Second-generation Panel Unit Root Tests Research Articles

The role of fintech, mineral resource abundance, green energy and financial inclusion on ecological footprint in E7 countries: New insight from panel nonlinear ARDL cointegration approach

This main objective of the study is to examine the impact of green energy, financial inclusion, fintech, and mineral resource abundance on the ecological footprints (EFP) of the top seven emerging economies. The research mainly explores the role of mineral resource abundance and fintech advancements in promoting environmental sustainability, while also analyzing the benefits of green energy in reducing ecological footprints in E7 countries. This research employed the panel Nonlinear ARDL approach to gain a deeper understanding of positive and negative variations of the data of E7 countries from 2000 to 2020.The study employed the robust and second-generation panel unit root test to enhance the understanding of the estimated model. There are many benefits to using these most robust second-generation techniques; such as they possess an ability to recognize patterns and correlations in panel data. In addition, these second-generation tests provide enhanced estimators in comparison to first-generation methods. To ensure utmost precision and to ensure reliability and validity of the data analysis, the authors have employed process underwent comprehensive testing with both CIPS and CADF. Furthermore, the HASIO test is used to evaluate uniformity in data. The findings of the study reveal that green energy has a significant and complex relationship with the ecological footprint, indicating that investments in green technologies can have immediate beneficial effects on environmental quality, albeit with varying impacts over time. Financial technology emerges as a pivotal factor with both positive and negative shocks displaying a substantial influence on the ecological footprint, suggesting that technological advancements in the financial sector can lead to sustainable economic practices that are crucial for environmental health. The results of the study imply that strategic investments in green energy and innovative financial technologies are essential for achieving the SDGS, particularly SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). The results of the study further imply that these investments not only reduce the ecological footprint but also promote sustainable economic growth in emerging economies, demonstrating the interconnectedness of economic advancement and environmental stewardship.

An empirical investigation of the impact of energy consumption, globalization and natural resources on ecological footprint and economic growth, evidence from China, Japan, South Korea and China Taiwan

Natural resources are regarded as important indicators that make great contributions to reducing environmental pollution and promoting growth in today's era of globalization. Thus, a more rigorous assessment of the complexity of determining growth and ecological footprint is critical. This study examines the dynamic linkages between globalization, natural resources, renewable and non-renewable energy use, ecological footprint and growth in Taiwan, Japan, China, and South Korea from 1975 to 2020. In terms of the certainty of cross-sectional dependence of panel variable data, this study uses second-generation panel unit root, cointegration, long-term elasticity, and two-way causality estimation tests to obtain reliable and valid results. The findings explore the fact that environmental degradation is substantially mitigated by the using of renewable energy sources, while other underlying factors, such as non-renewable energy sources, natural resource rent (NRR), economic growth, and globalization, exacerbate environmental pollution. In addition, the use of renewable and non-renewable energy, NRRs and globalization drive economic progress. Globalization and ecological footprint have a bilateral causal association. The research analysis supports the feedback hypothesis based on a bidirectional causal relationship between renewable energy use and ecological footprint. Based on the empirical findings of the current study, various policy endorsements are proposed to scare and control environmental damage without hampering growth in specific East Asian economies.

Investigating the relationship between macroeconomic indicators, renewables and pollution across diverse regions in the globalization era

This paper delves into an econometric analysis to uncover the differences between Nordic European Countries - NEC (Norway, Denmark, Finland, Sweden) and South-East European Countries - SEEC (Greece, Bulgaria, Romania, Hungary). The focus is on exploring the interplay among electricity generation from Renewable Energy Sources (RES), CO2 emissions, urban population and GDP per capita in these two European regions. The study employs cross-sectional dependence, first and second-generation panel unit root tests, Pedroni panel and Westerlund panel cointegration tests, ARDL, Dumitrescu-Hurlin causality test to establish the relation among variables. The findings reveal that in both regions, CO2 emissions are significantly influenced by GDP per capita, urbanization and RES generation. Furthermore, urbanization plays an important role. When examining causality in SEEC, three bidirectional relationships are observed: urbanization and CO2, urbanization and GDP, urbanization and generation from RES, and two unidirectional causalities: CO2 and GDP, generation from RES and CO2. In contrast, for the NEC, there are two bidirectional causalities: urbanization and CO2, urbanization and generation from RES, and two unidirectional causalities: GDP and CO2, generation from RES and CO2. These results highlight the nuanced and varied nature of environmental and economic dynamics across various European regions.

Revisiting the debt–growth nexus in sub-Saharan Africa: fresh evidence from panel nonlinear ARDL approach

PurposeWhile some countries have used debt to drive economic growth, the asymmetric effect on sub-Saharan African (SSA) countries has received little attention in the empirical literature. This paper therefore examines the asymmetric effect of external debts on economic growth.Design/methodology/approachThe panel nonlinear autoregressive distributed lag (NARDL) approach was employed in the study for 29 sub-Saharan African countries from 1990 to 2021. The cross-sectional dependence test was used to determine the presence of cross-sectional dependence, while the second-generation panel unit root tests was used to examine the unit-root properties.FindingsThe empirical results show that external debt has an asymmetric effect on economic growth in both the short and long run. In the long run, a positive shock in external debts of 1% triggers an upturn in economic growth by 0.216% while a negative shock triggers 0.354% decline in economic growth. This implies that the negative shock of external debts has a much stronger impact on economic growth than the positive shock. In the short run, a positive shock in external debts by 1% triggers a decline in economic growth by 0.641%, while a negative shock of 1% triggers a fall in economic growth of 0.170%.Originality/valueThe paper used the NARDL model to examine the asymmetric impact of external debt on the economic growth of SSA countries, which has not been extensively studied. It is recommended that governments in the selected countries in sub-Saharan Africa should drive economic growth by promoting domestic revenue mobilization since external debts impede economic growth.

Revisiting the Classical Theory of Investment: An Empirical Assessment from the European Union

In alignment with classical investment theory, this study explores the enduring relationships and causal linkages among total private investment, profit rate, unit labour costs, and demand growth within the European Union throughout the period spanning from 1961 to 2019. The empirical approach adopted involves the use of advanced econometric techniques designed to address cross-sectional dependence and slope heterogeneity. As a first stage, we examine stationarity and cointegration by employing second-generation panel unit root and cointegration tests. Subsequently, we estimate long-run equations through estimators intended to control for cross-sectional dependence and slope heterogeneity. As a further step, we use the Dumitrescu-Hurlin procedure to examine potential bidirectional causality between the variables and detect whether there exists endogeneity in the data. Finally, we apply the dynamic common correlated effects estimator mean group with instrumental variables to control for the potential presence of endogeneity. The outcomes of the analysis underscore a positive association between private investment and the profit rate, unit labour costs, and demand growth, thus providing robust empirical support for the classical theory of investment.

Revisiting long-run dynamics between financial inclusion and economic growth in developing nations: evidence from CS-ARDL approach

PurposeThis study aims to analyze the long-run dynamic relationship between financial inclusion and economic growth for developing nations.Design/methodology/approachThis study develops a comprehensive financial inclusion index based on the UNDP methodology for 53 developing nations. The authors use second-generation unit root tests, cointegration techniques and an advanced dynamic common correlated effects estimator model called cross-sectional augmented autoregressive distributed lags (CS-ARDL) to examine long-run dynamics among variables.FindingsThe tests confirm the presence of slope-heterogeneity and cross-sectional dependency. The second-generation panel unit root tests show the chosen variables are stationary at first difference. The bootstrap Westerlund cointegration result shows the variables are cointegrated in the long run. The CS-ARDL estimates conclude that financial inclusion positively enhances gross domestic product per capita in selected developing countries. The robustness check through augmented mean group estimation validates the findings.Originality/valueThe study makes three important contributions: first, it constructs a comprehensive financial inclusion index using 10 variables for a panel of 53 developing nations; second, the potential cross-section dependence and slope heterogeneity of panel data have been accounted for by applying the second-generation unit root tests; third, the study uses the dynamic common correlated effects estimator model (CS-ARDL) to examine long-run dynamics among variables.

Could Globalisation and Renewable Energy Contribute to a Decarbonised Economy in the European Union?

This study investigates the impact of globalisation, renewable energy consumption, and economic growth on CO2 emissions in 26 European Union (EU) countries, in the period 1990–2020. Second-generation panel unit root tests are applied, the Westerlund cointegration test is used, and a panel of fully modified least squares (FMOLS) and dynamic ordinary least squares (DOLS) techniques are employed to estimate the long-term relationship between variables. The causality relationship among the considered variables is identified using the heterogeneous Dumitrescu–Hurlin causality test. It was found that globalisation and renewable energy consumption contributed to the carbon emissions’ mitigation, while economic growth induced their increase. The results are robust when control variables (i.e., financial development, foreign direct investment, and urbanisation) are added to the model. Foreign direct investment and urbanisation are contributors to carbon emissions’ increase, whereas financial development induces their decrease. The effect of the considered variables on carbon emissions is differentiated by economic development and level of institutional quality. Unidirectional causality relationships were identified from globalisation to carbon emissions and from carbon emissions to foreign direct investment and bidirectional relationships were found between economic growth, renewable energy consumption, financial development, and carbon emissions. The policy implications of the results are also discussed.

Eco-innovations, green growth, and environmental taxes in EU countries: a panel quantile regression approach.

The purpose of this study is to examine how environmental taxation, green growth, and eco-innovations contribute to a more sustainable environment. This study examines the influence of green growth, environmental taxes, and eco-innovations on carbon dioxide emissions in 26 environmentally responsive European Union (EU) countries from 2000 to 2020. The analysis was conducted using the second-generation panel unit root test, cross-sectional dependence, panel cointegration, and panel quantile regression. Theoretical and empirical research has demonstrated that both linear and non-linear green growth strategies are effective in reducing CO2 emissions. There is evidence that CO2 emissions can be reduced through the implementation of environmental taxes, eco-innovations, the use of renewable energy sources, and enhanced energy efficiency. In contrast, economic growth has a positive effect on carbon emissions, and its square term verifies the environmental Kuznets curve. Nevertheless, our research findings provide empirical support for the hypothesis that sustainable development contributes to the maintenance of stringent environmental standards. For the sampled countries, the study's findings have significant policy implications. These results encourage governments to prioritize green growth over traditional economic growth and to encourage eco-innovations in renewable energy technology.

Impact of taxes on the 2030 agenda for sustainable development: Evidence from Organization for Economic Co-operation and Development (OECD) countries

Multiple ecological and socioeconomic problems have occurred worldwide, raising the awareness of sustainability. This study aims to examine the impact of taxes on Sustainable Development Goals (SDGs) in the context of Organization for Economic Co-operation and Development (OECD) countries. This research used effective average tax (EAT), tax on personal income (TPI), tax on corporate profits (TCP), and tax on goods and services (TGS) as the variables of taxes, and employed secondary data from 38 OECD countries covering 2000–2021. The study also used Breusch-Pagan Lagrange Multiplier (LM), Pesaran Scaled LM, Bias-Corrected Scaled LM, and Pesaran Cross-sectional dependence (CSD) tests to analyze the existence of cross-sectional dependency. Then, we established the stationarity of variables through second-generation panel unit root tests (Cross-sectional Augmented Dickey-Fuller (CADF) and Cross-sectional Im, Pesaran, and Shin (CIPS)), and confirmed the long-run cointegration of the variables by using second-generation panel cointegration test (Westerlund cointegration test). The results showed that EAT, TPI, TCP, and TGS are positively associated with SDGs. However, the change in TPI has a smaller effect on SDGs than the change in EAT or TCP or TGS. The result of panel causality indicated that EAT, TPI, and TGS have a unidirectional causal relationship with SDGs. The study also found that TCP has a bi-directional causal relationship with SDGs. Moreover, the finding indicated that the OECD countries need to focus on tax policies to achieve the 2030 Agenda for Sustainable Development. This study is based on the theory of optimal taxation (TOT), which suggests that tax systems should be designed to maximize social welfare. Finally, we suggests the importance of taking a comprehensive approach for the managers and policy-makers when analyzing the impact of taxes on SDGs.

Ecological response to industrialisation drivers in Africa

More than ever, ecological conditions are fast deteriorating due to rising greenhouse gas emissions. These emissions are significantly propelled into the atmosphere by growth in specific human activities that also advance industrialisation. These activities will increase considerably in developing countries since industrial growth can lead to rapid economic modernisation. Consequently, this study examined the long-term ecological implications of these industrialisation drivers, including manufacturing activities, resource wealth, urban development, income growth, globalisation, and human capital development. This study conducted a panel analysis of 32 African countries between 1991 and 2019, and empirical inferences were derived through a battery of advance estimation techniques. They include second-generation panel unit root and cointegration tests, generalised estimating equation, generalised least squares mixed effect model, dynamic common correlated effect, Driscoll-Kraay, and the panel corrected standard error methods. The study demonstrated that an increase in manufacturing value-added, natural resources wealth, income growth, globalisation, and human capital diminishes ecological quality in Africa. However, urbanisation was environmentally-enhancing. The study proposed relevant policy measures to mitigate environmental pollution from industrialisation drivers.

Does economic growth stimulate energy consumption? New evidence from national and regional levels in China

A detailed investigation of the nexus between economic growth and energy use is imperative for formulating sustainable development policies. In this study, we examine panel cointegration and causality relations among economic growth, energy use, capital stock, and labor in 30 Chinese provinces between 2000–2019. We conduct a comprehensive empirical analysis based on panel modeling and a neoclassical production function. The findings of the second-generation panel unit root and co-integration tests reveal that these variables have long-term co-integration linkages. We then perform a panel cointegration estimation using the fully modified ordinary least squares technique and find that total energy consumption, electricity consumption, capital stock, and labor significantly influence economic growth at the national and regional levels in China. Moreover, the outcomes of the Dumitrescu-Hurlin causality test indicate the existence of a two-way causal nexus between economic output and total energy consumption at the national level, but only a causal link from GDP to total energy use in the eastern and central regions. Conversely, a causality from total energy use to economic output is identified in the western region. Finally, we provide policy implications for the sustainable development of both energy and the economy at the national and regional levels.

The impact of geopolitical risk, governance, technological innovations, energy use, and foreign direct investment on CO2 emissions in the BRICS region.

Geopolitical risk (GPR) and other social indicators have raised many somber environmental-related issues among government environmentalists, and policy analysts. To further elucidate whether or not these indicators influence the environmental quality, this study investigates the impact of GPR, corruption, and governance on environmental degradation proxies by carbon emissions (CO2) in BRICS(Brazil, Russia, India, China, and South Africa) countries, namely Brazil, Russia, India, China, and South Africa, using data over the period 1990 to 2018. The cross-sectional autoregressive distributed lag (CS-ARDL), fully modified ordinary least square (FMOLS), and dynamic ordinary least square (DOLS) methods are usedfor empirical analysis. First and second-generation panel unit root tests report a mixed order of integration. The empirical findings show that government effectiveness, regulatory quality, the rule of law, foreign direct investment (FDI), and innovation have a negative effect on CO2 emissions. In contrast, geopolitical risk, corruption, political stability, and energy consumption have a positive effect on CO2 emissions. Based on the empirical outcomes, the present research invites the concentration of central authorities and policymakers of these economies toward redesigning more sophisticated strategies regarding these potential variables to protect the environment.

Is stock market development a spur to poverty reduction? Empirical evidence from selected sub-Saharan African countries

ABSTRACT In this study, the relationship between stock market development and poverty reduction is examined in sub-Saharan African countries during the period 1993–2019. Three proxies of stock market development were used, namely stock market capitalization, stock market traded value and stock market turnover ratio, thereby leading to three separate model specifications. A battery of panel data estimation techniques was used in the study to examine the existence of cross-sectional dependence. Furthermore, the second-generation panel unit root test and panel cointegration test were used alongside the first-generation tests to examine this linkage. Contrary to some of the previous studies, the results of the panel least squares, fully modified ordinary least squares and dynamic ordinary least squares show that stock market development has no significant impact on poverty reduction in sub-Saharan countries during the period under study. These results apply irrespective of the proxy used to measure the level of stock market development. The results were also corroborated by the heterogenous non-Granger causality test, in which a prima facie causal flow was found from poverty reduction to stock market development when stock market turnover ratio was used as a proxy. Policy implications are discussed.

Nexus of natural resources, urbanization and economic recovery in Asia: The moderating role of innovation

Despite their population, Asian countries have failed to provide full economic recovery, and what recovery has occurred may be short-lived if they do not protect the environment. Asian nations' economic recovery from the Asian Financial crisis (1997–1998) is examined in this study, with a focus on the consequences of globalization, economic growth, financial development, natural resource utilization and innovation. Econometric approaches that can handle cross-sectionally dependent panel datasets are used to determine the environmental implications of these variables over the period 1980 to 2016. This work uses the second-generation panel unit root and long-run cointegration tests for robust and reliable results. There is a mixed order of integration for the variables, which are cointegrated. The long-term regressions show increased economic recovery due to natural resource use, while technological advancement reduces economic recovery. The results suggest that financial development and eco-innovation enhance economic recovery, whereas urbanization accelerates environmental deterioration by increasing the ecological footprint. This study recommends that Asian countries become more financially incorporated, fund environmental initiatives, support environmental modernization and accelerate economic recovery rates through their energy production and consumption.

Nexus between oil price and stock market development in Southeast Asian economy: Evidence from linear and nonlinear assessment

The literature has extensively investigated stock market development and its critical role. Another variety of studies focuses on determining the factors responsible for stock market development. The motivation of the study is to investigate the impact of oil price movement on stock market development in the Southeast Asian economy for the period 1990-2020.study applied several economical tools such as the second-generation panel unit root test widely known as CADF and CIPS, panel cointegration test with error correction term, panel ARDL and nonlinear ARDL. Study findings have revealed that oil price prices are negatively associated with stock market development both long-run and short-run. The nonlinear assessment established a long-run asymmetric association between oil price and stock market development. Refers to asymmetric elasticity, the study documented a negative and statistically significant linkage between asymmetric shocks of oil price and the measures of stock market development.

The Impact of CO2 Emissions and Energy Consumption on Economic Growth: A Panel Data Analysis

This study aims to examine the dynamic connection among economic growth, CO2 emissions, energy consumption, and foreign direct investments (FDIs). The panel section considers the period of 2000–2020 for 25 EU Member States excluding Malta and Croatia. The annual data are retrieved from the World Bank and Eurostat databases. The empirical analysis used estimation procedures such as first- and second-generation panel unit root tests (CIPS) and panel ARDL based on the three estimators PMG, MG, and DFE. The Hausman test indicated that the PMG estimator is the most efficient. The PMG and DFE estimators suggested that there exist only short-run causalities from CO2 emissions, energy consumption, and FDIs to GDP growth rate, while the MG estimator proved the existence of both short-run and long-run causalities. Three hypotheses on the positive correlation between the three regressors and GDP growth rate were in general confirmed. The identified causalities may represent recommendations for policymakers to stimulate the renewable energy sector to improve sustainable development.

Exploring the role of nuclear energy in the energy transition: A comparative perspective of the effects of coal, oil, natural gas, renewable energy, and nuclear power on economic growth and carbon emissions

Nuclear power has received renewed attention during the energy transition in recent years. This study is aimed to explore whether nuclear energy can promote economic growth without increasing carbon emissions. In order to have a more comprehensive understanding of the relationship between nuclear energy, economic growth, and carbon emissions, this study also discusses the impact of coal, oil, natural gas, and renewable energy on economic growth and carbon emissions. The second-generation panel unit root test, panel cointegration test, panel fully modified ordinary least squares, and Heterogeneous Dumitrescu and Hurlin causality test were used to estimate the long-term elasticity and causality among variables. Results based on panel data from 24 countries with nuclear energy from 2001 to 2020 show that both nuclear energy and renewable energy can curb carbon emissions. Especially in Canada, Finland, Russia, Slovenia, South Korea, and The United Kingdom, nuclear energy reduces carbon emissions more significantly than renewable energy. Meanwhile, there is a positive relationship between increased nuclear energy, increased renewable energy, and economic growth, which means that nuclear energy and renewable energy could increase economic growth as well. There is a positive relationship between increased oil, increased natural gas, and economic growth, while there is a negative relationship between the increase in coal and economic growth. Meanwhile, there is a positive relationship between increased oil, increased coal, and increased carbon emissions, while the positive relationship between increased natural gas and increased carbon emissions is not significant. Thus, in the 22 countries with nuclear power, increased coal consumption does not drive economic growth but increases carbon emissions. Increased oil consumption increases economic growth, but it increases carbon emissions. Increased natural gas consumption boosts economic growth but adds little to carbon emissions. In the authors' view, nuclear power and renewable energy are all options for these nuclear-power countries to pursue economic growth without increasing carbon emissions. Moreover, nuclear power has a better effect on curbing carbon emissions in some countries than renewable energy. Therefore, under the premise of safety, nuclear power should be seriously considered and re-developed.

The asymmetric effect of agriculturalization toward climate neutrality targets

Agricultural activities immensely contribute to greenhouse gas emissions (GHGs). This study investigates the heterogeneous effect of agricultural production (AGRIP) on three major GHGs emissions, i.e., carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) under the Environmental Kuznets Curve (EKC) framework using a balanced panel data of 90 countries from the period 1991 to 2019. Second-generation panel unit root and cointegration tests are conducted to account for cross-sectional dependence. The findings suggest that there is a long run equilibrium among target variables. Evidence from panel quantile regression suggests that AGRIP significantly reduced CO2 emissions, and the effect is stronger in lower quantiles (least carbon emitters). On the other hand, AGRIP increases N2O and CH4 emissions in all quantiles. However, AGRIP is homogeneously distributed across N2O quantiles while the effect is stronger in higher quantiles (high methane emitters) in the case of CH4 model. Concerning agricultural trade, exports impede CO2 emissions but increase N2O and methane emissions. Agricultural imports are positively associated with all GHGs emissions. The effect of agricultural trade is largely heterogeneous and varies across different quantile levels of GHGs emissions. The EKC is fully valid for CO2 and N2O but not for the methane emissions model. Based on the results, it is suggested that high GHGs emitter should shift their agricultural activities from traditional to sustainable approaches along with green trade policies to achieve climate neutrality targets.

The Effect of Macroeconomic Variables on Private Savings in BRICS-T Economies

Considering the fact that savings are very important for developing countries and that they should be increased, in this study, the effects of macroeconomic variables consisting of economic growth rate, inflation rate, real interest rate and per capita income on private savings for BRICS-T countries, have been examined with the annual data of 1996-2019 period. For this purpose, firstly, the cross-sectional dependency and homogeneity situations between the mentioned countries have been evaluated. Then, the second-generation panel unit root test, the CADF Test, has been applied to test for stagnation. Westerlund (2008) Durbin-H method has been used to determine the long-term cointegration relationship. In the estimation of long-term cointegration coefficients, for inter-unit correlation and heterogeneity, the common correlated effects – CCE estimator proposed by Pesaran (2006) has been used. Although the findings differ for countries, they reveal that there are important relationships between macroeconomic variables and savings.

Environmental degradation in terms of health expenditure, education and economic growth. Evidence of novel approach

Physical education benefits health and the environment because the world takes long-term steps to stop environmental degradation and its effects. Therefore, the present study examined the impact of health expenditure, education, economic growth, and population on environmental degradation in seven emerging economies from 2000 to 2019. The cross-sectional dependency (CSD) reflected the panel nations’ CSD, whereas the second-generation panel unit root test confirmed all indicators’ stationarity at first difference. Thus, the second-generation cointegration approach identified a long-term equation among the CO2, health expenditure, education, economic growth and population. The long-run empirical estimations derived from the PFMLOS and PDOLS method emphasized that education increases the region’s environmental sustainability and decreases CO2 emissions. Conversely, health expenditure, economic growth, and population increase CO2 emissions and reduce environmental quality in the E-7 bloc. Moreover, our findings are resilient to alternative measures by AMG and CCEMG, which might help policymakers develop long- and short-term initiatives for environmental protection. The study suggests adopting physical education and physical health activities to curb environmental degradation in the panel region.