IDEAS home Printed from https://ideas.repec.org/p/eui/euiwps/eco2004-20.html
   My bibliography  Save this paper

Practical Problems with Reduced Rank ML Estimators for Cointegration Parameters and a Simple Alternative

Author

Listed:
  • Ralf BRUEGGEMANN
  • Helmut LUETKEPOHL

Abstract

Johansen's reduced rank maximum likelihood (ML) estimator for cointegration parameters in vector error correction models is known to produce occasional extreme outliers. Using a small monetary system and German data we illustrate the practical importance of this problem. We also consider an alternative generalized least squares (GLS) system estimator which has better properties in this respect. The two estimators are compared in a small simulation study. It is found that the GLS estimator can indeed be an attractive alternative to ML estimation of cointegration parameters.

Suggested Citation

  • Ralf BRUEGGEMANN & Helmut LUETKEPOHL, 2004. "Practical Problems with Reduced Rank ML Estimators for Cointegration Parameters and a Simple Alternative," Economics Working Papers ECO2004/20, European University Institute.
    • Handle: RePEc:eui:euiwps:eco2004/20
    as

    Download full text from publisher

    File URL: http://www.iue.it/PUB/ECO2004-20.pdf
    File Function: main text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    2. Hargreaves, Colin P. (ed.), 1994. "Non-Stationary Time Series Analysis and Cointegration," OUP Catalogue, Oxford University Press, number 9780198773924.
    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. Dreger, Christian & Wolters, Jürgen, 2010. "M3 Money Demand and Excess Liquidity in the Euro Area," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 144(3), pages 459-472.
    2. Gebhard Kirchgässner & Jürgen Wolters, 2010. "The Role of Monetary Aggregates in the Policy Analysis of the Swiss National Bank," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 146(I), pages 221-253, March.
    3. Lütkepohl, Helmut, 2008. "Problems related to over-identifying restrictions for structural vector error correction models," Economics Letters, Elsevier, vol. 99(3), pages 512-515, June.
    4. Siliti jr Hammadi & Ben mbarek jr Hassene, 2013. "Shocks Transmission in the Mediterranean Zone," Economics Bulletin, AccessEcon, vol. 33(2), pages 1010-1028.
    5. 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.
    6. Julián Ramajo Hernández(1) & Montserrat Ferré Carracedo(2), "undated". "Testing For Long-Run Purchasing Power Parity In The Post Bretton Woods Era: Evidence From Old And New Tests," Working Papers 24-05 Classification-JEL , Instituto de Estudios Fiscales.
    7. Chauvin, V. & Damette, O., 2010. "Wealth effects: the French case," Working papers 276, Banque de France.
    8. Christian Dreger & Hans-Eggert Reimers, 2012. "The long run relationship between private consumption and wealth: common and idiosyncratic effects," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(1), pages 21-34, April.
    9. Westerlund, Joakim, 2014. "On the choice of test for a unit root when the errors are conditionally heteroskedastic," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 40-53.
    10. Costa, Rafael & Bessler, David & Rosson, C. Parr, 2015. "The Impacts of Foot and Mouth Disease Outbreaks on the Brazilian Meat Market," Journal of Food Distribution Research, Food Distribution Research Society, vol. 46(3), pages 1-19, November.
    11. Badi Baltagi & Zijun Wang, 2007. "Testing for Cointegrating Rank Via Model Selection: Evidence From 165 Data Sets," Empirical Economics, Springer, vol. 33(1), pages 41-49, July.
    12. Breitung, Jörg & Pesaran, Mohammad Hashem, 2005. "Unit roots and cointegration in panels," Discussion Paper Series 1: Economic Studies 2005,42, Deutsche Bundesbank.
    13. Park, Suk K. & Ahn, Sung K. & Cho, Sinsup, 2011. "Generalized method of moments estimation for cointegrated vector autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2605-2618, September.
    14. Iikka Korhonen & Aaron Mehrotra, 2010. "Money Demand in Post-Crisis Russia: Dedollarization and Remonetization," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(2), pages 5-19, March.
    15. repec:zbw:bofitp:2007_014 is not listed on IDEAS
    16. Joakim Westerlund & Paresh Narayan, 2013. "Testing the Efficient Market Hypothesis in Conditionally Heteroskedastic Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(11), pages 1024-1045, November.
    17. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.

    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. Pulina, M. & O'Brien, R.J., 2002. "Monthly, annual and quarterly frequencies: a comparison of models for tourism in Sardinia and bounded rationality," Discussion Paper Series In Economics And Econometrics 206, Economics Division, School of Social Sciences, University of Southampton.
    2. Okunade, Albert A. & Murthy, Vasudeva N. R., 2002. "Technology as a 'major driver' of health care costs: a cointegration analysis of the Newhouse conjecture," Journal of Health Economics, Elsevier, vol. 21(1), pages 147-159, January.
    3. Tronzano, Marco, 2017. "Testing Fiscal Sustainability In The Transition Economies Of Eastern Europe: The Case Of Poland (1999-2015)," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 70(1), pages 103-132.
    4. Justin Doran & Bernard Fingleton, 2014. "Economic shocks and growth: Spatio-temporal perspectives on Europe's economies in a time of crisis," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 137-165, November.
    5. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    6. Lisbeth Funding la Cour, 1995. "A Component® based Analysis of the danish Long-run Money Demand Relation," Discussion Papers 95-18, University of Copenhagen. Department of Economics.
    7. Levent, Korap, 2007. "Modeling purchasing power parity using co-integration: evidence from Turkey," MPRA Paper 19584, University Library of Munich, Germany.
    8. Alessia Naccarato & Andrea Pierini & Giovanna Ferraro, 2021. "Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment," Annals of Operations Research, Springer, vol. 299(1), pages 81-99, April.
    9. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    10. Darrian Collins & Clem Tisdell, 2004. "Outbound Business Travel Depends on Business Returns: Australian Evidence," Australian Economic Papers, Wiley Blackwell, vol. 43(2), pages 192-207, June.
    11. Christian Schoder, 2012. "Effective demand, exogenous normal utilization and endogenous capacity in the long run. Evidence from a CVAR analysis for the US," IMK Working Paper 103-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    12. Muhammad Shahbaz & Vassilios G. Papavassiliou & Amine Lahiani & David Roubaud, 2023. "Are we moving towards decarbonisation of the global economy? Lessons from the distant past to the present," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2620-2634, July.
    13. Karaman Örsal, Deniz Dilan & Droge, Bernd, 2014. "Panel cointegration testing in the presence of a time trend," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 377-390.
    14. Jakšić Saša, 2022. "Modelling Determinants of Inflation in CESEE Countries: Global Vector Autoregressive Approach," Review of Economic Perspectives, Sciendo, vol. 22(2), pages 137-169, June.
    15. António Duarte, 2009. "The Portuguese Disinflation Process: Analysis of Some Costs and Benefits," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 16(1), pages 157-173, May.
    16. Njangang Henri & Nembot Ndeffo Luc & Nawo Larissa, 2019. "The Long‐run and Short‐run Effects of Foreign Direct Investment on Financial Development in African Countries," African Development Review, African Development Bank, vol. 31(2), pages 216-229, June.
    17. Lego, Brian & Gebremedhin, Tesfa & Cushing, Brian, 2000. "A Multi-Sector Export Base Model of Long-Run Regional Employment Growth," Agricultural and Resource Economics Review, Cambridge University Press, vol. 29(2), pages 192-197, October.
    18. Ali MNA & Moheddine YOUNSI, 2018. "A monetary conditions index and its application on Tunisian economic forecasting," Journal of Economics and Political Economy, KSP Journals, vol. 5(1), pages 38-56, March.
    19. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Hauser, Shmuel & Kedar-Levy, Haim & Milo, Orit, 2022. "Price discovery during parallel stocks and options preopening: Information distortion and hints of manipulation," Journal of Financial Markets, Elsevier, vol. 59(PA).

    More about this item

    Keywords

    Vector autoregressive process; Vector error correction model; Cointegration; Reduced rank estimation; Maximum likelihood estimation;
    All these keywords.

    JEL classification:

    • 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

    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:eui:euiwps:eco2004/20. 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: Cécile Brière (email available below). General contact details of provider: https://edirc.repec.org/data/deiueit.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.