Functional SAR models: with application to spatial econometrics
Simultaneous autoregressive (SAR) models have been extensively used for the analysis of spatial data in areas as diverse as demography, economy and geography. These are linear models with a scalar response, scalar explanatory variables and autoregressive errors. In this work we extend this model...
| Autor Principal: | Pineda-Ríos, Wilmer |
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| Otros Autores: | Giraldo, Ramón, Porcu, Emilio |
| Formato: | Generación de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicos |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: |
Pineda-Ríos, W., Giraldo, R., & Porcu, E. (2018). Functional SAR models: With application to spatial econometrics. Bogotá: doi:10.1016/j.spasta.2018.12.002 |
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| Sumario: |
Simultaneous autoregressive (SAR) models have been extensively
used for the analysis of spatial data in areas as diverse as demography,
economy and geography. These are linear models with a
scalar response, scalar explanatory variables and autoregressive
errors. In this work we extend this modeling approach from scalar
to functional covariates. Least squares and maximum likelihood
are used as estimation methods of the parameters. A simulation
study is considered for evaluating the performance of the proposed
methodology. As an illustration, the model is used to establish
the relationship between unsatisfied basic needs and curves of
gross domestic product obtained in 32 departments of Colombia
(districts of the country). |
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