Spatial effects are endemic in models based on spatially referenced data. The increased awareness of the relevance of spatial interactions, spatial externalities and networking effects among actors, evoked the area of spatial econometrics. Spatial econometrics focuses on the specification and...

We design a conceptual framework for linking two approaches: the literature on absorptive capacity and the literature on spatial knowledge spillovers. Regions produce new knowledge, but only part of it is efficiently adopted in the economy; the share of efficiently adopted technology depends on...

An important subset of the literature on agglomeration externalities hypothesizes thatintrasectoral and intersectoral relations are endogenously determined in models of localand regional economic growth. Remarkably, structural adjustment models describing thespatio-temporal dynamics of...

In this paper we employ techniques developed in spatial econometrics to analyse spatial patterns of technology diffusion, to detect clusters and to estimate theoretical models that incorporate space explicitly. These techniques correct for misspecifications resulting from the omission of spatial...

Finding proper policy instruments to promote productivity growth features prominently on the Lisbon agenda and is central in many national as well as European policy debates. In view of the increased mobility of high-skilled workers in Europe, ongoing globalization and increased interregional...

In many microeconometric models we use distances. For instance, in modelling the individual behavior in labor economics or in health studies, the distance from a relevant point of interest (such as a hospital or a workplace) is often used as a predictor in a regression framework. However, in...

Hospital emergency departments are often overused by patients that do not really need urgent care. These admissions are one of the major factors contributing to hospital costs, which should not be allowed to compromise the response and effectiveness of the National Health Services (SNS). The aim...

The integrated nested Laplace approximation (INLA) for Bayesian inference is an efficient approach to estimate the posterior marginal distributions of the parameters and latent effects of Bayesian hierarchical models that can be expressed as latent Gaussian Markov random fields (GMRF). The...

We consider the problem of testing for a structural break in the spatial lag parameter in a panel model (spatial autoregressive). We propose a likelihood ratio test of the null hypothesis of no break against the alternative hypothesis of a single break. The limiting distribution of the test is...