Performance of autoregressive order selection criteria: a simulation study
Proper selection of autoregressive order plays a crucial role in econometrics modeling cycles and testing procedures. This paper compares the performance of various autoregressive order selection criteria in selecting the true order. This simulation study shows that Schwarz information criterion (SI...
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| Format: | Article |
| Language: | English |
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Universiti Putra Malaysia Press
2008
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| Online Access: | http://psasir.upm.edu.my/id/eprint/40526/1/56.%20Performance%20of%20Autoregressive%20Order%20Selection%20Criteria.pdf |
| _version_ | 1796973758066458624 |
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| author | Liew, Venus Khim-Sen Shitan, Mahendran Choong, Chee Keong Hooy, Chee Wooi |
| author_facet | Liew, Venus Khim-Sen Shitan, Mahendran Choong, Chee Keong Hooy, Chee Wooi |
| author_sort | Liew, Venus Khim-Sen |
| collection | UPM |
| description | Proper selection of autoregressive order plays a crucial role in econometrics modeling cycles and testing procedures. This paper compares the performance of various autoregressive order selection criteria in selecting the true order. This simulation study shows that Schwarz information criterion (SIC), final prediction error (FPE), Hannan-Qiunn criterion (HQC) and Bayesian information criterion (BIC) have considerable high performance in selecting the true autoregressive order, even if the sample size is small, whereas Akaike's information criterion (AIC) over-estimated the true order with a probability of more than two-thirds. Further, this simulation study also shows that the probability of these criteria (except AIC) in correctly estimating the true order approaches one as sample size grows. Generally, these findings show that the most commonly used AIC might yield misleading policy conclusions due to its unsatisfactory performance. We note here that out of a class of commonly used criteria, BIC performs the best for a small sample size of 25 observations. |
| first_indexed | 2024-03-06T08:47:19Z |
| format | Article |
| id | upm.eprints-40526 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T08:47:19Z |
| publishDate | 2008 |
| publisher | Universiti Putra Malaysia Press |
| record_format | dspace |
| spelling | upm.eprints-405262015-11-20T00:09:32Z http://psasir.upm.edu.my/id/eprint/40526/ Performance of autoregressive order selection criteria: a simulation study Liew, Venus Khim-Sen Shitan, Mahendran Choong, Chee Keong Hooy, Chee Wooi Proper selection of autoregressive order plays a crucial role in econometrics modeling cycles and testing procedures. This paper compares the performance of various autoregressive order selection criteria in selecting the true order. This simulation study shows that Schwarz information criterion (SIC), final prediction error (FPE), Hannan-Qiunn criterion (HQC) and Bayesian information criterion (BIC) have considerable high performance in selecting the true autoregressive order, even if the sample size is small, whereas Akaike's information criterion (AIC) over-estimated the true order with a probability of more than two-thirds. Further, this simulation study also shows that the probability of these criteria (except AIC) in correctly estimating the true order approaches one as sample size grows. Generally, these findings show that the most commonly used AIC might yield misleading policy conclusions due to its unsatisfactory performance. We note here that out of a class of commonly used criteria, BIC performs the best for a small sample size of 25 observations. Universiti Putra Malaysia Press 2008-07 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/40526/1/56.%20Performance%20of%20Autoregressive%20Order%20Selection%20Criteria.pdf Liew, Venus Khim-Sen and Shitan, Mahendran and Choong, Chee Keong and Hooy, Chee Wooi (2008) Performance of autoregressive order selection criteria: a simulation study. Pertanika Journal of Science & Technology, 16 (2). pp. 171-176. ISSN 0128-7680; ESSN: 2231-8526 http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2016%20%282%29%20Jul.%202008/11%20Pages%20171-176.pdf |
| spellingShingle | Liew, Venus Khim-Sen Shitan, Mahendran Choong, Chee Keong Hooy, Chee Wooi Performance of autoregressive order selection criteria: a simulation study |
| title | Performance of autoregressive order selection criteria: a simulation study |
| title_full | Performance of autoregressive order selection criteria: a simulation study |
| title_fullStr | Performance of autoregressive order selection criteria: a simulation study |
| title_full_unstemmed | Performance of autoregressive order selection criteria: a simulation study |
| title_short | Performance of autoregressive order selection criteria: a simulation study |
| title_sort | performance of autoregressive order selection criteria a simulation study |
| url | http://psasir.upm.edu.my/id/eprint/40526/1/56.%20Performance%20of%20Autoregressive%20Order%20Selection%20Criteria.pdf |
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