Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171853
Authors: 
Arbia, Giuseppa
Espa, Giuseppe
Giuliani, Diego
Year of Publication: 
2015
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 3 [Year:] 2015 [Issue:] 4 [Pages:] 709-718
Abstract: 
In many microeconometric models we use distances. For instance, in modelling the individual behavior in labor economics or in health studies, the distance from a relevant point of interest (such as a hospital or a workplace) is often used as a predictor in a regression framework. However, in order to preserve confidentiality, spatial micro-data are often geo-masked, thus reducing their quality and dramatically distorting the inferential conclusions. In particular in this case, a measurement error is introduced in the independent variable which negatively affects the properties of the estimators. This paper studies these negative effects, discusses their consequences, and suggests possible interpretations and directions to data producers, end users, and practitioners.
Subjects: 
spatial econometrics
spatial microeconometrics
consistency of estimates
geo-masking
confidentiality
distance evaluation
JEL: 
C01
C13
C31
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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