IDEAS home Printed from https://ideas.repec.org/p/max/cprwps/83.html
   My bibliography  Save this paper

Testing for Cointegrating Rank via Model Selection: Evidence from 165 Data Sets

Author

Abstract

The model selection approach has been proposed as an alternative to the popular tests for cointegration such as the residual-based ADF test and the system-based trace test. Using information criteria, we conduct cointegration tests on 165 data sets used in published studies. The empirical results demonstrate the usefulness of the model selection approach for applied researchers.

Suggested Citation

  • Badi H. Baltagi & Zijun Wang, 2006. "Testing for Cointegrating Rank via Model Selection: Evidence from 165 Data Sets," Center for Policy Research Working Papers 83, Center for Policy Research, Maxwell School, Syracuse University.
  • Handle: RePEc:max:cprwps:83
    as

    Download full text from publisher

    File URL: https://surface.syr.edu/cpr/82/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ralf Brüggemann & Helmut Lütkepohl, 2005. "Practical Problems with Reduced‐rank ML Estimators for Cointegration Parameters and a Simple Alternative," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 673-690, October.
    2. Allan W. Gregory & Alfred A. Haug & Nicoletta Lomuto, 2004. "Mixed signals among tests for cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 89-98.
    3. Chao, John C. & Phillips, Peter C. B., 1999. "Model selection in partially nonstationary vector autoregressive processes with reduced rank structure," Journal of Econometrics, Elsevier, vol. 91(2), pages 227-271, August.
    4. Phillips, Peter C B & Ploberger, Werner, 1996. "An Asymptotic Theory of Bayesian Inference for Time Series," Econometrica, Econometric Society, vol. 64(2), pages 381-412, March.
    5. Wang, Zijun & Bessler, David A., 2005. "A Monte Carlo Study On The Selection Of Cointegrating Rank Using Information Criteria," Econometric Theory, Cambridge University Press, vol. 21(3), pages 593-620, June.
    6. Phillips, Peter C B, 1996. "Econometric Model Determination," Econometrica, Econometric Society, vol. 64(4), pages 763-812, July.
    7. Gonzalo, Jesus & Lee, Tae-Hwy, 1998. "Pitfalls in testing for long run relationships," Journal of Econometrics, Elsevier, vol. 86(1), pages 129-154, June.
    8. Kapetanios, George, 2004. "The Asymptotic Distribution Of The Cointegration Rank Estimator Under The Akaike Information Criterion," Econometric Theory, Cambridge University Press, vol. 20(4), pages 735-742, August.
    9. Peter Winker & Dietmar Maringer, 2004. "Optimal Lag Structure Selection in VEC-Models," Contributions to Economic Analysis, in: New Directions in Macromodelling, pages 213-234, Emerald Group Publishing Limited.
    10. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    11. Aznar, Antonio & Salvador, Manuel, 2002. "Selecting The Rank Of The Cointegration Space And The Form Of The Intercept Using An Information Criterion," Econometric Theory, Cambridge University Press, vol. 18(4), pages 926-947, August.
    12. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
    13. Phillips, Peter C B & Ouliaris, S, 1990. "Asymptotic Properties of Residual Based Tests for Cointegration," Econometrica, Econometric Society, vol. 58(1), pages 165-193, January.
    14. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    15. Boswijk, Peter & Franses, Philip Hans, 1992. "Dynamic Specification and Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 369-381, August.
    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. Mu, Jianhong E. & McCarl, Bruce A. & Bessler, David A., 2013. "Impacts of BSE and Avian Influenza on U.S. Meat Demand," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150392, Agricultural and Applied Economics Association.
    2. Moonsoo Park & Yanhong Jin & Alan Love, 2011. "Dynamic and contemporaneous causality in a supply chain: an application of the US beef industry," Applied Economics, Taylor & Francis Journals, vol. 43(30), pages 4785-4801.
    3. Peri, Massimo & Baldi, Lucia, 2010. "Vegetable oil market and biofuel policy: An asymmetric cointegration approach," Energy Economics, Elsevier, vol. 32(3), pages 687-693, May.
    4. Moonsoo Park & Yanhong H. Jin & David A. Bessler, 2008. "The impacts of animal disease crises on the Korean meat market," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 183-195, September.
    5. Hagerman, Amy D. & Jin, Yanhong H., 2009. "The Buzz In The Pits: Livestock Futures' Response To A Rumor Of Foreign Animal Disease," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49493, Agricultural and Applied Economics Association.
    6. Maxym Chaban, 2010. "Cointegration analysis with structural breaks and deterministic trends: an application to the Canadian dollar," Applied Economics, Taylor & Francis Journals, vol. 42(23), pages 3023-3037.
    7. Kosei Fukuda, 2011. "Cointegration rank switching model: an application to forecasting interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(5), pages 509-522, August.

    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. Moonsoo Park & Yanhong H. Jin & David A. Bessler, 2008. "The impacts of animal disease crises on the Korean meat market," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 183-195, September.
    2. Yan Qian & Zijun Wang, 2021. "A model selection approach to jointly testing for structural breaks and cointegration with application to the Eurocurrency interest rates market," Empirical Economics, Springer, vol. 61(2), pages 799-825, August.
    3. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.
    4. Athanasopoulos, George & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor & Vahid, Farshid, 2011. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," Journal of Econometrics, Elsevier, vol. 164(1), pages 116-129, September.
    5. Xu Cheng & P eter C. B. Phillips, 2009. "Semiparametric cointegrating rank selection," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 83-104, January.
    6. Miller J. Isaac, 2010. "A Nonlinear IV Likelihood-Based Rank Test for Multivariate Time Series and Long Panels," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-38, September.
    7. Li, Qiaoling & Pan, Jiazhu & Yao, Qiwei, 2009. "On determination of cointegration ranks," LSE Research Online Documents on Economics 24106, London School of Economics and Political Science, LSE Library.
    8. Kosei Fukuda, 2011. "Cointegration rank switching model: an application to forecasting interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(5), pages 509-522, August.
    9. Chao, John C. & Phillips, Peter C. B., 1999. "Model selection in partially nonstationary vector autoregressive processes with reduced rank structure," Journal of Econometrics, Elsevier, vol. 91(2), pages 227-271, August.
    10. Miller, J. Isaac & Ratti, Ronald A., 2009. "Crude oil and stock markets: Stability, instability, and bubbles," Energy Economics, Elsevier, vol. 31(4), pages 559-568, July.
    11. Hagerman, Amy D. & Jin, Yanhong H., 2009. "The Buzz In The Pits: Livestock Futures' Response To A Rumor Of Foreign Animal Disease," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49493, Agricultural and Applied Economics Association.
    12. Neri, Marcelo Côrtes & Soares, Wagner Lopes, 2008. "Turismo sustentável e alivio a pobreza: avaliação de impacto," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 689, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    13. Haug, Alfred A., 1996. "Tests for cointegration a Monte Carlo comparison," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 89-115.
    14. Kleibergen, Frank & Paap, Richard, 2002. "Priors, posteriors and bayes factors for a Bayesian analysis of cointegration," Journal of Econometrics, Elsevier, vol. 111(2), pages 223-249, December.
    15. Barry Falk & Chun-Hsuan Wang, 2003. "Testing long-run PPP with infinite-variance returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 471-484.
    16. Österholm, Pär, 2003. "Testing for Cointegration in Misspecified Systems –A Monte Carlo Study of Size Distortions," Working Paper Series 2003:21, Uppsala University, Department of Economics.
    17. Peter C. B. Phillips, 2003. "Laws and Limits of Econometrics," Economic Journal, Royal Economic Society, vol. 113(486), pages 26-52, March.
    18. Bryant, Henry L. & Outlaw, Joe L. & Anderson, David P., 2005. "Rice World Market Prices," 2005 Annual meeting, July 24-27, Providence, RI 19178, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Cheng, Xu & Phillips, Peter C.B., 2012. "Cointegrating rank selection in models with time-varying variance," Journal of Econometrics, Elsevier, vol. 169(2), pages 155-165.
    20. Bayer, Christian & Hanck, Christoph, 2008. "Is double trouble? How to combine cointegration tests," Technical Reports 2008,10, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:max:cprwps:83. 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: Margaret Austin or Zia Jackson or Katrina Fiacchi (email available below). General contact details of provider: https://edirc.repec.org/data/cpsyrus.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.