A Study of Multiregional Economic Correlation Analysis Based on Big Data—Taking the Regional Economy of Cities in Shaanxi Province, China, as an Example

Shouheng Tuo and Hong He
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Shouheng Tuo: School of Computer Science and Technology, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
Hong He: College of Economics and Management, Xi’an University of Posts and Telecommunications, Xi’an 710121, China

Sustainability, 2021, vol. 13, issue 9, 1-13

Abstract: To enhance the sustainability of the regional economy, this study attempts to integrate historical big data of multiregional and multi-industry economic indicators, aiming to explore and discover the correlations among regions, industries, or cross-regional economic indicators. In this paper, two correlation analysis models (the 2-order correlation model and the elastic-net regularized generalized linear model) are used to conduct a correlation analysis study of multiregional and multi-industry economies, and 20 years of historical data from 9 prefecture-level cities in Shaanxi (778 indicators in total) are analyzed empirically. The results show that the proposed method can mine complex correlations from economic big data.

Keywords: big data; multiregions; regional economy; association analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:9:p:5121-:d:548320

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