Economic growth in Italian NUTS 3 provinces

This paper analyzes the conditional $$\beta $$ β -convergence hypothesis for NUTS 3 Italian provinces. A methodology for the simultaneous treatment of spatial dependence and spatial heterogeneity is developed. Spatial dependence is introduced in the economic model by assuming a spatial Durbin model specification. The absence of data experienced by some economic variables at the NUTS 3 level is addressed through a modified version of the Bayesian interpolation method introduced by Palma and Benedetti (J Geogr Syst 5:199–220, 1998 ). Spatial heterogeneity is taken into account by identifying convergence clubs. For this purpose, we use the modified simulated annealing algorithm introduced by Postiglione et al. (Comput Econ 42:151–174, 2013 ). The methodology is compared with the heteroscedastic approach proposed by Kelejian and Prucha (J Econom 157:53–67, 2010 ). Copyright Springer-Verlag Berlin Heidelberg 2014