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.

The asymmetric and long-run effect of environmental innovation and CO2 intensity of GDP on consumption-based CO2 emissions in Denmark.

The study explores the relationship between globalization, GDP, the carbon intensity of GDP, patents, and its effect on consumption-based carbon emissions (CCO2E). For analysis, novel econometric approaches include nonlinear ARDL and Fourier ARDL, and for robustness, dynamic OLS applied. The results from cointegration tests reveal that there exists a significant long-run relationship between CCO2E, globalization, economic growth, patents, and the carbon intensity of GDP. Additionally, the empirical results indicate that only positive shock in patents on environmental innovations have a negative and significant impact on CCO2E, while positive and negative shocks in GDP and carbon intensity of GDP significantly increase CCO2E. However, only a negative shock in globalization demonstrates the increase in CCO2E. Also, dynamic OLS findings confirmed the robustness. Given the outcome, it is recommended that the Danish government be cautious when approving policies intended to increase economic growth, as this could negatively affect environmental sustainability. More so, research and development must contribute to technological advancement in the Danish manufacturing sector. Despite this, it is important to prioritize patent promotion. Patent protection can enable Denmark to develop eco-friendly technologies that can reduce carbon emissions, thus enabling life to be more sustainable by utilizing fewer resources and energy. Denmark can reduce CO2E and foster economic development through a strong patent system on environmental technologies.

Carbon dioxide intensity of GDP and environmental degradation in an emerging country.

This paper investigates whether the carbon dioxide (CO2) intensity of GDP matters for environmental degradation in an emerging country, namely, Turkey, over the period of 1990-2018 while controlling economic growth, foreign direct investment, and renewable energy consumption. The present study uses both linear and nonlinear time series estimators, namely, the Gregory and Hansen cointegration test, bounds test, nonlinear autoregressive distributed lag (NARDL) model, fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegrating regressions (CCR), to encapsulate the possible effect of CO2 intensity of GDP, economic growth, foreign direct investment, and renewable energy consumption on environmental degradation in Turkey. The empirical finding of the present study reveals that the CO2 intensity of GDP is an important factor to determine environmental degradation in Turkey and the declining CO2 intensity of GDP reduces environmental degradation. Moreover, economic growth is the primary environmental sustainability factor in Turkey. The result is vital for policymaking and can perhaps be applied to take decisive policy actions to mitigate environmental issues.

Economic complexity, tourism, energy prices, and environmental degradation in the top economic complexity countries: fresh panel evidence.

The study explores the association between economic complexity index (ECI), tourism (TR), gross domestic products (GDP), gross domestic products per capita (GPC), and energy prices indices (EPI) on CO2e using the top 18 economic complexity index countries data from 1990 to 2019. We employ the second-generation cointegration methods and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) to analyze the short- and long-term association also Dumitrescu and Hurlin Granger causality test applied. The results of Pesaran and Yamagata slope heterogeneity and Pesaran CD test confirm the presence of cross-sectional unit relationship and slope heterogeneity across countries, while positive long- and short-term associations were found among ECI, GDP, and CO2e. Also, TR, GPC, and EPI decrease carbon emissions both in the long and short term . Moreover, Augmented Mean Group (AMG) techniques verified and support these findings. The outcomes of the Dumitrescu and Hurlin Granger causality test showed that any policy aim at ECI, TR, GDP, GPC, and EPI has a considerable impact on CO2e. Based on the rigorous empirical analysis, we suggest that economic complexity, tourism, GDP, GPC, and energy prices would help alleviate high economic complexity countries' environmental degradation challenges.

Does exports diversification and environmental innovation achieve carbon neutrality target of OECD economies?

Achieving carbon neutrality is of great importance to many developed and developing countries around the globe. Global warming is one of the leading issues caused by human activities. To cope with environmental challenges, and to achieve carbon neutrality, fiscal decentralization and eco-innovation are promising strategies that can also enable countries and local governments to pursue visible economic growth. This study investigates the role of export diversification, environment-related technological innovation, and fiscal decentralization in effectively achieving carbon neutrality target for 37 OECD (Organization for Economic Cooperation and Development) economies from 1970 to 2019. For empirical analysis, it uses second-generation tests that deal with heterogeneity and cross-sectional dependence issues. To this end, this study employs updated cointegration techniques. The augmented mean group (AMG) approach is used to examine the long-run dynamic equilibrium among the variables of interest. The findings indicate that export diversification and fiscal decentralization followed by GDP growth affect carbon dioxide emission positively. While renewable energy consumption and environment-related technological innovation assure environmental improvement. Additionally, short-run causal and unidirectional links are found running from fiscal decentralization, export diversification, and environment-related technological innovation to carbon emissions. Our findings suggest that OECD partner countries need to be careful while devising fiscal decentralization and export diversification policies. They should increase the share of renewable energy, and expand environment-related technological innovation. Such strategic efforts would direct the OECD countries to meet the climate change mitigation agenda of sustainable development goals.

Do energy use and economic policy uncertainty affect CO2 emissions in China? Empirical evidence from the dynamic ARDL simulation approach.

Global warming is currently the biggest problem. China is the world's highest CO2 emitter. The Chinese authorities agreed to overcome global pollution per the current Paris treaty and have shown deep concern regarding global warming. Hence, policymakers are paying attention to economic policy uncertainty. Motivated by this issue, the study examines the effect of energy use, economic policy uncertainty, and economic growth on China's CO2 emissions from 1970 to 2018 by employing a novel dynamic ARDL simulation model. The findings show that energy use and economic growth have statistically substantial long-run and short-run positive effects on CO2 emissions. However, economic policy uncertainty has a statistically insignificant effect on CO2 emissions, due to firms' sustainability policies. Energy use can have valuable policy consequences, particularly for environmental sustainability. Therefore, based on the empirical findings, the crucial partnership and feedback on China's carbon emission policy should be carried forward.

Interventions for the Current COVID-19 Pandemic: Frontline Workers' Intention to Use Personal Protective Equipment.

BACKGROUND: Frontline workers (FLWs) are at a higher risk of COVID-19 infection during care interactions than the general population. Personal protective equipment (PPE) is regarded as an effective intervention for limiting the transmission of airborne viruses. However, research examining FLWs' intention to use PPE is limited. OBJECTIVES: This study addresses this research gap and also contributes by expanding the conceptual mechanism of planned behavior theory by incorporating three novel dimensions (perceived benefits of PPE, risk perceptions of the epidemic, and unavailability of PPE) in order to gain a better understanding of the factors that influence FLWs' intentions to use PPE. METHOD: Analysis is based on a sample of 763 FLWs in Pakistan using a questionnaire survey, and the structural equation modeling approach is employed to evaluate the suppositions. RESULTS: Study results indicate that attitude, perceived benefits of PPE, and risk perceptions of the epidemic have positive influence on FLWs' intention to use PPE. In comparison, the unavailability of PPE and the cost of PPE have opposite effects. Meanwhile, environmental concern has a neutral effect. CONCLUSIONS: The study results specify the importance of publicizing COVID-19's lethal impacts on the environment and society, ensuring cheap PPE, and simultaneously enhancing workplace safety standards.