Testing for vector autoregressive dynamics under heteroskedasticity
AbstractIn this paper we introduce a bootstrap procedure to test parameterrestrictions in vector autoregressive models which is robust incases of conditionally heteroskedastic error terms. The adoptedwild bootstrap method does not require any parametricspecification of the volatility process and takes contemporaneouserror correlation implicitly into account. Via a Monte Carloinvestigation empirical size and power properties of the newmethod are illustrated. We compare the bootstrap approach withstandard procedures either ignoring heteroskedasticity or adoptinga heteroskedasticity consistent estimation of the relevantcovariance matrices in the spirit of the White correction. Interms of empirical size the proposed method clearly outperformscompeting approaches without paying any price in terms of sizeadjusted power. We apply the alternative tests to investigate thepotential of causal relationships linking daily prices of naturalgas and crude oil. Unlike standard inference ignoring time varyingerror variances, heteroskedasticity consistent test procedures donot deliver any evidence in favor of short run causality betweenthe two series.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2002-36.
Date of creation: 09 Oct 2002
Date of revision:
Contact details of provider:
Web page: http://www.few.eur.nl/few
Energy markets; Causality; Bootstrap; Heteroskededasticity; Hypothesis testing; Vector autoregression;
Other versions of this item:
- Hafner, Christian M. & Herwartz, Helmut, 2002. "Testing for vector autoregressive dynamics under heteroskedasticity," SFB 373 Discussion Papers 2003,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Anneke Kop).
If references are entirely missing, you can add them using this form.