Federico Fantechi

This article investigates the labour-market consequences of the circular economy (CE) transition across Euro Area regions. We build a NUTS‑2 × year panel (2012–2022) that aggregates firm‑level data with granular industry detail and exploits cross‑regional variation in the EU Cohesion Policy disbursements targeted to CE‑related projects in the last programming period as a measure of local transition intensity. Linking these disbursements to employment dynamics, we estimate models with region and year fixed effects and rich details for sectoral composition to classify different types of regional labour markets and assess whether CE investment translates into net job creation or reallocation. We document systematic heterogeneity: In some regions, there is a net growth in jobs in repair, reuse, remanufacturing, recycling, and secondary raw materials, while others face larger losses in other resource‑intensive industries. Net of the transition’s aggregate benefits, our estimates imply a spatial mismatch between where new CE jobs emerge and where incumbent workers are most exposed to displacement. We conclude that in the coming mid-course adjustments, policymakers should focus on responding with place‑sensitive targeting and complementary measures; hence, investments align better with local assets and needs. In this sense, the study provides actionable evidence for implementing changes to the EU’s circular‑transition agenda in ways that maximize benefits and mitigate losses, supporting a just transition and equitable labour‑market outcomes across diverse regional economies.

The manuscript proposed is well written, with a clear structure, well connecting the aim to the results of the model and their interpretation. The concluding paragraph summarizes well the results of the different forecasted scenarios and connects the...

The concept of competitiveness is today a central element for regional development, European cohesion policies and smart specialisation strategies. Despite being born for firm-level analyses, competitiveness is indeed commonly used at the territorial level, mainly at the regional or urban scale, normally measured with different composite structural indicators. However, since territorial competitiveness is unevenly distributed in space, territorial units smaller than a full NUTS-2 region might be differently competitive and hence suited to implement differentiated cohesion policies and smart specialisation strategies. To test the hypothesis that these firm-level indicators can characterize the intraregional differences in aggregate performance, the paper sets up a meta-analysis framework between these indicators and structural indicators (employment growth and specialisation index) measured at the NUTS-3 level. For the meta-analysis at this novel intraregional level, the paper exploits the Lombardy region as a case study. Lombardy is well suited for the aims of this paper, being a large and competitive European region, whose territory—as well as its labor market—is highly differentiated, from peripheral and mountainous areas to many medium and small cities, second-tier large cities and a large metropolitan area—the city of Milan. All these territories are characterized by different economic and social vocations, but all share the same regional administration. The results of the meta-analysis show that firm-level indicators correlate with the aggregate performance of regions and that the structural measures selected can characterize different territories in different conditions. Hence, the competitiveness of firms seems to translate into aggregate territorial performance at small spatial scales. This implies that territorial specificities are also relevant inside regions and should be considered in designing regional policy interventions, such as those of the Smart Specialisation Strategy (S3).

Italy has been affected by many different shocks in recent years, from the Great Recession to many natural hazards. While many studies have analysed the effects of natural and socio-economic shocks on urbanized and developed areas, very few have focused on locked-in and less developed regions. In this study we focus on the pernicious effects of three earthquakes that have affected the labour markets of rural and inner municipalities of Central Italy during the last 20 years. We adopt a machine-learning technique that allows us to provide a scenario five to seven years after the earthquake for 133 municipalities affected by the Central Italy earthquake in 2016.

This paper analyses regional competitiveness at the subregional level through a novel methodological approach that adopts a matching design. By comparing the performance of similar firms in different parts of the region, it is possible to detect whether different places provide different competitive territorial assets. Using data for Lombardy, a large and competitive European region, the analysis shows that the different territories of the region are differently competitive in different industries, even when they are similar in terms of total GDP per capita or specialization. The paper also confirms that measuring competitiveness on different indicators (Labour Productivity, TFP, Profitability) can provide different results, and this especially happens when comparing static and dynamic indicators. The methodology presented here is especially relevant to the design of regional policies, that are mostly deployed at the NUTS-2 level but would benefit from accounting for the presence of strongly dis-homogeneous territories inside the same region.