Maria Tsiapa (p)

Nicola Pontarollo

Productivity is historically a core topic in the evolution of economies as it is related to sustained growth and competitiveness. The recent slowdown of productivity growth and the new state in which economies are trapped in an extended productivity stall raises questions stimulating researchers, analysts and policymakers to attempt to explain it. Moreover, the current period having experienced consecutive crises (financial crisis of 2008-09, covid-19 pandemic and the onset of war in the European area) has led to various shocks and economic disruptions.

This analysis aims to investigate the impact of socio-economic determinants on labour productivity of European regions during the period 2000-2020 incorporating factors from the theoretical well-grounded framework (Kaldor, Schumpeter, Baumol) which highlight the importance of innovation, institutions, skills and structural changes as they exert a growth-dampening effect. It will be based on a GMM spatial panel econometric model of which the structural change effect will be a component of the decomposition of productivity growth and the estimation of a shift-share analysis. The goal of the analysis is, firstly to detect the causes of the productivity stagnancy in different sub-periods as well as the degree of persistence of the productivity gap in certain regions. Secondly, to investigate whether a specific form of production (sectoral) transformation, as a corollary of an external shock, functions as a parameter of resilience and constitutes stage of reorientation and adaptation. Thirdly, to explore the existence of regional spillovers through various channels of diffusion or, on the contrary, the formation of spatial clusters in a declining path. The outcomes of the analysis will contribute to the understanding of productivity patterns over time and space, as well as to the provision of policy suggestions.

Silvia Cerisola (p), Roberta Capello

Maria Tsiapa

Reindustrialization was suggested by the political institutions in Europe as one of the strategies to counteract the productivity stagnation of European economies in the last 20-30 years. What is advocated by the European Institutions is a modern reindustrialization. This paper enters the debate by claiming that modernization, intended as process innovation taking place through digitalization of production activities, is fundamental for productivity gains especially when reindustrialization takes place in areas where a diversified variety of local sectors do not create a critical mass of know-how on which local firms can excel and compete. This is true for both high- or low-tech sectors. The paper presents empirical evidence on this claim, thanks to an original database on employment and value added disaggregated at regional (NUTS2) manufacturing sub-sectors level for the European members plus the UK. The results show that, while a reindustrialization focused on specialised sectors provides productivity gains irrespective of an explicit modernization strategy of the sectors, a reindustrialization in a variety of local sectors provides productivity increases only if sectors strongly modernize.

Nicola Pontarollo (p), Anna Rossi

Silvia Cerisola

This paper analyses the relationship between the urban spatial structure and the productivity growth of 7,272 Italian municipalities over the period 2012-2018. We focused our attention on medium-sized cities, and, specifically, on whether proximity to them has an impact on the productivity growth of neighbouring areas. To capture their influence, we used a spatial lag model, and we built the spatial weight matrix by considering municipalities within a certain distance from them as neighbours. Moreover, in order to evaluate whether agglomeration has an impact on growth, both a-spatial concentration measures and spatial autocorrelation measures were included in the model. The results indicate that proximity to medium-sized cities has a positive effect on productivity growth; and that the more monocentric an area, the lower its productivity growth.