A unit root test based on the modified least squares estimator
A unit root test based on the modified least squares (MLS) estimator for first-order autoregressive process is proposed and compared with unit root tests based on the ordinary least squares (OLS), the weighted symmetric (WS) and the modified weighted symmetric (MWS) estimators. The percentiles of th...
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| Format: | Article |
| Language: | English |
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Universiti Kebangsaan Malaysia
2014
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| Online Access: | http://journalarticle.ukm.my/7826/ http://journalarticle.ukm.my/7826/ http://journalarticle.ukm.my/7826/1/20_Wararit.pdf |
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ukm-78262016-12-14T06:45:19Z http://journalarticle.ukm.my/7826/ A unit root test based on the modified least squares estimator Wararit Panichkitkosolkul, A unit root test based on the modified least squares (MLS) estimator for first-order autoregressive process is proposed and compared with unit root tests based on the ordinary least squares (OLS), the weighted symmetric (WS) and the modified weighted symmetric (MWS) estimators. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of type I error and powers of the unit root tests were estimated via Monte Carlo simulation. The simulation results showed that all unit root tests can control the probability of type I error for all situations. The empirical power of the test is higher than the other unit root tests, and Apart from that, the and tests also provide the highest empirical power. As an illustration, the monthly series of U.S. nominal interest rates on three-month treasury bills is analyzed. Universiti Kebangsaan Malaysia 2014-10 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/7826/1/20_Wararit.pdf Wararit Panichkitkosolkul, (2014) A unit root test based on the modified least squares estimator. Sains Malaysiana, 43 (10). pp. 1623-1633. ISSN 0126-6039 http://www.ukm.my/jsm/ |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Kebangasaan Malaysia |
| building |
UKM Institutional Repository |
| collection |
Online Access |
| language |
English |
| description |
A unit root test based on the modified least squares (MLS) estimator for first-order autoregressive process is proposed and compared with unit root tests based on the ordinary least squares (OLS), the weighted symmetric (WS) and the modified weighted symmetric (MWS) estimators. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of type I error and powers of the unit root tests were estimated via Monte Carlo simulation. The simulation results showed that all unit root tests can control the probability of type I error for all situations. The empirical power of the test is higher than the other unit root tests, and Apart from that, the and tests also provide the highest empirical power. As an illustration, the monthly series of U.S. nominal interest rates on three-month treasury bills is analyzed. |
| format |
Article |
| author |
Wararit Panichkitkosolkul, |
| spellingShingle |
Wararit Panichkitkosolkul, A unit root test based on the modified least squares estimator |
| author_facet |
Wararit Panichkitkosolkul, |
| author_sort |
Wararit Panichkitkosolkul, |
| title |
A unit root test based on the modified least squares estimator |
| title_short |
A unit root test based on the modified least squares estimator |
| title_full |
A unit root test based on the modified least squares estimator |
| title_fullStr |
A unit root test based on the modified least squares estimator |
| title_full_unstemmed |
A unit root test based on the modified least squares estimator |
| title_sort |
unit root test based on the modified least squares estimator |
| publisher |
Universiti Kebangsaan Malaysia |
| publishDate |
2014 |
| url |
http://journalarticle.ukm.my/7826/ http://journalarticle.ukm.my/7826/ http://journalarticle.ukm.my/7826/1/20_Wararit.pdf |
| first_indexed |
2023-09-18T19:50:42Z |
| last_indexed |
2023-09-18T19:50:42Z |
| _version_ |
1777406199994515456 |