Empirical evidence of emissions discourse related to food, beverage, and tobacco production in leading manufacturing nations.

The proliferation of carbon dioxide (CO2) emissions has resulted in significant environmental challenges worldwide, particularly within industrialized nations. The present paper tries to investigate the role of food, beverages, and tobacco in mitigating CO2 emissions in the top industrial countries. Economic growth and renewable and non-renewable energy consumption are integrated as control variable in the empirical model. The study applied the pooled mean group-autoregressive distributed lag (PMG-ARDL) model proposed by (J Appl Econ, 16:289-326, 2001) and Granger causality test for causalities directions. The empirical outcomes suggest the presence of cross-sectional dependence, and variables are integrated of order one and cointegrated. Long-run estimates revealed the presence of inversed U curve proving the validity of the environmental Kuznets curve. Also, the results show that renewable energy (RE) consumption contribute in reducing emissions, while non-renewable energy (NRE) and food, beverages, and tobacco (FBT) led to increase emissions level in the long run. Granger shows bidirectional long-run relationship between CO2 emissions, non-renewable energy, and economic growth. Moreover, Granger recorded no causality between food, beverages, and tobacco and any other variable. We recommend that firms engaged in the production of food, beverages, and tobacco products are increasingly urged to make investments in clean technologies powered by renewable energy sources for their manufacturing processes. This is considered a necessary step to achieve a significant reduction in CO2 emissions over an extended period.

Does ICT influence carbon emissions in the context of universal connectivity: a global perspective?

The Connect 2030 initiative, launched by the International Telecommunication Union, is in alignment with the Sustainable Development Goals (SDGs) of the United Nations Agenda 2030. Its main objective is to achieve universal connectivity, a goal that is closely related to environmental issues. This topic currently receives attention from researchers and policymakers. Given these considerations, our study investigates the impact of information and communication technologies on carbon dioxide emissions for a panel of 84 countries spanning the years 2009 to 2020. Using principal component analysis, we construct an ICT index that encompasses international bandwidth, reflecting the universal connectivity, and participation in international data exchanges. The empirical analysis applies the pooled mean group-panel autoregressive distributive lag (PMG-ARDL) approach to estimate both the long-run and short-run coefficients of CO2 emissions' determinants. Our findings show that ICT and renewable energy mitigate CO2 emissions, unlike financial development, GDP, and non-renewable energy, which contribute significantly to emissions for the full sample. These outcomes suggest that promoting ICTs in general and international bandwidth in particular, as part of universal connectivity, improves the quality of the global environment.

Do financial development, financial stability and renewable energy disturb carbon emissions? Evidence from asia-pacific economic cooperation economics.

The present paper investigates the influence of renewable energy consumption (REC), economic growth (GDP), financial development index (FDI), z-score (ZS) and control of corruption (CC) on carbon dioxide (CO2) emissions, for eighteen different APEC economies over the period 2000-2019 using the Pooled Mean Group-Autoregressive Distributed Lags (PMG-ARDL) approach and Granger causality tests. The outcomes of the empirical study confirm that the variables are cointegration using Pedroni tests. The long-run estimates revealed that economic growth and renewable energy contribute to the huge of carbon emissions, while financial development, ZS and CC lead to decrease carbon emissions. Granger causality shows that, in the long-run, there is bidirectional causality between CO2 emissions, economic growth, and financial development. In the short-run and for basic variables, Granger shows a unidirectional causality from CO2 emissions and economic growth to REC and; unidirectional causality from financial development, ZC and CC to CO2 emissions. A comprehensive approach is needed in APEC countries to effectively reduce CO2 emissions and promote sustainable development, including encouraging green financial products, reinforcing financial regulations, transitioning to a low-carbon economy, enhancing renewable energy usage, and improving governance and institutional quality, while considering the distinctive characteristics of each country.

The productive capacity and environment: evidence from OECD countries.

Environmental degradation is one of the most important and vital issues of today. In this context, many researchers are testing the environmental impact of different indicators. Many economic parameters affect environmental degradation. At the forefront of these parameters is the productive economic structures of the countries. For the first time in the literature, the present paper discusses the dynamic relationship between carbon dioxide (CO2) emissions, economic growth, and the productive capacity index (PCI) for a panel of 38 organization for economic co-operation and development (OECD) countries spanning the period 2000-2018. In this context, the PCI serves as a measure of the productive economic structure of a country. This empirical study applies panel cointegration techniques to reveal that the series are cointegrated in the long-run. In addition, the pooled mean group-panel autoregressive distributive lag (PMG-ARDL) approach is employed to estimate long-run coefficients. These coefficients confirm the environmental Kuznets curve hypothesis. Finally, the empirical findings confirm that improved productive capacity decreases environmental degradation. This results in important policy recommendations for involved governmental and private stakeholders.

Inspecting the influence of renewable energy and R&D in defending environmental quality: evidence for California.

The United Nations's Sustainable Development Goals (SDGs) is international cooperation that aims to climate change mitigation, and encourage the use of clean energy. Investing in green technology to reduce carbon dioxide (CO2) emissions is among the most important objective of the SDGs. As the USA is part of this collaboration, the present study tries to examine the progress of one State to meet the Global Goals. This paper uses the autoregressive distributed lags (ARDLs) approach and Granger causality test to evaluate the dynamic relationships uniting gross domestic product (GDP), CO2 emissions, renewable energy consumption (REC), and research and development (R&D) for the California State over the period 1987-2017. The outcome of the econometric analysis proved that REC affects CO2 emissions in the short run, and vice versa. In addition, a bidirectional relationship is detected between GDP and R&D and CO2 emissions and REC Granger causes GDP. In the long run, REC, R&D, and GDP Granger cause CO2 emissions, while REC, R&D, and CO2 emissions Granger cause GDP. We also found a bidirectional causality linking CO2 emissions and GDP. The long-run elasticities show that R&D and GDP impact positively CO2 emissions whereas REC affects it. Thus, R&D increases pollution but REC reduces it. Environmental degradation is perhaps related to the excessive consumption of fossil energy in most activities. California is advised to enhance the effort to meet the SDGs. Encouraging R&D of low carbon technologies and applying several taxations for non-renewable fuel adoption may also constitute a useful strategy to protect the environment.

What does the EKC theory leave behind? A state-of-the-art review and assessment of export diversification-augmented models.

Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.

Can green trade save the environment? Introducing the Green (Trade) Openness Index.

Environmental degradation is one of the main drivers of climate change. One of the most broadly accepted tools to minimize environmental degradation is the introduction of "green products". This paper introduces the "Green Trade Openness Index" to (a) measure the importance of green products in a region and (b) revisit the trade-environment nexus in a sample study of 31 OECD countries over the period 2007-2017. The empirical analysis confirms the environmental Kuznets curve hypothesis and - more importantly - demonstrates for the first time that the presence of green products in a country's trade basket reduces that country's ecological footprint. This is essential information for practitioners and policy makers looking for a pathway to sustainable development. Finally, the novel index creates opportunities for future research, as the index can be used as explanatory variable in different research questions and fields of research.

Industrial growth, clean energy generation, and pollution: evidence from top ten industrial countries.

Unlike the previous study, this paper employs panel cointegration and Granger causation approaches to discuss the associations among carbon dioxide (CO2) emissions, GDP growth, clean energy generation, and industrial growth for the top ten industrial countries spanning the period 1980-2014. The primary empirical outcomes show a two-way long-run association between environmental indicator, GDP growth, and clean energy generation, while one short-run causation from clean energy generation to CO2 emissions and from industrial growth to clean energy generation. The computed coefficients elasticity's under FMOLS, DOLS, and CCR estimates revealed that the clean energy generation statistically contributes to declining emissions of CO2 in Australia, Austria, and Chile while statistically increase emissions of CO2 in Denmark and the Netherlands. Industrial growth statistically contributes to reducing emissions of CO2 in Denmark and Norway but increases emissions in Chile, France, and Sweden. For the global panel, industrial growth leads to mitigate the rate of emissions while clean energy generation raises CO2 emissions in the long period. Investing in clean energy is needed to stimulate the growth of the industrial sector and then reduce the rate of emissions.

Exploring the role of renewable energy and foreign and non-foreign patents on mitigating emissions: evidence for Tunisian economy.

This study investigates the relationships among renewable energies (RE), carbon dioxide (CO2) emissions, foreign direct investment (FDI), foreign and non-foreign patents (FP, NFP), and trade (TR) for the case of Tunisia using time series data spanning the period 1980-2017. The autoregressive distributed lags (ARDL) model approach of Pesaran et al. (J Appl Econ 16:289-326, 2001) and the causality of Granger are employed to explore the dynamic association between the underlined variables. The results from the long-run elasticities show that FDI and TR have negative and statistically significant impacts on RE, while NFP has a positive and statistically significant effect on the consumption of RE. Both FP and CO2 emission variables are insignificant in the long run. In the short run, there are no Granger causal links between RE and patents (FP and NFP), but we have one-way causality running from CO2 emissions to patents (FP and NFP). In the long run, there are bidirectional causalities between RE, NFP, and TR. The Tunisian authorities must impose more stringent environmental standards to attract foreign investments that are more respectful of the environment, and import and export cleaner. It is also necessary to encourage R&D and innovation which appear to be beneficial for the environment.

Investigating the Effects of Meteorological Parameters on COVID-19: Case Study of New Jersey, United States.

This research aims to explore the correlation between meteorological parameters and COVID-19 pandemic in New Jersey, United States. The authors employ extensive correlation analysis including Pearson correlation, Spearman correlation, Kendall's rank correlation and auto regressive distributed lag (ARDL) to check the effects of meteorological parameters on the COVID new cases of New Jersey. In doing so, PM 2.5, air quality index, temperature (°C), humidity (%), health security index, human development index, and population density are considered as crucial meteorological and non-meteorological factors. This research work used the maximum available data of all variables from 1st March to 7th July 2020. Among the weather indicators, temperature (°C) was found to have a negative correlation, while humidity and air quality highlighted a positive correlation with daily new cases of COVID-19 in New Jersey. The empirical findings illustrated that there is a strong positive association of lagged humidity, air quality, PM 2.5, and previous infections with daily new cases. Similarly, the ARDL findings suggest that air quality, humidity and infections have lagged effects with the COVID-19 spread across New Jersey. The empirical conclusions of this research might serve as a key input to mitigate the rapid spread of COVID-19 across the United States.

On the causal links between health indicator, output, combustible renewables and waste consumption, rail transport, and CO2 emissions: the case of Tunisia.

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.

Economic growth, combustible renewables and waste consumption, and CO2 emissions in North Africa.

This paper uses panel cointegration techniques and Granger causality tests to examine the dynamic causal link between per capita real gross domestic product (GDP), combustible renewables and waste (CRW) consumption, and CO2 emissions for a panel of five North African countries during the period 1971-2008. Granger causality test results suggest short- and long-run unidirectional causalities running from CO2 emissions and CRW consumption to real GDP and a short-run unidirectional causality running from CRW to CO2 emissions. The results from panel long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that CO2 emissions and CRW consumption have a positive and statistically significant impact on GDP. Our policy recommendations are that these countries should use more CRW because this increases their output, reduces their energy dependency on fossil energy, and may decrease their CO2 emissions.

The dynamic interaction between combustible renewables and waste consumption and international tourism: the case of Tunisia.

This paper employs the autoregressive distributed lag (ARDL) bounds methodological approach to investigate the relationship between economic growth, combustible renewables and waste consumption, carbon dioxide (CO2) emissions, and international tourism for the case of Tunisia spanning the period 1990-2010. The results from the Fisher statistic of both the Wald test and the Johansen test confirm the presence of a long-run relationship among the variables under investigation. The stability of estimated parameters has been tested, while Granger causality tests recommend a short-run unidirectional causality running from economic growth and combustible renewables and waste consumption to CO2 emissions, a bidirectional causality between economic growth and combustible renewables and waste consumption and unidirectional causality running from economic growth and combustible renewables and waste consumption to international tourism. In the long-run, the error correction terms confirm the presence of bidirectional causality relationships between economic growth, CO2 emissions, combustible renewables and waste consumption, and international tourism. Our long-run estimates show that combustible renewables and waste consumption increases international tourism, and both renewables and waste consumption and international tourism increase CO2 emissions and output. We recommend that (i) Tunisia should use more combustible renewables and waste energy as this eliminates wastes from touristic zones and increases the number of tourist arrivals, leading to economic growth, and (ii) a fraction of this economic growth generated by the increase in combustible renewables and waste consumption should be invested in clean renewable energy production (i.e., solar, wind, geothermal) and energy efficiency projects.