Generalizing impact computations for the autoregressive spatial interaction model

Résumé

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 non-cartesian 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.

Mots-clés

Impact decomposition; local effects; spatial interaction autoregressive models; non-cartesian flow data;

Codes JEL

C13: Estimation: General
C31: Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction Models
C46: Specific Distributions • Specific Statistics
C51: Model Construction and Estimation
C65: Miscellaneous Mathematical Tools