EconPapers    
Economics at your fingertips  
 

A study of industrial electricity consumption based on partial Granger causality network

Can-Zhong Yao, Qing-Wen Lin and Ji-Nan Lin

Physica A: Statistical Mechanics and its Applications, 2016, vol. 461, issue C, 629-646

Abstract: The paper studies the industrial energy transferring paths among the industries of China by distinguishing direct causality from the indirect. With complementary graphs, we propose that industrial causal relationship can be heterogeneous, and provide insights for refining robust industrial causality framework.

Keywords: Granger causality network; Partial Granger causality network; Bootstrap; Complementary network; Industrial influence (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116303405
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:461:y:2016:i:c:p:629-646

DOI: 10.1016/j.physa.2016.06.072

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).

 
Page updated 2024-12-28
Handle: RePEc:eee:phsmap:v:461:y:2016:i:c:p:629-646