Digital financial inclusion (DFI) is creating dynamics in trade credit financing and trading environmentally through rapid growth of information and communication technology (ICT). Conversely, the empirical evidence is not available to validate the contribution of ICT and DFI in promoting trade in environmental goods. Hence, this research work is an attempt to unfold the nexuses of trade in environmental goods, DFI, and ICT globally in Asia, America, and Europe, respectively. The findings infer that DFI and ICT are the primary factors boosting trade in environmental goods globally, in Asia, America, and Europe, respectively. Furthermore, environmental pollution, economic development, and education are also uplifting the trading related to environmental goods in most regions. In the light of empirical estimates, it suggests that policymakers should give ICT infrastructure and digital connectivity priority investments to maintain the accessibility and effectiveness of environmental goods trading.
{"title":"Rethinking digital finance and information and communication technology (ICT) capital impacts on environmental goods trade under carbon neutrality targets","authors":"Zheng Yang Kuang, Qi Liang, Feng Yu, Wenxiu Hu, Tolassa Temesgen Hordofa, Nafeesa Mughal","doi":"10.1111/1477-8947.12490","DOIUrl":"https://doi.org/10.1111/1477-8947.12490","url":null,"abstract":"Digital financial inclusion (DFI) is creating dynamics in trade credit financing and trading environmentally through rapid growth of information and communication technology (ICT). Conversely, the empirical evidence is not available to validate the contribution of ICT and DFI in promoting trade in environmental goods. Hence, this research work is an attempt to unfold the nexuses of trade in environmental goods, DFI, and ICT globally in Asia, America, and Europe, respectively. The findings infer that DFI and ICT are the primary factors boosting trade in environmental goods globally, in Asia, America, and Europe, respectively. Furthermore, environmental pollution, economic development, and education are also uplifting the trading related to environmental goods in most regions. In the light of empirical estimates, it suggests that policymakers should give ICT infrastructure and digital connectivity priority investments to maintain the accessibility and effectiveness of environmental goods trading.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"19 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
China's economy has transtioned into the “new normal”, which demands higher standards for energy utilization efficiency. Meanwhile, the spatial distribution of China's energy consumption and economic development exhibits a significant imbalance, complicating efforts to achieve Pareto optimization of regional energy allocation efficiency. Addressing this issue, this study explores the heterogeneity of the factors influencing energy consumption in China from the dual perspectives of economic “new normal” and geographic space, using an exponential decomposition model. The results of the study show that: (1) the inhibitory effect of the energy intensity effect on the growth of regional energy consumption is differentiated, with stronger inhibitory effects in Guangdong, Jiangsu and other provinces, and weaker inhibitory effects in Hainan, Qinghai, and other provinces. Living standard effect on the regional energy consumption growth of the promotion of the effect also has differences, Jiangsu, Shandong and other provinces of the promotion of the effect is stronger, while Hainan, Qinghai, and other provinces of the promotion of the effect is weaker. (2) Population size effect on regional energy consumption growth is not consistent in the direction of the role of Guangdong, Zhejiang, and other provinces have a promotional effect and the role of the effect of the stronger, on the contrary, the provinces of Heilongjiang, Jilin, and Gansu has an inhibitory effect. (3) In the late stage of the economic “new normal”, the effects of energy intensity effect, living standard effect and population size effect on the growth of energy consumption in the four regions show a weakening trend, and this weakening trend is more obvious in the northeast region. This study expands theoretical research on factors affecting energy consumption and offers practical guidance for China's government to coordinate regional energy allocation under the economic “new normal” and geographical considerations.
{"title":"Understanding the influencing factors of energy consumption in China: A dual perspective of geographical space and economic “new normal”","authors":"Jun Nie, Tangyang Jiang, Yang Yu","doi":"10.1111/1477-8947.12483","DOIUrl":"https://doi.org/10.1111/1477-8947.12483","url":null,"abstract":"China's economy has transtioned into the “new normal”, which demands higher standards for energy utilization efficiency. Meanwhile, the spatial distribution of China's energy consumption and economic development exhibits a significant imbalance, complicating efforts to achieve Pareto optimization of regional energy allocation efficiency. Addressing this issue, this study explores the heterogeneity of the factors influencing energy consumption in China from the dual perspectives of economic “new normal” and geographic space, using an exponential decomposition model. The results of the study show that: (1) the inhibitory effect of the energy intensity effect on the growth of regional energy consumption is differentiated, with stronger inhibitory effects in Guangdong, Jiangsu and other provinces, and weaker inhibitory effects in Hainan, Qinghai, and other provinces. Living standard effect on the regional energy consumption growth of the promotion of the effect also has differences, Jiangsu, Shandong and other provinces of the promotion of the effect is stronger, while Hainan, Qinghai, and other provinces of the promotion of the effect is weaker. (2) Population size effect on regional energy consumption growth is not consistent in the direction of the role of Guangdong, Zhejiang, and other provinces have a promotional effect and the role of the effect of the stronger, on the contrary, the provinces of Heilongjiang, Jilin, and Gansu has an inhibitory effect. (3) In the late stage of the economic “new normal”, the effects of energy intensity effect, living standard effect and population size effect on the growth of energy consumption in the four regions show a weakening trend, and this weakening trend is more obvious in the northeast region. This study expands theoretical research on factors affecting energy consumption and offers practical guidance for China's government to coordinate regional energy allocation under the economic “new normal” and geographical considerations.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"41 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study analyzes the effect of energy poverty on environmental quality for a sample of 43 countries in sub‐Saharan Africa. We specify and estimate a linear panel data model for the period 2000–2021, using fixed effects and the Driscoll‐Kraay method. The results show that access to electricity and clean energy for cooking have a positive and significant effect on deforestation and carbon emissions. Taking into account non‐linear analysis, we find that there is an inverted U‐relationship between energy indicators and environmental quality, thus, verifying the hypothesis of the Kuznet environmental curve. Thus, access to electricity and access to clean cooking energy improve environmental quality from a threshold. For the resolution of endogeneity, Lewbel 2SLS, the Kiviet method and S‐GMM were used. In addition, analysis of the sample data using a structural equation model (PLS‐SEM) shows that energy indicators pass through various channels to affect environmental quality. Therefore, based on these results, we recommend increasing investments in electricity infrastructure, especially in clean decentralized energy, in order to reduce deforestation and, therefore, CO2 emissions.
{"title":"Energy poverty in light of the climate emergency in Sub‐Saharan Africa: Impact and transmission channels","authors":"Thierry Messie Pondie, Fon Dorothy Engwali","doi":"10.1111/1477-8947.12489","DOIUrl":"https://doi.org/10.1111/1477-8947.12489","url":null,"abstract":"This study analyzes the effect of energy poverty on environmental quality for a sample of 43 countries in sub‐Saharan Africa. We specify and estimate a linear panel data model for the period 2000–2021, using fixed effects and the Driscoll‐Kraay method. The results show that access to electricity and clean energy for cooking have a positive and significant effect on deforestation and carbon emissions. Taking into account non‐linear analysis, we find that there is an inverted U‐relationship between energy indicators and environmental quality, thus, verifying the hypothesis of the Kuznet environmental curve. Thus, access to electricity and access to clean cooking energy improve environmental quality from a threshold. For the resolution of endogeneity, Lewbel 2SLS, the Kiviet method and S‐GMM were used. In addition, analysis of the sample data using a structural equation model (PLS‐SEM) shows that energy indicators pass through various channels to affect environmental quality. Therefore, based on these results, we recommend increasing investments in electricity infrastructure, especially in clean decentralized energy, in order to reduce deforestation and, therefore, CO<jats:sub>2</jats:sub> emissions.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"19 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141063967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lingli Qing, Peng Li, Yaode Wang, Usman Mehmood, Hind Alofaysan
This study investigates the impact of natural resources (NRs), economic growth (GDP), institutional quality, mining and coal rents, and foreign direct investment (FDI) on the environmental quality in the E‐7 countries (Brazil, China, India, Indonesia, Russia, Turkey, and Mexico) from 1990 to 2021. To do this, such advanced estimation methods are used as the method of moments quantile regression (MMQR), with the artificial neural network utilized for robustness checks. The initial diagnostic test results unveiled the presence of cross‐sectional dependence, slope heterogeneity, and long‐run cointegration. The MMQR analysis results indicate that coal and mineral rents escalate environmental pollution by reducing the load capacity factor (LCF) across all quantiles. The results further indicate that FDI and economic growth negatively affect while institutional quality (INS) significantly promotes the LCF in E‐7 countries. Moreover, INS significantly moderates the relationship between mineral resources and LCF, as well as coal resources and LCF. The robustness test also validates these findings. Based on these results, policy measures aimed at strengthening institutional quality, particularly within the NR sector, are crucial for mitigating the adverse impacts of coal and mineral extraction on LCF and promoting sustainable development in the E‐7 countries.
{"title":"Non‐linear nexus of mineral rents, coal rents, foreign direct investment, and environmental sustainability: Importance of institutional quality in E‐7 nations","authors":"Lingli Qing, Peng Li, Yaode Wang, Usman Mehmood, Hind Alofaysan","doi":"10.1111/1477-8947.12470","DOIUrl":"https://doi.org/10.1111/1477-8947.12470","url":null,"abstract":"This study investigates the impact of natural resources (NRs), economic growth (GDP), institutional quality, mining and coal rents, and foreign direct investment (FDI) on the environmental quality in the E‐7 countries (Brazil, China, India, Indonesia, Russia, Turkey, and Mexico) from 1990 to 2021. To do this, such advanced estimation methods are used as the method of moments quantile regression (MMQR), with the artificial neural network utilized for robustness checks. The initial diagnostic test results unveiled the presence of cross‐sectional dependence, slope heterogeneity, and long‐run cointegration. The MMQR analysis results indicate that coal and mineral rents escalate environmental pollution by reducing the load capacity factor (LCF) across all quantiles. The results further indicate that FDI and economic growth negatively affect while institutional quality (INS) significantly promotes the LCF in E‐7 countries. Moreover, INS significantly moderates the relationship between mineral resources and LCF, as well as coal resources and LCF. The robustness test also validates these findings. Based on these results, policy measures aimed at strengthening institutional quality, particularly within the NR sector, are crucial for mitigating the adverse impacts of coal and mineral extraction on LCF and promoting sustainable development in the E‐7 countries.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"25 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Festus Victor Bekun, Gizem Uzuner, Muhammad Saeed Meo, Ashutosh Yadav
The relationship between energy utilization and the environment is crucial in an era of environmental concerns by global economies and rising energy consumption. Emerging economies such as Mexico, Indonesia, Nigeria, and Turkey (hereafter, MINT) face complex trade‐offs between economic growth and environmental sustainability. Strengthening this study are the UN Sustainable Development Goals prepositions on access to clean and alternative energy, decent economic growth, responsible production and consumption and climate action (UN‐SDGs‐7, 8, 12, and 13). The present study examines the environmental Kuznets curve (EKC) hypothesis for MINT economies within the framework of the load capacity factor (LCF). The article leverages panel econometrics to operationalize the relationship between study variables. Empirical findings show that the present study fails to confirm the presence of EKC. Thus, it implies that the MINT economies are at their first stage of accelerated economic growth which might result in an augmented ecological footprint and exert pressure on natural resources, as indicated by the observed negative outcome. Furthermore, there is a positive and significant relationship between renewable energy consumption (RENENG) and LCF. It implies that a 1% increase in RENENG leads to an increase in LCF of 0.70%. These outcomes indicate that the level of RENENG in MINT economies is not sufficient to mitigate climate change issues. Thus, from a policy perspective, there is a need for change in the MINT nations' energy portfolio mix, such as the need to switch from conventional energy sources (fossil fuels) to renewable energy sources, including solar, wind, photovoltaic and hydropower, which usually have a smaller negative impact on the environment. Furthermore, there is a need for investment in new and green energy technologies in the countries investigated to arrive at a clean and better ecosystem as desired. More insight is outlined in the concluding section.
在全球经济关注环境问题和能源消耗不断增加的时代，能源利用与环境之间的关系至关重要。墨西哥、印度尼西亚、尼日利亚和土耳其等新兴经济体（以下简称 MINT）面临着经济增长与环境可持续性之间的复杂权衡。联合国可持续发展目标中关于获取清洁和替代能源、体面的经济增长、负责任的生产和消费以及气候行动（联合国可持续发展目标 7、8、12 和 13）的前提条件加强了本研究。本研究在负载能力系数（LCF）的框架内，探讨了多边贸易体系经济体的环境库兹涅茨曲线（EKC）假设。文章利用面板计量经济学来操作研究变量之间的关系。实证研究结果表明，本研究未能证实 EKC 的存在。因此，这意味着 MINT 经济体正处于经济加速增长的第一阶段，这可能会导致生态足迹扩大，并对自然资源造成压力，正如观察到的负面结果所显示的那样。此外，可再生能源消费（RENENG）与低碳足迹之间存在显著的正相关关系。这意味着 RENENG 每增加 1%，LCF 就会增加 0.70%。这些结果表明，MINT 经济体的可再生能源消费水平不足以缓解气候变化问题。因此，从政策角度来看，有必要改变 MINT 国家的能源组合结构，例如需要从传统能源（化石燃料）转向可再生能源，包括太阳能、风能、光伏发电和水电，这些能源通常对环境的负面影响较小。此外，被调查国家还需要对新的绿色能源技术进行投资，以实现所期望的清洁和更好的生态系统。结论部分将概述更多见解。
{"title":"Another look at energy consumption and environmental sustainability target through the lens of the load capacity factor: Accessing evidence from MINT economies","authors":"Festus Victor Bekun, Gizem Uzuner, Muhammad Saeed Meo, Ashutosh Yadav","doi":"10.1111/1477-8947.12481","DOIUrl":"https://doi.org/10.1111/1477-8947.12481","url":null,"abstract":"The relationship between energy utilization and the environment is crucial in an era of environmental concerns by global economies and rising energy consumption. Emerging economies such as Mexico, Indonesia, Nigeria, and Turkey (hereafter, MINT) face complex trade‐offs between economic growth and environmental sustainability. Strengthening this study are the UN Sustainable Development Goals prepositions on access to clean and alternative energy, decent economic growth, responsible production and consumption and climate action (UN‐SDGs‐7, 8, 12, and 13). The present study examines the environmental Kuznets curve (EKC) hypothesis for MINT economies within the framework of the load capacity factor (LCF). The article leverages panel econometrics to operationalize the relationship between study variables. Empirical findings show that the present study fails to confirm the presence of EKC. Thus, it implies that the MINT economies are at their first stage of accelerated economic growth which might result in an augmented ecological footprint and exert pressure on natural resources, as indicated by the observed negative outcome. Furthermore, there is a positive and significant relationship between renewable energy consumption (RENENG) and LCF. It implies that a 1% increase in RENENG leads to an increase in LCF of 0.70%. These outcomes indicate that the level of RENENG in MINT economies is not sufficient to mitigate climate change issues. Thus, from a policy perspective, there is a need for change in the MINT nations' energy portfolio mix, such as the need to switch from conventional energy sources (fossil fuels) to renewable energy sources, including solar, wind, photovoltaic and hydropower, which usually have a smaller negative impact on the environment. Furthermore, there is a need for investment in new and green energy technologies in the countries investigated to arrive at a clean and better ecosystem as desired. More insight is outlined in the concluding section.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"32 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Population and industrial structure, as foundational characteristics of economic and social systems, exhibit significant spatial heterogeneity and dynamic evolutionary trends in their impact on sustainable economic and social development. However, existing research often employs subjective spatial categorization of samples and overlooks the dynamic transitions of influencing patterns, potentially leading to biases in empirical results. To address this, the current study, based on the calculation of green total factor productivity (GTFP) for 30 provinces in China from 2000 to 2018, incorporates a finite mixture model. This model examines the objective heterogeneity and dynamic transition patterns of industrial structure's impact on GTFP, both from the perspectives of industrial structure advancement (ISA) and rationalization (ISR), and reveals the mechanisms of heterogeneity and dynamic changes from a population standpoint. The findings indicate that there are three patterns in the impact of industrial structure on GTFP, with nearly half of the provinces undergoing pattern transitions during the observation period. The key factors for these transitions are identified as the improvement in human capital levels and urbanization rates. In provinces like Beijing, Guangdong, and Shanghai, ISA and ISR significantly promote GTFP, with their effects further enhanced by increased urbanization and human capital levels. Conversely, in regions such as Shanxi and Hebei, ISA does not favor GTFP improvement, and while ISR can enhance GTFP, this positive effect diminishes with increasing urbanization and labor force numbers. This research not only enriches the literature on the positive interaction patterns between industrial and population structures but also provides a comprehensive analytical framework for governments to adopt differentiated policy measures for sustainable economic development.
{"title":"Industrial structure optimization and green growth in China based on a population heterogeneity perspective","authors":"Tingting Li, Wei Dou, Jing Han, Wenqing Zhang","doi":"10.1111/1477-8947.12487","DOIUrl":"https://doi.org/10.1111/1477-8947.12487","url":null,"abstract":"Population and industrial structure, as foundational characteristics of economic and social systems, exhibit significant spatial heterogeneity and dynamic evolutionary trends in their impact on sustainable economic and social development. However, existing research often employs subjective spatial categorization of samples and overlooks the dynamic transitions of influencing patterns, potentially leading to biases in empirical results. To address this, the current study, based on the calculation of green total factor productivity (GTFP) for 30 provinces in China from 2000 to 2018, incorporates a finite mixture model. This model examines the objective heterogeneity and dynamic transition patterns of industrial structure's impact on GTFP, both from the perspectives of industrial structure advancement (ISA) and rationalization (ISR), and reveals the mechanisms of heterogeneity and dynamic changes from a population standpoint. The findings indicate that there are three patterns in the impact of industrial structure on GTFP, with nearly half of the provinces undergoing pattern transitions during the observation period. The key factors for these transitions are identified as the improvement in human capital levels and urbanization rates. In provinces like Beijing, Guangdong, and Shanghai, ISA and ISR significantly promote GTFP, with their effects further enhanced by increased urbanization and human capital levels. Conversely, in regions such as Shanxi and Hebei, ISA does not favor GTFP improvement, and while ISR can enhance GTFP, this positive effect diminishes with increasing urbanization and labor force numbers. This research not only enriches the literature on the positive interaction patterns between industrial and population structures but also provides a comprehensive analytical framework for governments to adopt differentiated policy measures for sustainable economic development.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"44 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tangyang Jiang, Juanjuan Xu, Yang Yu, Atif Jahanger, Daniel Balsalobre‐Lorente
Green finance is a market‐driven approach to achieve the “double carbon” goal. However, the existing research predominantly focuses on the connotations and empowerment aspects of green finance. Notable regional disparities exist in China's financial markets and resource endowments, resulting in uneven levels of green finance development among various areas, significantly impeding the overall green transformation of the economy and society. In light of this, our paper explores the spatial patterns and association network of green finance development in China. The research findings indicate that: (1) The development of green finance in China exhibits an “east high, west low” spatial distribution pattern, with significant spatial clustering observed among neighboring provinces. The eastern region displays a “H‐H” clustering, while the western region shows an “L‐L” clustering. (2) The spatial correlation distribution of provincial green finance in China demonstrates an eastward concentration and westward dispersion trend, with strong correlation areas gradually expanding. Notably, Jiangsu, Zhejiang, Shanghai, and the Beijing‐Tianjin‐Hebei urban agglomerations lead nationally in attractiveness. (3) The external radiation capability of provincial green finance is progressively improving, with provinces such as Beijing, Hebei, Hubei, and Sichuan likely to occupy strategic structural positions, possessing greater development advantages. This study not only expands the theoretical scope of existing green finance research but also provides a practical reference for coordinating and achieving the high‐quality development of regional green finance from a practical perspective.
{"title":"The spatial pattern and association network of green finance development: Empirical evidence from China","authors":"Tangyang Jiang, Juanjuan Xu, Yang Yu, Atif Jahanger, Daniel Balsalobre‐Lorente","doi":"10.1111/1477-8947.12474","DOIUrl":"https://doi.org/10.1111/1477-8947.12474","url":null,"abstract":"Green finance is a market‐driven approach to achieve the “double carbon” goal. However, the existing research predominantly focuses on the connotations and empowerment aspects of green finance. Notable regional disparities exist in China's financial markets and resource endowments, resulting in uneven levels of green finance development among various areas, significantly impeding the overall green transformation of the economy and society. In light of this, our paper explores the spatial patterns and association network of green finance development in China. The research findings indicate that: (1) The development of green finance in China exhibits an “east high, west low” spatial distribution pattern, with significant spatial clustering observed among neighboring provinces. The eastern region displays a “H‐H” clustering, while the western region shows an “L‐L” clustering. (2) The spatial correlation distribution of provincial green finance in China demonstrates an eastward concentration and westward dispersion trend, with strong correlation areas gradually expanding. Notably, Jiangsu, Zhejiang, Shanghai, and the Beijing‐Tianjin‐Hebei urban agglomerations lead nationally in attractiveness. (3) The external radiation capability of provincial green finance is progressively improving, with provinces such as Beijing, Hebei, Hubei, and Sichuan likely to occupy strategic structural positions, possessing greater development advantages. This study not only expands the theoretical scope of existing green finance research but also provides a practical reference for coordinating and achieving the high‐quality development of regional green finance from a practical perspective.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"9 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Decarbonizing economies requires an energy transition from conventional energy resources to renewable and clean energy resources. However, this transition largely depends upon the availability of huge investments to manage high start‐up costs and operational infrastructure. In this respect, the financial sector can play a vital role. This study explores the financial sector's role in renewable energy consumption utilizing a comprehensive measure of financial sector development constituting both financial institutions and financial markets. Moreover, the study utilizes an advanced econometric technique “dynamic panel threshold model” on panel data of 165 countries ranging from 1980 to 2019. The empirical analysis reveals the presence of a threshold value of 0.191, 0.196, and 0.008 for the overall financial development index, financial institutions index, and financial market index, respectively. This finding confirms the presence of a U‐shaped curve between financial sector development and renewable energy consumption, validating the existence of the financial Kuznets curve. Thus, initially, financial sector development results in lower renewable energy consumption while after reaching the threshold level it boosts renewable energy consumption. Furthermore, the study also shows the statistically significant role of economic growth, trade openness, and inflation in explaining renewable energy usage. The obtained outcomes suggest a pressing necessity to improve both financial institutions and markets to surpass the threshold levels of financial sector performance within the financial sector, thus supporting a rise in renewable energy consumption.
经济去碳化要求能源从传统能源过渡到可再生清洁能源。然而，这种过渡在很大程度上取决于是否有巨额投资来管理高昂的启动成本和运营基础设施。在这方面，金融部门可以发挥至关重要的作用。本研究利用金融机构和金融市场构成的金融业发展综合衡量标准，探讨了金融业在可再生能源消费中的作用。此外，本研究还利用先进的计量经济学技术 "动态面板阈值模型"，对 1980 年至 2019 年 165 个国家的面板数据进行了分析。实证分析表明，金融发展总指数、金融机构指数和金融市场指数分别存在0.191、0.196和0.008的阈值。这一结果证实了金融业发展与可再生能源消费之间存在 U 型曲线，验证了金融库兹涅茨曲线的存在。因此，金融业发展在初期会降低可再生能源的消耗，而在达到临界水平后，则会促进可再生能源的消耗。此外，研究还表明，经济增长、贸易开放度和通货膨胀在解释可再生能源的使用方面具有显著的统计学作用。研究结果表明，迫切需要改善金融机构和市场，使金融部门的表现超过临界水平，从而支持可再生能源消费的增长。
{"title":"Financial sector development and renewable energy consumption nexus: Evidence from global dynamic panel threshold analysis","authors":"Muhammad Tariq Majeed, Zubia Hussain","doi":"10.1111/1477-8947.12469","DOIUrl":"https://doi.org/10.1111/1477-8947.12469","url":null,"abstract":"Decarbonizing economies requires an energy transition from conventional energy resources to renewable and clean energy resources. However, this transition largely depends upon the availability of huge investments to manage high start‐up costs and operational infrastructure. In this respect, the financial sector can play a vital role. This study explores the financial sector's role in renewable energy consumption utilizing a comprehensive measure of financial sector development constituting both financial institutions and financial markets. Moreover, the study utilizes an advanced econometric technique “dynamic panel threshold model” on panel data of 165 countries ranging from 1980 to 2019. The empirical analysis reveals the presence of a threshold value of 0.191, 0.196, and 0.008 for the overall financial development index, financial institutions index, and financial market index, respectively. This finding confirms the presence of a U‐shaped curve between financial sector development and renewable energy consumption, validating the existence of the financial Kuznets curve. Thus, initially, financial sector development results in lower renewable energy consumption while after reaching the threshold level it boosts renewable energy consumption. Furthermore, the study also shows the statistically significant role of economic growth, trade openness, and inflation in explaining renewable energy usage. The obtained outcomes suggest a pressing necessity to improve both financial institutions and markets to surpass the threshold levels of financial sector performance within the financial sector, thus supporting a rise in renewable energy consumption.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"2011 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James Temitope Dada, Folorunsho Monsur Ajide, Mamdouh Abdulaziz Saleh Al‐Faryan, Mosab I. Tabash
This study investigates whether trade policy instruments—tariffs—strengthen or worsen African environmental sustainability. To drive out the objectives of the study, fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), augmented mean group (AMG), method of moment quantile regression (MMQR) and Dumitrescu–Hurlin panel causality approaches are used to analyse the effect of tariff in addition to other control variables on carbon and ecological footprints as measured of environmental sustainability from 2001 to 2020. The results from the MMQR reveal that tariffs have a significant positive effect on carbon footprints in the 0.15 quantile, while the effect becomes insignificant between 0.25 and 0.5 quantiles. However, at the upper quantiles level (0.75–0.95), the impact of the tariff on carbon footprint is negative and significant, with increasing coefficients. Furthermore, tariffs significantly positively affect lower and middle quantiles' ecological footprints (0.15–0.5). However, the effect turns negative at the upper quantiles (0.9 and 0.95), suggesting that tariff reduces ecological footprint at these levels. In addition, the long‐run estimates (FMOLS, DOLS and AMG) also support the upper quantile estimates of MMQR. A one‐way causality between tariffs, carbon and ecological footprint was found. These findings reveal that tariffs do not create market inefficiency in Africa. This study recommends that tariffs as a trade policy instrument could be used to strengthen Africa's environmental quality. The government can use the tariff revenue to subsidize cleaner production and consumption and move the economy from a traditional energy source to renewable energy.
{"title":"Trade policy and environmental sustainability in Africa: An empirical analysis","authors":"James Temitope Dada, Folorunsho Monsur Ajide, Mamdouh Abdulaziz Saleh Al‐Faryan, Mosab I. Tabash","doi":"10.1111/1477-8947.12488","DOIUrl":"https://doi.org/10.1111/1477-8947.12488","url":null,"abstract":"This study investigates whether trade policy instruments—tariffs—strengthen or worsen African environmental sustainability. To drive out the objectives of the study, fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), augmented mean group (AMG), method of moment quantile regression (MMQR) and Dumitrescu–Hurlin panel causality approaches are used to analyse the effect of tariff in addition to other control variables on carbon and ecological footprints as measured of environmental sustainability from 2001 to 2020. The results from the MMQR reveal that tariffs have a significant positive effect on carbon footprints in the 0.15 quantile, while the effect becomes insignificant between 0.25 and 0.5 quantiles. However, at the upper quantiles level (0.75–0.95), the impact of the tariff on carbon footprint is negative and significant, with increasing coefficients. Furthermore, tariffs significantly positively affect lower and middle quantiles' ecological footprints (0.15–0.5). However, the effect turns negative at the upper quantiles (0.9 and 0.95), suggesting that tariff reduces ecological footprint at these levels. In addition, the long‐run estimates (FMOLS, DOLS and AMG) also support the upper quantile estimates of MMQR. A one‐way causality between tariffs, carbon and ecological footprint was found. These findings reveal that tariffs do not create market inefficiency in Africa. This study recommends that tariffs as a trade policy instrument could be used to strengthen Africa's environmental quality. The government can use the tariff revenue to subsidize cleaner production and consumption and move the economy from a traditional energy source to renewable energy.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"9 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recognizing the paramount importance of health, the United Nations Development Program has outlined sustainable development goals, emphasizing Goal 3, which focuses on ensuring and promoting healthy lives and well‐being for all. Consequently, this study delves into the determinants of healthcare expenditure (HCE), specifically focusing on financial development (FDV), tourism (TOR), technological innovations (TINs), economic growth (EG), and climate change in the United States. The investigation utilizes data spanning from the first quarter of 2000Q1 to the fourth quarter of 2020Q4. To achieve this objective, we employed innovative quantile‐based methodologies, including wavelet quantile regression and quantile‐on‐quantile Granger causality. These approaches facilitated a comprehensive exploration of the dynamic interactions between HCE and its influencing factors across various quantiles and periods. The wavelet quantile regression and quantile‐on‐quantile regression analysis findings consistently indicate a positive impact of CO2, TOR, EG, globalization, FDV, foreign direct investment, and TIN on HCE in the United States. Furthermore, the results obtained from the quantile‐on‐quantile Granger causality demonstrate that CO2 emissions, TOR, EG, globalization, FDV, foreign direct investment, and TIN significantly predict HCE across all quantiles. These insights have informed the formulation and implementation of various policies addressing the complex interplay between healthcare spending and its driving factors.
联合国开发计划署认识到健康的极端重要性，概述了可持续发展目标，强调目标 3 的重点是确保和促进所有人的健康生活和福祉。因此，本研究深入探讨了医疗保健支出（HCE）的决定因素，特别关注美国的金融发展（FDV）、旅游业（TOR）、技术创新（TINs）、经济增长（EG）和气候变化。调查使用了 2000Q1 第一季度至 2020Q4 第四季度的数据。为实现这一目标，我们采用了创新的基于量值的方法，包括小波量值回归和量值对量值的格兰杰因果关系。这些方法有助于全面探讨 HCE 及其影响因素在不同量级和时期的动态互动关系。小波量化回归和量化对量化回归分析结果一致表明，二氧化碳、TOR、EG、全球化、FDV、外国直接投资和 TIN 对美国的 HCE 有正向影响。此外，量级对量级的格兰杰因果关系分析结果表明，二氧化碳排放、TOR、EG、全球化、FDV、外国直接投资和 TIN 对所有量级的 HCE 都有显著的预测作用。这些见解有助于制定和实施各种政策，解决医疗保健支出及其驱动因素之间复杂的相互作用。
{"title":"Projecting a long‐term healthcare expenditure in the United States: Do climate change, globalization, and technological innovation play a major role?","authors":"Laurine Chikodiri Nwosu, Abraham Ayobamiji Awosusi, Oktay Özkan, Dervis Kirikkaleli, Tomiwa Sunday Adebayo","doi":"10.1111/1477-8947.12485","DOIUrl":"https://doi.org/10.1111/1477-8947.12485","url":null,"abstract":"Recognizing the paramount importance of health, the United Nations Development Program has outlined sustainable development goals, emphasizing Goal 3, which focuses on ensuring and promoting healthy lives and well‐being for all. Consequently, this study delves into the determinants of healthcare expenditure (HCE), specifically focusing on financial development (FDV), tourism (TOR), technological innovations (TINs), economic growth (EG), and climate change in the United States. The investigation utilizes data spanning from the first quarter of 2000Q1 to the fourth quarter of 2020Q4. To achieve this objective, we employed innovative quantile‐based methodologies, including wavelet quantile regression and quantile‐on‐quantile Granger causality. These approaches facilitated a comprehensive exploration of the dynamic interactions between HCE and its influencing factors across various quantiles and periods. The wavelet quantile regression and quantile‐on‐quantile regression analysis findings consistently indicate a positive impact of CO<jats:sub>2</jats:sub>, TOR, EG, globalization, FDV, foreign direct investment, and TIN on HCE in the United States. Furthermore, the results obtained from the quantile‐on‐quantile Granger causality demonstrate that CO<jats:sub>2</jats:sub> emissions, TOR, EG, globalization, FDV, foreign direct investment, and TIN significantly predict HCE across all quantiles. These insights have informed the formulation and implementation of various policies addressing the complex interplay between healthcare spending and its driving factors.","PeriodicalId":49777,"journal":{"name":"Natural Resources Forum","volume":"66 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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