Abstract
The problem of model selection of a univariate long memory time series is investigated once a semi parametric estimator for the long memory parameter has been used. Standard information criteria are not consistent in this case. A Modified Information Criterion (MIC) that overcomes these difficulties is introduced and proofs that show its asymptotic validity are provided. The results are general and cover a wide range of short memory processes. Simulation evidence compares the new and existing methodologies and empirical applications in monthly inflation and daily realized volatility are presented.
| Original language | English |
|---|---|
| Pages (from-to) | 116-131 |
| Journal | Computational Statistics & Data Analysis |
| Volume | 76 |
| Early online date | 03 May 2013 |
| DOIs | |
| Publication status | Published - Aug 2014 |
Keywords
- Long memory
- ARFIMA models
- Modified Information Criteria
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