期刊：
Energy Economics,2025年144:108307 ISSN：0140-9883
通讯作者：
Han, XY
作者机构：
[Jiang, Dongming] Guangzhou Coll Technol & Business, Coll Accounting, Guangzhou, Peoples R China.;[Jia, Fang] Wuhan Polytech Univ, Sch Management, Wuhan 430023, Peoples R China.;[Han, Xiaoyu] Wuhan Text Univ, Sch Accountancy, Wuhan 430020, Peoples R China.
通讯机构：
[Han, XY ] W;Wuhan Text Univ, Sch Accountancy, Wuhan 430020, Peoples R China.
关键词：
Return and volatility spillovers;Energy;Electricity;Cryptocurrency;QVAR
摘要：
Over the past decade, the cryptocurrency market has experienced significant growth. However, the dynamics of risk spillover between various types of cryptocurrencies and the electricity market, as well as energy markets, under different quantile conditions remain ambiguous. To address this gap, this paper utilizes the Quantile Vector Autoregression (QVAR) model to examine the returns and volatility spillovers among energy (fossil and clean energy), the electricity market, and cryptocurrencies (clean and dirty cryptocurrency) markets across varying quantile conditions. Additionally, this paper investigates the determinants of spillover effects among these markets. The findings reveal that moderate spillover effects exist among these markets under conditional mean and median quantiles, while such effects are intensified in extreme quantile conditions. Moreover, oil, clean cryptocurrency, wind energy, and geothermal energy typically act as recipients of spillover effects, whereas natural gas, dirty cryptocurrency, bioenergy, solar energy, and, fuel cells generally function as transmitters of spillover effects. The electricity market serves as a recipient under mean and median quantile conditions but acts as a transmitter under extreme conditions. Furthermore, EPU, CFGI, TERM, and COVID-19 significantly enhance spillover effects among these three markets. These insights offer valuable implications for investors and policymakers.
Over the past decade, the cryptocurrency market has experienced significant growth. However, the dynamics of risk spillover between various types of cryptocurrencies and the electricity market, as well as energy markets, under different quantile conditions remain ambiguous. To address this gap, this paper utilizes the Quantile Vector Autoregression (QVAR) model to examine the returns and volatility spillovers among energy (fossil and clean energy), the electricity market, and cryptocurrencies (clean and dirty cryptocurrency) markets across varying quantile conditions. Additionally, this paper investigates the determinants of spillover effects among these markets. The findings reveal that moderate spillover effects exist among these markets under conditional mean and median quantiles, while such effects are intensified in extreme quantile conditions. Moreover, oil, clean cryptocurrency, wind energy, and geothermal energy typically act as recipients of spillover effects, whereas natural gas, dirty cryptocurrency, bioenergy, solar energy, and, fuel cells generally function as transmitters of spillover effects. The electricity market serves as a recipient under mean and median quantile conditions but acts as a transmitter under extreme conditions. Furthermore, EPU, CFGI, TERM, and COVID-19 significantly enhance spillover effects among these three markets. These insights offer valuable implications for investors and policymakers.
摘要：
Payment digitalization has reformed consumer preferences and significantly influenced economic forms. Using the 2017 and 2019 China Household Finance Survey data, this study examines the impact of payment digitalization on tourism consumer spending and explores the moderating effect of transportation infrastructure improvement. Findings reveal that payment digitalization can encourage tourism consumption expenditure. Furthermore, improvements in transportation infrastructure can boost the promotion effect of payment digitalization on tourism consumption expenditure.
Payment digitalization has reformed consumer preferences and significantly influenced economic forms. Using the 2017 and 2019 China Household Finance Survey data, this study examines the impact of payment digitalization on tourism consumer spending and explores the moderating effect of transportation infrastructure improvement. Findings reveal that payment digitalization can encourage tourism consumption expenditure. Furthermore, improvements in transportation infrastructure can boost the promotion effect of payment digitalization on tourism consumption expenditure.
摘要：
This study demonstrates that extreme temperatures disproportionately affect women’s employment in China’s manufacturing sector. Using matched data from county-level weather records and industrial enterprise surveys, we find that a one-percentage-point increase in extreme temperature exposure reduces female employment share by 4.75% points. Mechanism analysis reveals that this relationship is primarily driven by firms’ hiring decisions based on both perceived and actual gender differences in weather-related productivity. Our findings contribute to the literature by providing novel evidence on how indoor working conditions in manufacturing can perpetuate gender-based labour market disparities.
摘要：
The digital economy has reshaped the geography of tourism but its effect on regional tourism disparities remains unexplored. Based on provincial panel data in China from 2011 to 2022, this study explores the effect of the digital economy on regional disparities in tourism development. The results show that the digital economy regional disparities have a positive impact on the tourism development regional disparities, maintaining a positive influence throughout the 12th and 13th Five-Year Plans, but the coefficient decreases in different years. When analyzed regionally, narrowing digital economy regional disparities is conducive to narrowing the tourism development regional disparities between the eastern and central regions. This study is informative for balancing the tourism distribution pattern and reducing regional economic inequalities in the digital era.
通讯机构：
[Li, HH ] H;Henan Normal Univ, Sch Polit Sci & Publ Adm, Xinxiang 453007, Peoples R China.
关键词：
digital economy;green and low-carbon transformation of land use;spatial spillover effect;financial agglomeration;intellectual property protection
摘要：
The green and low-carbon transformation of land use (GLTLU) is a pressing global issue that requires urgent attention. The digital economy has emerged as a new driver for the GLTLU. However, current research mainly focuses on the measurement and environmental effects of the digital economy, with less exploration of how the digital economy influences the spatial effects and regulatory mechanisms of GLTLU, particularly regarding the differential impacts and specific mechanisms at the regional level. This study uses panel data from 283 cities in China from 2011 to 2019, employing the spatial Durbin model (SDM) and the panel threshold model to examine the spatial and regulatory mechanisms of the digital economy's impact on GLTLU. The findings reveal that digital economy promotes GLTLU not only within cities but also in surrounding regions. Robustness analyses support this conclusion. Notably, the digital economy's positive impact on GLTLU in surrounding areas is confined to the central region of China. In contrast, the Yangtze River Delta urban agglomeration experiences a significant negative impact on GLTLU in nearby regions due to the digital economy. The study also identifies that the positive spatial spillover effect of the digital economy on GLTLU reaches its peak at a distance of 450 km. Additionally, the digital economy's ability to promote GLTLU is contingent upon financial agglomeration levels exceeding 9.1728. Moreover, the local government's emphasis on the digital economy and intellectual property protection enhances the digital economy's impact on GLTLU. The promotion effect is maximized when these factors surpass the thresholds of 27.8054 and 3.5189, respectively. Overall, this study contributes to the understanding of how the digital economy influences sustainable land development, highlighting the critical role of regional factors and regulatory mechanisms in amplifying the digital economy's positive effects on GLTLU.
作者机构：
[Gan, Chang] Wuhan Polytech Univ, Sch Management, Wuhan, Peoples R China.;[Voda, Mihai] Dimitrie Cantemir Univ, Fac Geog, Targu Mures, Romania.;[Wang, Kai] Hunan Normal Univ, Coll Tourism, Changsha, Peoples R China.
通讯机构：
[Wang, K ] H;Hunan Normal Univ, Coll Tourism, Changsha, Peoples R China.
关键词：
economic growth;inclusive growth;moderating effect;tourism development;urban–rural income gap
摘要：
<jats:title>Abstract</jats:title><jats:p>Social fairness and economic recovery stimulation constitute crucial challenges in countries all around the world, and tourism development has enormous potential for balancing efficiency and fairness. Based on the panel data at city level in Yangtze River Delta Region, China, this study uncovered the role that tourism development plays in economic growth and urban–rural income gap by adopting the dynamic SYS‐GMM model. In addition, the moderating effect model was employed to concentrate on the moderating role of urbanization on the relationship between tourism development and economic growth as well as urban–rural income gap. The main conclusions are as follows. First, tourism development does not only promote economic growth, but it also narrows the urban–rural income gap. Second, when it comes to the dynamic effect generated by tourism development, the economic growth‐promotion effect is stronger than the urban–rural income gap‐inhibiting effect. Third, urbanization can enhance the impact of tourism development on economic growth and the reduction of urban–rural income gap.</jats:p>
摘要：
Intertwined supply network (ISN) is a complex system consisting of multiple interconnected supply chains orchestrated by different focal firms. The inherent interconnectedness of an ISN makes it vulnerable to localized disruptions, which can propagate through intricate supplier-buyer relationships, causing unpredictable disruption ripple effects that exacerbate vulnerabilities. While existing literature provides valuable insights into the vulnerability of supply networks with a single focal firm, less attention has been given to ISN comprising multiple competing focal firms. This study proposes an agent-based model to simulate the diffusion of disruption ripple effects in a realistic ISN. The model is used to assess the relative effects of firms' structural and operational attributes on vulnerability and to compare the effectiveness of three mainstream resilience strategies—resistance, adaptation, and recovery—in mitigating the overall vulnerability of ISN. Furthermore, the interaction of resilience strategies initiated by different focal firms in the ISN is explored. The results suggest that focal firms should prioritize their own structural attributes and those of their neighboring firms to address vulnerabilities effectively. Moreover, focal firms can identify partners with higher reciprocity and engage in cooperation for resilience investment. This study contributes to the understanding of ISN vulnerability and provides practical insights for developing effective resilience strategies in complex supply networks.
Intertwined supply network (ISN) is a complex system consisting of multiple interconnected supply chains orchestrated by different focal firms. The inherent interconnectedness of an ISN makes it vulnerable to localized disruptions, which can propagate through intricate supplier-buyer relationships, causing unpredictable disruption ripple effects that exacerbate vulnerabilities. While existing literature provides valuable insights into the vulnerability of supply networks with a single focal firm, less attention has been given to ISN comprising multiple competing focal firms. This study proposes an agent-based model to simulate the diffusion of disruption ripple effects in a realistic ISN. The model is used to assess the relative effects of firms' structural and operational attributes on vulnerability and to compare the effectiveness of three mainstream resilience strategies—resistance, adaptation, and recovery—in mitigating the overall vulnerability of ISN. Furthermore, the interaction of resilience strategies initiated by different focal firms in the ISN is explored. The results suggest that focal firms should prioritize their own structural attributes and those of their neighboring firms to address vulnerabilities effectively. Moreover, focal firms can identify partners with higher reciprocity and engage in cooperation for resilience investment. This study contributes to the understanding of ISN vulnerability and provides practical insights for developing effective resilience strategies in complex supply networks.
