Arbeitspapier
A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests
This paper provides an extensive Monte-Carlo comparison of severalcontemporary cointegration tests. Apart from the familiar Gaussian basedtests of Johansen, we also consider tests based on non-Gaussianquasi-likelihoods. Moreover, we compare the performance of these parametrictests with tests that estimate the score function from the data using eitherkernel estimation or semi-nonparametric density approximations. Thecomparison is completed with a fully nonparametric cointegration test. Insmall samples, the overall performance of the semi-nonparametric approachappears best in terms of size and power. The main cost of thesemi-nonparametric approach is the increased computation time. In largesamples and for heavily skewed or multimodal distributions, the kernel basedadaptive method dominates. For near-Gaussian distributions, however, thesemi-nonparametric approach is preferable again.
- Sprache
-
Englisch
- Erschienen in
-
Series: Tinbergen Institute Discussion Paper ; No. 99-012/4
- Klassifikation
-
Wirtschaft
- Thema
-
Schätztheorie
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Boswijk, H. Peter
Lucas, Andre
Taylor, Nick
- Ereignis
-
Veröffentlichung
- (wer)
-
Tinbergen Institute
- (wo)
-
Amsterdam and Rotterdam
- (wann)
-
1999
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Boswijk, H. Peter
- Lucas, Andre
- Taylor, Nick
- Tinbergen Institute
Entstanden
- 1999
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