ABSTRACT The current study looks into the impact of green finance on carbon emissions (CO 2 ) in BRICS (Brazil, Russia, India, China and South Africa) countries. It utilised balanced panel data from 2000 to 2023. The current study integrates long‐term dynamic estimation and conditional process analysis (CPA) to comprehend the channels of influence, both temporally and structurally. We apply the cross‐sectionally autoregressive distributed lag model to determine the short‐ and long‐term impacts of green finance on emissions by considering cross‐sectional dependence. Following this, we use CPA, which uses fixed‐effects panel regressions to examine the hypothesis of whether green technological innovation mediates green finance and carbon emissions. In addition, we examine how green fiscal policy might moderate both direct and indirect effects. Our findings demonstrate that in the long run, green finance positively influences carbon emissions. Despite this, green technology innovation also affects emissions in the transition period. Notably, green fiscal policy plays a crucial role in modifying this relationship: it mitigates the emissions‐increasing impact of innovation while enhancing the emissions‐reduction effects of green finance. Furthermore, the analysis of bootstrap evidence demonstrates the evidence of moderated mediation, which means that the indirect impacts of green finance using innovation are much more emissions‐reducing when enhanced by the increase in the level of fiscal policy. Finally, the findings presented in this paper emphasise the necessity of avoiding using only financial tools; effective decarbonisation in developing economies requires having well‐developed fiscal systems.

Purpose This paper employs yearly data from 1965 to 2022 to examine carbon dioxide emissions (CO2), real GDP (Y), GDP per capita (Y2), energy use (EU) and economic policy uncertainty (EPU) in Australia, China, India, Japan, South Korea, Malaysia, New Zealand, the Philippines, Singapore and Thailand. Design/methodology/approach The constraint test for the autoregressive distributed lag model evaluates the sufficiency of both short- and long-term fitness. Findings The findings indicate a positive correlation between the EU and carbon dioxide (CO2) emissions in Australia, China, South Korea and Japan during a limited time. Nevertheless, it is worth noting that only Japan and New Zealand exhibit a positive link between energy consumption and carbon dioxide emissions over an extended period. The link between GDP and GDP per capita and CO2 emissions varies across various nations. Originality/value The study provides country-specific evidence on the relationship between economic policy uncertainty and CO2 emissions in the Asia-Pacific region. The results indicate that the effects of economic policy uncertainty on emissions are heterogeneous across countries, with no uniform short-run or long-run pattern. These findings highlight the importance of context-specific environmental and economic policies rather than one-size-fits-all approaches.

This study aims to analyze the dynamic impact of leverage risk and capital structure on the market capitalization of a sample of Iraqi commercial banks listed on the Iraq Stock Exchange over the period 2004–2024, using annual time-series data. The Autoregressive Distributed Lag (ARDL) model was employed after testing the stationarity of the study variables using the Phillips–Perron test. The results of the bounds test indicate the existence of a long-run equilibrium relationship among the study variables. Furthermore, the ARDL model explains approximately 97% of the variations in market capitalization. The findings reveal that some leverage indicators have a statistically significant negative effect on market capitalization, while the impact of capital structure appears weak and varies in terms of statistical significance. Additionally, the regression results suggest that financing variables explain only a limited proportion of fluctuations in market value despite their statistical significance, reflecting the influence of other market and financial factors on stock pricing. This study provides empirical evidence from the Iraqi banking sector on the dynamic relationship between leverage, capital structure, and market capitalization within an emerging financial environment.

The deployment of agricultural inputs considerably influences national agrarian output, which is a key driver of economic growth. This study contributes to the literature by examining how changes in crop yield growth reflect resource allocation in agricultural production. Data spanning 1994 to 2019, obtained from the World Bank, were used to examine the impact of agricultural input productivity on agricultural output. The 26-year time-series data were employed for the Organization for Economic Co-operation and Development (OECD) and Latin American Caribbean (LAC). The findings from the Autoregressive Distributed Lag model, along with the Vector Error Correction Model, reveal a negative but significant long-term impact of agricultural land use on crop yields in OECD, and a negative and insignificant impact in LAC countries. Moreover, agricultural land use showed a positive but insignificant short-run effect on crop yield in OECD countries, while a negative and insignificant short-run effect was observed in LAC countries. This study highlights disparities in agricultural productivity drivers between OECD and LAC regions. By linking productivity dynamics with input utilization, the analysis provides policy-relevant insights for improving sustainability, food security, and agricultural productivity.

Purpose Deforestation remains a major environmental concern in Sierra Leone, with implications for biodiversity, climate change and livelihoods. This underscores the urgency for sustainable forest practices. The study investigated the socio-economic determinants of deforestation in Sierra Leone. Design/methodology/approach The study used annual time series data within a vector error correction and autoregressive distributed lag model to estimate both the short- and long-run drivers of deforestation in Sierra Leone. Forecast error variance decomposition and impulse response function were also employed to determine the magnitude and direction of shocks. Findings The decomposition of forecast error variance shows that biomass consumption (traditional renewable energy consumption) is the short-, medium- and long-term dominant factor. Income is found to reduce deforestation in the short term, while biomass consumption (traditional renewable energy consumption) increases it. Weak institutions, biomass consumption (traditional renewable energy consumption), natural resource rents and population increase deforestation in the long run. Originality/value The study contributes to the deforestation literature by providing new empirical evidence on the long- and short-run drivers of forest loss in Sierra Leone using a dynamic econometric framework that integrates institutional quality, income, population, natural resource rents and energy consumption. By distinguishing temporal effects and governance channels, the study advances understanding of how structural and policy factors interact over time to shape deforestation outcomes in resource-dependent developing economies, offering insights for sustainable forest management.

A strong transportation infrastructure is critical in advancing ICT trade by facilitating the efficient movement of goods and services. This efficiency enhances supply chains and attracts greater foreign direct investment, ultimately supporting technological development and boosting the economy. This article evaluates the relationship between transportation infrastructure (TI), information and communication technology trade openness (ICT trade), foreign direct investment (FDI), and economic growth (GDP) in Saudi Arabia from 1990 to 2023. Using the Autoregressive Distributed Lag (ARDL) model, we found that ICT trade has a statistically significant positive effect on long-run GDP growth. However, in the short run, ICT trade has a positive but non-significant impact on GDP growth. Additionally, the results show that TI has a statistically significant negative effect on short-run GDP growth. Moreover, the non-linear Threshold Regression model results show a threshold value for information and communication technology trade openness (ICT trade) of approximately 0.4051. Specifically, the findings indicate that increased ICT trade reduces the negative impact on economic growth beyond a certain threshold. This study is highly significant for Saudi Arabian decision-makers, as it highlights the roles of transportation infrastructure and ICT trade in attracting FDI and bolstering the economy.

The aim of the article is to study the factors that influence the bank short-term and long-term interest rates. The relevance : in modern conditions the interest rate policy is considered not only as a way to ensure bank efficiency and financial stability, but also as a tool to stimulate economic activity. The purpose of the study is to identify the factors that determine the short-term and long-term interest rates and, on this basis, to determine economic and/or regulatory measures to improve the bank interest rate policy for the purposes of national economy. The scientific novelty includes the identification of the factors that determine the banking interest rate policy in the short-term and longterm aspects. The research methodology is based on statistical modeling using the vector autoregressive distributed lag model. The statistical database includes the Russian banking sector financial indicators and a significant range of macroeconomic variables. Results . The authors identified the factors of bank loans interest rates. The key parameters include macroeconomic variables: the money market interest rate and the structural liquidity deficit of the banking sector. The impact of macroeconomic parameters differs with respect to long-term and short-term rates, as nominal GDP is significant only for long-term interest rates. Loan portfolio quality indicators do not affect interest rates. Based on the study's findings, the authors proposed directions to develop the current banking regulation: to set regulatory alignment between the credit risk premium and the loan loss reserve requirement; to limit the corporate floating rates lending; to introduce an additional credit instrument of the Bank of Russia —a secured loan to systemically important banks for a one year.

In this modern era, investigating the factors influencing energy intensity is a valuable area of research. Although numerous studies have explored the influence of macroeconomic variables on energy intensity, limited research has addressed its asymmetric effects. Recognizing the significance of asymmetries, this study investigates the non-linear impacts of urbanization, industrialization, financial development and education on both aggregate and disaggregate energy intensity in Pakistan. This study utilized data for the period 1972–2022 and followed a relatively new estimation technique: the non-linear autoregressive distributed lag model. The empirical outcomes demonstrated that urbanization and industrialization have a constructive influence on aggregate and household energy intensity, while their impact is adverse in the case of industrial sector energy intensity. The financial development confirmed a constructive influence on both household and industrial sector energy intensity, while its impact was found to be the opposite in the case of aggregate energy intensity. Education exerts a constructive influence on disaggregate energy intensity in the industrial sector and on household energy intensity, while there is an adverse relationship in the case of aggregate energy intensity. These findings suggest that to reverse the rising trend of energy intensity, it is crucial to focus on enhancing basic infrastructure in rural areas and adopting energy-efficient production techniques. Besides this, sound financial systems in the industrial sector and improving education levels also diminish energy intensity and enhance production under the current status quo of the Pakistan economy.

Abstract This study investigates the determinants of greenhouse gas (GHG) emissions in Morocco, a country that has recently recorded an improvement in national economic growth, reaching 5.5% in the second quarter of 2025 (HCP, [24]). However, the country faces a growing dependence on fossil fuels, amounting to 90.36% according to the Ministry of Energy Transition and Sustainable Development (MEM, [33]), and the share of renewable energy in the national energy mix remains limited despite significant efforts. In a global context marked by ecological crisis and economic challenges, which urges developing countries to adopt more resilient models, Morocco continues to rely heavily on fossil fuel imports, the main sources of pollution and environmental imbalance. This situation calls for an examination of how the drivers behind this strong dependence and the growth-related factors contribute to GHG emissions? To this end, the research employs an ARDL (Autoregressive Distributed Lag) model, a methodological approach still rarely used in the Moroccan context, enabling the assessment of both short- and long-term relationships among the variables under study. The results show that fossil fuel consumption and economic growth are the primary drivers of rising GHG emissions. In contrast, the share of renewable energy has no statistically significant effect on emission reduction, underscoring its still marginal role in the country’s energy transition. Furthermore, the analysis reveals strong inertia in emissions, which remain locked into historical trajectories and adjust only slowly to new dynamics. These findings highlight the urgent need to implement more ambitious and coherent energy policies aligned with climate objectives. Beyond accelerating the adoption of clean energy sources, Morocco must establish effective mitigation mechanisms, strengthen regulatory and fiscal instruments, and address structural lock-ins that maintain high emission levels. Such measures are essential to break the cycle of persistent emissions and guide the country toward a more resilient and sustainable development trajectory.

Based on the Autoregressive Distributed Lag (ARDL) method, this paper assesses the effects of international trade on the economic growth of India starting in 1980 and up to 2025. Since India has been opening up to international trade after undergoing major economic reforms, the trade-growth relationship has become essential. The ARDL model offers a sound model in the analysis of both short-term and long-term dynamic relationships to investigate the relationship between exports, imports, and GDP growth. The results indicate that there is a strong long term equilibrium relationship between these variables and the co-integration is indicated by F-statistic of 5.22 and a p-value of 0.0042. This implies that trade variables play an important role in the long run-in affecting GDP. Conversely, short-term dynamics, examined by the Error Correction Model (ECM) and Wald tests, show that immediate variation in trade variables has minimal impact on a GDP with p-values indicating that there is no significant short-run causality. The paper emphasizes the need to focus on long run trade strategies to make use of the economic growth as well as demonstrates that short run fluctuations in trade do not have a significant effect on GDP. The insights could be useful to the policy makers who seek to establish effective trade policies that will result in sustainable economic development in India. Keywords: International Trade, ARDL Approaches, Economic Growth, GDP, Error Correction Model

Ecological effects of income inequality, financial development, and natural resources in E7 Countries

The effect of climate change on food security in ethiopia using auto-regressive distributed lag model

Abstract This study examines the effect of inflation on economic growth in Somalia using annual time-series data spanning 1990–2023. Given Somalia’s prolonged institutional fragility and limited monetary policy capacity, understanding the inflation–growth relationship is particularly important for macroeconomic stabilization. The analysis employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to estimate both short-run and long-run dynamics, with government expenditure, foreign direct investment, gross capital formation, and external debt included as control variables. Unit root tests confirm mixed orders of integration, justifying the use of the ARDL framework. To ensure robustness, the long-run results are validated using Dynamic Ordinary Least Squares (DOLS) and Canonical Cointegrating Regression (CCR) estimators. The findings indicate a stable long-run cointegrating relationship among the variables. Inflation exerts a negative and statistically significant effect on economic growth in both the short and long run. Specifically, a 1 percent increase in inflation reduces GDP per capita growth by approximately 0.22 percent in the long run. Government expenditure positively contributes to growth, while foreign direct investment exhibits a negative effect, reflecting structural and institutional constraints. Gross capital formation is statistically insignificant, suggesting inefficiencies in investment utilization, while the effect of external debt varies depending on its allocation. Overall, the results underscore the importance of price stability, efficient public spending, and improved investment governance for sustaining long-term economic growth in Somalia.

ABSTRACT Cross-border financial flows can catalyse growth in emerging economies, yet evidence is mixed because many studies pool heterogeneous inflows and use narrow proxies for financial innovation. Using annual data for Brazil, Russia, India, China, and South Africa from 2005 to 2022, we examine how the composition of external finance, including foreign direct investment, portfolio flows, external debt, remittances, and official development assistance, interacts with domestic financial innovation measured by a multidimensional index of inclusion, depth, stability, literacy, and digital adoption. We estimate panel autoregressive distributed lag models with a pooled mean-group estimator to separate long-run effects from short-run dynamics, and we apply nonlinear specifications and instrumental-variable approaches to test asymmetries and address endogeneity. Results show that foreign direct investment and remittances support long-run growth, whereas portfolio flows and external debt coincide with weaker outcomes. Financial innovation directly raises growth, enhances the payoff from productive inflows, and attenuates the drag of debt-based financing. The study clarifies how flow composition and innovation capacity jointly shape growth and offers policy guidance on financial development and digital finance reforms that turn external resources into sustained growth.

Purpose This study aims to investigate non-interest-bearing real estate acquisition and investment as financed across four countries, namely, Saudi Arabia, Malaysia, Indonesia and Pakistan. Design/methodology/approach This paper used a quantitative research approach. It employed a Nonlinear Autoregressive Distributed Lag and Autoregressive Distributed Lag model techniques, using quarterly data from 2014Q1 to 2024Q2 for analysis. Findings The findings indicate that financing Mudarabah is stronger in Indonesia than in other non-interest-bearing real estate acquisitions and investments. They also demonstrated that Musharakah and Musharakah-mutanakisah have a significant influence on Mudarabah financing, particularly in Malaysia and Pakistan, but not in Saudi Arabia. The findings also revealed that Musharakah and Musharakah-Mutanakisah asymmetrically and significantly predict Mudarabah financing. Research limitations/implications Data constraint is one of the main limitations of this study. Most Islamic banks that provide their information on the Islamic Financial Services Board database do not provide detailed information that could be used for analysis. Therefore, the analysis was restricted to four Asian countries. Insufficient data for including Murabahah in this study supports the conclusion of some researchers that Murabahah attracts less attention from Islamic banks as a means of financing. Practical implications The findings of this study have practical implications, suggesting that in the presence of asymmetric information, Islamic bank stakeholders possess different levels of information regarding similar contracts. This discrepancy could lead the fund provider to withdraw the investment deposit from the bank, potentially affecting its economic viability. Therefore, intervention by authority is crucial for contract financing, particularly when asymmetric effects are present, before the triple effect of asymmetric information impacts the national economy in countries where asymmetric information is significant. Originality/value This study is unique in employing asymmetric modelling to provide the presence of long-run effects and asymmetric relationships across the countries under study. The findings from this study provide insight into real estate portfolio managers, authorities and prospective investors in non-interest-bearing real estate acquisition and investment across four countries.

This study aims to investigate the asymmetric effects of changes in international prices of energy and food and the monetary variables, including exchange rates and policy interest rates, on consumer price index (CPI) inflation in Indonesia. This study employs the Nonlinear Autoregressive Distributed Lag (NARDL) model for the period July 2005 to December 2023. The findings indicate that increases in global food prices led to a significant rise in the Consumer Price Index (CPI), indicating inflation. The study also provides empirical evidence of the asymmetric effect of changes in international food prices on the CPI. The exchange rate emerged as the variable with the most influence on inflation, with the depreciation and appreciation of the local currency. Lessons from these findings, in implementing monetary policy, authorities need to focus on inflation originating from supply shocks, which are influenced by changes in global energy and food prices and exchange rates.

Abstract This research investigates the intricate dynamics of waste-to-energy technology adoption within European Union countries, providing critical insights for sustainable waste management. Using a robust methodology, including comprehensive data analysis and the cross-sectional autoregressive distributed lag model, we examine both short-term and long-term factors influencing WtE adoption. Our findings reveal a pronounced short-term uptake of waste-to-energy technologies in regions with established incineration infrastructure, echoing successes in countries such as Sweden. However, a detailed long-term analysis reveals challenges, underscoring the need for public engagement and ongoing technological innovation, which aligns with circular economy principles. The role of advanced environmental technology emphasizes the importance of sustained development for effective waste management practices. Additionally, a stable primary energy supply is critical in facilitating waste-to-energy adoption, as demonstrated by Sweden. By integrating demand-based CO 2 emissions into waste-to-energy policies, our research aligns with global commitments to reduce carbon emissions. We advocate for a holistic approach that considers historical infrastructure, technological advancements, energy supply, and environmental concerns, seamlessly integrating circular economy principles into the waste-to-energy framework. Ultimately, this research provides a comprehensive understanding of waste-to-energy adoption dynamics, emphasizing the urgent need for transformative practices and urging policymakers and stakeholders to develop resilient and eco-friendly WtE strategies across the European Union.

This study looked at how taxes and government capital expenditures affected Nigeria's economic growth. Secondary time series data from 1992 to 2021 make up the data set used in this investigation. The Granger Causality Test Result and Autoregressive Distributed Lag Model (ARDL) were employed in the study to describe the relationship's direction. According to the findings, the percentage of changes in the dependent variable that can be accounted for by the independent variables is indicated by the coefficient of determination (R2). Economic growth may be described by changes in the explanatory variables as shown by the model, according to the R2 of 0.614087, or 61%. The dummy variable accounts for 49% of the explanation. The model is significant at 5%, according to the F-statistic, which suggest the model's overall importance. The F-statistics and its probability (4.177050 and 0.004027, respectively) support this. Therefore, the study comes to the conclusion that taxes and government capital expenditures significantly contribute to Nigeria's economic growth. As a deterrence to others, this study suggests, among other things, that the government impose a death penalty on people who divert funds from the petroleum profit tax and misappropriate government capital expenditures.

Abstract Purpose This study explores the impact of health capital on economic growth, employing an ARDL model with data from 2000 to 2022. The aim is to assess the contribution of health capital, alongside other key macroeconomic variables, to the economic performance of the country. Findings The results show that health capital plays a significant positive role in economic growth, with improvements in health contributing to higher productivity and overall economic development. Education expenditure, however, exhibits a negative long-term impact, suggesting inefficiencies in public spending. Gross fixed capital formation and trade openness emerge as key drivers of economic growth, reinforcing the importance of investment in infrastructure and global integration. The findings also highlight the importance of maintaining macroeconomic stability to ensure sustained growth. Implications Policymakers should prioritize investments in health capital while improving the efficiency of public education spending. The results further emphasize the role of physical capital accumulation and trade openness in supporting economic growth, alongside the need for sound fiscal and monetary policies to maintain macroeconomic stability. Originality/value This study provides country-specific evidence on the role of health capital in long-term economic growth by integrating health, education, and key macroeconomic variables within a unified ARDL framework. The findings offer valuable insights for policymakers in Bangladesh and other emerging economies seeking to balance growth acceleration with economic stability.

Recently, Indian economy has experienced strong Foreign investment flows through Foreign Direct Investment(FDI) and Foreign Portfolio Investment (FPI). It's long term trend highlighted economy has received $748.78 billion through FDI since 2014-2025 whereas FPI has been boosted by equity market gains with total FPI asset under custody hitting $858 billion. A healthy and vibrant industrial sectors of capital markets is important for development of a nation. In the present scenario, sectors of Foreign investment in Indian economy for instance Automotive, Pharmaceuticals, Information Technology (IT), Textiles, Construction, power, equity segment and assets under custody (AUC) have attracted attention of investors to invest in these Industries particularly. This paper attempted to analyse some of sectors and their impact on Industrial Development in India by foreign investors. The present study is based on quantitative data and used secondary data of annual time series. Data has been collected from the report of Reserve Bank of India, Department for Promotion of Industry and Internal Trade (DPIIT),world Bank report etc. To study the impact methods are practised such as comparative sectorial analysis, Autoregressive Distributed Lag (ARDL) and Garch model has been used to estimate volatility spillovers of FPI to sectoral output. The results indicated strong and positive long-run relationship with capital intensive, technology-based sectors hence leading to stable output growth and value addition. On the contrary, the FPI inflows showed a strong but volatile connection between FPI inflows and construction and power industries, which is highly vulnerable to market sentiment. However, it was observed from study that the investment activities in industrial sectors of FDI and FPI have had significant impact on Indian economy.