Spatial Club Convergence of Regional Economic Growth in Inland China

Cheng-lin, Qin; Ye, Xinyue; Liu, Yingxia

doi:10.3390/su9071189

Cited by 13 publications

(9 citation statements)

References 30 publications

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“…Xiao et al analyzed the convergence of innovation capabilities on different space-scales by applying the spatial panel of the β-convergence model [45]. In addition, studies of convergence in this context have also included economic growth [46] and per capita energy consumption [47], among other factors. These studies of convergence provide a methodology reference for considering the convergence of spatial effects.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Transport Efficiency and Its Spatial Convergence in China’s Provinces: A Super-SBM DEA Model Considering Undesirable Outputs

Ma¹,

Wang²,

Sun³

et al. 2018

Applied Sciences

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Undesirable outputs, such as carbon emissions and loss of property due to traffic accidents, hold great significance for the sustainable development of the transport industry. In this study, we applied a super-efficiency data envelopment analysis model with a slack-based measure (Super-SBM DEA) considering undesirable outputs to measure the integrated transport efficiency (ITE) of 31 provinces in China during the period of 2009–2016. Following this, we used a spatial autocorrelation model to test and verify the spatial autocorrelation of the ITEs at the level of the 31 provinces, and further to explore the aggregating features. Finally, considering the spatial effects that emerged, we constructed a β-convergence model to analyze the convergence characteristics of China’s ITEs and investigate its conditional factors. The research results show that the average ITE demonstrated a linear growth trend; the effective decision-making units (the ITE value was greater than 1) are only 11 provinces, accounting for about 35% by 2016. The mean of ITEs was also found to present a law of decreasing order of Eastern, Central and Western Zones. However, the Central Zone and Western Zone have a better efficiency improvement trend compared to the Eastern Zone. The Moran’s I index was bigger than zero, indicating that the ITEs formed a spatial autocorrelation phenomenon. The Moran scatter plots further showed that the provincial ITEs mainly followed the patterns of high–high, high–low and low–low aggregation. The ITE of the 31 provinces was found to have a clear absolute β-convergence and conditional β-convergence characteristics. Moreover, the level of economic development, household per capita traffic consumption, transport industry scale, technology advancement and transport intensity were all seen to have an important impact on the convergence of integrated transport efficiency. It is hoped that the findings of this study may contribute further insights and practical knowledge to effectively measuring the development level of China’s integrated transport efficiency, and to understanding future changes in the ITE gap among Chinese provinces.

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Section: Literature Reviewmentioning

confidence: 99%

Integrated Transport Efficiency and Its Spatial Convergence in China’s Provinces: A Super-SBM DEA Model Considering Undesirable Outputs

Ma¹,

Wang²,

Sun³

et al. 2018

Applied Sciences

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“…Ramajo et al (2008) applied spatial econometric methods to estimate the convergence rate of 163 EU regions in the period 1981 -1996 based on multiple spatial clubs. Qin et al (2017) tested and verified the hypothesis of the spatial convergence of the Chinese urban agglomeration over the period 1993 -2009. The empirical analysis presented in this paper will focus on testing the spatial income convergence hypothesis of the EU 245 NUTS 2 (Nomenclature of Units for Territorial Statistics) regions during the period 2003 -2014. The main motivation for this analysis is the fact that the classical concept of income convergence neglects spatial effects between regions what caused misleading results and conclusions.…”

Section: Introductionmentioning

confidence: 84%

Does Spatial Heterogeneity Matter in the EU Regions’ Convergence Income Process?

Furková¹

2020

ekoncas

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This paper explores the role spatial heterogeneity in the EU regions' convergence income process. For this purpose we tested income convergence hypothesis of the 245 NUTS 2 European Union regions during the period 2003-2014. We used spatial econometric approach which allowed an explicit modelling of both spatial effects: spatial heterogeneity and spatial autocorrelation. Our results showed an appropriate consideration of the role of spatial effects. First, we found that the rate of economic growth in the region is not only affected by the exogenous characteristics of the region, but also potentially by the rate of economic growth in neighbouring regions. Secondly, estimated spatial regime model identified two spatial regimes-convergence clubs. The regions under the first spatial convergence regime included economically "weaker" regions (mainly regions of post-socialist countries, regions of Portugal, Spain, Greece and southern regions of Italy) and these regions are converging separately from the rest of regions of the EU.

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“…Though the sample is relatively small the results are obtained with caution, therefore, may be treated as robust. 8 These variables were chosen following the standard practice in growth empirics and are in concurrence with the factors affecting the club convergence (Li, Li, Qin, Qin, & Ma, 2018;Qin et al, 2017;Sala-i-Martin, Doppelhofer, & Miller, 2004). Table A2 present the summary statistics of the variables used.…”

Section: Ethics Statementmentioning

confidence: 99%

“…Consequently, the assumption of non‐interaction becomes invalid which necessitates the need to account for spatial interaction (Lee & Yu, 2016). These interactions may be directly or indirectly affecting the convergence pattern and may contribute to more concentrated club formation (Ertur & Koch, 2007; Qin, Ye, & Liu, 2017). 2 Yet, studies examining the spatial dependence and club convergence are still thin.…”

Section: Introductionmentioning

confidence: 99%

Economic growth and club convergence: Is there a neighbour's effect?

2021

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The study investigates economic growth and club convergence in a crosscountry framework from 1970-1971 to 2014-2015. In particular, we test the club convergence hypothesis through a non-parametric and spatial interaction setting. The kernel density estimate shows a cyclical behaviour of per capita incomes, albeit following a common steady state. The conditional distribution is concentrated around the mean indicating a similar relative position across the heterogeneous countries. The transitional probabilities are strong enough to demonstrate a significant sign of clubbing. On testing the convergence hypothesis, we perceive strong evidence of club convergence across the countries. A persistent spatial dependence is unveiled across the proximities, therefore confirming the neighbour's effects in club formation. The study realizes a need to harmonize the interaction between the countries to improve the conditions for achieving long-run sustained economic growth.

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Spatial Club Convergence of Regional Economic Growth in Inland China

Cited by 13 publications

References 30 publications

Integrated Transport Efficiency and Its Spatial Convergence in China’s Provinces: A Super-SBM DEA Model Considering Undesirable Outputs

Integrated Transport Efficiency and Its Spatial Convergence in China’s Provinces: A Super-SBM DEA Model Considering Undesirable Outputs

Does Spatial Heterogeneity Matter in the EU Regions’ Convergence Income Process?

Economic growth and club convergence: Is there a neighbour's effect?

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