Generalizing Impact Computations for the Autoregressive Spatial Interaction Model

Thibault Laurent

doi:10.1111/gean.12358

Generalizing Impact Computations for the Autoregressive Spatial Interaction Model

2023-03-01

2

OA

AI

Christine Thomas‐Agnan

DOI：10.1111/gean.12358

Original

Original request for help

Save

Abstract

En 中文

We extend the impact decomposition proposed by LeSage and Thomas-Agnan (2015) in the spatial interaction model to a more general framework, where the sets of origins and destinations can be different, and where the relevant attributes characterizing the origins do not coincide with those of the destinations. These extensions result in three flow data configurations which we study extensively: the square, the rectangular, and the noncartesian cases. We propose numerical simplifications to compute the impacts, avoiding the inversion of a large filter matrix. These simplifications considerably reduce computation time; they can also be useful for prediction. Furthermore, we define local measures for the intra, origin, destination and network effects. Interestingly, these local measures can be aggregated at different levels of analysis. Finally, we illustrate our methodology in a case study using remittance flows all over the world.

Keywords:

AUTOCORRELATION

SPACE

Generalizing Impact Computations for the Autoregressive Spatial Interaction Model

Abstract

Journal

Organization