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...

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...

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...

This paper reviews the empirical literature on growth and convergence that has addressed the importance of spatial factors. An important distinction in this literature is the one between absolute and relative location. The literature on absolute location predominantly uses non-spatial...

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...

Outcomes of the shallow lake interest conflict are presented in a number of different contexts: quasi-static and dynamic social planning, and quasi-static one-shot and repeated non-cooperative play. As the underlying dynamics are non-convex, the analysis uses geometrical-numerical methods: the...

This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the...

Important choices for efficient and accurate evaluation of marginal likelihoods by means of Monte Carlo simulation methods are studied for the case of highly non-elliptical posterior distributions. We focus on the situation where one makes use of importance sampling or the independence chain...

An efficient and accurate approach is proposed for forecasting Value at Risk [VaR] and Expected Shortfall [ES] measures in a Bayesian framework. This consists of a new adaptive importance sampling method for Quantile Estimation via Rapid Mixture of <I>t</I> approximations [QERMit]. As a first step the...</i>

Experts can rely on statistical model forecasts when creating their own forecasts. Usually it is not known what experts actually do. In this paper we focus on three questions, which we try to answer given the availability of expert forecasts and model forecasts. First, is the expert forecast...