This paper suggests an empirical framework for analysing income distribution dynamics and cross-region convergence in the European Union of 27 member states, 1995-2003. The framework lies in the research tradition that allows the state income space to be continuous, puts emphasis on both shape...

Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such...

Regions and industries are not isolated islands; so, when evaluating productivity growth, regional and sectoral growth paths should not be expected to generate independently. Moreover, accounting for spatial interactions via econometric models has become normal practice; but modelling...

Econometric analysis of convergence processes across countries or regions usually refers to a transition period between an arbitrary chosen starting year and a fictitious steady state. Panel unit root tests and panel cointegration techniques have proved to belong to powerful econometric tools if...

Since the early 1990s, there has been a renaissance in the study of regional growth, spurred by new models, methods, and data. We survey a range of modeling traditions, and some formal approaches to the hard problem of regional economics; namely, the joint consideration of agglomeration and...

Chile is characterized as being a country with an extreme concentration of the economic activity around Santiago. In spite of this, and in contrast to what is found in many industrialized countries, income levels per inhabitant in the capital are below the country average and far from the levels...

The present book is concerned with spatial interaction modelling. In particular, it aims to illustrate, through a collection of methodological and empirical studies, how estimation approaches in this field recently developed, by including the tools typical of spatial statistics and spatial...

Bootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms...