Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/235808 
Year of Publication: 
2020
Citation: 
[Journal:] REGION [ISSN:] 2409-5370 [Volume:] 7 [Issue:] 1 [Publisher:] European Regional Science Association (ERSA) [Place:] Louvain-la-Neuve [Year:] 2020 [Pages:] 1-19
Publisher: 
European Regional Science Association (ERSA), Louvain-la-Neuve
Abstract: 
This study focus on models with spatially varying coefficients using simulations.  As shown by Sarrias (2019), this modeling strategy is intended to complement the existing approaches by using variables at micro level and by adding flexibility and realism to the potential domain of the coefficient on the geographical space. Spatial heterogeneity is modelled by allowing the parameters associated with each observed variable to vary 'randomly' across space according to some distribution. To show the main advantages of this modeling strategy, the Rchoice package in R is used.
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article

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