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This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

The Organization for Economic Cooperation and Development (OECD) countries are facing unprecedented challenges related to climate change and population aging. The purpose of the analysis is to explore the relationship between population aging and environmental degradation, accounting for human capital, using a sample of 19 OECD countries over the period 1980–2019.

On the empirical methodology, the analysis uses panel estimators with heterogenous coefficients and an error structure that takes into consideration cross-country heterogeneity and cross-sectional dependence for a panel of 19 OECD countries over the period 1980–2019. To examine the relationship between population aging and environmental degradation, the authors employ two alternative measures of environmental degradation that is energy consumption and CO2 emissions in metric tons per capita. Concerning the regressors, the authors account for two alternative aging indicators, namely the elderly population and the old-age dependency ratios to confirm robustness.

The analysis provides evidence that population aging and human capital development (IHC) lead to lower energy consumption in the OECD sample. Overall, the growing number of elderly people in the OECD seems to act as a mitigating factor for energy consumption. The authors view these results as conveying the message that the evolution of population aging along with channeling government expenditures towards human capital enhancement are important drivers of curbing energy consumption and ensuring environmental sustainability. The authors' research is of great significance for environmental policymakers by illuminating the favorable energy consumption patterns that population aging brings to advanced economies.

The main limitation of this study concerns data availability. Future research, and subject to greater data availability in the future, could dig deeper into understanding the dynamics of this complex nexus by incorporating additional control variables. Similarly, the authors focus on aggregate renewable energy consumption, and the authors do not explicitly model the sources of renewable energy (wind, hydropower, solar power, solid biofuels and other). Additional analysis of the breakdown of renewable energy sources would be insightful – subject to data availability – especially for meeting the recently agreed new target of 42.5% for European Union (EU) countries by 2030. A deep transformation of the European energy system is needed for the EU to meet the target. Finally, extending the model to include a range of non-OECD countries that are also experiencing demographic transformations is a promising avenue for future research.

To the best of the authors' knowledge, this study is the first to examine the effects of population aging and human capital on environmental degradation using a broad set of OECD countries and advanced spectrum estimation methods. Given cross-sectional dependencies and cross-country heterogeneity, the authors' empirical results underline the importance of cross-OECD policy spillovers and knowledge diffusions across the OECD countries. The new “energy culture” calls for concerted policy action even in an aging era.

This study aims to examine the nexuses between economic growth, trade openness, renewable energy consumption and environmental degradation among organization of petroleum exporting countries (OPEC) members over the period 1990–2019.

The empirical strategy for the study includes dynamic heterogeneous panel pooled mean group (PMG), mean group (MG) estimators and dynamic panel threshold regression (TR) analysis. For clarity, PMG and MG are used to explore the long-run relationship between the variables, whereas TR is used to uncover the actionable and complementary policy thresholds in the nexuses between green growth and environmental degradation.

The empirical evidence is based on the significant estimates from PMG and TR. First, using PMG, the study finding revealed a long-run relationship between economic growth and environmental degradation via the PMG estimator. Second, using TR, the study revealed an actionable threshold for carbon dioxide emissions (CO₂) metrics tons per capita (mtpc) not beyond a critical mass of 4.88mtpc, and the complementary policy threshold of 85% of the share of trade to gross domestic product, respectively.

The policy relevance of the thresholds is apparent to policymakers in the cartel and for policy formulation. The policy implication of this study is straightforward.

The novelty of this study stalk in the extant literature on providing policymakers with an actionable threshold for CO₂ emissions with the corresponding complementary threshold for trade policies in the nexuses between green growth and the environment.

This study aims to investigate the dynamic relationship between renewable and non-renewable energy sources on the economic growth of eight countries, the capital stock and labour force being used as control variables in each case. Questions that need to be asked include the following: Is there is an asymmetric and, hence, a non-linear relationship between variables? If yes, how does economic growth interact with both renewable and non-renewable energy consumption (EC)? How different are these relationships in the countries highly rated in the performance of renewable EC compared to those lowly rated?

This paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables.

A newly developed asymmetric panel quantile approach suggests that EC has a significant effect on economic growth in both directions of shocks as well as for the considered sample. The results further support the findings in recent literature on renewable energy deployment, given the importance of renewable EC for economic growth with the increased levels of renewable EC, although the initial investments may have a negative effect on economic growth for some countries.

This study contributes to the literature in twofold. Firstly, it aims to contribute to the ongoing debate in literature by incorporating both renewable and non-renewable energy resources in the production function with labour and capital to test their asymmetric impact on economic growth. Secondly, this paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables. Another point that should be emphasised in this study is the need for studies analysing economic growth and EC for a sample of G20 countries based on a comparative view for the renewable and non-renewable EC in literature.

In pursuit of good governance and better allocation of resources, corruption and informal economy are of interest to policymakers and citizens alike. The impacts of military spending on the informal economy are scant. Moreover, the effects of an external factor, such as corruption that moderates this relationship, have largely been neglected in previous studies. Hence, this paper investigates how corruption moderates the effects of military spending on the informal economy in 30 Asian countries from 1995 to 2017.

This paper utilizes the GMM estimation technique, which allows cross-sectional dependence and slope homogeneity in panel data analysis, to examine the moderating role of corruption on the relationship between military spending and the informal economy.

Empirical findings from this paper indicate that an increase in military spending declines the informal economy while corruption increases it. Interestingly, the negative effects of military spending on the informal economy will mitigate with a greater degree of corruption in the Asian region. We also find that enhancing economic growth and attracting more FDI has reduced the informal economy in Asian countries.

To the best of the authors' knowledge, this is the first empirical study conducted to examine the moderating role of corruption on the military spending – informal economy nexus. Thus far, this approach has not been investigated in the existing literature, particularly for Asian countries.

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.

This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined.

In order to obtain insight into the openness–unemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis et al. (2021).

Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale.

A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels – an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis et al. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables.

Higher economic growth accompanied by rising energy demand poses severe challenges to the long-term environmental sustainability of E7 economies, including Brazil, China, India, Indonesia, Mexico, Russia and Turkey. Thus, this paper explores the influence of foreign direct investment (FDI) inflows on energy diversification for E7 economies.

The dataset is panel data for emerging seven (E7) economies, covering the period 1992–2017. The empirical investigation relies on econometric techniques: panel cointegration test and panel autoregressive distributed lag model.

The findings reveal that energy diversification and FDI inflows are cointegrated. In the long run, higher FDI inflows encourage energy diversification, but energy efficiency improvements discourage energy diversification. In the short run, the effects of FDI inflows on energy diversification vary across E7 economies, highlighting the role of country-specific factors in determining the short-run influence of FDI inflows on energy diversification.

The findings suggested that FDI policies should encourage the adoption of nonconventional energy resources to stimulate energy diversification in E7 economies. Besides, better coordination between energy diversification and energy efficiency policies is required in the long run for a successful transition towards low-carbon economy goals.

This study is a unique empirical exercise that uncovers a cointegrating relationship between energy diversification and FDI inflows for E7 economies. Moreover, the analysis provides homogenous long-run and heterogeneous (country-specific) short-run coefficient estimates for the effect of FDI inflows on energy diversification.

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.