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The research analyzes the convergence of several socioeconomic indicators in a sample of 137 countries over the period 1990–2019. Applying log t-convergence tests, it finds that socioeconomic indicators’ convergence is divergent. Measuring seven different indicators, there are only two indicators of life expectancy and access to the internet converging at the global level, while the remaining indicators of gross domestic product per capita (GDPP), foreign direct investment (FDI) inflow, urbanization, fertility, and CO₂ emissions do not. An extension to sub-sample analysis by levels of income and clustering convergence clubs is employed to confirm the heterogeneity and complexity of development pathways among countries. There are several insights for researchers and governments regarding future research and policies, especially for the development of developing countries.

The main purpose of this paper is to examine the convergence hypothesis of House Price Index (HPI) in the case of 18 major Indian cities for the period 2014–2019.

To attain the authors main goal, this study applies a clustering algorithm advanced by Phillips and Sul. This test creates a club of convergence based on the growth of the cities in terms of HPI.

The study findings show the existence of two convergence clubs and one non-convergent group. Club 1 includes the cities with high HPI growth, whereas club 2 comprises of cities with least HPI growth. Cities belonging to the non-convergent group are neither converging nor diverging.

This study findings will benefit home buyers, sellers, investors, regulators and policymakers interested in the dynamic interlinkages of house price (HP) among Indian cities.

The majority of the studies are conducted in the case of China at the province or city levels. Furthermore, in the case of India, none of the studies has investigated the HP club convergence across Indian cities. Therefore, the present study fills this research gap by examining the HP club convergence across Indian cities.

The purpose of this study is to examine the club convergence of Financial integration (FI) in the case of 60 countries from 1970 to 2015. FI plays a vital role in economic growth through sharing the risk between countries, cross-border capital association, investment and financial information. It also leads to the efficient allocation of capital and capital accumulation, thereby improving the systematic growth and productivity of the economy. Literature on examining the convergence hypothesis of FI is scarce.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables the identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings indicate the non-convergence when all 60 countries were taken together. This highlights that the selected countries' have unique transition paths in terms of FI. Hence, the authors implement the clustering algorithm, and the estimation shows that 56 countries are categorised into three different clubs. However, for the rest of four countries, the results are sort of ambiguous, favouring neither convergence nor divergence.

On the basis of three country clubs, Club 1 presents the model countries such as the Netherlands, Singapore and Switzerland. The Club 2 and Club 3 countries can start making moves towards the model countries by making policy adaptations for trade, finance and business facilitation.

The existing literature provides a plethora of studies investigating the convergence of stock markets, exchange rates and equity markets, but studies on the convergence of FI, particularly across the countries, are scarce. This study contributes by bridging this gap. The study is unique in its type as it takes into account the multiple steady states or club convergence. This study also contributes in policymaking by suggesting Club 1 countries (the Netherlands, Singapore and Switzerland) as the model ones for the FI.

This paper aims to examine the convergence pattern of residential house prices in a panel of 55 major cities in Turkey over the period between 2010 and 2018 and to investigate the determinants of convergence club formations.

The authors applied the log t-test to identify the convergence clubs and estimated ordered logit model to determine the key drivers.

The results suggest that there are five convergence clubs and confirm the heterogeneity of the Turkish housing market. Istanbul, the commercial capital, and Mugla, an attractive tourist destination, are at the top of the housing market and followed by the cities located in the western part, particularly along the Aegean and Mediterranean coasts of Turkey. Moreover, the ordered logit model results point out that the differences in employment rate, climate, population density and having a metropolitan municipality play a significant role in determining convergence club membership.

Large-scale policy measures aiming to increase employment opportunities in rural cities of central and eastern provinces and providing lower land prices and property taxes in the metropolitan cities of Turkey can help mitigate some of the divergence in the house prices across cities.

The novelty of this study lies in employing a new data set at the city level containing 55 cities in Turkey, which is by far the largest in terms of city coverage among emerging market economies to implement the log t-test. It also contributes to the literature on city-specific determinants of convergence club formation in the case of an emerging economy.

EU countries, including those in Central and Eastern Europe, seem to have increasingly similar economies, allowing for the study of real convergence as a process of equalising income levels (measured by GDP per capita). Studies of income convergence in the European Union also have a regional dimension and often focus on convergence at the NUTS2 or NUTS3 regional level. The level of development and income in Polish regions differ significantly. The regional policy implemented at the national and EU level focuses on reducing these differences.

The main aim of the chapter is to analyse the income convergence process among regions in Poland and verify the effectiveness of regional policy implemented at the national and EU level.

The study uses Barro type regression for panel data, log t convergence test, and club clustering algorithm introduced by Phillips and Sul to identify patterns of club convergence in Polish regions. The data used for the study is the Local Data Bank provided by Statistics Poland, which includes gross domestic product per capita at the NUTS-3 level for 73 Polish regions over the period of 2000–2020.

The results of the study indicate a very weak convergence process for all Polish NUTS-3 regions and suggest a club convergence. The club convergence is characterised by regions with similar income levels clustering together. The regional distribution of clubs is similar to the regional distribution of income. The study's findings provide important insights into the effectiveness of regional policy in Poland and suggest that policymakers need to focus on policies that promote catch-up growth in less developed regions. The study also highlights the importance of supporting the most developed regions in the country as they can play a crucial role in driving the country's economic growth and prosperity.

There is vast disparity in public expenditure on science, technology and environment (STE) across various Indian states. Public expenditure on STE is crucial in maintaining symmetric growth, social cohesion and sustainable development. Literature on this topic is scarce, which prompted the investigation of club convergence of STE public expenditure. In particular, the purpose of this paper to study the club convergence of STE public expenditure in the case of 20 Indian states during the period from 1987–1988 to 2019–2020.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings of this paper show that all Indian states do not converge towards single steady states. This suggests a disparity in STE public expenditure across Indian states. Moreover, the findings favour three clubs that have their own unique transition paths. The results of this study are supported by the robustness check.

The findings suggest that the allocation of public expenditure on STE can be made based on club convergence to achieve social cohesion, sustainable development and millennium development goals across states.

Although several previous studies have investigated the convergence of public expenditure by considering either aggregate public expenditure or health/education expenditure, literature on the convergence hypothesis of STE public expenditure, particularly across Indian states, is scarce. Moreover, this paper is unique, as it examines multiple steady states or club convergence. Finally, this paper contributes to policymaking by suggesting which states should be given a push to achieve social cohesion and sustainable development.

This paper investigates income convergence using different convergence concepts and methodologies for 72 countries over the period between 1960 and 2010.

This study applies beta (β), sigma (s), stochastic and club convergence approaches. For β-convergence analysis, it derives the cross-country growth regressions of the Solow growth model under the basic and augmented Cobb–Douglass (CD) production functions and estimates them using cross-section and panel data estimators. While it employs both the widely used coefficient of variation and recently developed weak s-convergence approaches for s-convergence, it applies three different unit root tests for stochastic convergence. To test club convergence, it estimates the log-t regression.

The results reveal that (1) there exists conditional β-convergence, meaning that poorer countries grow faster than richer countries; (2) income per worker is not (weakly) s-converging, and cross-sectional variation does not tend to fall over the years; (3) stochastic convergence is not found and (4) countries in the sample do not converge to the unique equilibrium, and there exist five distinctive convergence clubs.

The results clearly show that heavily relying on one of the convergence techniques might lead researchers to obtain misleading results regarding the existence of convergence. Therefore, to draw reliable inferences, the results should be checked using different convergence concepts and methodologies.

Contrary to the previous literature, which is generally restricted to testing the existence of absolute and conditional β-convergence between countries, to the best of the author’s knowledge, this is the first study to consider and compare all originally and recently developed fundamental concepts of convergence altogether. Besides, it uses the Penn World Table (PWT) 9.1 and extends the period to 2010. From this point of view, this study is believed to provide the most up-to-date empirical evidence.

Like the cross-country convergence or divergence analysis in incomes to address the global phenomenon, the same analysis is also required to be done in the case of a group of states within a national territory. Further, it is also required to see whether convergence or divergence in incomes of the states is attributable to the convergence or divergence in their allocations of bank credits. Thus, this chapter aims at examining whether the selected major states in India are converging or diverging in the allocations of bank credit, and if so, what will be the magnitudes of decreases or increases in the level of disparities and inequalities in credit allocations. This study concludes that there is a clear diverging tendency of credit allocations of the states of India during the post-reform period so far as the absolute convergence hypothesis of the neoclassical theory is concerned. Further, in terms of the framework of σ convergence, the study observes that all phases of the Indian economy have produced converging paths of the inter-state credit allocations, and the path becomes diverging during the post-reform phase. Based on the quantifications of the magnitudes of disparities and inequalities in terms of CV, C4 concentration, HHI and Gini values, this study thus reveals that there are significant increases in the levels of disparities and inequalities in the allocations of credit to the states from the pre-reform to the post-reform phases. Therefore, the persistence of divergence in income or rising income inequality during the phase of the major reform program in India may be due to the persistence of divergence and rising inequality in the allocation of bank credit.

With the growth of income at the global level, the World Bank data show that there are rising levels of income disparity across countries, groups, regions and within the countries. This fact otherwise hints at the inter-country divergence in incomes, particularly between the developed and developing countries of the world. This chapter, therefore, attempts to examine the convergence or divergence in credit, GDP and HDI across the 10 selected countries for the period of 1990–2019 applying the neoclassical growth approach and the time series approach. The results of the exercise in line with the neoclassical theories on absolute convergence and sigma convergence show that the countries are unquestionably converging in GDP and HDI with mixed results in case of credit. The results of convergence in GDP and HDI in all the countries and their developed and developing counterparts provide a possible explanation as to why the cross countries’ income inequalities as well as world inequality in income and development are reducing over time. On the other hand, the results of the time series approach display that credit and HDI are converging in both absolute and conditional terms but the countries are converging in conditional terms only for GDP. Thus, the claims of the World Bank are not valid for the selected countries in the chapter, rather, they can be verified by taking other countries and groups into consideration.

This paper aims to explore the existence of convergence in non-monetary working conditions in Europe resorting to widely used definitions of this phenomenon and composite indexes of job quality.

The analysis relies on composite indexes, widely used in previous literature, for 207 regions in six different areas of job quality drawing on the microdata of the European Working Conditions Survey from 1995 to 2015. This study assesses the occurrence of convergence both in terms of dispersion of job quality outcomes (sigma-convergence) and, especially, regarding the existence of a catch-up process (beta-convergence).

This study finds evidence of both types of convergences in all the domains, with the exception of skills and discretion and prospects dimensions according to the sigma-convergence approach. The results do not suggest substantial differences between the 15 European Union countries before the 2004 enlargement and the new Member States and are robust to a wide range of changes in the sample and different econometric specifications.

Tot he best of the authors’ knowledge, this paper represents the first rigorous and systematic attempt of addressing the existence of convergence in non-monetary working conditions, applying formal and widely accepted definitions of this phenomenon. It contributes to our knowledge on this topic providing strong evidence of convergence in job quality. Those results can be of interest for scholars in Economics and other Social Sciences.