This study investigates the spatial influence and spillover effects of foreign direct investment (FDI) on environmental pollution (EP) by using panel spatial data in 1970–2016 for 12 selected Arab countries. It employs the STochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The spatial econometric approach is applied to examine the validity of the pollution haven hypothesis (PHH) and the pollution halo hypothesis (P-HH) (from now on, we will use the acronyms PHH and P-HH to denote the pollution haven hypothesis and pollution halo hypothesis, respectively). The Sustainable Development Goals (SDGs) are linked to the study results with a focus on cleaner production practices. The global Moran’s I, local Moran’s I, and Lagrange multiplier (LM) tests are used to ascertain the existence of spatial autocorrelation (SAR) and determine its trend. We also apply the spatial lag model (SLM), the spatial error model (SEM), and the spatial Durbin model (SDM) to achieve the study objectives. Data are analyzed by using the SDM on the basis of the results of the Wald and likelihood ratio tests. The results of the LM and global and local Moran’s I tests confirm the existence of SAR. The SDM results reveal that a slight increase in CO₂ is an influence of the FDI on EP. Findings support the existence of PHH in the Arab countries. The direct effect of the FDI is increased CO₂ and environmental degradation, and the spatial spillover effects are statistically insignificant. This study suggests a set of policies for managing and directing FDI toward clean technology-based industries and reduced CO₂ emissions. Such policies may contribute to the achievement of some SDGs and balancing economic development and environmental sustainability according to the cleaner production practice perspective in the Arab countries and other states with similar conditions.

Trade openness is one of the main channels of globalization and technological transfers. In environmental economic literature, the implications of trade openness remain controversial and still could be potential drivers of carbon dioxide emissions. This study therefore explores the effect of trade openness in developed countries using EU-18 economies. We employed an econometric approach that accounts for cross-section dependence among study variables. The panel CIPS and CADF unit root show that the variables are stationary and the long-run relationship was confirmed in Westerlund cointegration tests. The mean group (MG) and augmented mean group (AMG) results show that trade openness increases CO₂-emissions in EU-18. Again, energy consumption and urbanization escalate emissions. The study confirmed the environmental Kuznets curve. Finally, pollution halo and pollution haven hypothesis were confirmed at both estimation methods. The Dumetriscu-Hurlin Granger causality test results confirmed bidirectional causality between trade openness and energy consumption and between trade openness and economic growth. Again, unidirectional Granger causality is running from trade openness and CO₂ emissions. Policy recommendations are further proposed.

The main aim of this current study is to empirically scrutinize the determinants of energy consumption for 24 African countries sub-grouped into three panels based on income levels: low-, lower-middle-, and upper-middle-income countries, from 1990 to 2015. Due to the presence of heterogeneity and cross-sectional reliance among country groups, recently developed econometric approaches, which include cross-sectional Im, Pesaran, and Shin together with cross-sectional Augmented Dickey-Fuller stationarity tests, Pedroni and Westerlund–Edgerton cointegration assessment, dynamic common correlated effect estimation approach and Dumitrescu–Hurlin Granger causality test are employed. Empirically, our findings depict analyzed variables are stationary and characterized by long-term stability affiliations for all panels. Economic growth, urbanization, population growth, and oil price with labor and capital stock as intermittent variables had palpable significant positive sway on energy consumption for all panels though their respective weight of contribution differed from one country group to another. The granger test of causation unveiled that (i) among all panels, urbanization and energy consumption are connected bidirectionally, whereas population growth causes energy consumption; (ii) a one-way causal link from economic growth to energy use is evidenced in low-income African countries, whereas a two-sided connection is confirmed in both lower-middle- and upper-middle-income economies; (iii) a bilateral causal association in low-income African nations is observed amid oil price and energy use, while a uni-lateral relationship extends from oil price to energy consumption in both lower-middle- and upper-middle-income nations in Africa. Such new methodologies and findings reveal that the long-term estimated effects as well as causal affiliations amid variables are skewed by different income levels of African countries in an attempt to conserve energy. Policy recommendations are further propose.

This study aims to explore the relationship of environmental degradation with economic growth and energy innovation by utilizing the panel data of 33 European countries by covering the period of 1996 to 2017. We use the cross-sections independence and control the heterogeneity between cross-sections by using the second-generation econometric of panel data. The Westerlund bootstrap co-integration, CIPS unit root test, Pedroni co-integration, panel causality techniques, and FMOLS have been used to analyze the relationship. The result of the study shows that all the variables are integrated in the long run. Energy innovation has a negative and significant impact on environmental degradation. On the other hand, gross domestic product has a U-shape and significant relationship with environmental degradation by supporting Kuznets curve. Therefore, this study helps not only the policymaker and government but also the people and businessmen on how they can increase the growth of the business and economy without effecting the environment.

The article examines the effects of renewable energy, trade, carbon dioxide emissions and international tourism on economic growth in EU-28, considering panel data for the period 1995–2014. The investigation finds the new determinants of economic growth. The empirical results find support from the panel fully modified least squares (FMOLS), panel dynamic least squares (DOLS) and fixed effects (FE) as estimation techniques. The econometric results are consistent with the existing literature. The variables considered in this study are cointegrated in the first difference, as suggested by the panel unit root test. The present study seeks to advance the knowledge of the growth determinants, paying attention to the effect that both the tourism and energy sector exerts on economic growth for EU-28 countries. The empirical results demonstrate that trade openness, tourism arrivals and renewable energy encourage economic growth. Therefore, according to the econometric results, renewable energy allows improving environmental quality. However, CO₂ emissions are positively correlated with economic growth, showing that growth is directly correlated by climate change and greenhouse gas. The results also confirm the tourism-led growth hypothesis (TLGH) for the panel. Finally, the empirical results confirm that trade openness, energy use and international tourism contribute to enhance economic growth. Based on these findings, further insights and policy prescription are offered in the concluding section.Graphical abstract

China is a rising power of the twenty-first century with its brilliant economic performance as a result of the transition to the free market economy model. However, China’s economic development process has caused high environmental costs. For the past decade, China has been the leading country responsible for global carbon dioxide emissions (CO₂). Therefore, determining the dynamics that have a reducing effect on CO₂ emissions in China is very important for the development of sustainable environmental policies. This paper aims to examine the impacts of the institutional structure on environmental sustainability in China. To this end, the study follows the method of cointegration with multiple breaks that produce robust econometric results and consider structural changes. According to the results, (i) the validity of an N-shaped EKC relationship is supported between economic growth and environmental pollution. (ii) Industrialization and trade have an increasing impact on environmental pollution. (iii) Political rights and civil liberties have a reducing effect on environmental pollution. Consequently, this study implies that political rights and civil liberties can make an important contribution to achieving sustainability goals in China.

Most of the countries of South America depend heavily on mining and agriculture, which develops through the destruction of the forest. The expansion of the agricultural frontier is more visible in countries with proximity to the Amazon. Otherwise, the increase in urban primacy and real income per capita has led to an increase in the use of non-renewable energy in recent decades. The interest in quantifying greenhouse gas emissions has increased, oriented towards the search for mechanisms that mitigate the irreversible effects of climate change. In this context, the objective of this research is to examine the causal link among non-renewable energy consumption and real GDP per capita in greenhouse gas emissions in ten countries of South America during 1971–2014. In addition, we group the countries according to their productive structure and we incorporate the structural changes of each country in the econometric estimations, allowing to significantly improve the understanding of the sources of greenhouse gases. We use cointegration and causality techniques for time series data, and we found that there is a relationship of short- and long-term equilibrium between the three variables in all countries. The causality test indicates that in Bolivia, Peru, and Uruguay, there is causality from the consumption of non-renewable energy to greenhouse gas emissions. Likewise, in Venezuela and the agricultural countries, GDP causes greenhouse gas emissions. An implication of the public policy derived from this research is that most of the countries of South America can promote a change in the energy matrix to contribute to the mitigation of greenhouse gas emissions without limiting economic growth.

Recently, several seminal works have been drawing attention to the revolution of shale gas production technology of the USA, the impact of shale gas on energy sectors, as well as the influences of shale gas on macroeconomic variables of employment, economic growth, etc. Nevertheless, one may claim that two gaps appear in literature. The first gap is the absence of an econometric study estimating the effect of shale oil/gas on national economies. The more considerable second gap is the absence of econometric analyses revealing the impulses of shale gas on local economies. Therefore, this paper observes the possible causalities between the shale gas and local gross domestic product (GDP) employing quarterly data covering the period 2007–2016 for 12 states in the US. After performing the tests of cross-sectional dependence, heterogeneity, stationarity, and cointegration, the paper conducts the panel Granger causality analyses. The empirical findings depict that (i) there is available unidirectional relationship from local shale gas production to local GDP in Colorado, Ohio, and West Virginia; (ii) there occurs an impulse from GDP to local shale gas production for Louisiana, North Dakota, and Oklahoma; (iii) a bidirectional causality coexists between local shale gas production and GDP in Arkansas, California, and Texas; and (iv) there exists no association between local GDP and local shale gas extraction in Montana, New Mexico, and Wyoming.

The aim of this study is to examine the relationship between climate change and political instability in the MENA region. To this extent, 18 Middle East and North African (MENA) countries are analyzed covering the period 1985:01–2016:12 with monthly data. In econometric analysis, at first cross-sectional dependency analysis is applied, and existence of cross-sectional dependency among countries is found. Therefore, CADF-second generation panel unit root test applied, and finally, Dumitrescu and Hurlin (2012) panel causality test that consider the cross-sectional dependency are utilized. For empirical analysis, temperature and precipitation data representing climate change, political instability, and conflict data are employed. According to the findings, there is a causal relationship from climate change to political instability in 16 countries and to conflict in 15 countries. In addition to this, at least one causal relationship is determined from climate change to political instability or conflict in all MENA countries. Therefore, empirical results support the assumption that climate change acts as a threat multiplier in MENA countries since it triggers, accelerates, and deepens the current instabilities.

Fixed-asset investment directly affects energy consumption through purchasing and upgrading energy-saving equipment on the one hand, and indirectly affects energy consumption by expanding output scale on the other hand. This paper analyzes the multiple effects of fixed-asset investment on energy consumption by three strata of industry in China during 1991–2017. The econometric methods based on VAR model such as Johansen co-integration test and Granger causality test (linear Granger causality test and non-linear Granger causality test) are utilized to explore the long-run stable equilibrium relationships and causal interactions between fixed-asset investment and energy consumption. And the mediation test is performed by employing the bias-corrected non-parametric percentile bootstrap method combined with causal steps approach to obtain the direct and indirect effects of fixed-asset investment on energy consumption. Our study indicates that there are long-run stable equilibrium relationships between fixed-asset investment and energy consumption by three strata of industry. Bidirectional causalities exist in secondary and tertiary industries between fixed-asset investment and their respective energy consumption, and a unidirectional causality exists in primary industry from fixed-asset investment to energy consumption. The fixed-asset investment in primary industry directly suppresses its energy consumption, while indirectly promotes its energy consumption through its value added. And the fixed-asset investment in secondary industry not only directly promotes its energy consumption but also indirectly promotes its energy consumption through its value added.