The role of financial development, energy demand, and technological change in environmental sustainability agenda: evidence from selected Asian countries

Saleem, Hummera; Khan, Muhammad Bilal; Shabbir, Malik Shahzad

doi:10.1007/s11356-019-07039-0

Cited by 108 publications

(74 citation statements)

References 97 publications

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“…Similarly, Umar et al (2020) examine the long-run and causal effects of financial development on CO emissions in China using the combined co-integration and wavelet coherence approaches over the period 1971 to 2018; they discover that in the long run, there are negative correlations between CO 2 emissions and financial development for the case of China. Furthermore, Paramati et al (2017), Renzhi and Baek (2020), Saleem et al (2020), Shahbaz et al (2013b), and Zhao and Yang (2020) report the same results for the financial development-carbon emissions nexus, indicating that the effect of financial development on CO 2 emissions is negative. The second strand of literature suggests a positive effect of financial development on CO 2 emissions.…”

Section: Literature Reviewmentioning

confidence: 68%

“…First, scholars who have explored the impact of financial development on CO 2 emissions at the country level include Abbasi and Riaz (2016) and Shahbaz et al (2016) for Pakistan; Ali et al (2017) and Shahbaz et al (2013b) for Malaysia; Boutabba (2014) and Sehrawat et al (2015) for India; Moghadam and Dehbashi (2018) for Iran; Ozturk and Acaravci (2013) for Turkey; Shahbaz et al (2018) for France; Shahbaz et al (2013a) for Indonesia; and Ahmad et al (2018), Lahiani (2020), Umar et al (2020), Qi (2018), Yin et al (2019), Zhao and Yang (2020), and Zhang (2011) for China. For cross-country case studies, Paramati et al (2017) analyze the role of financial development in CO 2 emissions for the case of G20 countries; similar studies at the regional level have been conducted by Abdouli and Hammami (2020) for Middle East countries; Acheampong (2019) for 46 sub-Saharan Africa countries; Adams and Klobodu (2018) for 26 African countries; Charfeddine and Khediri (2016) and Shahbaz et al (2020) for the United Arab Emirates (i.e., a federation of seven emirates, including Abu Dhabi, Ajman, Dubai, Fujairah, Ras-al-Khaimah, Sharjah, and Ummal-Quwain); Koengkan et al (2019) for Latin American and Caribbean countries; Le et al (2020) for 31 Asian countries; Saleem et al (2020) for selected Asian countries; Seetanah et al (2019) for 12 selected small island developing states; Wang et al (2020a) for G-7 countries; Wang et al (2020b) for N-11 countries; Shoaib et al (2020) for eight developing countries (D8) and eight developed countries (G8); Tamazian et al (2009) for BRIC countries (i.e. Brazil, Russia, India, and China); and Ziaei (2015) for European, East Asian, and Oceania countries.…”

Section: Literature Reviewmentioning

confidence: 99%

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Time-varying impact of financial development on carbon emissions in G-7 countries: Evidence from the long history

Shahbaz

Destek

Dong

et al. 2021

Technological Forecasting and Social Change

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Financial development has been widely proved to be a key driver of economic growth; however, its environmental impact is still inconclusive, especially for G-7 countries (i.e. Canada, France, Germany, Italy, Japan, the United Kingdom (UK), and the United State (US)). This paper, therefore, investigates the time-varying impact of financial development on carbon dioxide (CO 2 ) emissions for G-7 countries over a long historical period. The study analyzes historical data from 1870 to 2014 for each country using bootstrap time-varying co-integration (TVC) and bootstrap rolling window estimation approaches. In addition, the polynomial trends of the estimated parameters are obtained to observe the relationship between financial development and carbon emissions. The empirical findings reveal that the impact of financial development on CO 2 emissions over a long history is M-shaped in Canada, Japan, and the US; inverted N-shaped in France, Italy, and the UK; and inverted M-shaped (W-shaped) in Germany. This empirical evidence opens new directions for policy makers to design comprehensive economic policy for using the financial sector as an economic tool to keep environmental quality at sustainable levels.

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Section: Literature Reviewmentioning

confidence: 68%

Section: Literature Reviewmentioning

confidence: 99%

Time-varying impact of financial development on carbon emissions in G-7 countries: Evidence from the long history

Shahbaz

Destek

Dong

et al. 2021

Technological Forecasting and Social Change

View full text Add to dashboard Cite

show abstract

“…Using several econometric methods, they verified both the EKC and renewable energy Kuznets Curve (RKC) hypotheses, indicating that a 10% rise in RER would lead to a 1.6% carbon emission reduction. Saleem et al [27] used the data for a period of 1980-2015 from selected Asian countries and employing several econometrics models, found the presence of an EKC hypothesis, where the impact of GDP growth and the square of GDP growth on CO 2 emissions are positive and negative, respectively. They also found that lower-income economies do not support the EKC hypothesis.…”

Section: Introductionmentioning

confidence: 99%

Forecasting the CO2 Emissions at the Global Level: A Multilayer Artificial Neural Network Modelling

2021

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Better accuracy in short-term forecasting is required for intermediate planning for the national target to reduce CO2 emissions. High stake climate change conventions need accurate predictions of the future emission growth path of the participating countries to make informed decisions. The current study forecasts the CO2 emissions of the 17 key emitting countries. Unlike previous studies where linear statistical modeling is used to forecast the emissions, we develop a multilayer artificial neural network model to forecast the emissions. This model is a dynamic nonlinear model that helps to obtain optimal weights for the predictors with a high level of prediction accuracy. The model uses the gross domestic product (GDP), urban population ratio, and trade openness, as predictors for CO2 emissions. We observe an average of 96% prediction accuracy among the 17 countries which is much higher than the accuracy of the previous models. Using the optimal weights and available input data the forecasting of CO2 emissions is undertaken. The results show that high emitting countries, such as China, India, Iran, Indonesia, and Saudi Arabia are expected to increase their emissions in the near future. Currently, low emitting countries, such as Brazil, South Africa, Turkey, and South Korea will also tread on a high emission growth path. On the other hand, the USA, Japan, UK, France, Italy, Australia, and Canada will continuously reduce their emissions. These findings will help the countries to engage in climate mitigation and adaptation negotiations.

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“…Research that investigates specifically the connection between technological innovation and the EF is not common. By taking carbon emissions as the main environmental measure, most research has centered on the effect of technological change on environmental quality [20][21][22][23][24]. The following mathematical model is set out in Eq.…”

Section: Model Specificationmentioning

confidence: 99%

“…There are also a variety of generic studies that discussed the environmental quality implications of technology and innovation [17][18][19]. There is limited evidence of the use of innovation and research and development as a combination of technological effects in measuring their influence on environmental quality [20][21][22][23][24]. To the best of our knowledge there is a very little indication that technology-environmental link has been incorporated in a single analysis using EF as a measure of environmental quality.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Technological Innovation on Environmental Quality: Accounting Ecological Footprint Indicators for Asian Countries

Hosan¹,

Rahman²,

Karmaker³

et al. 2020

Proceedings of International Exchange and Innovation Conference on Engineering &Amp; Sciences (IEICES)

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This paper explores the impact of technological innovation on the quality of the environment during the period 1985-2014, using the environmental footprint (EF) as an environmental proxy for selected Asian nations. The findings show that technological innovation in relation to EF is negative and significant, indicating that a one-point increase in technological change leads to a decrease of 0.097 per cent in environmental deterioration. In addition, the granger causality test Dumitrescu-Hurlin (DH) indicated that technological advancement has a bi-directional relation with EF. Moreover, the study of variance decomposition showed that EF is strongly influenced by technological innovation. The policy implications of this study suggest that leveraging policy instruments and incentives should be pursued to improve technological innovation toward ensuring a sustainable environment.

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The role of financial development, energy demand, and technological change in environmental sustainability agenda: evidence from selected Asian countries

Cited by 108 publications

References 97 publications

Time-varying impact of financial development on carbon emissions in G-7 countries: Evidence from the long history

Time-varying impact of financial development on carbon emissions in G-7 countries: Evidence from the long history

Forecasting the CO2 Emissions at the Global Level: A Multilayer Artificial Neural Network Modelling

The Effect of Technological Innovation on Environmental Quality: Accounting Ecological Footprint Indicators for Asian Countries

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