Improving Fractional Integration Tests With Bootstrap Distributions
AbstractAsymptotic 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 severely distorted by non-normalities and ARCH errors. This paper demonstrates how the bootstrap can be implemented to correct for such size distortions.
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Bibliographic InfoPaper provided by National Institute of Economic Research in its series Working Paper with number 74.
Length: 18 pages
Date of creation: 01 Jun 2000
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Long memory; Resampling; Skewness and kurtosis; ARCH; Size correction; Power;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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- Arteche, J. & Orbe, J., 2005. "Bootstrapping the log-periodogram regression," Economics Letters, Elsevier, vol. 86(1), pages 79-85, January.
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