Omay, Tolga (2012): The comparison of optimization algorithms on unit root testing with smooth transition.
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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.
|Item Type:||MPRA Paper|
|Original Title:||The comparison of optimization algorithms on unit root testing with smooth transition|
|English Title:||The comparison of optimization algorithms on unit root testing with smooth transition|
|Keywords:||Nonlinear trend; Deterministic smooth transition; Structural change; Estimation methods|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics
|Depositing User:||Tolga Omay|
|Date Deposited:||22. Oct 2012 14:22|
|Last Modified:||19. Feb 2013 18:11|
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