Formation Of Convergence Clubs Research Articles

Transition towards a low-carbon global economy: An integrated analysis of club convergence, catch-up and the agenda 2030

This study employs the Biennial Malmquist-Luenberger (BML) productivity approach to measure Green Total Factor Productivity (GTFP) in 120 countries from 1990 to 2021. Next, the Phillips and Sul methodology is applied to investigate whether these countries have witnessed an absolute convergence process, or whether there has been a club convergence process. We also use an Ordered Logit method to identify the factors affecting the formation of clubs. Finally, the fuzzy regression discontinuity method is used to examine the exogenous shock of the 2030 agenda on the global GTFP. The key findings are presented as: (1) during the study period, the global GTFP on average has shown an upward trajectory. The European region performed better than the other regions, whereas Sub-Saharan Africa lagged in GTFP. Developed economies led in technological progress, while developing ones have achieved slightly higher carbon efficiency; (2) although the full sample divergence was supported, three clubs were identified with significant disparities in GTFP. We found that per capita GDP, industrial structure, energy structure, and particularly, indigenous and foreign innovations play major roles in explaining the formation of convergence clubs; (3) there was an apparent positive jump at the cut-off, indicating agenda 2030′s favorable treatment effect on the global GTFP. Therefore, all countries, poorer and richer alike, should use the half-way momentum to self-critically review and revise their national SDG strategies and commit to strengthening multilateralism.

Provincial income convergence in Vietnam: spatio-temporal dynamics and conditioning factors

In this article, we use a three-step procedure that combines the log t convergence test, Explanatory Spatial Data Analysis, and ordered logit regression to determine the spatio-temporal dynamics and determinants of provincial income clustering in Vietnam during the 2010–2020 period. Our findings are three-fold. First, provincial income clustering in Vietnam follows patterns of club convergence towards multiple equilibria. Seven convergence clubs encompassing 61 provinces are identified. Second, spatial autocorrelation encourages neighboring provinces to converge toward shared income equilibria. High-income clusters are observed in the Northern and Southern Key Economic Regions, while low-income clusters are concentrated in the mountainous areas of Northern Vietnam. Finally, both internal and external factors significantly affect the formation of convergence clubs. Vital internal factors include localities’ initial conditions of physical capital and structural change. Meanwhile, external factors refer to spatial externalities among neighboring provinces. We highlight spatial complementarity in physical capital accumulation and spatial competition in industrial intensification among neighboring provinces.

Productivity convergence in international trade: The role of industrial-based policies

The Prebisch-Singer hypothesis implies divergence in the terms of trade between developing and developed countries but does not eliminate the possibility of convergence if productivity in developing countries’ exports sufficiently improves. This study constructs a new and unique export sophistication dataset for the productivity of high-technology export products to examine convergence behavior of developed and emerging market countries. Relative and weak σ-convergence tests reveal overall productivity divergence in international trade. However, there are convergence clubs whereby income, R&D expenditures, foreign direct investment, and educational expenditures yield similar effects on the convergence club formation in both developed and emerging market countries.

Convergence in renewable energy innovation and factors influencing convergence club formation

Innovation and adaptation of renewable energy technologies significantly reduce carbon dioxide (CO2) emissions and increase energy efficiency. Understanding the convergence patterns in renewable energy innovation will enable policymakers to design policies to increase energy efficiency and renewable energy consumption and reduce CO2 emissions. This paper applies the convergence algorithm proposed by Philips and Sul to assess the convergence in renewable energy innovation for 90 countries covering the period between 1993 and 2018. This paper also examines the determinants/factors driving the convergence clubs of the countries using Probit and Logit regression. The convergence analyses suggest that there is no global convergence in renewable energy innovation. Findings highlight two convergence clubs: i) a club comprising more innovative countries and ii) another club that includes less innovative countries. We find that countries with higher income per capita, CO2 emissions per capita, research and development (R&D) investment, better environmental regulations and stronger institutional settings are more likely to be part of the innovative club. Countries should increase their R&D investment and environmental regulations and improve their institutional quality to increase their likelihood of belonging to a more innovative club. Furthermore, less innovative countries could promote policies to transfer renewable energy technologies from innovative countries.

Related and unrelated variety and convergence to technological frontier: empirical evidence for Polish regions

ABSTRACT This paper examines the effects of related and unrelated variety on total factor productivity (TFP) in Poland. Based on dynamic panel data regression results for Polish regions in 2003-2019, we find the positive effect of related variety and the strong negative effect of unrelated variety on TFP. This implies that regions with high related and low unrelated variety optimize TFP. Using the estimated TFP values, we tested for TFP convergence to the technological frontier using convergence tests that take into account significant differences in technological advancement across regions. We reject TFP convergence for all regions, but we find evidence of regional club convergence. The results of the convergence tests obtained for the simulation variants indicate that changes in related and unrelated variety structures may lead to the formation of convergence clubs with the regional technological leader. Furthermore, the changes primarily in related variety structures lead to the convergence of some regions to the regional technological frontier.

Convergence clubs and spatial structural change in the European Union

This article studies regional income convergence and its conditioning factors in 267 subnational regions of the European Union during the 2003–2016 period. Building on previous research that documents the formation of multiple convergence clubs in per-capita income, we study the role of structural change and spatial dependence as key conditioning factors of the club convergence process. Our results are threefold. First, we document that the spatial distribution of the convergence clubs shows a strong degree of spatial dependence. Second, when we study the evolution of structural change and spatial dependence, our results show that the share of manufacturing has been decreasing, while its degree of spatial dependence has been increasing over time. In contrast, the share of knowledge-intensive services has increased, while its degree of spatial dependence has decreased. Third, we evaluate the role of structural change and spatial dependence in the formation of convergence clubs using a spatial ordered-logit model. Our results show that when spatial dependence is omitted from the econometric specification, both manufacturing and knowledge-intensive services are not significant predictors of club convergence. Only when spatial dependence is added to the specification do most of the structural change variables become statistically significant. In addition, there are contrasting spatial effects between variables of structural change. The geographical spillover effects for manufacturing and routine services are statistically significant, while knowledge-intensive services do not exhibit such significant spillover effects. Overall, our results highlight the joint importance of structural change and spatial dependence in the formation of convergence clubs. Specifically, the notion of spatial structural change deserves further attention, as it appears to play a major role in the evolution of regional disparities in the European Union.

Are greenhouse gas emissions converging in Latin America? Implications for environmental policies

This paper investigates greenhouse gas emissions convergence among nineteen Latin American countries, for the period 1970 to 2018. To that end, we use the Phillips–Sul methodology to examine whether these countries have followed an absolute convergence process, or whether there has been a club convergence process. Our results offer important insights into the greenhouse gas emissions catch-up exhibited by several countries, and do not support the hypothesis that all countries of the Latin American region, taken together, converge to a single equilibrium in greenhouse gas emissions intensity. We find strong evidence of subgroups that converge to different steady states. An iterative testing procedure reveals the existence of different patterns of behavior and shows that such emissions are not uniform across these countries. We also estimate an Ordered Logit Model to identify the forces underlying the creation of clubs and the likelihood that any given country will be a member of any convergence club. Estimates from an Ordered Logit Model reveal that income, population density, openness, natural resources rents, and – particularly – the level of corruption, play a crucial role in explaining the formation of convergence clubs. The existence of clubs means that the climate policies aimed at reducing emissions should consider the specific characteristics of the countries, according to the club convergence results.

Club Convergence of Economies' Per Capita Carbon Emissions: Evidence from Countries That Proposed Carbon Neutrality.

To achieve the long-term goals outlined in the Paris Agreement that address climate change, many countries have committed to carbon neutrality targets. The study of the characteristics and emissions trends of these economies is essential for the realistic formulation of accurate corresponding carbon neutral policies. In this study, we investigate the convergence characteristics of per capita carbon emissions (PCCEs) in 121 countries with carbon neutrality targets from 1990 to 2019 using a nonlinear time-varying factor model-based club convergence analysis, followed by an ordered logit model to explore the mechanism of convergence club formation. The results reveal three relevant findings. (1) Three convergence clubs for the PCCEs of countries with proposed carbon neutrality targets were evident, and the PCCEs of different convergence clubs converged in multiple steady-state levels along differing transition paths. (2) After the Kyoto Protocol came into effect, some developed countries were moved to the club with lower emissions levels, whereas some developing countries displayed elevated emissions, converging with the higher-level club. (3) It was shown that countries with higher initial emissions, energy intensity, industrial structure, and economic development levels are more likely to converge with higher-PCCEs clubs, whereas countries with higher urbanization levels are more likely to converge in clubs with lower PCCEs.

Biocapacity convergence clubs in Latin America: an analysis of their determining factors using quantile regressions.

Latin America experiences an increasing urban primacy index and a rapid expansion of the financial system, putting direct pressure on the demand for resources to satisfy the consumption of large cities. We investigate the convergence of per capita biocapacity in 16 Latin America countries and evaluate the factors that influence its evolution over time. Specifically, we analyze the impact of the urban primacy index, economic progress, and the financial globalization index on the convergence of per capita biocapacity. We use the methodological framework developed by Phillips and Sul Econometrica 75:1771-1855, (2007) to analyze the convergence and the formation of convergence clubs of biocapacity during 1970-2017. The findings indicate that the countries of the region do not share a common trend of biocapacity, although they are grouped into five converging clubs. Biocapacity transition analysis reveals that countries have heterogeneous transition pathways between them. Using marginal effects, we find that the urban primacy index and economic progress reduce the biocapacity. The effect of the financial globalization index on biocapacity is not conclusive. The quantile regressions reveal that quantiles' impact of the urban primacy index and financial globalization on per capita biocapacity is heterogeneous. However, the effect of economic progress on biocapacity that predominates among quantiles is positive. The adoption of common policies among the countries that form the converging clubs could improve the effectiveness of pro-environmental policies and promote the achievement of the Sustainable Development Goals related to environmental quality.

Club convergence and factors of income inequality in the European Union

AbstractThe measurement of inequality and its determinants are major tasks within the economic literature. The main objectives of this paper are to identify patterns of convergence in the income inequality in European Union countries and to investigate the factors behind the formation of convergence clubs. For those purposes and considering the Gini index during the period 2007–2018, the club convergence approach and an ordered logit model are employed. The results show four clubs and four divergent countries. In addition, the analysis identifies certain factors, such as economic openness, public intervention and education, as the main drivers of inequality reduction. Finally, the results from the club convergence analysis for an alternative inequality measure, specifically the ratio 80:20, are similar to those achieved in the case of the Gini index.

Club convergence and drivers of house prices across Turkish cities

PurposeThis 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.Design/methodology/approachThe authors applied the log t-test to identify the convergence clubs and estimated ordered logit model to determine the key drivers.FindingsThe 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.Practical implicationsLarge-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.Originality/valueThe 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.

Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals

The aim of this paper is to test for overall and cluster convergence of housing rents across Polish provincial capitals and to identify drivers of convergence club formation. In order to achieve the goal of the study, several novel convergence tests were used, including the Kong et al. (J Econom 209:185–207, 2019. https://doi.org/10.1016/j.jeconom.2018.12.022) and Phillips and Sul (Econometrica 75:1771–1855, 2007. https://doi.org/10.1111/j.1468-0262.2007.00811.x) approaches. Moreover, club convergence analysis was carried out in four different configurations, varying in the technique of trend component extraction from the data. In particular, three well-known methods of time series decomposition were used, i.e. the Hodrick–Prescott, Butterworth and Christiano–Fitzgerald filters, as well as the most recent boosted Hodrick–Prescott filter. The results indicated that rental prices across the studied cities do not share a common path in the long run. It is possible, however, to identify convergence clubs where rents are moving towards a club-specific steady state. Detailed analysis of the structure of estimated clusters showed that data filtering using the boosted Hodrick–Prescott method leads to the most reliable allocation of cities to convergence clubs. Moreover, the estimation of logit models revealed that the likelihood of any two cities belonging to the same convergence club depends mainly on similar levels in terms of the unemployment rate, housing stock, city area, and the number of students. Finally, recommendations for local and national policy-makers concerning the development of the rental market have been formulated, particularly in the areas of urban land-use planning policy, housing legislation and public–private partnerships.

Convergence Triggers in Africa: Evidence from Convergence Clubs and Panel Models

AbstractThis paper investigates the formation of convergence clubs and examines the drivers of growth convergence in Africa by accounting for individual heterogenous effects and establishing transitional paths. We particularly employ the sophisticated log t test to identify underlying convergence clubs and use LSDVC as a benchmark model for analysing the drivers of convergence. We also apply the System Generalized method of moments (GMM) model for sensitivity purposes. Our results reveal four core convergence clubs; seemingly characterised by the measures of institutional stability with distinct transitional paths. We consequently highlight the importance of initial conditions, human capital and institutions in the formation of convergence clubs. Thus, the paper provides insights into the adoption of differentiated development policies consistent with the specific conditions of African countries with the integration agenda driven by accelerated levels of human capital development and technological progress.

Do regional house prices converge? Evidence from a major developing economy

This paper analyzes the long-run convergence of regional house prices in a major developing country, Turkey. Using a non-linear time-varying factor model and quarterly hedonic house price data from 2010 to 2018, we find that house prices do not converge across 26 regions of Turkey. Results reveal that the regions can be grouped into seven convergence clubs and one divergent club, confirming the Turkish housing market’s heterogeneity and complexity. We extend the analysis to explore the possible factors driving the convergence clubs. We find that income, population, education, unemployment, being in an earthquake zone, and inflow of Syrian refugees are significant driving forces in explaining convergence club formation. These outcomes will benefit home buyers/sellers, investors, regulators, and policymakers interested in analyzing the dynamic interlinkages among house prices and the effects of shocks originating from the regional housing markets in developing countries.

Spatial dynamics of consumer price in Indonesia: convergence clubs and conditioning factors

This paper aims to identify convergence clubs in regional price across 34 provinces in Indonesia and investigate conditioning factors of club formation. We analyze regional monthly consumer price data from January 2012 to December 2019 with a novel club convergence test developed by Phillips and Sul (Econometerica 756:1771–1855, 2007), and show that regional consumer price does not converge into a single universal equilibrium. Instead, there are four convergence clubs identified. Further investigation shows that labor productivity, inflation expectation, consumption growth, and spatial externalities influence the convergence club formation. From a policy perspective, our findings of multiple convergence clubs and their influencing factors alert policy makers to rethink the possibility of augmenting uniform monetary policy with region-specific inflation management measures.

Interregional Inequality in Africa, Convergence and Multiple Equilibria: Evidence from Night-Time Light Data

Understanding the dynamics of interregional inequality is important when formulating development policies. In this paper, we investigate the convergence pattern in regional inequality within 49 African countries over the period 1992-2012 using satellite night-light based inequality proxies. We find evidence of multiple equilibria in regional income inequality. Four convergent clubs is distinguished instead of overall convergence. The results show that countries with high regional inequality steadily do not converge over time towards those of countries with low regional inequality, indicating that these countries are indeed stuck in regional income inequality traps. From the convergence analysis, we further analyze through an ordered logit estimation those relevant variables that drive convergence club formation. We find that the level of initial conditions such as GDP per capita, urbanization, natural resources rents and the change in country size are significant in explaining convergence club formation.

Can neighbor regions shape club convergence? Spatial Markov chain analysis for Turkey

This study explores the impact of neighbor regions on the club convergence for Turkey. Markov chain analyses are augmented by using the spatial lag conditioning. The central hypothesis is that, having a rich (poor) spatial proximity increases the chances to move towards higher (lower) income classes. Our preliminary evidence covers the 1975–2017 period and points out that Turkish regions are not converging on average rather converging to varying income levels. This signals the formation of convergence clubs. Our augmented analyses highlight that the club convergence process is influenced from the income level of neighbor regions. Those regions whose neighbors belong to high income classes have higher chances to move to higher income classes, whereas the peripheral regions linked with the poor ones are getting more isolated. Our results highlight that regional policy framework and local economic activity has an influence beyond the administrative boundaries of regions. This calls for spatially flexible and smart local policies to combat with regional disparities.

World economic convergence: Does the estimation methodology matter?

An extant empirical literature produces evidence on economic convergence using methods that assume an underlying deterministic trend. Competing approaches that assume a stochastic trend, however, produce only limited evidence of economic convergence. In this paper we address this puzzling feature of the literature by providing a comprehensive analysis of economic convergence using three methodologies that cover all possible underlying assumptions: deterministic, stochastic, and combination trends. We also develop a method for an overall Stochastic Convergence Rate Index, that combines the outcomes of alternative stochastic tests and provides a single measure of the intensity of stochastic convergence. We consider 135 economies over the period 1980–2017. We find that economic convergence occurs at a global level through the formation of convergence clubs, and economic convergence emerges as a deterministic rather than a stochastic process. Tests that ignore deterministic trends tend to understate the evidence for convergence.

Convergence analysis of city-level energy intensity in China

Understanding the convergence patterns of energy intensity and the drivers leading to the club convergence are of great significance for local governments to implement targeted policies to improve energy efficiency. With this in mind, we begin with the collection of energy consumption data of 193 Chinese cities at prefecture level or above, then we adopt the log t-test and clustering algorithm to investigate convergence characteristics of energy intensity. Besides, the Ordered Probit model is adopted to investigate the drivers that affect the formulation of convergent club. We identify four convergent clubs among total 193 cities, and these clubs show great differences in energy intensity. Marketization degree, population density, foreign direct investment, resource endowment, and industrial structure are recognized as the drivers of the formation of convergence clubs. This paper adds more evidence to understand the energy intensity gap, we propose that upgrading the industrial structure, exerting economic assemble advantage, enhancing the level of opening up, and improving the marketization level are favorable measures to reduce energy intensity.

Property heterogeneity and convergence club formation among local house prices

We investigate the extent of convergence club formation in local house prices. Our study is novel in a number of key ways. First, new insights are obtained through utilising a large disaggregated panel dataset comprising multiple types of housing (detached, semi-detached, terraced housing and flats) for a very large sample of 348 England and Wales local authorities. Second, we analyse through probit estimation those factors that drive convergence club formation. Third, we also consider within-city club formation as well as club formation during periods of house price bubbles. Using a study period of more than two decades, we find the presence of divergence or multiple house price convergence clubs rather than a single club. While location, distance, income, population density, congestion and education are significant in explaining convergence club formation, housing type is also an important factor with convergence less likely among detached, semi-detached and terraced housing than among flats.