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“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

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.

The cyclical behavior of US crime rates reflects the dynamics of crime in the country. This paper aims to investigate the US's club convergence of crime rates to provide insights into whether the crime rates increased or decreased over time. The paper also analyzes the factors influencing the probability of states converging to a particular convergence club of crime.

The analysis is based on balanced panel data from all 50 states and the district of Columbia on violent and property crime rates covering 1976–2019. This yields a cross-state panel of 2,244 observations with 55 time periods and 51 groups. In addition, the author used a club clustering procedure to investigate the convergence hypothesis in the study.

The empirical results support population convergence of violent crime rates. However, the evidence that supports population convergence of property crime rates in the study is not found. Further analysis using the club clustering procedure shows that property crime rates converge into three clubs. The existence of club convergence in property crime rates means that the variation in the property crime rates tends to narrow among the states within each of the clubs identified in the study. Analysis based on an ordered probit model identifies economic, geographic and human capital factors that significantly drive the state's convergence club membership.

The central policy insight from these results is that crime rates grow slowly over time, as evident by the convergence of violent crime and club convergence of property crime in the study. Moreover, the existence of club convergence of property crime is an indication that policies to mitigate property crime might need to target states within each club. This includes the efforts to use state rather than national crime-fighting policies.

As crimes are committed at the local level, this study's primary limitation is the lack of community-level data on crime and other factors considered. Analysis based on community-level data might provide a better representation of crime dynamics. However, the author hopes to consider this as less aggregated data are available to use in future research.

The paper provides new insights into the convergence of crime rates using the club convergence procedure in the USA. This is considered an improvement to the methods used in the previous studies.

The purpose of this paper is to examine the convergence analysis of public debt among Indian states using annual data from 1990‒1991 to 2014‒2015.

The paper tests this hypothesis using club convergence technique propounded by Phillips and Sul (2007).

The results reveal the existence of debt divergence for overall Indian states. States are formed into four clubs on the basis of their level of debt, and three clubs support the hypothesis of club convergence. Further, the total public debt decomposes into three compositions such as market loans, bank loans and loans and advances from the central government. The existence of convergence is found for market loans and bank loans; however, the presence of divergence is found in case of loans and advances for overall states.

Since public debt plays an important role for fiscal health of the Indian states, findings of this study suggest to squeeze the fiscal consolidation further for Indian states whose debts as a percentage to gross state domestic product are on the higher side. Further, the examination of debt convergence helps to manage debt level among the states because heavy dependence on public debt could retard investment and economic growth.

Whereas bulk of empirical studies emphasize on examining the linkage between public debt and economic growth, and issue on debt sustainability across Indian states, examination of convergence of debt and its compositions (markets borrowings, bank loans and loans and advances from the central government) among the Indian states is scanty.

This paper investigates the per-capita output club convergence in case of 120 countries for the period 1995–2015. Further, we disaggregate per-capita output into three broad sectors such as agriculture, industry, and service and investigate the convergence hypothesis.

The paper tests this hypothesis using the Phillips and Sul panel club convergence technique.

Our findings are as follows: (1) our results indicate the evidence of output divergence for the full sample; (2) when countries are divided into different clubs, the results exhibit the sign of per capita output club convergence both for aggregate and three major sectors. Further, this study confirms that industry's per capita output is the main driver for aggregate per-capita output club convergence in case of club 1. For club 2, agriculture's per capita output is a primary source for aggregate per capita output club convergence. Likewise, in the case of clubs 3 and 4, we find the service sector's per capita output is the main component for aggregate per-capita output club convergence; (3) both the service and industry sectors are major drivers for aggregate per-capita output club convergence.

This study suggests to the policymaker that sector-specific policies need to be adopted to boost the per-capita output growth by improving the performance of each of the sectors across the countries.

Notwithstanding, there are many studies that examine the output convergence using a notion of beta and sigma convergence, but studies regarding per capita output club convergence both at the aggregate and sectoral level are scanty.

This paper aims to examine the per capita income convergence of 57 member countries of the Organization of Islamic Cooperation (OIC) over the period 1990–2017 and to investigate the determinants of convergence club formations.

The authors applied the methodology of Phillips and Sul (2007, 2009) to identify the convergence clubs and estimated several-ordered logit models to determine the key drivers.

The results support existence of two convergence clubs and one diverging unit, indicating that 30 and 26 member countries form two separate groups converging to their own steady-state paths. They also suggest a significant productivity divergence between these clubs. The authors showed that the number of convergence clubs started to decline after the global financial crisis in 2008. Moreover, they found that fixed capital formation, education and political stability are key drivers of convergence club membership.

There is a strong need for large-scale policy interventions to close the gap between leading and lagging clubs of the OIC. A substantial investment in human and physical capital seems necessary for lower-income OIC countries.

This is the first empirical study on the existence of convergence clubs among member countries of the OIC.

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.

The purpose of this paper is to investigate the food price inflation convergence across countries and regions. This study aims to identify the key drivers for food price inflation across countries and regions.

We test whether the international food price inflations are converging over time using the log t convergence test and clustering analysis. These inflation data are collected from the Food and Agriculture Organization of the United Nations.

The test results suggest that there is little evidence of overall convergence. Then we utilize a clustering algorithm and the results support that there is strong evidence of multiple convergence clubs. In addition, we examine the transition path of the various convergence and find that social stability regulation together with economic conditions are important determinants of convergence club membership.

First off, local conflict and economic environment result in food supply and prices, but this study is limited to the dynamics of prices.

Food prices inflations are not converging to single common price inflation, but there exist subgroups of countries or regions within which food price inflation tends to converge. These groupings tend to be related to the economic development and social stability of countries and regions.

The authors believe that any analysis of food price inflations that does not consider the political environment and economic conditions dynamics will likely be omitting important components of food price dynamics.

This study uses a unique data set covering 198 countries and regions and provides a comprehensive analysis of international food price inflation convergence identifying the key drivers of convergence club membership.