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Article

Selecting the Lag Length for the MGLS Unit Root Tests with Structural Change: A Warning Note for Practitioners Based on Simulations †

1
Central Reserve Bank of Peru, 441–445 Antonio Miró Quesada Street, Lima 1, Lima, Peru
2
Department of Economics, Pontificia Universidad Católica del Perú, Av. Universitaria 1801, Lima 32, Lima, Peru
*
Author to whom correspondence should be addressed.
This Note is drawn from the Thesis of Ricardo Quineche at the Department of Economics, Pontificia Universidad Católica del Perú (PUCP). This is a substantial revised version of an earlier version circulated under the title Data-Dependent Methods for the Lag Length Selection in Unit Root Tests with Structural Change which appear as Working Paper 404 of the Department of Economics, PUCP. The current version has been improved thanks to the relevant comments received from the Guest Editor of the Review (Professor Pierre Perron) and three anonymous Referees. Further, we thank comments of Luis García, José Tavera and Jorge Rojas (PUCP). Any remaining errors are our responsibility.
Academic Editor: Pierre Perron
Econometrics 2017, 5(2), 17; https://doi.org/10.3390/econometrics5020017
Received: 31 August 2016 / Revised: 31 March 2017 / Accepted: 4 April 2017 / Published: 16 April 2017
(This article belongs to the Special Issue Unit Roots and Structural Breaks)
This is a simulation-based warning note for practitioners who use the M G L S unit root tests in the context of structural change using different selection lag length criteria. With T = 100 , we find severe oversize problems when using some criteria, while other criteria produce an undersizing behavior. In view of this dilemma, we do not recommend using these tests. While such behavior tends to disappear when T = 250 , it is important to note that most empirical applications use smaller sample sizes such as T = 100 or T = 150 . The A D F G L S test does not present an oversizing or undersizing problem. The only disadvantage of the A D F G L S test arises in the presence of M A ( 1 ) negative correlation, in which case the M G L S tests are preferable, but in all other cases they are very undersized. When there is a break in the series, selecting the breakpoint using the Supremum method greatly improves the results relative to the Infimum method. View Full-Text
Keywords: unit root tests; structural change; truncation lag; GLS detrending; information criteria; sequential general to specific t-sig method unit root tests; structural change; truncation lag; GLS detrending; information criteria; sequential general to specific t-sig method
MDPI and ACS Style

Quineche, R.; Rodríguez, G. Selecting the Lag Length for the MGLS Unit Root Tests with Structural Change: A Warning Note for Practitioners Based on Simulations. Econometrics 2017, 5, 17. https://doi.org/10.3390/econometrics5020017

AMA Style

Quineche R, Rodríguez G. Selecting the Lag Length for the MGLS Unit Root Tests with Structural Change: A Warning Note for Practitioners Based on Simulations. Econometrics. 2017; 5(2):17. https://doi.org/10.3390/econometrics5020017

Chicago/Turabian Style

Quineche, Ricardo, and Gabriel Rodríguez. 2017. "Selecting the Lag Length for the MGLS Unit Root Tests with Structural Change: A Warning Note for Practitioners Based on Simulations" Econometrics 5, no. 2: 17. https://doi.org/10.3390/econometrics5020017

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