Please use this identifier to cite or link to this item:
Lauridsen, Jørgen
Mur, Jesus
Year of Publication: 
Series/Report no.: 
44th Congress of the European Regional Science Association: "Regions and Fiscal Federalism", 25th - 29th August 2004, Porto, Portugal
European Regional Science Association (ERSA), Louvain-la-Neuve
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.
Document Type: 
Conference Paper

Files in This Item:

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.