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The study examines whether the growth effect of government spending is contingent on the level of institutional environment prevalent in Economic Community of West African States (ECOWAS).

The study adopts the more refined and more appropriate dynamic threshold panel by Seo and Shin (2016) and made applicable be Seo et al. (2019). The technique models a nonlinear asymmetric dynamics and cross-sectional heterogeneity simultaneously in a dynamic threshold panel data framework.

The results show that there is a threshold effect in the government spending-growth relationship. Specifically, the authors found that the impact of government spending on economic growth is positive and statistically significant only above a certain threshold level of institutional development. Below that threshold, the effect of government spending on growth is insignificant and negative at best. The findings suggest that government spending-growth nexus is contingent on the level of Institutional quality.

Unlike previous studies that adopt the linear interaction model which pre-impose a priori conditional restrictions, this study adopts the dynamic threshold panel framework which allows the lagged dependent variable and endogenous covariates.

This research investigates the threshold effects of the interplay between finance, development and carbon emissions across 97 countries, including 50 low-income and 47 high-income countries, during the period from 1991 to 2019.

Employing various econometric modeling techniques such as dynamic linear regression, dynamic panel threshold regression and in/out of sample splitting, this study analyzes the data obtained from the World Bank's world development indicators.

The results indicate that low-income countries require a minimum financial development threshold of 0.354 to effectively reduce carbon emissions. Conversely, high-income countries require a higher financial development threshold of 0.662 to mitigate finance-induced carbon emissions. These findings validate the presence of a finance-led Environmental Kuznet Curve (EKC). Furthermore, the study highlights those high-income countries exhibit greater environmental concern compared to their low-income counterparts. Additionally, a minimum GDP per capita of US$ 10,067 is necessary to facilitate economic development and subsequently reduce carbon emissions. Once GDP per capita surpasses this threshold, a rise in economic development by a certain percentage could lead to a 0.96% reduction in carbon emissions across all income levels.

This study provides a novel contribution by estimating practical financial and economic thresholds essential for reducing carbon emissions within countries at varying levels of development.

Insurance companies play a significant role in every economy; hence, it is essential to investigate and understand the factors that propel their profitability. Unlike previous studies that present a linear relationship, this study provides initial evidence by exploring the non-linear impacts of the determinants of profitability amongst life insurers in South Africa.

The study uses a panel dataset of 62 life insurers in South Africa, covering 2013–2019. The generalised method of moments and the dynamic panel threshold estimation technique were used to estimate the relationship.

The empirical results from the direct relationship reveal that investment income and solvency significantly predict life insurance companies' profitability. On the other hand, underwriting risk, reinsurance and size reduce profitability. Further, the dynamic panel threshold analysis confirms non-linearities in the relationships. The results show that insurance size, investment income and solvency promote profitability beyond a threshold level, implying a propelling effect on life insurers' profitability at higher levels. Below the threshold, these factors have an adverse effect. The study further points to underwriting risk, reinsurance and leverage having a reduced effect on life insurers' profitability when they fall above the threshold level.

The findings suggest that insurers interested in boosting their profit position must commit more resources to maintain their solvency and manage their assets and returns on investment. The study further recommends that effective control of underwriting risk is critical to the profitability of the life insurance industry.

The study contributes to the literature by providing first-time evidence on the determinants of life insurance companies' profitability by way of exploring threshold effects in South Africa.

This study aims to analyze the factors that influenced the stability of Islamic banks in Asia.

The panel data consisted of 16 Asian countries operating Islamic banks from 2010 to 2019. The data were analyzed through dynamic panel regression using Arellano–Bond generalized method of moments (GMM).

This study provides novel insights into the factors influencing the stability of Islamic banks in Asia. The findings suggest that past financial stability, liquidity risk, loan risk, inflation, gross domestic product, government effectiveness, rule of law and control of corruption are all significant contributors to Islamic bank stability. Notably, political stability, voice and accountability and regulatory quality did not show a significant association.

The current study’s focus was solely on Islamic bank stability in Asian countries, which leaves room for further exploration. Future research could benefit from expanding the scope to encompass all nations with active Islamic banking institutions. In addition, incorporating a broader range of macroeconomic variables, such as exchange rates, interest rates, profit-sharing equivalents and investment rates, could provide deeper insights into the factors influencing Islamic bank stability across diverse contexts.

This study has significant practical implications for policymakers, bank managers and regulatory authorities seeking to enhance the stability of Islamic banks in Asia. By implementing robust risk management frameworks, adopting prudent regulatory policies, and actively fostering economic growth, policymakers can create an environment conducive to the sustained development and prosperity of Islamic banking institutions. Notably, promoting good governance practices and instituting effective crisis prevention measures can further bolster the resilience of the Islamic banking sector, enabling it to play a more dynamic role in contributing to the overall development and welfare of Asian societies.

The findings of this study carry significant social implications, highlighting the need for governments in Asian countries to prioritize public policies that promote good governance and ethical practices within the banking industry. Such policies, coupled with efforts to attract foreign investments and foster a stable and transparent banking sector, have the potential to generate far-reaching positive effects on society. Through economic growth stimulated by a robust Islamic banking sector, Asian countries can create new employment opportunities, improve living standards and ultimately enhance the overall well-being of their citizens.

This study contributes to the ongoing discourse on Islamic banking stability by offering novel insights and expanding the empirical knowledge base in this field. The dual application of robust regression methodologies – namely, GMM dynamic panel data models – presents a unique analytical framework for investigating the complex interplay between diverse variables and Islamic bank stability. This methodological choice fosters deeper understanding of the dynamic relationships at play, advancing our understanding of how specific factors influence the sector's resilience and performance. In addition, the study uses rigorous empirical techniques and engages with the extant literature to provide fresh perspectives and nuanced interpretations of the findings, further solidifying its contribution to the field's originality and richness.

The empirical analysis dealt in this paper emphasizes on the impact of military expenditures on out of pocket (OOP) healthcare payments. A sizeable body of defence economics literature has investigated the trade-off between military and public health expenditure, by testing the crowding-out or growth-stimulating hypothesis; does military expenditure scaling up crowd-out or promote governmental resources for social and welfare programs, including also state health financing?

In this study, panel data from 2000 to 2018 for 129 countries is used to examine the impact of military expenditure on OOP healthcare payments. The dataset of countries is categorized into four income-groups based on World Bank's income-group classification. Dynamic panel data methodology is applied to meet study objectives.

The findings of this study indicate that military expenditure positively affects OOP payments in all the selected groups of countries, strongly supporting in this way the crowding-out hypothesis whereby increased military expenditure reduces the public financing on health. Study econometric results are robust since different and alternative changes in specifications and samples are applied in our analysis.

Under the economic downturn backdrop for several economies in the previous decade and on the foreground of a potential limited governmental fiscal space related to the Covid-19 pandemic adverse economic effects, this study provides evidence that policy-makers have to adjust their government policy initiatives and prioritize Universal Health Coverage objectives. Consequently, the findings of this study reflect the necessity of governments as far as possible to moderate military expenditures and increase public financing on health in order to strengthen health care systems efficiency against households OOP spending for necessary healthcare utilization.

Despite the fact that a sizeable body of defence economics literature has extensively examined the impact of military spending on total and public health expenditures, nevertheless to the best of our knowledge there is no empirical evidence of any direct effect of national defence spending on the main private financing component of health systems globally; the OOP healthcare payments.

This study aims to investigate the impact of government support on the coupling coordination degree of innovation chain and capital chain in integrated circuit (IC) enterprises and to explore the mechanism for considering talent in the influence path.

This paper uses coupling coordination degree model to estimate the coupling of two chains, and applies dynamic panel system generalized method of moments (system-GMM) to analyze the impact of government support on coupling of two chains and conducts dynamic panel threshold regression to explore the threshold effect of talent in the influence of government support on coupling coordination degree.

Serious imbalance in the coupling of two chains is a major obstacle in IC enterprises. Government support significantly reduces the coupling coordination degree. The talent in IC enterprises has a significant threshold effect. When the number of talent is lower than the threshold value, government support has a negative impact. Once the number of talent reaches a certain level, government support can significantly enhance the coupling of two chains. Compared with state-owned enterprises, government support has a greater negative impact on the coupling of the two chains in non-state-owned enterprises. The former needs more talent to take advantage of government support.

This paper applies the concept of coupling into enterprises and deeply studies the coupling coordination degree of two chains. The influence mechanism of government support and talent on the coupling of two chains is explored, which reveals that government support cannot achieve the expected incentive effect without the support of talent. We also discuss the heterogeneous effect of government support and of talent in enterprises of different ownership types.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

Debt sustainability and the growing level of external debt in sub-Saharan African (SSA) continue to be significant research priorities. This study aims to examine the corruption-external debt nexus in SSA economies and whether different levels of corruption better explain this relationship.

The panel quantile regression approach was applied to account for the heterogeneous effect of the exogenous variables on external debts. The research covers 30 years of panel data from 30 selected SSA economies for the period spanning from 2000 to 2021.

The empirical findings of the regression analysis demonstrate the heterogeneous influences of the exogenous variables on external debt. While there was a positive impact of foreign direct investment (FDI) inflows on external debts, corruption established a negative relationship with external debt from the 10th to the 80th quantile. The findings showed a positive link between trade openness and external debt, while they also showed a negative relationship between gross fixed capital formation and external debt.

It is implied that corruption “sands the wheels” of external debts in the selected SSA countries. Therefore, the amount of external debt that flows into SSA is inversely correlated with corruption activity.

To the best of the authors’ knowledge, this study is one of the first to use panel quantile regression to analyze how corruption affects debt dynamics across different levels of debt, allowing for a more nuanced understanding of how corruption affects debt dynamics. Based on the findings of this study, SSA countries should create enabling environments to attract FDI inflows and to continue to drive domestic revenue mobilization and capital so as to be less dependent on external debts.

The purpose of this paper is to fill the momentous gap by explicitly investigating the asymmetric effects of monetary policy (MP) on non-bank financial intermediation (NBFI) assets.

The authors utilized panel data from 29 countries for the period of 2012–2020 and used the quantile regression estimation. In addition to simultaneous quantile regression (SQR), the authors also employ quantile regression with clustered data (Parente and Silva, 2016) and the generalized quantile regression (GQR) method (Powell, 2020).

The empirical results show a significant heterogeneous impact of MP. While there is a positive relationship between MP and NBFI assets (“waterbed effect”) at lower quantiles of NBFI assets, at middle and higher quantiles, MP has a negative impact on NBFI assets (“search for yield” effect). The authors further find that negative impact strengthens as the quantile levels of NBFI assets rise from mid to high. Findings also reveal that “procyclicality” (except higher quantile) and “institutional demand” hypotheses hold. However, regarding “regulatory arbitrage,” mixed results are observed indicating the impact of Basel III requirements.

Previous empirical studies have concentrated on either the Dynamic Stochastic General Equilibrium (DSGE) framework or conditional mean regression approaches and delivered mixed findings of the MP effects on NBFI. The current paper takes a step toward dealing with this issue by deploying quantile regression methodology, which shows the impact of MP on NBFI at different conditional distributions (quantiles) of NBFI assets instead of just NBFI's conditional mean distribution.

The study aims to explore and establish the relationship that exists between board independence and corporate social responsibility (CSR) practices of Indian firms.

A sample of 76 non-financial companies listed on the National Stock Exchange has been considered for a period of seven years (from 2013 to 2019). The study has used several statistical tools such as the static panel data model and the Arellano–Bond dynamic panel data model based on generalized method of moments approach.

The results of the analysis have indicated board independence to have a significant positive relationship with the firms’ CSR performance. However, board size and number of board meetings have been found to have a negative relationship with CSR. Further, outcomes have also revealed that variables such as companies’ size and liquidity have a positive effect on the extent of CSR activities performed.

The firms which have the intention to engage in impactful CSR activities should support the independent directors’ participation in companies’ boards. The study’s findings suggest the companies to appoint independent directors strategically, keeping in mind the requirements of their board. Also, the independent directors selected should be independent in true sense, i.e. they should not be acquaintances of the company’s chief executive officer. This would ensure unbiased decision-making and would enhance the company’s CSR performance.

In India, CSR has gained great importance. So much so that it was made mandatory by the Companies Act, 2013. However, research studies that may assist in understanding the influence of board independence on Indian firms’ CSR performance are still scarce. The present study would foster value to the existing set of limited literature. Besides, the study has considered the dynamic nature of the relationship and has also controlled the endogeneity bias which has been examined by few studies in the past.