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This paper is dedicated to studying and modeling the interdependence between the oil returns and exchange-rate movements of oil-exporting and oil-importing countries. Globally, twelve countries/regions are investigated, representing more than 60% and 67% of all oil exports and imports. The sample period encompasses economic and natural events like the Great Recession period (2007–2009) and the COVID-19 pandemic. We use the dynamic conditional correlation mixed-data sampling (DCC-MIDAS) model, with the aim of investigating the interdependencies expressed by the long-run correlation, which is a smoother (but always daily observed) version of the (daily) time-varying correlation. Focusing on the advent of the COVID-19 pandemic in 2020, the long-run correlations of the oil-exporting countries (Saudia Arabia, Russia, Iraq, Canada, United States, United Arab Emirates, and Nigeria) and (lagged) WTI crude oil returns strongly increase. For a subset of these countries (that is, Saudia Arabia, Iraq, United States, United Arab Emirates, and Nigeria), the (lagged) correlations turn out to be positive, while for Canada and Russia they remain negative as before the advent of the pandemic. In addition, the oil-importing countries and regions under investigation (Europe, China, India, Japan, and South Korea) experience a similar pattern: before the COVID-19 pandemic, the (lagged) correlations were negative for China, India, and South Korea. After the COVID-19 pandemic, the correlations of these latter countries increased.

The health and wellness of people through life expectancy, mortality rate improvement, and sustaining the productivity of labor contributes a lot to national income. Infrastructure development consumes energy and releases carbon dioxide at different stages of the construction process. The current study explores the nexus between CO2 emission, energy consumption, mortality, life expectancy, and GDP in the top five carbon-emitting countries by using time series data from 1975 to 2015. The study used a cointegration technique to find the long- and short-run relationships between study variables. The study also used a structural break test to identify the break time. The results of the correlation matrix show strong positive correlation between CO2 emissions and energy consumption. It also reflects a weak correlation with mortality and life expectancy in Japan and Russia. The results of the ADF test indicated that the series are stationary at first difference and provided evidence to use Johansen cointegration test for long- and short-run relationships between independent series. Vector error correction term and ECT method are used to find long-run relationships between cointegrated series and adjustment parameters. For the structural breaks of health indicators and energy consumption study, we used the Gregory Hanson structural break. Mortality rate and life expectancy rate of China, U.S., Russia, India, and Japan show relevant policy changes with economic policies of each country.

This study examines the impact of economic growth, energy consumption, trade openness, financial development on carbon emissions for the case of Turkey by using annual time series data for the period of 1960–2013. The Lee and Strazicich test suggests that the variables are suitable for applying the bounds testing approach to cointegration. The cointegration analysis reveals that there exists a long-run relationship between the per capita real income, per capita energy consumption, trade openness, financial development, and per capita carbon emissions in the presence of structural breaks. The results show that in the long run, carbon emissions are mainly determined by economic growth, energy consumption, trade openness, and financial development. The VECM Granger causality analysis indicates a long-run unidirectional causality running from economic growth, energy consumption, trade openness, and financial development to carbon emissions. The findings also show that the EKC hypothesis is valid for Turkey both in the long run and short run. The study provides some implications for policy makers to decrease carbon emissions in Turkey.

This paper aimed at evaluating the validity of the deforestation-induced Environmental Kuznets Curve hypothesis controlling for the democracy between 1971 and 2018 in Bangladesh. The cointegration results provide statistical evidence of long-run associations between economic growth, deforestation propensities and the quality of democracy. The elasticity estimates certify the validity of the EKC hypothesis for all the three indicators of deforestation used in this paper: forest area coverage, deforestation rate and net forest depletion rate. Moreover, controlling for democracy lowers the threshold level of growth beyond which the marginal impact of growth results in environmental betterment by reducing the deforestation propensities in Bangladesh. Moreover, democracy and economic growth are also seen to exert a combined impact on the growth-deforestation nexus. The estimated growth thresholds are above the current real GDP level of Bangladesh which reasons the nation’s deforestation woes. Finally, the causality results also affirm causal associations between economic growth, deforestation and the quality of democracy. Thus, these findings impose key policy implications keeping into cognizance the sustainable economic and environmental development goals of Bangladesh.

The government of Argentina has recently declared its objective of turning the nation carbon-neutral by 2050. Thus, it is essential to identify the relevant factors which can facilitate the attainment of this environmental development target. Against this backdrop, this study aims to evaluate the impacts of renewable electricity output, trade globalization, economic growth, financial development, urbanization, and technological innovation on sectoral carbon dioxide emissions in Argentina during the 1971-2014 period. The findings, overall, suggest that enhancing renewable electricity output share in the total electricity output figure of the nation helps to curb carbon dioxide emissions generated from Argentina's energy, manufacturing and industry, residential and commercial buildings, and transportation sectors. Contrarily, greater trade globalization is evidenced to boost carbon dioxide emissions in almost all the aforementioned economic sectors. Besides, the findings also validate the existence of the carbon dioxide emission-induced environmental Kuznets curve hypothesis for all four sectors. In addition, financial development and urbanization are also evidenced to exert carbon dioxide emission-stimulating impacts, while technological innovation is witnessed to be necessary for curbing sector-based carbon dioxide emissions in Argentina. Accordingly, to decarbonize the economy, this study recommends the government of Argentina to adopt necessary policies for fostering renewable energy transition within the electricity sector, greening the trade globalization strategies, achieving environmentally sustainable economic growth, developing the financial sector by introducing green financial schemes, planning sustainable urbanization, and financing technological development-oriented projects.

Fossil fuel-dependency has induced a trade-off between economic growth and environmental degradation across the developing nations in particular. Against this backdrop, this study aims to evaluate the impacts of renewable energy use on the ecological footprints in the context of four South Asian fossil fuel-dependent nations: Bangladesh, India, Pakistan, and Sri Lanka. The econometric analysis involves the use of recently developed methods that account for cross-sectional dependency, slope heterogeneity, and structural break issues in the data. The results reveal that renewable energy consumption reduces the ecological footprints while nonrenewable energy use boosts the ecological footprints. The results also confirm the validity of the environmental Kuznets curve and pollution haven hypotheses for the panel of the South Asian nations. Besides, foreign direct investment inflows are found to degrade the environment while higher institutional quality improves it. Furthermore, unidirectional causalities are run from overall energy use, economic growth, and institutional quality to ecological footprints. At the same time, bidirectional associations between foreign direct investment inflows and ecological footprints are also ascertained. The overall findings highlight the pertinence of reducing fossil fuel-dependency, enhancing economic growth, restricting dirty foreign direct investment inflows, and improving institutional quality to ensure environmental sustainability across South Asia.

Methodology is proposed to uncover structural breaks in functional data that is ‘fully functional’ in the sense that it does not rely on dimension reduction techniques. A thorough asymptotic theory is developed for a fully functional break detection procedure as well as for a break date estimator, assuming a fixed break size and a shrinking break size. The latter result is utilized to derive confidence intervals for the unknown break date. The main results highlight that the fully functional procedures perform best under conditions when analogous estimators based on functional principal component analysis are at their worst, namely when the feature of interest is orthogonal to the leading principal components of the data. The theoretical findings are confirmed by means of a Monte Carlo simulation study in finite samples. An application to annual temperature curves illustrates the practical relevance of the procedures proposed.

Bangladesh is well on course to become one of the leading emerging market economies in the world. Hence, it can be expected that the economic growth of Bangladesh would substantially increase over the next decade. This, in turn, is likely to boost the energy consumption levels of the nation whereby meeting the surge in the energy demand would be a crucial agenda of the government. Therefore, it is important to understand the factors that influence the nation’s energy demand. Against this backdrop, this paper aims to evaluate the macroeconomic determinants of total, renewable, and non-renewable energy demands in Bangladesh between 1980 and 2014. Besides, the analysis is conducted for both primary energy and electricity consumption levels. The econometric methods used in this study controlled for the structural break issues in the data. The key findings, in a nutshell, show that economic growth and household consumption expenditure positively influence the overall primary energy and electricity demands in Bangladesh while income inequality exerts opposite effects. Besides, technological innovations are found to be reducing the total and non-renewable energy demand in Bangladesh while increasing the demand for renewable energy. On the other hand, positive oil price shocks are found to be ineffective in influencing the renewable energy demand but slightly reducing the non-renewable energy demand. Finally, the causality estimates portray the feedback hypothesis in almost all the cases to highlight the inter-relationships between economic growth and energy demand in Bangladesh. Hence, in line with these findings several critically important policy implications are suggested for managing the overall energy demand in Bangladesh.

This paper aims to scrutinize the validity of the greenhouse emissions-induced environmental Kuznets curve (EKC) hypothesis, controlling for liquefied petroleum gas (LPG) consumption, FDI inflows, and trade openness, in the context of six South Asian economies. Besides, the impacts of LPG use on both aggregate and disaggregated emissions of greenhouse gases are also evaluated. Using annual data from 1980 to 2016, the elasticity estimates from the autoregressive distributed lag (ARDL) regression analysis confirms the authenticity of the EKC hypothesis for Bangladesh, India, Sri Lanka, and Bhutan. In the cases of Pakistan and Nepal, economic growth, in the long-run, is evidenced to monotonically increase and decrease the greenhouse emissions, respectively. However, LPG consumption is found to homogenously reduce all types of greenhouse emissions in each of the selected South Asian nations. Moreover, in majority of the cases, statistical evidence of joint favorable impacts of economic growth and LPG consumption on the environment are ascertained. Furthermore, the Hacker and Hatemi-J bootstrapped causality analysis finds causal relationships between economic growth, greenhouse emissions, and LPG consumption. However, the causality estimates are found to be heterogeneous across the different South Asian nations considered in the analysis. The results, in a nutshell, denote that economic growth is both the cause and the solution to the greenhouse emission problems faced by the South Asian economies. Moreover, the results also assert that LPG can be a transitional fuel to reduce these emissions before the South Asian nations are ready to undergo transition from non-renewable to renewable energy consumption. Hence, the findings impose key fuel-diversification policy implications for the South Asian governments.

This study explores the feasibility of forming an optimal currency area (OCA) within the ASEAN + 3 + 3 group, including Pakistan, using the extended generalized purchasing power parity (G-PPP) theory. The objective is to determine whether these countries share a common stochastic trend and could form a stable OCA, considering the impacts of the Asian Financial crisis (AFC) and the Global financial crisis (GFC), with the US, China, and Japan serving as base countries, as predicted by G-PPP theory. The analysis employs the Johansen (Econ J 3:215–49, 2000) methodology, incorporating up to two exogenous structural breaks. The results suggest the presence of 127 out of 179 long-run G-PPP relationships with Pakistan, indicating greater potential for an OCA within sub-groups of countries that include Pakistan in the ASEAN + 3 + 3 setting. Stability tests confirm the parameter stability for Pakistan’s integration with ASEANBig5 + 3 + 3 countries in the post-AFC period.