Advanced Search
MyIDEAS: Login to save this paper or follow this series

Shrinkage methods for instrumental variable estimation

Contents:

Author Info

  • Ryo Okui
Registered author(s):

Abstract

This paper proposes shrinkage methods in instrumental variable estimations to solve the ``many instruments'' problem. Even though using a large number of instruments reduces the asymptotic variances of the estimators, it has been observed both in theoretical works and in practice that in finite samples the estimators may behave very poorly if the number of instruments is large. This problem can be addressed by shrinking the influence of a subset of instrumental variables. An instrumental variable estimator is the solution to an equation which is a weighted sum of sample moment conditions; We reconstruct the estimating equation by shrinking some elements of that weighting vector. This idea can also be interpreted as shrinking some of the OLS coefficient estimates from the regression of the endogenous variables on the instruments then using the predicted values of the endogenous variables based on the shrunk coefficient estimates as the instruments. The shrinkage parameter is chosen to minimize the asymptotic MSE. It is found that the optimal shrinkage parameter has a closed form which leads to easy implementation. The Monte Carlo result shows that the shrinkage methods work well and moreover perform better than the instrument selection procedure in Donald and Newey (2001) in several situations relevant to applications

Download Info

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" 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.

Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 Far Eastern Meetings with number 678.

as in new window
Length:
Date of creation: 11 Aug 2004
Date of revision:
Handle: RePEc:ecm:feam04:678

Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Email:
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC

Related research

Keywords: TSLS; LIML; shrinkage estimator; instrumental variables;

Find related papers by JEL classification:

References

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

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:ecm:feam04:678. 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.