Sandy Dall’erba, Regional Economics Applications Laboratory
University of Illinois at Urbana-Champaign, Urbana, USA, Marco Percoco, Instituto di Economia Politica, Milano, Italy, Gianfranco Piras, Faculty of Economics, Tor Vergata University of Rome, Italy, Rome, Italy
The Italian regional growth process revisited - Increasing returns and spatial dynamic setting (assigned to theme
Most of the recent contributions based on spatial econometrics which measure convergence among regions rely on a cross-sectional estimation of Solow’s (1956) model. However, this type of approach presents two drawbacks. The first one is the lack of consideration for increasing returns to scale, which are at the origin of endogenous growth and new economic geography models. The second concerns the incapacity of a cross-sectional approach to solve problems due to omitted variables and the complete regional homogeneity it imposes. In that purpose, we use Fingleton’s (2001) model which links manufacturing labor productivity growth to manufacturing output growth and technology gap and apply it to the 92 Italian provinces over 1970-2000. The novelty comes from estimation results which are presented according to a spatial panel data approach and a spatial cross-sectional approach, since both methodologies are complementary in a spatial dynamic setting.
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