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The study aims to explore the sectoral contributions defined as agriculture, manufacturing and services value added, capital inflows defined as workers' remittances, foreign direct investment, official development assistance and domestic credit by banks as a proxy for financial deepening in Brazil-led, and Mexico-led clusters, and Latin America and the Caribbean region as a whole. The goal is to ascertain the polarization and uniformity effects of these parameters in shaping the growth and development in the midst of global financial crisis and economic challenges facing the region.

Using the classifications of Brazil-led cluster and Mexico-led cluster from Izquierdo and Talvi, the study is advanced using panel (pool) data estimation using the ARDL approach. The author used the augmented Solow framework to advance the study. He first established the desired cointegration vector for individual countries within the cluster, each cluster level and the region prior to pursuing the regression estimation. Both clusters were combined to represent the region. The author estimates the short-run (first-difference) and long-run effects of sectoral contributions and capital inflows in the region.

The region's capital productivity is driven by Brazil-led cluster. In phase 1 (sectoral shifts), polarization is noted in agriculture (dominated by Brazil-led cluster); and services (dominated by Mexico-led cluster). Uniformity exists in two clusters and the region with respect to manufacturing share where both clusters have almost equal (positive) dominance and hence exuding positive effects in the region. In phase 2, polarization is noted in remittances (dominated Brazil-led cluster), foreign direct investment (dominated by Mexico-led cluster) and financial development (dominated by Brazil-led cluster). Uniformity is noted in both clusters and the region from negative effects of official development assistance (ODA).

The study is fairly new and contemporary in its attempt to analyze the effects of sectoral shifts and capital inflows in Latin America and the Caribbean (LAC) region. Using the classification of Brazil-led cluster and Mexico-led cluster, it investigates the polarization and uniformity in the region with respect to these parameters. The study contributes to policy dialogue, and explores the emerging trends in key economic and structural factors of growth whilst highlighting some burgeoning issues shaping LAC's growth and development overall.

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T ) and the cross-section dimension (N ) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL-type estimator, the CS-DL estimator is robust to misspecification of dynamics and error serial correlation. The theoretical results are illustrated with small sample evidence obtained by means of Monte Carlo simulations, which suggest that the performance of the CS-DL approach is often superior to the alternative panel ARDL estimates, particularly when T is not too large and lies in the range of 30–50.

The search for more effective policies, choice of optimal implementation strategies for achieving defined policy targets (e.g., cost-containment, improved access, and quality healthcare outcomes), and selection among the metrics relevant for assessing health system policy change performance simultaneously pose continuing healthcare sector challenges for many countries of the world. Meanwhile, research on the core drivers of healthcare costs across the health systems of the many countries continues to gain increased momentum as these countries learn among themselves. Consequently, cross-country comparison studies largely focus their interests on the relationship among health expenditures (HCE), GDP, aging demographics, and technology. Using more recent 1980–2014 annual data panel on 34 OECD countries and the panel ARDL (Autoregressive Distributed Lag) framework, this study investigates the long- and short-run relationships among aggregate healthcare expenditure, income (GDP per capita or per capita GDP^_HCE), age dependency ratio, and “international co-operation patents” (for capturing the technology effects). Results from the panel ARDL approach and Granger causality tests suggest a long-run relationship among healthcare expenditure and the three major determinants. Findings from the Westerlund test with bootstrapping further corroborate the existence of a long-run relationship among healthcare expenditure and the three core determinants. Interestingly, GDP less health expenditure (GDP^_HCE) is the only short-run driver of HCE. The income elasticity estimates, falling in the 1.16–1.46 range, suggest that the behavior of aggregate healthcare in the 34 OECD countries tends toward those for luxury goods. Finally, through cross-country technology spillover effects, these OECD countries benefit significantly from international investments through technology cooperations resulting in jointly owned patents.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – foreign direct investment, remittances and official development assistance – can be a key factor in the development of the economy. The purpose of this study is to analyze the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been used. As part of this study, an attempt was made to use a combined autoregressive distributed lag (ARDL) panel approach to study the short-term and long-run effects of financial flows on economic growth. The results indicate ambiguous effects. Economically, the effect of financial flows on economic growth depends on the investor’s expectations.

To study the short-run and long-run effects of financial flows on economic growth, this paper considers an empirical approach based on the panel ARDL. This model makes it possible to distinguish between the short-run effect and the long-run one. This type of model is based on three estimators, namely, mean group, pooled mean group (PMG) and dynamic fixed effect.

Results confirm the existence of a long-run relationship because the adjustment coefficient (error correction parameter) is negative and statistically significant. This paper finds that the PMG estimator is more consistent and more efficient. In the short-run, foreign direct investment do negatively affect economic growth, the effect is no significant in the long-run. On the other hand, the effect of remittances on economic growth is significant in the short-run. However, it is no significant in the long-run. Finally, the results suggest that the effect of official development assistance on economic growth is insignificant; both in the long-run and in the short-run.

To study the interaction between financial flows and economic growth, some empirical methodology are used such as the dynamic panel data and the autoregressive vector (VAR) model. In this study, we apply the panel ARDL model to analyze the short-run and the long-run effect for each financial flow on economic growth. The objective is to study the heterogeneity on dynamic adjustment in the short-term and long-term.

Large-scale industrialization, growth and development have come at the cost of severe environmental degradation, primarily measured in terms of carbon dioxide emissions. Apart from the several measures taken to reduce enviornmental degradation, provision of private capital is a necessity apart from the public capital. There is a debate on impact of carbon dioxide emissions with increase in affluence, technology, population and renewable energy. The purpose of the study is to look into the role of private equity investment on renewable energy and technological patents.

The study extends the use of stochastic impact by regression on population, affluence and technology model to include another factor for investments and capital, i.e. private equity along with renewable energy, population, technology and GDP growth on carbon emissions for the BRICS countries. The time period for the study is from 2002 to 2021, and the relationship between the variables has been tested using pooled mean group/autoregressive distributed lag, fully modified ordinary least squares and panel quantile regression.

First, the results depict a log-run relationship between the variables across the panel using cointegration. Private equity investments do not have a significant impact on carbon emissions. The study proposes important policy implications. There are two schools of thought on the impact of private equity on carbon emissions. For example, inherently private equity investments come with higher stakes and a shorter holding period because of which their primary focus remains on having higher returns instead of responsible investing. However, as private equity adds up to capital, which leads to an increase in productivity and eventually higher economic growth, this could affect carbon emissions. This study supports the first thought. Additionally, renewable energy also affects carbon emissions positively. The policymakers should look into the role and intent of the private equity investors in green investments and invest in technologies and patents that can lead to energy consumption.

The paper is the first of its kind, to the best of the authors’ knowledge, to look into the impact of private equity on renewable energy and technological patents.

The purpose of this paper is to empirically examine the effect of corruption on public debt and economic growth in 20 developing countries over the period 1996-2018.

This study makes use of the autoregressive distributed lag (ARDL) model to detect the long-term relationships, on the one hand, between corruption and public debt and, on the other hand, between corruption and economic growth.

The empirical results reveal that corruption increases the debt-to-GDP ratio and that the interactions between corruption and public revenues and between corruption and public spending have a positive influence on public debt in the long run. The estimations also show that high corruption hampers long-term economic growth and increases the negative effect of public debt on economic growth in developing countries.

While corruption is a prevalent phenomenon in most developing countries, the literature still lacks empirical examination of its economic effects. This study fills this gap with the aim of highlighting that high corruption hinders development in developing nations. This study also examines the impact of the interactions between corruption and components of the fiscal balance on public debt. Moreover, while the existing empirical literature uses regression techniques, this paper uses a panel ARDL approach to detect the long-term effects of corruption.

This study aims to examine the effect of foreign direct investment (FDI) inflows on tax revenue in 34 developed and developing countries from 2006 to 2020.

Feasible generalised least squares (FGLS), a dynamic panel of a two-step system generalised method of moments (GMM) system and a pool mean group (PMG) panel autoregressive distributed lag (ARDL) approach were used to compare the developed and developing countries. Basic estimators were used as pre-estimators and diagnostic tests were used to increase robustness.

The FGLS, a two-step system of GMM, PMG–ARDL estimator’s results showed that there was a significant negative long and positive short-term in most countries relationship between FDI inflows and tax revenue in developed countries. This study concluded that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Meanwhile, there was a significant positive long and negative short-term relationship between FDI inflows and tax revenue in the developing countries. The developing countries sought to attract FDI that could be used to create job opportunities and transfer technology to simultaneously develop infrastructure and impose a tax policy that would achieve high tax revenue.

The present study sheds light on the effect of FDI on tax revenue and compares developed and developing countries through the design and implementation of policies to create jobs, transfer technology and attain economic growth in order to assure foreign investors that they would gain continuous high profits from their investments.

This paper aims to test whether a debt threshold of public debt has any effect on economic growth in Africa.

The authors applied the panel autoregressive distributed models on 38 African countries with annual data from 1970 to 2015. It was established that the threshold and the trajectory of debt has an impact on economic growth.

Specifically, the authors found that public debt hampers economic growth when the depth is in the region of 20 to 80 per cent of GDP. Based on debt trajectory, this study established that increasing public debt beyond 50 to 80 per cent of GDP adversely affects economic growth in Africa. The study also finds that the persistent rise in debt also has adverse effect on economic growth in the African countries in the sample. It must be known to policymakers that the threshold of debt in developing countries, and for that matter African countries, are less than that of developed countries.

This study suggests threshold effects between 20 and 50 per cent; this should be a guide for policymakers in the accumulation of debt stock. Interestingly, the findings suggest some debt trajectory effect, which policymakers might consider by increasing efforts to reduce debt levels when they fall between 50 to 80 per cent of GDP. This implies that reducing such debt levels can help African countries increase their economic growth.

The study is unique because it seeks to add new evidence on the relationship between public debt and growth in the African region, by considering the impact of the persistent growth of public debt on economic growth.

This purpose of this paper is to empirically examine the contribution of the Islamic banking and financial institutions (IBFIs) to economic growth in Malaysia.

Focusing on the post-1997 economic turmoil, the paper relies on several time series tests, such as autoregressive distributed lag (ARDL), vector error correction model (VECM) and variance decompositions (VDCs).

The paper documents significant role played by the IBFIs in Malaysian economy. In particular, significant unidirectional causality was found from the IBFIs development to economic growth, supporting the finance-growth led hypothesis or the supply-leading view.

The paper only focuses its analysis on the role of the IBFIs in the Malaysian economy and not the financial sector as a whole. Thus, the findings of this paper are indicative, but inconclusive for the entire financial sector in the country.

Continuous efforts should be undertaken to promote the development of the Islamic banking industry due to its significant contribution to Malaysia’s economic growth by further improving the Islamic financial infrastructure, increasing the pool of human capital in the Islamic banking industry, providing conducive legal environment to the IBFIs and maintaining the Islamic financial sector stability.

This paper is the first attempt to empirically assess the contribution of Islamic banking institutions in Malaysia using ARDL, VECM and VDCs.