Cross-sectional Dependence Tests Research Articles

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.

Leveraging AI for Promoting Sustainable Environments in G-7: The Impact of Financial Development and Digital Economy via MMQR Approach

This study investigates the role of Artificial Intelligence (AI) in promoting a sustainable environment within the G-7 countries by testing the Load Capacity Curve (LCC) hypothesis. Additionally, it examines the effects of financial development, the digital economy, and urbanization on the load capacity factor using data from 2010 to 2022. The research employs cross-sectional dependence and slope homogeneity tests, revealing issues of cross-sectional dependence and heterogeneity. Panel unit root tests, both first and second generation, confirm that the variables are free from unit root problems. Furthermore, panel cointegration tests indicate that the variables are cointegrated in the long run. To assess the impact of the explanatory variables on the load capacity factor, the study utilizes the Method of Moments Quantile Regression (MMQR). The findings reveal a U-shaped relationship between income and the load capacity factor, supporting the LCC hypothesis in the G-7 region. The results also indicate that AI innovation and financial development have a significant positive correlation with the load capacity factor. In contrast, the digital economy and urbanization are found to significantly reduce the load capacity factor. Robustness checks, including the Driscoll-Kraay standard error, Augmented Mean Group, and Common Correlated Effect Mean Group estimation approaches, validate the findings obtained from the MMQR method. Moreover, the Dumitrescu-Hurlin (D-H) causality assessment is utilized to explore the causal connections between variables. The results reveal a unidirectional causal relationship between income and the load capacity factor. Additionally, bidirectional causal relationships are the remaining explanatory variables and load capacity factors.

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.

Corporate Citizenship and Wealth Maximisation: A Re-evaluation of Stakeholder Theory Using Evidence from Listed Industrial Goods Firms in Nigeria

Based on stakeholder theory, the study examined the extent to which firm involvement in corporate citizenship influences the wealth maximisation of listed industrial goods firms in Nigeria. While corporate citizenship was measured using corporate donations, the proxy for wealth maximisation was market value of the firms. Ex-post facto research design was used on a population of thirteen listed industrial goods firms in Nigeria, from which a sample size of nine was purposively selected. Secondary data were gleaned from the firms’ annual reports from 2013 to 2023 (11 year interval). Panel Cross-section Heteroskedasticity LR Test was conducted while White cross-section standard errors and covariance was applied to correct the heteroskedasticity anomaly. In addition, Residual Cross-Section Dependence Test was carried out of which Cross-section Seemingly Unrelated Regression was used to address the issue of cross-sectional dependence. Therefore, the hypothesis were tested using estimates from Panel Estimated Generalised Least Squares, which revealed that involvement in corporate citizenship significantly and positively influences wealth maximisation among listed industrial goods firms in Nigeria (β = 32.79912; p-value = 0.000). In conclusion, firms that engage in meaningful corporate citizenship are likely to build stronger relationships and this, in turn, contributes to increased sustainable wealth creation. We recommend that senior management of listed industrial goods firms in Nigeria should prioritise and formalise their corporate citizenship initiatives as integral parts of their corporate strategies in order to ensure that the community development efforts they make are not ad hoc but embedded in the firm's strategic planning and operations.

The Trend in Environmental Load in the European Union during the Period of 2012–2022

The environmental burden is a global problem affecting the European Union. A comprehensive analysis of the environmental burden is essential for creating strategies supporting sustainable economic development. This study attempts to answer the question of why, despite the continuously decreasing energy consumption of the EU, the environmental burden of this region is not substantially decreasing. This study provides novel insights into this research area by integrating EU economic dynamics and environmental efficiency indicators. In this study, we used the IPAT method. Before the main analysis, the researcher conducted cross-sectional dependence, slope heterogeneity, and Westerlund cointegration tests using the primary data. Based on the results, the EU member states were classified into clusters, and a linear trend model analysis was carried out. The results show that the total environmental load of the EU did not decrease significantly between 2012 and 2022. The fact that the environmental burden remained at the same level is explained by the fact that there were 16 member countries whose total environmental load increased but whose economic output was lower during this time period. This was offset by 11 member countries with high economic outputs, whose total environmental load decreased. This study proved that GDP growth was the main driving force maintaining the total environmental load at the same level. The EU should encourage member states to continue to implement environmental protection rules to limit and eliminate costly environmental burdens on their societies and economies. This study can be helpful to researchers, political decision-makers, and experts working on environmental public policies for the EU.

Achieving sustainable development in ECOWAS countries: the impact of trade openness, poverty and human capital

This study investigates the relationship among trade openness, poverty, and human capital development in the pursuit of sustainable development across a panel of ten ECOWAS economies over a 34-year period (1987–2020). Specifically, it examines the roles of trade openness, poverty, and human capital development in sustainable development, while also exploring the moderating role of trade openness on the poverty-sustainable development relationship within the ECOWAS region. To conduct this analysis, the study employs panel autoregressive distributed lag (ARDL) using both the Pool Mean Group (PMG) estimator and Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) techniques, taking into account cross-sectional dependence, cointegration, and other relevant diagnostic tests. The findings indicate that poverty has a consistent negative long-run impact on sustainable development, while human capital is positively associated with sustainability over the long term. Trade openness lacks a significant relationship with sustainability in both the short and long run. Inflation is insignificantly related to sustainability. Exchange rates demonstrate mixed effects. In terms of moderation, trade openness positively and significantly moderates the poverty-sustainability relationship in the long run but not the short run. Robustness testing using the AMG and P-OLS models further validates the significant positive impact of human capital and the insignificant effect of trade openness on sustainable development. Given poverty’s significant negative association and human capital’s positive link with sustainable development, the findings suggest the need for integrated policy mixes prioritizing multidimensional poverty reduction and human capability enhancement to promote sustainability objectives across both short- and long-term horizons in ECOWAS countries. Furthermore, prudent management of exchange rates and well-designed trade policies should complement these efforts to mitigate potential risks and harness any benefits for sustainability.

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.

Can board funds, bank credit, and economic development improve food production? Evidence from South Asia

PurposeThis study investigates the impact of board funds, banking credit, and economic development on food production in the context of South Asian economies (India, Pakistan, Bangladesh, Sri Lanka, and Nepal).Design/methodology/approachThis study used data from the World Development Indicators covering the years 1991–2019. To investigate the relationship between the variables of the study, we employed the panel unit root test, panel cointegration test, cross-sectional dependence test, fully modified least squares (FMOLS), and panel dynamic least squares (DOLS) estimators.FindingsThe empirical results indicate that board funding significantly increase food production; however, banking credit had a negative impact. Furthermore, the findings indicate that economic development, Arable land, fertilizer consumption, and agricultural employment play a leading role in enhancing food production. The results of the Dumitrescu-Hurlin causality test also show substantiated the significance of the causal relationship among all variables.Practical implicationsSouth Asian countries should prioritize board funding, bank credit, and economic development in their long-term strategies. Ensuring financial access for farmers through micro-credit and public bank initiatives can spur agricultural productivity and economic growth.Originality/valueThis study is the first to combine board funding, banking credit, and economic development to better comprehend their potential impact on food production. Instead of using traditional approaches, this study focuses on these financial and developmental aspects as critical determinants for increasing food production, using evidence from South Asia.

The implications of the ecological footprint and renewable energy usage on the financial stability of South Asian countries

This study explores the complex relationships involving ecological footprints, energy use, carbon emissions, governance efficiency, economic prosperity, and financial stability in South Asian nations spanning the period from 2000 to 2022. Employing various methodologies such as cross-sectional dependence tests, co-integration analysis, and first- and second-generation unit-root tests, we use a panel Autoregressive Distributed Lag model, feasible generalized least squares, and Panel Corrected Standard Errors to ensure the robustness of our findings. We find noteworthy positive correlations between several variables, including heightened ecological consciousness, effective governance structures, increased GDP per capita, and amplified CO2 emissions. These relationships suggest potential pathways to strengthen the financial stability of the entire region; they also highlight the latent potential of embracing ecologically sustainable practices to fortify economic resilience. Our results also underscore the pivotal role of appropriate governance structures and higher income levels in bolstering financial stability in South Asian countries. Interestingly, we also find negative coefficients associated with the use of renewable energy, suggesting that escalating the adoption of renewable energy could create financial instability. This finding stresses the importance of diversification in energy strategies, cautioning policymakers to carefully consider the financial ramifications of potentially costly imports of renewable energy sources while seeking to reduce carbon emissions, emphasizing the need to strike a balance between ambitious sustainability goals and the pursuit of sustained economic robustness in the region. In considering the implications of these findings, it is crucial to consider each country’s broader socioeconomic context. Our results offer valuable insights for policymakers in developing renewable energy strategies.

Unleashing sustainability in uncertain times: Can we leverage economic complexity, uncertainty, and remittances to combat environmental degradation?

Rapid economic growth and human activities have seriously damaged the environment and hindered the achievement of Sustainable Development Goals (SDGs). Hence, this study aims to explore the impact of economic complexity, uncertainty, and remittance on environmental degradation in 134 countries from 2000 to 2022. In addition, it examines whether uncertainty moderates the relationship between remittance and environmental degradation. Two proxies (ecological footprint and CO2) were used to measure environmental degradation. The analysis was conducted using a cross-sectional dependency test, second-generation unit root test, and panel quantile regression. The results revealed that economic complexity significantly and positively impacted environmental degradation, while uncertainty and remittance significantly and negatively impacted environmental degradation. Furthermore, uncertainty weakened the negative relationship between remittance and environmental degradation. Accordingly, this paper discusses various recommendations and policy implications regarding economic complexity, uncertainty, remittance, and environmental degradation.

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.

Unveiling the power of education, political stability and ICT in shaping technological innovation in BRI nations

Technological innovation is a critical element of economic and environmental sustainability; thus, the promotion of technological innovation in the economy has gained an apex among policy makers. The study's impetus is to measure the effect of investments in information and communication technology (ICT), education, and political stability on technical innovation in BRI countries for 2004–2020. In the process of documenting the empirical nexus through the implementation of novel panel techniques commonly known as Dynamic Seemingly Unrelated Regressions (SUR), continuously updated fully modified" (Cup-FM) and continuously updated bias-corrected (Cup-BC). The results of the slope of heterogeneity, cross-sectional dependency test, and panel cointegration test have revealed the presence of heterogeneity, all the research variables possessed certain common dynamics, and, most importantly presence of long-run association. The study documented the coefficients of ICT, education and Political stability are positive and statistically significant, indicating a contributory effect in fostering technological innovation in BRI nations. The findings emphasize the importance of upholding political stability, directing resources toward education, and fostering an environment that encourages innovation through the integration of information and communication technology (ICT). The study also highlights how critical it is to bring in FDI and use it to your advantage in order to boost tech development and the economy.

How do product responsibility and corporate philanthropy affect firm value?

Satisfying the consumer and contributing to societal well-being have been globally acknowledged, and these developments consequently boost corporate image, attract investors, increase stock prices, enhance firm value, and enable industrial and other firms to contribute to national development. This paper examines how product responsibility and philanthropy affect the performance of industrial goods firms in Nigeria. A sample of 7 firms was selected from 24 listed firms after employing a judgmental sampling technique and using secondary data and a quantitative research method. Data validation and analysis were aided by econometric views statistical software, panel data regression, fixed and random effects estimators, stationarity test, cross-section dependence test, Durbin-Watson test, and Hausman test. The study revealed that investment in product responsibility, as evidenced by the rising stock turnover rate, is value-enhancing in Nigeria {B1 = 0.076807, P = 0.0171 or P < 0.05}, while philanthropic donation is value destroying {B1 = –0.369535, P = 0.5817 or P > 0.05}. It was concluded that consumers’ confidence in corporate institutions can enhance corporate value, while investment in philanthropy is not usually value-enhancing when done irresponsibly and non-strategically. The study, therefore, recommended that investment in product responsibility should be consolidated to sustain the rising stock turnover rate, while investment in philanthropy should be done strategically and responsibly to make it value-enhancing. AcknowledgmentThis research was based on Nnamdi Azikiwe University Ph.D. Dissertation funded by the Tertiary Education Trust Fund (Tetfund), Nigeria. University of Calabar in Nigeria is highly acknowledged for funding the PhD dissertation through its Tetfund platform.

Do remittances mitigate poverty? Evidence from selected countries in Africa, Asia and Latin America

The overall objective of the Sustainable Development Goals is to end poverty in all its manifestations by 2030. To achieve this, international remittance inflows have been identified as crucial external financing, especially for developing countries, to secure the resources needed to improve the living conditions of the poor in these countries. It is on this premise that this study investigates the nexus between remittances and poverty in selected countries in Asia, Africa and Latin America, given that these regions receive the highest amount of remittances globally. The study uses annual data on 38 top recipients of remittances between 1990 and 2021. To ensure the robustness of the results, the study employs two indicators of poverty: household consumption expenditure and poverty headcount. On the methodological front, the study addresses the issue of cross-sectional dependence in a panel study and also corrects for endogeneity, using both static and dynamic methods of analysis, respectively. Empirical findings from the cross-sectional dependence test confirm the interdependence of countries in the study. Interestingly, the study confirms the optimistic view that remittance reduces poverty in the selected countries. This finding is consistent for the two poverty indicators regardless of the methodology adopted. The study concludes that remittance inflows play a pivotal role in alleviating poverty in the selected countries. Based on the findings, governments in the three regions are advised to devise appropriate policies and structures that can support and channel the proceeds from remittances to productive ventures to reduce the incidence of poverty in their respective countries.

Tourism development and ecological footprint indicators in island destinations: evidence from the members of the alliance of small island states

ABSTRACT Considering the crucial debates on sustainable development it is significant to understand the link between the development of tourism in small island countries and the ecological footprint. However, to date, little knowledge is available about the contribution of tourism to the EF of small island states. Therefore, the study aims to investigate the effects of international tourism, tourism revenues, total natural resource rents, urbanisation, energy intensity, and per capita gross domestic product (GDP) on ecological footprint among the Members of the Alliance of Small Island States (AOSIS). The results of our study provide new empirical results on the impact of tourism, economic growth, energy intensity, natural resource rents, and urbanisation on the ecological footprint of the 7 AOSIS member countries. Cross-sectional dependency and cointegration test results are positive for the variables of interest. Our estimates based on CCEMG and AMG regressions showed which factors contribute to environmental degradation at the AOSIS and country levels.

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.

Permanent VS Transitory Shocks to Electricity Consumption: Panel Evidence from 19 African Countries

ABSTRACT: Considering Africa's increasing electricity demands and the pivotal role of electricity in socio-economic development, this study addresses a research gap in understanding the stochastic properties of per capita electricity consumption in African contexts. Through examining the integration properties of per capita electricity consumption across 19 African countries, the research determines whether 'shocks' yield transitory or permanent effects, aiding policy formulation and future demand forecasting. Annual electric power consumption data (1971 – 2014) (kWh per capita) from the WDI across 19 African countries are used. Our methodology starts with formally testing for cross-sectional dependence (CSD) using various tests to avoid potential size distortions. Subsequently, we employ the novel panel stationarity test of Nazlioglu and Karul (2017), a Fourier KPSS panel stationarity test. The robustness of the analysis is enriched by incorporating the Hadri and Kurozumi (2011) panel stationarity test and Nazlioglu et al. (2021) new panel stationary tests. The CSD test results reveal mutual dependency in electricity consumption among the sampled African countries, underscoring the need for a panel testing methodology that accommodates CSD. The results of the panel stationarity tests that allow CSD and structural breaks—specifically, the Nazlioglu and Karul (2017) test, which models structural breaks as a gradual process—reject the null hypothesis of trend stationarity for both single frequencies, i.e., k =1, and 2. Similarly, all new, complementary panel stationarity tests from Nazlioglu et al. (2021) reject the null hypothesis of stationarity for both frequencies. Collectively, the outcomes from various panel stationarity tests present strong evidence of nonstationary per capita electricity consumption within the sampled African countries. Additionally, the Nazlioglu and Karul panel stationarity test enables an analysis of the individual Fourier KPSS test for cross-sectional units in the panel. Of the 19 countries, only Togo does not reject the null hypothesis of stationarity for both frequencies. These individual country results align with the panel outcomes, providing compelling evidence for the nonstationarity of the per capita electricity consumption series across the investigated African nations. Accordingly, shocks to electricity consumption will have permanent effects, indicating that per capita electricity consumption will not return to its pre-shock equilibrium path. In this case, demand or consumption stabilizing policies will have long-run effects.

Nexus among Exchange Rate Volatility, Inflation, and Economic Growth: A Panel Data Analysis

This study undertakes an examination of the intricate relationships among exchange rate fluctuations, inflation, and economic growth within South Asian nations, namely Pakistan, India, Bangladesh, Sri Lanka, and Nepal. Spanning the temporal horizon from 1990 to 2021, the research endeavors to unveil the repercussions of exchange rate instability on economic growth—a formidable challenge confronted by monetary authorities and policymakers in South Asia. The central focus lies on comprehending the dynamics of exchange rate volatility, inflationary pressures, and their collective impact on economic growth. In the pursuit of these objectives, GDP per capita serves as the yardstick for economic growth, while independent variables encompass a spectrum including broad money supply, exchange rate volatility, inflation, government consumption expenditures, and gross fixed capital formation. The quantification of exchange rate volatility entails the utilization of both the standard deviation and the GARCH (1,1) models. Subsequent to an in-depth analysis, the initial unit test results undergo reevaluation, incorporating the Breusch-Pagan LM, Pesaran CD, and Pesaran scaled LM tests to discern cross-sectional dependence. To address potential data non-stationarity while considering cross-sectional dependence, the Pesaran-CIPS and Pesaran's CADF tests are applied. A pivotal aspect of the research involves the application of a Feasibly Generalized Least Squares (FGLS) regression model. The outcomes of the FGLS panel data regression illuminate a noteworthy finding: exchange rate volatility, quantified through both techniques, significantly and adversely influences economic growth. In contrast, inflation exhibits a statistically insignificant negative impact on economic growth. The study culminates by proffering specific recommendations to policymakers, urging concerted efforts to ensure exchange rate stability and foster sustained economic growth.

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.

Exploring the impact of economic growth and energy consumption on SO2 emissions in China based on the Environmental Kuznets Curve hypothesis

This study aims to analysis the influence of economic growth (EG) and energy consumption (EC) on sulfur dioxide emissions (SE) in China. Accordingly, this study explores the link between EG, EC, and SE for 30 provinces in China over the span of 2000–2019. This study also analyzes cross-sectional dependence tests, panel unit root tests, Westerlund panel cointegration tests, Dumitrescu-Hurlin (D-H) causality tests. According to the test results, there is an inverted U-shaped association between EG and SE, and the assumption of the Environmental Kuznets Curve (EKC) is verified. The signs of EG and EC in the fixed effect (FE) and random effect (RE) methods are in line with those in the dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS) and autoregressive distributed lag (ARDL) estimators. Moreover, the results verified that EC can obviously positive impact the SE. To reduce SE in China, government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency. This requires the comprehensive use of policies, regulations, economic incentives, and public participation to promote sustainable development.