This article presents the results of a laboratory experiment and an online multi-country experiment testing the effect of motor vehicle eco-labels on consumers. The laboratory study featured a discrete choice task and questions on comprehension, while the ten countries online experiment included measures of willingness to pay and comprehension. Labels focusing on fuel economy or running costs are better understood, and influence choice about money-related eco-friendly behaviour. We suggest that this effect comes through mental accounting of fuel economy. In the absence of a cost saving frame, we do not find a similar effect of information on CO 2 emissions and eco-friendliness. Labels do not perform as well as promotional materials. By virtue of being embedded into a setting designed to capture the attention, the latter are more effective. We found also that large and expensive cars tend to be undervalued once fuel economy is highlighted.

According to NEG literature, spatial concentration of industrial activities increases growth at the regional and aggregate level without generating regional growth differentials. This view is not supported by the data. We extend the canonical model with an additional sector producing non-tradable goods which benefits from localized knowledge spillovers coming from the R&D performing industrial sector. This view, motivated by the evidence, generates both an anti-growth and a pro-growth effect of agglomeration for both the deindustrializing and the industrializing regions and leads to two novel results: 1) when agglomeration takes place, growth is lower in the periphery; 2) agglomeration may have a negative effect on the growth rate of real income, both at the regional and at the aggregate level. Our conclusions have relevant policy implications: contrary to the standard view, current EU and US regional policies favouring industrial dispersion might be welfare-improving both at the regional and the aggregate level and may reduce regional income disparities

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This paper gives a contribution to the debate on regional convergence by comparing the long run prediction of convergence clubs introduced by Quah (1996 and 1997) with the actual observed dynamics of the Italian regions during the period 1970-2004. To this end we analyze the evolution of per capita income levels for the Italian regions using a non-traditional (non-parametric) statistical model. In addition we segment the set of economies by the mean of hierarchical clustering methodologies and compare the trajectories of the regions by introducing different notions of distance. The general conclusion is that the average distance identifies a clear division between a high performance club consisting of regions from the Center North, and a low performance club composed by regions from the South and islands. The presence of a cluster composed by Center North regions is substantially confirmed by the distance correlation analysis, suggesting an homogeneous response to external shocks. By contrast Southern regions display the same dynamical evolution but difference in co-movements. Our analysis provides hints about the fundamentals that link the regions in their process of divergence. In fact the performance clubs pattern we discovered reflects the distribution of economic activities as well as the structural attributes of the regional economies

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