Absolute Β-convergence Research Articles

Evaluation and convergence analysis of science and technology innovation efficiency in China’s national central cities based on the super-efficiency SBM-ML model

ABSTRACT Scientific and Technological Innovation (STI) is an important driving force for economic development and social progress. National central cities are the main connection points of China’s economic activity network and play a leading role in the national economic development of the country. In order to explore the efficiency of STI and the convergence characteristics of STI in China’s national central cities, this paper selects S&T innovation input-output indicators and constructs a system of indicators for high-quality economic development. It measures the STI innovation efficiency of China’s national central cities by combining with the super-efficiency SBM-ML model and then constructs a model to analyze its convergence situation. The results of the study show that: from 2011 to 2021, the STI efficiency of China’s national central cities has reached an effective level, and the overall trend has increased; the total factor productivity of STI in China’s national central cities has obvious differences, with Beijing having the highest total factor productivity, while Shanghai has the lowest; the STI innovation efficiency of China’s national central cities exhibits both absolute β-convergence and conditional β-convergence, but there is no significant α convergence, and regional differences are obvious.

Impact of Covid-19 on the Economic Growth of ASEAN Countries: Convergence or Divergence?

This contribution addresses the question of whether economic growth among ASEAN member countries is converging or diverging within the context of the COVID-19 pandemic. ASEAN has significantly developed economic and social mechanisms aimed at achieving greater integration among member countries, with the goal of enhancing economic growth and especially accelerating the catch-up of the poorer member countries. How resilient have the member countries been? Has the COVID-19 pandemic more severely affected the poorer member countries? To answer these questions, our contribution addresses this issue based on economic growth theories, particularly drawing on Solow’s theory regarding beta and gamma convergence. The study covers the period from 2000 to 2022. In the pre-pandemic period from 2000 to 2019, there is a general phenomenon of absolute convergence, demonstrating a reduction in the disparity in absolute values between less advanced and more modern countries, which also leads to a reduction in inequality as shown by the confirmation of the σ-convergence hypothesis. This is true for both GDPC and GDPW variables. The catch-up effect of absolute β-convergence is not evident when looking at the period from 2020 to 2022. During this timeframe, both the absolute β-convergence and σ-convergence hypotheses are rejected, which slows down the economic growth of poorer economies relative to the more advanced ASEAN countries. Overall, the entire 2000–2022 period confirms the unconditional β-convergence and σ-convergence assumptions of the pre-pandemic period.

Are crimes against women in India converging? Some empirical observations

ABSTRACT Using the Indian state-level panel data on crimes against women for the period 2000–2019, we examined whether various rates of crime against women were converging. The second-generation unit-root test proposed by Pesaran (2007) was employed to check for absolute β-convergence after conforming to cross-sectional dependence in our panel analysis. The results showed no convergence for various rates of crime against women at the aggregate level, barring dowry deaths. The disaggregated zone-wise results revealed convergence in Eastern and North Eastern states for the Composite Crime Index (CI). The rate of rape was convergent in the west zone, while dowry deaths and cruelty by husbands were convergent only in the Eastern zone. Note that there was a weak convergence in dowry deaths in the North zone. In short, our study fails to find robust evidence of strong convergence in various categories of crime against women in India. The system-GMM results of conditional β-convergence broadly supported the no-convergence results of Pesaran’s unit-root test, as divergence was found in most crime categories. The prominent sources of divergence are women’s employment, female foeticide rate, number of pending cases, rate of arrest, and the proportion of Schedule Castes (SCs) people in the total population.

The impact of human capital misallocation on green economy efficiency: Empirical analysis of Chinese urban agglomerations

This paper uses panel data of 260 prefecture-level cities from 2000 to 2019 to explore spatial characteristics such as spatiotemporal divergence and dynamic convergence based on measuring the level of human capital misallocation in Chinese cities and empirically tests the green development effect of human capital misallocation. The study finds that: ① the human capital misallocation levels of the country and the eight major urban agglomerations show a fluctuating downward trend. ② Divergences in human capital misallocation continue to narrow across the country and urban agglomerations, and the difference between inter-urban agglomerations is the primary source of regional difference. ③ The YRD, PRD, MYR, HC, and CP have significant σ-convergence characteristics of human capital misallocation. Meanwhile, the country and each urban agglomeration show significant spatial absolute β-convergence and conditional β-convergence trends. ④ Human capital misallocation significantly negatively affects green economic efficiency, inhibiting green economy efficiency. Therefore, in the future, it is necessary to improve the match between regional industrial structure and human capital allocation through a combination of targeted policy guidance and market mechanisms tailored to local conditions to enhance the efficiency of the green economy. The significance of the study lies in accelerating the accumulation of human capital while realizing the appropriate matching of human capital, releasing the human capital dividend to the maximum extent, and boosting the structural reform of the labor market to realize the transformation of the green economy.

The coupling coordination between health service supply and regional economy in China: spatio-temporal evolution and convergence.

The coordination of health service supply and regional economy is an integral path to promote China's prosperity. Based on the coupling mechanism of health service supply and regional economy, we sampled the data from 30 provinces in China from 2009 to 2021 in this study and constructed the evaluation index system. Additionally, we calculated the coupling coordination degree (HED) of the two through the coupling coordination degree model. We further used the kernel density estimation, Moran's I index, and spatial β convergence model to assess the dynamic evolution trends, spatial aggregation effect, and spatial convergence characteristics of coupling coordination. (1) HED in China showed a rising trend during the study period but with large regional differences, forming a gradient distribution pattern of "high in the east and low in the west." (2) The results of Kernel density estimation show that HED has formed a gradient differentiation phenomenon within each region in China. (3) HED has modeled spatial clustering characteristics during the study period, with high-value clusters mainly appearing in the eastern region and low-value clusters appearing in the northwestern region. (4) There are absolute β-convergence and conditional β-convergence trends in HED in China and the three major regions during the study period, but there is an obvious regional heterogeneity in the control factors. The research provides a reference for accurately implementing policies according to different levels of health service supply and economic development, in addition to narrowing the regional differences of the coupling coordination between the regional economy and health service supply.

Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas.

Reducing multidimensional relative poverty is one of the important issues in the current global poverty governance field. This article takes 12 ethnic regions in China as the research object and constructs a multidimensional relative poverty measurement system. The calculated multidimensional relative poverty index is decomposed according to provinces, cities, dimensions, and indicators. Then, the Dagum Gini coefficient and convergence analysis are used to analyze spatiotemporal heterogeneity and convergence characteristics. The results show that the multi-dimensional relative poverty situation of various provinces in ethnic minority areas has improved from 2012 to 2021, among which Tibet province is the most serious and Shaanxi is the best. According to the analysis of convergence, it was observed that there is no σ-convergence of multidimensional relative poverty in ethnic areas in general, and there is absolute β-convergence in general and in the southwest and northwest regions, and there is no absolute β-convergence in the northeast region. Based on this, policy recommendations for reducing multidimensional relative poverty are proposed at the end of the article. Compared with previous studies, this article focuses on ethnic regions that are easily overlooked. Starting from the dimensions of economy, social development, and ecological environment, the poverty measurement system has been enriched.

Analyzing regional disparities and spatial distribution dynamics of energy consumption levels in China

This article uses the Dagum Gini coefficient and kernel density estimation to analyze the regional differences and distribution dynamics of energy consumption and applies the coefficient of variation with a static panel model to test its σ-convergence and β-convergence characteristics. The study finds noticeable differences in energy consumption intensity among provinces and regions, and the main source of regional differences is inter-regional differences. In contrast, the contribution of intra-regional differences and hypervariable intensity is smaller and more similar. Specifically, the absolute difference in the eastern region experienced a first decline, then a rise, and finally a slight decline; the absolute difference in the central region had a more significant overall fluctuation and a declining trend in the later period, and the absolute difference in the western region tended to narrow. No polarization trend was observed during the sample period in the eastern, central, and western regions. Not only σ-convergence but also absolute β-convergence and conditional β-convergence exist in the whole country and the eastern, central, and western regions. Therefore, it provides a factual basis for deepening the perception of the spatial pattern and regional disparity of energy utilization levels in China and has policy implications for promoting inter-regional and intra-regional coordinated development.

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.

Spatial-temporal differences and convergence analysis of residential building carbon emission efficiency in China.

Data indicate that carbon dioxide emissions from residential buildings in China constitute 60% of the country's total, making carbon reduction efforts in residential construction crucial for achieving dual carbon goals. From the perspective of eight major economic regions, this paper selects energy consumption, per capita residential area, and residential population as input indicators, per capita disposable income as the output indicator, and carbon dioxide emissions as the undesired output indicator. It employs the super-efficiency model based on the directional distance (super-DDF) function and the Malmquist-Luenberger (ML) index to measure the static and dynamic carbon emission efficiencies of residential buildings (RBCEE) during their operational phase from 2010 to 2020. After analyzing the differences and equity in RBCEE among regions using the Theil index and Gini coefficient, the σ-convergence, absolute β-convergence, and conditional β-convergence methods are utilized to explore the changing trends of RBCEE across the eight major economic regions. Results show that the static RBCEE in China is at a medium level; dynamic efficiency has improved across all eight regions, though at varying rates; overall, RBCEE exhibits poor equity and significant differences, with intra-group differences being a major cause. In terms of convergence, all eight economic regions display significant absolute β-convergence and conditional β-convergence. Finally, based on the research findings, this paper proposes corresponding emission reduction recommendations for the eight major economic regions.

Regional differences, distributional dynamics and convergence of multidimensional food security levels in China.

Food security is one of the important issues in the current world development process. The article takes 31 provinces (districts and cities) in China as the research object and constructs a multidimensional food security level evaluation index system from four dimensions: quantitative security, nutritional security, ecological security, and capacity security. Using the entropy method, China's food security index was calculated for the ten-year period from 2013 to 2022. Overall, China's food security level showed an upward trend during the decade, with the provinces of Shandong, Heilongjiang, and Henan having the highest level of security. The distribution dynamics of food security and its spatiotemporal evolution in the seven regions were examined using the Dagum Gini coefficient and its decomposition, and the absolute and conditional convergence of food security in the different areas was verified. The results of the study show that the provinces within East China have the largest gap in food security levels between them, and there is absolute β-convergence. Looking at China as a whole, the development of its food security level is characterized by significant convergence, which means that provinces with a low level of food security will have a faster rate of growth than those with a high level of food security, resulting in a gradual narrowing of the gap in food security levels between provinces.

Convergence in transport and ICT infrastructure: Evidence of EU member states

While countries' social and economic well-being depends on various factors, recent research emphasises the importance of transport and ICT infrastructure. To reduce the welfare differences among EU countries, the European Commission and governments have to ensure the convergence of this infrastructure as well. Previous studies have shown that convergence is taking place at the national level, however the situation at the regional level still needs to be determined. In light of this, the study examines transport and ICT infrastructure convergence in EU member states and NUTS 2 regions at different periods. The research methodology is based on the neoclassical approach of convergence, i.e., β-convergence model presented by Barro and Sala-i-Martin (1992). This approach is deemed most appropriate for determining whether the disparities in terms of infrastructure among EU members and regions are diminishing. Research findings present clear evidence of absolute β-convergence in infrastructure development across EU member states and NUTS 2 regions. Strong evidence of transport convergence is identified among EU member states and among NUTS 2 regions, however, it is observed only in one out of the three types of infrastructure. In contrast, the robust evidence of ICT infrastructure convergence is prominent across EU countries and NUTS 2 regions, showcasing substantial reductions in disparities.

Does Industrial Agglomeration Promote Regional Innovation Convergence in China? Evidence From High-Tech Industries

The literature examining the importance of industrial agglomeration in innovation performance has expanded greatly in recent years, but the impact of industrial agglomeration, especially high-tech industrial agglomeration on regional innovation convergence, has been neglected. Using quantitative data from 30 provinces in China pertaining to the period 2005–2016, in this article, we analyze regional innovation convergence by focusing on three different types of convergence: σ-convergence, absolute σ-convergence, and conditional β-convergence. On the basis of the spatial effects, this article empirically investigates the impact of high-tech industrial agglomeration on regional innovation convergence in China by using spatial econometric models. The empirical results show that there is significant spatial autocorrelation in regional innovation. Thus, in the assessment of regional innovation convergence, the spatial effects should not be neglected. Moreover, our results demonstrate that regional innovation exists three different types of convergence (i.e., σ-convergence, absolute β-convergence, and conditional β-convergence). In addition, high-tech industrial agglomeration can promote regional innovation convergence. Finally, the grouping of high-tech industries into five subindustries shows that industrial agglomeration has different effects on regional innovation convergence. Overall, our findings provide convincing empirical evidence of the relationship between the high-tech industrial agglomeration and regional innovation convergence and valuable insights into how to realize regional innovation convergence.

Multiscale disparity and spatial pattern of comprehensive carrying capacity in the Yangtze River Economic Belt, China

Exploring and revealing the comprehensive carrying capacity is a critical barometer and benchmark for multiregional sustainable development. Using a typical multiscale region moving forward on a green development demonstration belt (China’ s Yangtze River Economic Belt) as a case study, the multiscale disparity of comprehensive carrying capacity during the period 2005–2019 is presented after a comprehensive assessment of multiscale carrying capacity level. Some convergence models, covering δ-convergence, absolute β-convergence, and conditional β-convergence, are constructed to test the disparity of urban comprehensive carrying capacity. Furthermore, the multiscale disparity of comprehensive carrying capacity is quantified when the decomposition model is used to determine the specific contributions to total disparity (from inter-urban agglomerations or intra-urban agglomeration), and then the spatial aggregation effect of urban comprehensive carrying capacity is analyzed. The results highlight that: YREB’s comprehensive carrying capacity is gradually improving whether at the scale of upper, middle, lower reaches, or the whole; there is an obvious inter-city disparity of comprehensive carrying capacity from the results of conditional β-convergence; the further conditional β-convergence tells that urban ecological and sustainable management and its stakeholder engagements should begin with the sufficient eco-environment endowment, good transportation system, well-reconstructed market environment, and the healthy economic structure or benefit; the disparity from the lower reaches is greater than that from the middle and upper reaches when the specific disparity from intra-low reaches plays a significant role, and there is a spatial aggregation effect of urban carrying capacity in the study area. Future policies and regulatory decisions must address such multiregional disparities to foster sustainable development based on the “equity and efficiency” philosophy.

Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA-Malmquist model.

This study investigates the present situation of and changing trend in the innovation efficiency of health industry enterprises in China. Based on panel data for 192 listed health companies in China from 2015 to 2020, we analyse innovation efficiency using the DEA-Malmquist index and test convergence using σ-convergence and β-convergence models. From 2016 to 2019, comprehensive average innovation efficiency increased from 0.6207 to 0.7220 and average innovation efficiency decreased significantly in 2020. The average Malmquist index was 1.072. Innovation efficiency in China as a whole, North China, South China, and Northwest China showed σ-convergence. Except for the Northwest region, absolute β-convergence was evident, and in China as a whole, North China, Northeast China, East China, and South China, conditional β-convergence was evident. Overall innovation efficiency of these companies has increased annually but needs further improvement, and the COVID-19 pandemic has had a great negative impact on it. Innovation efficiency and trends in it vary across regions. Furthermore, we should pay attention to the impacts of innovation infrastructure and government scientific and technological support on innovation efficiency.

Is there regional convergence between Morocco and its OECD partner countries in terms of well-being?

Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco's openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries (Morocco and 35 of its partner member countries of the Organization for Economic Co-operation and Development (OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains (economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we showed that β-convergence of regions is significant for well-being and three of its domains (economic, social, and governance). These convergences are made by a spatially autocorrelated error model (SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.

The changing health convergence for life expectancy and spatial interactions

ABSTRACT Spatial interactions are important to consider issues like health convergence between the European Union countries and Spanish provinces. Health status is measured by a combination of objective health outcome indicators, such as life expectancy: at birth, at age 65, disability-adjusted life expectancy and healthy life expectancy based on self-perceived health. The period analysed differs from one indicator to another considering 1998–2018. There are two forms of convergence: σ-convergence and absolute β-convergence. Furthermore, the Moran Test is performed to disentangle the degree of spatial dependencies and two models of spatial regression are used to include these dependencies in the absolute β-convergence estimation. Our findings suggest that there is a convergence process among European Union countries and the Spanish provinces. On the other hand, β-convergence is higher in women among European countries and in men for Spanish provinces. Nevertheless, the rise of the dispersion means that there is not clear evidence about trends in the period considered. There are two contributions in our research: to achieve an updated vision of health convergence and to incorporate spatial econometrics in Health Economics research. These insights can help to reduce health inequalities.

Human Capital, Trade Competitiveness and Environmental Efficiency Convergence Across Asia Pacific Countries.

This study mainly investigates 14 Asia Pacific economies' environmental efficiency. Departing from previous studies ignoring environmental technology heterogeneity, we evaluate environmental efficiency through metafrontier super epsilon based model (EBM). We compare environmental efficiency convergence across different regions via unit root test and truncated regressions. We analyze how trade competitiveness impact environmental efficiency. We also explore effect of green technology and human capital on environmental efficiency from the perspective of endogenous growth. Our findings indicate that stochastic and absolute β-convergence tendencies were confirmed. Human capital can enhance environmental efficiency convergence. Trade competitiveness showed a mixed impact on environmental efficiency convergence, confirming scale, composition and technical effects. It is better to enhance human capital, strengthening environmental regulations under international competition as well as relentlessly pursuing green industrialization across Asia Pacific countries.

Regional disparities and dynamic evolution of competitiveness of marine fish aquaculture industry − A study of China

China has emerged as a major player in marine fish aquaculture, contributing significantly to economic, social, and environmental development. Analyzing the competitive evolution pattern of regional marine aquaculture is critical to promote the synergistic development of this industry. The “vertical and horizontal” scatter degree method was employed to examine the dynamic evolution trend and spatial non-equilibrium of the competitiveness level of marine fish aquaculture in nine Chinese provinces and cities. Using the σ-convergence model and absolute β-convergence model, the evolution of absolute differences was characterized. The study reveals the existence of stage and regional characteristics of marine fish aquaculture in the nine provinces and cities, with an observable gradient effect. The overall difference is observed to decrease, indicating a trend towards regional synergistic development in the marine fish aquaculture industry. This finding holds practical significance and theoretical value in promoting the growth of the industry.

Measuring the Cultivated Land Use Efficiency in China: A Super Efficiency MinDS Model Approach

Cultivated land is a vital strategic resource to ensure human survival and development. It is pertinent to introduce the environmental constraint index into the study of cultivated land use efficiency and promote the coordinated development of environmental and economic benefits. Based on the construction of the evaluation index system of cultivated land use efficiency, including carbon emission as the undesired output, this paper used the super efficiency MinDS model to measure the cultivated land use efficiency of China by using the data from 2009 to 2019. The results show the following. (1) During 2009-2019, the overall use efficiency of cultivated land in China showed a tendency to fluctuate and increase, ranging from 0.871 to 0.948, indicating high use efficiency. Eleven provinces had an average land use efficiency of more than 1. (2) Among the input-output indicators, the carbon emission indicator showed the largest average percentage of improvement at 15.21%, followed by the pesticide index and agricultural machinery index, and the smallest average improvement was the irrigation indicator at 3.55%. (3) There were apparent differences in the average relaxation and improvement proportion of input-output indicators of cultivated land use in the provinces. (4) China's cultivated land use efficiency has absolute σ-convergence, absolute β-convergence and conditional β-convergence, which means that the difference in cultivated land use efficiency between provinces has a tendency to decrease, and that China's cultivated land use efficiency will stabilize. This paper provides a clear direction for the promotion and improvement of cultivated land use efficiency in China.

Dynamic Evolution, Regional Differences, and Spatial Spillover Effects of Urban Ecological Welfare Performance in China from the Perspective of Ecological Value

Ecological welfare performance (EWP) is a necessary condition for achieving sustainable economic development and is a crucial initiative for resolving the dilemma of balancing economic development, social welfare, ecology, and the environment. This paper constructs and enhances a comprehensive evaluation system of ecological welfare performance (EWP) from an ecological value viewpoint for the purpose of making the results of the evaluation both comprehensive and objective. In the meantime, the Dagum Gini decomposition, kernel density, and the spatial Durbin model were initiated to measure and analyze urban EWP, which supplies new empirical results for studies on the dynamic evolution, regional differences and driving factors of urban EWP. The findings indicate the following: (1) In each spatial dimension, the urban EWP roughly demonstrates first a decreased and then an increased trend. There is a discrepancy in the east-central-west distribution of urban EWP in space, in which urban EWP in the east and west is larger than that in the central area. (2) For relative differences, intra-regional and inter-regional differences in urban EWP are significantly spatially uneven. Supervariable density is the main source of regional differences. For absolute differences, the EWP demonstrates a significant polarization effect. (3) The urban EWP does not have σ-convergence; nonetheless, it has spatial absolute β-convergence and spatial conditional β-convergence. (4) The urban EWP has a significant spatial correlation. Industrial structure, science and technology innovation, foreign investment, urbanization, government intervention, finance development, and environmental regulations all have influence effects and spatial effects on urban EWP; notwithstanding, the direction and magnitude of the effects vary across the different spatial dimensions.