oru.sePublikationer
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Testing for Cointegration in Multivariate Time Series: An evaluation of the Johansens trace test and three different bootstrap tests when testing for cointegration
Örebro University, Orebro University School of Business, Örebro University, Sweden.
2013 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In this paper we examine, by Monte Carlo simulation, size and power of the Johansens trace test when the error covariance matrix is nonstationary, and we also investigate the properties of three different bootstrap cointegration tests. Earlier studies indicate that the Johansen trace test is not robust in presence of heteroscedasticity, and tests based on resampling methods have been proposed to solve the problem. The tests that are evaluated is the Johansen trace test, nonparametric bootstrap test and two different types of wild bootstrap tests. The wild bootstrap test is a resampling method that attempts to mimic the GARCH model by multiplying each residual by a stochastic variable with an expected value of zero and unit variance. The wild bootstrap tests proved to be superior to the other tests, but not as good as earlier indicated. The more the error terms differs from white noise, the worse these tests are doing. Although the wild bootstrap tests did not do a very bad job, the focus of further investigation should be to derive tests that does an even better job than the wild bootstrap tests examined here.

Place, publisher, year, edition, pages
2013. , 33 p.
Keyword [en]
Johansen trace test, wild bootstrap, cointegration, heteroscedasticity, simulation
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:oru:diva-30067OAI: oai:DiVA.org:oru-30067DiVA: diva2:638279
Subject / course
Statistik
Supervisors
Examiners
Available from: 2013-10-11 Created: 2013-07-29 Last updated: 2013-10-11Bibliographically approved

Open Access in DiVA

Testing for Cointegration in Multivariate Time Series(914 kB)2817 downloads
File information
File name FULLTEXT02.pdfFile size 914 kBChecksum SHA-512
9cdd74a1ec6de7111b779f60dfe70e166cc18847bcf7432261090199499204f388d38f3da63f45d6b37409a809e8a1c4941cb8b12e9fe19cadfd7dd160f30ba4
Type fulltextMimetype application/pdf

By organisation
Orebro University School of Business, Örebro University, Sweden
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 2817 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 221 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf