Search Results (23)

This study investigates the interactive link between bank performance and financial innovation in Tunisian banking using a mixed-methods research framework that combines econometric approaches and institutional factors. The empirical analysis uses a panel data of 11 commercial banks from the period of 2000–2024 and employs an Autoregressive distributed lag (ARDL) model to estimate short- and long-run impacts of innovation on return on equity (ROE). A composite indicator of Fintech investment, digital service adoption, and innovation productivity characterizes financial innovation. Governance factors like the presence of risk management departments and executive compensation are taken into account. The results reveal a robust positive impact of financial innovation on bank performance in the long run, especially in more concentrated market settings. Risk management supports performance, while inefficient executive compensation is negatively associated with profitability. These findings are confirmed by robustness tests with HAC standard errors. This research contributes to the literature by situating financial innovation in the context of an emerging North African market and produces practitioner-relevant information for policymakers and bank executives interested in ensuring that performance results are consistent with innovation strategy. Full article

This study examines the effects of artificial intelligence investments, green financing, government stability, and institutional quality on renewable energy consumption from a multidimensional perspective. Using panel data for the period 2014–2023, 15 leading countries in the field of green financing were included in the analysis. The Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) method was preferred in the empirical analysis; robustness tests were conducted with Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) estimators to assess the reliability of the findings. According to the findings, artificial intelligence investments have a significant and positive impact on renewable energy consumption in both the short and long term. Similarly, green financing contributes strongly and statistically significantly by enhancing the feasibility of clean energy projects. Furthermore, stable governments and the effective functioning of institutional structures support this process; both factors are observed to have a positive effect on renewable energy consumption. This study offers concrete policy recommendations in line with the United Nations sustainable development goals (SDGs) 7, 9, 13, and 16. Full article

Achieving environmental sustainability in the G20 requires aligning economic growth with effective policy interventions. This study examines the role of financial technology (FNT), environmental legislation (ENL), and institutional quality (INQ) in reducing the ecological footprint (EF), while also assessing the adverse impacts of natural resource extractions (NRS) and economic expansion. Using CS-ARDL on panel data from 2000 to 2022, the study confirms cross-sectional interdependence and long-term cointegration through CIPS, CADF, and Westerlund tests. The findings reveal that FNT, ENL, and INQ significantly mitigate EF, whereas NRS and economic growth exacerbate it. Robustness is validated through the AMG and CCEMG methods, with ANN models reinforcing the results. The Dumitrescu–Hurlin test establishes a bidirectional link between NRS, economic growth, and EF, while FNT, ENL, and INQ exert a unidirectional influence on sustainability. These insights underscore the need for stronger regulatory frameworks, green fintech integration, and governance reforms to drive sustainable economic transitions in G20 economies. Full article

Environmental degradation poses a significant global challenge which necessitates innovative strategies to achieve sustainability. This study investigates the impact of technological innovation (TCN), higher education (EDU), green finance (GRF), globalization (GLI), and entrepreneurship (ENT) on environmental quality (EQ) in G20 countries. The study uses panel data from 2000 to 2020 to investigate relationships between study variables. Among the various diagnostic tests conducted, the Variance Inflation Factor (VIF) confirms that multicollinearity is not present. Furthermore, the cross-sectional dependence (CSD) test identifies cross-sectional interdependence among the study variables. Moreover, the slope homogeneity (SL) test indicates heterogeneity in the data. For the stationarity check, the Cross-Sectional Augmented Im–Pesaran–Shin (CIPS) test indicates mixed results. Finally, the study uses the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) and the Generalized Method of Moments (GMM) for the long- and short-run analysis of variables. The outcomes of CS-ARDL indicate that GLI has a significant negative impact on EQ, hence causing deterioration in G20 economies. On the other hand, TCN, EDU, GRF, and ENT show positive and significant impacts on EQ, therefore enhancing environmental outcomes. Additionally, the Dumitrescu–Hurlin causality test reveals bidirectional causality, which highlights the interconnected relationship between TCN and ENT with EQ. However, GRF, EDU, and GLI demonstrate unidirectional causality with EQ. The takeaway of the study focuses on the importance of policies in promoting green innovation, resource efficiency, and sustainable practices to advance environmental quality within G20 economies. Full article

This paper empirically investigates the short- and long-term impact of public expenditure on economic growth. We use annual data from 28 European Union (EU) countries for the 1995–2022 period and estimate a growth model augmented for public expenditure employing the Autoregressive Distributed Lag (ARDL) panel data approach. Our results support the view that different categories of public expenditures have dissimilar long- and short-term effects on the economic performance of EU countries. Full article

Entrepreneurship has been critical in fostering economic growth. The technological innovations and quality of institutions are crucial in promoting entrepreneurship and promoting an environment conducive to entrepreneurial activities. This study investigated the effect of technological innovations and institutional quality on entrepreneurial development with annual data from 2014 to 2021 across Southeastern European countries. The cross-sectional auto-regressive regressive distributed lag model (C-S ARDL), quantile regression and Granger causality were employed to achieve the objectives of this study. A dynamic panel generalized method of moments (GMM) estimator was also applied to perform a robust analysis. The findings revealed a significant long-term relationship between technological innovations and entrepreneurial development, with a coefficient of 0.088. There also exists a significant and positive impact on institutional quality and entrepreneurial development in the long run, with a coefficient of 5.912. Furthermore, the outcome revealed that the exchange rate negatively influences entrepreneurial development in Southeast Europe. The Granger causality reports a bi-directional relationship between technological innovations and entrepreneurial development in Southeastern Europe. The study concluded that a significant relationship exists between technological innovations, institutional quality, and entrepreneurial development in Southeastern Europe. The study recommends that governments of Southeastern European countries strengthen their regulatory structures and institutions to improve the welfare of society through a reduction in political, social, and economic unpredictability while boosting trust and investment from entrepreneurs. Full article

The global trend of rapid economic development and urbanization has created questions regarding the quality of the environment. In the group of emerging economies (E7), environmental challenges have intensified due to specific dynamics unique to these nations. This research is focused on determining the influence of urbanization (UBNZ), renewable energy (RWNE), capital formation (CPFR), foreign direct investment (FDIN), and natural resources (NTRR) on the ecological footprint (ECLF) of the E7 economies. The study employs the Panel Autoregressive Distributed Lag (PMG-ARDL) approach to examine these relationships, utilizing data spanning the period of 1990–2022. The results reveal that a 1% increase in the CPFR, NTRR, and UBNZ leads to increases in the ECLF of 0.0581%, 0.0263%, and 0.0299%, respectively. Conversely, a 1% increase in RWNE and FDIN reduces the ECLF by 0.0207% and 0.0556%, respectively, in the E7 economies. The study’s findings are further validated through robustness testing via the fully modified ordinary least squares (FMOLS) method. The study concludes with actionable policy recommendations aimed at enhancing environmental quality within these economies. These recommendations include promoting renewable energy adoption, attracting environmentally sustainable foreign investments, and implementing strategies to manage urbanization and natural resource use effectively. Full article

Scientific consensus affirms human activity, particularly carbon emissions from market participants, drives global warming. Foreign investment, crucial for sustainability in developing nations, now faces scrutiny regarding its impact on environmental quality in emerging economies. This study examines the influence of Chinese Outward Foreign Direct Investment (OFDI) and fintech on environmental conditions in the top five Chinese-invested African economies, alongside factors such as energy consumption, economic performance, and unemployment affecting CO₂ pollution. Quarterly data from 2006–2021 confirm cointegration among variables via panel unit root and cointegration tests. Panel ARDL method estimates coefficients for short and long-run effects. Our findings reveal: (1) A 1% increase in Chinese investment leads to a 0.56% decrease in CO₂ emissions, supporting its positive environmental impact. (2) Fintech adoption also demonstrates a beneficial effect, with a 1% increase associated with a 0.18% reduction in CO₂ levels. (3) Total energy consumption, as expected, has a detrimental impact, causing a 0.92% increase in CO₂ emissions with a 1% rise. (4) Interestingly, economic growth fosters environmental sustainability, while unemployment correlates negatively with it. These findings suggest that targeted Chinese investments and fintech adoption can aid in mitigating CO₂ pollution in African economies while balancing economic considerations. Full article

This study examines the relationship between entrepreneurship density and environmental quality in 28 Asia-Pacific countries using the PMG estimator as a panel data estimation method in the context of the ARDL model. The study finds that entrepreneurship density has no statistically significant short-term effects on CO₂ emissions in all three economic sectors, but it appears to have statistically significant effects on CO₂ emissions in agriculture and industry in the long run. The study suggests that the nature of entrepreneurship activities and their impact on the environment changes from low-income to high-income countries, with entrepreneurship activities with innovations and creativity primarily found in the industrial sector, improving economic efficiency and reducing industrial emissions. However, entrepreneurship activities with natural resource rents, such as large land use or forest rents, can cause environmental degradation. The study provides further insights by interacting entrepreneurship density with the income variable, revealing that entrepreneurship density has different effects on sectoral emissions in low, lower-middle, upper-middle, and high-income countries. Finally, the study provides interesting findings on the relationship between entrepreneurship density and environmental quality, such as biodiversity and water quality. Full article

The diurnal temperature range (DTR) is a significant indicator of climate change, and a previous study has shown its impact on human health. However, research investigating the influence of DTR on road traffic accidents is scarce. Thus, this study aims to evaluate the impact of changes in DTR on road traffic accidents. The present study employs two methods to address the complexities of road accidents. Firstly, panel data from 20 cities and counties in Taiwan are utilized, and the autoregressive distributed lag (ARDL) model is employed for estimation. Secondly, distributed lag non-linear models (DLNMs) are used with quasi-Poisson regression analysis to assess the DTR’s lagged and non-linear relationships with road accidents using time series data from six Taiwanese metropolitan cities. The study results indicate that a decrease of 1 °C in DTR raises long-term road traffic accidents by 17.1%. In the short term, the impact of declining DTR on road accidents is around 4%. Moreover, the effect of low DTR values differs in each city in Taiwan. Three cities had high levels of road accidents, as evidenced by an increase in the relative risk value; two cities had moderate responses; and one city had a relatively lower response compared to high DTR values. Finally, based on the cumulative relative risk estimations, the study found that a low diurnal temperature range is linked to a high road traffic accident rate, especially during the lag-specific 0–5 months. The findings of this study offer fresh evidence of the negative impact of climate factor on road traffic accidents. Full article

Many earlier development finance studies have attempted to assess the relationship between financial inclusion and economic growth. However, the findings of these studies vary from economy to economy and region to region due to various social and economic factors. We, therefore, deemed it pertinent to examine the relationship between financial inclusion and economic growth while further identifying the direction of causality between the two variables in twenty-six (26) Sub-Saharan African (SSA) economies using annual secondary data over the 2000–2019 period. In our paper, we used the principal component analysis (PCA) technique to develop a single composite index to proxy financial inclusion while adopting panel unit root, system generalised method of moment (GMM), and ARDL cointegration tests to assess the stationarity properties, assess the factors that affect economic growth, and examine the long-run relationships between financial inclusion and economic growth, respectively. In addition, a Granger non-causality test is used to verify the direction and magnitude of causality. Our study revealed that financial inclusion and economic growth share a strong long-run relationship and that there is bi-directional causality, indicating synergy between these two variables. In order to ensure sustainable economic growth, we thus recommend that developing countries develop macroeconomic policies that will promote financial inclusion while enhancing the functioning and regulation of the domestic financial markets to ensure that all citizens are catered for in the available instruments, products, and service offerings. Within the same policy framework, efforts must be made to further support productive sectors of the economy to ensure economic growth. Full article

Global warming has become a major concern for countries around the world. In this context, developed countries have decided to reduce global emissions to achieve sustainable development. The energy mix of OECD countries consists of 80% fossil fuels and accounts for about 35% of worldwide carbon emissions. Therefore, it is important to analyze how environmental factors affect carbon emissions in OECD countries. This study uses fossil energy, renewable energy (RE), and GDP for the period 1990–2019. Unlike previous studies, we will estimate two separate models for FFE and RE. To evaluate the empirical results, advanced panel data estimation methods using the cointegration test and the CS-ARDL estimation technique are employed to examine the long-run relationship between the variables. The results of the study demonstrate that fossil fuel use and GDP increase carbon emissions both in the short and long term. However, the use of RE hurts carbon emissions and is associated with sustainable development in OECD countries. Therefore, it is assumed that although fossil fuel use degrades the environment, economic growth helps it by reducing carbon emissions. Overall, our study shows that the use of RE is essential for OECD countries to achieve their environmental sustainability goals because it reduces the share of fossil fuels in the overall energy mix. Furthermore, in order to achieve a sustainable environment, OECD countries are recommended to begin long-term planning to reduce carbon emissions. Full article

The COVID-19 pandemic has inflicted structural shocks on the global economic system by raising high economic uncertainty. Policymakers are exploring alternative measures and incentivizing foreign direct investment for the restoration of global economic operations to achieve short- and long-term growth. Given this, the study examines the global response of FDI inflow to measure the change in productive capacity. The productive capacity is proxied by structural change, private business sector, institutional quality, transportation infrastructure development, and natural capital. The study implements empirical analysis for a large panel of 170 countries in a data set from 2000 to 2021. Furthermore, the study employed the cross-sectional augmented auto-regressive distributed lag (CS-ARDL) econometric estimation method for better examinations of current changes in an economic outbreak. From the results of the study, the estimations reveal that FDI inward has significant positive impact over the private business sector, institutional quality, transportation infrastructure, and natural capital on inward FDI. In accordance with discussions, the study suggests several pragmatic policy implications to achieve maximum output by utilizing the inward FDI as incentivized by the governments of the selected countries. Full article

The present study intends to scrutinize the asymmetrical influence of economic growth, industrial production, CPI (consumer price index) and oil price on the trade deficit for the People’s Republic of China’s economy. The Toda–Yamamoto causality, non-linear ARDL method, and quarterly data for 1995Q1 to 2021Q4 have been utilized to investigate the results. The estimated results confirm the uni-directional causality and presence of non-linear co-integration among variables under discussion. However, bound test analysis also reveals the long-run asymmetrical association among TD (trade deficit), IP (industrial production), oil price, and GDP growth, but not the CPI (consumer price index). Further, long-run asymmetrical outcomes highlight that a decrease (increase) in industrial production and an increase (decrease) in oil price and GDP growth rate increase (decrease) the trade deficit. Short-run asymmetrical outcomes reveal a similar trend to the long run, but the impact of all variables in the short run is insignificant, which means that linkages between the trade deficit and the explanatory variables are a long-run phenomenon in People’s Republic of China. Thus, in terms of policy, to reduce the trade deficit, it is necessary to focus on attaining standardized GDP growth, increasing industrial-sector production using advanced technology, and replacing oil-using energy sources with green technology (solar panels, wind farm energy). Full article

In the current era of digital economy, the role of information communication and technology (ICT) and economic complexity are important for controlling environmental unsustainability and formulating policies to deal with ecological concerns. However, the relationship between digital economy and environment has been studied widely; nevertheless, the relationship between ICT-based digital economy, economic complexity, and ecological footprint has not been studied extensively. Therefore, the aim of current study is to fill the existing gap by investigating the relationship between ICT, economic complexity, and ecological footprint in the case of G-seven (digital) economies. Furthermore, the past research studies were usually based on carbon emissions to measure environmental sustainability, while this study fills the gap using ecological footprint as a proxy for environmental degradation. By using the panel data over the period of 2001–2018 for G-seven economies, this study performs first-generation as well as second-generation unit root testing methods. Findings of both Pesaran’s and B&P’s cross-sectional dependence testing approaches confirm the presence of cross-sectional dependence across all G-seven economies. The empirical findings of cointegration (Pedroni and Kao) tests verify a stable long-run association between ecological footprint, ICT import, ICT export, economic complexity, economic growth, and other control grouped variables. The empirical evidence obtained from the fully modified OLS model suggests that ICT export, economic complexity, and economic growth enhance the intensity of ecological footprint, while ICT import, research and development (RD), and trade are helpful in reducing ecological footprint in G-seven economies. These empirical findings obtained are verified by pooled mean group-ARDL (PMG-ARDL) methodologies and confirm that there is no inconsistency in the results. On the basis of these results, some policy implications for ecological footprint, ICT, and economic complexity are discussed. Full article