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The present study aims to investigate the non-linear relationship between trade and income inequality to address goal 10 of sustainable development goals (SDGs) using the Kuznets Curve (KC) framework for major emerging countries during 1991–2020.

For this purpose, recent econometric techniques, such as Common Correlated Effect (CCE) and Dynamic Common Correlated Effect (DCCE) estimators have been employed to deal with the cross-section dependence (CD) that arises in panel data, while the robustness of the study is checked through Driscoll–Kraay standard errors method.

The empirical results of the study confirm the existence of inverted “U-shaped” relationship between trade and income inequality suggesting evidence for the trade-led KC in the panel of emerging countries. Along with the non-linear model, the threshold value is estimated to be between 3.5 and 4% of gross domestic product (GDP).

The authors' findings support that trade contributes significantly toward reducing income inequality and helps in achieving goal 10 of SDGs. Hence, trade policies appear to be more egalitarian. The results widen the scope for further research and provide insights for regulators and policymakers in modeling trade policies and changing the status quo trade policy framework accordingly.

The present study is a pioneering attempt to examine the non-linear relationship between trade and income inequality under the KC framework in light of the Agenda 2030 for sustainable development. The study also considers other explanatory factors that have an impact on income inequality. Furthermore, the study considers other explanatory factors that have an impact on income inequality, and the attempt to estimate the threshold value for the trade-led KC is novel and interesting.

Despite the longstanding male dominance in the socio-politico-economic spheres, recent decades have witnessed remarkable improvements in gender inclusion. Although the issue of gender inclusion has been widely documented, answers to the question of whether institutional arrangements and information technology shape gender inclusion remain contentious. This study, therefore, empirically examines the effects of institutional quality and ICT penetration on gender inclusion on a global scale.

To control for the endogeneity of modeled variables and cross-sectional dependence inherent with large panel datasets, the study employs the Driscoll-Kraay Fixed Effects (DKFE) and the system Generalised Method of Moments (GMM) estimators for a panel of 142 countries from 1996 to 2020.

The empirical findings from the DKFE and system GMM estimators reveal that strong institutions significantly enhance gender inclusion. Moreover, by disaggregating institutional quality into various governance indicators, we show that besides corruption control, which has a positive but insignificant effect on women’s empowerment, other governance indicators significantly enhance gender inclusion. Furthermore, there is evidence that various ICT measures promote gender inclusion.

The study results suggest that policymakers in developing countries should implement stringent measures to curb corruption. Moreover, policymakers in low-income countries should create avenues to facilitate women’s access to ICTs. Hence, policymakers in low-income countries should create and equip ICT training centers and render them accessible to all categories of women. Furthermore, developed countries with high-tech knowledge could help developing countries by organizing free training workshops and sensitization campaigns concerning the use of ICTs vis-à-vis women empowerment in various fields of life.

The present study fills a significant research gap by comprehensively exploring the nexuses between governance, ICT penetration, and the socio-politico-economic dimensions of gender inclusion from a global perspective. Besides the paucity of studies in this regard, the few existing studies have either been focused on region and country-specific case studies in developed or developing economies. Moreover, this study is timely, given the importance placed on gender inclusion (SDG5), quality of institutions (SDG16), and ICT penetration (SDG9) in the 2015–2030 global development agenda.

The present study aimed to examine the effect of received remittance inflows on the price level ratio of the purchasing power parity conversion factor to the market exchange rate in 36 developed and developing countries from 2004 to 2020.

The panel data conducted a comparative analysis and used panel least squares, regression with Driscoll-Kraay standard errors of fixed effect, random effect, feasible generalised least squares and maximum likelihood robust least squares to overcome the heterogeneity issue. Furthermore, the two-step difference generalised method of moments to overcome the endogeneity issue. Diagnostic tests were used to increase robustness.

In the studied countries, there was a statistically significant negative relationship between received remittance inflows and the price-level ratio of the purchasing power parity conversion factor to the market exchange rate. This relationship explains why remittance flows depreciate the real exchange rate. The study’s results also indicated that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue.

The current study findings enrich the understanding of policies of how governments should minimise tariff rates on capital imports and introduce export-oriented incentive programmes. The study also revealed that Dutch disease can occur due to differences in the demand structure and manufacturing development policy.

This paper analyzes the direct effect of financial development and the mediating impact of financial development through foreign direct investment (FDI), foreign aid and trade on economic growth for all Asian countries.

A fixed-effect model with Driscoll–Kraay panel corrected estimators was employed to find the direct and mediating impact of financial developments on growth for all 47 Asian economies from 1980 to 2020. The bootstrapped panel-quantile regression (BPQR) model is used to check how this effect varies for different income groups of countries.

The results demonstrated that financial development positively impacts countries' economic growth. The interaction effect of financial development with FDI, foreign aid and foreign trade negatively impacts economic growth. The BPQR results showed that FDI and foreign aid help in the growth of lower quantile economies; however, the impact is negative for middle- and upper-income countries. Trade impacts growth positively for all the quantiles of economies.

The results suggest that the Asian economies must continue to provide thrust on the financial development of their own countries to achieve better growth. It also implied that the dependence on external finance is good for low-income countries and not advisable for middle- and upper-income countries.

To the best of the authors’ knowledge, the current study is the first to provide empirical evidence on analyzing both the direct and interaction effect of financial development on economic growth by considering all the Asian economies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0587

Studies on sustainable finance examine how it is interrelated with economic, social, governance and environmental issues. Using financial data on publicly traded firms in Indonesia, this study aims to explore the interplay between the cost of capital, firm performance and the COVID-19 pandemic.

This study uses firm-level data sets of publicly listed firms from 2012 to 2021. The regression analysis reported in the study includes the Driscoll–Kraay estimator, propensity score matching model and fixed-effects regression.

The study revealed three significant findings. First, on average, non-environmental, social and governance (ESG) companies’ cost of capital is lower than that of ESG firms. Second, ROE in ESG enterprises is significantly impacted by capital costs. Third, the cost of capital has a negative impact on the market value (Tobin’s q) of non-ESG firms. The study specifically shows that after accounting for the pandemic, ESG firms did not benefit during the troubled COVID-19 crisis after controlling for the pandemic dummy years of 2020 and 2021. These results indicate that the adoption of green or sustainable finance is still in its infancy and that the sector requires more time to establish an enabling environment.

This study benefits from capital structure and ESG theories. It supports the argument that the debt utilization ratio is still relevant to a company’s value because it affects its financial performance. Moreover, adopting ESG principles helps businesses survive crises. Thus, the analysis confirms the superiority of ESG-based firms.

This study draws two conclusions. First, the results could be a reference for academics and practitioners to understand the effect of pandemic-related crises on a firm’s capital structure and performance. In terms of survival during a crisis, such as the COVID-19 pandemic, this study demonstrates how firms with strong ESG may perform differently than those without ESG. Second, this study supports the need for an empirical study and examination of the development of sustainable finance in the country while considering setbacks.

The results should be of interest to policymakers who focus on the ESG market and academics conducting ESG-related research on emerging markets.

This study contributes to the literature by establishing empirical evidence on the relationship between the cost of capital and firm performance of ESG- and non-ESG-rated enterprises in the Indonesian setting while controlling for the impact of the pandemic.

The Russian export flow is highly concentrated on few trading partners that results in its high vulnerability to external shock. Furthermore, the Russian–Ukraine conflict and corresponding western sanctions has enhanced the need of export markets diversification for Russia. Therefore, this study is a baseline attempt to explore determinants of export flow along with identifying potential export markets. This objective is realized by employing an augmented version of gravity model on export flow of Russian Federation to 108 trading partners from 2000 to 2020.

The augmented gravity model of export flow is estimated by using employing contemporary panel econometrics such as panel generalized ordinary least square estimation technique with cross-sectional weight along with heteroskedasticity consistent white coefficients is employed to explore impact of selected macroeconomic and policy variables. Furthermore, the sensitivity analysis is performed by using panel random effect along with the Driscoll–Kraay standard errors with pooled ordinary least squares (OLS) regression and random effect generalized least square (GLS) estimator techniques. The estimated result of panel GLS technique is subjected to in-sampled forecasting technique to explore potential export markets.

The findings show that an increase in the income of trading partners and enhancement of domestic production capacity has significant positive impact on Russian export flow, whereas geographic distance has a significant negative impact. Income of trading partners emerged as major determinant of export flow with high explanatory power. Among augmented variables, the real exchange rate reveals a significant positive impact of lower intensity, whereas binary variables for the common border, common history and preferential/free trade agreement show a significant positive impact. The finding of export potential reveals a high concentration of export with existence of large potential for exports across the globe. For instance, many developing countries in Asia, Africa and America reveal high potential for Russian exports.

The findings urge Russian Federation to diversify its export markets by targeting potential export markets. Many emerging developing countries are witnessing a high potential for Russian exports, therefore attempts should be taken to diversify toward them. The expansion of existing transportation facilities along with development of cargo trade can be important policy instrument to realize objective of export diversification.

This study is the first comprehensive analysis that employs augmented gravity model to explore potential export markets for Russian Federation by using panel data of 108 global trading partners from 2000 to 2020. This finding of this study provides a framework of export diversification toward potential markets across the globe.

Growing food insecurity is a leading cause of fatalities, particularly in developing nations like Sub-Saharan Africa and Southeast Asia. However, the rising energy consumption and carbon dioxide (CO2) emissions are mostly associated with food production. Balancing the trade-offs between energy intensity and food security remains a top priority for environmentalists. Despite the critical role of the environment in food security, there is a scarcity of substantial studies that explore the statistical connections among food security, CO2 emissions, energy intensity, foreign direct investment (FDI) and per capita income. Therefore, this study aims to provide more precise and consistent estimates of per capita CO2 emissions by considering the interplay of food security and energy intensity within the context of emerging economies.

To examine the long-term relationships between CO2 emissions, food security, energy efficiency, FDI and economic development in emerging economies, this study employs correlated panel-corrected standard error, regression with Newey–West standard error and regression with Driscoll–Kraay standard error models (XTSCC). The analysis utilizes data spanning from 1980 to 2018 and encompasses 32 emerging economies.

The study reveals that increasing food security in a developing economy has a substantial positive impact on both CO2 emissions and energy intensity. Each model, on average, demonstrates that a 1 percent improvement in food security results in a 32% increase in CO2 levels. Moreover, the data align with the Environmental Kuznets Curve (EKC) theory, as it indicates a positive correlation between gross domestic product (GDP) in developing nations and CO2 emissions. Finally, all experiments consistently demonstrate a robust correlation between the Food Security Index (FSI), energy intensity level (EIL) and exchange rate (EXR) in developing markets and CO2 emissions. This suggests that these factors significantly contribute to environmental performance in these countries.

This study introduces novelty by employing diverse techniques to uncover the mixed findings regarding the relationship between CO2 emissions and economic expansion. Additionally, it integrates energy intensity and food security into a new model. Moreover, the study contributes to the literature by advocating for a sustainable development goal (SDG)-oriented policy framework that considers all variables influencing economic growth.

Despite the importance of tax policy in reducing energy consumption and carbon emissions, there is a dearth of research on the environmental impact of indirect taxes. This paper examines the impact of indirect taxes on carbon dioxide (CO₂) emissions, with an emphasis on institutional quality.

The study uses the Government Revenue Dataset (2021), comprising 143 countries, dividing into 114 developing and 29 developed countries, during the period between 1996 and 2019. The author adopts panel data techniques, with Driscoll–Kraay standard errors to account for the issue of cross-sectional dependence (CSD).

The results indicate that indirect tax revenues have a negative and significant impact on CO₂ emissions for the total sample. The subsample analysis revealed that while indirect taxes reduce carbon emissions in developing countries, opposed results are reported for developed countries. This finding implies that most of the advanced countries have already reached a high level of taxes, at which carbon emissions increase as indirect tax increases further. Interestingly, the results revealed that institutional quality enhances the role of indirect taxes in mitigating carbon emissions for both developing and developed countries.

To the best of the authors' knowledge, this is the sole study using the newly developed tax data by the United Nations University, World Institute for Development Research (UNU-WIDER) to investigate the impact of indirect taxes on carbon emissions, with an emphasis on institutional quality. The existing literature focuses on specific taxes, like carbon taxes, with no comprehensive research on the link between indirect taxes and carbon emissions.

The study examines the presence of the pollution haven or pollution halo hypothesis in Brazil, Russia, India, China and South Africa (BRICS) and Next-11 economies. Hence, it empirically tests the direct impact of foreign direct investment (FDI) on the ecological footprint. Further, it explores the moderating role of green innovation on the nexus between FDI and ecological footprint.

The study uses the Driscoll–Kraay (DK) standard error panel regression technique to examine the long-run elasticities amongst the variables for the group of emerging countries, BRICS and Next-11, during the period of 1992 to 2018. Further, statistical robustness is demonstrated using the fully modified ordinary least squares technique.

The empirical finding shows that FDI degrades environmental quality by raising the ecological footprint. Thus, it proves that FDI is a source of pollution haven in BRICS and Next-11 countries. However, green innovation negatively moderates the relationship between FDI and ecological footprint. That means the joint impact of green innovation, and FDI proves the presence of the pollution halo hypothesis. Further, renewable energy consumption is reducing the ecological footprint, but economic growth and industrialisation are worsening the environmental quality.

This study offers policy implications for governments and policymakers to promote environmental sustainability by improving green innovation and allowing FDI that encourages clean and advanced technology.

No prior studies examine the moderating role of green innovation on the relationship between FDI and ecological footprint in the context of emerging countries.

This paper aims to investigate the link between uncertainty in banking and bank lending behavior, particularly shedding light on the modifying role of bank competition in the nexus.

The study uses a panel of Vietnamese banks over the 2007–2019 period for empirical analysis and the dispersion of shocks to bank-level variables to measure banking uncertainty. To strongly confirm our findings, the authors perform a battery of alternative checks based on different econometric techniques, including fixed effect regressions with Driscoll–Kraay standard errors, the two-step system generalized method of moments estimator and the least squares dummy variable-corrected estimator.

Uncertainty induces multifaceted unfavorable impacts on bank lending. Concretely, banks tend to restraint loan growth, suffer more credit risk, and charge higher lending rates during periods of higher uncertainty. Further investigation reveals that lending activities of banks with greater market power are less sensitive to adverse uncertainty shocks; in other words, increased competition in the banking system is associated with more substantial consequences of uncertainty on bank lending.

To the best of the authors’ knowledge, this study is the first attempt to simultaneously explore the impacts of uncertainty on quantity, quality and prices of bank lending. This paper also aim at putting forth the level of uncertainty particularly related to the banking sector. Importantly, examining the conditionality of the linkage between uncertainty and bank lending with respect to bank competition is entirely novel.