Unraveling the interplay between globalization, financial development, economic growth, greenhouse gases, human capital, and renewable energy uptake in Indonesia: multiple econometric approaches

Addressing global environmental concerns requires the widespread adoption of renewable energy sources. More research is needed to examine the relationships between renewable energy (RE) and globalization, economic growth, and environmental quality in Indonesia. Therefore, we examined how renewable energy usage in Indonesia has changed due to the dynamic effects of globalization, financial development, and environmental quality. Time-series data were analyzed using an autoregressive distributed lag (ARDL) model to test for cointegration and long-run/short-run dynamics between 1990 and 2020. In addition to ARDL bounds testing, we used the Johansen and Engle-Granger cointegration methods for confirmation. Globalization, financial progress, human capital, greenhouse gas emissions, and economic expansion have favorable long- and short-term effects on renewable energy sources. Globalization has enabled Indonesia to expand trade, FDI, and financial investment. It has also increased energy-efficient technology use due to environmental policies. The computed results are robust enough to substitute estimators, such as dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). We recommend the implementation of policies that support financial and environmental development by utilizing renewable resources and increasing investments in renewable energy ventures.

Democracy, green energy, trade, and environmental progress in South Asia: Advanced quantile regression perspective

Unquestionably, the industrial revolution of the twenty-first century contributes to global warming. Excessive amounts of carbon emissions into the atmosphere are responsible for global warming. Therefore, this research aims to assess the impact of GDP, green energy consumption, population, trade openness, and democracy on CO2 emissions in four selected South Asian countries from 1990 to 2019. This research also attempts to evaluate the EKC hypothesis in terms of economic growth (GDP2). The unit root of panel data and cointegration tests are executed in this study as a prelude to the regression analysis. Quantile regression for panel data, which (Powell, 2016) devised to deal with the fixed effect problem, is used in this study, and (Powell, 2016) empirical findings are the main focus. The estimated coefficient of GDP is positively significant, demonstrating that economic activity increases the burning of fossil fuels and upsurges atmospheric CO2 emissions. After attaining economic development, the reversed U-shaped EKC theory is valid for four selected South Asian countries. Economic development encourages these countries to use green technology, which helps mitigate CO2 emissions. The research, however, reveals that green energy is to blame for CO2 emissions. Burning biomass releases carbon dioxide that negatively impacts the quality of the environment. The study confirms that human activities are the leading contributor to environmental deterioration. Population growth has a worsening effect on the environment. The association between population and CO2 emissions is positively significant. The estimated coefficient of trade openness is positive, which increases CO2 emissions significantly. The estimated coefficient of democracy is quite negative. Therefore, this study suggests prioritizing democracy to reduce CO2 emissions. Citizens who live in democracies are better informed, more organized, and able to protest, all of which contribute to increased government responsiveness to environmental preservation. The results of the Wald test support the differential effects at various quantiles. The Dumitrescu-Hurlin (2012) panel causality tests are also used in this analysis to check causality between variables. Based on the findings, this research makes many policy suggestions for lowering carbon emissions.

Evaluating a pathway for environmental sustainability: the role of energy mix and research and development in European countries

Within the European Union (EU), the majority of countries are considered developed, and the level of economic activity is rising. As a result, carbon dioxide emissions have increased. If the European Union wants to maintain long-term, sustainable growth, it must act quickly to find solutions to pollution. Population, wealth, renewable energy, nuclear energy, and research and development (R&D) are all factored into the STIRPAT model to determine their respective environmental impacts. Slope heterogeneity and cross-sectional dependence are explored in panel data for 30 European nations from 1990 to 2021 using a newly developed Cross Section Autoregressive Distributed Lag (CS-ARDL) method. The study found that population growth and the continued use of fossil fuels are major causes of environmental degradation. Alternately, employing renewable and raising incomes both have the potential to significantly cut pollution over the long run. Likewise, investments in R&D assist lessen the damage done to the environment. The nuclear energy coefficients, however, are insignificant. However, fossil fuels have negative effects on the ecosystem. If the EU wishes to stop the degradation of the environment, the analysis demonstrates that renewable energy is the best way to do it. The time has come for the EU to make a gradual transition away from fossil fuels and toward more environmentally friendly alternatives. Economic growth should be matched by decreased CO₂ emissions, and increasing investment in R&D can serve as a catalyst for environmental sustainability. The results were reviewed using three different estimators: the augmented mean group (AMG), the mean group (MG), and the common correlated effects mean group (CCEMG). Important policy recommendations for a sustainable European environment are also suggested by the research.

Does tourism have an impact on carbon emissions in Asia? An application of fresh panel methodology

This research investigates the effects of tourism, GDP per capita, renewable energy, energy intensity, urbanization, and population on the environment in 40 Asian countries. Data from 1995 to 2019 are used in this analysis. Slope heterogeneity (SH), cross-sectional dependency (CSD), and the combination of level and first differenced stationary are all addressed using a new cross-sectionally autoregressive distributed lag (CS-ARDL) model in this work. Using Westerlund's cointegration method, these variables can be connected throughout time. To validate the findings, both augmented mean groups (AMG) and Common correlated effect mean groups (CCEMG) were utilized. The study results indicate that tourism helps slow the degradation of the natural environment. CO2 emissions increase as a result of variables such as population growth, energy use, and economic development. Only tourism and renewable energy can help cut CO2 emissions. As a consequence, CS-ARDL results are supported by results from AMG and CCEMG tests. Policymakers may be encouraged countries to adopt renewable energy and foster the expansion of the sustainable tourism industry.

Evaluating the Influences of Health Expenditure, Energy Consumption, and Environmental Pollution on Life Expectancy in Asia

This study examines the effects of health expenditure, energy consumption, CO₂ emissions, population size, and income on health outcomes in 46 Asian nations between 1997 and 2019. Cross-sectional dependence (CSD) and slope heterogeneity (SH) tests are utilized due to the close linkages between Asian nations as a result of commerce, tourism, religion, and international agreements. The research uses unit root and cointegration tests of the second generation after validating CSD and SH issues. Due to the results of the CSD and SH tests, it is clear that conventional methods of estimation are inappropriate, so a new panel method, the inter autoregressive distributive lag (CS-ARDL) model, is used instead. In addition to CS-ARDL, the study's results were checked with a common correlated effects mean group (CCEMG) method and an augmented mean group (AMG) method. According to the CS-ARDL study, higher rates of energy use and healthcare spending lead to better health outcomes for Asian countries over the long run. CO₂ emissions are shown to be harmful to human health, according to the study. The influence of a population's size on health outcomes is shown to be negative in the CS-ARDL and CCEMG, but favorable in the AMG. Only the AMG coefficient is significant. In most instances, the results of the AMG and CCEMG corroborate the results of the CS-ARDL. Among all the factors influencing life expectancy in Asian countries, healthcare spending is the most influential. Hence, to improve health outcomes, Asian countries need to take the required actions to boost health spending, energy consumption, and long-term economic growth. To achieve the best possible health outcomes, Asian countries should also reduce their CO₂ emissions.

Impact of FDI, industrialization, and education on the environment in Argentina: ARDL approach

Purpose

This study employed the stochastic implications of regression on population, affluence, and technology (STIRPAT) methodology between 1972 and 2021. The main goal of this research is to look at how FDI, population growth, industrialization, and education affect the environment in Argentina.

Methodology

The F-bound test and Johansen cointegration test are employed in this research to determine if there is a co-integration association among the variables. Additionally, the Autoregressive Distributed Lag (ARDL) method is used to examine the short-run and long-run elasticity of the independent variable. This study also incorporated a pairwise Granger causality test to determine the direction of causation between the variables. After that, the study applied several diagnostic and stability tests.

Findings

The empirical evidence demonstrates the presence of a co-integration association among CO₂ emissions, population, industrialization, and education. The findings indicate that population growth and industrialization harm the environment in Argentina in the long run. In addition, a significant inverse association was obtained between CO₂ emissions and educational expenditures in the short run.

Practical implications

The existence of STIRPAT suggests that Argentina is capable of achieving sustained economic growth. To achieve the goal, countries must implement appropriate government policies and ensure their implementation. This paper argues strongly for more investment in education, renewable energy, sustainable industrialization, and research and development, all of which are essential for a green economy.

Investigating the EKC hypothesis with renewable energy, nuclear energy, and R&D for EU: fresh panel evidence

The European Union (EU) is extremely concerned about the environmental harm caused by rising CO₂ emissions and other factors. The EU has to uncover factors that decrease pollution before it's too late to achieve long-term sustainable growth. The paper applies the environmental Kuznets curve (EKC) hypothesis to examine the dynamic connection between GDP, energy use, energy intensity, research and development (R&D), and CO₂ emissions. Data from 34 countries in the EU, spanning from 1990 to 2021, were applied. EU countries are very interdependent on one another due to tourism, trade, education, religion, and culture. Therefore, tests for cross-sectional dependency (CSD) and slope heterogeneity (SH) are used in this research. After establishing the presence of CSD and SH issues, the study employed second-generation unit root and cointegration tests. In response to these concerns, the study implemented a novel cross-section autoregressive distributed-lag model (CS-ARDL) method. There exists a U-shaped quadratic link between environmental pollution and wealth. That rules out the existence of the EKC hypothesis in the EU. This means that when income grows, pollution will drop up to a certain point, and then it will begin to climb again. Long-term pollution is reduced by the use of renewable energy and R&D. On the other hand, energy intensity increases CO₂ emissions. The article also applied the CCEMG, AMG, and MG estimators to test the robustness. The CS-ARDL methodology demonstrates that increasing national income, nuclear energy, and investment in R&D alone will not be sufficient to fulfill environmental needs and that the use of alternative renewable energy sources is the greatest approach to mitigate environmental deterioration in the EU. The AMG, MG, and CCEMG estimators all agree that switching to renewable energy is the most effective strategy to lower emissions. This research offers crucial guidelines for advancing environmental policy and realizing sustainable development. Discussion, policy recommendations, and future research based on the findings are presented.

The pattern of international trade between Bangladesh and USA: Heckscher–Ohlin and Rybczynski analysis

Purpose

Research based on Bangladesh–US trade data examines the Heckscher–Ohlin model and the Rybczynski hypothesis in this study.

Design/methodology/approach

Ordinary least square (OLS) techniques are used in this study, which relies on data from the NBER International Trade and Geography Data and the UN Comtrade Database for the years 2018 and 2008.

Findings

The research shows that trade between the United States and Bangladesh follows Heckscher–Ohlin and Rybcyzinski's trade predictions. According to the study, since labor is in plentiful supply in Bangladesh, Bangladesh's labor-based sectors have a higher US labor-to-capital import shares than US capital-based industries. As Bangladesh has not changed significantly from a labor-based country since 2008, it retains the same pattern even though the share of US unskilled labor-based sectors imported from Bangladesh decreased in 2018.

Originality/value

The findings of this study have a wide range of implications for both trade theory and policy debates between Bangladesh and the United States.

Investigating the subsistence of Environmental Kuznets Curve in the midst of economic development, population, and energy consumption in Bangladesh: imminent of ARDL model

The main purpose of this study is to analyze the existence of an environmental Kuznets curve (EKC) considering the midst of energy consumption, population and economic development. The main objective is to investigate the impact of energy consumption, population and economic development on CO₂ emissions. This study has taken data from 1971 to 2020 to see the existence of an EKC in the country of Bangladesh. Besides population growth, energy consumption and economic development are also taken into consideration. An autoregressive distributed lag (ARDL) model was used to scrutinize cointegration based on selected variables and their respective I (0) and I (1) values. This study has confirmed the long-term existence of the EKC in the environment. The environmental Kuznets curve was also tested using economic performance coefficients on emissions. In the long run, EKC explains why per capita carbon output decreases with population expansion but turns down after a certain threshold level is achieved because of this inverted U-shaped pattern. For decades, increased energy consumption has been linked to worsening environmental conditions, according to this study. According to the findings, there are a wide variety of approaches to advancing Bangladesh's economy and improving its environmental quality. In the long run, the population has no positive impact on CO₂ secretion. The use of fossil fuels such as gas and oil can have a detrimental environmental impact. As a result, if we want to conserve the environment, we need to use renewable energy sources like solar and biodiesel instead of traditional, nonrenewable fuels.

Assessment of food safety knowledge, attitudes and practices of fish farmers and restaurants food handlers in Bangladesh

The study was conducted to assess the present status of knowledge, attitudes and practices (KAP) concerning the food safety and hygiene issues among fish farmers and food handlers in Noakhali, Bangladesh. Data were collected from 100 respondents (50 fish farmers and 50 food handlers) through face to face interviews. All the respondents agreed that training on hygiene practices was necessary and they were interested to attend training in their spare time. Food handlers (88%) agreed that raw foods must be kept separate from prepared foods and 68% of them believed that improper preservation of foods is harmful to health. About 52% of farmers used a face mask when spreading insecticides, fertilizers, and chemicals. Food handlers were wearing protective clothing (32%) and masks (12%) when touching and distributing unwrapped foods, however no handlers used a cap. A significant strong correlation coefficient (rs) was found between knowledge with attitudes, knowledge with practices and attitudes with practices of 0.73-0.99 among the three domains for fish farmers and food handlers. The correlation among the three levels was satisfactory, however, some food safety concepts and practices regarding hygiene were still insufficient. Therefore, an effective and appropriate training program on food safety and hygiene should be launched in a holistic approach for all fish farmers and food handlers to increase awareness and ensure safe food for consumers with a view to reducing the possibility of disease outbreak.