Empirical Study of Regional Innovation Capability and Economic Convergence in China

Yang, Chunxi; Zhao, Zhicong; Zhang, Zhijuan

doi:10.22459/cnseg.07.2017.10

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…Based on the extensive EKC literature, which has estimated CO 2 , SO 2 , and other industrial hazards discharge per unit output at the national level, 5 , 31 , 52 , 53 this study has focused on finding additional driving forces of the EKC, such as administrative ranking, and certifying whether the income level alters the relationship between hazardous discharge and economic growth. Although environmental disadvantages were found in developing countries, most studies omitted regional differences in identifying the sources of industrial pollution.…”

Section: Discussionmentioning

confidence: 99%

Green-production transitions and hazardous industrial discharge: A regional case study from China

Hou

2023

Science Progress

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Green production, which reduces hazardous industrial discharges per unit output, is promoted throughout China. The Environmental Kuznets Curve suggests a negative correlation between hazardous industrial discharge and economic growth due to green innovation. This study expanded the EKC framework by including heterogeneity in evaluating the relationship between hazardous industrial discharges and economic growth to reflect green transformation. Administrative ranking disparity is identified as one of the fundamental driving forces of green production transition in a developing country. Building on an enriched EKC framework, we used a spatial estimation model to exclude spatial effects and obtained accurate estimates of the classified regions. The modified research method was used to examine whether industrial pollution has been reduced in 267 cities and towns in China from 2007 to 2021. Environmental protection performance was examined to estimate whether there is a switch to green manufacturing. As industrial hazards are of different types, the author sought to determine whether there was a decrease in industrial sulphur dioxide emissions, wastewater, solid waste, or dust, even though more industrial hazards were recycled than before. The spatial estimates indicated that (a) the national level of pollution remains positively linked with the total output, and every percentage of output growth increases sulphur dioxide emissions by 444.573 tons; (b) a positive relationship between economic growth and wastewater is altered by environmental protection in cities, while the general decoupling between economic growth and other types of industrial pollution, such as solid waste and industrial dust, was not observed; (c) growth in the southeast was decoupled from sulphur emissions, and its sulphur dioxide production per unit of output increased to 0.021 tons. Sulphur dioxide emissions per unit of economic growth along the southeast coast were 379. 048 tons, which was well below the overall average of 444.573 tons. High-income towns along the southeast coast have achieved clean production breakthroughs, realising a 15% reduction in industrial sulphur dioxide emissions by 2021. Although there were signs of a shift toward clean manufacturing in high administrative ranking cities, most regions of China are transitioning to environmentally friendly manufacturing and suffer from the hardships of green production transformation.

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Section: Discussionmentioning

confidence: 99%

Green-production transitions and hazardous industrial discharge: A regional case study from China

Hou

2023

Science Progress

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“…Regional Innovation Systems can be evaluated through such nonparametric methods as Data Envelopment Analysis-DEA [77][78][79][80][81][82] and Free Disposal Hull-FDH [83] (they also used DEA in their studies) and through parametric methods such as Stochastic Frontier Analysis (SFA) [84], [85] (also they used DEA in their studies) and Thick Frontier Analysis-TFA. In addition, some other statistical methods, mainly factor [86,87], discriminant [88], cluster [89] and regression [78,90], and also normalization methods [66][67][68][69]72,73] and Markov Chains [91][92][93] are used to evaluate regional innovation performances and to classify regions with similar characteristics.…”

Section: Methodsmentioning

confidence: 99%

Regional Innovation Performances in Turkey

Özen

Baycan

2022

Sustainability

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The purpose of this study is to provide a temporal dynamic analysis of transitions of the regions in Turkey from one state of innovative performance to another by using successive Markov Chains. Regarding the intellectual assets, consisting of the patent, utility model, trademark and design applications, Markov Chains have revealed that there are regional disparities (between i. regions located in the east and west of the country, ii. metropolitan and non-metropolitan regions, iii. high-developed and relatively less-developed regions). Results show that metropolitan regions have higher performances. Innovation leaders which take place in all indicators and time periods in terms of applications are Adana, Ankara, Bursa, Eskişehir, İstanbul, İzmir, Kayseri, Kocaeli, Konya and Manisa regions. It is explicitly distinct that İstanbul leads in the innovation performances for each variable in all time periods. In contrast, regions with the lowest innovation performances are Ağrı, Artvin, Bingöl, Bitlis, Erzincan, Hakkari, Kars, Muş, Siirt, Tunceli, Bayburt, Bartın, Ardahan, Iğdır and Kilis. In addition to having the lowest innovation performances, these regions are identified by state policies as ‘priority regions in development’ or ‘state of emergency regions’.

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“…However, compared to the research on HDI itself or its application dimensions, the research on the factors influencing human development in China is deficient in terms of research perspectives, empirical methods, and research data. In terms of research perspective, most existing studies have been conducted on economic growth and public finance, as discussed by (Yang et al, 2017), the impact of regional innovation capability in China on economic convergence, and less attention has been paid to the crucial role of science and technology in human development. At the same time, science and technology play a fundamental role in promoting social progress in the historical context and realistic environment of human development and have always promoted the improvement of living standards and had a profound impact on human development.…”

Section: Introductionmentioning

confidence: 99%

Impact of R&D Investment and Network Penetration on Human Development: Evidence from China

Qin

Zhao

2023

Soc Indic Res

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This paper measures the human development indices of 31 inland provinces (municipalities) in China in a continuous time series during 2000-2017 according to the 2010 HDI compilation method. It uses a geographically and temporally weighted regression model for conducting an empirical study on the effects of R&D investment and network penetration on human development in each province (municipality) of China. There is significant spatial and temporal heterogeneity in the impact of R&D investment and network penetration on human development across provinces (municipalities) in China due to differences in resource endowments and economic and social development. For R&D investment, eastern provinces (municipalities) have mostly positive effects on human development, and central regions have mostly weak positive or negative effects. In contrast, western provinces (municipalities) show different development paths, with weak positive effects in the early stage and significant positive effects after 2010. Most provinces (municipalities) show a continuous and increasing positive effect for network penetration. The marginal contributions of this paper are mainly in improving the shortcomings in research perspectives, empirical methods, and research data in the study of human development influencing factors in China relative to the study of HDI itself in terms of measurement or application dimensions. This paper constructs a human development index for China, analyzes its spatial and temporal distribution, and explores the impact of R&D investment and network penetration on human development in China, with the hope of providing lessons for China and developing countries to promote the level of human development and cope with the pandemic. KeywordsR&D investment • Network penetration • Human development level • Geographically and temporally weighted regression model * Hongli Zhang

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Empirical Study of Regional Innovation Capability and Economic Convergence in China

Cited by 4 publications

References 11 publications

Green-production transitions and hazardous industrial discharge: A regional case study from China

Green-production transitions and hazardous industrial discharge: A regional case study from China

Regional Innovation Performances in Turkey

Impact of R&D Investment and Network Penetration on Human Development: Evidence from China

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