Biomass energy, technological progress and the environmental Kuznets curve: Evidence from selected European countries

Ahmed, Ali; Uddin, Gazi Salah; Sohag, Kazi

doi:10.1016/j.biombioe.2016.04.004

Cited by 220 publications

(114 citation statements)

References 29 publications

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“…Yet, the relationship is insignificant in most estimations for the high-income-countries. The results are inconsistent with those of Álvarez et al (2015), Ahmed et al (2016), and Álvarez-Herranz and Balsalobre Lorente (2015, 2016), where the effect was negative. However, their studies were conducted on OCED countries and European countries, which are more developed than parts of our sample.…”

Section: Discussioncontrasting

confidence: 74%

“…Culas (2012) also finds the inverted U-shaped EKC for 9 Latin American countries when using a random effects model (REM). This shape has also been found for 29 OECD countries when using a stochastic impacts by regression on population, affluence, and technology model (Shafiei and Salim 2014) and for 24 European countries when using a pooled mean group approach (Ahmed et al 2016). Further, Al-Mulali et al (2016) find the inverted U-shaped relationship for Europe, East Asia and the Pacific, South Asia, and the Americas when using dynamic OLS.…”

Section: Literature Reviewsupporting

confidence: 52%

“…All, strongly connected with environmental policies. For instance, several studies use research and development and patent to measure countries’ technology and innovation (Álvarez et al 2015; Álvarez-Herranz and Balsalobre Lorente 2015, 2016; Ahmed et al 2016). They found that technological innovation has a negative effect on environmental degradation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…According to Popp (2012), the collection of data for expenditures in research and development can differ between countries and this data is therefore noisy. The available data is also limited for this variable and patent applications is a commonly used proxy for technology (Ahmed et al 2016). To measure the effects of trade on environmental degradation, we use trade as share of GDP ( TRD) as a proxy.…”

Section: Data and Preliminary Analysismentioning

confidence: 99%

See 3 more Smart Citations

The N-shaped environmental Kuznets curve: an empirical evaluation using a panel quantile regression approach

Allard

Takman

Uddin

et al. 2017

Environ Sci Pollut Res

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306

108

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We evaluate the N-shaped environmental Kuznets curve (EKC) using panel quantile regression analysis. We investigate the relationship between CO2 emissions and GDP per capita for 74 countries over the period of 1994–2012. We include additional explanatory variables, such as renewable energy consumption, technological development, trade, and institutional quality. We find evidence for the N-shaped EKC in all income groups, except for the upper-middle-income countries. Heterogeneous characteristics are, however, observed over the N-shaped EKC. Finally, we find a negative relationship between renewable energy consumption and CO2 emissions, which highlights the importance of promoting greener energy in order to combat global warming.

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Section: Discussioncontrasting

confidence: 74%

Section: Literature Reviewsupporting

confidence: 52%

Section: Literature Reviewmentioning

confidence: 99%

Section: Data and Preliminary Analysismentioning

confidence: 99%

See 2 more Smart Citations

The N-shaped environmental Kuznets curve: an empirical evaluation using a panel quantile regression approach

Allard

Takman

Uddin

et al. 2017

Environ Sci Pollut Res

Self Cite

306

108

View full text Add to dashboard Cite

show abstract

“…Next, considering both the numbers of countries ( N = 72) and the number of time‐series observations ( T = 42) is large in our study, so the assumption of homogeneity of slope parameters is also inappropriate (Pesaran & Smith, ). Third, this estimator is still unbiased regardless of whether our variables are I(1) or I(0); more importantly, by taking sufficient lag difference, this method addresses the endogeneity bias issue (Ahmed, Uddin, & Sohag, ). Accordingly, the PMG estimator is quite suitable for studying the long‐term effect of women's political empowerment on CO 2 emissions.…”

Section: Introductionmentioning

confidence: 99%

Does women's political empowerment matter for improving the environment? A heterogeneous dynamic panel analysis

Deng

2019

Sustainable Development

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According to the UN Agenda 21 in 1992, women were regarded as a very important part in achieving sustainable development. In this agenda, participation, equality, and empowerment for females were emphasized as bases for sustainable development. In this paper, we make an attempt to explore the relationship between women's political empowerment (WPE) and CO2 emissions. To that end, we apply panel‐cointegration techniques to investigate both long‐term and short‐term effects of WPE on the environment in 72 countries during 1971–2012. The results from the pooled mean group (PMG) estimator indicate that, in the long run, CO2 emissions decrease by about 11.51 percent points in response to a one‐unit increase in the index of WPE after controlling for a variety of other factors. However, the short‐term estimated coefficient of WPE is statistically insignificant. Moreover, further study shows that women's civil society participation has the largest effect, followed by political participation. Another noteworthy result is the effect of energy intensity. We find that both the long‐term and short‐term estimated coefficient of energy intensity are positive and highly statistically significant, but the magnitude of the short‐term estimated coefficient is lower than the long‐term one. This comparison suggests that the influence of energy intensity on CO2 emissions would usually take some time to materialize fully. From a policy perspective, our estimation results suggest that improving the status of women worldwide, especially in the developing countries, can reduce CO2 emissions.

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The role of biomass energy consumption and economic complexity on environmental sustainability in G7 economies

et al. 2022

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This paper empirically examines the effect of biomass energy consumption and economic complexity on environmental sustainability in G7 economies. The current study attempts to report a comprehensive analysis of biomass energy and economic complexity on ecological and carbon footprints and carbon emissions. We employ data from 1990 to 2019 and adopt robust panel econometric techniques that account for the analysis's cross‐sectional dependence. We conduct cointegration analysis, pooled ordinary least squares (OLS), system generalized method of moments (GMM) and conditional quantile model for our empirical analysis. The empirical findings show that both biomass energy consumption and economic complexity are detrimental to the ecological footprint and carbon footprint. Additionally, we find that globalization positively affects the environment, while we find some evidence that bureaucratic quality improves environmental quality. Finally, in line with other research, we find that economic growth has detrimental effects on the environment. Our results suggest that policymakers should be more cautious in promoting biomass as a clean energy source and that the G7 economies should take advantage of their leading position in innovation to invest more in sustainable practices and investment.

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Biomass energy, technological progress and the environmental Kuznets curve: Evidence from selected European countries

Cited by 220 publications

References 29 publications

The N-shaped environmental Kuznets curve: an empirical evaluation using a panel quantile regression approach

The N-shaped environmental Kuznets curve: an empirical evaluation using a panel quantile regression approach

Does women's political empowerment matter for improving the environment? A heterogeneous dynamic panel analysis

The role of biomass energy consumption and economic complexity on environmental sustainability in G7 economies

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