The impact of economic growth, energy consumption, trade openness, and financial development on carbon emissions: empirical evidence from Malaysia

The governance factor: Mitigating carbon emissions through FDI and financial development in emerging Asian economies

This study investigates the influence of foreign direct investment (FDI), financial development (FD), and governance on carbon emissions in 15 emerging Asian economies (EAEs) from 2000 to 2021. It aims to assess how successful these nations have been in upholding ecological sustainability while promoting themselves as alternative manufacturing destinations to China and fostering domestic manufacturing through significant financial development. It creates a composite governance quality (GQ) measure and three subdimensions-EcoGov, InstGov, and PolGov-to assess its precise role in influencing the FDI-carbon dioxide (CO2) and FD-CO2 nexuses. Using fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) panel cointegration techniques, this study yielded findings revealing that FDI and FD significantly enhance carbon emissions. The overall GQ significantly moderates the FD-CO2 nexus but fails to moderate FDI's detrimental environmental influence. More specifically, EcoGov significantly moderates FDI's and FD's influence on carbon emissions, whereas InstGov significantly enhances their influence on emissions. In contrast, PolGov is only found to moderate FD's impact on environmental quality since the Government frequently endorses liberal environmental regulations to facilitate FDI-led growth. The findings from this study are robust and carry distinct policy ramifications.

Nexuses between carbon emissions, trade openness, transport services, globalization index, and growth in China: targeting the sustainable development goals

Since the end of the twentieth century, the world has observed a considerable upsurge in carbon emissions as several countries have surfaced as industrial centers and production monsters worldwide. The present study contributes to the existing literature examining the effects of carbon-based emissions, industrial value added, trade openness, transport services, railway lines, and globalization index on per capita GDP growth in China. The study covers a period of 40 years, from 1982 to 2021, introducing the impact of railway transport on GDP growth in contemporary environmental empirics. A vector error correction model (VECM) was applied to achieve the study's envisaged objectives. The findings of this study reveal that carbon emissions are responsible for the reduction of per capita GDP growth in China. On the contrary, industrial value added, transport services, railway lines, and globalization index positively support the per capita GDP growth-dependent variable. The study proposes that pragmatic policies are needed to control pollution resulting from carbon emissions. The eventual effect of maintaining greenhouse gases is expected to assist in achieving sustainable growth of per capita GDP leading to the accomplishment of sustainable development goals in the economy.

Towards a greener future: examining carbon emission dynamics in Asia amid gross domestic product, energy consumption, and trade openness

The purpose of this study is to examine the impact of gross domestic product, energy consumption, and trade openness on carbon emission in Asia. Among the 48 countries in Asia, 42 were included in the analysis, spanning a period of 20 years. Given that Asia is the predominant contributor, accounting for 53% of global emissions as of 2019, a comprehensive examination at both continental and individual country levels becomes imperative. Such an approach aligns with local, regional, and global development agendas, contributing directly and indirectly to climate change mitigation. The analytical techniques employed in this study encompassed panel regression and multiple linear regression, illuminating the specific contributions of each country to the study variables and their impact on carbon emissions. The findings suggest that gross domestic product (13 out of 42 countries), energy consumption (21 out of 42 countries), and trade openness (eight out of 42 countries) have a highly significant impact (p < 0.01) on carbon emissions in Asia. Energy consumption plays a vital role in increasing carbon emissions in Asia, driven by rising populations, urbanisation, and oil and gas production. Policymakers can take several actions such as adopting a carbon pricing system, using sustainable transportation, renewable energy development, and international cooperation within Asia to reach the goal of being carbon neutral by 2050.

House dust mite allergy in Malaysia: review of research gaps in the current scenario and the way forward

The prevalence of house dust mite (HDM) allergy, especially in Asian countries with rapid urbanization, has been increasing. House dust mites thrive in places with relatively high humidity. With the combination of climate change, naturally high humidity, and urbanization, tropical countries like Malaysia are becoming a hotspot for HDM allergy fast. With a previously reported sensitization rate of between 60 and 80%, it is a worrying trend for Malaysia. However, due to incomplete and out-of-date data, as seen by the limited study coverage in the past, these numbers do not paint a complete picture of the true HDM allergy scene in Malaysia. This review briefly discusses the HDM fauna, the HDM sensitization rate, the common diagnosis and therapeutic tools for HDM allergy in Malaysia, and makes suggestions for possible improvements in the future. This review also highlights the need of more comprehensive population-based prevalence studies to be done in Malaysia, encompassing the three main HDMs-Dermatophagoides pteronyssinus, Dermatophagoides farinae, and Blomia tropicalis-as the lack of up-to-date studies failed to give a clearer picture on the current scenario of HDM allergy in Malaysia. Future studies will be beneficial to the nation in preparing a better blueprint for the management and treatment of HDM allergy.

Nexus between inflation, income inequality, and economic growth in Ethiopia

The relationship between inflation, income inequality, and economic growth is a subject of intense debate among economic researchers and policymakers. This study aims to analyze this relationship in Ethiopia using advanced statistical techniques such as VEC (vector error correction) model with Granger causality, and Johansen's cointegrated. The study covers the period from 1980 to 2022 and includes pre and post-estimation diagnosis tests to ensure the accuracy of the model. The results indicate the presence of a long-run relationship among inflation, income inequality, and economic growth, as confirmed by Johansen's cointegrated test. Additionally, the vector error correction model shows a strong long-run relationship between economic growth, income inequality, and inflation. In the short run, there is a significant association between income inequality and economic growth, as well as between inflation and economic growth. The Granger causality test reveals a bidirectional causality between economic growth and income inequality and between economic growth and inflation. However, there is a unidirectional causality from inflation to income inequality. Based on these findings, it is suggested that the government should implement various strategies and policies, including redistribution policies, social safety nets, promoting inclusive economic growth, coordinating effective monetary and fiscal policies, implementing progressive taxation, and reforming the labor market.

Can environmentally friendly technology help China to achieve a carbon neutrality target by 2060? An asymmetrical based study in China

Climate change-related environmental challenges are prompting an increasing number of countries to set carbon-neutral targets. Since 2007, China has pursued numerous initiatives to attain carbon neutrality by 2060, including increasing the percentage of non-fossil energy, developing zero-emission and low-emission technologies, and taking actions that reduce CO2 emissions or boost carbon sinks. As a result, utilizing quarterly data from 2008/Q1 to 2021/Q4, and applying the nonlinear autoregressive distributed lag (NARDL) approach, this study evaluates the effectiveness of the measures taken by China to improve the ecological situation. The results of the study show that the measures enacted to reduce CO2 emissions did not accomplish their ultimate purpose. Specifically: (i) high-speed railways and new energy vehicles do not improve the environment in the long run; (ii) investments and patents in the energy sector, as well as low-carbon sources, will degrade the environment; (iii) only investments in the treatment of environmental pollution will improve the ecological situation. Various policy implications are suggested based on the empirical results in order to attain environmental sustainability.

The temporal and spatial pattern evolution of provincial industrial carbon intensity under the carbon neutral target: evidence from China

Industry is a core area to achieve the carbon neutrality target for most developing countries including China. Hence, it is of great practical significance to study the spatio-temporal characteristics of China's industrial carbon intensity and its evolution. The exploratory spatial data analysis methods were adopted to conduct global and local spatial correlation analysis in this paper. The result shows that (1) the industrial carbon emission intensity decreases year by year, with high industrial carbon emission intensity in the West and low in the East. (2) There is a correlation in the spatial distribution of industrial carbon intensity, with the Moran index experiencing the stage of descending first and then ascending. (3) The local spatial clustering of industrial carbon intensity is obvious. (4) Half of the provinces have experienced a leap, with the majority located in the western part of China. Based on these findings, it is concluded that industrial emission reduction policy synergy between provinces is particularly important, such as low-carbon industrial production policy and green industry development policy.

Estimation performance comparison of machine learning approaches and time series econometric models: evidence from the effect of sector-based energy consumption on CO2 emissions in the USA

By considering the existence of two separate analysis families and the usage of different data frequencies, this study aims to examine the effect of method choice, data frequency, and sector-based energy consumption on carbon dioxide (CO₂) emissions by performing machine learning (ML) algorithms and time series econometric (TS) models simultaneously. In this situation, the study examines the United States (USA), considers sector-based energy consumption indicators as explanatory variables, uses monthly and yearly data between January 1973 and December 2021, estimates CO₂ emissions, and compares the estimation performance of the models. The empirical findings reveal that (i) the ML algorithms outperform the TS models based on R² and goodness of fit criteria; (ii) the estimation performance of the models increases with the high-frequency (i.e., monthly) data; (iii) the ML algorithms perform much better in case of high-frequency usage; (iv) some thresholds identify the effects of the sector-based energy consumption indicators on the CO₂ emissions; (v) electric power and transportation sectors are the most important sectors in the estimation of the CO₂ emissions for monthly and yearly data, respectively. Hence, the study provides to help the understanding role of method choice, data frequency, and sector-based energy consumption for the estimation of CO₂ emissions. Based on the results, this study proposes that US policymakers should consider the ML algorithms, use higher-frequency data, and include sector-based energy consumption indicators to have a better estimation of CO₂ emissions.

The impacts of resource abundance and export diversity on financial development in the South Asian economic bloc

One of the most essential aspects of a nation's economic progress that determines the citizens' lifestyles and general wellbeing is the level of financial development (FD). Thus, the current study examines the influence of natural resources as key variable for financial development in South Asian economic bloc while accounting for the roles of export diversity, inflation, and economic expansion. The dataset utilized for the South Asian bloc stretches between 1990 and 2020. Second-generation panel econometric approaches that are robust to slope heterogeneity and cross-sectional dependence were employed in the study. The relevance and applicability of the second-generation techniques was reinforced by some preliminary assessments while the cointegration checks confirm the existence of long-run interconnectedness between financial development and the regressors. The elaborate empirical analysis that was conducted shows that export diversity and natural resources abundance exert diametric impacts on financial development of the South Asian bloc. While the former positively influences financial development, the latter's impact was significantly negative thereby signaling the resource curse tendency of the South Asian countries. Furthermore, the observed roles of economic progress and inflation on the bloc's financial development were positive and significant. Therefore, authorities in the South Asian countries need to maintain greater regulatory oversight of the resources market to ensure that rent seeking and resource abuse are avoided at all costs towards building a more prudent fiscal mechanism within a stable financial system. Authorities also need to ensure that resources are fully efficiently utilized by channeling them to production activities that create value addition to resources to harness greater exports for improved FD levels. Other policy measures were also highlighted for the South Asian stakeholders in the main text.

How does financial development reduce carbon emissions: evidence from BRI countries

Low-carbon development in BRI countries is crucial to the global response to climate change. As an important factor in promoting economic growth, financial development has a great impact on BRI countries' carbon emissions. This paper applies the panel data of 43 BRI countries for the period 1997-2019 to investigate the influence of financial development on carbon emissions. The two-tier stochastic Frontier model is employed to decompose the restraining and rebounding effects of financial development. The results show that financial development has both restraining and rebounding effects on carbon emissions, and the rebounding effect is less than the restraining effect, resulting in a positive net effect. The average restraining effect is 0.165, and the average rebounding effect is 0.018, causing the net effect of financial development on carbon emissions to have an average value of 0.147. The restraining effect decreases year by year, implying there is a blocking point to release the restraining effect. Moreover, technological progress strengthens the restraining effect, while the increase in energy consumption weakens the restraining effect. The findings indicate that excavating the restraining effect of financial development, promoting technological progress, and reducing fossil energy consumption is crucial to promoting the low-carbon development of BRI countries.

Investigation of the effect of human capital on environmental pollution: empirical evidence from Turkey

Reducing environmental pollution is a highly important issue that must be resolved globally. Improving human capital (HC) can significantly contribute to lowering environmental pollution. Using the Fourier ADL (FADL) method, this study examines the long-term effect of HC on carbon emissions (CO₂ emissions) and ecological footprint (EF) in Turkey from 1980 to 2018. In addition, the study examined the long-term effects of economic growth (GDP), financial development (FD), and globalization (KOF) on CO₂ emissions and EF. According to empirical results, HC has a negative effect on both CO₂ emissions and EF. Furthermore, the findings indicate that GDP and FD have a positive effect on CO₂ emissions and EF, whereas KOF has no statistically significant effect on CO₂ emissions and negative EF. According to the FFFF-TY causality test results, there is bidirectional causality between FD and EF and a unidirectional causality from HC to EF and from EF to KOF. This study underlines the importance of human capital in improving environmental quality in Turkey. In this context, the results of this study will assist policy makers in the development of precise policies to enhance human capital in order to improve environmental quality.

The impact of renewable and non-renewable energy consumption on carbon emission intensity in China: Fresh evidence from novel dynamic ARDL simulations

Given the dire state of global warming, it is critical to investigate the elements that influence carbon emissions intensity and to precisely monitor progress in carbon emissions intensity growth in order to meet the aim of lowering CO2 emissions. This research explores the association among renewable energy and non-renewable energy consumption, the urban population, research and development expenditure, technological innovation, and carbon emissions intensity in China using annual time series data over the period 1990 to 2019. The Dynamic ARDL simulation technique was utilized to investigate the long-run and short-run correlations between renewable and non-renewable energy consumption and CEI. The results suggest that there is strong evidence of a long-run correlation between the variables. The findings indicate that in the long-run, renewable energy and non-renewable energy consumption, and research and development expenditure have a positive influence on CEI by 0.27%, 0.75%, and 0.21%, whereas the urban population has a negative influence by 2.31%, respectively. However, the urban population and technological innovation have positively affected the short-run CEI by 12.17% and 0.23%, respectively. Policies should focus on continuous investment in renewable energy sources, clean energy innovation, improving energy efficiency, forest restoration, and carbon neutrality initiatives to lessen the environmental extreme pressure associated with CO2 emissions.

Investigating possibility of achieving sustainable development goals through renewable energy, technological innovation, and entrepreneur: a study of global best practice policies

This study is anchored on the global best practice policies for achieving sustainable goals for Malaysia. Malaysia is among the countries that made commitment at 2015 United Nations Climate Change Conference to reduce its carbon emissions by 2030. This is expected to contribute to the country's sustainable development. Malaysian quarterly data of 1992Q1-2019Q4 with relevant policy-based instruments (renewable energy policy, technological innovations, financial development, and entrepreneur activities) are adopted in our study for explicit and clear insight on the subject. Different scientific and analytical methods are equally applied in this study, but the focus and emphasis are laid on the findings from linear (dynamic ordinary least square, DOLS) and non-linear autoregressive distributed lag (NARDL) and Granger causality. Findings from both NARDL and DOLS confirmed the positive shocks of renewable energy policy, technological innovations, financial development, and entrepreneur activities are mitigating carbon emissions. Also, inverted U shape of EKC hypothesis is found for Malaysia. Findings from Granger causality support the findings from both estimates by establishing both feedback and unidirectional causal nexus among the instruments. From the finding myms, policy-based instruments are mitigating carbon emissions in Malaysia; thus, it will be a very good idea to frame policies around these instruments.

Does Globalization Cause Greenhouse Gas Emissions in Pakistan? A Promise to Enlighten the Value of Environmental Quality

Global environmental issues such as environmental degradation, climate change, and global warming have posed a threat to the global economy, including Pakistan. The primary source of these problems is greenhouse gas emissions. These emissions are the result of human activity. The objective of the study was to investigate the symmetric and asymmetric relationship between globalization and greenhouse gas emissions in Pakistan. The ARDL modern econometric techniques of the time series model were used. Firstly, the stationarity test favors the use of the ARDL model in this study. The BDS test result confirmed that the ARDL model has a non-linearity issue. As a result, the ARDL approach was used to test both the symmetric and asymmetric effect. The results of the asymmetric ARDL model are more robust and reliable than those of the symmetric ARDL model. According to the results of the symmetric ARDL, economic, social, and political globalization have a positive relationship with greenhouse gas emissions in both the short and long run. Furthermore, the long-run results of the asymmetric ARDL model show that positive and negative shocks of economic and political globalization have positive and negative shock effects on greenhouse gas emissions. In the long run, however, the positive shock of social globalization has a negative relationship with greenhouse gas emissions. According to the results of impulse response functions, economic globalization has a significantly more relationship with greenhouse gas emissions than social and political globalization. A policy should be developed that allows only the positive effects of globalization while prohibiting the negative effects of globalization.

Dynamic linkages between non-renewable energy, renewable energy and economic growth through nonlinear ARDL approach: evidence from Malaysia

The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the nonlinear autoregressive distributive lag (NARDL) model in Malaysia for the period of 1980-2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as the short run in Malaysia. The findings also show that in the long and short run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth, whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia, RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption.

Is Female a More Pro-Environmental Gender? Evidence from China

The purpose of this study is to determine whether there are gender differences in people’s pro-environmental psychology and behaviors in China. An online survey was conducted with the snowball sampling technique, and a sample of 532 Chinese respondents was obtained for the research. This study finds that gender does affect green psychology and behaviors, with females reporting a higher level of environmentalism in China. Specifically, females are more concerned with environmental problems, more supportive of plastic ban policies, more positive towards reducing plastics (reduce), and have stronger intention to bring a reusable bag for shopping (reuse and recycle). Moreover, females use fewer disposable toiletries when checking in a hotel and require less disposable tableware when ordering takeout. This study contributes to the current literature by identifying the relationship between gender and environmentalism in China. Implications for anti-plastic policy design and environmental management are also presented.

The cyclical impact of green and sustainable technology research on carbon dioxide emissions in BRICS economies

This paper explored the asymmetrical relationships between green and sustainable technology research and environmental sustainability among the BRICS states from 1990 to 2018. The data was analyzed by second- and third-generation economic techniques such as slope heterogeneity and cross-section independence test, unit root test, structural break unit root test, panel cointegration with structural breaks cointegration tests, cross-section autoregressive distributed lags technique, augmented mean group, and Dumitrescu-Hurlin panel causality test. First, the results validated a long-run cointegration among variables. Second, the results showed that renewable energy consumption and positive shocks to green and sustainable technology research are proper to mitigate carbon dioxide emissions (short- and long-run). Third, gross domestic product, foreign direct investment, exports, and negative shocks to green and sustainable technology research increase carbon dioxide emissions. Fourth, the nexus between green and sustainable technology research and carbon dioxide emissions was counter-cyclical during economic expansion and contraction periods. Fifth, the impact of positive shocks to green and sustainable technology research on carbon dioxide emissions was more than the impact of negative shocks to green and sustainable technology research on carbon dioxide emissions.

Does energy consumption reinforce environmental pollution? Evidence from emerging Asian economies

Steadily improving per capita income level, energy consumption, and delivery of financial services in South and Southeast Asian countries has remained a subject of discussion among policymakers. Because these endeavors have not only elevated their growth trajectory but also widened the scope for carbon emissions, especially in the preceding two decades. In order to confirm this argument, therefore, in the present study, we intended to examine their dynamic impacts on carbon emissions. In this pursuit, by using the second-generation unit-root test, cointegration test, and panel regression procedures, we investigated the moderating impact of energy solutions on the association between per capita income and CO₂ emissions and financial development and CO₂ emissions from 1976 to 2015. The computed results revealed that the energy's interaction with the linear per capita income significantly escalated carbon emissions in the long run. However, the impact of energy's interaction with the squared per capita income on carbon emissions is found insignificant but positive in the long run. On the other hand, the interaction of energy with financial development provided a negative but insignificant coefficient. Based on the outcomes, we can ascertain that, at the lower level of income, energy consumption leads to environmental pollution, whereas at the higher level of income, its harmful effect on carbon emissions becomes weak in the given regions. By taking a cue from the computed results, we proposed a policy framework that might help these regions to navigate the energy-led environmental challenges in the coming years.

Moderating effects of personal innovativeness and driving experience on factors influencing adoption of BEVs in Malaysia: An integrated SEM-BSEM approach

Electric cars are relatively in the early stage of acceptance in Malaysia, the purpose of the current research was to determine the factors affecting the adoption of battery electric vehicles in Kuala Lumpur, Malaysia. This research utilized a quantitative method to gather and analyze the data and proposed a novel theoretical framework to explain the acceptance of battery electric vehicles. 500 surveys were distributed and 322 were gathered. Respondents of the study were University lecturers, postgraduate students, and employees in private companies. The results of SEM analysis indicated that the developed model provides a good fit for constructs used for this research. The result showed that social influence, facilitating conditions, environmental concern, and perceived enjoyment have positive effects on the adoption of BEVs. However, respondents indicated anxiety about the battery range. In conclusion, this study has contributed additional variables such as range anxiety and driving experience to the electric vehicle's acceptance literature. The findings are significant to electric car producers and policy makers who have environmental concerns to understand consumer prospective in this field.