Template-Type: ReDIF-Article 1.0
Author-Name:  Muhammad Irfan Malik
Author-Email: irfanmalik@outlook.com
Author-Workplace-Name: International Institute of Islamic Economics, International Islamic University Islamabad, Pakistan.
Author-Name:  Atiq-ur-Rehman
Author-Email: ateeqmzd@gmail.com
Author-Workplace-Name: International Institute of Islamic Economics, International Islamic University Islamabad, Pakistan.
Title:  Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis
Abstract:Ng and Perron (2001) designed a unit root test, which incorporates the properties of DF-GLS 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.
Classification-JEL: C01, C15, C63
Keywords: Ng-Perron Test, Monte Carlo, Spectral Density, Unit Root Testing.
Journal: International Econometric Review
Pages: 51-63
Volume: 7
Issue: 2
Year: 2015
Month: September
File-URL: http://www.era.org.tr/makaleler/20110103.pdf
File-Format: Application/pdf
Handle: RePEc:erh:journl:v:7:y:2015:i:2:p:51-63