Advanced Search
MyIDEAS: Login

Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown

Contents:

Author Info

  • Kulan Ranasinghe

    ()

  • Mervyn J. Silvapulle

    ()

Registered author(s):

    Abstract

    The parameters in duration models are usually estimated by a Quasi Maximum Likelihood Estimator [QMLE]. This estimator is efficient if the errors are iid and exponentially distributed. Otherwise, it may not be the most efficient. Motivated by this, a class of estimators has been introduced by Drost and Werker (2004). Their estimator is asymptotically most efficient when the error distribution is unknown. However, the practical relevance of their method remains to be evaluated. Further, although some parameters in several common duration models are known to be nonnegative, this estimator may turn out to be negative. This paper addresses these two issues. We propose a new semiparametric estimator when there are inequality constraints on parameters, and a simulation study evaluates the two semiparametric estimators. The results lead us to conclude the following when the error distribution is unknown: (i) If there are no inequality constraints on parameters then the Drost-Werker estimator is better than the QMLE, and (ii) if there are inequality constraints on parameters then the estimator proposed in this paper is better than the Drost-Werker estimator and the QMLE. In conclusion, this paper recommends estimators that are better than the often used QMLE for estimating duration models.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2008/wp1-08.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 1/08.

    as in new window
    Length: 29 pages
    Date of creation: Jan 2008
    Date of revision:
    Handle: RePEc:msh:ebswps:2008-1

    Contact details of provider:
    Postal: PO Box 11E, Monash University, Victoria 3800, Australia
    Phone: +61-3-9905-2489
    Fax: +61-3-9905-5474
    Email:
    Web page: http://www.buseco.monash.edu.au/depts/ebs/
    More information through EDIRC

    Order Information:
    Email:
    Web: http://www.buseco.monash.edu.au/depts/ebs/pubs/wpapers/

    Related research

    Keywords: Adaptive inference; Conditional duration model; Constrained inference; Efficient semiparametric estimation; Order restricted inference; Semiparametric efficiency bound.;

    Find related papers by JEL classification:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Fernandes, Marcelo & Grammig, Joachim, 2006. "A family of autoregressive conditional duration models," Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
    2. Newey, Whitney K, 1990. "Semiparametric Efficiency Bounds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 99-135, April-Jun.
    3. Drost, F.C. & Werker, B.J.M., 2004. "Semiparametric duration models," Open Access publications from Tilburg University urn:nbn:nl:ui:12-140875, Tilburg University.
    4. Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE).
    5. Shyamal D. Peddada & Joseph K. Haseman & Xiaofeng Tan & Greg Travlos, 2006. "Tests for a simple tree order restriction with application to dose-response studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 493-506.
    6. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
    7. Shyamal D. Peddada & David B. Dunson & Xiaofeng Tan, 2005. "Estimation of order-restricted means from correlated data," Biometrika, Biometrika Trust, vol. 92(3), pages 703-715, September.
    8. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    9. BAUWENS, Luc & GIOT, Pierre, . "The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks," CORE Discussion Papers RP -1497, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Hammou El Barmi & Hari Mukerjee, 2005. "Inferences Under a Stochastic Ordering Constraint: The k-Sample Case," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 252-261, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:msh:ebswps:2008-1. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Simone Grose).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.