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The Comparison of Power and Optimization Algorithms on Unit Root Testing with Smooth Transition

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  • Tolga Omay

    (Türk Hava Kurumu University (THK))

  • Furkan Emirmahmutoğlu

    (Gazi University)

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, sequential quadratic programming 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 et al. (J Time Ser Anal 19:83–97, 1998) (LNV) and Sollis (J Time Ser Anal 25:409–417, 2004) unit root tests. Besides, we extend our analysis by including exponential smooth transition type of trend function in to unit root testing which is not used in the previous literature. The same result also holds true for our newly proposed unit root test with exponential smooth transition function type of trend model. Furthermore, we realize that there is a gap in the unit root studies that the newly proposed tests are not analyzed between each other’s data generating process (DGP). Hence, we investigate the power comparison of different nonlinear unit root test under various DGP including nonlinear unit root tests and find interesting results such as LNV type unit root test can manage to capture state dependent nonlinearity when the transition speed is high. Finally, we have used the Australian real interest rate parity hypothesis to empirically verify the results that we have obtained in the simulation studies.

Suggested Citation

  • Tolga Omay & Furkan Emirmahmutoğlu, 2017. "The Comparison of Power and Optimization Algorithms on Unit Root Testing with Smooth Transition," Computational Economics, Springer;Society for Computational Economics, vol. 49(4), pages 623-651, April.
    • Handle: RePEc:kap:compec:v:49:y:2017:i:4:d:10.1007_s10614-016-9574-3
    DOI: 10.1007/s10614-016-9574-3
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    References listed on IDEAS

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    Cited by:

    1. Furkan Emirmahmutoglu & Tolga Omay & Syed Jawad Hussain Shahzad & Safwan Mohd Nor, 2021. "Smooth Break Detection and De-Trending in Unit Root Testing," Mathematics, MDPI, vol. 9(4), pages 1-25, February.
    2. Yifei Cai & Tolga Omay, 2022. "Using Double Frequency in Fourier Dickey–Fuller Unit Root Test," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 445-470, February.
    3. Corakci, Aysegul & Omay, Tolga, 2023. "Is there convergence in renewable energy deployment? Evidence from a new panel unit root test with smooth and sharp structural breaks," Renewable Energy, Elsevier, vol. 205(C), pages 648-662.
    4. Omay, Tolga & Shahbaz, Muhammad & Stewart, Chris, 2021. "Is There Really Hysteresis in OECD Countries’ Unemployment Rates? New Evidence Using a Fourier Panel Unit Root Test," MPRA Paper 107691, University Library of Munich, Germany, revised 10 May 2021.
    5. Zarina Oflaz, 2017. "Structural Break, Nonlinearity and the Hysteresis hypothesis: Evidence from new unit root tests," Econometrics Letters, Bilimsel Mektuplar Organizasyonu (Scientific letters), vol. 4(2), pages 1-16.
    6. Nawaz, Kishwar & Lahiani, Amine & Roubaud, David, 2019. "Natural resources as blessings and finance-growth nexus: A bootstrap ARDL approach in an emerging economy," Resources Policy, Elsevier, vol. 60(C), pages 277-287.
    7. Shahbaz, Muhammad & Nasir, Muhammad Ali & Roubaud, David, 2018. "Environmental degradation in France: The effects of FDI, financial development, and energy innovations," Energy Economics, Elsevier, vol. 74(C), pages 843-857.
    8. Shahbaz, Muhammad & Omay, Tolga & Roubaud, David, 2019. "Sharp and Smooth Breaks in Unit Root Testing of Renewable Energy Consumption: The Way Forward," MPRA Paper 92176, University Library of Munich, Germany, revised 11 Feb 2019.

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    More about this item

    Keywords

    Nonlinear trend; Deterministic smooth transition; Structural change; Estimation methods;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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