Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis
Ng and Perron (2001) designed a unit root test, which incorporates the properties of DFGLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally well especially in the presence of a negative moving average. However, the performance of the test depends heavily on the ch...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Econometric Research Association
2015-09-01
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| Series: | International Econometric Review |
| Subjects: | |
| Online Access: | http://www.era.org.tr/makaleler/20110103.pdf |
| _version_ | 1797918582372302848 |
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| author | Muhammad Irfan Malik Atiq-ur-Rehman |
| author_facet | Muhammad Irfan Malik Atiq-ur-Rehman |
| author_sort | Muhammad Irfan Malik |
| collection | DOAJ |
| description | Ng and Perron (2001) designed a unit root test, which incorporates the properties of DFGLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally
well especially in the presence of a negative moving average. However, the performance
of the test depends heavily on the choice of the spectral density estimators used in the
construction of the test. Various estimators for spectral density exist in the literature; each
have a crucial impact on the output of test, however there is no clarity on which of these
estimators gives the optimal size and power properties. This study aims to evaluate the
performance of the Ng-Perron for different choices of spectral density estimators in the
presence of a negative and positive moving average using Monte Carlo simulations. The
results for large samples show that: (a) in the presence of a positive moving average,
testing with the kernel based estimator gives good effective power and no size distortion,
and (b) in the presence of a negative moving average, the autoregressive estimator gives
better effective power, however, huge size distortion is observed in several specifications
of the data-generating process. |
| first_indexed | 2024-04-10T13:31:41Z |
| format | Article |
| id | doaj.art-dd5f90d404c84c53805953a0722e76e4 |
| institution | Directory Open Access Journal |
| issn | 1308-8793 1308-8815 |
| language | English |
| last_indexed | 2024-04-10T13:31:41Z |
| publishDate | 2015-09-01 |
| publisher | Econometric Research Association |
| record_format | Article |
| series | International Econometric Review |
| spelling | doaj.art-dd5f90d404c84c53805953a0722e76e42023-02-15T16:11:33ZengEconometric Research AssociationInternational Econometric Review1308-87931308-88152015-09-01725163Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative AnalysisMuhammad Irfan Malik0Atiq-ur-Rehman1International Islamic University Islamabad International Islamic University IslamabadNg and Perron (2001) designed a unit root test, which incorporates the properties of DFGLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally well especially in the presence of a negative moving average. However, the performance of the test depends heavily on the choice of the spectral density estimators used in the construction of the test. Various estimators for spectral density exist in the literature; each have a crucial impact on the output of test, however there is no clarity on which of these estimators gives the optimal size and power properties. This study aims to evaluate the performance of the Ng-Perron for different choices of spectral density estimators in the presence of a negative and positive moving average using Monte Carlo simulations. The results for large samples show that: (a) in the presence of a positive moving average, testing with the kernel based estimator gives good effective power and no size distortion, and (b) in the presence of a negative moving average, the autoregressive estimator gives better effective power, however, huge size distortion is observed in several specifications of the data-generating process.http://www.era.org.tr/makaleler/20110103.pdfNg-Perron TestMonte CarloSpectral DensityUnit Root Testing |
| spellingShingle | Muhammad Irfan Malik Atiq-ur-Rehman Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis International Econometric Review Ng-Perron Test Monte Carlo Spectral Density Unit Root Testing |
| title | Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis |
| title_full | Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis |
| title_fullStr | Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis |
| title_full_unstemmed | Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis |
| title_short | Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis |
| title_sort | choice of spectral density estimator in ng perron test a comparative analysis |
| topic | Ng-Perron Test Monte Carlo Spectral Density Unit Root Testing |
| url | http://www.era.org.tr/makaleler/20110103.pdf |
| work_keys_str_mv | AT muhammadirfanmalik choiceofspectraldensityestimatorinngperrontestacomparativeanalysis AT atiqurrehman choiceofspectraldensityestimatorinngperrontestacomparativeanalysis |