Proceedings of the 2016 International Conference on Modern Management, Education Technology, and Social Science (MMETSS 2016)

Multivariate Statistical Analysis of Industrial Overcapacity in Chinese Provinces

Authors
Pan Wu
Corresponding Author
Pan Wu
Available Online February 2017.
DOI
https://doi.org/10.2991/mmetss-16.2017.34How to use a DOI?
Keywords
Industry, Overcapacity, Multivariate statistical.
Abstract
In recent years, excess production capacity has been plagued by China's economic development, especially under the background of the new normal, excess capacity in the short term and long term will cause certain negative influence to our country economy, destroy the healthy development of the industrial structure, increase the risk of a total economic fluctuations, hinder economic growth mode transformation, reduce the quality of efficiency of economic growth. Overcapacity problem has aroused high attention, and relevant government departments have to adopt a series of measures to adjust the problem, but so far has not been effectively resolved. In this context, study the formation mechanism of excess production capacity, should have very important guiding significance. In this paper, based on multivariate statistical method, the utilization of capacity of 31 provinces in China for principal component analysis, it is concluded that the capacity utilization first reflected in terms of input and output, the second is the use of funds, and there is obvious regional difference in the capacity utilization, better utilization of capacity, economically developed provinces and eastern overall capacity utilization of the Midwest.
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Cite this article

TY  - CONF
AU  - Pan Wu
PY  - 2017/02
DA  - 2017/02
TI  - Multivariate Statistical Analysis of Industrial Overcapacity in Chinese Provinces
BT  - Proceedings of the 2016 International Conference on Modern Management, Education Technology, and Social Science (MMETSS 2016)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/mmetss-16.2017.34
DO  - https://doi.org/10.2991/mmetss-16.2017.34
ID  - Wu2017/02
ER  -