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The underdevelopment of the financial sector could be one of the barriers to the deployment of renewable energies in developing countries. The purpose of this paper is therefore to analyse the effect of financial development in the deployment of renewable energies in sub-Saharan African countries.

The empirical analysis is based on a production approach and a cross-sectionally augmented autoregressive distributive lag error correction model estimate for 25 sub-Saharan African countries over the period 1990–2018. The augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators were used for the robustness analysis.

Two results emerge: financial development contributes positively to renewable energy deployment in sub-Saharan African countries in the short and long run; and fossil fuel dependence impedes significantly renewable energy deployment in the short and long run. The robustness analyses using the AMG and CCEMG methods confirm these results.

These results suggest the need for policies to support and strengthen the development of the financial sector to improve its ability to effectively finance investments in renewable energy technologies.

The originality of this paper lies in the fact that the analysis is based on a renewable energy production approach. Indeed, the level of renewable energy deployment is measured by the production and not the consumption of renewable energy, unlike other previous work. In addition, this research uses recent econometric estimation techniques that overcome the problems of cross-sectional dependence and slope heterogeneity.

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.

Financial inclusion is a critical component of financial development, which disseminates accessible financial services to benefit all parts of society and consequently promotes economic growth. The study explores the dynamic common correlated effects of financial inclusion on economic growth in Organization of Islamic Cooperation (OIC) countries.

The conventional econometric techniques overlook heterogeneity and cross-sectional dependence and provide false results. Hence, a unique methodology, ‘Dynamic Common Correlated Effects (DCCE)’, is used, which can efficiently tackle the above-mentioned issues.

The DCCE estimation indicates a positive and significant impact of financial inclusion on economic growth in overall and higher-income OIC economies. Moreover, in the lower-income OIC group, financial inclusion is inversely correlated with economic growth, which converts into a positive linkage by including an interaction term of financial inclusion and institutional quality.

Based on the research outcomes, it is recommended that policymakers and governments of OIC economies seek to increase financial inclusion to achieve sustainable, optimal and inclusive economic growth.

The DCCE technique in this study considers heterogeneity and cross-sectional dependence among countries and thus provides robust findings.

The growth of both the informal sector and illicit financial outflows necessitated this study, in order to investigate how countries in Africa respond to these realities in terms of mobilization of domestic resources. These are the main motivation for the current study to the extant literature in conjunction with the adoption of employing second-generation econometric techniques which take into account cross-sectional dependence and country-specific heterogeneity.

This study therefore examined the capacity of Africa to mobilize domestic resources amidst rising illicit financial outflows and informal sector size in selected African countries between 2000 and 2018. Second-generation econometric techniques such as cross-sectional dependence tests, slope homogeneity tests, Westerlund (2007) long-run co-integration tests, Eberhardt and Teal (2010) augmented mean group estimations and Kónya (2006) panel causality testing were employed.

Findings revealed the existence of cross-sectional dependence and slope homogeneity in the data series. Findings also supported the existence of depressing long-run impacts of IFOs and ISS on domestic savings. Causality test results were not uniform across variables among countries. Policy recommendations favour formalizing the largely informal African economies through budgetary policy adjustments and commitment to building stronger institutions.

The fragility of the African countries economy and its macroeconomic indicators is suggestive for more policy construction.

This economic reality about the nature of the informal sector is one that has negated the traditional view which holds that economic reforms would make the informal sector shrink as it transits to formal sector. Experiences from Latin America and Africa in fact indicate that the informal sector is actually on an expansionary path in the wake of adjustment and policy reforms. It is often called the unobserved, unorganized or unprotected economy. With this sector growing in size, the possibility of a reverse may not be in sight, owing to the increasing poverty levels and unemployment prevalent in most African countries. Uncertain foreign investment and aid inflows coupled with lower export revenues and high levels of indebtedness have created new impetus to examine the capacity of Africa's fiscal policy regime to mobilise domestic resources for the development of the region. Surprisingly, the last decade witnessed continued rise in Africa's illicit financial outflows amidst large informal sector size (ISS).

This paper aims to examine whether there exists a long-run causal relationship between the prices of households’ two major assets: stocks and houses over the period 1975Q1–2017Q1 for seven major European countries.

The paper uses the bootstrap panel Granger causality approach to determine the causal structure, focusing on cross-sectional dependence, slope heterogeneity and structural breaks.

The findings show that, in most cases, there is a unidirectional causality running from stock price to house price but the converse is not true. This confirms a strong wealth effect in housing markets. The findings are important for not only households but also policymakers concerned with financial stability and housing prices.

First, the methodology used here devotes full attention to dynamic co-movement between housing and stock markets. Second, this study uses a rather long quarterly data, which implies that the findings could be robust. Third, the study uses real personal disposable income as a control variable to remove the effects of economic growth. Fourth, most of the previous studies do not consider the presence of structural breaks and this makes the result of causality invalid and biased. Fifth, most of the previous studies on housing and stock markets concentrated on the US and non-European countries such as China, Korea and Singapore.

This paper aims to examine whether there exists a long-run causal relationship between house prices and unemployment rates for eight major European countries.

The bootstrap panel Granger causality approach that accounts for cross-sectional dependence, slope heterogeneity and structural breaks is used to detect the direction of causality.

The empirical findings for the overall panel support the presence of unidirectional causality running from house prices to unemployment.

The findings are not only important for households but also for policymakers concerned with economic and financial stability.

There are only a limited number of studies that have investigated the direct link between house prices and employment or unemployment. Given the increased importance of labor market variables, particularly the choice of the unemployment rate as a key indicator in designing forward guidance and the increased financial stability concerns regarding house price dynamics, it is important to better understand the causal linkages between house prices and unemployment rates. To the best of the author’s knowledge, this paper is the first to apply the bootstrap panel Granger causality approach to examine the relationship between house prices and unemployment rates.

This paper aims to investigate the effects of the COVID-19 crisis on trade flows in Asia Pacific countries and explores the causality between COVID-19-related shocks and trade.

The authors used two novel techniques, namely, two-stage instrumental-variables (2SIV) approach and Juodis, Karavias and Sarafids (JKS) causality test, to examine trade dynamics in the Asia Pacific region during the pandemic.

Using the monthly trade data of 17 Asia Pacific countries between January 2020 and December 2021, the results were threefold. Firstly, the empirical analysis showed that during the COVID-19 crisis, the flow of exports tended to persist idiosyncratically in comparison to the flow of imports. In particular, a specific finding was that the persistence level in exports was about 20%–25% higher than that in imports. Secondly, the authors found that the past values of COVID-19 cases and COVID-19 deaths contain information that helps to predict exports/imports over and above the information contained in the past values of exports/imports alone. Finally, the study established that the government response and stringency indexes have a Granger-causal relationship with exports and imports.

For the foreseeable future, these findings have significant policy ramifications. Firstly, if a COVID-19 crisis-like situation emerges in the future, it will be critical for countries to maintain their competitiveness throughout the crisis, like the COVID-19 pandemic, while also rebuilding trade relationships wherever possible. Secondly, because information about government responses and measures can also be used to predict future trade flows, prudent management of government responses and stringent measures will be necessary in a crisis like COVID-19 to achieve the optimum level of exports and imports. At the same time, the trading partners should give up the idea of trade protection and focus on finding a way to balance the conflicting needs of imports and exports.

To the best of the authors’ knowledge, the authors, for the first time, used a 2SIV approach and JKS causality test to examine trade dynamics in the Asia Pacific region during the pandemic. In addition, the authors present the first comprehensive analysis of the evolving relationships between export and import flows and governmental policy responses under COVID-19. As a result, it contributes uniquely to both public and international economics.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.