Energy mix with technological innovation to abate carbon emission: fresh evidence from Mexico applying wavelet tools and spectral causality

European Union and its progress towards affordable and clean energy in context of the Agenda 2030

The topic related to affordable and clean energy is currently highly actual. It is essential to realize that affordable and clean energy is energy without negative effects on the environment. Its advantage is that a lot of clean energy is renewable. Therefore, this type of energy contributes positively to the development of several spheres in the economy, such as agriculture, trade, communications, education, health and transport. The aim of the study is to analyze changes in the development of sustainable indicators set of affordable and clean energy in relation to Sustainable Development Goal 7 in the European Union, using cluster analysis to identify the differences and compare changes in the grouping of countries into clusters in the two years studied (2010, 2020). In addition to categorizing countries and confirming differences among member states of the European Union, the results allow us to evaluate the contribution of selected indicators to achieving affordable and clean energy. Our findings indicate that primary energy consumption per capita, final energy consumption in households per capita, energy productivity, share of renewable energy in gross final energy consumption and population unable to keep their home adequately warm shows a positive trend and supports the achievement of the Sustainable Development Goal 7.the energy import dependency is a problematic area in several countries. The results of cluster analysis showed that the largest shifts within the clusters were recorded in Italy, Estonia, and Luxembourg. The most positive shift occurred in Italy due to a significant improvement in four indicators. Luxembourg as a solo country cluster showed in 2020 some of the worst results due to the highest primary energy consumption per capita and the lowest share of renewable energy in gross final energy consumption. The dynamics of Estonia within the clusters was marked by the lowest value of the indicator of dependence on energy imports, as well as an increase in the share of renewable energy and insufficient energy productivity. The results of our study also confirm, that Sweden and Finland are leader countries, which despite high energy consumption are applying renewable energy sources to a greater extent by which they make a positive movement toward affordable and clean energy.

Linking tourist's footprint and environmental tragedy through transportation, globalization and energy choice in BIMSTEC region: Directions for a sustainable solution using novel GMM-PVAR approach

The rising temperature in the world's atmosphere is an outcome strongly linked to man-made manufactured interventions. Recreational activities in the form of tourism are such interventions that can unleash multidimensional negative externalities if not regulated properly. The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) region has become one of the major hubs for recreational activities in the last few decades. However, the region's tourism-led environmental degradation has received scant attention in the literature. As such, this paper unveils how tourist footprint affects the region's environmental sustainability and explores potential solutions to encourage the tourism industry to be more pro-environmental. We have used the novel GMM-PVAR technique to assess how globalization, transportation, green energy, and economic growth have affected the tourism industry and carbon footprint in the BIMSTEC region from 1990 to 2019. We lean on the empirical outcomes to propose regional sustainable tourism development policies. The GMM-PVAR model indicates that renewable energy, economic growth, and the transportation sector's development positively affect the tourism industry's growth in the region. However, globalization and environmental degradation negatively influence tourists' arrival. Contrarily, transportation services, economic growth, and tourism boost the carbon footprint in the region. Although globalization and clean energy reduce carbon footprint, these indicators are insignificant, indicating that this region is still lagging in renewable energy generation and failed to reap the positive spillovers of globalization. Based on these outcomes, we propose that the region redesign its tourism industry to encourage eco-friendly tourism by leaning more on pro-environmental strategies (i.e., powering the tourism industry through the penetration of renewable energies) and tightening environmental regulations.

Impact of COVID-19 on China's business and economic conditions: the importance of quantile asymmetries

China has remained a growth engine for the global economy for the last several years. In this study, we assess the impact of COVID-19 on China's business and economic conditions; employing the quantile-on-quantile (QQ) regression and the quantile causality approaches. These econometrics batteries suit our research postulation, as they are capable to delineate underlying asymmetries across the whole distribution, based on which we can infer whether the response of China's business and economic conditions towards COVID-19 is heterogenous or homogenous. Utilizing the novel business and economic conditions measures, we observed that COVID-19 had initially disrupted both business and economic conditions in China. However, they showcased recovery over time. Our in-depth analysis allowed us to infer that the effect of COVID-19 on China's business and economic conditions is heterogeneous across different quantiles, and there is reliable evidence of asymmetry. The outcomes of quantile causality in mean and variance corroborate our primary estimations. These findings educate policymakers, companies, and other stakeholders to understand the nuances of China's business and economic conditions vis-a-vis COVID-19 in the short-run and as time elapsed.

Investigating the nexus between trade policy uncertainty and environmental quality in the USA: empirical evidence from aggregate and disaggregate level analysis

Worldwide, environmental sustainability is a hot topic, particularly in industrialized countries due to their higher emission intensity. Environmental conservation and equitable economic growth have been prioritized in economic debate and policy development. Over the past three decades, the USA's emissions of carbon dioxide (CO₂e) have risen exponentially, as trade policy uncertainty (TPU). In this circumstance, this paper aims to contribute to the existing literature by exploring the effect of TPU on environmental quality by controlling the energy consumption, economic growth, and population in the USA over the period 1985M1 to 2022M3 employing the augmented ARDL and NARDL procedures in the presence of structural breaks. From our analysis, the results revealed that TPU affects negatively CO₂e in the residential sector, and negative changes in TPU positively affect CO₂e in the commercial sector both in the long and short run. On the other side, the outcomes show that energy consumption is a crucial key determinant factor in environmental degradation at the aggregate level and in all sectors. Furthermore, our findings clarify that economic growth upsurges the CO₂e at the aggregate level precisely in the industrial and residential sectors. Juxtaposing, in the long run, the results indicate that population growth could make additional pressure on environmental quality at the aggregate level, especially in commercial, power generation, and residential sectors. Accordingly, it is clear from our results that the regulations put in place to encourage Americans to buy locally created goods instead of those imported, especially in light of the high levels of TPU, maybe the best option to decrease the long-term impact of international trade on the environment to achieve sustainable development goals (SDGs).

Analyzing the role of green innovation and public-private partnerships in achieving sustainable development goals: a novel policy framework

The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13.