Spatial Panel Data Analysis on the Effect of Urbanization on Energy Consumption in China

2016 ◽  
Author(s):  
Honglei Niu ◽  
Zhiyong Liu
Keyword(s):  
Energy Consumption ◽  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Spatial Panel ◽  
Spatial Panel Data

scholarly journals A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns

2018 ◽  
Vol 10 (8) ◽  
pp. 2800 ◽  
Author(s):  
Rui Jin ◽  
Jianya Gong ◽  
Min Deng ◽  
Yiliang Wan ◽  
Xuexi Yang
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Interaction Model ◽  
Spillover Effects ◽  
Spatiotemporal Pattern ◽  
Regional Economic ◽  
Spatial Panel ◽  
Economic Agglomeration ◽  
Spatial Panel Data

Understanding regional economic agglomeration patterns is critical for sustainable economic development, urban planning and proper utilization of regional resources. Taking Guangdong Province of China as the study area, this paper introduces a comprehensive research framework for analyzing regional economic agglomeration patterns and understanding their spatiotemporal characteristics. First, convergence and autocorrelation methods are applied to understand the economic spatial patterns. Then, the intercity spatial interaction model (ISIM) is proposed to measure the strength of interplay among cities, and social network analysis (SNA) based on the ISIM is utilized, which is designed to reveal the network characteristics of economic agglomerations. Finally, we perform a spatial panel data analysis to comprehensively interpret the influences of regional economic agglomerations. The results indicate that from 2001 to 2016, the economy in Guangdong showed a double-core/peripheral pattern of convergence, with strengthened intercity interactions. The strength and external spillover effects of Guangzhou and Shenzhen enhanced, while Foshan and Dongguan had relatively strong absorptive abilities. Moreover, expanding regional communication and cooperation is key to enhancing vigorous economic agglomerations and regional network ties in Guangdong by spatial panel data analysis. Our results show that this is a suitable method of reflecting regional economic agglomeration process and its spatiotemporal pattern.

ECONOMIC FREEDOM AND INCOME LEVELS ACROSS U.S. STATES: A SPATIAL PANEL DATA ANALYSIS

2018 ◽  
Vol 37 (1) ◽  
pp. 40-49 ◽  
Author(s):  
Joshua C. Hall ◽  
Donald J. Lacombe ◽  
Timothy M. Shaughnessy
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Economic Freedom ◽  
Panel Data Analysis ◽  
Income Levels ◽  
Spatial Panel ◽  
Spatial Panel Data
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