Browsing by Author "Sharif, Arshian"

Now showing 1 - 4 of 4

Citation - WoS: 44
Citation - Scopus: 43
Nuclear Energy Consumption, Energy Access and Energy Poverty: Policy Implications for the COP27 and Environmental Sustainability
(Elsevier Sci Ltd, 2023) Bashir, Muhammad Farhan; Ma, Beiling; Sharif, Arshian; Ao, Tong; Koca, Kemal
The ever-increasing energy resource demand and subsequent environmental challenges mean that policymakers have shifted their focus to nuclear energy to address energy and environmental issues due to its unlimited potential. The current study investigates the role of nuclear energy consumption to unveil contextual information and report novel evidence concerning the significance of energy and environmental policies. This research is a novel attempt to outline methodological and topical contributions, thematic analysis, co-citation analysis, and country-collaboration analysis. As energy and environmental solutions have been prioritized within sustainable development goals, our research approach would allow policymakers and researchers to understand the extent to which nuclear energy can provide solutions towards environmental sustainability and identify research limitations to overcome by future studies. Moreover, our extensive analysis allows us to argue that nuclear energy impacts energy demand and is the most critical factor in fulfilling environmental commitments under regional and international environmental agreements.
Citation - WoS: 89
Citation - Scopus: 99
Analysis of the Spillover Effects Between Green Economy, Clean and Dirty Cryptocurrencies
(Elsevier, 2023) Sharif, Arshian; Brahim, Mariem; Dogan, Eyup; Tzeremes, Panayiotis
Cryptocurrencies have been widely used as financial instruments over the past decade. Given the development of the cryptocurrency market and the increasing awareness of greener and more energy-efficient tokens, their connection to the green economy has become a popular topic for understanding economic and policy issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green economy in-dicators. Therefore, this study examines the correlations and spillover relationships between green economy indices, five black cryptocurrencies, and five clean cryptocurrencies for the U.S., Euro, and Asian markets. To this end, it applies the novel quantile spillover index approach of Ando et al. (2018) to daily data from November 9, 2017, to April 4, 2022. The empirical results show that the overall linkage is stronger for green economy indices and clean cryptocurrencies than for dirty cryptocurrencies. Moreover, green economy indices show net receiving behavior, while cryptocurrencies' results differ across variables, quantiles, and time. In addition, a notable point for clean cryptocurrencies is 2020, which was the start of the COVID-19 pandemic. The overall spillover effect is very high for all quantiles for the three markets, especially for Asia. This outcome signifies the safe harbor property for diversification purposes of the green economy. The results presented in this study are important for investors, regulators and, policymakers, cryptocurrency founders as they seek to be financially integrated and develop a more sustainable business.
Citation - WoS: 12
Citation - Scopus: 10
Rare Disaster and Renewable Energy in the USA: New Insights from Wavelet Coherence and Rolling-Window Analysis
(Springer, 2020) Sharif, Arshian; Dogan, Eyup; Aman, Ameenullah; Khan, Hafizah Hammad Ahmad; Zaighum, Isma
The increasing trend of economic and political crises in different parts of the world has made global economies highly vulnerable because of having globally as well as regionally integrated economic systems. In such an environment, switching to alternative energy products, such as renewable energy production, may be devastating. Therefore, the aim of this paper is to provide novel insights for the relationship between rare disaster risks and renewable energy production (REN) of the USA by utilizing the time series monthly data from 1973 to 2016. Using time-varying continuous wavelet power spectrum, the wavelet coherence, and the modified bootstrap rolling-window analysis, the results reveal significant linkages between all the categories of rare disaster risks and renewable energy production. Rare disaster risks and REN are linked with each other, and both the variables have time-varying cyclic and anti-cyclic effects on each other with robust and significant predictability from rare disasters to REN. These findings have novel implications for many stakeholders. For instance, producers of energy may safely switch to renewable energy production since disasters are found to have potential to leave cyclic effect on renewable energy at most.
Citation - WoS: 30
Citation - Scopus: 30
Influence Mechanism of Electricity Price Distortion on Industrial Green Transformation: A Spatial Analysis of Chinese Regions
(Elsevier, 2024) Razzaq, Asif; Sharif, Arshian; Yang, Xiaodong; Dogan, Eyup
Electricity price distortion (DIS) can significantly affect industrial green transformation (IGT), influencing the pace and direction of sustainable economic growth. Understanding this link is essential for crafting effective green energy policies. Initially, this study evaluates the direct and heterogeneous effects of DIS on IGT and then investigates the indirect influence channels using a sample of 30 Chinese provincial-level administrative regions from 2006 to 2019. Spatial analysis techniques (standard deviation ellipse and geographically and temporally weighted regression methods) are applied to explore the spatial and temporal dependence and non-stationary association between DIS and IGT. The outcomes suggest that DIS significantly reduces IGT in the eastern region through R&D input intensity and energy mix, while insignificant in the central and western regions. The adverse effect of DIS is more substantial at higher quantiles of IGT. The individual spatial heterogeneity characteristics reveal that the gravity centre of IGT is located in the southeast of the geometric centre of China, displays a southwest-northeast-southeast directional migration, and distributed at the junction of Henan and Hubei. Manifestly, the ellipse and azimuth of IGT vary significantly between 0.862 degrees -32.854 degrees. The IGT level steadily progresses from discrete to concentrated, reflected by the ellipse's long and short semi-axes. These regions are mainly concentrated in the eastern and northwestern areas, with the most significant inhibitory effects in Fujian, Anhui, Shaanxi, Zhejiang, and Yunnan. These findings offer valuable policy implications.