Volume 4, Issue 6, December 2015, Page: 112-117
Descriptive Study of 2013 China per Capita Wage in Logistics and Transportation Industry
Jie Zhu, School of Information, Beijing Wuzi University, Beijing, China
Ruoling Zhang, School of Information, Beijing Wuzi University, Beijing, China
Binbin Fu, School of Information, Beijing Wuzi University, Beijing, China
Renhao Jin, School of Information, Beijing Wuzi University, Beijing, China
Received: Oct. 31, 2015;       Accepted: Nov. 9, 2015;       Published: Nov. 19, 2015
DOI: 10.11648/j.eco.20150406.13      View  3120      Downloads  51
Abstract
This paper does a descriptive study on 2013 area level per capita wage in logistics and transportation industry data in China. The per capita wage value is found to have increased over 11 years with annual increasing rate 13.9%. However, China per capita value is still less than western countries. The spatial autocorrelations are found in the area per capita wage data, and area per capita wage data is found to be high correlated with area per capita GDP data and area per capita wage in employment.
Keywords
China per Capita Wage, Area per Capita Wage, Area per Capita GDP, Spatial Distribution
To cite this article
Jie Zhu, Ruoling Zhang, Binbin Fu, Renhao Jin, Descriptive Study of 2013 China per Capita Wage in Logistics and Transportation Industry, Economics. Vol. 4, No. 6, 2015, pp. 112-117. doi: 10.11648/j.eco.20150406.13
Copyright
Copyright © 2015 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Anselin, L. (1995). Local indicators of spatial association – LISA. Geographical Analysis 27, 93--115.
[2]
Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society B 36, 192--225.
[3]
Getis, A. and Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis 24, 189--206.
[4]
Griffith, D. (1987). Spatial Autocorrelation: A Primer. Washington, DC: Association of American Geographers Resource Publication.
[5]
Griffith, D. (1992). What is spatial autocorrelation? Reflections on the past 25 years of spatial statistics. l’Espace Ge´ographique 21, 265--280.
[6]
Griffith, D. (1996). Spatial autocorrelation and eigenfunctions of the geographic weights matrix accompanying geo-referenced data. The Canadian Geographer 40, 351--367.
[7]
"GDP (Official Exchange Rate)". CIA World Factbook. RetrievedJune 2, 2012.
[8]
Dawson, Graham (2006). Economics and Economic Chenge. FT / Prentice Hall. p. 205. ISBN 9780273693512.
[9]
Mardia, K. and Marshall, R. (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71, 135--146.
[10]
Richardson, S. and He´ mon, D. (1981). On the variance of the sample correlation between two independent lattice processes. Journal of Applied Probability 18, 943--948.
[11]
Tiefelsdorf, M. and Boots, B. (1995). The exact distribution of Moran’s I. Environment and Planning. A 27, 985--999.
[12]
SAS Institute Inc, (2008). SAS/STAT® 9.2 User’s Guide: The variogram Procedure (Book Excerpt). NC: SAS Institute Inc, Cary.
[13]
George Peck (2015). Tableau 9: The Official Guide. McGraw-Hill Education.
Browse journals by subject