Second-generation Panel Research Articles

The impact of human capital on the load capacity factor in the middle east and north Africa

Although there has been a substantial body of research analysing the factors influencing environmental sustainability, the role of human capital has been relatively understudied. The objective of this research is to fill this gap by examining the impact of human capital on load capacity factor (LCF) across 14 MENA countries from 1990 to 2019. The empirical investigation employs the Method of Moments Quantile Regression (MMQR) alongside a variety of second-generation panel data techniques. The empirical analysis confirms the presence of a long-term linkage between human capital and environmental sustainability. Furthermore, the MMQR suggests a negative impact of human capital on LCF across all quantile orders, indicating that enhanced human capital reduces LCF and deteriorates environmental quality. Although the detrimental effects of human capital on the environment is observed in all countries, they are more pronounced in countries with good environmental performance. Additionally, the MMQR indicates the validity of the Load Capacity Curve hypothesis within MENA countries. Finally, economic globalisation and population have detrimental impacts on the environment, whereas clean energy consumption has a positive effect. This study emphasises the necessity of increasing public awareness of environmental challenges, as well as the implementation of strategies for mitigating climate change in the MENA region.

Domestic and External Drivers of Inflation in Oil Importing Developing Countries

This paper explores inflation drivers in 12 oil-importing developing economies, focusing on domestic and external drivers, such as monetary policy rate, government expenditure, global oil prices, exchange rate, imports, global food prices, and other factors. The study aims to establish a hierarchy of these drivers from the most to the least significant, which is essential for a better implementation of anti-inflationary policies in oil-importing developing countries. Using Seemingly Unrelated Regression (SUR) model and second-generation panel unit root test to handle cross-sectional dependence, and applying Dumitrescu-Hurlin panel Granger causality approach to confirm SUR outcomes, this research paper revealed for the period between 2000Q1, and 2023Q2 that lagged inflation is the most important driver of current inflation, supporting the theoretical concept of inertial inflation. Unexpectedly, this study showed that monetary policy rate is positively impacting inflation, confirming the presence of the price puzzle. Additionally, monetary base doesn’t have any significant impact on aggregate price level, meaning that the inflation is not a monetary phenomenon for the studied countries. Producer prices, used as a proxy for domestic supply shocks, seemed to have a positive and significant effect on inflation. Government expenditure, trade openness, and global oil prices have notable effects. Even if all the studied countries are oil importers, the impact of oil prices on inflation is mitigated by subsidies and price controls. Finally, inflation is negatively affected by imports and exchange rate. The study underscores the necessity for new central bank tools adapted to these countries context, monetary and fiscal policies coordination, a strategic use of subsidies, and an integrated policy to improve market competition.

Exploring the effect of ODA on poverty: insights from least developed countries

PurposeThe purpose of this study is to examine the long run impact of official development assistance (ODA) on Poverty levels in a sample of 33 least developed countries (LDCs) from 1991 to 2018.Design/methodology/approachThis study employed second-generation panel econometric techniques like Westerlund (2007), Pedroni (2004) cointegration tests and the augmented mean group (Eberhardt and Bond, 2009); (Eberhardt and Teal, 2010) and fully modified ordinary least squares (Phillips and Hansen, 1990) estimations to ascertain the long-run nexus between the variables of interest.FindingsOur findings revealed that ODA has a significant and positive impact on poverty expansion in LDCs. This indicates that ODA perpetuates poverty in LDCs in the long run. While gross domestic product (GDP) per capita and trade openness significantly contributed to reducing poverty levels. Our findings have several policy implications.Originality/valueThis paper sheds light on a panel of LDCs on which research on the ODA–poverty nexus is sparse in prevailing literature. Although studies have documented the impact of single country episodes on LDCs, research on the panel of LDCs remains largely unexplored. This is surprising given the heightened economic and social issues faced by these cross-sections. Additionally, a sustained downturn in ODA flows to LDCs and the commitment to meet SDG Goal 1 underscore the need for comprehensive analysis on LDCs. Hence, our study aims to address the critical gap in the prevailing literature and contribute to the field.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2024-0390

Carbon dynamics: A holistic analysis of FDI, trade liberalization, urbanization, economic growth, and effects on CO2 emissions in South Asia

In recent years, South Asian nations have experienced robust economic growth, prompting concerns among policymakers about the sustainability of this growth due to rising pollution emissions. This study conducts an objective assessment of the impact of key variables, such as trade liberalization, economic growth, foreign direct investment inflows, and urbanization, on environmental outcomes across selected economies of South Asia from 1990 to 2022. To describe cross-sectional dependencies in the dataset, panel cointegration techniques are employed alongside cross-sectionally augmented autoregressive distributed lag (CS-ARDL) models. For added robustness, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) techniques are utilized to investigate the long-term coalition among the variables. The study integrates first- and second-generation panel methods to improve the depth and reliability of the analysis by addressing methodological limitations. The pragmatic results reveal that trade liberalization, FDI inflows, economic growth, and urbanization increase CO2 emissions by 0.392%, 0.354%, 0.275%, and 0.429%, respectively. Dumitrescu and Hurlin (D–H) causality tests show a unidirectional causal link from trade liberalization to environmental degradation. Additionally, a bidirectional causal link is observed between environmental deterioration and both FDI inflows and urbanization in South Asian countries. To mitigate environmental impact, these nations should evaluate foreign investment conditions and enhance technology transfer from foreign enterprises. Furthermore, implementing trade-related policies to reduce CO2 emissions is imperative.

Interlinkages between public expenditures, non-tax government revenues and corruption in the transition economies

PurposeThis article examines potential impacts of increase in non-tax government revenues and public expenses on corruption for 11 transition economies in the Central and Eastern Europe.Design/methodology/approachThe empirical analysis uses yearly panel datasets and employs second-generation panel data models which take cross-sectional dependency and slope heterogeneity into account.FindingsThe empirical results reveal the fact that there is a strong linkage between public expenses and corruption and a weak linkage between non-tax revenue collection and corruption in the transition economies. We perform the same analysis by using data sets from G-7 countries but do not notice any linkages between those variables.Research limitations/implicationsThe research topic requires further discussion on constitutional political economy to digest the empirical findings. Thus, an extended version combined with political economic approach might be useful.Practical implicationsThrough economic transitions, there might be a linkage between public expenditures and corruption index. Thus, public spending might be controlled by using constitutional economics policies.Originality/valueThis paper is the first empirical work in the literature, which examines if there is a linkage between corruption and public expenditures and government tax income structure by using panel data sets. Moreover, it compares the results from transition countries with those of G-7 countries and provides certain policy suggestions in the context of constitutional economics.

Does structural change matter for sustainable development in newly industrialized countries? Fresh evidence from a new sustainability indicator

The economic gap between developed and developing economies has been diminishing due to the recent rapid economic growth performance of developing economies. While achieving this swift growth level, developing economies have structurally transformed their economies. However, the impact of this structural change on environmental sustainability remains unclear. Therefore, this study focuses on the impacts of structural change, energy structure, and economic growth on the load capacity factor, a comprehensive sustainability indicator, in newly industrialized countries during 2000–2020. To this end, second-generation panel data techniques, which account for cross-sectional dependence and heterogeneity, are used to provide more robust and reliable estimates. The results show that economic growth, structural change, and fossil energy utilization decrease the load capacity factor while renewable energy utilization increases it. These findings underscore the need for energy efficiency and resource-conscious policies that align with environmental sustainability while promoting economic growth, highlighting their crucial role in the future of sustainable development.

Towards a healthier future for the achievement of SDGs: unveiling the effects of agricultural financing, energy poverty, human capital, and corruption on malnutrition

The objective of the present study is to address child and maternal malnutrition in nine African countries located in the Western sub-region of Sub-Saharan Africa (SSA) by incorporating three types of agricultural financing (domestic and external) along with energy poverty, human capital and corruption on malnutrition for the 1990–2019 period and present implications for Sustainable development goals (SDGs). This objective is realized by employing recently advanced panel techniques such as the second-generation panel econometrics techniques and the method of moments quantile regression (MMQR) approach. The estimated results reveal that agricultural credit and foreign aid in the agriculture sector significantly and negatively affect the malnutrition of children and mothers, while research spending in agriculture positively influences malnutrition. Energy poverty and human capital exert a negative and significant influence on child and maternal malnutrition, while corruption induces it. The study finally recommends several policy insights for the governments across the SSA region for tackling child and maternal malnutrition and advancing towards the achievement of SDG 3 through investment in SDG 4, SDG 7 and SDG 17.

Shadow economy-income inequality nexus: a panel analysis of West African countries

ABSTRACT This paper examines the nexus between shadow economy and income inequality in the West African region. The study applies second-generation panel estimation techniques to analyze the effect and the direction of causation between the variables. The results reveal that the shadow economy reduces income inequality in the region in both short-run and long-run estimations. A similar result is documented when alternative estimation techniques are employed. In addition, the panel causality results show a bidirectional relationship between shadow economy and income inequality in the West African economy. The implications of the study are discussed.

Exploring the LCC Hypothesis in the Nordic Region: The Role of AI Innovation, Environmental Taxes, and Financial Accessibility via Panel ARDL

This study investigates the impact of artificial intelligence (AI) innovation on environmental sustainability in the Nordic region. Additionally, it tests the Load Capacity Curve (LCC) hypothesis by incorporating factors such as financial accessibility, environmental tax, and urbanization, using data spanning from 1990 to 2020. The methodology includes the Cross-Sectional Dependence test and the slope homogeneity test, revealing issues of heterogeneity and cross-sectional dependence. Furthermore, first and second-generation panel unit root assessments indicate that the variables are free from unit root problems. Panel Cointegration tests confirm that the variables are cointegrated in the long run. To analyze both short-run and long-run relationships, the study employs the Panel Autoregressive Distributed Lag (ARDL) model. The results from the Panel ARDL model support the LCC hypothesis in the Nordic region, showing a U-shaped relationship between income and load capacity factor. Moreover, AI innovation and environmental tax significantly and positively contribute to environmental sustainability in both the short and long run. In contrast, higher financial accessibility and urbanization degrade environmental sustainability over these timeframes. To validate the robustness of the Panel ARDL estimations, the study also uses Fully Modified OLS, Dynamic OLS, and Fixed Effects OLS approaches, all of which corroborate the ARDL findings. The study employs the D-H causality test to explore causal relationships among the variables. The test results reveal a unidirectional causal relationship between income and AI innovation to the load capacity factor and a bidirectional causal relationship between financial accessibility and the load capacity factor, as well as between urbanization and the load capacity factor. However, no causal relationship is found between environmental tax and the load capacity factor.

Assessing Fiscal Sustainability with Panel Unit Root, Cointegration, and Granger Causality Tests: Evidence from the Broader Groups of Countries

Abstract The question of fiscal sustainability of countries has become one of the central topics in economic policy, especially in times of increasing public debts. One way to assess fiscal sustainability is to examine compliance with the intertemporal budget constraint, which involves testing the stationarity of government revenues and expenditures, the primary budget balance, and the first differences of public debt. Part of this approach includes testing cointegration and causality among different pairs of variables. Under this approach, the paper is focused on both first- and second-generation panel unit root tests, cointegration, and Granger causality test. This paper focuses on assessing the fiscal sustainability of four panels of countries divided by continents: Europe, Asia and Oceania, Africa, and Latin America, the Caribbean, and North America. It has been found that fiscal sustainability is present in all the broader groups of countries considered but in a weak form. Fiscal sustainability was confirmed when considering a constant in calculations, while deviations were observed among groups of countries when both a constant and trend were considered. The study serves as a starting point for a more extensive analysis of fiscal sustainability. For more accurate findings, it would be necessary to categorize countries into smaller and economically more homogeneous groups and analyze them using other fiscal sustainability methods as well.

Analyzing the Nexus between AI Innovation and Ecological Footprint in Nordic Region: Impact of Banking Development and Stock Market Capitalization using Panel ARDL method

This study investigates the impact of Artificial Intelligence (AI) innovation on the ecological footprint in the Nordic region from 1990 to 2020, alongside the effects of banking development, stock market capitalization, economic growth, and urbanization. Utilizing the STIRPAT model, the study incorporates cross-sectional dependence and slope homogeneity tests, revealing issues of heterogeneity and cross-sectional dependence. The analysis employs both first and second-generation panel unit root tests, confirming that the variables are free from unit root problems. Panel cointegration tests demonstrate that the variables are cointegrated in the long run. To explore the short- and long-term relationships, the study utilizes the Panel Autoregressive Distributed Lag (ARDL) model. The Panel ARDL results indicate that economic growth, stock market capitalization, and urbanization positively correlate with the ecological footprint in both the short and long run. Conversely, AI innovation and banking development negatively correlate with the ecological footprint. To validate the Panel ARDL estimations, robustness checks are performed using Fully Modified OLS, Dynamic OLS, and Fixed Effects with OLS, all of which support the initial findings. Furthermore, the study employs the D-H causality test to identify causal relationships. The results show a unidirectional causal relationship between AI innovation, stock market capitalization, urbanization, and the ecological footprint. In contrast, a bidirectional causal relationship exists between economic growth and the ecological footprint, as well as between banking development and the ecological footprint.

Health-led growth hypothesis and health financing systems: an econometric synthesis for OECD countries.

This study investigates the Health-Led Growth Hypothesis (HLGH) within OECD countries, examining how health expenditures influence economic growth and the role of different health financing systems in this relationship. Utilizing a comprehensive analysis spanning 2000 to 2019 across 38 OECD countries, advanced econometric methodologies were employed. Both second-generation panel data estimators (Dynamic CCEMG, CS-ARDL, AMG) and first-generation models (Panel ARDL with PMG, FMOLS, DOLS) were utilized to test the hypothesis. The findings confirm the positive impact of health expenditures on economic growth, supporting the HLGH. Significant disparities were observed in the ability of health expenditures to stimulate economic growth across different health financing systems, including the Bismarck, Beveridge, Private Health Insurance, and System in Transition models. This study enriches the ongoing academic dialog by providing an exhaustive analysis of the relationship between health expenditures and economic growth. It offers valuable insights for policymakers on how to optimize health investments to enhance economic development, considering the varying effects of different health financing frameworks.

Green Finance, Environmental Regulations, and Green Technologies in China: Implications for Achieving Green Economic Recovery

Abstract In the framework of foreign direct investments (FDI) and green finance (GF), environmental regulations (ERs) and green technologies have influenced China’s green economic recovery between 2000 and 2020. The idea is to conduct an empirical investigation of the main drivers behind China’s green economic revival. Second-generation panel cointegration techniques were adopted for the analysis. The relationship among ERs, green technological investment, GF, and green economic recovery is supported by the long-run cointegration results. In this context, some of the most important measures include ER, GF, and increased investment in environmentally friendly technologies. The estimated results demonstrate a positive contribution towards the green economic recovery from GF, the development of green technologies, and ERs. Evidence suggests that green economic recovery is inversely associated with FDI. The establishment of an environmentally sustainable economy can be rendered by policy implications to continue advocating for the green shift in financial institutions along with enforcing the appropriate regulations and laws.

Symbioza kreatywności i zrównoważonego rozwoju: modelowanie dynamicznych relacji pomiędzy zrównoważonym rozwojem a kulturą i przemysłem kreatywnym w krajach UE, Wielkiej Brytanii i Ukrainie

This study aims to examine the impacts of energy consumption and economic growth on the human development index of seven emerging countries (E-7) with high economic performance for yearly observations from 1992 to 2021. The analyses were carried out with second-generation panel data analyses: (i) Panel cointegration test with structural breaks proposed by Westerlund (2006), (ii) augmented mean group estimator recommended by Eberhardt and Bond (2009), and (iii) Dumitrescu and Hurlin (2012) panel causality test. The empirical model also included trade openness and urbanization parameters as control variables. The panel cointegration test outcomes reveal the presence of a long-run relation among the human development index and energy consumption, economic growth, urbanization, and trade openness for all countries. Augmented mean group test outcomes signify that energy consumption, economic growth, and trade openness have positive and statistically significant impacts on the human development index, whereas urbanization does not have any statistically significant impact in the long-run. Finally, panel causality test results signify that there is a bidirectional relation between the human development index and energy consumption, economic growth, and trade openness and also a unidirectional relation from urbanization to the human development index in E-7 countries. All these findings indicate that the main macroeconomic indicators have an important role on the human development index in E-7 countries. In this context, these countries should implement a more effective and innovative economic policy for Sustainable development goals.

Should the European Union prioritize renewble energy or tackle energy poverty?

Energy poverty is a type of poverty that is not solely based on monetary factors. It has recently been highlighted in the literature alongside the acknowledgment of energy as a key component of sustainable economic growth. Many studies focus on replacing fossil fuels with renewable energy sources to address this issue. This study aims to analyze the impact of renewable energy consumption on energy poverty in the European Union from 1996 to 2020. The study incorporates a control variable, developed using Principal Component Analysis (PCA), to account for economic development. Second-generation panel data tests and the Common Correlated Effects Model are utilized to assess the short and long-term effects. The findings indicate that the control variable had no significant impact on energy poverty during the relevant period. Still, renewable energy consumption had both positive effects in developed countries and negative effects in transition economies. According to the results, energy poverty measures remain a key priority in most of Europe's energy policies. This highlights the significance of ensuring that the underprivileged section of society has access to affordable and sustainable energy sources.

Do resource efficiency and energy productivity matter for environmental sustainability in G7 ?

In spite of the fact that the COP26 and COP27 Climate Conferences clearly emphasized the importance of resource efficiency in reducing global CO2 emissions, there is a paucity of empirical literature on the effect of resource efficiency on environmental sustainability. To close the gap in the literature and open new debate about the concept, the present study aims to capture the effect of resource efficiency on environmental sustainability in the G7 countries using novel panel-based estimators. The present study employs second-generation panel estimators, namely Westerlund model, common correlated effects mean group, augmented mean group, and Juodis, Karavias, and Sarafidis Granger noncausality tests. The outcomes of the study reveal that (i) there is a long-run linkage between environmental sustainability and resource efficiency, energy productivity, economic growth, and financial development; (ii) resource efficiency is an important predictor of environmental sustainability, whereas resource efficiency also causes to decrease in CO2 emissions in G7 countries; (iii) economic growth contributes to the environmental sustainability negatively. To achieve a low-carbon future, G7 policymakers should continue to raise awareness about resource efficiency. Moreover, it is possible for policymakers to reduce regulatory and market barriers by targeting their policies and programs to promote energy productivity.

The critical role of green innovation technologies and democracy in the transition to sustainability: A study on leading emerging market economies

Recent studies emphasize the potential of green technologies and political factors as catalysts for sustainability. Despite extensive examination of various factors' impacts on ecological footprints in previous literature, there is limited empirical evidence regarding the environmental effects of these two factors. Addressing this gap in the literature, this study underscores the importance of green innovation technologies and democracy in the transition to sustainability. The study aims to investigate the impact of green innovation technologies, democracy, income inequality, globalization, economic growth, and energy consumption on the ecological footprint in seven leading emerging market nations from 1990 to 2018. The study utilized second-generation panel data methodology to identify the relationship between variables using the Augmented Mean Group procedure. The study's findings indicate that green innovation technologies and democracy reduce the ecological footprint of the entire panel. While globalization is a force that reduces ecological pressure, income distribution has no significant impact. Factors that significantly increase the ecological footprint include economic growth and energy consumption. Although the results at the country level are somewhat heterogeneous, they provide supportive and promising insights for the panel.

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.

Advancing environmental sustainability in the G-7: The impact of the digital economy, technological innovation, and financial accessibility using panel ARDL approach

This study examines the impact of the digital economy, technological innovation, financial accessibility, and urbanization on CO2 emissions in the G-7 region from 1990 to 2019. The analysis employed Cross-Sectional Dependence (CSD) and Slope Homogeneity tests, revealing the presence of CSD issues and heterogeneous slope coefficients. First- and second-generation panel unit root tests indicated no unit root problem within the dataset, with variables showing mixed integration orders. Panel cointegration tests confirmed that the variables are cointegrated over the long run. To assess the short-run and long-run impacts of the explanatory variables on CO2 emissions, the study utilized the Panel Autoregressive Distributed Lag (ARDL) model. The findings indicate that the digital economy significantly reduces CO2 emissions, while economic growth, technological innovation, financial accessibility, and urbanization increase CO2 emissions in the G-7 region. The robustness of the Panel ARDL results was validated using Driscoll-Kraay standard errors, Augmented Mean Group (AMG), and Common Correlated Effects Mean Group (CCEMG) estimations. Additionally, the Dumitrescu-Hurlin causality test revealed a unidirectional causal relationship between the digital economy and CO2 emissions, GDP and CO2 emissions, and CO2 emissions and technological innovation. Furthermore, bidirectional causality was found between financial accessibility and CO2 emissions, as well as between urbanization and CO2 emissions. These findings provide comprehensive insights into the dynamic interactions between economic, technological, and environmental variables in the G-7 region, highlighting the complexity of achieving sustainable development.

Does environmental policy stringency alter the natural resources-emissions nexus? Evidence from G-7 countries

Natural resource management is indispensable keeping in view their positive economic impacts as well as their detrimental environmental consequences. To achieve certain SDGs, it is inevitable to manage natural resources through effective policies that help to inhibit adverse environmental impacts. Based on this approach, the current empirical analysis aims to probe whether environmental policy stringency intensifies, meagres, and/or halts the abysmal environmental impact of natural resources in G-7 countries (United Kingdom, United States, Canada, Italy, France, Japan, and Germany) for the period from 1990 to 2020. To that end, we rely on the second-generation panel data approaches and panel quantile regression. The outcomes reveal that natural resources increase carbon dioxide emission whereas the synergy of natural resources and environmental policy stringency plunges emissions across the quantiles. These findings suggest adoption of a strict environmental policy for attaining the targets of SGD-08 (economic growth), SDG-09 (innovations), SDG-11 (sustainable cities), SDG-12 (responsible consumption of natural resources), and SDG-13 (climate action).