Abstract
This article considers a single-equation cointegrating model and proposes the locally best invariant and unbiased (LBIU) test for the null hypothesis of cointegration. We derive the local asymptotic power functions and compare them with the standard residual-based test, and show that the LBIU test is more powerful in a wide range of local alternatives. Then, we conduct a Monte Carlo simulation to investigate the finite sample properties of the tests and show that the LBIU test outperforms the residual-based test in terms of both size and power. The advantage of the LBIU test is particularly patent when the error is highly autocorrelated. Furthermore, we point out that finite sample performance of existing tests is largely affected by the initial value condition while our tests are immune to it. We propose a simple transformation of data that resolves the problem in the existing tests.
Original language | English |
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Pages (from-to) | 476-500 |
Number of pages | 25 |
Journal | Journal of Time Series Analysis |
Volume | 29 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2008 May |
Externally published | Yes |
Keywords
- Cointegration
- Locally best test
- Point optimal test
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics