IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

RMSE Reduction for GMM Estimators of Linear Time Series Models

  • Guido Kuersteiner

    (Massachusetts Institute of Technology)

In this paper we analyze GMM estimators for time series models as advocated by Hayashi and Sims, and Hansen and Singleton. It is well known that these estimators achieve efficiency bounds if the number of lagged observations in the instrument set goes to infinity. A new version of the GMM estimator based on kernel weighted moment conditions is proposed. Higher order asymptotic expansions are used to obtain optimal rates of expansions for the number of instruments to minimize the asymptotic MSE of the estimator. Estimates of optimal bandwidth parameters are then used to construct a fully feasible GMM estimator where the number of lagged instruments are endogenously determined by the data. Expressions for the asymptotic bias of kernel weighted GMM estimators are obtained. It is shown that standard GMM procedures have larger asymptotic biases than kernel weighted GMM. A bias correction for the estimator is proposed. It is shown that the bias corrected version achieves a faster rate of convergence of the higher order terms of the MSE than the uncorrected estimator.

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:
File Function: main text
Download Restriction: no

Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0892.

in new window

Date of creation: 01 Aug 2000
Date of revision:
Handle: RePEc:ecm:wc2000:0892
Contact details of provider: Phone: 1 212 998 3820
Fax: 1 212 995 4487
Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

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

When requesting a correction, please mention this item's handle: RePEc:ecm:wc2000:0892. 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: (Christopher F. Baum)

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.