Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/72305 
Year of Publication: 
2006
Series/Report no.: 
Reihe Ökonomie / Economics Series No. 188
Publisher: 
Institute for Advanced Studies (IHS), Vienna
Abstract: 
We introduce a regression-based gravity model for commodity flows between 35 regions in Austria. We incorporate information regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model. We find that our approach produces improved model fit and higher likelihood values. The model accounts for spatial dependence in the origin-destination flows by introducing a spatial connectivity matrix that allows for three types of spatial dependence in the origins to destinations flows. We modify this origin-destination connectivity structure that was introduced by LeSage and Pace (2005) to include information regarding the presence or absence of a major highway/train corridor that passes through the regions. Empirical estimates indicate that the strongest spatial autoregressive effects arise when both origin and destination regions have neighboring regions located on the highway network. Our approach provides a formal spatial econometric methodology that can easily incorporate network connectivity information in spatial autoregressive models.
Subjects: 
commodity flows
spatial autoregression
Bayesian
maximum likelihood
spatial connectivity of origin-destination flows
JEL: 
R1
R41
L92
C21
Document Type: 
Working Paper

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