| 1. |
- Andersson, Michael K., et al.
(författare)
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Bootstrap testing for fractional integration
- 1998
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Asymptotic tests for fractional integration, such as the Geweke-Porter-Hudak test, the modified rescaled range test and Lagrange multiplier type tests, exhibit size distortions in small samples. This paper investigates a parametric bootstrap testing procedure, for size correction, by means of a computer simulation study. The bootstrap provides a practical method to eliminate size distortions in the case of an asymptotic pivotal statistic while the power, in general, is close to the corresponding size adjusted asymptotic test. The results are very encouraging and suggest that a bootstrap testing procedure does correct for size distortions.
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| 2. |
- Andersson, Michael K., et al.
(författare)
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Power and bias of likelihood based inference in the cointegration model under fractional cointegration
- 1999
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Ingår i: Economics Letters. - : Elsevier. - 0165-1765. ; 65:2, s. 143-147
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper investigates how fractional cointegration affects the common maximum likelihood cointegration procedure. It is shown that the likelihood ratio test of no cointegration has considerable power against fractional alternatives. In contrast to the case of a cointegrated system, the usual maximum likelihood estimator gives severely biased estimates of the long-run relation under fractional cointegration. This suggests that the standard likelihood approach should be used with caution and that a test to separate fractionally cointegrated series from series that are cointegrated of an integer order should be executed prior to estimation.
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| 3. |
- Andersson, Michael K., et al.
(författare)
-
Robust testing for fractional integration using the bootstrap
- 1998
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Asymptotic tests for fractional integration are usually badly sized in small samples, even for normally distributed processes. Furthermore, tests that are well-sized (under normality) may be seriously distorted by non-normalities and ARCH errors. This paper demonstrates how the bootstrap can be implemented to correct for such size distortions. It is shown that a well-designed bootstrap test based on the MRR and GPH tests is exact, and that a procedure based on the REG test is nearly exact. Ort, förlag, år, upplaga, sidor
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| 4. |
- Gredenhoff, Mikael P.
(författare)
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Bootstrap inference in time series econometrics
- 1998
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This dissertation contains five essays in the field of time series econometrics. The main issue discussed is the lack of coherence between small sample and asymptotic inference. Frequently, in modern econometrics distributional results are strictly only valid for a hypothetical infinite sample. Studies show that the attained actual level of a test may be considerable different from the nominal significance level, and as a concequence, too many true null hypotheses will falsely be rejected. This leads, in the extension, to applied users that too often reject evidence in the data for theoretical predictions. In large, the thesis discusses how computer intensive methods may be used to adjust the test distribution, such that the actual significance level will coincide with the desired nominal level. The first two essays focus on how to improve testing for persistence in data, through a bootstrap procedure within a univariate framework. The remaining three essays are studies of multivariate time series models. The third essay considers the identification problem of the basic stationary vector autoregressive model, which is also the basic-line econometric specification for maximum likelihood cointegration analysis. In the fourth essay the multivariate framework is expanded to allow for components of different integrating order and in this setting the paper discusses how fractional cointegration affects the inference in maximum likelihood cointegration analysis. The fifth essay consider once again the bootstrap testing approach, now in a multivariate application, to correct inference on long-run relations in maximum likelihood cointegration analysis.
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| 5. |
- Gredenhoff, Mikael P., et al.
(författare)
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Bootstrap testing and approximate finite sample distributions for tests of linear restrictions on cointegrating vectors
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- This paper considers computer intensive methods to inference on cointegrating vectors in maximum likelihood cointegration analysis. The likelihood ratio test statistics used in the literature are known to have an asymptotic X2-distribution. However, previous simulation studies show that the size distortion of the test can be considerable for small samples. Typically the nominal significance level, say 5%, is much smaller than the attained actual level, and as a consequence, too many true null hypotheses will be rejected. It is demonstrated how a parametric bootstrap can be implemented, frequenly resulting in a nearly exact a level test. Furthermore, response surface regression is used to examine small sample properties of the asymptotic likelihood ratio test. The estimated equations can be used as approximate finite-sample corrections, allowing rough, but easily applied, corrections of the LR test.
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