Title :

Interaction matrix selection in spatial econometrics with an application to growth theory

Author(s) :

Debarsy, Nicolas [Auteur]
Lille économie management - UMR 9221 [LEM]
Centre National de la Recherche Scientifique [CNRS]
Ertur, Cem [Auteur]
Laboratoire d'Économie d'Orleans [FRE2014] [LEO]

Journal title :

Regional Science and Urban Economics

Pages :

49-69

Publisher :

Elsevier

Publication date :

2019-03

ISSN :

0166-0462

English keyword(s) :

Bootstrap
GMM
Interaction matrix
J tests
Non-nested models
Heteroscedasticity
Spatial autoregressive models
Heteroskedasticity

HAL domain(s) :

Sciences de l'Homme et Société/Economies et finances

English abstract : [en]

The interaction matrix, or spatial weight matrix, is the fundamental tool to model cross-sectional interdependence between observations in spatial econometric models. However, it is most of the time not derived from theory, ...
Show more >The interaction matrix, or spatial weight matrix, is the fundamental tool to model cross-sectional interdependence between observations in spatial econometric models. However, it is most of the time not derived from theory, as it should be ideally, but chosen on an ad hoc basis. In this paper, we propose a modified version of the J test to formally select the interaction matrix. Our methodology is based on the application of the robust against unknown heteroskedasticity GMM estimation method, developed by Lin & Lee (2010). We then implement the testing procedure developed by Hagemann (2012) to overcome the decision problem inherent to non-nested models tests. An application is presented for the Schumpeterian growth model with worldwide interactions (Ertur & Koch 2011) using three different types of interaction matrix: genetic distance, linguistic distance and bilateral trade flows and we find that the interaction matrix based on trade flows is the most adequate. Furthermore, we propose a network based innovative representation of spatial econometric results.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Lille Économie Management (LEM) - UMR 9221

Source :

Harvested from HAL