The literature analyzing the ecological impacts of financial development (FD) documents mixed results. In addition, very limited researches consider the role of technological innovation in ecological sustainability even though technological innovation is indispensable to achieve technological advancement, which may help in sustainable development and ecological sustainability. Therefore, this work probes the effects of technological innovation, financial development, and economic growth (GDP) on the ecological footprint (EF) controlling urbanization and employing a STIRPAT framework. The analysis of data from West Asia and Middle East nations from 1990 to 2017 revealed cointegration in the model. The long-run coefficients produced by the continuously updated fully modified technique revealed that a 1% upsurge in technological innovation decreases EF by 0.010%. Interestingly, technological innovation is helpful to decrease EF and enhance economic growth in the West Asia and Middle East (WAME) countries. However, a 1% rise in FD boosts the level of EF by 0.0016% inferring that FD stimulates ecological degradation. Likewise, urbanization in the WAME countries raises EF levels and contributes adversely to ecological quality. In addition to this, the study revealed the environmental Kuznets curve hypothesis in the selected countries accounting for technological innovation, FD, and urbanization in the model. The causal analysis provided evidence of unidirectional causality from FD to EF and bidirectional causality between technological innovation and EF. The study recommends more investment in research and development and strong collaboration between the universities and industries to promote the level of technological innovation for both sustainable development and ecological sustainability. In addition, urban sustainability policies are necessary without decreasing the urbanization level.

Linking financial development, economic growth, and ecological footprint: what is the role of technological innovation?

The aim of the study is to estimate the nexus between energy insecurity and energy poverty with the role of climate change and other environmental concerns. We used DEA like WP methods and properties of MCDA, a most common form of data envelopment analysis (DEA) to estimate the nexus between constructs. This paper presents a measurement and analysis of G7 countries’ energy, economic, social, and environmental performance associated with energy poverty indexes. The study used the multiple, comprehensive, and relevant set of indicators, including energy economics and environmental consideration of energy poverty. The net energy consumption of al G7 economies is equal to 34 percent of the entire world along with the net estimate GDP score of around 50 percent. Using DEA modelling and estimation technique, our research presented valuable insights for readers, theorists and policy makers on energy, environment, energy poverty and climate change mitigation. For this reasons, all these indicators combined in a mathematical composite indicator to measure energy, economic, social, and environmental performance index (EPI). Results show that Canada has the highest EPII score, which shows that Canada’s capacity to deal with energy self-sufficiency, economic development, and environmental performance is greater than the other G7 countries. France and Italy rank second and third. Japan comes next with 0.50 EPI scores, while the USA has the lowest average EPI score environment vulnerable even though have higher economic development among the G7 group countries. We suggest a policy framework to strengthen the subject matter of the study.

How energy insecurity leads to energy poverty? Do environmental consideration and climate change concerns matters

This article measures renewable energy firm-level pure innovation efficiency, green productivity, technical efficiency, scale efficiency and total investment efficiency from micro input–output factors using Banker, Charnes and Cooper’s (BCC) data envelopment analysis (DEA) approach. Its main novelty is that it clearly explores the effective impacts of government subsidies and tax rebate policies on renewable energy firms’ investment efficiency using China’s renewable energy firm-level panel data. Our observational findings indicate that between 2001 and 2018, the aggregate degree of total investment performance from renewable energy firms rose steadily before declining. Renewable energy firms had larger ranges of total investment efficiency and size efficiency, and their levels of pure technological efficiency were both greater than 0.457%. At the 16% trust mark, current government subsidies and taxation rebates had dramatically positive effects on pure technological efficiency and total investment efficiency; additionally, government subsidies have a stronger positive impact on total investment efficiency and pure technical efficiency than taxation rebates. Furthermore, the ownership concentrations of renewable energy companies greatly encourage pure technological efficiency, size efficiency and total investment efficiency, and asset returns will significantly increase their average degree of total investment efficiency and pure technical efficiency.

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Testing green fiscal policies for green investment, innovation and green productivity amid the COVID-19 era

The study estimates the long-run dynamics of a cleaner environment in promoting the gross domestic product of E7 and G7 countries. The recent study intends to estimate the climate change mitigation factor for a cleaner environment with the GDP of E7 countries and G7 countries from 2010 to 2018. For long-run estimation, second-generation panel data techniques including augmented Dickey-Fuller (ADF), Phillip-Peron technique and fully modified ordinary least square (FMOLS) techniques are applied to draw the long-run inference. The results of the study are robust with VECM technique. The outcomes of the study revealed that climate change mitigation indicators significantly affect the GDP of G7 countries than that of E7 countries. The GDP of both E7 and G7 countries is found depleting due to less clean environment. However, green financing techniques helps to clean the environment and reinforce the confidence of policymakers on the elevation of green economic growth in G7 and E7 countries. Furthermore, study results shown that a 1% rise in green financing index improves the environmental quality by 0.375% in G7 countries, while it purifies 0.3920% environment in E7 countries. There is a need to reduce environmental pollution, shift energy generation sources towards alternative, innovative and green sources.The study also provides different policy implications for the stakeholders guiding to actively promote financial hedging for green financing. So that climate change and envoirnmental pollution reduction could be achieved effectively. The novelty of the study lies in study framework.

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Testing role of green financing on climate change mitigation: Evidences from G7 and E7 countries

In recent years, many empirical studies investigated the effects of globalization on the ecological footprint (EF). Most of these studies relied on the KOF index of globalization and studied the effects of total globalization and disaggregated impacts of economic, social, and political globalization on the EF. However, less attention has been given to financial globalization which can also influence the EF. Hence, this study investigates the association between financial globalization (FG), economic growth (GDP), and EF controlling population density (PD) in the selected West Asian and the Middle East (WAME) nations from 1990 to 2017. The study relied upon second-generation methods for checking stationary properties and Westerlund and other techniques to scrutinize cointegration. The evidence showed cointegration in the model. The long-run approximations from continuously updated fully modified (CUP-FM) and continuously updated bias corrected (CUP-BC) tests divulge that financial globalization is an important factor to promote ecological sustainability in the sample countries because it decreases EF. Population density exacerbates EF and worsens environmental deterioration in sample countries. The study detected the environmental Kuznets curve (EKC) between EF and economic growth in the presence of financial globalization and population density. Besides, financial globalization Granger causes EF, while the feedback effect exists between EF and economic growth. Based on these results, WAME economies can accomplish ecological sustainability and sustainable development by enhancing their financial globalization levels.

Is there a tradeoff between financial globalization, economic growth, and environmental sustainability? An advanced panel analysis.

Zhao, X; Gu, B; Gao, F, and Chen, S, 2020 Matching model of energy supply and demand of the integrated energy system in coastal areas In: Yang, Y; Mi, C; Zhao, L, and Lam, S (eds), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering Journal of Coastal Research, Special Issue No 103, pp 983–989 Coconut Creek (Florida), ISSN 0749-0208Due to the uncertainty of the selection range of the main equipment capacity of the distributed energy system in coastal areas, the matching ability of energy supply and demand is relatively low From the two directions of “power by heat” and “heat by electricity”, the operation and output modes of energy in the system are studied; the selection range of the main equipment capacity of the distributed energy system is determined by calculating the load of energy supply and demand; according to the selection range, the necessary mapping conditions of the matching relationship between energy supply and demand are analyzed, and the matching model of energy supply and demand is constructed by using the matching relationship between energy supply and demand, so as to complete the matching of energy supply and demand of the integrated energy system in coastal areas The experimental results show that the total energy output of the integrated energy system in coastal areas reaches 1867 kJ in unit time, but the proportion occupancy rate between the output nodes is the lowest, which has a good matching ability of energy supply and demand

Xuejiao Zhao

Papers

Matching Model of Energy Supply and Demand of the Integrated Energy System in Coastal Areas