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Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
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2026, 41(1): 4-16.
Abstract:
Speculative practices such as trend-chasing and narrative-driven hype prevail in capital markets and pose substantial risks to the quality of the information environment. How to identify and govern discrepancies between firms' rhetoric and actual practices in promoting artificial intelligence (AI) activities constitutes a critical issue for the high-quality development of the AI industry. Using textual data from listed firms' annual reports and firm-level data on AI innovation and application from 2007 to 2023, this study constructs a novel measure of corporate AI hype. The results show that AI hype significantly exacerbates analyst forecast bias while failing to generate corresponding substantive innovation or application outcomes. Mechanism analyses indicate that this effect operates by elevating optimism among analysts and investors. Heterogeneity analyses further show that analysts' on-site visits, stronger professional competence, and a well-functioning external information environment help mitigate the misleading effects of AI hype, whereas firms' incentives for market value manipulation intensify these effects. Overall, the findings reveal corporate speculative behavior amid the AI wave and its implications for the capital market information environment, and provide useful insights for promoting the healthy development of AI and improving the standardization and credibility of information disclosure.
Speculative practices such as trend-chasing and narrative-driven hype prevail in capital markets and pose substantial risks to the quality of the information environment. How to identify and govern discrepancies between firms' rhetoric and actual practices in promoting artificial intelligence (AI) activities constitutes a critical issue for the high-quality development of the AI industry. Using textual data from listed firms' annual reports and firm-level data on AI innovation and application from 2007 to 2023, this study constructs a novel measure of corporate AI hype. The results show that AI hype significantly exacerbates analyst forecast bias while failing to generate corresponding substantive innovation or application outcomes. Mechanism analyses indicate that this effect operates by elevating optimism among analysts and investors. Heterogeneity analyses further show that analysts' on-site visits, stronger professional competence, and a well-functioning external information environment help mitigate the misleading effects of AI hype, whereas firms' incentives for market value manipulation intensify these effects. Overall, the findings reveal corporate speculative behavior amid the AI wave and its implications for the capital market information environment, and provide useful insights for promoting the healthy development of AI and improving the standardization and credibility of information disclosure.
2026, 41(1): 17-32.
Abstract:
In the context of the in-depth development of China's aging population, artificial intelligence has become an important driving force to address the challenges of aging and boost the development of the elderly care industry. Based on panel data from 30 provinces in China from 2014 to 2023, this study measures the development level of the elderly care industry across various provinces and empirically examines the impact of AI on this development level. The results indicate that the impact of AI on the development level of the elderly care industry is inverted U-shaped. Yet, the current AI development level in most provinces of China lies on the left side of the inflection point, with a prominent technological dividend effect. AI exerts its influence on the development of elderly care industry through the effect of industrial structure servitization and the effect of human capital structure optimization. Both the level of marketization and the degree of opening-up strengthen the inverted U-shaped relationship between AI and the development level of the elderly care industry. Regionally, the impact of AI on the development level of elderly care industry presents an inverted U-shape in the eastern and central regions, while it exerts a positive promoting effect in the western region. In terms of aging intensity, an inverted U-shaped relationship is observed in low-aging areas, whereas a positive promotional effect is manifested in high-aging areas. Further exploration reveals that the impact of AI on the elderly care industry demonstrates differentiated characteristics across different application scenarios. Therefore, while promoting the "incremental empowerment" of AI applications, it is also important to pay attention to improving its adaptability to the development of the elderly care industry, in order to fully unleash the dividends of artificial intelligence technology and drive high-quality development of the elderly care industry.
In the context of the in-depth development of China's aging population, artificial intelligence has become an important driving force to address the challenges of aging and boost the development of the elderly care industry. Based on panel data from 30 provinces in China from 2014 to 2023, this study measures the development level of the elderly care industry across various provinces and empirically examines the impact of AI on this development level. The results indicate that the impact of AI on the development level of the elderly care industry is inverted U-shaped. Yet, the current AI development level in most provinces of China lies on the left side of the inflection point, with a prominent technological dividend effect. AI exerts its influence on the development of elderly care industry through the effect of industrial structure servitization and the effect of human capital structure optimization. Both the level of marketization and the degree of opening-up strengthen the inverted U-shaped relationship between AI and the development level of the elderly care industry. Regionally, the impact of AI on the development level of elderly care industry presents an inverted U-shape in the eastern and central regions, while it exerts a positive promoting effect in the western region. In terms of aging intensity, an inverted U-shaped relationship is observed in low-aging areas, whereas a positive promotional effect is manifested in high-aging areas. Further exploration reveals that the impact of AI on the elderly care industry demonstrates differentiated characteristics across different application scenarios. Therefore, while promoting the "incremental empowerment" of AI applications, it is also important to pay attention to improving its adaptability to the development of the elderly care industry, in order to fully unleash the dividends of artificial intelligence technology and drive high-quality development of the elderly care industry.
2026, 41(1): 33-49.
Abstract:
As a key institutional innovation platform in the reform of the registration-based IPO system, the STAR Market (Science and Technology Innovation Board) is aimed to address the issue of "innovation stagnation" under the traditional IPO framework through the design focused on "hard technology" positioning and enhanced information disclosure. Based on micro-level data of Chinese firms listed on the STAR Market from 2017 to 2022, this paper employs a difference-in-differences model to evaluate the impact of STAR Market listing on firms' high-quality innovation. The findings show that firms do not experience an expected leap in innovation quality immediately after listing, while they reduce high-risk, long-term exploratory R & D and shift toward more easily achievable strategic innovation. Mechanism analysis indicates that the STAR Market's institutional arrangements influence firms' innovation decisions mainly through two channels: post-listing market valuation pressures compelling firms to reallocate R & D resources, and stricter information disclosure requirements altering management's risk-taking willingness. Heterogeneity tests reveal that increased information transparency strengthens knowledge spillovers within industries, which benefits technology-following firms in improving innovation performance, however, for technology-leading firms at the frontier, higher disclosure costs and risks of core technology leakage suppress their high-quality innovation. Dynamic analysis uncovers that these negative effects are concentrated mainly in the early post-listing period and ease as firms gradually adjust their strategies. This study enriches empirical evidence at the micro-level regarding the relationship between information disclosure systems and corporate innovation behavior under the registration-based reform, and provides targeted policy implications for more effectively incentivizing high-quality technological innovation while promoting capital market transparency.
As a key institutional innovation platform in the reform of the registration-based IPO system, the STAR Market (Science and Technology Innovation Board) is aimed to address the issue of "innovation stagnation" under the traditional IPO framework through the design focused on "hard technology" positioning and enhanced information disclosure. Based on micro-level data of Chinese firms listed on the STAR Market from 2017 to 2022, this paper employs a difference-in-differences model to evaluate the impact of STAR Market listing on firms' high-quality innovation. The findings show that firms do not experience an expected leap in innovation quality immediately after listing, while they reduce high-risk, long-term exploratory R & D and shift toward more easily achievable strategic innovation. Mechanism analysis indicates that the STAR Market's institutional arrangements influence firms' innovation decisions mainly through two channels: post-listing market valuation pressures compelling firms to reallocate R & D resources, and stricter information disclosure requirements altering management's risk-taking willingness. Heterogeneity tests reveal that increased information transparency strengthens knowledge spillovers within industries, which benefits technology-following firms in improving innovation performance, however, for technology-leading firms at the frontier, higher disclosure costs and risks of core technology leakage suppress their high-quality innovation. Dynamic analysis uncovers that these negative effects are concentrated mainly in the early post-listing period and ease as firms gradually adjust their strategies. This study enriches empirical evidence at the micro-level regarding the relationship between information disclosure systems and corporate innovation behavior under the registration-based reform, and provides targeted policy implications for more effectively incentivizing high-quality technological innovation while promoting capital market transparency.
2026, 41(1): 50-67.
Abstract:
Using financial tools to address the challenges of zombie enterprise governance is a key measure to promote the orderly withdrawal of backward production capacity and prevent and resolve major economic and financial risks. Based on the loan data disclosed in listed companies' announcements, this paper empirically examines the governance effect of banks' ESG performance on zombie enterprises. The findings show that banks' ESG performance can effectively reduce enterprises' zombie risk, when the level of banks' ESG performance increases by one standard deviation, the probability of enterprises becoming zombie enterprises decreases by 1.21%. Mechanism tests reveal that, different from the traditional "credit blood transfusion", banks' ESG performance not only eases enterprises' credit constraints, but also systematically reduces their zombie risk by strengthening the governance of backward production capacity and improving their investment efficiency and production efficiency, thereby helping zombie enterprises escape from distress and achieve rebirth. Heterogeneity tests indicate that the governance effect of banks' ESG performance is more significant for non-state-owned enterprises, non-heavily polluting enterprises, enterprises with high external financing dependence, and the enterprises with high debt financing costs.
Using financial tools to address the challenges of zombie enterprise governance is a key measure to promote the orderly withdrawal of backward production capacity and prevent and resolve major economic and financial risks. Based on the loan data disclosed in listed companies' announcements, this paper empirically examines the governance effect of banks' ESG performance on zombie enterprises. The findings show that banks' ESG performance can effectively reduce enterprises' zombie risk, when the level of banks' ESG performance increases by one standard deviation, the probability of enterprises becoming zombie enterprises decreases by 1.21%. Mechanism tests reveal that, different from the traditional "credit blood transfusion", banks' ESG performance not only eases enterprises' credit constraints, but also systematically reduces their zombie risk by strengthening the governance of backward production capacity and improving their investment efficiency and production efficiency, thereby helping zombie enterprises escape from distress and achieve rebirth. Heterogeneity tests indicate that the governance effect of banks' ESG performance is more significant for non-state-owned enterprises, non-heavily polluting enterprises, enterprises with high external financing dependence, and the enterprises with high debt financing costs.
2026, 41(1): 68-81.
Abstract:
Accelerating the release of entrepreneurial vitality among low-altitude economy enterprises is a crucial approach to developing this sector in a context-specific manner. Drawing on business registration data from 282 Chinese cities from 2011 to 2023, this study leverages a quasi-natural experiment facilitated by government public data platforms. A multi-period difference-in-differences model is constructed to empirically examine the impact and underlying mechanisms of public data openness on entrepreneurial dynamism within the low-altitude economy. The findings reveal that public data openness significantly enhances entrepreneurial dynamism in the low-altitude economy, increasing the average number of new enterprises by 11.1%. This effect operates through strengthening technological integration, optimizing institutional and cultural environments, alleviating financing constraints, and expanding market demand. Heterogeneity analysis indicates that the promotional effect of public data openness is more pronounced in regions with steeper topography and higher internet penetration rates, while it exerts a stronger impact on the entrepreneurial dynamism of the medium-to-large-scale enterprises in the low-altitude economy. These findings enrich empirical evidence on the entrepreneurial effects of public data openness and offer valuable insights for unleashing entrepreneurial vitality in low-altitude economy enterprises and promoting their safe and healthy development.
Accelerating the release of entrepreneurial vitality among low-altitude economy enterprises is a crucial approach to developing this sector in a context-specific manner. Drawing on business registration data from 282 Chinese cities from 2011 to 2023, this study leverages a quasi-natural experiment facilitated by government public data platforms. A multi-period difference-in-differences model is constructed to empirically examine the impact and underlying mechanisms of public data openness on entrepreneurial dynamism within the low-altitude economy. The findings reveal that public data openness significantly enhances entrepreneurial dynamism in the low-altitude economy, increasing the average number of new enterprises by 11.1%. This effect operates through strengthening technological integration, optimizing institutional and cultural environments, alleviating financing constraints, and expanding market demand. Heterogeneity analysis indicates that the promotional effect of public data openness is more pronounced in regions with steeper topography and higher internet penetration rates, while it exerts a stronger impact on the entrepreneurial dynamism of the medium-to-large-scale enterprises in the low-altitude economy. These findings enrich empirical evidence on the entrepreneurial effects of public data openness and offer valuable insights for unleashing entrepreneurial vitality in low-altitude economy enterprises and promoting their safe and healthy development.
2026, 41(1): 82-96.
Abstract:
In the context of the deep integration of global energy transition and the digital economy, it is crucial to leverage digital innovation to address the trilemma of energy security, equity, and sustainability. Based on the panel data from 276 Chinese cities from 2008 to 2023, this study constructs models of dynamic panel and mediation effect, employing the system GMM method to empirically examine the internal mechanisms through which the digital economy influences the energy trilemma. The findings reveal that: the digital economy has a significant and sustained ameliorating effect on the energy trilemma; its impact exhibits a notable"Matthew effect", with more pronounced benefits in cities with a stronger foundation for energy transition; the pathways of influence display stage-specific characteristics—technology innovation dominates in robust cities, presenting that "technology-industry" dual-driven dynamics emerge in advanced cities, while industrial structure upgrading plays the primary role in potential cities; the digital economy operates through a trinity transmission mechanism of "technology-structure-capital", mediated by technological innovation, industrial restructuring, and capital infusion. This research deepens the understanding of how the digital economy enables energy transition, and provides theoretical and empirical support for formulating differentiated policies and promoting the deep integration of the digital economy with energy systems.
In the context of the deep integration of global energy transition and the digital economy, it is crucial to leverage digital innovation to address the trilemma of energy security, equity, and sustainability. Based on the panel data from 276 Chinese cities from 2008 to 2023, this study constructs models of dynamic panel and mediation effect, employing the system GMM method to empirically examine the internal mechanisms through which the digital economy influences the energy trilemma. The findings reveal that: the digital economy has a significant and sustained ameliorating effect on the energy trilemma; its impact exhibits a notable"Matthew effect", with more pronounced benefits in cities with a stronger foundation for energy transition; the pathways of influence display stage-specific characteristics—technology innovation dominates in robust cities, presenting that "technology-industry" dual-driven dynamics emerge in advanced cities, while industrial structure upgrading plays the primary role in potential cities; the digital economy operates through a trinity transmission mechanism of "technology-structure-capital", mediated by technological innovation, industrial restructuring, and capital infusion. This research deepens the understanding of how the digital economy enables energy transition, and provides theoretical and empirical support for formulating differentiated policies and promoting the deep integration of the digital economy with energy systems.
2026, 41(1): 97-113.
Abstract:
Data factor marketization is a crucial link in unlocking the value of data as a factor of production. By facilitating the efficient, low-cost circulation of data, it is of significant importance for firms seeking breakthroughs in key and core technologies. Drawing on transaction cost theory, this study uses a sample of A-share listed firms in China's advanced manufacturing sector from 2012 to 2022 and exploits the establishment of data trading platforms as a quasi-natural experiment to examine the effect of data factor marketization on firms' key core technological breakthroughs. The results show that data factor marketization significantly promotes such technological breakthroughs, and this finding remains robust across a series of robustness checks. Mechanism analyses indicate that easing financing constraints and reducing both institutional transaction costs and market transaction costs constitute the key channels through which data factor marketization fosters breakthroughs in key and core technologies. Heterogeneity analyses further reveal that the positive effect varies significantly across firm characteristics, industry and regional environments, and platform characteristics. This study enriches the literature on how data factor marketization shapes firms' technological breakthroughs, extends the analytical perspectives of transaction cost economics and innovation management, and provides policy-relevant implications for advancing China's innovation-driven development and the building of a strong scientific and technological nation.
Data factor marketization is a crucial link in unlocking the value of data as a factor of production. By facilitating the efficient, low-cost circulation of data, it is of significant importance for firms seeking breakthroughs in key and core technologies. Drawing on transaction cost theory, this study uses a sample of A-share listed firms in China's advanced manufacturing sector from 2012 to 2022 and exploits the establishment of data trading platforms as a quasi-natural experiment to examine the effect of data factor marketization on firms' key core technological breakthroughs. The results show that data factor marketization significantly promotes such technological breakthroughs, and this finding remains robust across a series of robustness checks. Mechanism analyses indicate that easing financing constraints and reducing both institutional transaction costs and market transaction costs constitute the key channels through which data factor marketization fosters breakthroughs in key and core technologies. Heterogeneity analyses further reveal that the positive effect varies significantly across firm characteristics, industry and regional environments, and platform characteristics. This study enriches the literature on how data factor marketization shapes firms' technological breakthroughs, extends the analytical perspectives of transaction cost economics and innovation management, and provides policy-relevant implications for advancing China's innovation-driven development and the building of a strong scientific and technological nation.
2026, 41(1): 114-129.
Abstract:
Effectively controlling the hidden debt risks of local government serves as a critical defense against regional financial risks escalating into systemic financial crises. The ongoing fiscal digital transformation may offer modern solutions for managing hidden debt risks through penetrative supervision and intelligent early warning systems. Therefore, based on deconstructing the theoretical link between these two concepts, this study examines the impact of fiscal digital transformation on the hidden debt risks of local government using the data from China's prefecture-level cities from 2016 to 2023. The study finds that fiscal digital transformation can mitigate hidden debt risks by enhancing debt expenditure efficiency and improving fiscal revenue quality. The governance effect on the risks is more pronounced in regions with smaller economies, favorable institutional environments, and relatively lagging digital innovation and business environments. These findings offer valuable insights for accelerating digital fiscal development, mitigating the hidden debt risks of local government, and alleviating fiscal revenue-expenditure pressures.
Effectively controlling the hidden debt risks of local government serves as a critical defense against regional financial risks escalating into systemic financial crises. The ongoing fiscal digital transformation may offer modern solutions for managing hidden debt risks through penetrative supervision and intelligent early warning systems. Therefore, based on deconstructing the theoretical link between these two concepts, this study examines the impact of fiscal digital transformation on the hidden debt risks of local government using the data from China's prefecture-level cities from 2016 to 2023. The study finds that fiscal digital transformation can mitigate hidden debt risks by enhancing debt expenditure efficiency and improving fiscal revenue quality. The governance effect on the risks is more pronounced in regions with smaller economies, favorable institutional environments, and relatively lagging digital innovation and business environments. These findings offer valuable insights for accelerating digital fiscal development, mitigating the hidden debt risks of local government, and alleviating fiscal revenue-expenditure pressures.
2026, 41(1): 130-144.
Abstract:
The deep integration of information technology and government services has reshaped governance models and become a key driver of economic transformation and development. Using the policy of "National Pilot Cities for Information Benefiting the People" as a quasi-natural experiment, this study employs a difference-in-differences (DID) framework to examine the effect of government service informatization on firms' labor income share. The results show that government service informatization significantly increases firms' labor income share. This effect is stronger for firms with a lower share of fixed assets, higher leverage, those in the secondary sector, firms operating in regions with greater market segmentation, firms in administratively monopolized industries, and firms located in regions with more advanced digital infrastructure. Mechanism tests indicate that government service informatization raises the labor income share by easing financing constraints and increasing labor hiring. Further analysis suggests that government service informatization reduces intra-firm income inequality and curbs excessive pay disparities. These findings provide theoretical support and policy implications for promoting governance transformation, improving the income distribution pattern, and advancing common prosperity in a solid and sustained manner.
The deep integration of information technology and government services has reshaped governance models and become a key driver of economic transformation and development. Using the policy of "National Pilot Cities for Information Benefiting the People" as a quasi-natural experiment, this study employs a difference-in-differences (DID) framework to examine the effect of government service informatization on firms' labor income share. The results show that government service informatization significantly increases firms' labor income share. This effect is stronger for firms with a lower share of fixed assets, higher leverage, those in the secondary sector, firms operating in regions with greater market segmentation, firms in administratively monopolized industries, and firms located in regions with more advanced digital infrastructure. Mechanism tests indicate that government service informatization raises the labor income share by easing financing constraints and increasing labor hiring. Further analysis suggests that government service informatization reduces intra-firm income inequality and curbs excessive pay disparities. These findings provide theoretical support and policy implications for promoting governance transformation, improving the income distribution pattern, and advancing common prosperity in a solid and sustained manner.
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。
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。
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。
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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