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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.

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.

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.

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.

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 integration of housing markets in Canada by examining housing price data (1999–2016) of six metropolitan areas in different provinces, namely, Calgary, Vancouver, Winnipeg, Toronto, Montreal and Halifax. The authors test for cointegration, driver cities of long-run relationships, long-run Granger causality and instantaneous causality in light of the global financial crisis (GFC) (2007–2008).

The authors use Johansen’s system cointegration approach with structural breaks. Moving average representation is used for common stochastic trend(s) analysis. Finally, the authors apply vector error correction model-based Granger causality and instantaneous causality.

Cities’ housing prices are in long-run equilibrium. Post-crisis Canadian housing markets became more integrated. The Calgary, Vancouver, Toronto and Montreal markets drive the Canadian housing market, leading all cities toward long-run equilibrium. Strong long-run Granger causality exists, but the authors observe no instantaneous causality. Price information takes time to disseminate, and long-run price adjustments play a significant role in causation.

The findings of cointegration increasing after the GFC and strong lead–lag can be used by investors to arbitrage and optimize portfolios. This can also help national and local policymakers in mitigating risk. Incorporating these findings can lead to better price forecasting.

This study presents many novelties for the Canadian housing market: it is the first to use repeat-sales regional pricing indices to test long-run behaviors, conduct common stochastic trend analyzes and present causality relations.

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.

The purpose of the study is to examine the long-run convergence properties of condominium prices based on the ripple effect for five major US metropolitan areas (Boston, Chicago, Los Angeles, New York and San Francisco). Specifically, we test for both overall convergence in condominium prices and the possibility of distinct convergence clubs to ascertain the interdependence of geographically dispersed metropolitan condominium markets.

Our analysis uses two approaches to identify the convergence properties of condominium prices: the Lee and Strazicich (2003) unit root test with endogenous structural breaks and the Phillips and Sul (2007, 2009) time-varying nonlinear club convergence tests.

The Lee and Strazicich (2003) unit root tests identify two structural breaks in 2006 and 2008 with the rejection of the null hypothesis of a unit root and long-run convergence in condominium prices in the cases of Boston and New York. The Phillips and Sul (2007, 2009) club convergence test reveals the absence of overall convergence in condominium prices across all metropolitan areas, but the emergence of two distinct convergence clubs with clear geographical segmentation: on the east coast with Boston and New York and the west coast with Los Angeles and San Francisco while Chicago exhibits a non-converging path.

The results highlight the distinct geographical segmentation of metropolitan condominium markets, which provides useful information to local policymakers, financial institutions, real estate developers and real estate portfolio managers. The limitations of the research are the identification of the underlying sources for the convergence clubs identified due to the availability of monthly data for a number of potential variables.

The absence of overall convergence in condominium prices, but the emergence of distinct convergence clubs that reflects the geographical segmentation of metropolitan condominium markets raises the potential for portfolio diversification.

Unlike previous studies that have focused on single-family housing, this is the first study to examine the convergence of metropolitan area condominium prices.

This survey of the literature on the convergence of carbon dioxide (CO₂) emissions informs researchers on areas for future research by summarizing the countries examined, the types of convergence tested and the methodological approaches undertaken.

This survey examines peer-reviewed empirical studies of CO₂ emissions convergence with respect to country coverage and alternative approaches to test for various types of convergence.

For large multicountry studies, the support for convergence is quite limited. However, studies focused exclusively on a subset of countries defined by income classification, geographic region or institutional structure reveal the finding of convergence is more prevalent. Studies at the subnational level have primarily been in the cases of the US and China with the exception of two studies across industry sectors in Portugal and Sweden.

This study focuses exclusively on peer-reviewed published studies.

This study is relevant to the design of mitigation strategies to reduce CO₂ emissions and the assumption of convergence underlying climate change models.

As a major component of greenhouse gas emissions, CO₂ emissions is of global importance in its impact on the environment and climate change.

This study provides the most recent and comprehensive survey of the empirical literature on the convergence of CO₂ emissions.

This paper investigates the development of efficiency and the progress of banking integration in the European Union by checking for convergence among banks of European and Eurozone countries as well as contrasting the results with those of United States banks.

Initially, we employ the two-stage semi-parametric double bootstrap DEA method, which absorbs the effects of possible integration barriers in the measurement of efficiency. Afterwards, we apply a panel data model, in order to investigate the process of banking integration by testing for convergence and for convergent clusters in banking efficiency.

Our main findings show that the bank efficiency of the US is considerably higher than that of the Eurozone and the European Union. Although there is no evidence of convergence across the banking groups, our results indicate the presence of club convergence. We also conclude that the US banking system is closer to convergence than the Eurozone and the European Union banks. Nevertheless, this outcome is subject to change in the future due to the fact that Eurozone and European Union banks' speed of convergence is higher than that of US banks.

Our survey is unique in trying to check for convergence while controlling for country-specific and bank-specific factors that affect the efficiency of European and Eurozone banks. Moreover, recent literature does not compare the convergence of efficiency of Eurozone, European and US banking. Finally, in our paper special consideration was given to the comparison of commercial, cooperative and savings banks, as subsets of our banking groups.