Spatial modeling of economic phenomena requires the adoption of complex econometric tools, which allow us to deal with important methodological issues, such as spatial dependence, spatial unobserved heterogeneity and nonlinearities. In this paper we describe some recently developed econometric...

We propose a semi-parametric spatial auto-covariance specification of the growth model to examine the growth behaviour of European regions in the period 1988-2000. This specification simultaneously takes account of the problems of non-linearities and spatial dependence. We obtain two main...

Using data for the European regions at NUTS-2 level, we test the predictions of a microfounded Schumpeterian growth model with technological interdependence recently developed by Ertur and Koch (2011, EK11). Spatial interdependence is identified by means ofa semiparametric geoadditive spatial...

This paper addresses two important methodological issues in the analysis of industrial location: spatial dependence and nonlinearities. To this end, we estimate a semi-parametric spatial autoregressive negative binomial model using data on the number of inward greenfield FDI occurred over the...

Economic theory emphasizes that risk sharing makes it possible to exploit benefits from comparative advantages and economies of scale. Unlike previous studies we reject the assumption of parameter homogeneity across geographical units in measuring risk sharing. The estimated regional-specific...