Roberta Capello, Camilla Lenzi (p), Giobanni Perucca

Andre Carrascal-Incera

More than 30 years ago, Robert Solow provided the first evidence of the paradoxical low return of technological progress on productivity. Today, in an era of radical technological changes, characterized by disruptive socio-economic transformations in businesses and society, the puzzle is far from being solved. This paper offers a contribution in this direction. Stemming from the recognition that in European regions a productivity paradox still persists, this study systematically defines and empirically tests some of the sources that could explain the weak association between the adoption of new technologies and the growth of regional labour productivity. Our findings indicate that, in general, new technologies do have a positive impact on the productivity of the sectors of adoption. The propagation of this effect to the whole regional economy, however, is mitigated by reallocation effects towards less productive sectors.

Eveline van Leeuwen (p), Daniel Arribas, Yunyu Tian

Camilla Lenzi

Single settlements, being towns or cities, often have their own policies and strategies. However, they cannot and should not be seen as independent economies. Even the largest cities cannot ‘single-handed generate agglomeration benefits and endogenous growth’ (Partridge et al., 2010). In this study, we consider the relationship between urban-rural interaction and economic performance. Using an explicitly spatial modelling approach, we show that proximity to regions of different nature and degree of urbanity is associated with higher growth rates of GDP, employment, and population. We do this by comparing the effect of different regional neighbouring configurations on the performance of a given area. To gain further insight under which spatial circumstances growth takes place, we also develop bespoke indicators to characterize the landscape at finer spatial resolution than the region. Unlike most of the literature in the field, we take a pan-European (EU27) approach, which allows us to compare different countries and development stages, obtaining a more complete picture that summarizes a large and important part of the World. Our results show that, when only looking at population growth, spread effects from urban to rural regions are significant, but we also find population effects from rural to urban areas. In addition, we find positive effects of having rural neighbours on GDP and employment growth in both urban and intermediate regions.

Davide Fiaschi (p), Angela Parenti, Cristiano Ricci

Eveline van Leeuwen

We propose a spatial model of growth which encompasses amenities, local factor accumulation, spatial spillovers, and factors and technological flows among locations driven by differential factors returns in an explicit geographical space. We then show how the model can be used to investigate the actual geography of income distribution dynamics. Finally, we estimate the model on the income dynamics of Italian municipalities over the period 2008-2019. We find evidence of conditional convergence, but also of the presence of i) spatial agglomeration, which we trace back to positive spatial spillovers; and ii) tendency of income to spread toward poorer locations, which we trace back to the reallocation of factors toward more productive locations.

Andre Carrascal-Incera (p), Luis Orea

Davide Fiaschi

We examine in this paper the economic and welfare effects of the COVID-19 pandemic for a set of European countries, based on a (frontier) production model with upstream-downstream sectoral linkages. We embed the theoretical framework developed by Caliendo et al (2017) into this model to control for productivity effects caused by the international competition for intermediate inputs in a globalized world. The proposed model provides an analytical framework that can simulate a large variety of cascading effects caused by the public health measures implemented in each country and the changes in preferences aiming to avoid infection. Deriving overall impact estimates involves modelling immediate (first-order) supply and demand-side shocks, as well as second-order effects, such as the decline in aggregate consumption due to lower income or the additional reductions in supply as potential shortages propagate through supply chains.