Giuseppe Arbia • Badi H. Baltagi (Eds.) Spatial Econometrics Methods and Applications Physica-Verlag A Springer Company Contents 1. Introduction 1 Badi H. Baltagi and Giuseppe Arbia 2 Errors in Variables and Spatial...

Spatial Econometrics is a rapidly evolving field born from the joint efforts of economists, statisticians, econometricians and regional scientists. The book provides the reader with a broad view of the topic by including both methodological and application papers. Indeed the application papers...

This paper studies the convergence of per-capita GDP across European regions over a fairly long period. Most of the works in the field are based on either cross-sectional or fixed-effects estimates. We propose the estimation of convergence in per-capita GDP across European regions by making use...

In this paper we use spatial dependence panel data models to analyse regional growth behaviour in Italy. Controlling for fixed-effects allows us to disentangle the effect of spatial dependence (or spatial interaction) from that of spatial heterogeneity and of omitted variables and, thus, to...

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)...

In any economic analysis, regions or municipalities should not be regarded as isolated spatial units, but rather as highly interrelated small open economies. These spatial interrelations must be considered also when the aim is to forecast economic variables. For example, policy makers need...

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...