Determinants of CO2 emissions and economic progress: A case from a developing economy

The impact of freedom of expression and belief on CO2 emissions: An examination of the group of seven

Growing concerns about the level of CO2 emissions have made identifying the key drivers of the emission issue a critical agenda item. These developments have turned identifying drivers of CO2 emissions into a popular research area. Researchers have been attempting to determine the root causes of CO2 emissions for quite some time. While many economic factors have been associated with the emission levels, researchers' interest in undiscovered factors has brought political factors to the forefront. Although some institutional/political factors have been linked to CO2 emissions in the relevant literature, the specific impact of freedom of expression and belief (FEB) has yet to be examined. Notably, as democracies' provision of economic freedoms motivates production and consumption, exerting pressure on the environment, FEB can balance it. This study is a pioneering attempt to seek answers to this question. By assigning a specific role to FEB, the research seeks to determine the key factors influencing CO2 emissions in the Group of Seven (G7) between 2006 and 2022. Results suggest that FEB might be crucial in lowering CO2 emissions, whereas economic expansion and energy use tend to increase CO2 emissions. However, the impact of trade openness has yet to be found to be significant. Thus, securing and enhancing FEB could lead to significant environmental gains in G7 countries and globally.

Investigating the simultaneous impact of infrastructure and geographical factors on international trade: Evidence from asian economies

Infrastructure and geography are the most important components of international trade. They provide trade-oriented amenities for the trade volume among trading partners. Thus, this study assesses the simultaneous impact of infrastructure and geographic factors on trade in Asian economies from 2004 to 2020. This work contributes to the existing literature by exploring the significance of infrastructure and geography in international trade. Furthermore, this research seeks to determine whether these factors have complementary or simultaneous effects. To examine these aspects, the augmented gravity model and cross-sectional autoregressive distributed lags are used in the current model. Then, the multilateral resistance terms are corrected. Results reveal that infrastructure has a significant and positive impact on trade. More precisely, transport infrastructure, communication infrastructure, financial infrastructure, and border-transport efficiency are productive influencers for trade over a certain period. Notably, the simultaneous impacts of infrastructure and geographic factors can lead to the deterioration of trade volume. The policy implications and future research direction of this study suggest that economies should improve infrastructure and geographic factors through gross domestic product.

Clean energy production index and CO2 emissions in OECD countries

This study aimed to analyze the relationship between the energy transition index recently developed by Lau et al. (2023) and CO2 emissions in OECD countries. The topic is relevant, as the energy transition is a sustainable path to reduce CO2 emissions in countries. The CS-ARDL approach is used to estimate the short-run and long-run coefficients. Additionally, the Dumitrescu and Hurlin (2012) test is employed to determine the causal relationship between the variables. It was found that a 1 % increase in clean energy production reduces CO2 emissions by 0.33 % and 0.23 % in the short and long run, respectively. Furthermore, a bidirectional causal relationship exists between CO2 emissions and the energy transition indicator. This suggests that policies implemented by OECD countries to reduce carbon emissions will inevitably entail the adoption of cleaner energy sources.

The impact of agriculture production and renewable energy consumption on CO2 emissions in developing countries: the role of governance

Environmental pollution has aggravated the climate change issues posing unusual challenges to the survival and growth of humanity, including extreme weather, loss of species, and sustainability of the ecosystem in developing countries. Unlike previous studies, this paper adds new dimension to the literature by incorporating corruption into agriculture production-environment nexus. This study adds new dimension to the literature by examining corruption, agriculture, and renewable energy on CO2 emissions. The study therefore examines the effects of governance (corruption) and agriculture production on CO2 emissions in 20 countries in Africa from 1990 to 2019. The study employed recent panel econometric approach which accounts for cross-sectional dependence in the variables. The findings of the fixed effect model and panel dynamic ordinary least squares (PDOLS) show that forest and renewable energy consumption decrease CO2 emissions. However, corruption, agriculture production, export, and urbanization escalate CO2 emissions in African countries covered in the paper. Moreover, the Dumitrescu-Hurlin Granger causality indicates a bidirectional causality between agriculture production and CO2 emissions, renewable energy use, agricultural output, and forest. Also, unidirectional Granger causality runs from corruption to forest and agriculture production. On these premises, consented efforts by governments should be made to support good institutions in order to promote good governance to avert pervasive consequences of corruption on the environment.

Assessing the role of green economy on sustainable development in developing countries

Purpose

Over the last few years, the green economy (GE) notion has been realized as a key tool for achieving sustainable development (SD) in both developing and developed nations. Therefore, the current study tries to investigate the role of GE in achieving SD in developing countries. Through empirically examining the relationship between the GE and three different dependent variables which are GDP per capita, total unemployment rate, and poverty level, using cross-sectional data for 60 developing countries in 2018.

Design/methodology/approach

Applying generalized least square (GLS) approach. The four dimensions of the Global Green Economy Index (GGEI) are the key independent variables that measure the accomplishment of nations in aspects of the global green economy.

Findings

The empirical results showed the existence of a positive statistically significant relationship between the GE and GDP per capita and the level of total unemployment, while there is a negative statistically significant relationship between the GE and the poverty rate in developing countries.

Implication policy

This study recommends that both the private and public sectors continue to endorse and adopt GE in the future for SD, job creation, and poverty alleviation.The original value of the study: It is the first research for developing countries that explores the relationship between GE and SD using three indicators of SD using a GLS approach according to our information. Also, this study categorized the dataset of the developing countries based on their income level for addressing the heteroskedasticity problem.