IDEAS home Printed from https://ideas.repec.org/p/hhs/cesisp/0227.html
   My bibliography  Save this paper

Linear and Non-linear Causality Test in a LSTAR model - wavelet decomposition in a non-linear environment

Author

Listed:
  • Li, Yushu

    (CAFO, Växjö University)

  • Shukur, Ghazi

    (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)

Abstract

In this paper, we use simulated data to investigate the power of different causality tests in a two-dimensional vector autoregressive (VAR) model. The data are presented in a non-linear environment that is modelled using a logistic smooth transition autoregressive (LSTAR) function. We use both linear and non-linear causality tests to investigate the unidirection causality relationship and compare the power of these tests. The linear test is the commonly used Granger causality test. The non-linear test is a non-parametric test based on Baek and Brock (1992) and Hiemstra and Jones (1994). When implementing the non-linear test, we use separately the original data, the linear VAR filtered residuals, and the wavelet decomposed series based on wavelet multiresolution analysis (MRA). The VAR filtered residuals and the wavelet decomposition series are used to extract the non-linear structure of the original data. The simulation results show that the non-parametric test based on the wavelet decomposition series (which is a model free approach) has the highest power to explore the causality relationship in the non-linear models.

Suggested Citation

  • Li, Yushu & Shukur, Ghazi, 2010. "Linear and Non-linear Causality Test in a LSTAR model - wavelet decomposition in a non-linear environment," Working Paper Series in Economics and Institutions of Innovation 227, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    • Handle: RePEc:hhs:cesisp:0227
    as

    Download full text from publisher

    File URL: https://static.sys.kth.se/itm/wp/cesis/cesiswp227.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    2. Bell, David & Kay, Jim & Malley, Jim, 1996. "A non-parametric approach to non-linear causality testing," Economics Letters, Elsevier, vol. 51(1), pages 7-18, April.
    3. Huh, Hyeon-seung, 2002. "GDP growth and the composite leading index: a nonlinear causality analysis for eleven countries," Economics Letters, Elsevier, vol. 77(1), pages 93-99, September.
    4. Li, Jing, 2006. "Testing Granger Causality in the presence of threshold effects," International Journal of Forecasting, Elsevier, vol. 22(4), pages 771-780.
    5. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    2. Yii Siing Wong & Chong Mun Ho & Brian Dollery, 2012. "Impact of exchange rate volatility on import flows: the case of Malaysia and the United States," Applied Financial Economics, Taylor & Francis Journals, vol. 22(24), pages 2027-2034, December.
    3. Lim, Shiok Ye & Ho, Chong Mun, 2013. "Nonlinearity in ASEAN-5 export-led growth model: Empirical evidence from nonparametric approach," Economic Modelling, Elsevier, vol. 32(C), pages 136-145.
    4. Monica Billio & Silvio Di Sanzo, 2015. "Granger-causality in Markov switching models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 956-966, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    2. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    3. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
    4. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2008. "Modelo de Crescimento Baseado nas Exportações: Evidências empíricas para Chile, Brasil e México, em uma perspectiva Não Linear," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807170923500, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. M-Ali Sotoudeh & Andrew C. Worthington, 2016. "A comparative analysis of monetary responses to global oil price changes: net oil producing vs. net oil consuming countries," International Economics and Economic Policy, Springer, vol. 13(4), pages 623-640, October.
    6. Péguin-Feissolle, Anne & Strikholm, Birgit & Teräsvirta, Timo, 2007. "Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form," SSE/EFI Working Paper Series in Economics and Finance 672, Stockholm School of Economics, revised 18 Jan 2012.
    7. Skalin, Joakim & Terasvirta, Timo, 1999. "Another Look at Swedish Business Cycles, 1861-1988," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(4), pages 359-378, July-Aug..
    8. Qiao, Zhuo & Chu, Patrick Kuok-Kun, 2014. "Does fine wine price contain useful information to forecast GDP? Evidence from major developed countries," Economic Modelling, Elsevier, vol. 38(C), pages 75-79.
    9. Cook, Steven, 2008. "Further analysis of spurious causality," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 647-651.
    10. Qiao, Zhuo & McAleer, Michael & Wong, Wing-Keung, 2009. "Linear and nonlinear causality between changes in consumption and consumer attitudes," Economics Letters, Elsevier, vol. 102(3), pages 161-164, March.
    11. Zhuo Qiao & Keith Lam, 2011. "Granger causal relations among Greater China stock markets: a nonlinear perspective," Applied Financial Economics, Taylor & Francis Journals, vol. 21(19), pages 1437-1450.
    12. Alexander Zeitlberger & Alexander Brauneis, 2016. "Modeling carbon spot and futures price returns with GARCH and Markov switching GARCH models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 149-176, March.
    13. Baghli, Mustapha, 2006. "A model-free characterization of causality," Economics Letters, Elsevier, vol. 91(3), pages 380-388, June.
    14. Kumar, Satish, 2017. "On the nonlinear relation between crude oil and gold," Resources Policy, Elsevier, vol. 51(C), pages 219-224.
    15. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    16. Semei Coronado & Rebeca Jim'enez-Rodr'iguez & Omar Rojas, 2015. "An empirical analysis of the relationships between crude oil, gold and stock markets," Papers 1510.07599, arXiv.org, revised May 2016.
    17. Polanco-Martínez, J.M. & Fernández-Macho, J. & Neumann, M.B. & Faria, S.H., 2018. "A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1211-1227.
    18. Wang, Gang-Jin & Chen, Yan & Zhu, You & Xie, Chi, 2024. "Systemic risk prediction using machine learning: Does network connectedness help prediction?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    19. Josué M. Polanco-Martínez & Luis M. Abadie, 2016. "Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach," Energies, MDPI, vol. 9(12), pages 1-19, December.
    20. Yahya Can DURA & Mustafa Kemal BESER & Hakan ACAROGLU, 2017. "Türkiye’nin Ihracata Dayali Buyumesinin Ekonometrik Analizi," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 17(2), pages 295-310.

    More about this item

    Keywords

    Granger causality; LSTAR model; Wavelet multiresolution; Monte Carlo simulation;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:cesisp:0227. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Vardan Hovsepyan (email available below). General contact details of provider: https://edirc.repec.org/data/cekthse.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.