Nonlinear estimation of the gravity model with Poisson/negative binomial methods has become popular to model international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each...

Bilateral trade flows traditionally have been analysed by means of the spatial interaction gravity model. Still, (auto)correlation of trade flows has only recently received attention in the literature. This paper takes up this thread of emerging literature, and shows that spatial filtering (SF)...

Nonlinear estimation of the gravity model with Poisson-type regression methods has become popular for modelling international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each...

Nonlinear estimation of the gravity model with Poisson/negative binomial methods has become popular to model international trade flows, as it permits a better accounting for large numbers of zero flows. Nevertheless, as trade flows are not independent of each other due to spatial...

Nonlinear estimation of the gravity model with Poisson-type regression methods has become popular to model international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each...

Nonlinear estimation of the gravity model with Poisson/negative binomial methods has become popular to model international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each...

Bilateral trade flows traditionally have been analysed by means of the spatial interaction gravity model. Still, (auto)correlation of trade flows has only recently received attention in the literature. This paper takes up this thread of emerging literature, and shows that spatial filtering (SF)...