This study aims to examine the impact of renewable and non-renewable energy consumption on the agriculture, industry, services, and overall economic activities (GDP) across a panel of G20 nations. The study makes use of annual data from 1980 to 2012 on 17 countries of the G20. To achieve the study objectives, we apply several robust panel econometric models which account for cross-sectional dependence and heterogeneity in the analysis. The empirical findings confirm the significant long-run equilibrium relationship among the variables. The long-run elasticities indicate that both renewable and non-renewable energy consumptions have significant positive effect on the economic activities across the sectors and also on the overall economic output. These results also imply that the impact is more from renewable energy on economic activities than that of non-renewable energy. Given that, our results offer significant policy implications. We suggest that the policy makers should aim to initiate effective policies to turn domestic and foreign investments into renewable energy projects. This eventually ensures low carbon emissions and sustainable economic development across the G20 nations.

This work investigates the dynamic heterogeneous causal links among financial development, construction industry, energy use, and environmental quality across the development levels, for 30 Chinese provinces during the period 2001–2016. For this purpose, a model of environmental quality has been constructed introducing the financial development and construction industry as endogenous factors. A Pedroni’s cointegration is employed and found the long-run cointegrating mechanism among the variables of interest. The dynamic common correlated effects mean group approach (DCCEMGA) is adopted to estimate the impact elasticities. Moreover, for robustness check, a sensitivity analysis is conducted employing common correlated effects mean group approach (CCEMGA). The main results are first, a two-way positive causal bridge is existent between gross domestic product (GDP) and energy use, construction industry and GDP, and financial development and GDP. In terms of the contribution of the construction industry to economic performance, construction industry-driven growth acceleration impact is observed. Second, a one-way positive causal link is identified running from financial development (both the banking sector and stock market) to the construction industry and is termed as finance-driven construction promotion effect. Also, a one-sided positive causal connection is operating from financial development and construction industry to energy use and carbon dioxide emissions. Finally, a standard environmental Kuznets curve (EKC), financial development-augmented EKC, and construction industry-augmented EKC hypotheses are found valid in the whole country and eastern region of China. Based on empirics, a regional heterogeneity has been observed in terms of the degree of impact and statistical significance while comparing the regional panels. The sensitivity analysis proved the empirical results to be robust and reliable. Moreover, based on the findings, policy recommendations are documented. Graphical abstract

Emerging economies are experiencing considerable economic changes due to change in energy demand and CO₂ emissions. To explore the link between energy demand and CO₂ emissions, this study disaggregates energy consumption into renewable and nonrenewable, and investigates its impact on carbon (CO₂) emissions by incorporating the role of trade openness using the environment Kuznets curve (EKC) framework. Emerging economies from 1990 to 2015 are examined based on Morgan Stanley Capital International’s (MSCI’s) classification. This empirical study uses cross-sectional dependence (CD) test and second-generation panel unit root test for precise estimation. The Pedroni and Westerlund panel cointegration tests are used to examine the long-run equilibrium. Continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) approaches are applied to investigate long-run output elasticities while the vector error correction model (VECM) is used to examine the direction of causal relationships among the variables. The results show that renewable energy consumption affects the CO₂ emissions negatively while nonrenewable energy consumption positively impacts the CO₂ emissions. The study also supports the EKC hypothesis. Trade openness adversely affects the CO₂ emissions which are an imperative inclination of these economies towards globalization. Moreover, in the long run, energy consumption from renewable energy and economic growth Granger cause CO₂ emission, nonrenewable energy, and trade openness. In the short run, renewable energy Granger causes economic growth, while economic growth Granger causes nonrenewable energy. The study offers some vital policy suggestions for these emerging economies and some interesting lessons for the developing economies.

This study attempts to investigate the relationship among electricity consumption, economic growth, and employment in China. Distinct from most of the previous studies, our empirical research identifies a long-run equilibrium cointegration relationship among the three covariates during the period of 1971–2009 with the recently developed autoregressive distributed lag (ARDL) bounds testing approach. The parameters are estimated through a long-run static solution of the estimated ARDL model and short-run dynamic solutions of the error correction model. The estimated models successfully pass diagnostic tests and both the long-run and short-run elasticities are found to be statistically significant. The study also indicates the existence of short-run and long-run causalities from electricity consumption and employment to economic growth. Results of this study show that electricity serves as an important driver of economic growth. Based on these results, several policy prescriptions on energy use and economic development are suggested for China.

This article researches the impact of financial openness on environmental degradation in the MERCOSUR countries over the time spanning from 1980 to 2014. The Panel Autoregressive Distributed Lag (PARDL), in the form of Unrestricted Error Correction Model (UECM), was computed with the purpose of decomposing the total effects of variables in their short- and long-run ones. The results of short-run impacts and elasticities of PARDL model showed that the financial openness increases the CO₂ emissions both in the short- and in the long-run. Moreover, the results also support that economic growth, consumption of primary energy, and agricultural production are responsible for an increase of emissions in the MERCOSUR countries. Therefore, these empirical findings will help expand the literature that assesses the impact of financial development on the environment. The results also point out to the need of policymakers to change the way the energy mix is financed.

The paper examines the impacts of financial development on sectoral carbon emissions (CO₂) for environmental quality in Malaysia. Since the financial sector is considered as one of the sectors that will contribute to Malaysian economy to become a developed country by 2020, we utilize a cointegration method to investigate how financial development affects sectoral CO₂ emissions. The long-run results reveal that financial development increases CO₂ emissions from the transportation and oil and gas sector and reduces CO₂ emissions from manufacturing and construction sectors. However, the elasticity of financial development is not significant in explaining CO₂ emissions from the agricultural sector. The results for short-run elasticities were also consistent with the long-run results. We conclude that generally, financial development increases CO₂ emissions and reduces environmental quality in Malaysia.

This study employs the autoregressive distributed lag (ARDL) approach and Granger causality test to investigate the short- and long-run relationships between health indicator, real GDP, combustible renewables and waste consumption, rail transport, and carbon dioxide (CO₂) emissions for the case of Tunisia, spanning the period of 1990–2011. The empirical findings suggest that the Fisher statistic of the Wald test confirm the existence of a long-run relationship between the variables. Moreover, the long-run estimated elasticities of the ARDL model provide that output and combustible renewables and waste consumption have a positive and statistically significant impact on health situation, while CO₂ emissions and rail transport both contribute to the decrease of health indicator. Granger causality results affirm that, in the short-run, there is a unidirectional causality running from real GDP to health, a unidirectional causality from health to combustible renewables and waste consumption, and a unidirectional causality from all variables to CO₂ emissions. In the long-run, all the computed error correction terms are significant and confirm the existence of long-run association among the variables. Our recommendations for the Tunisian policymakers are as follows: (i) exploiting wastes and renewable fuels can be a good strategy to eliminate pollution caused by emissions and subsequently improve health quality, (ii) the use of renewable energy as a main source for national rail transport is an effective strategy for public health, (iii) renewable energy investment projects are beneficial plans for the country as this contributes to the growth of its own economy and reduce energy dependence, and (iii) more renewable energy consumption leads not only to decrease pollution but also to stimulate health situation because of the increase of doctors and nurses numbers.

This paper investigates the impact of tourism investments on energy efficiency across the transportation and residential sectors of 32 Organization for Economic Co-operation and Development economies. Using annual data from 1995 to 2012, we employ various panel econometric techniques to achieve the study objectives. Given the nature of variables, the paper applies panel autoregressive distributed lag models to estimate the long-run elasticities of energy intensity. The long-run estimates confirm that tourism investments play an essential role in improving energy efficiency across the transportation and residential sectors. Furthermore, the results show that both the foreign direct investment inflows and trade openness also play a considerable role in reducing energy uses across these sectors. Finally, the findings suggest that the tourism investments Granger cause energy efficiency of transportation and residential sectors in the short-run. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.