Detecting Spatio-Temporal Dependance in Spatial Data Pooled over Time : (session 5: contributed lectures)

Abstract : This paper addresses the possible problem related to using strictly spatial modelling techniques for spatial data poole d over time. For these data, such as real estate, the spatial dimension is present, but subject to constraints related to temporal dimension. Three empirical examples are presented to investigate the impact of neglecting the temporal dimension in spatial analysis and to show how such an approach overestimates the pattern of spatial dependence, and overestimates the spatial autoregressive coefficient estimated. If generalized to all other empirical applications, this conclusion may have important considerations if one tries to measure the effect of extrinsic amenities on house prices.
Type de document :
Communication dans un congrès
Jean Paelinck Seminar of Spatial Econometric, Oct 2015, Dijon, France. 〈http://metodos.upct.es/8JP/〉
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https://hal.archives-ouvertes.fr/hal-01428575
Contributeur : Msh Dijon - Université de Bourgogne <>
Soumis le : vendredi 6 janvier 2017 - 14:05:27
Dernière modification le : jeudi 11 janvier 2018 - 06:25:42

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  • HAL Id : hal-01428575, version 1

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Jean Dubé, Diego Legros. Detecting Spatio-Temporal Dependance in Spatial Data Pooled over Time : (session 5: contributed lectures). Jean Paelinck Seminar of Spatial Econometric, Oct 2015, Dijon, France. 〈http://metodos.upct.es/8JP/〉. 〈hal-01428575〉

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