IDEAS home Printed from https://ideas.repec.org/p/roc/rocher/410.html
   My bibliography  Save this paper

Adaptive Estimation of Error Correlation Models

Author

Listed:
  • Hodgson, D.J.

Abstract

This paper considers adaptive maximum likelihood estimation of reduced rank vector error correction models. It is shown that such models can be asymptotically efficiently estimated even in the absence of knowledge of the shape of the density function of the innovation sequence, provided that this density is symmetric. The construction of the estimator, involving the nonparametric kernel estimation of the unknown density using the residuals of a consistent preliminary estimator, is described, and its asymptotic distribution is derived. Asymptotic efficiency gains over the Gaussian pseudo–maximum likelihood estimator are evaluated for elliptically symmetric innovations.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hodgson, D.J., 1995. "Adaptive Estimation of Error Correlation Models," RCER Working Papers 410, University of Rochester - Center for Economic Research (RCER).
    • Handle: RePEc:roc:rocher:410
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2012. "Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Other publications TiSEM bc68a2f2-3ca3-443c-b3ac-f, Tilburg University, School of Economics and Management.
    2. Dong Wan Shin & Oesook Lee, 2004. "M‐Estimation for regressions with integrated regressors and arma errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 283-299, March.
    3. Perez-Alonso, Alicia, 2007. "A bootstrap approach to test the conditional symmetry in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3484-3504, April.
    4. Yiguo Sun, 2014. "Semi-Parametric Estimation Of Linear Cointegrating Models With Nonlinear Contemporaneous Endogeneity," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 437-461, August.
    5. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.
    6. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing Forward Exchange Rate Unbiasedness Efficiently: A Semiparametric Approach," Journal of Applied Economics, Taylor & Francis Journals, vol. 7(1), pages 325-353, May.
    7. Keith Vorkink & Douglas J. Hodgson & Oliver Linton, 2002. "Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 617-639.
    8. Douglas Hodgson, 2002. "Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form," Cahiers de recherche CREFE / CREFE Working Papers 146, CREFE, Université du Québec à Montréal.
    9. Jushan Bai & Serena Ng, 1998. "A Test for Conditional Symmetry in Time Series Models," Boston College Working Papers in Economics 410, Boston College Department of Economics.
    10. Douglas Hodgson & Barrett Slade & Keith Vorkink, 2006. "Constructing Commercial Indices: A Semiparametric Adaptive Estimator Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 32(2), pages 151-168, March.
    11. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Other publications TiSEM d1b040c9-db57-4e55-846f-4, Tilburg University, School of Economics and Management.
    12. Boswijk, H. Peter & Lucas, Andre, 2002. "Semi-nonparametric cointegration testing," Journal of Econometrics, Elsevier, vol. 108(2), pages 253-280, June.
    13. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    14. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    15. Hallin, Marc & van den Akker, Ramon & Werker, Bas J.M., 2016. "Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank," Journal of Econometrics, Elsevier, vol. 190(1), pages 46-61.
    16. Hodgson, Douglas J., 1998. "Adaptive estimation of cointegrating regressions with ARMA errors," Journal of Econometrics, Elsevier, vol. 85(2), pages 231-267, August.

    More about this item

    Keywords

    EVALUATION; ECONOMETRICS;

    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:roc:rocher:410. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Richard DiSalvo (email available below). General contact details of provider: .

    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.