Javier Barbero

The public sector and convergence with spatial interdependence: empirical evidence from Spain

ABSTRACT We propose a framework to analyse convergence between regions, incorporating the public sector and technological knowledge spillovers in the context of a Neoclassical Growth Model. Second, we apply novel estimation methods pertaining to the spatial econometrics literature introducing a spatial Durbin panel data model based on instrumental variables and maximum-likelihood estimation. Our model makes it possible to analyse, in terms of convergence, the results obtained in Spanish regions with the policies implemented during the period 1980–2011. The results support the idea that education and fiscal policies have a positive effect on regional development and cohesion. Therefore, we can conclude that it is possible to obtain better results for regional convergence with higher rates of public investment in education and tax revenues. We also obtain interesting results that confirm the existence of spillover effects in economic growth and public policies, identifying their magnitude and significance.

The effect of broadband on European Union trade: A regional spatial approach

The positive effect of information and communication technologies (ICT) on trade between countries has been widely studied in the literature, but how ICT impacts regional trade is limited due to the lack of regional trade data. In this paper, we test whether broadband, as a proxy for ICT, increases bilateral trade at the regional level in Europe. We use a novel regional trade database of European Union regions and estimate an origin–destination flow gravity model for 2007 and 2010, accounting for spatial dependence among trade flows. Our results indicate that broadband is positive and significant in explaining trade patterns between European regions during both time periods.

Environmental Productivity Change in World Air Emissions: A new Malmquist-Luenberger Index Approach

Over the last twenty years an accelerating number of studies have relied on the standard definition of the Malmquist-Luenberger index proposed by Chung et al. (1997) [J. Environ. Manage., 51 229-240], to assess environmental sensitive productivity change. While recent contributions have shown that it suffers from relevant drawbacks related to inconsistencies and infeasibilities, no one has studied systematically the performance of the original model, and to what extent the existing results are unreliable. This paper introduces the optimization techniques that allow implementing the first model solving these problems, and using a country level database including air pollutants, systematically compares the results obtained with both approaches. We discuss the relative number, magnitude and significance of the disparities that researchers should expect if resorting to the original model. Results show that inconsistencies and infeasibilities in the original model are increasing in the number of undesirable outputs included, reaching remarkable values that seriously question the reliability of results, and compromise any policy recommendation based on them.