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The global economy has recorded an unprecedented increase in growth rates in the last few decades occasioned by the expanding interconnectedness among countries through exchanging goods and services. The expanding production base has increased the demand for fossil fuels, specifically crude oil, both in local and foreign markets, leading to inevitable imports. Despite this, factors driving the increasing demand for oil imports have not been extensively researched thus calling for an empirical verification on the matter. Hence, this study contributes to the literature by investigating the tripartite effects of transportation infrastructure, economic growth, and renewable energy on crude oil imports. The empirical evidence relies on the autoregressive distributed lag (ARDL) model for bound test cointegration employed to obtain long- and short-run estimates. The empirical results from the study's analysis show that renewable energy hinders crude oil importation while transportation stimulates it in both economies. The inducing role of economic growth is substantial only in China, and the significant effect of foreign direct investment and industrialization prove to be fundamental in driving crude oil imports. Consequently, the study concludes that other explanatory variables contribute to crude oil dependence in China and India, asides from renewable energy. The post estimation tests conducted further accentuate the validity and reliability of the empirical outcomes. Drawing from the empirical outcome, the study suggests the criticality of renewable energy promotion as a viable policy decision to resolve the growth of oil dependence in the countries under study. [ABSTRACT FROM AUTHOR]

Ecologically unequal exchange theory posits asymmetric net flows of biophysical resources from poorer to richer countries. To date, empirical evidence to support this theoretical notion as a systemic aspect of the global economy is largely lacking. Through environmentally-extended multi-regional input-output modelling, we provide empirical evidence for ecologically unequal exchange as a persistent feature of the global economy from 1990 to 2015. We identify the regions of origin and final consumption for four resource groups: materials, energy, land, and labor. By comparing the monetary exchange value of resources embodied in trade, we find significant international disparities in how resource provision is compensated. Value added per ton of raw material embodied in exports is 11 times higher in high-income countries than in those with the lowest income, and 28 times higher per unit of embodied labor. With the exception of embodied land for China and India, all other world regions serve as net exporters of all types of embodied resources to high-income countries across the 1990–2015 time period. On aggregate, ecologically unequal exchange allows high-income countries to simultaneously appropriate resources and to generate a monetary surplus through international trade. This has far-reaching implications for global sustainability and for the economic growth prospects of nations. • We provide empirical evidence that supports the theory of ecologically unequal exchange. • High-income nations are net importers of embodied materials, energy, land, and labor. • High-income nations gain a monetary trade surplus via this resource appropriation. • Lower-income nations provide resources but experience monetary trade deficits. • The observed inequality is systemic and hampers global sustainability in multiple ways. [ABSTRACT FROM AUTHOR]

Added global carbon emissions have mainly come from China and India since 2012, which indicates importance of two countries in curbing global CO 2 emissions. Thus, their respective mitigation lessons have more realistic significance in developing more effective mitigation strategy. This study compared the dynamic evolution of their CO 2 emissions and driving factors behind changes, in order to find similarities and differences of two countries, and provide available policy implications to further reduce carbon emissions. Firstly, both China's and India's carbon emissions have been increasing during 2000-14: 3.4–9.9 Gt and 0.9–2.0 Gt, respectively. However, tendency of two countries varied differently: growth of China 's CO 2 have slowed down after the 2008 financial crisis, while India 's emissions were still accelerating at a high level on account of growing share of carbon-intensive energy in the whole energy structure. From the national and sectoral perspectives, both trends of carbon emissions from two countries have been analyzed. According to structural decomposition analysis, efficiency gains and slowdown of economic growth in China contributed to most decline of CO 2 but both production and consumption structures urged emissions up, while structure effects in India slightly reduced its CO 2 but low emission efficiency and expansion of trade scales caused growth of emissions. On this basis, firstly, China should optimize production structures by upgrading industries, while India should promote energy transformation and improve energy efficiencies. Secondly, strengthening cooperation and communications with developed countries with advanced technology and experience may make more progress in climate change for two countries. Experience and lessons of emission reduction deriving from the two would also provide references for other regions. Image 1 • Investigating CO 2 emissions of China and India for 2000–2014. • Explore main sources and sectors that dominated CO 2 emissions. • Improving efficiency and optimizing energy structure offset China's emission growth. • Optimizing its consumption structure offset India's emission growth. • Optimizing their consumption structure should be considered in China and India. [ABSTRACT FROM AUTHOR]

A boom in renewable energy consumption as a percentage of final energy consumption (REC) has a significant impact on cleaner production and environmental sustainability. However, studies on REC as for an individual country-case and panel case approach for top emitters are rare. Against this backdrop, this study investigates the long-run drivers of REC by using a time series data from 1990 to 2015. The FMOLS-grouped results indicate that economic growth and trade openness increase REC whereas population growth has a negative but significant impact on REC. To check for causal links, the innovating accounting approach using variance decomposition analysis is applied. The results show that there is a unidirectional causality running from economic growth, trade openness, and population growth to REC. Further, the predictive accuracy of the FMOLS based econometric output and the bi-directional long short-term memory (Bi-LSTM) is analyzed. The Bi-LSTM formulated algorithm outperformed the econometric output. The Bi-LSTM is utilized to forecast REC to the year 2030. The output from the Bi-LSTM shows that China, the US, India, the Russian Federation's, and Japan's REC will hit ∼11.3395, ∼11.1245, ∼34.6969, ∼2.9097, and ∼7.4859, respectively. The US and Japan's REC levels will increase while that of China, India, and Russia Federation will decrease. As a policy implication, new policy directives for China, India, and the Russian Federation are required to boost REC levels. [ABSTRACT FROM AUTHOR]