IDEAS home Printed from https://ideas.repec.org/a/rsr/journl/v65y2017i3p17-34.html
   My bibliography  Save this article

Power and Size analysis of Co-integration tests in Conditional Heteroskedascity: A Monte Carlo Simulation

Author

Listed:
  • Osabuohien-Irabor Osarumwense

    (Ambrose Alli University (A.A.U), Ekpoma, Edo, Nigeria)

  • Julian I. Mbegbu

    (University of Benin, Benin City, Nigeria)

Abstract

This paper investigates the finite sample performance of power and size properties of several major co-integration tests using simulation analysis. These tests include; the co-integration Regression Durbin-Watson test (CRDW), Eagle-Granger test, Dicky Fuller unit root test with () statistics, Johansen likelihood ratio tests, and Phillips-Ouliaris test. Comparisons of tests are evaluated based on the proportion of rejects of the hypothesis of a no co-integration. This study answers the question of which co-integration test is better, particularly between the Eagle-Granger two-step test and the Johansen’s tests for co-integration, when the sets of parameters in models are persistence and spiky. The bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH(1,1)) model with Gaussian innovations, is used in the data generating process (DGP). Our simulation results reveal that there is size distortion in the different co-integration test considered. The Eagle-Granger two-step test shows good robustness with respect to heteroskedasticity for the different sample sizes applied. However, the Johansen’s test for co-integration still proves to be powerful in capturing co-integration relationship, particularly for large sample when the co-integration innovations are Gaussian.

Suggested Citation

  • Osabuohien-Irabor Osarumwense & Julian I. Mbegbu, 2017. "Power and Size analysis of Co-integration tests in Conditional Heteroskedascity: A Monte Carlo Simulation," Romanian Statistical Review, Romanian Statistical Review, vol. 65(3), pages 17-34, September.
    • Handle: RePEc:rsr:journl:v:65:y:2017:i:3:p:17-34
    as

    Download full text from publisher

    File URL: http://www.revistadestatistica.ro/wp-content/uploads/2017/09/RRS-3_2017_A2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mallory Mindy & Lence Sergio H., 2012. "Testing for Cointegration in the Presence of Moving Average Errors," Journal of Time Series Econometrics, De Gruyter, vol. 4(2), pages 1-68, November.
    2. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    3. Hyungsun Chloe Cho & Miguel D. Ramirez, 2016. "Money Demand in Korea: A Cointegration Analysis, 1973-2014," Business and Economic Research, Macrothink Institute, vol. 6(1), pages 96-110, June.
    4. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    5. David H. Bernstein & Bent Nielsen, 2019. "Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient," Econometrics, MDPI, vol. 7(1), pages 1-24, January.
    6. Turgut Tursoy & Faisal Faisal, 2017. "Re-testing for financial integration of the Turkish Stock Market and the US Stock Market: An Evidence from co-integration and error correction models," Romanian Statistical Review, Romanian Statistical Review, vol. 65(2), pages 43-55, June.
    7. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    10. Müller, Ulrich K. & Watson, Mark W., 2013. "Low-frequency robust cointegration testing," Journal of Econometrics, Elsevier, vol. 174(2), pages 66-81.
    11. Enrique Moral-Benito & Luis Serv鮠, 2015. "Testing weak exogeneity in cointegrated panels," Applied Economics, Taylor & Francis Journals, vol. 47(30), pages 3216-3228, June.
    12. Raul Caruso & Marco Di Domizio, 2016. "Interdependence between US and European military spending: a panel cointegration analysis (1988-2013)," Applied Economics Letters, Taylor & Francis Journals, vol. 23(4), pages 302-305, March.
    13. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    14. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    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. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    2. Osamah M. Al-Khazali, 2003. "Stock Prices, Inflation, and Output: Evidence from the Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 2(3), pages 287-314, September.
    3. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    4. Yarovaya, Larisa & Lau, Marco Chi Keung, 2016. "Stock market comovements around the Global Financial Crisis: Evidence from the UK, BRICS and MIST markets," Research in International Business and Finance, Elsevier, vol. 37(C), pages 605-619.
    5. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    6. Panagiotou, Dimitrios, 2015. "Volatility Spillover Effects In The Extra Virgin Olive Oil Markets Of The Mediterranean," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(3), pages 1-11, July.
    7. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    8. Syriopoulos, Theodore, 2006. "Risk and return implications from investing in emerging European stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(3), pages 283-299, July.
    9. Haigh, Michael S. & Bryant, Henry L., 2000. "Price And Price Risk Dynamics In Barge And Ocean Freight Markets And The Effects On Commodity Trading," 2000 Conference, April 17-18 2000, Chicago, Illinois 18934, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    10. Ebenezer, Appiah Collins & Jatoe, John Baptist D. & Mensa-Bonsu, Akwasi, 2018. "Food Price Sensitivity To Changes In Petroleum Price And Exchange Rate In Ghana: A Cointegration Analysis," 2018 Conference (2nd), August 8-11, Kumasi, Ghana 277791, Ghana Association of Agricultural Economists.
    11. Chien, Mei-Se & Lee, Chien-Chiang & Hu, Te-Chung & Hu, Hui-Ting, 2015. "Dynamic Asian stock market convergence: Evidence from dynamic cointegration analysis among China and ASEAN-5," Economic Modelling, Elsevier, vol. 51(C), pages 84-98.
    12. Glen, D.R. & Martin, B.T., 2004. "2. A Survey Of The Modelling Of Dry Bulk And Tanker Markets," Research in Transportation Economics, Elsevier, vol. 12(1), pages 19-64, January.
    13. Myers, Robert J., 1994. "Time Series Econometrics and Commodity Price Analysis: A Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 62(02), pages 1-15, August.
    14. Abimelech Paye Gbatu & Zhen Wang & Presley K. Wesseh Jr. & Isaac Yak Repha Tutdel, 2017. "Causal Effects and Dynamic Relationship between Exchange Rate Volatility and Economic Development in Liberia," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 119-131.
    15. Ming-Yuan Leon Li & Chun-Nan Chen, 2010. "Examining the interrelation dynamics between option and stock markets using the Markov-switching vector error correction model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(7), pages 1173-1191.
    16. Roberto Martínez-Espiñeira, 2007. "An Estimation of Residential Water Demand Using Co-Integration and Error Correction Techniques," Journal of Applied Economics, Taylor & Francis Journals, vol. 10(1), pages 161-184, May.
    17. Kerry Patterson & Michael A. Thornton, 2013. "A review of econometric concepts and methods for empirical macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 2, pages 4-42, Edward Elgar Publishing.
    18. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    19. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    20. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.

    More about this item

    Keywords

    Co-integration test; Size; Monte-Carlos Simulation; Power; Heteroskedasticity;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    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:rsr:journl:v:65:y:2017:i:3:p:17-34. 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: Adrian Visoiu (email available below). General contact details of provider: https://edirc.repec.org/data/stagvro.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.