Outliers in Cross-Sectional Regression
AbstractThe 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 InfoIf 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.
Bibliographic InfoPaper provided by European Regional Science Association in its series ERSA conference papers with number ersa04p27.
Date of creation: Aug 2004
Date of revision:
Contact details of provider:
Postal: Welthandelsplatz 1, 1020 Vienna, Austria
Web page: http://www.ersa.org
This paper has been announced in the following NEP Reports:
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.:
- Perron, Pierre, 1989.
"The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis,"
Econometric Society, vol. 57(6), pages 1361-1401, November.
- Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gunther Maier).
If references are entirely missing, you can add them using this form.