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

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  • Ralf Brüggemann
  • Helmut Lütkepohl

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. Copyright 2005 Blackwell Publishing Ltd.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:obuest:v:67:y:2005:i:5:p:673-690
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    References listed on IDEAS

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    1. Hargreaves, Colin P. (ed.), 1994. "Non-Stationary Time Series Analysis and Cointegration," OUP Catalogue, Oxford University Press, number 9780198773924.
    2. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
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    Cited by:

    1. Dreger, Christian & Wolters, Jürgen, 2010. "M3 Money Demand and Excess Liquidity in the Euro Area," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 459-472.
    2. Korhonen, Iikka & Mehrotra, Aaron, 2007. "Money demand in post-crisis Russia : De-dollarisation and re-monetisation," BOFIT Discussion Papers 14/2007, Bank of Finland, Institute for Economies in Transition.
    3. 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.
    4. 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.
    5. 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.
    6. Breitung, Jörg & Pesaran, Mohammad Hashem, 2005. "Unit roots and cointegration in panels," Discussion Paper Series 1: Economic Studies 2005,42, Deutsche Bundesbank.
    7. 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.
    8. 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.
    9. 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), November.
    10. Chauvin, V. & Damette, O., 2010. "Wealth effects: the French case," Working papers 276, Banque de France.
    11. 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.
    12. 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.
    13. Bruggemann, Ralf & Lutkepohl, Helmut & Saikkonen, Pentti, 2006. "Residual autocorrelation testing for vector error correction models," Journal of Econometrics, Elsevier, vol. 134(2), pages 579-604, October.
    14. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    15. 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.

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    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

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