This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Ordinary Least Squares Bias and Bias Corrections for iid Samples

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Lonnie Magee

Additional information is available for the following registered author(s):

Abstract

No abstract is available for this item.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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://socserv.mcmaster.ca/qsep/p/qsep419.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by McMaster University in its series Quantitative Studies in Economics and Population Research Reports with number 419.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 46 pages
Date of creation: Jun 2007
Date of revision:
Handle: RePEc:mcm:qseprr:419

Contact details of provider:

For technical questions regarding this item, or to correct its listing, contact: ().

Related research
Keywords: OLS bias; finite sample moments; Nagar approximation; bias correction; pairs bootstrap The O(n-1) bias and O(n-2) MSE of OLS are derived for iid samples. An approach is suggested for handling nonexistent finite sample moments. Bias corrections based on plug-in; weighting; jackknife and pairs bootstrap methods are equal to Op(n-3/2). Sometimes they are effective at lowering bias and MSE; but not always. In simulations; the bootstrap correction removes more bias than the others; but has a higher MSE. A hypothesis test is given for the presence of this bias. The techniques are applied to survey data on food expenditure; and the estimated bias is small and statistically insignificant.;

Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other
C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

This paper has been announced in the following NEP Reports:

Statistics
Access and download statistics

Did you know? Over 1000 institutions contribute their bibliographic data directly to this service.

This page was last updated on 2009-11-19.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.