Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis

Based on data of 31 provinces in China for the period 2007–2017, this paper establishes spatial models by means of a transcendental logarithmic production function and analyzes the impact of regional credit and technological innovation on regional economic growth. The Jenks natural breaks method, ke...

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Main Authors: Huan Zhou, Shaojian Qu, Xiaoguang Yang, Qinglu Yuan
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2020/1738279
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spelling doaj-fc0fed7b5921412e983cbbb794d2155a2020-11-25T04:06:42ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/17382791738279Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel AnalysisHuan Zhou0Shaojian Qu1Xiaoguang Yang2Qinglu Yuan3Business School, University of Shanghai for Science and Technology, Shanghai 200093, ChinaBusiness School, University of Shanghai for Science and Technology, Shanghai 200093, ChinaAcademy of Mathematics and Systems Science, CAS, Beijing 100190, ChinaInstitute of Disaster Prevention, Beijing 101601, ChinaBased on data of 31 provinces in China for the period 2007–2017, this paper establishes spatial models by means of a transcendental logarithmic production function and analyzes the impact of regional credit and technological innovation on regional economic growth. The Jenks natural breaks method, kernel density function, and Moran index are introduced for spatial statistical analysis. Spatial weight matrices are constructed from two aspects of geographical characteristics and innovative input characteristics. The empirical results show significant spatial heterogeneity and spatial autocorrelation in economic growth, regional credit, and technological innovation. Both regional credit and technological innovation are important impacts to economic growth, whereas the interaction of regional credit and technological innovation has a negative effect on provincial economic growth. Therefore, we argue that China should rationally allocate regional credit resources, strengthen technological innovation capabilities, and boost the integrated development of regional credit and technological innovation. It is a particularly important way to facilitate regional economic integration and sustainable development.http://dx.doi.org/10.1155/2020/1738279
collection DOAJ
language English
format Article
sources DOAJ
author Huan Zhou
Shaojian Qu
Xiaoguang Yang
Qinglu Yuan
spellingShingle Huan Zhou
Shaojian Qu
Xiaoguang Yang
Qinglu Yuan
Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis
Discrete Dynamics in Nature and Society
author_facet Huan Zhou
Shaojian Qu
Xiaoguang Yang
Qinglu Yuan
author_sort Huan Zhou
title Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis
title_short Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis
title_full Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis
title_fullStr Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis
title_full_unstemmed Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis
title_sort regional credit, technological innovation, and economic growth in china: a spatial panel analysis
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2020-01-01
description Based on data of 31 provinces in China for the period 2007–2017, this paper establishes spatial models by means of a transcendental logarithmic production function and analyzes the impact of regional credit and technological innovation on regional economic growth. The Jenks natural breaks method, kernel density function, and Moran index are introduced for spatial statistical analysis. Spatial weight matrices are constructed from two aspects of geographical characteristics and innovative input characteristics. The empirical results show significant spatial heterogeneity and spatial autocorrelation in economic growth, regional credit, and technological innovation. Both regional credit and technological innovation are important impacts to economic growth, whereas the interaction of regional credit and technological innovation has a negative effect on provincial economic growth. Therefore, we argue that China should rationally allocate regional credit resources, strengthen technological innovation capabilities, and boost the integrated development of regional credit and technological innovation. It is a particularly important way to facilitate regional economic integration and sustainable development.
url http://dx.doi.org/10.1155/2020/1738279
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AT shaojianqu regionalcredittechnologicalinnovationandeconomicgrowthinchinaaspatialpanelanalysis
AT xiaoguangyang regionalcredittechnologicalinnovationandeconomicgrowthinchinaaspatialpanelanalysis
AT qingluyuan regionalcredittechnologicalinnovationandeconomicgrowthinchinaaspatialpanelanalysis
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