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The processes of convergence are particularly challenging in the Sub-Saharan African frameworks, considering the diversity of contexts and endogenous particularities. Creating conditions to support these nations to improve their socioeconomic dynamics and performance requires additional contributions from international organisations, governments and the scientific community. In this scenario, this paper aims to analyse the convergence process in Sub-Saharan African countries over the past three decades.

To achieve these objectives, data from the World Bank were considered for the gross domestic product (GDP) per capita over the period 1990–2021. This statistical information was assessed through panel data approaches based on the models from the convergence theory. Specifically, the concepts of sigma and beta convergence were addressed, as well as the concept of catch-up rates.

The findings obtained highlight evidence of the existence of clubs of convergence among the Sub-Saharan African countries and the processes of catching up. These results may be relevant support for the policymakers and international funds and programmes.

This research provides a new perspective on the convergence of GDP per capita in Sub-Saharan African countries, based on an analysis focused on groups of countries identified on the basis of catch-up rates. This approach presents a way of dealing with the different specificities of these nations.

This article investigates the validity of the different types (conditional, unconditional, deterministic, stochastic) of ß-convergence in per capita GDP for EU-28 and EU-19 between 1990 and 2019.

The study uses nonstationary heterogeneous panel-data methodology.

The panel data reveal that both conditional and unconditional ß-convergence are valid in EU-28 countries However, only conditional convergence exists in EU-19 countries; group-specific findings show that the income levels of 10-EU countries converge toward the EU-19 average and 11-EU countries converge to the EU-28. The convergence speed to EU average varies between 15 and 18%. The robustness of the augmented mean group (AMG) findings are checked with common correlated effects mean group (CCEMG) and are consistent. Moreover, panel unit root tests are applied to examine the stochastic and deterministic convergence of the average EU per capita income in the two groups of EU economies. The findings show no evidence of deterministic or stochastic convergence in EU countries. Besides, conditional convergence has not been experienced in countries such as Bulgaria, Croatia, Czech Republic, Hungary, Latvia, Malta, Romania, Slovakia and Slovenia, which are new members of the EU. As a remarkable aspect of the study, the evidence suggests that the Brexit is economically rational for the UK.

The growth and convergence processes of economies differ from each other. Convergence studies in the literature are generally based on the cross-section OLS methodology. In this context, the study is one of the rare studies to examine convergence using heterogeneous panel techniques and allows the convergence of countries to the EU average to be analyzed individually.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

One of the best ways to assist China is through infrastructure investment. China might become more resilient to natural calamities by pouring more money into its transport network. Analyzing the relationship between China's degree of planned expansion and the country's current network of transport hubs can help with city development estimates. A wide range of factors were taken into consideration while evaluating China's dominance and the caliber of its transportation infrastructure. Using a geographical autocorrelation model and a coupling coordination model, the dynamic link between China's adaptability and the caliber of its transportation infrastructure is examined.

China's northwest is underdeveloped in comparison to the southeast, which has a high level of resilience and development of its transportation infrastructure. The relationship between the levels of resilience upheld by China's transport infrastructure is suggested to be coordinated.

The authors find a positive geographical autocorrelation between the degree of coupling coordination and the degree of agglomeration, despite the fact that the distance between cities increases with time. They now believe that there is a connection between an area's population density and the degree of interspousal cooperation within. The consequence is an improvement in both national security and economic prosperity. The facilities for disaster management and transportation in China have received several proposals for improvement.

The authors' Practical Implications suggests that scale inefficiency is a major contributor to the relatively poor efficiency of China's primary inland river ports. Different types of inland river ports may have vastly different water system efficiencies. Input and output congestion at China's important interior river ports has reached 51%, making it very clear that massive amounts of valuable port resources are being wasted.

Many variables, such as climate and human error, affect the total amount of goods that can be moved via inner river ports. Ports situated either higher up or lower down the same canal may perform better or worse, respectively, depending on the circumstances.

Since 1966, the Severn crossing has been connecting England and Wales. In January 2018, its ownership returned to the UK Government, and this marked the start of a toll-free journey across the two countries and made commuting between the regions more affordable. In this paper, we examine the impact of the toll removal on the property market.

We employ property-level data from the Land Registry and a difference-in-differences (DiD) empirical model for the periods 2016–2018 and 2019–2021 to capture the pre- and post-toll removal dynamics. The DiD estimation allows us to examine the causal relationship between policy changes and property prices.

Our findings suggest that property prices in Newport and Monmouthshire (South East Wales) are positively affected by the policy, which results in a statistically significant increase of 5.8% more than those located in the South West England (Bristol and South Gloucestershire) region in the period 2019–2021. The impact can reach up to 13.1% for properties located in a 10 km radius of the bridge. The results indicate that the toll removal enables the ripple effect across the two markets by reducing commuting costs.

This is the first paper that examines the Severn Crossing case study. Its contribution is significant since we provide empirical evidence on how reduced transportation costs increase property prices in the lowest income region and have the opposite effect on the area with higher incomes and economic activity levels.

The purpose of this paper is to measure the high-quality entrepreneurial efficiency of family-owned small- and medium-sized enterprises (SMEs) while exploring the potential determinants of their performance. This study places particular emphasis on the firms' technological competencies and internationalization efforts. The authors aim to shed light on the internal and external characteristics that impact the efficiency of family SMEs.

This study adopts a two-stage approach. In the first stage, a data envelopment analysis model is utilized to measure the high-quality entrepreneurial efficiency of family SMEs. To achieve this, this study considered as outputs three key quality aspects of entrepreneurship, namely innovativeness, export orientation and turnover rate, while the inputs were the number of employees and the business environment. Then, in the second stage, the efficiency scores are regressed against a set of environmental factors that may affect the efficiency. The proposed efficiency measurement models are utilized with a particularly rich dataset of 1,910 family SMEs from 35 developed countries.

The results demonstrated that the efficiency of family SMEs primarily engaged in the production of goods was significantly higher than those providing services. Importantly, the presence of barriers related to innovation and digitalization had a pronounced negative impact on efficiency. Additionally, scale-up firms exhibited higher levels of efficiency. When examining family SMEs within their national context, it was observed that non-EU countries and countries with a higher gross domestic product displayed significantly higher efficiencies.

The findings of this research provide guidance for the development of entrepreneurship-oriented policies that consider both the internal characteristics of family SMEs and the diverse socioeconomic contexts in which they operate.

Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018.

After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches.

The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance.

The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

This article aims to investigate how institutional characteristics affect the level of financial development of economies collectively and compare between developed and undeveloped economies.

A dynamic panel with 131 countries, including developed and developing ones, was utilized; the estimators of the generalized method of moments system (GMM system) model were selected because they have econometric characteristics more suitable for analysis, providing superior statistical precision compared to traditional linear estimation methods.

The results from the full panel suggest that concrete and well-defined institutions are important for financial development, confirming previous research, with a more limited scope than the present work.

Limitations of this research include the availability of data for all countries worldwide, which would make the research broader and more complete.

A panel of countries was used, divided into developed and developing countries, to analyze the impact of institutional variables on the financial development of these countries, which is one of the differentiators of this work. Another differentiator of this research is the presentation of estimates in six different configurations, with emphasis on the GMM system model in one and two steps, allowing for comparison between results.

The purpose of this study is to examine the relationship between the productive structure and the size of the informal economy in Latin American countries.

The study employs econometric techniques for panel data covering the period from 2002 to 2017 and considering 17 Latin American countries. The evidence presented is based on the informal economy data generated by Medina and Schneider (2018) who estimate the size of the informal economy using a structural equation model and the share of manufacturing in total employment as a measure of the size of the manufacturing sector. Also, the study addresses the possible endogeneity bias in the relationship studied and makes the conclusions more robust, thus avoiding spurious correlations that weaken the findings.

The results indicate that most industrialized Latin American countries are associated with a smaller size of the informal economy.

The findings have important policy implications, as they suggest that Latin American economies need to switch the structure of the economy toward more sophisticated productive structures if they want to reduce the size of the informal economy. Thus, more efforts should be deployed to policies to diversify and upgrade economies.

The study contributes to the literature on the informal economy by connecting the country’s productive structure and informality. Specifically, the results show that the productive structure of countries is a plausible explanation for the size of the informal economy.