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2025, 40(6): 4-14.
Abstract:
The long-term implementation of the financial budget system for social insurance agency fees in China is difficult to adapt to the inherent requirements of the actuarial system for the accuracy of cost accounting and the stability of funds, which restricts the digital transformation and integrated coordinated development of the national social insurance agency, and does not meet the reform requirements of the actuarial system of social insurance. Based on the construction practice of the financial insurance project, this paper systematically analyzes the realistic predicaments of the financial budget system in the perspective of the sustainability of handling investment, the release of scale effect and international comparison. On this basis, with the actuarial balance theory as the core support, this study demonstrates the advantages of the cost budgeting system by internalizing the handling expenses into the legal cost of the fund and establishing a scientific accounting system; on the other hand, it explains the inevitability of constructing the social insurance actuarial system. The research shows that promoting the transformation of social insurance agency investment system to a cost budgeting system is the fundamental path to break through the bottleneck of social insurance agency investment and ensure its digital transformation. The transformation is not only the concrete embodiment of the implementation of "improving the actuarial system of social insurance" at the Fourth Plenary Session of the 20th CPC Central Committee, but also the main contents of social security system reform in the 15th Five-Year Plan period.
The long-term implementation of the financial budget system for social insurance agency fees in China is difficult to adapt to the inherent requirements of the actuarial system for the accuracy of cost accounting and the stability of funds, which restricts the digital transformation and integrated coordinated development of the national social insurance agency, and does not meet the reform requirements of the actuarial system of social insurance. Based on the construction practice of the financial insurance project, this paper systematically analyzes the realistic predicaments of the financial budget system in the perspective of the sustainability of handling investment, the release of scale effect and international comparison. On this basis, with the actuarial balance theory as the core support, this study demonstrates the advantages of the cost budgeting system by internalizing the handling expenses into the legal cost of the fund and establishing a scientific accounting system; on the other hand, it explains the inevitability of constructing the social insurance actuarial system. The research shows that promoting the transformation of social insurance agency investment system to a cost budgeting system is the fundamental path to break through the bottleneck of social insurance agency investment and ensure its digital transformation. The transformation is not only the concrete embodiment of the implementation of "improving the actuarial system of social insurance" at the Fourth Plenary Session of the 20th CPC Central Committee, but also the main contents of social security system reform in the 15th Five-Year Plan period.
2025, 40(6): 15-30.
Abstract:
The deep integration of the digital economy and the real economy is characterized by significant data-driven features. Public data opening, as an important channel for the supply of data elements, lays a crucial data foundation for enterprises to achieve the integration of digital and real economy technologies. This study constructs a quasi-natural experiment based on the public data opening platforms of various prefecture-level cities in China and uses a multi-period difference-in-differences method to examine the impact of public data opening on the integration of digital and real economy technologies in enterprises. The results show that public data opening can promote the integration of digital and real economy technologies in enterprises, mainly through the mechanisms such as reducing transaction costs, promoting digital transformation, and enhancing innovation efficiency. Heterogeneity analysis reveals that public data opening has a more significant promoting effect on the integration of digital and real economy technologies in small-scale enterprises, non-high-tech enterprises, and enterprises located in cities with low levels of digital infrastructure construction and high economic development levels. Based on the research on the quality dimensions of opening, it is found that the overall quality of public data opening, data quality, and platform construction quality play a major role in the integration of digital and real economy technologies in enterprises, while the role of policy guarantee strength has not yet been highlighted, and the intensity of policy supply in digital economy plays a reverse regulatory role in this process. The conclusions of this study provide empirical evidence for improving data empowerment policies and realizing the dividend effect of public data opening in promoting the integration of digital and real economy technologies.
The deep integration of the digital economy and the real economy is characterized by significant data-driven features. Public data opening, as an important channel for the supply of data elements, lays a crucial data foundation for enterprises to achieve the integration of digital and real economy technologies. This study constructs a quasi-natural experiment based on the public data opening platforms of various prefecture-level cities in China and uses a multi-period difference-in-differences method to examine the impact of public data opening on the integration of digital and real economy technologies in enterprises. The results show that public data opening can promote the integration of digital and real economy technologies in enterprises, mainly through the mechanisms such as reducing transaction costs, promoting digital transformation, and enhancing innovation efficiency. Heterogeneity analysis reveals that public data opening has a more significant promoting effect on the integration of digital and real economy technologies in small-scale enterprises, non-high-tech enterprises, and enterprises located in cities with low levels of digital infrastructure construction and high economic development levels. Based on the research on the quality dimensions of opening, it is found that the overall quality of public data opening, data quality, and platform construction quality play a major role in the integration of digital and real economy technologies in enterprises, while the role of policy guarantee strength has not yet been highlighted, and the intensity of policy supply in digital economy plays a reverse regulatory role in this process. The conclusions of this study provide empirical evidence for improving data empowerment policies and realizing the dividend effect of public data opening in promoting the integration of digital and real economy technologies.
2025, 40(6): 31-42.
Abstract:
Comprehensively strengthening financial regulation is a crucial measure for implementing high-quality development of the financial sector in serving the real economy. Promoting the sharing of financial regulatory information is of great significance for enhancing the effectiveness of financial supervision. Based on the joint credit pilot policy implemented in 2018 by the former China Banking and Insurance Regulatory Commission as a quasi-natural experiment, this study examines the impact of financial regulatory information sharing on corporate mergers and acquisitions (M&A). The findings show that joint credit significantly increases the probability and frequency of M&A for firms included in the pilot program. Mechanism tests indicate that joint credit promotes corporate M&A decisions primarily through two channels: curbing corporate financialization and strengthening creditor governance. Heterogeneity analysis reveals that the promoting effect of joint credit on corporate M&A decisions is more pronounced when pilot firms have more investment opportunities, belong to high-tech industries, have highly active internal capital markets, or are audited by non-Big Four accounting firms. Tests on economic consequences demonstrate that the implementation of joint credit significantly improves the performance of corporate M&A, indicating that the real economic effects induced by joint credit contribute to resource allocation optimization. This study not only provides empirical evidence for improving the modern financial regulatory system but also offers important policy implications for fully leveraging the power of robust financial regulation to promote high-quality development of the real economy.
Comprehensively strengthening financial regulation is a crucial measure for implementing high-quality development of the financial sector in serving the real economy. Promoting the sharing of financial regulatory information is of great significance for enhancing the effectiveness of financial supervision. Based on the joint credit pilot policy implemented in 2018 by the former China Banking and Insurance Regulatory Commission as a quasi-natural experiment, this study examines the impact of financial regulatory information sharing on corporate mergers and acquisitions (M&A). The findings show that joint credit significantly increases the probability and frequency of M&A for firms included in the pilot program. Mechanism tests indicate that joint credit promotes corporate M&A decisions primarily through two channels: curbing corporate financialization and strengthening creditor governance. Heterogeneity analysis reveals that the promoting effect of joint credit on corporate M&A decisions is more pronounced when pilot firms have more investment opportunities, belong to high-tech industries, have highly active internal capital markets, or are audited by non-Big Four accounting firms. Tests on economic consequences demonstrate that the implementation of joint credit significantly improves the performance of corporate M&A, indicating that the real economic effects induced by joint credit contribute to resource allocation optimization. This study not only provides empirical evidence for improving the modern financial regulatory system but also offers important policy implications for fully leveraging the power of robust financial regulation to promote high-quality development of the real economy.
2025, 40(6): 43-55.
Abstract:
Driven by climate change, geoeconomic competition and the "Blue Engine" strategy, the ocean has become a new frontier in the global resource game, and the marine economy is emerging as a new engine for economic growth in coastal countries and regions. Based on the panel data from 53 coastal prefecture-level cities in China from 2004 to 2022, this study constructs a dual machine learning model to investigate the impact and mechanism of new quality productivity on marine economic growth. The results show that the level of new quality productivity in China's coastal areas is on the rise, and that new quality productivity positively empowers marine economic growth by promoting the innovative allocation of production factors. Heterogeneity analysis indicates that new quality productivity has a more significant impact on marine economic growth in the southern marine economic zone and regions with low talent endowments. Therefore, China should accelerate the development of new quality productivity, innovatively allocate production factors to traditional, emerging, and future industries in the ocean, promote the coordinated development of new quality productivity in the northern, eastern, and southern marine economic zones. These measures aim to comprehensively empower new drivers of marine economic growth with new quality productivity and promote the construction of a maritime power.
Driven by climate change, geoeconomic competition and the "Blue Engine" strategy, the ocean has become a new frontier in the global resource game, and the marine economy is emerging as a new engine for economic growth in coastal countries and regions. Based on the panel data from 53 coastal prefecture-level cities in China from 2004 to 2022, this study constructs a dual machine learning model to investigate the impact and mechanism of new quality productivity on marine economic growth. The results show that the level of new quality productivity in China's coastal areas is on the rise, and that new quality productivity positively empowers marine economic growth by promoting the innovative allocation of production factors. Heterogeneity analysis indicates that new quality productivity has a more significant impact on marine economic growth in the southern marine economic zone and regions with low talent endowments. Therefore, China should accelerate the development of new quality productivity, innovatively allocate production factors to traditional, emerging, and future industries in the ocean, promote the coordinated development of new quality productivity in the northern, eastern, and southern marine economic zones. These measures aim to comprehensively empower new drivers of marine economic growth with new quality productivity and promote the construction of a maritime power.
2025, 40(6): 56-68.
Abstract:
Driven by the "dual carbon" strategic goals and the low-carbon restructuring of global industrial chains, green transformation has become a critical pathway for China's manufacturing industry to gain competitive advantages. Using the carbon emission trading pilot launched in 2013 as a quasi-natural experiment and leveraging data from A-share listed manufacturing companies in Shanghai and Shenzhen Stock Exchange from 2007 to 2022, this study systematically examines the impact mechanism of carbon emission trading policies on the green transformation of manufacturing enterprises from a value chain perspective. The findings reveal that the pilot policy for carbon emission trading significantly drives manufacturing enterprises to achieve green transformation through dual pathways that not only promote enterprises to ascend to upstream green innovation segments in the value chain but also facilitates their expansion into downstream service business segments. Mechanism analysis indicates that increased R&D funding and deepened customer engagement are the core pathways driving green innovation and service extension respectively, while the application of digital technologies and executives' overseas experience play positive moderating roles. Heterogeneity analysis shows the policy effects are more pronounced in equipment manufacturing enterprises, high-tech manufacturing enterprises, and state-owned manufacturing enterprises. This research provides important theoretical support and empirical evidence for optimizing policy design for carbon emission trading, and promoting the green and high-end development of the manufacturing industry.
Driven by the "dual carbon" strategic goals and the low-carbon restructuring of global industrial chains, green transformation has become a critical pathway for China's manufacturing industry to gain competitive advantages. Using the carbon emission trading pilot launched in 2013 as a quasi-natural experiment and leveraging data from A-share listed manufacturing companies in Shanghai and Shenzhen Stock Exchange from 2007 to 2022, this study systematically examines the impact mechanism of carbon emission trading policies on the green transformation of manufacturing enterprises from a value chain perspective. The findings reveal that the pilot policy for carbon emission trading significantly drives manufacturing enterprises to achieve green transformation through dual pathways that not only promote enterprises to ascend to upstream green innovation segments in the value chain but also facilitates their expansion into downstream service business segments. Mechanism analysis indicates that increased R&D funding and deepened customer engagement are the core pathways driving green innovation and service extension respectively, while the application of digital technologies and executives' overseas experience play positive moderating roles. Heterogeneity analysis shows the policy effects are more pronounced in equipment manufacturing enterprises, high-tech manufacturing enterprises, and state-owned manufacturing enterprises. This research provides important theoretical support and empirical evidence for optimizing policy design for carbon emission trading, and promoting the green and high-end development of the manufacturing industry.
2025, 40(6): 69-81.
Abstract:
Against the backdrop of green and low-carbon development, the enabling mechanism of data assets for enterprise green innovation urgently requires in-depth research. Leveraging the data of A-share listed firms from 2008 to 2023, this study explores the impact of data assets on enterprise green innovation and its mechanism. The findings show that data assets significantly promote enterprise green innovation via three pathways: attracting patient equity capital, facilitating strategic resource reorganization, and strengthening internal green governance. Heterogeneity analysis indicates the driving effect of data assets on collaborative green innovation is more significant than on the independent green innovation, while enterprise supply chain collaboration mechanisms and industry-university-research practices both enhance this promotion effect. Analysis of economic consequences reveals data assets drive enterprises' green innovation to reduce carbon intensity and increase green patent citations. The conclusions provide a theoretical perspective for enterprise data-empowered green transformation, and offer insights for governments to foster and expand green innovation entities.
Against the backdrop of green and low-carbon development, the enabling mechanism of data assets for enterprise green innovation urgently requires in-depth research. Leveraging the data of A-share listed firms from 2008 to 2023, this study explores the impact of data assets on enterprise green innovation and its mechanism. The findings show that data assets significantly promote enterprise green innovation via three pathways: attracting patient equity capital, facilitating strategic resource reorganization, and strengthening internal green governance. Heterogeneity analysis indicates the driving effect of data assets on collaborative green innovation is more significant than on the independent green innovation, while enterprise supply chain collaboration mechanisms and industry-university-research practices both enhance this promotion effect. Analysis of economic consequences reveals data assets drive enterprises' green innovation to reduce carbon intensity and increase green patent citations. The conclusions provide a theoretical perspective for enterprise data-empowered green transformation, and offer insights for governments to foster and expand green innovation entities.
2025, 40(6): 82-96.
Abstract:
Against the backdrop of digitalization and organizational transformation driving China's agricultural transition, how to achieve income growth among farmers has become a research concern. Using microdata from the 2020 China Rural Revitalization Survey (CRRS), this study constructs multidimensional indicators measuring farmers' participation depth in contract and digital chains, and employs a Conditional Mixed Process (CMP) model to empirically examine the structural effects of the dual-chain participation on household income. The results show that deeper participation in both contract and digital chains significantly increases farmers' income levels, with the marginal income effect of contract chain participation being stronger. Mechanism analysis reveals that contract chain participation primarily enhances income through greater use of socialized services and improved access to credit, while digital chain participation increases income mainly by improving digital literacy and facilitating credit acquisition. The income effects of the dual-chain participation vary substantially across groups: crop farmers benefit more from the the participation than livestock farmers; contract chain participation has a stronger effect on the small-scale and less-educated farmers, whereas digital chain participation is more advantageous for large-scale and better-educated households. Furthermore, the income gains from the dual-chain participation are more pronounced among higher-income groups, exhibiting a clear Matthew effect that may exacerbate income disparities among farmers. The findings reveal the internal mechanisms through which rural industrial upgrading affects income structures, and provide policy insights for promoting high-quality agricultural and rural development.
Against the backdrop of digitalization and organizational transformation driving China's agricultural transition, how to achieve income growth among farmers has become a research concern. Using microdata from the 2020 China Rural Revitalization Survey (CRRS), this study constructs multidimensional indicators measuring farmers' participation depth in contract and digital chains, and employs a Conditional Mixed Process (CMP) model to empirically examine the structural effects of the dual-chain participation on household income. The results show that deeper participation in both contract and digital chains significantly increases farmers' income levels, with the marginal income effect of contract chain participation being stronger. Mechanism analysis reveals that contract chain participation primarily enhances income through greater use of socialized services and improved access to credit, while digital chain participation increases income mainly by improving digital literacy and facilitating credit acquisition. The income effects of the dual-chain participation vary substantially across groups: crop farmers benefit more from the the participation than livestock farmers; contract chain participation has a stronger effect on the small-scale and less-educated farmers, whereas digital chain participation is more advantageous for large-scale and better-educated households. Furthermore, the income gains from the dual-chain participation are more pronounced among higher-income groups, exhibiting a clear Matthew effect that may exacerbate income disparities among farmers. The findings reveal the internal mechanisms through which rural industrial upgrading affects income structures, and provide policy insights for promoting high-quality agricultural and rural development.
2025, 40(6): 97-109.
Abstract:
Seed industry innovation drives agricultural resource reallocation and value chain reconstruction through biotechnology breakthroughs and system integration, and becomes the core engine for breaking through the boundaries of rural industries and realizing multi-dimensional integration. This paper constructed a multidimensional evaluation index system of seed industry innovation level and rural industry integration level, and conducted empirical tests based on the provincial panel data of China from 2012 to 2022. The study finds that seed industry innovation can significantly promote rural industrial integration, and achieve differentiated driving through the vertical technological penetration of breeding patents, the vertical synergistic innovation in variety markets and the scale-driven industrial chain integration. The mechanism test suggests that seed industry innovation promotes rural industrial integration through the dual mechanism of technological innovation penetration and entrepreneurial resource integration. Heterogeneity analysis shows that the driving efficiency of seed industry innovation is subject to the interaction of geographic location, factor agglomeration and digital infrastructure, and shows significant spatial differentiation in the main grain producing areas, agricultural big data test areas and large-scale operation areas. The threshold effect test confirms that the promotion effect of seed industry innovation on rural industrial integration is featured with nonlinear enhancement after the level of farmers' scientific and technological quality exceeds a single threshold value. The study aims to analyze the complex mechanism of seed industry innovation driving rural industrial integration, and provide theoretical support and practical guidance for the optimization of seed industry innovation resource allocation and the precise formulation of regional industrial policies.
Seed industry innovation drives agricultural resource reallocation and value chain reconstruction through biotechnology breakthroughs and system integration, and becomes the core engine for breaking through the boundaries of rural industries and realizing multi-dimensional integration. This paper constructed a multidimensional evaluation index system of seed industry innovation level and rural industry integration level, and conducted empirical tests based on the provincial panel data of China from 2012 to 2022. The study finds that seed industry innovation can significantly promote rural industrial integration, and achieve differentiated driving through the vertical technological penetration of breeding patents, the vertical synergistic innovation in variety markets and the scale-driven industrial chain integration. The mechanism test suggests that seed industry innovation promotes rural industrial integration through the dual mechanism of technological innovation penetration and entrepreneurial resource integration. Heterogeneity analysis shows that the driving efficiency of seed industry innovation is subject to the interaction of geographic location, factor agglomeration and digital infrastructure, and shows significant spatial differentiation in the main grain producing areas, agricultural big data test areas and large-scale operation areas. The threshold effect test confirms that the promotion effect of seed industry innovation on rural industrial integration is featured with nonlinear enhancement after the level of farmers' scientific and technological quality exceeds a single threshold value. The study aims to analyze the complex mechanism of seed industry innovation driving rural industrial integration, and provide theoretical support and practical guidance for the optimization of seed industry innovation resource allocation and the precise formulation of regional industrial policies.
2025, 40(6): 110-119.
Abstract:
The high-quality supply of training data plays a decisive role in promoting the development of large-scale model technology. However, the current legal regulation for large-scale model training data in China focuses primarily on security control and risk constraints, relatively neglecting the incentive function of the supply side. This has led to a structural dilemma of triple failure in source generation, market regulation, and government intervention. To promote the continuous and stable supply of the high-quality training data, based on the symbiotic logic of "effective market" and "active government", incentive-based legal regulation can be introduced into the legislation on the supply of large-scale model training data. This can transform behavioral constraints into behavioral incentives through incentive-compatible mechanisms. Specifically, the principles of incentive-based legal regulation featured with value balance, hierarchical coordination, and appropriate proportion should be established. The scope of subjects and objects of incentive-based regulation should be broadened to form a diversified and collaborative incentive mechanism, and incentive-based regulatory tools such as rights-granting, benefit-cost, and qualification-honoring types should be improved, strengthening legislative support and application coordination. Simultaneously, under the premise of incentive-based regulation that respects market rules, appropriate mandatory regulation should be supplemented to achieve a balance between market regulation and government intervention.
The high-quality supply of training data plays a decisive role in promoting the development of large-scale model technology. However, the current legal regulation for large-scale model training data in China focuses primarily on security control and risk constraints, relatively neglecting the incentive function of the supply side. This has led to a structural dilemma of triple failure in source generation, market regulation, and government intervention. To promote the continuous and stable supply of the high-quality training data, based on the symbiotic logic of "effective market" and "active government", incentive-based legal regulation can be introduced into the legislation on the supply of large-scale model training data. This can transform behavioral constraints into behavioral incentives through incentive-compatible mechanisms. Specifically, the principles of incentive-based legal regulation featured with value balance, hierarchical coordination, and appropriate proportion should be established. The scope of subjects and objects of incentive-based regulation should be broadened to form a diversified and collaborative incentive mechanism, and incentive-based regulatory tools such as rights-granting, benefit-cost, and qualification-honoring types should be improved, strengthening legislative support and application coordination. Simultaneously, under the premise of incentive-based regulation that respects market rules, appropriate mandatory regulation should be supplemented to achieve a balance between market regulation and government intervention.
2025, 40(6): 120-128.
Abstract:
Algorithmic administration has a great empowering effect in the field of digital government construction, which can drive efficient and precise administrative decision-making, benefit personalized and convenient government services, and promote the integration of administrative supervision throughout the entire process. The application of algorithmic administration presents a multi-level, nested and complex structure. The three nested structures of "conceptual level, organizational level and technical level" are coupled with each other, emphasizing the close connection and interaction between algorithmic technology and social value, organizational structure, and technological innovation, providing a comprehensive perspective and framework for the application of algorithmic administration. As technology empowers, the potential risks and challenges behind algorithmic administration are becoming increasingly prominent. It is necessary to establish a algorithmic ethical framework of value-rationality at the conceptual level, build a collaborative system for public participation at the organizational level, clarify technical standards to determine the operating boundaries of algorithms at the technical level, in order to seek benefits and avoid harm, and integrate the institutional effectiveness of algorithmic administration into the legal track.
Algorithmic administration has a great empowering effect in the field of digital government construction, which can drive efficient and precise administrative decision-making, benefit personalized and convenient government services, and promote the integration of administrative supervision throughout the entire process. The application of algorithmic administration presents a multi-level, nested and complex structure. The three nested structures of "conceptual level, organizational level and technical level" are coupled with each other, emphasizing the close connection and interaction between algorithmic technology and social value, organizational structure, and technological innovation, providing a comprehensive perspective and framework for the application of algorithmic administration. As technology empowers, the potential risks and challenges behind algorithmic administration are becoming increasingly prominent. It is necessary to establish a algorithmic ethical framework of value-rationality at the conceptual level, build a collaborative system for public participation at the organizational level, clarify technical standards to determine the operating boundaries of algorithms at the technical level, in order to seek benefits and avoid harm, and integrate the institutional effectiveness of algorithmic administration into the legal track.
2019, 34(6): 35-49.
摘要：
数字普惠金融发展对产业结构升级具有重要积极意义。在对数字普惠金融发展与产业结构升级之间的关系进行理论分析的基础上, 基于283个地级以上城市2011—2015年的面板数据, 采用面板门槛模型等回归方法, 实证分析数字普惠金融发展及其各维度发展与产业结构升级之间的关系。结果表明: 数字普惠金融发展与产业结构升级之间存在非线性关系; 数字普惠金融发展存在瓶颈, 具有门槛效应; 数字普惠金融覆盖广度对产业结构升级具有长期且显著的促进作用, 数字普惠金融的使用深度和数字化程度与产业结构升级之间存在非线性关系; 不同区域的数字普惠金融发展对产业结构升级的非线性效应具有异质性, 对产业结构升级的正效应从东部到中西部逐级增强。因而政府部门和金融机构应加大建设数字金融基础设施的力度, 尤其要重视增加落后地区的普惠金融服务供给和提升其数字化程度, 同时, 也要防止数字普惠金融的过度发展为产业结构升级带来负的外部效应。
数字普惠金融发展对产业结构升级具有重要积极意义。在对数字普惠金融发展与产业结构升级之间的关系进行理论分析的基础上, 基于283个地级以上城市2011—2015年的面板数据, 采用面板门槛模型等回归方法, 实证分析数字普惠金融发展及其各维度发展与产业结构升级之间的关系。结果表明: 数字普惠金融发展与产业结构升级之间存在非线性关系; 数字普惠金融发展存在瓶颈, 具有门槛效应; 数字普惠金融覆盖广度对产业结构升级具有长期且显著的促进作用, 数字普惠金融的使用深度和数字化程度与产业结构升级之间存在非线性关系; 不同区域的数字普惠金融发展对产业结构升级的非线性效应具有异质性, 对产业结构升级的正效应从东部到中西部逐级增强。因而政府部门和金融机构应加大建设数字金融基础设施的力度, 尤其要重视增加落后地区的普惠金融服务供给和提升其数字化程度, 同时, 也要防止数字普惠金融的过度发展为产业结构升级带来负的外部效应。
2021, 36(5): 27-40.
摘要：
数字经济是经济发展提质增效的新动能和新引擎，对产业结构的转型升级具有重要驱动作用。在理论分析的基础上，从产业转型速度、产业结构高度化以及产业结构合理化三个维度对产业结构的转型升级进行分解，以区域创新创业指数表征城市创新创业水平，采用2011—2018年我国城市面板数据实证考察数字经济发展的产业结构转型升级效应及其作用机制。研究发现：(1)数字经济能显著提升产业转型速度、产业结构高度化和产业结构合理化，且基于互联网发展和数字普惠金融发展的分析结果趋同。(2)数字经济对产业结构转型升级的效应具有边际报酬递增的后发性优势，且东中西部区域异质性特征明显，其中中部地区是未来数字经济发展的重心。(3)从城市规模看，中等城市和大城市是数字经济驱动产业转型升级的重要着力点；从城市等级来看，二三线城市是产业转型的关键所在。(4)中介效应分析显示，创新创业水平是数字经济产业转型升级效应的重要传导路径，数字经济通过激发区域创新创业活力可加快产业转型速度、促进产业结构的高度化和合理化。以上结论对探索中国城市数字经济可持续发展、助推其与产业结构转型升级深度融合具有一定的参考意义。
数字经济是经济发展提质增效的新动能和新引擎，对产业结构的转型升级具有重要驱动作用。在理论分析的基础上，从产业转型速度、产业结构高度化以及产业结构合理化三个维度对产业结构的转型升级进行分解，以区域创新创业指数表征城市创新创业水平，采用2011—2018年我国城市面板数据实证考察数字经济发展的产业结构转型升级效应及其作用机制。研究发现：(1)数字经济能显著提升产业转型速度、产业结构高度化和产业结构合理化，且基于互联网发展和数字普惠金融发展的分析结果趋同。(2)数字经济对产业结构转型升级的效应具有边际报酬递增的后发性优势，且东中西部区域异质性特征明显，其中中部地区是未来数字经济发展的重心。(3)从城市规模看，中等城市和大城市是数字经济驱动产业转型升级的重要着力点；从城市等级来看，二三线城市是产业转型的关键所在。(4)中介效应分析显示，创新创业水平是数字经济产业转型升级效应的重要传导路径，数字经济通过激发区域创新创业活力可加快产业转型速度、促进产业结构的高度化和合理化。以上结论对探索中国城市数字经济可持续发展、助推其与产业结构转型升级深度融合具有一定的参考意义。
2021, 36(2): 16-27.
摘要：
构建多渠道机制下数字经济影响出口贸易的理论模型，利用2008—2017年中国省级面板数据，实证检验数字经济对制造业高质量走出去的空间溢出效应、非线性边际递增效应及影响机制。研究结果表明：数字经济显著促进了中国省级出口技术复杂度的提升，其产生的正向空间溢出效应能助推出口贸易的高质量发展；数字经济的空间溢出效应存在区域异质性，沿海省份较内陆省份享受了更多的数字红利；数字经济对出口技术复杂度的影响具有动态非线性驱动效应，出口贸易水平较高的地区享受的数字经济红利更大；通过人力资本与贸易成本两个渠道，数字经济能间接提升省级出口技术复杂度；数字经济作用于实体经济时普遍存在边际递增的网络效应。因而应加强数字经济基础设施建设，优化创新环境，让数字经济的发展推动我国制造业高质量走出去。
构建多渠道机制下数字经济影响出口贸易的理论模型，利用2008—2017年中国省级面板数据，实证检验数字经济对制造业高质量走出去的空间溢出效应、非线性边际递增效应及影响机制。研究结果表明：数字经济显著促进了中国省级出口技术复杂度的提升，其产生的正向空间溢出效应能助推出口贸易的高质量发展；数字经济的空间溢出效应存在区域异质性，沿海省份较内陆省份享受了更多的数字红利；数字经济对出口技术复杂度的影响具有动态非线性驱动效应，出口贸易水平较高的地区享受的数字经济红利更大；通过人力资本与贸易成本两个渠道，数字经济能间接提升省级出口技术复杂度；数字经济作用于实体经济时普遍存在边际递增的网络效应。因而应加强数字经济基础设施建设，优化创新环境，让数字经济的发展推动我国制造业高质量走出去。
2022, 37(3): 4-20.
摘要：
数字经济是促进新时代经济高质量增长的重要引擎。基于2011—2019年30个省份的面板数据，分别利用熵值法和DEA-Malmquist指数法测算我国省级数字经济发展综合指数与全要素生产率，实证探讨数字经济对经济高质量发展的影响效应。研究发现：数字经济能显著促进经济高质量发展，该结论经过一系列稳健性检验后仍显著成立；机制分析表明，数字经济是通过提升区域创新水平、加快产业结构升级赋能于经济高质量发展；进一步分析表明，数字经济对相邻地区的经济高质量发展存在空间溢出效应，数字经济对经济高质量发展的促进效应因区域、生产率与人力资本的不同而存在异质性。因而应积极推进数字化基础设施建设，协调好各地区数字经济的均衡发展，实施数字化驱动发展战略，推进经济的高质量发展。
数字经济是促进新时代经济高质量增长的重要引擎。基于2011—2019年30个省份的面板数据，分别利用熵值法和DEA-Malmquist指数法测算我国省级数字经济发展综合指数与全要素生产率，实证探讨数字经济对经济高质量发展的影响效应。研究发现：数字经济能显著促进经济高质量发展，该结论经过一系列稳健性检验后仍显著成立；机制分析表明，数字经济是通过提升区域创新水平、加快产业结构升级赋能于经济高质量发展；进一步分析表明，数字经济对相邻地区的经济高质量发展存在空间溢出效应，数字经济对经济高质量发展的促进效应因区域、生产率与人力资本的不同而存在异质性。因而应积极推进数字化基础设施建设，协调好各地区数字经济的均衡发展，实施数字化驱动发展战略，推进经济的高质量发展。
2022, 37(2): 71-87.
摘要：
“双循环”背景下，新型城镇化不仅是经济发展的新动力，也是实现共同富裕的有力支撑。基于扎实推进共同富裕的背景，从富裕水平、区域差距和城乡差距三方面构建共同富裕的指标体系，测算了281个城市的共同富裕水平，并采用SARAR模型分析新型城镇化对共同富裕的影响。研究发现：推进地区经济发展是实现共同富裕的根本途径；新型城镇化和共同富裕存在着空间相关性，且新型城镇化对共同富裕及其各维度产生显著的促进作用；共同富裕不仅受新型城镇化的影响，还受到城市初始经济发展的影响；比较而言，新型城镇化更能够提升贫困地区的共同富裕水平；新型城镇化对共同富裕产生直接作用的同时，还会通过农民收入和公共服务对共同富裕产生间接的促进作用。在推进新型城镇化过程中，可从提高富裕水平、缩小城乡收入差距和区域经济差距角度助推共同富裕。
“双循环”背景下，新型城镇化不仅是经济发展的新动力，也是实现共同富裕的有力支撑。基于扎实推进共同富裕的背景，从富裕水平、区域差距和城乡差距三方面构建共同富裕的指标体系，测算了281个城市的共同富裕水平，并采用SARAR模型分析新型城镇化对共同富裕的影响。研究发现：推进地区经济发展是实现共同富裕的根本途径；新型城镇化和共同富裕存在着空间相关性，且新型城镇化对共同富裕及其各维度产生显著的促进作用；共同富裕不仅受新型城镇化的影响，还受到城市初始经济发展的影响；比较而言，新型城镇化更能够提升贫困地区的共同富裕水平；新型城镇化对共同富裕产生直接作用的同时，还会通过农民收入和公共服务对共同富裕产生间接的促进作用。在推进新型城镇化过程中，可从提高富裕水平、缩小城乡收入差距和区域经济差距角度助推共同富裕。
2019, 34(5): 4-21.
摘要：
以环保经历嵌入为研究视角, 基于2008—2016年中国沪深A股重污染企业的经验证据, 实证检验高管环保经历嵌入对企业绿色转型的影响及其机制。研究发现:环保经历嵌入能有效促进企业绿色转型; 环保经历嵌入管理层和董事会均能显著地提高企业绿色转型水平, 但环保经历嵌入监事会的影响不显著。进一步研究发现, 新《环境保护法》实施后, 环保经历嵌入对企业绿色转型的促进作用更加显著, 并主要表现在民营企业与低融资约束企业中, 其作用路径一般是通过提高企业创新水平和降低企业调整成本来促进企业绿色转型。因此, 为推进企业绿色转型, 聘请和重视环保经历人才有助于降低绿色转型的风险和成本。
以环保经历嵌入为研究视角, 基于2008—2016年中国沪深A股重污染企业的经验证据, 实证检验高管环保经历嵌入对企业绿色转型的影响及其机制。研究发现:环保经历嵌入能有效促进企业绿色转型; 环保经历嵌入管理层和董事会均能显著地提高企业绿色转型水平, 但环保经历嵌入监事会的影响不显著。进一步研究发现, 新《环境保护法》实施后, 环保经历嵌入对企业绿色转型的促进作用更加显著, 并主要表现在民营企业与低融资约束企业中, 其作用路径一般是通过提高企业创新水平和降低企业调整成本来促进企业绿色转型。因此, 为推进企业绿色转型, 聘请和重视环保经历人才有助于降低绿色转型的风险和成本。
2022, 37(1): 58-74.
摘要：
建设数字中国与实现绿水青山都是推动新时代经济高质量发展的重要战略举措。利用2005—2019年中国283个城市的面板数据，在环境库兹涅茨曲线理论的框架下，基于国家级大数据综合试验区这一准自然实验，运用多期DID和PSM-DID方法，评估以数据要素为核心的数字经济发展对城市空气质量的影响。研究结果表明：数字经济发展对城市空气质量的改善作用显著，且减排效应呈厚积薄发的特征；异质性研究表明，数字经济对秦岭—淮河一线以北的城市空气质量具有更强的影响效应，且在较大规模、高互联网发展水平以及低财政支出水平的城市其减排效应更加明显；机制检验表明，数字经济通过推动产业升级、促进技术创新以及优化资源配置改善了城市空气质量；进一步研究表明，数字经济的发展不仅推动了本地空气质量的改善，而且对降低相邻城市的空气污染也具有激励作用。因此，要进一步推动大数据试验区建设，提升该政策战略执行的包容性和灵活度，同时完善信息基础设施建设，以充分发挥数字经济对城市空气质量的改善作用。
建设数字中国与实现绿水青山都是推动新时代经济高质量发展的重要战略举措。利用2005—2019年中国283个城市的面板数据，在环境库兹涅茨曲线理论的框架下，基于国家级大数据综合试验区这一准自然实验，运用多期DID和PSM-DID方法，评估以数据要素为核心的数字经济发展对城市空气质量的影响。研究结果表明：数字经济发展对城市空气质量的改善作用显著，且减排效应呈厚积薄发的特征；异质性研究表明，数字经济对秦岭—淮河一线以北的城市空气质量具有更强的影响效应，且在较大规模、高互联网发展水平以及低财政支出水平的城市其减排效应更加明显；机制检验表明，数字经济通过推动产业升级、促进技术创新以及优化资源配置改善了城市空气质量；进一步研究表明，数字经济的发展不仅推动了本地空气质量的改善，而且对降低相邻城市的空气污染也具有激励作用。因此，要进一步推动大数据试验区建设，提升该政策战略执行的包容性和灵活度，同时完善信息基础设施建设，以充分发挥数字经济对城市空气质量的改善作用。
2020, 35(2): 55-67.
摘要：
以2008—2017年我国A股上市公司为研究样本, 实证检验了资产剥离对企业财务绩效的影响及其作用机制。研究发现, 资产剥离的实施能够显著影响企业的财务绩效, 其对企业财务绩效的作用方向取决于剥离前企业的业绩基础, 即对于经营不佳的企业而言, 资产剥离损害了企业财务绩效, 反之则显著提升了企业财务绩效。机制检验表明, 融资约束在资产剥离与企业财务绩效的负向关系中发挥了中介效应, 投资效率在资产剥离与企业财务绩效的正向关系中发挥了中介效应。
以2008—2017年我国A股上市公司为研究样本, 实证检验了资产剥离对企业财务绩效的影响及其作用机制。研究发现, 资产剥离的实施能够显著影响企业的财务绩效, 其对企业财务绩效的作用方向取决于剥离前企业的业绩基础, 即对于经营不佳的企业而言, 资产剥离损害了企业财务绩效, 反之则显著提升了企业财务绩效。机制检验表明, 融资约束在资产剥离与企业财务绩效的负向关系中发挥了中介效应, 投资效率在资产剥离与企业财务绩效的正向关系中发挥了中介效应。
2021, 36(1): 98-112.
摘要：
员工持股计划作为企业内部的一项集体激励政策，在优化企业产权配置的同时亦对企业融资能力产生重要影响。基于2011—2018年A股上市公司样本，探究员工持股计划对企业融资约束的影响及作用机制，研究发现，员工持股计划通过降低外部融资成本来缓解企业的融资约束状况，这种缓解作用对东部地区的企业以及民营企业更为显著；员工持股计划通过增强员工身份认同、缓解员工层面代理问题等途径来提升企业内部控制质量，内部控制质量在员工持股计划与融资约束作用之间起到部分中介作用；由于员工之间的“监督效应”及员工持股计划的“公告效应”，员工持股计划在提升内部控制质量方面不存在“搭便车”行为，在缓解融资约束方面存在“1/N”效应。本研究结论为新时期推进员工持股深化改革、提升本土企业内部竞争力提供了参考。
员工持股计划作为企业内部的一项集体激励政策，在优化企业产权配置的同时亦对企业融资能力产生重要影响。基于2011—2018年A股上市公司样本，探究员工持股计划对企业融资约束的影响及作用机制，研究发现，员工持股计划通过降低外部融资成本来缓解企业的融资约束状况，这种缓解作用对东部地区的企业以及民营企业更为显著；员工持股计划通过增强员工身份认同、缓解员工层面代理问题等途径来提升企业内部控制质量，内部控制质量在员工持股计划与融资约束作用之间起到部分中介作用；由于员工之间的“监督效应”及员工持股计划的“公告效应”，员工持股计划在提升内部控制质量方面不存在“搭便车”行为，在缓解融资约束方面存在“1/N”效应。本研究结论为新时期推进员工持股深化改革、提升本土企业内部竞争力提供了参考。
2021, 36(2): 69-85.
摘要：
相较于美国式面向全体员工的退休储蓄型计划，中国式员工持股计划面向关键少数员工，员工大多自行出资，持股期更加灵活。基于2011—2017年A股上市公司数据，研究员工持股计划与企业创新产出数量与质量之间的关系；并进一步依据员工持股计划的契约特征将其分为治理型、激励型与绑定型三类，研究不同路径取向下的员工持股计划对企业创新的影响差异。结果表明：相对于治理型计划，激励型计划与绑定型计划均能提升企业的创新产出，且绑定型计划的作用更加显著；影响机制检验发现，激励型计划促进了员工在创新活动中的努力投入，绑定型计划降低了员工流失率并提升了高管的风险承担水平。本研究证实员工持股计划的实施符合利益协同观而非市值管理观，中国式员工持股计划具有创新促进效应。
相较于美国式面向全体员工的退休储蓄型计划，中国式员工持股计划面向关键少数员工，员工大多自行出资，持股期更加灵活。基于2011—2017年A股上市公司数据，研究员工持股计划与企业创新产出数量与质量之间的关系；并进一步依据员工持股计划的契约特征将其分为治理型、激励型与绑定型三类，研究不同路径取向下的员工持股计划对企业创新的影响差异。结果表明：相对于治理型计划，激励型计划与绑定型计划均能提升企业的创新产出，且绑定型计划的作用更加显著；影响机制检验发现，激励型计划促进了员工在创新活动中的努力投入，绑定型计划降低了员工流失率并提升了高管的风险承担水平。本研究证实员工持股计划的实施符合利益协同观而非市值管理观，中国式员工持股计划具有创新促进效应。
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