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

Outliers in Cross-Sectional Regression

Contents:

Author Info

  • Jørgen Lauridsen

    ()

  • Jesus Mur

    ()

Abstract

The robustness of the results coming from an econometric application depends to a great extent on the quality of the sampling information. This statement is a general rule that becomes especially relevant in a spatial context where data usually have lots of irregularities. The purpose of our paper is to examine more closely this question paying attention to one point in particular, namely outliers. The presence of outliers in the sample may be useful, for example in order to break some multicollinearity relations but they may also result in other inconsistencies. The main aspect of our work is that we resolve the discussion in a spatial context, looking closely into the behaviour shown, under several unfavourable conditions, by the most outstanding misspecification tests. For this purpose, we plan and solve a Monte Carlo simulation. The conclusions point to the fact that these statistics react in a different way to the problems posed.

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-sre.wu-wien.ac.at/ersa/ersaconfs/ersa04/PDF/27.pdf
Download Restriction: no

Bibliographic Info

Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa04p27.

as in new window
Length:
Date of creation: Aug 2004
Date of revision:
Handle: RePEc:wiw:wiwrsa:ersa04p27

Contact details of provider:
Postal: Welthandelsplatz 1, 1020 Vienna, Austria
Web page: http://www.ersa.org

Related research

Keywords:

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. Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers, Princeton, Department of Economics - Econometric Research Program 338, Princeton, Department of Economics - Econometric Research Program.
  2. Pena, Daniel, 1990. "Influential Observations in Time Series," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 8(2), pages 235-41, April.
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:wiw:wiwrsa:ersa04p27. 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: (Gunther Maier).

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.