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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.

The purpose of this paper is to examine the dynamics between banking penetration, infrastructure development and regional growth within a multivariate framework in 23 Indian states over the period 2000-2012.

The study employs the multivariate panel data framework to analyze the dynamics between banking penetration, infrastructure development and regional growth within the vector error correction model (VECM) framework.

The findings confirm the long-run equilibrium relationship between banking penetration, infrastructure and income for the panel. Long-run income elasticity of infrastructure, estimated using Panel dynamic ordinary least square, is positive, statistically significant and has a value of 0.1531. Further, results show bidirectional causality between income and aggregate infrastructure and unidirectional causality running from banking penetration to income and aggregate infrastructure in the long run. However, there is unidirectional causality running from income to banking penetration and aggregate infrastructure and from banking penetration to aggregate infrastructure in the short run.

The study mainly concentrates on the 2000-2012 period and includes transportation (roadways and railways), energy (including electricity) and telecommunication as indicators for infrastructure, as the data for these sectors are easily available at the state level. Second, this study employs the panel data technique as it has a shorter data count.

In order to minimize the existing regional disparity in a developing India, national infrastructure policies should be aimed toward improving the overall access to as well as the quality of infrastructure (existing as well as newly planned). Further, widening the banking outreach at the bottom level may further help the economy as well as the infrastructure sector in mobilizing long-term finances for productive investments, in order to have a balanced, more inclusive and faster growth in the long run.

The study employs panel unit root, cointegration and Granger causality tests within the panel VECM framework to explore the dynamics among the system variables. Further, the study creates a composite index of infrastructure with principle component analysis.

The purpose of this paper is to examine the direction of causality between government expenditure and economic growth in the Economic Community of West African States (ECOWAS) countries.

The study adopts the recently developed panel vector autoregressive (PVAR) by Love and Abrrigo (2015) and two-step system generalized method of moments (GMM) in order to resolve the inherent problems of endogeneity and persistence in economic data.

The results from the study show no evidence of either unidirectional or bidirectional causal relationship between government expenditure and economic growth in ECOWAS member countries.

Unlike previous studies that adopted cointegration technique, we adopt a system GMM through the application of a dynamic PVAR framework within the framework of panel data analysis in order to address the possibility of feedback effect in the causal relationship between government expenditure and economic growth. In addition the PVAR also allows us to model shocks across countries.

The purpose of this paper is to use the recent development in unit root tests and cointegration as applied to panel data and dynamic time series, to estimate the relationship between financial liberalization, financial development and growth.

The paper assesses the dynamics of the relationship between financial development, financial liberalization and growth using the latest dynamic panel data framework and time series analyses comprising up to 15 Sub‐Saharan African countries with annual observations over the period of 1976‐2005. The research uses various measures of, or proxies for, financial intermediary development, including ratio of private sector credit and share of domestic credit to income.

The results obtained from a heterogenous panel investigation and time series methodology such as Granger causality, indicate a long‐run equilibrium relationship between financial development and economic growth. This is consistent with the view that financial development can act as an “engine of growth” and plays a crucial role in the process of economic development. However, there is little evidence to support the hypothesis that financial liberalization directly “leads” growth.

Group mean panel fully modified ordinary least squares (FMOLS) and country‐by‐country time series investigations show evidence of causality running from financial development to growth. The analysis yielded limited evidence of financial liberalization Granger‐causing economic growth. However, this is not to say that financial liberalization does not promote growth, as it could do so indirectly through fostering financial development.

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.

The purpose of this paper is to investigate two famous postulates of the Schumpeterian doctrine and its implications for the US economy.

Analytically, the authors investigate whether sector size matters for sectoral: technological change and stability, as expressed through the relevant quantitative measures and variables. To this end, the authors test a number of relevant models that express the various forms of this relationship. More precisely, the authors use panel data for the 14 main sectors of economic activity in the USA over the period 1957-2006, just before the first signs of the US and global recession made their appearance.

The results seem to be in line with the Schumpeterian postulate that market size matters for technological change and economic stability, for the US economy (1957-2006). Clearly, further research would be of great interest.

This work contributes to the literature in the following ways: first, it provides an extensive review of the literature on the subject and adopts two relevant methodological approaches. Second, based on these quantitative approaches, the paper offers a complete investigation of two famous postulates of the Schumpeterian theory for the US economy, and it is the first, to the best of the authors’ knowledge, to do so by sector of economic activity, in a panel data framework. Third, the paper uses a wide data set (1957-2006) to examine the US economy up until the first signs of the US and global economic recession made their appearance.

This research has two primary goals: first, to develop a composite index that evaluates the degree to which Asian–Pacific economies are prepared to engage in public–private partnerships (PPPs), and second, to investigate the factors that have been most influential in the formation of PPP arrangements in the nations' infrastructure over the course of the period 1995–2016.

The study constructs sectoral and overall index of possible determinants of PPP. Subsequently, it examines each constructed index's role in PPP investment. The author also conducted a panel data analysis to understand the role of each of the potential determinants on PPP projects and investments. This paper analyzes the author’s empirical models using a range of cross-section and panel estimators, including Poisson, zero-inflated Poisson and fixed effect.

The study’s results based on cross-section analysis suggest that regulatory and institution quality, institutional arrangement and regulatory frameworks, financial market development and macroeconomic stability positively impact investment in PPP. Moreover, the results depict that financial market development has the most substantial impact on PPP investment, followed by macroeconomic stability and prior experience with PPPs. The panel data analysis shows that per-capita income, financial development, inflation, debt, resource import and fuel export are crucial determinants of PPP in Asian–Pacific economies.

Governments of the countries should promptly amend the important policies outlined in this study and adopt a more robust strategy to foster a competitive PPP environment. This will aid in maintaining transparency and gaining the confidence of investors. The study’s findings may assist policymakers in focusing on specific areas in need of improvement. Social welfare and industrialization are ultimately enhanced by the formulation of such policies and by attracting additional infrastructure investment.

This is the first attempt to rank countries on the basis of PPP enablers. Unlike previous studies, this study examines the role of a large number of indicators in determining PPP investment and projects in cross-section as well as panel data framework. The study also investigates the effects of PPP specific provisions and rules. Furthermore, the focus is specifically on Asian–Pacific countries, which are a mix of third-world, emerging, developing and developed countries. Focusing on Asia–Pacific is also crucial because the region is home to most of the world's population, and the region's infrastructure outcomes significantly impact their lives.

The development of green economy is of academic and policy importance to governments and policymakers worldwide. In the light of the necessity of renewable energy to sustain green economic growth, this study aims to examine the relationship between renewable energy consumption and green economic growth, controlling for the impact of trade openness for Organization for Economic Co-operation and Development countries over the period 1990-2015, within a multivariate panel data framework.

To investigate the long-run relationship between variables, panel cointegration tests are performed. Panel Granger causality based on vector error correction models is adopted to understand the short- and long-run dynamics of the data. Furthermore, ordinary least square (OLS), dynamic OLS and fully modified OLS methods are used to confirm the long-run elasticity of green growth for renewable energy consumption and trade openness. Moreover, system generalized method of moment is applied to eliminate serial correlation, heteroscedasticity and endogeneity problems. The authors used the panel Granger causality test developed by Dumitrescu and Hurlin (2012) to infer the directionality of the causal relationship, allowing for both the cross-sectional dependence and heterogeneity.

The results suggest that renewable energy consumption and trade openness exert positive effects on green economic growth. The results of long-run estimates of green economic growth reveal that the long-run elasticity of green economic growth for trade openness is much greater than for renewable energy consumption. The estimated results of the Dumitrescu and Hurlin (2012) test reveal bidirectional causality between green economic growth and renewable energy consumption, providing support for the feedback hypothesis.

This paper provides strong evidence of the contribution of renewable energy consumption on green economy for a wide range of countries. Despite the costs of establishing renewable energy facilities, it is evident that these facilities contribute to the green growth of an economy. Governments and public authorities should promote the consumption of renewable energy and should have a support policy to promote an active renewable energy market. Furthermore, the regulators must constitute an efficient regulatory framework to favor the renewable energy consumption.

Many countries focus on increasing their GDP without taking the environmental impacts of the growth process into account. This paper shows that renewable energy consumption points to the fact that countries can still increase their economic growth with minimal damage to environment. Despite the costs of adopting renewable energy technologies, there is still room for economic growth.

This paper provides evidence on the contribution of renewable energy consumption on green economic growth for a wide range of countries. The paper focuses on the impact of renewable energy on economic growth by taking environmental degradation into consideration on a wide scale of countries.

The purpose of this paper is to examine the relationship between the quality of different dimensions of institutional and economic growth in a panel of 15 member ECOWAS.

The study adopts Driscoll and Kraay′s nonparametric covariance matrix estimator, and the spatial error model to account for cross-section dependency, cross-country heterogeneity and spatial dependence inherent in empirical modelling, which has largely been ignored in previous studies. This is because, the likelihood that corruption and human capital cluster in space is very high because factors that affect these phenomena disperse across borders. Similarly, to test the threshold effect, the study adopts the more refined and more appropriate dynamic panel data which models a nonlinear asymmetric dynamics and cross-sectional heterogeneity, simultaneously, in a dynamic threshold panel data framework.

The empirical evidence supports findings by previous researchers that better-quality political and economic institutions can have positive effects on economic growth. Similarly, our results support a nonlinear relationship between political institutions and economic institution, confirming the “hierarchy of institution hypothesis” in ECOWAS. Specifically, the findings show that economic institutions will only have the desired economic outcome in ECOWAS, only when political institution is above a certain threshold.

Unlike previous studies which assume cross-sectional and spatial independence, the authors account for cross-section dependency and cross-country heterogeneity inherent in empirical modelling.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2019-0630

This study aims to examine the asymmetric effects of energy efficiency on employment in India. Instead of relying on partial factor energy efficiency measures, this study uses a total factor energy efficiency (TFE) measure to estimate sector-specific energy efficiency for empirical investigation.

Multi-sectoral panel data for India from 2000 to 2014 are considered for empirical estimation. The sector-specific energy efficiency estimates (using the TFE measure) are estimated in the initial stage using the stochastic frontier approach (SFA). Then the asymmetric effect of energy efficiency on employment is investigated by using a non-linear panel autoregressive distributed lag model.

The estimates of energy efficiency display that there is not much significant change in the trend of average energy efficiency over the period. The negative and statistically significant value of the error-correction term confirms the existence of asymmetric cointegrating relationship between energy efficiency and employment in India. Moreover, in the empirical findings, the positive and negative shocks in energy efficiency provide a long-run asymmetric and short-run symmetric effect on employment in India.

Rather than depending on the absolute measure of energy efficiency (energy to output ratio), this study estimates the sector-specific energy efficiency for India using panel SFA, which provides a relative measure of energy efficiency. Moreover, to the best of the authors’ knowledge, it is the first empirical study investigating the asymmetric impact of energy efficiency on employment at an aggregate level in developing countries like India. By contrast, previous studies have either concentrated on the symmetric effect of energy efficiency on employment or primarily restricted to developed countries.