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This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance process and define both a random effects and a fixed effects spatial generalized two-stage least squares estimator for the regression parameters of the model. We prove consistency of the proposed estimators and derive their joint asymptotic distribution, which is robust to heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random against the spatial fixed effects model. (authors' abstract)

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ePub-WU OAI Archive (Vienna Univ. of Econ. and B.A.)   ePub-WU OAI Archive (Vienna Univ. of Econ. and B.A.)  

Autor(es)

Badinger, Harald -  Egger, Peter - 

Id.: 58493362

Idioma: inglés  - 

Versión: 1.0

Estado: Final

Tipo:  application/pdf -  application/pdf - 

Palabras claveJEL C13, C21, C23 - 

Tipo de recurso: Paper  -  NonPeerReviewed  - 

Tipo de Interactividad: Expositivo

Nivel de Interactividad: muy bajo

Audiencia: Estudiante  -  Profesor  -  Autor  - 

Estructura: Atomic

Coste: no

Copyright: sí

Formatos:  application/pdf -  application/pdf - 

Requerimientos técnicos:  Browser: Any - 

Relación: [References] http://www.wu.ac.at/economics/forschung/wp
[References] http://dx.doi.org/10.1080/17421772.2014.992362
[References] http://epub.wu.ac.at/4126/

Fecha de contribución: 18-oct-2016

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