Measurement Errors Arising When Using Distances in Microeconometric Modelling and the Individuals’ Position Is Geo-Masked for Confidentiality
Giuseppe Arbia (),
Giuseppe Espa () and
Diego Giuliani ()
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Giuseppe Espa: Department of Economics and Management, University of Trento, Trento 38122, Italy
Diego Giuliani: Department of Economics and Management, University of Trento, Trento 38122, Italy
Econometrics, 2015, vol. 3, issue 4, 1-10
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.
Keywords: spatial econometrics; spatial microeconometrics; consistency of estimates; geo-masking; confidentiality; distance evaluation (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:3:y:2015:i:4:p:709-718:d:57989
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