In this paper we provide a brief overview of some of the most recent empirical research on spatial econometric models and spatial data mining. Data mining in general is the search for hidden patterns that may exist in large databases. Spatial data mining is a process to discover interesting,...

This paper contributes to the recent literature in spatial econometrics that focuses on space-time data modeling implementing a multi-location time-series statistical framework to analyze a regional system. Therefore, taking as a point of departure the Global Vector Autoregression approach...

A new spatial decomposition of TFP growth into direct (own) and indirect (spillover) components is set out. We then apply the decomposition in the context of a spatial autoregressive production frontier analysis of 40 European countries over the period 1995-2008

Most studies that incorporate spatial effects use a very limited number of spatial variables in the growth model, e.g. growth spillovers or infrastructure impacts of neighbouring regions. This article innovates on previous work in spatial econometrics by differentiating among spatial...

This paper revisits the ubiquitous bi-proportional gravity model and investigates the reasons why different theoretical frameworks may lead to the same empirical formula. The generic gravity equation possesses scale invariance symmetries that constrain possible theoretical explanations based on...

A gravity model at the industry level is implemented to estimate the potential and industrial distribution of trade between former non-trading neighboring countries. The model incorporates a differentiated proxy for transportation costs at the industry level, rather than simply using geographic...

This paper provides a method for the analysis of the spatial and temporal diffusion of shocks in a dynamic system. We use changes in real house prices within the UK economy at the level of regions to illustrate its use. Adjustment to shocks involves both a region specific and a spatial effect....

(Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete...

Gravity or spatial interaction models have a long history in regional science and international trade. In the empirical trade literature, Poisson pseudo-maximum likelihood estimation methods (PPML) have become popular as a way of dealing with several econometric issues that arise when modeling...