The Use of Trimming to Improve the Performance of Tests for Nonlinear Serial Dependence with Application to the Australian National Electricity Market

Wild, Phillip, Hinich, Melvin J. and Foster, John (2008). The Use of Trimming to Improve the Performance of Tests for Nonlinear Serial Dependence with Application to the Australian National Electricity Market. Discussion Paper no. 367, School of Economics, The University of Queensland.

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
econdp367_0608.pdf Discussion Paper no. 367 application/pdf 353.40KB 82
Author Wild, Phillip
Hinich, Melvin J.
Foster, John
Title The Use of Trimming to Improve the Performance of Tests for Nonlinear Serial Dependence with Application to the Australian National Electricity Market
School, Department or Centre School of Economics
Institution The University of Queensland
Series Discussion Paper
Report Number no. 367
Publication date 2008-06
Publisher School of Economics
Start page 1
End page 35
Total pages 35
Language eng
Subject 340202 Environment and Resource Economics
Abstract/Summary In this article, we build on the results reported in Wild, Hinich and Foster (2008) for the National Electricity Market (NEM) of Australia by testing for episodic nonlinearity in the dynamics governing weekly cycles in spot price time series data. We apply the portmanteau correlation, bicorrelation and tricorrelation tests introduced in Hinich (1996) and the Engle (1982) ARCH LM test to the time series of half hourly spot prices from 7/12/1998 to 29/02/2008. We use trimming to improve the finite sample performance of the various test statistics mentioned above given the presence of significant skewness and leptokurtosis in the source datasets which may adversely affect the convergence properties of the test statistics in finite samples. With trimming, we still find the presence of significant third and fourth order (non-linear) serial dependence in the weekly spot price data, pointing to the presence of ‘deep’ nonlinear structure in this data.
Keyword Bicorrelations
Tricorrelations
Episodic Nonlinearity
ARCH/GARCH
Australian spot electrocity prices
Additional Notes JEL Classification: C32, C53, C89.

Document type: Working Paper
Collection: Discussion Papers (School of Economics)
 
Versions
Version Filter Type
Citation counts: Google Scholar Search Google Scholar
Access Statistics: 38 Abstract Views, 82 File Downloads  -  Detailed Statistics
Created: Mon, 16 Jun 2008, 09:46:26 EST by Belinda Weaver on behalf of Marketing, Outreach and Corporate Services