has a certain space aggregation and uneven development between the east and the west. The construction of new infrastructure and the cultivation of new workers will be the key points to the development of new quality productive forces in the future.
  • China's Industrial Structure Adjustments Under COVID-19Pandemic
    Jiefei ZHENG, Zhiqiang YE, Yanjie WANG, Shunming ZHANG
    China Journal of Econometrics. 2025, 5(4): 993-1021. https://doi.org/10.12012/CJoE2025-0129
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    By characterizing COVID-19 as exogenous shocks to labor supply and tertiary sector production, we use CGE method to build a general equilibrium model to examine the effects on China's industrial structural adjustments. Using China's economic data from 2017 to 2023, we conduct numerical simulations through adjusting initial labor endowments and production scale parameters of the tertiary industry. Compared to no-pandemic scenarios, labor shifts toward the tertiary industry and capital flows into the secondary industry. The primary, secondary and tertiary industries experience the largest, smallest, and moderate reductions in output, respectively, leading to an increasing share of the secondary industry and a decreasing share of the tertiary industry. Moreover, supply side shocks transmit to the demand side, resulting in a decline in consumption and fluctuations in foreign trade, and eventually a continuous decline in national income relative to the no-pandemic benchmark. From 2020 to 2022, the epidemic caused annual social welfare losses of 7.83%, 7.24% and 7.01%, respectively. Our findings confirm that the international trade fluctuations do not alter China's industrial adjustment trajectory. The limited overall impact of international trade on China's economy suggests that domestic cycle remains the primary driver of growth. These insights offer policy recommendations for navigating complex and multiple exogenous shocks and optimizing China's industrial structure in the post-pandemic era under the dual cycle development strategy.
  • How Does the Opening of High-Speed Rail Affect the Wage Disparity for Enterprises?
    Shujin ZHU, Bin PENG, Dan LI
    China Journal of Econometrics. 2025, 5(4): 1022-1052. https://doi.org/10.12012/CJoE2025-0050
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    China's mass construction of new road infrastructure, represented by high-speed railways, provides an excellent narrative for the relationship between transport infrastructure and income inequality. Based on the data of Chinese industrial enterprises and the statistical information about prefecture cities from 2000 to 2013, this paper explores the impact of new road of urban high-speed railways on the labor pay gap within enterprises from the perspective of labor market change. Our results show that the new road of urban high-speed railways will accelerate the inter-regional flow of labor factors, cause the adjustment of labor market, and reduce the labor pay gap within enterprises by promoting the integration of labor market and changing the labor and employment structure. The heterogeneity analysis shows this pro-equal effect of new road infrastructure varies among industries, cities and enterprises. Further analysis verifies the existence of spatial spillover effect of the impact of urban high-speed trains on the labor market, indicating that the operation of urban high-speed trains will also reduce the labor market segmentation degree of other cities, which is conducive to the formation of a unified national labor market.
  • Model Merging with Multiple Structural Neural Networks for Crude Oil Price Forecasting
    Haiteng ZHANG, Qiushi BU, Xinyu ZHANG
    China Journal of Econometrics. 2025, 5(4): 1053-1071. https://doi.org/10.12012/CJoE2025-0123
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    Crude oil price forecasting is critical for global economic stability and the development of the energy industry. However, existing single neural network methods face significant limitations: Increasing the depth and width of the network provides only marginal performance improvements while exacerbating overfitting risks and reducing generalization capabilities. To address these challenges, this paper proposes a method based on model merging with multiple structural neural networks. By constructing shallow MultiLayer Perceptron variant networks with sparse connections and skip connections, and assigning appropriate weights to the predictions of these neural networks, the proposed method significantly enhances prediction performance. Experimental results demonstrate that, for crude oil price time series forecasting, the method achieves superior accuracy compared to deep neural networks, without relying on complex and deep architectures of neural network. Instead, it leverages the merging of multiple structurally simple small-scale neural networks to deliver robust and precise predictions.
  • Digital Government Construction and Corporate ESG Performance—Evidence from Listed Companies
    Kexin XU, Yahong ZHOU, Jingru PANG, Bolin WANG
    China Journal of Econometrics. 2025, 5(4): 1072-1094. https://doi.org/10.12012/CJoE2025-0025
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    The construction of digital government enhances governance capacity through government information disclosure, digital governance, online services, and external supervision. It empowers enterprises by improving their information access, technological innovation, and cost reduction, thereby promoting ESG performance. This paper examines the impact of digital government on corporate ESG performance using A-share listed companies from 2012 to 2023 and a quasi-natural experiment of "big data management reform" with the DID method. The results show that digital government significantly improves corporate ESG performance. Robustness tests, including controlling for concurrent policies, digital economic levels, and market expectations, confirm the stability of the findings. Heterogeneity analysis reveals that the impact is more pronounced for firms with low digital transformation, high pollution levels, and non-state ownership. Mechanism analysis indicates that digital government affects ESG performance by reducing financing constraints, promoting digital innovation, and lowering transaction and agency costs. This study provides empirical evidence for the positive effects of digital government and offers insights for policy-making.
  • SLSTM-Based Covariance Prediction and Its Application in Hierarchical Risk Parity Asset Allocation
    Jiliang SHENG, Lanxi CHEN, Yan ZENG, Qi ZHOU
    China Journal of Econometrics. 2025, 5(4): 1095-1120. https://doi.org/10.12012/CJoE2024-0345
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    In this paper, we integrate the selective state space model (SSSM) with the long short term memory (LSTM) neural network to construct a selective long short term memory (SLSTM) neural network model. We propose a novel dynamic covariance matrix prediction method and apply it to improve the hierarchical risk parity (HRP) asset allocation strategy. Firstly, we propose an SLSTM model with long-term memory function and dynamic adjustment mechanism and design a composite loss function for dynamic covariance matrix prediction. Secondly, we apply the prediction results to the HRP to optimize financial asset allocation strategies. Finally, we select data from mainstream fund products in the financial market and conduct empirical and sensitivity analyses to verify the effectiveness and rationality of the model. The results show that: 1) The SLSTM model significantly improves the effectiveness of dynamically predicted covariance matrix compared to the LSTM model. 2) The composite loss function enhances the ability of model to learn the key attributes of the covariance matrix, thereby effectively improving the accuracy of covariance matrix prediction. 3) Compared with other asset allocation strategies, the HRP asset allocation strategy based on covariance matrix prediction by using the SLSTM model can improve risk-adjusted returns.
  • Spatio-temporal Modeling Method Driven by Policy Variables and its Application in APEC Effect Evaluation
    Jingyi SHI, Cheng QIAN, Xiaoyi HAN, Yingying MA
    China Journal of Econometrics. 2025, 5(4): 1121-1147. https://doi.org/10.12012/CJoE2024-0428
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    Air quality across different regions in China varies due to factors such as population density, geographical location, and climate. To address air pollution, the Chinese government has implemented a series of stringent energy-saving and emission-reduction measures to mitigate environmental damage. To gain a deeper understanding of the impacts of these policies on air quality, this paper proposes a policy evaluation framework based on a class of spatio-temporal model incorporating exogenous variables. By integrating the generalized Yule-Walker estimation method, it innovatively addresses the challenges of estimating exogenous variables within the model. Through theoretical derivations, simulation experiments, and empirical analysis, the reliability and applicability of the proposed model are validated. Notably, in evaluating air quality management policies during the 2014 APEC summit, this study provides more detailed quantitative results, revealing the heterogeneous impacts of policy implementation across different times and regions.
  • The Research on the Impact of Corporate Digital Transformation on Management Self-Interest Behavior
    Wei MA, Xin HUANG
    China Journal of Econometrics. 2025, 5(4): 1148-1171. https://doi.org/10.12012/CJoE2024-0271
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    At the micro level of the impact of digital transformation, there is a lack of research on the impact of digital transformation on management self-interest behavior. This paper constructs a fixed-effects model and analyzes the effect and transmission path of digital transformation on management self-interest based on the data of A-share listed companies. The study shows that the digital transformation of enterprises restrains the self-interested behavior of management by reducing information asymmetry, improving the efficiency of corporate governance, and reducing the flexibility of corporate finance and that the digital transformation of enterprises has heterogeneous effects on the self-interested behavior of management in different regions, levels of competition, and industries. The policy recommendations are to increase the efforts of digital transformation, reduce information asymmetry, improve the efficiency of corporate governance, reduce corporate financial flexibility, and differentially regulate the self-interested behavior of management. This paper responds positively to the spirit of promoting the deep integration of the real economy and the digital economy and takes the self-interested behavior of the management as a breakthrough to provide empirical explanations and decision-making references for the digital transformation of enterprises to promote corporate governance and improve operational efficiency.
  • Research on the Positive U-Shaped Impact of China's Digital Economy Development on Urban-Rural Income Gap and Countermeasures: Based on the Value Added of Provincial Digital Economy
    Yang CHEN, Ning CHANG
    China Journal of Econometrics. 2025, 5(4): 1172-1198. https://doi.org/10.12012/CJoE2024-0458
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    Accurate measurement is a prerequisite for understanding the digital economy and conducting follow-up research. This article follows the practices of BEA and OECD and calculates the added value of China's provincial digital economy. Based on the calculation, we examine how development of the digital economy affects income gap between urban and rural areas. The results show that China's digital economy is developing rapidly with huge gaps between provinces, and the digital infrastructure is the foundation of digital economy development. The development of the digital economy has a U-shape effect on the income gap between urban and rural areas. Further mechanistic analysis showed that the development of the digital economy promotes the transfer of rural labor and delay the U-shape turning point. It also promotes the development of agricultural modernization, increases the income of farmers and narrows the income gap between urban and rural areas. Moreover, it can narrow the urban-rural income gap in adjacent areas through spatial spillover effects. This paper provides policy recommendations for promoting inclusive development of the digital economy.
  • The Impact of Climate Transition Risk on High-Carbon Industries and Industry Spillover
    Jiachao PENG, Haonan LI, Jianzhong XIAO
    China Journal of Econometrics. 2025, 5(4): 1199-1230. https://doi.org/10.12012/CJoE2024-0262
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    How to measure the climate transition risk faced by the high-carbon industry, as well as how to effectively identify and mitigate the systemic risk spillover and contagious effects of the high-carbon industry, is an important issue facing policymakers and the academic community. This paper constructs a high-dimensional time-varying vector autoregression index model is used to measure the spillover effects within and between high-carbon industries. The research finds that the high-carbon industry faces the highest climate transition risk, while the financial industry has the lowest. The greater the climate transition risk, the higher the systemic risk faced by listed companies, and the stranded assets of the high-carbon industry are an important transmission path. Under different policy backgrounds, the risk spillover effects of the high-carbon industry to related industries show differentiated inclinations, and the main risk spillover targets of the high-carbon industry are all associated with their own production or financial networks. The banking industry always performs as a risk absorption role at the center of the risk network and is highly associated with the high-carbon industry. This paper provides a basis for governments and regulatory authorities to understand the impact of transition risk on the high-carbon industry and the industry correlation, and provides certain reference value for resolving the cross-industry transmission of systemic risks in the high-carbon industry.
ISSN 2097-2326 (Online)
ISSN 2096-9732 (Print)
CN 10-1738/F
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