Dumitrescu-Hurlin Panel Causality Research Articles

Financial Development, ICT Use, Renewable Energy Consumption and Foreign Direct Investment Impacts on Environmental Degradation in OIC Countries

This article examines the influence of financial development, ICT use, FDI and renewable energy on environmental degradation in 38 OIC countries using panel data from 2003 to 2021. For data estimation, the authors employed the CD test, slope homogeneity test, CIPS and CADF test, FGLS model, PCSE model and Dumitrescu Hurlin panel causality test. It is found that the variables have cross-sectional dependence, slope heterogeneity, heteroskedasticity, and autocorrelation in a model. The Westerlund test of cointegration also ensures the cointegration among variables in a model while panel unit root tests found the mixed integration order of variables. The FGLS model shows that FD and renewable energy consumption negatively and significantly influence CO2 emissions in OIC countries. The outcomes also show that the use of ICT and FDI inflows in OIC countries are positively related to CO2 emissions. The PCSEs model is used as a robustness estimation technique which also confirms the estimates of the FGLS model. The authors suggested that financial development should be promoted to finance green energy projects, design regulatory policies to prevent polluted technology from the FDI inflows and to prevent the harmful effects of ICT on the environment, the use of green energy resources in ICT use should be promoted.

The Impacts of Financial Market, Trade and Economic Policy Uncertainties on the Import Performance of Advanced Economies

This study aims to examine the long-term and short-term diverse effects of economic policy uncertainty, trade policy uncertainty, and financial market uncertainties on the import performance of advanced economies. It employs the Pooled mean group autoregressive distributed lag (PMG/ARDL) method for the panel of 27 advanced economies using quarterly data from the first quarter of 1996 to the fourth quarter of 2020. The study's results reveal that local and global economic and trade policy uncertainties have significant adverse long-term effects on the import performance of advanced economies. Besides, financial market uncertainties negatively impact advanced economies’ imports in the long run. Nonetheless, the results imply that domestic economic and trade policy uncertainties positively affect imports in the short run. Moreover, the Dumitrescu-Hurlin (D-H) panel causality test indicated that bidirectional causality exists between financial market and trade policy uncertainty indicators and imports. However, unidirectional causality exists between economic policy indicators and imports. The results are consistent across different sensitivity analyses. Based on these findings, we propose policy implications to control economic, trade and financial market uncertainties and thereby alleviating their impact on the import performance of advanced economies.

Exploring the Dynamic Relationships between Agricultural Production and Environmental Pollution: Evidence from a GMM-SYS Model in the Three Seas Initiative (3SI)

The Three Seas Initiative (3SI) is still an under-researched area and is particularly important due to historical circumstances and economic backwardness. A study was carried out to assess the impact of renewable energy and production made by the agricultural sector on CO2 emissions in 3SI countries between 2008 and 2020. The study used panel data analysis based on the two-step system’s generalized method of moments (GMM) and the Dumitrescu–Hurlin panel causality test. The results show that a 1% increase in the value added generated by agriculture increased CO2 emissions in the countries studied by 0.11%. In contrast, a 1% increase in GDP led to a 0.29% increase in CO2 emissions. Conversely, when renewable energy consumption increased by 1%, CO2 emissions fell by 0.25% in the countries studied. One way to reduce CO2 emissions from agricultural production in the short term is to increase the share of renewables, which incidentally is in line with EU action.

Trade policy and environmental sustainability in Africa: An empirical analysis

AbstractThis study investigates whether trade policy instruments—tariffs—strengthen or worsen African environmental sustainability. To drive out the objectives of the study, fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), augmented mean group (AMG), method of moment quantile regression (MMQR) and Dumitrescu–Hurlin panel causality approaches are used to analyse the effect of tariff in addition to other control variables on carbon and ecological footprints as measured of environmental sustainability from 2001 to 2020. The results from the MMQR reveal that tariffs have a significant positive effect on carbon footprints in the 0.15 quantile, while the effect becomes insignificant between 0.25 and 0.5 quantiles. However, at the upper quantiles level (0.75–0.95), the impact of the tariff on carbon footprint is negative and significant, with increasing coefficients. Furthermore, tariffs significantly positively affect lower and middle quantiles' ecological footprints (0.15–0.5). However, the effect turns negative at the upper quantiles (0.9 and 0.95), suggesting that tariff reduces ecological footprint at these levels. In addition, the long‐run estimates (FMOLS, DOLS and AMG) also support the upper quantile estimates of MMQR. A one‐way causality between tariffs, carbon and ecological footprint was found. These findings reveal that tariffs do not create market inefficiency in Africa. This study recommends that tariffs as a trade policy instrument could be used to strengthen Africa's environmental quality. The government can use the tariff revenue to subsidize cleaner production and consumption and move the economy from a traditional energy source to renewable energy.

Impacts of mineral resources, economic growth and energy consumption on environmental sustainability: Novel findings from global south region

This study investigates the dynamic effect of mineral markets, economic growth, urbanization, financial development, non-green and green energy consumption on environmental sustainability. In this context, CS-ARDL, QLARDL, and Dumitrescu Hurlin Panel Causality approaches are used to estimate the panel data collected from seven Global South countries from 1992 to 2019. Results suggested that the mineral market, green energy and green financial development positively impact environmental sustainability at various quantile levels. On the contrary, urbanization and energy consumption have a negative impact on LCC, but these effects are statically insignificant in the short run, while green energy improves environmental quality in the long run. At the same time, financial development and economic growth have significant negative impacts on LCP, in the long run, reporting how the financial development in the world is not concerned about environmental issues. Moreover, the circular economy plays a crucial role in maintaining environmental sustainability by balancing mineral markets, economic growth, financial development, urbanization and energy consumption. Based on the empirical findings, several policy implications are suggested to selected global south countries to improve environmental sustainability through green energy transition and financial development without halting economic growth.

ANALYZING THE RELATIONSHIP BETWEEN HEALTH EXPENDITURE, RENEWABLE ENERGY AND LIFE EXPECTANCY: EVIDENCE FROM ASIAN COUNTRIES

This study investigates the relationship between health expenditures, renewable energy and life expectancy in Asian countries within a model covering the period 2000-2020. GDP data are also included in the model. In the study, after applying cross-sectional dependence test and Cross-sectional Augmented Dickey-Fuller unit root tests, panel cointegration test is employed to show whether there is a long-run mutual relationship between health expenditures and other variables, and then Dumitrescu-Hurlin (2012) panel causality analysis method is used to test the causality between the relevant variables in Asian countries. According to the empirical findings, while causality is found between health expenditures and renewable energy in most of the Asian countries, there is also a high level of causality between life expectancy and health expenditures. Moreover, the cointegration test between health expenditures and other variables confirms that there is a long-run relationship between the variables. It is concluded that policy makers in Asian economies should develop policy frameworks that provide opportunities for renewable energy consumption and support investment in renewable energy projects to promote the use of clean technologies. Thus, an increase in renewable energy consumption can lead to economic prosperity by not only improving quality of life but also increasing productivity.

Dynamic effects of digital governance and government interventions on natural resources management: Fresh findings from Chinese provinces

This study investigates the dynamic effect of digital government on natural resource management in 30 Chinese provinces, considering the government intervention policies, GDP, foreign direct investment, trade openness, and energy prices. In this context, QLARDL, QR, and Dumitrescu Hurlin Panel Causality approach estimate the panel data collected from 2010 to 2020. Results suggested that the digital government positively impacts natural resources management at various quantile levels. On the contrary, government intervention has a limited effect, while Foreign direct investment boosts natural management, especially in the long run. At the same time, energy prices and openness trade significantly negatively impact natural resources management. Based on the empirical findings, several policy implications are suggested for the Chinese provinces.

Determinant on Economic Growth in Developing Country: A Special Case Regarding Turkey and Bangladesh

AbstractThis study delves into the complex interplay between gross domestic product (GDP) and key macroeconomic indicators in the contexts of Turkey and Bangladesh. By examining panel data spanning from 1981 to 2020 sourced from the World Bank, we investigate the causal relationships between GDP growth and various factors including population growth, inflation, literacy rate, natural resource utilization, investment, and foreign direct investment (FDI). Our research aims to address critical questions regarding the economic trajectories of these two emerging economies. Specifically, we seek to understand how different macroeconomic variables influence GDP growth in Bangladesh and Turkey, while also exploring the unique socio-economic landscapes of these nations. Methodologically, we employ the Dumitrescu–Hurlin panel causality test to analyze the causal relationships between GDP growth and the aforementioned macroeconomic indicators. Our findings reveal direct, statistically significant associations between GDP growth and these variables, with population growth emerging as a particularly influential factor. The implications of our study extend beyond empirical observations, offering valuable insights for policymakers and stakeholders seeking to foster sustainable economic development in both Bangladesh and Turkey. By identifying the key drivers of GDP growth and their impact on economic performance, our research contributes to the existing body of literature on economic development in emerging economies. In conclusion, this study sheds light on the intricate dynamics of GDP growth in Turkey and Bangladesh, highlighting the importance of understanding and leveraging macroeconomic indicators to promote inclusive and sustainable economic growth in these nations.

Impact of economic growth and financial development on renewable energy use in selected oil-exporting countries

The aim of this study is to explore the influence of economic growth and financial development on renewable energy consumption. For the purpose of analysis, this investigation uses annual data on renewable energy consumption, economic growth, financial development, consumer price index, domestic investment, and foreign direct investment for 13 major oil-exporting countries, including Algeria, Guinea, Gabon, Iran, Libya, Nigeria, Congo, Republic of Venezuela, Saudi Arabia, Mexico, Malaysia, Sudan, and Russia, during the period 1990-2020. The study employs the Pooled Mean Group (PMG) method and Dumitrescu-Hurlin panel causality test to conduct the empirical analysis. The Hausman test determines the PMG estimator as the most suitable among the Mean Group (MG), Dynamic Fixed Effect (DFE), and PMG estimators. This research shows that economic growth and financial development have a positive and significant long-term impact on renewable energy consumption. This suggests that as the economy grows and financial systems develop, there is a potential for an increase in the use of renewable energy. The Dumitrescu-Hurlin causality test and the panel dynamic ordinary least squares (DOLS) method support these findings. From a policy standpoint, promoting economic growth and financial development could lead to greater use of renewable energy and contribute to sustainable development in oil-exporting countries.

Combining the role of urbanization and renewable energy in sustainable development: testing the EKC hypothesis for Africa.

The pressing necessity to curb greenhouse gas emissions due to climate change has sparked significant scientific interest in comprehending the factors behind CO2 emissions, particularly concerning environmental sustainability challenges. Nonetheless, there exists a notable gap in our understanding of how the process of urbanization interacts with the utilization of renewable energy to impact CO2 emissions. This research endeavor seeks to evaluate the complex interplay among urbanization, renewable energy, and CO2 emissions across 46 African nations spanning from 1990 to 2019. To accomplish this objective, a variety of econometric methodologies are employed, including Driscoll-Kraay standard errors, IV-GMM, and method of moments quantile regression (MMQR) panel estimations to address issues like cross-sectional dependencies, endogeneity, heterogeneity, and panel Granger causality examination. The empirical results suggest that urbanization leads to an increase in CO2 emissions, whereas the consumption of renewable energy plays a role in enhancing environmental quality by reducing CO2 emissions. A significant outcome of the study is the revelation that a combination of urbanization and renewable energy leads to a decrease in carbon emissions. Moreover, the Environmental Kuznets Curve (EKC) hypothesis is validated. Lastly, through the Dumitrescu-Hurlin panel causality test, it is uncovered that urbanization and renewable energy consumption exhibit a bidirectional relationship with CO2 emissions. To reduce dependence on fossil fuels and curb CO2 emissions, policymakers should promote renewable energy usage in urban areas.

Nexus between climate change, agricultural output, fertilizer use, agriculture soil emissions: Novel implications in the context of environmental management

In evaluating the influence of greenhouse gases (GHGs) on climate change, the effectiveness of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) is intricately tied to their atmospheric turnover rates, which play a crucial role in their heat-trapping capacity. Understanding the dynamics of how these gases cycle through the atmosphere is essential for assessing their respective contributions to the greenhouse effect and, consequently, their impact on global warming and climate change. The prime objective of this research is to examine the role of climatic change, agriculture output, and fertilizer use on the agriculture soil's greenhouse gas emissions. In doing so, the present study has focused on the temperature of land, fertilizer consumption, crop and livestock production, and energy used in agriculture soils on the pollution level of agricultural soils. The study further delineates the intricate interdependencies between climate change factors and GHG emissions using novel econometric methodologies, specifically the PMG-ARDL, SC-ARDL, and Dumitrescu Hurlin Panel Causality frameworks. In doing so, we use a large panel dataset spanning 1990 to 2020. The estimations show that climate change, as measured by variations in terrestrial temperature, has a discernible and positive impact on GHG emissions over the short and long term. Energy consumption and livestock production positively correlate with GHG emissions, with the former having a more pronounced effect. The implications of fertilizer usage and overall crop yield become noticeably significant in the long term. It emphasizes the importance of using a diachronic perspective when assessing GHG emissions in the agricultural sector. It is also worth noting that agricultural land use appears to negatively impact GHG emissions, emphasizing the importance of implementing sustainable land management practices to mitigate adverse environmental consequences. The study also explores the causality between climate change, agricultural practices, and GHG emissions, revealing a bidirectional association between climatic change and soil emissions. Additionally, unidirectional causation is observed from fertilizer consumption and crop production to emissions, underscoring the importance of adopting sustainable agricultural practices to reduce emissions. The findings offer valuable insights for governments and researchers to create sustainability-related strategies for dealing with climate change issues, safeguarding natural resources, and ensuring a sustainable future for agriculture.

Can International Business Perspective Measure Sustainable Development of BRICS Countries? A Panel Data Analysis

The level of international business is highly dependent on the numerous macroeconomic and sustainable development factors that play their respective roles in defining a developing nation's economic progress. While examining the long-term growth of an economy, the consistency of the performance of the various elements in terms of their sustainability is a crucial matter to investigate. Moreover, it is known that the sustainable development of an economy is strongly associated with environmental impacts. Finally, the focus on new development patterns must be the highest concern for emerging economies. Considering this, the current study speculates on the relationship between foreign direct investment and the interaction effect of carbon emissions and poverty with control variables such as per capita income and education in BRICS economies. It concentrates on panel data ranging from 1993 to 2019 to explore the association among the said variables. It identifies the unique and definite macroeconomic parameters that are crucial for encouraging foreign direct investment in different countries. Applying the Panel Auto Regressive Distributed Lag Model, the study finds a positive interaction effect between carbon emissions and poverty that focuses on improving foreign direct investment in the long run. In the short run, an increase in per capita income always proves that BRICS will demonstrate less dependence on FDI net flows. The study also concentrates on the unit root measurement of the data by applying Panel Unit Root Test. Finally, to check the direction of causality, Pairwise Dumitrescu Hurlin Panel Causality Tests have been performed. The most recent update from these countries demonstrates that the strategy for achieving future sustainable economic growth is clear and swift. Hence, it emphasises the requirement of separate and exclusive policy-making to promote long-term sustainable economic growth in BRICS.

Synthesizing the role of biomass energy consumption and human development in achieving environmental sustainability

Promoting sustainable energy use is crucial to achieving environmental sustainability. However, there is limited documentation on how human development moderates the effect of energy consumption on environmental sustainability. Therefore, this study aims to uncover the impact of biomass energy consumption and human development on the ecological footprint in 31 African countries from 1996 to 2018. To achieve this, we employ Driscoll-Kraay, instrumental variables, and panel quantile regression techniques to address heteroscedasticity, endogeneity, and conditional heterogeneity. The result shows that biomass energy consumption increases ecological footprint, while human development reduces ecological footprint. The results also show that human development reduces the adverse effect of biomass energy consumption on environmental sustainability. Moreover, the pairwise Dumitrescu-Hurlin panel causality results prove the two-way causal association between biomass energy consumption and ecological footprint. The feedback effect between human development and the ecological footprint is also supported. To improve environmental sustainability, policymakers should promote sustainable biomass energy consumption through awareness and education campaigns.

How do information and communication technology, human capital and renewable energy affect CO2 emission; New insights from BRI countries

If nations want to attain sustainable development with the exponential growth of information and communication technology (ICT) around the world, they must understand the connection between ICT and carbon emissions. Therefore, this study has used panel data from 64 ‘‘Belt and Road Initiative economies between 2000 and 2021 while finding the impact of ICT, renewable energy consumption (REC), human capital (HC) and economic growth (EG) on CO2 emissions. This study employs the Augmented Mean Group (AMG) estimator, Mean Group (MG) estimator and the Dumitrescu-Hurlin panel causality. The findings indicate that the use of ICT, HC and the REC are inversely related to CO2 emissions, whereas EG is positively associated to CO2 emissions and hence poses a danger to environmental sustainability. In addition, the interaction term of EG with ICT, REC and HC has negative impact on CO2 emissions in BRI economies. Intriguingly, the results reveal that ICT and CO2 emissions has inverted U-shape relationship in BRI economies. Furthermore, the causality results show that ICT, REC, and human capital are all cause and effect linkages that affect CO2 emissions in both directions. In order to reduce energy utilization and boost economic growth, the findings stress the importance of implementing cutting-edge ICT and REC in the industrial sector.

How does technological innovation affect the ecological footprint? Evidence from E-7 countries in the background of the SDGs

Although technological innovation plays a critical role in promoting sustainable development and environmental sustainability, there are few studies in the existing literature that address this relationship. This study aimed to investigate the relationship between technological innovation (TI), renewable energy consumption (REC), natural resource rent (NRR) and ecological footprint (EF) of E-7 countries (i.e. Brazil, China, India, Indonesia, Mexico, Russia and Turkiye) from 1992 to 2018 in order to ensure environmental sustainability in the context of the Sustainable Development Goals (SDGs). Analysis was performed using the ARDL estimator, robustness test and Dumitrescu-Hurlin panel causality (DHC) test. Long-term empirical estimates from the PMG-ARDL technique have shown that a 1 % increase in TI and REC reduces EF by 0.064 % and 0.234 %, respectively, i.e. increases environmental sustainability. At this point, it is possible to say that TI and REC contribute to the achievement of SDG-7 and 13 in E-7 countries while NRR and real income (GDP) were found to impede the achievement of SDG-7 and 13 in E-7 countries through an increase in EF. The results were confirmed using robustness techniques. In the DHC test results, while there is a unidirectional causality from TI to EF, from EF to NRR and trade openness, a bidirectional causality was found between GDP and EF. This study suggests that policymakers should focus on introducing environmentally friendly equipment to reduce environmental degradation, increase the share of RECs and focus on sustainable development within the framework of the SDGs.

How Do Financial Development and Industrial Structure Affect Green Total Factor Energy Efficiency: Evidence from China

Improving energy efficiency is vital for addressing climate change and reducing carbon emissions in emerging economies. Financial development (FD) is crucial for economic growth, and its environmental impact and the adjustment of the industrial structure (IND) is a crucial lever in China’s economic transition period. This study explored the relationship between FD, IND, and China’s green total factor productivity (GTFEE) from 2000 to 2020 using the super-efficiency SBM-undesirable model, which estimates China’s GTFEE. The ARDL results suggest that FD and IND enhance GTFEE in the long term, with FD promoting GTFEE by facilitating industrial structure adjustments. The Dumitrescu–Hurlin panel causality tests supported this finding. The QRPD panel quantile regression and heterogeneity analysis revealed significant heterogeneity in the effects. With increasing GTFEE, FD exerts a restraining effect, gradually weakening and transitioning into a promoting effect, while the IND consistently plays a promoting role.

Energy Consumption and Economic Growth Nexus in Africa Countries: A Simultaneous Equations Model Approach

By adopting the Cobb-Douglas production function, this study examined the relationship between energy consumption, GDP, capital stock, and labour in 22 African countries from 1990 to 2018. To achieve this goal, the simultaneous equations were analysed after utilizing the Generalized Method of Moments (GMM)/Dynamic panel data estimation approaches. To determine the most fitted model between the fixed and random model, the study employed the Hausman model and its approved the random model as the best fitted model. According to the empirical results, energy consumption has a strong positive influence on GDP. This suggests that as the economy expands, so will energy consumption. The coefficients of labour and capital are significant, though labour implies negative effects. Also, GDP has a firm positive influence on energy consumption. This suggests that as the economy expands, so will energy consumption. Capital has a positive coefficient. This means that the countries are capital-intensive. The Labour coefficient is negative and statistically significant, indicating that capital is more energy intensive than labour-intensive generates the majority of GDP. This also implies that capital replaced labour in those countries. Further, the Dumitrescu Hurlin Panel Causality Tests revealed a bidirectional relationship between GDP and energy consumption. Thus, there is a bidirectional relationship between energy consumption and GDP across the entire continent. Energy policy formulations are likely to be the best long-term economic growth strategy in African countries.

The Symmetric and Asymmetric Impacts of Energy Consumption and Economic Growth on Environmental Sustainability

Climate change has emerged as a global challenge because of its threat to sustainable development goals. Fossil fuels and economic growth are responsible for pollution and, thus, for climate change. In this context, this study explored the environmental Kuznets curve hypothesis for the case of 17 MENA countries over the period of 1990–2020. It investigated the symmetric and asymmetric impact of energy consumption and economic growth on CO2 emissions by controlling for population density, trade openness, and FDI inflows using panel linear and nonlinear ARDL models. The robustness of the results was checked using the fully modified OLS and dynamic OLS methods. Moreover, the Dumitrescu–Hurlin panel causality test was employed to determine the directions of causality between the variables. Overall, the empirical results of both panel linear and nonlinear ARDL models validate the environmental Kuznets curve hypothesis for the selected sample of MENA countries. Economic growth leads to environmental degradation only in the long run, whereas a rise in energy consumption leads to an increase in pollution in both the short and long run. These results are confirmed by the fully modified OLS and dynamic OLS methods. The findings of the Dumitrescu–Hurlin panel causality test also indicate the existence of bidirectional causality between energy consumption and CO2 emissions and between economic growth and CO2 emissions. Therefore, policy makers in the MENA region should invest in clean technologies and accelerate the transition to renewable energies such solar energy, wind power, and hydropower to align with sustainable development goals.

Asymmetric linkages among fintech, oil prices, governance, and growth in Southeast Asian economies

Fintech's disruptive potential in Southeast Asia can revolutionize financial inclusion and accelerate economic growth, warranting a comprehensive analysis of its interplay with oil prices, governance, and overall economic development. Against this backdrop, this study analyze the quantile-dependent (asymmetric) influence of oil prices, cumulative financial technology index, and institutional quality on economic growth for selected Southeast Asian countries from 1996 to 2021. Method of Moments Quantile Regression (MMQR) is used to analyse the asymmetric relationship, while the Dumitrescu-Hurlin Panel Causality test applies to the intrinsic casualty. The study's outcomes exposed the positive (negative) influence of Fintech and governance (oil prices); however, there marginal impact substantially varies at lower a higher growth quantiles. Labor headcount and capital stocks are among the main contributor of economic growth, specifically at higher growth quantiles (countries). Bi-directional causality has been confirmed through Dumitrescu-Hurlin Panel Causality test between Fintech, oil prices and governance with economic growth. Therefore, Generalized Method of Moment and Augmented Mean Group is further applied for robustness. After controlling reverse causality and endogeneity issues, the prior outcomes are validated. These findings offer valuable outcomes.

Are Human Development and Innovativeness Levels Good Predictors of the Competitiveness of Nations? A Panel Data Approach

Nations must adapt to the changing and developing world to sustain and develop their competitiveness. Human development and innovation are the two key concepts to increase the competitiveness of a nation. This study aims to examine the relationship between the Human Development Index (HDI), Global Innovation Index (GII), and Global Competitiveness Index (GCI) across different income groups from 2010 to 2019. The main objective is to identify potential variations in these relationships based on the income level of the countries involved. Panel data analyses using Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are conducted to examine the relationships. Additionally, Pairwise Dumitrescu Hurlin Panel Causality Tests are conducted to examine the causal relationships between variables. The results show that HDI has a significant positive effect on GCI in each income group. Improving human development such as raising living standards and providing equal education opportunities for every member of society can contribute to a country’s competitiveness. Moreover, it is found that the effect of GII on GCI varies by income group. Specifically, the results indicate that the effect of GII on GCI is not supported for upper-middle-income countries. Therefore, while developing strategies to increase competitiveness through innovation, it is important to consider the income group of a nation. The findings of this study may assist policymakers, researchers, academics, and politicians to enhance their perspectives and formulate strategic and effective recommendations for action.