The comparison of optimization algorithms on unit root testing with smooth transition

MPRA Paper from University Library of Munich, Germany

Abstract: The aim of this study is to search for a better optimization algorithm in applying unit root tests that inherit nonlinear models in the testing process. The algorithms analyzed include Broyden, Fletcher, Goldfarb and Shanno (BFGS), Gauss-Jordan, Simplex, Genetic, and Extensive Grid-Search. The simulation results indicate that the derivative free methods, such as Genetic and Simplex, have advantages over hill climbing methods, such as BFGS and Gauss-Jordan, in obtaining accurate critical values for the Leybourne, Newbold and Vougos (1996, 1998) (LNV) and Sollis (2004) unit root tests. Moreover, when parameters are estimated under the alternative hypothesis of the LNV type of unit root tests the derivative free methods lead to an unbiased and efficient estimator as opposed to those obtained from other algorithms. Finally, the empirical analyses show that the derivative free methods, hill climbing and simple grid search can be used interchangeably when testing for a unit root since all three optimization methods lead to the same empirical test results.

Keywords: Nonlinear trend; Deterministic smooth transition; Structural change; Estimation methods (search for similar items in EconPapers)
JEL-codes: C01 C15 C22 (search for similar items in EconPapers)
Date: 2012-10-22
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ets
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Citations: View citations in EconPapers (2)

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