Convergence Clubs Research Articles

Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, β-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute β-convergence, and conditional β-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

Global long-run convergence of carbon emissions and intensity vis-à-vis countries' industrial profiles

<p>We examined distribution dynamics and the long-run evolution of cross-country relative per capita carbon emissions (REPC) and intensity (RCI) vis-à-vis countries' two factors: industrial and services sectors' output. Unlike other researchers, we employed two visual tools of the distribution dynamics approach and used a panel of 217 countries. We ranked the countries based on the two factors and grouped them into four quartiles (Q1 to Q4) for each factor, resulting in eight subsamples. The results suggested long-run absolute convergence in REPC (RCI) only among highly industrialized (Q3 and Q4) countries. However, two to four convergence clubs emerged within the remaining subsamples. Besides a few (many) of the least (the most) industrialized countries converging towards the global average RCI, clubs occur at levels significantly below or above the worldwide average. The convergence was more (less) significant and towards higher (lower) REPC and RCI values for economies with low (high) industrialization. We constructed a policy priority list consisting of the least services-oriented (Q1) countries with REPC (RCI) values of 3 (7.4) and 20 (30) percent probability of further divergence from the global average in the coming years. From the perspective of climate policies aiming at reducing and converging carbon emissions, these countries require the urgent development and implementation of coordinated, bespoke policies and ongoing monitoring.</p>

GHG Emissions in the Eu-28: A Multilevel Club Convergence Study of the Emission Trading System and Effort Sharing Decision Mechanisms

GHG Emissions in the Eu-28: A Multilevel Club Convergence Study of the Emission Trading System and Effort Sharing Decision Mechanisms

Konvergencija profitnih stopa u Evropskoj ekonomskoj oblasti - analiza panel podataka

This paper examines profitability disparities across the European economies using the aggregate and sectoral data for the period from 1995 to 2019 and applying a combination of panel unit root tests and the club convergence procedure. For most of the sectors, no convergence was identified at the aggregate level. Convergence within the clubs to multiple equilibrium levels, however, was identified. This convergence pattern was the most typical in the knowledge-intensive service sectors. The exogenous shocks had temporary effects on the economies' profit rates (thus contributing to convergence), whereas the country and sector-specific profitability components were characterized by stochastic behavior (attesting to nonconvergence). Overall, the persistence of profitability disparities was demonstrated. The findings suggest the importance of the firm-specific and local profitability drivers and the limited effects of the macroeconomic and competition policies on profit rates.

The path to global climate justice: From the perspective of regional discrepancy in embodied carbon emissions

Achieving climate justice is an important goal and basic principle of global climate governance. This paper evaluates the progress of achieving global climate justice by quantitatively depicting the evolution characteristics, group differences and driving factors of global embodied carbon emissions. The results indicate that the phenomenon of embodied carbon inequality is more obvious. Furthermore, a data-driven clustering algorithm is adopted to divide the world's major economies into four convergence clubs based on the embodied carbon emissions levels. We find that the embodied carbon emissions gap between different clubs has widened since 2008, which may be related to the re-industrialization of developed countries. The results of SDA analysis indicate that the embodied carbon emissions of developed countries, such as the United States, are more driven by per capita end-use. On the contrary, unclean consumption and investment structure is the main driving force for the increase of embodied carbon emissions in developing countries such as China. Therefore, efforts should be made in developing countries on the clean adjustment of consumption and investment structure to promote the convergence of embodied carbon emissions with developed countries.

Regional convergence in the European Union – Factors of growth between the great recession and the COVID crisis

In this paper, we provide a new look at convergence in the EU while focusing on development at the regional level between the Great Recession and the recent COVID crisis. We use the log t convergence test by Phillips and Sul (2007) to analyze convergence in income level among the European regions. We identified five convergence clubs rather than supporting the overall convergence hypothesis. Furthermore, we investigated the determinants of convergence club membership using logistic regression. Our results confirmed high inequality within the member states and a shifting geographic pattern of the top-performing regions, with the increasing prominence of the manufacturing core in southern Germany and the surrounding areas. We found a positive association between membership in higher clubs, research and patent activities, and specialization in manufacturing. We also confirmed the positive economic performance of capital cities and the main metropolitan areas.

Possibilities for mitigating the Matthew effect in low-carbon development: Insights from convergence analysis

Under global pressure of climate change, adopting an economic model of low-carbon development has become an inevitable choice for economies worldwide. Playing an important role in economics and carbon emission reduction, cities are crucial in development strategies planning at both national and regional levels. Based on the data of 198 prefecture-level cities in China from 2003 to 2019, this paper quantifies the low-carbon development index for each city, and analyzes the low-carbon development trend within cities using the club convergence method, and finally identifies the relevant factors influencing the low-carbon developmentby taking into account the divergent trends. The study found that: (1) The national low-carbon development index does not exhibit spontaneous convergence. (2) Cities ultimately fall into four converging clubs. Club 1 tends to converge toward a high level of low-carbon development, while Clubs 2, 3, and 4 tend to converge toward lower levels or may fail to achieve low carbon development, resulting in a widening gap with Club 1. This implies the existence of the Matthew effect. (3) Factors such as the financial interrelations ratio, foreign direct investment, urbanization, employment figures, and transportation enhancements can promote low-carbon development and alleviate the Matthew effect.

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.

Financial Development Convergence: Evidence from Top and Bottom Globalised Developing Economies

ABSTRACT This paper investigates the pattern of the financial development convergence for the top (Europe and Central Asia) and the bottom (South Asia) globalized developing regions from 1984 to 2016. We employ the Philips-Sul club convergence approach to measure the financial development convergence’s speed. The results validate the convergence of financial development in all countries, including the top and bottom of globalized developing regions. Interestingly, the speed of financial development convergence is less in the bottom globalized developing region than in the top globalized developing region. However, these results vary across developing regions in the case of financial institutions and financial markets. Therefore, solid financial market governance can provide a productive and efficient financial system, particularly in the bottom globalized economies.

The convergence mechanism and spatial spillover effects of urban industry-university-research collaborative innovation performance in China

ABSTRACT This study deconstructs the triple helix structure of urban industry-university-research collaborative innovation into a two-stage chain structure of knowledge innovation and technological innovation. Based on data of 285 China prefecture-level cities from 2004 to 2018, this study measures the urban industry-university-research collaborative innovation performance using the network data envelopment analysis model. Additionally, it clarifies its spatial convergence mechanism and spatial spillover effects using the spatial convergence test and spatial Durbin model. The results suggest that: (1) the performance of China's urban industry-university-research collaborative innovation at different stages shows a spatial pattern with obvious regional differences and diversified development modes. (2) The overall performance shows a trend of gradual σ convergence with a slightly fluctuating rate, and the gap is constantly decreasing. Additionally, it shows an absolute β convergence trend at different stages, with an obvious geospatial club convergence trend in the eastern, central, and western regions. (3) The spatial spillover effects of ‘research-to-production’ performance and overall performance are stronger than that of ‘university-to-research’ performance. Finally, the collaborative innovation performance of various cities is dominated by the polarisation effect, and the its role as the driving force of regional innovation needs to be strengthened.

Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal

Forestry’s high-quality development is crucial for China’s sustainable ecological, economic, and social progress. To elevate the efficiency of carbon sequestration in forestry, continuously improve the increment of carbon sinks, and contribute to achieving carbon neutrality, it is crucial to accurately assess the level of carbon sequestration efficiency in China’s forestry and explore its long-term evolution trend. In this paper, a super-efficiency SBM model, which combines the SBM model with the super-efficiency method and considers the relaxation variables, was selected to evaluate the forestry carbon sequestration efficiency of 31 provinces in China; likewise, the temporal development features of the efficacy of Chinese forests in sequestering carbon were examined using the nuclear density estimation method. Secondly, the study constructed traditional and spatial Markov probability transfer matrices to further explore the spatiotemporal evolution of carbon sequestration efficiency within Chinese forestry. Finally, combined with the Markov chain infinite distribution matrix, the future trajectory of carbon sequestration efficiency in China’s forestry was scientifically forecasted. The findings indicate that: (1) The average carbon sequestration efficiency of forestry in China showed a stable increase with fluctuations and reached the optimal state in 2018. The carbon sequestration efficiency level of various forest regions was always portrayed as southwest forest region > southern forest region > northeast forest region > northern forest region. From 2003 to 2018, there were significant differences in forestry carbon sequestration efficiency among provinces. The distribution of forestry carbon sequestration efficiency exhibited a “three-pillar” distribution pattern with Xizang, Zhejiang, and Heilongjiang as the core, and the marginal regions continuously promoted the carbon sequestration efficiency to the inland. (2) The type of transfer of forestry carbon sequestration efficiency in China is stable, and it is difficult to achieve cross-stage transfer in the short term. Moreover, the forestry carbon sequestration efficiency of each province tended to converge to a high (low) level over time, showing a “bimodal distribution” of low efficiency and high efficiency, indicating the existence of the obvious “club convergence phenomenon”. (3) Forecasting from a long-term evolution trend perspective, the outlook for the future evolution of forestry carbon sequestration efficiency in China is optimistic, and the overall trend was concentrated in the high-value area. Therefore, future forestry development in China should contemplate both internal structure optimization and coordinated regional development. Attention should be placed on forestry carbon sequestration’s role while considering the distinctive endowments of each region and developing reasonable, differentiated, and collaborative forestry management strategies.

Impact of the Spanish smoke-free laws on cigarette sales by brands, 2000-2021: Evidence from a club convergence approach.

In January 2006, the Spanish government enacted a tobacco control law that banned the advertising, promotion and sponsorship of tobacco. In January 2011, further legislation on this matter was adopted to provide a more restrictive specification of the ban. In this study, we analyze the effect produced on cigarette sales by these two prohibitions. We address this problem using a cluster time-series analysis to test whether the sales of cigarettes by brands have been homogenized with the prohibition of advertising, promotion, and sponsorship. The data source used was the official data on legal sales of cigarettes by brands in Spain, from January 2005 to December 2021 (excluding the Canary Islands and the Autonomous Communities of the cities of Ceuta and Melilla). To achieve our objective, we used log(t) test statistics to check if there is global convergence in the three selected periods according to the regulatory changes that have occurred in Spain (2005-2021, 2005-2010 and 2011-2021). Second, once absolute convergence is rejected, we applied a clustering algorithm to test for the existence of subgroup convergence. The cigarette brands that have been marketed during the period 2005-2021 (n=40), can only be grouped into three groups according to the behavior of their sales. When we focus on the period 2005-2010 (n=74), cigarette brands are grouped into five groups according to their sales behavior. Finally, the cigarette brands marketed during the period 2011-2021 (n=67) are grouped into three groups according to the temporal evolution of their sales. These results suggest a greater homogenization of cigarette sales after the application of the law of January 2011. Act 42/2010 (total ban on tobacco advertising, promotion, and sponsorship actions) was associated with greater homogenization of cigarette sales than the application of Act 28/2005 (partial ban). This finding supports what is established in the previous literature that indicates that Act 42/2010 provided a more restrictive specification of the ban than Act 28/2005.

Regional Income, Household Expenditure, Poverty, and Education Convergence Clubs at the District Level in Indonesia

This article reinvestigates the regional convergence in GDP per capita, household expenditure per capita, poverty rate, and average years of schooling in Indonesia at the district level during 2000–2017 using the convergence club method. This article finds that regional inequality in Indonesia at the district level is characterized by two convergence clubs in GDP per capita, five convergence clubs in household expenditure per capita, six convergence clubs in poverty, and five convergence clubs in average years of schooling. This article also confirms the existence of spatial concentration among regions and a development gap between the west and east sides of Indonesia.

Spatial and temporal evolution of the eco-efficiency of cultivated land use in the region around Beijing–Tianjin based on the Super-EBM model

The eco-efficiency of cultivated land use (ECLU) is an important indicator for ecological civilization construction in China. Exploring the spatiotemporal dynamic evolution of the ECLU is helpful for the sustainable use of arable land, ensuring food security and ecological security. However, previous studies have mostly focused on the use of a slacks-based measure (SBM) model for ECLU measurement, ignoring the more accurate epsilon-based measure (EBM) model. Therefore, in this study, first, we explored the conceptual framework of the ECLU, and then, based on 2005–2020 panel data covering the counties in the region around Beijing and Tianjin, we investigated the spatial and temporal evolution of the ECLU by using the Super-EBM model, kernel density estimation method, and spatial Markov chain model. The results show the following: 1) From 2005 to 2020, the ECLU in the region around Beijing and Tianjin displayed an increasing state, but the average value was only 0.55. 2) The temporal evolution of the ECLU has gradually polarized, and the internal gap has widened, but it tends to stabilize. 3) The ECLU in the region around Beijing and Tianjin was more inclined to remain the same, and there was a “club convergence” phenomenon, which was meaningfully affected by the background of neighboring areas. In this article, we emphasize the significance of the super‐efficient EBM model in measuring the ecological efficiency of arable land use, and discuss the spatiotemporal evolution of the ecological efficiency of arable land use at a deeper level. In light of local conditions, the government should reasonably formulate a path to optimize the ECLU, strengthen the linkage with surrounding cities, and bring into play the positive spillover effect.

Efficiency of agricultural modernization in China: Systematic analysis in the new framework of multidimensional security

Agricultural modernization is the foundation and pillar of national modernization, and its security should not be ignored. However, the traditional efficiency assessment does not take security factors into account. To improve this work, we tried to embed multidimensional security issues into the assessment framework of agricultural modernization efficiency (AME) and analyzed its efficiency levels, regional differences, and dynamic evolution using the Super-EBM model, Dagum Gini coefficient, and spatial Markov chain model. We found that: (1) At the national level, the agricultural operation efficiency (AOE) and agricultural service efficiency (ASE) were generally lower than the agricultural production efficiency (APE), with significant potential for improvement. The spatial characteristics exhibited evident spatial clustering, and the spatial differences in AME, AOE, and ASE were similar. (2) The overall Gini coefficient of AME fluctuates in the range of 0.1168–0.1334 from 2006 to 2020, and the differences in AME were dominated by inter-area differences, with an average contribution rate of 68.72%. (3) The spatial pattern of AME was relatively stable, with prominent “club convergence” characteristics, and spatial factors had adverse spillover effects on the evolution toward convergence. Policymakers should strive to fill the shortcomings of agricultural operations and agricultural services, formulate differentiated agricultural strategies for development and promote knowledge exchange and technological diffusion. These are important for building a modern agricultural system and promoting the spatially balanced development of modernized agriculture.

Measurement and characteristics of the temporal-spatial evolution of China’s healthcare services efficiency

BackgroundHealthcare services efficiency (HSE) is directly related to the healthcare demands of the general public and also plays an essential role in the country’s coordinated economic and social development.MethodsIn this study, the stochastic frontier approach (SFA)-Malmquist model was applied to measure the HSE of 31 Chinese provinces based on panel data from 2010–2020. Then, kernel density estimation, Markov chain, and exploratory spatial data analysis were adopted to study the temporal-spatial dynamic evolution characteristics of the HSE.ResultsThe study found that China’s HSE showed an average value of approximately 0.841, indicating room for improvement. The HSE varied significantly across regions, presenting an “East > Central > West” distribution layout. The TFP of healthcare services in China grew by 1.6% per year, driven mainly by technological progress of 1.8% per year. The trend of the HSE shifting to a high level in China was significant, but its evolution exhibited stability of maintaining the original state, and it was harder to achieve leapfrog transfer. The temporal-spatial evolution of the HSE was also significantly affected by geospatial factors, with a clear spatial spillover effect and spatial agglomeration characteristics. Provinces with high-level HSE exhibited positive spatial spillover effects, while provinces with low-level HSE had negative spatial spillover effects. Thus, the “club convergence” phenomenon of “high efficiency concentration, low efficiency agglomeration, high levels of radiation, and low levels of suppression” was formed in the spatial distribution.ConclusionsThe results indicate that countermeasures should be taken to improve the HSE in China. Theoretical support for the improvement of HSE is provided in this paper.

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.

Economic Convergence Among Asia-Pacific Economic Cooperation Members. A Comparative Analysis, 1960–2020

The process of global economic integration is justified by the primary goal of inclusive and balanced growth for all economies, so it is relevant to identify the extent to which this goal has been achieved. This research evaluates whether the member economies of the Asia-Pacific Economic Cooperation (APEC) have experienced economic convergence during the 1960–1990 (pre-APEC) and 1990–2020 (post-APEC) periods. For this purpose, beta, sigma and gamma convergence are estimated, which are methodological approaches proposed by Barro and Sala-i-Martin (1991, Brookings Papers on Economic Activity, 1991(1), 170–182) and Marchante et al. (2006, Fundación de Estudios de Economía Aplicada Working Papers No. 2006-05), for APEC as a region and for the high- and middle-income economies that conform it. The results show that the process of economic convergence among APEC members intensified after its formation in 1989 and that the region can be categorized as an ‘economic convergence club’. As well as that, the high- and middle-income groups are converging towards their respective stationary state.

Does club convergence matter in health outcomes? Evidence from Indian states

BackgroundPopulation health is vital to a nation’s overall well-being and development. To achieve sustainable human development, a reduction in health inequalities and an increase in interstate convergence in health indicators is necessary. Evaluation of the convergence patterns can aid the government in monitoring the health progress across the Indian states. This study investigates the progressive changes in the convergence and divergence patterns in health status across major states of India from 1990 to 2018.MethodsSigma plots (σ), kernel density plots, and log t-test methods are used to test the convergence, divergence, and club convergence patterns in the health indicators at the state level.ResultsThe result of the sigma convergence suggests that life expectancy at birth has converged across all states. After 2006, however, the infant mortality rate, neonatal mortality rate, and total fertility rate experienced a divergence pattern. The study’s findings indicate that life expectancy at birth converges in the same direction across all states, falling into the same club (Club One). However, considerable cross-state variations and evidence of clubs’ convergence and divergence are observed in the domains of infant mortality rate, neonatal death rate, and total fertility rate. As suggested by the kernel density estimates, life expectancy at birth stratifies, polarizes, and becomes unimodal over time, although with a single stable state. A bimodal distribution was found for infant, neonatal, and total fertility rates.ConclusionsTherefore, healthcare strategies must consider each club’s transition path while focusing on divergence states to reduce health variations and improve health outcomes for each group of individuals.

Assessing regional convergence of greenhouse gas emissions in Spain: insights from economic activities

ABSTRACT In recent decades, Spain has undergone a strong economic expansion; however, it has not made a robust response to fulfil the international greenhouse gas Paris Agreement targets. Thus, understanding the dynamics of the environmental performance of the Spanish regions is essential for policymakers. We explore the convergence process of emissions intensity at the regional level during 1990–2018, differentiating between direct and diffuse emission sector, based on the degree of energy intensity of economic activities, which is the most novel aspect of our analysis. Our results recognise several convergence clubs; predominantly, the determining factors are income level and added value breakdown, the energy mix of renewable power, as well as the temperature of the climate. In any event, the dispersion of behaviours and the existence of different factors driving the convergence process highlight the need for customised policies at the regional scale.