Giulio Breglia (p), Giulia Valeria Sonzogno

Declan Jordan

The green transition is a defining challenge for economic and environmental policies, yet its spatial distribution remains highly uneven, raising concerns
about territorial equity. While sustainability policies aim to mitigate climate change and foster resilience, they interact with existing regional disparities, potentially reinforcing inequalities (Iammarino et al., 2019). The European Union (EU), through Next Generation EU (NGEU), integrates climate goals into post-pandemic recovery strategies, allocating 37% of the Recovery and Resilience Facility (RRF) to green projects (Commission, 2019). However, how these investments translate into territorial development remains largely unexplored. Using Italy’s National Recovery and Resilience Plan (NRRP) as a case study, we classify over 92,000 green projects through a GPT-supervised clustering
approach and analyze their socio-economic determinants using a multinomial logit model. Our findings reveal significant spatial disparities: metropolitan regions attract high-value investments, while peripheral and less-developed areas focus on low-value sustainability measures. These results underscore the need for place-based strategies to ensure a just transition. By integrating machine learning with spatial analysis, this study advances the understanding of sustainability policies and provides a methodological framework for assessing green transition initiatives.

Declan Jordan (p), Frank Crowley, Justin Doran

Vassilis Monastiriotis

The emergence of mission-orientated industrial policy has seen the development of broad stakeholder-based approaches to grand societal challenges.
Mission-orientated policies require resilient and dynamic public agencies, the mobilisation of multiple industries and stakeholders, and be based on research and innovation and technological readiness (Mazzucato and Kattel, 2023). Due to these requirements, there may be differences in the ability of some cities and regions to participate in mission-orientated policies and to benefit from the outcomes of such policies. Industrial policy that relies on a mission orientation may reinforce regional inequalities, where those regions that lag in relation to research and development, technologically advanced sectors, and political power are excluded from mission-oriented policies.

While mission-oriented policies may mobilise national and supranational resources to address global, societal challenges, the spatial dimension is intrinsic to these policy goals. The principle of subsidiarity, the spatial variation in the scale and complexion of the issue, and the local knowledge of local context are critical to success.

This paper assesses whether left behind places are less likely to engage in mission-oriented policies and investigates the underlying reasons as to why this might be the case.

To do so, this paper constructs a novel dataset comprising information on EU cities’ participation in the EU Mission for Climate Neutral and Smart Cities (EU Missions, 2024). Of 705 EU cities included in the Eurostat dataset, 196 applied for participation in the mission and 88 were selected for inclusion. This is combined with detailed regional information taken from Eurostat on regional economic and demographic factors as well as established definitions of left behind places (Velthuis et al, 2024).

Using this dataset, we apply a series of probit estimations that analyse first whether cities located in left behind regions are less likely to apply for participation and second whether these cities are less likely to be selected as participating cities. The analysis controls for other factors that are associated with city performance to identify the degree to which different classifications of left behind regions (e.g. post-industrial decline, long term lagging etc.) affect cities’ engagement in EU Missions to address climate change. We provide a nuanced understanding of the potential effect of ‘left-behindness’ on participation in mission-oriented policies, through the introduction of interaction analysis which allows us to identify the degree to which variations in regional factors, such as quality of institutions, technology, and education may mitigate participation in EU Missions.

Vassilis Monastiriotis (p)

Giulio Breglia

Over the last 20 years a large literature has developed evaluating the effects of Cohesion Policy on regional growth and convergence. While the literature has told us a lot about whether and how Cohesion Funds work (Mohl and Hagen, 2010; Becker et al, 2012; Fratesi and Wishlade, 2017; Di Cataldo and Monastiriotis, 2018), attention on _how_ regions grow - with or without Cohesion Funds - has been at best limited. In this paper we pursue a comparative examination of the long-term regional growth processes found across the European economic space (i.e., examining the drivers of regional growth) and examine how these vary across groups of regions with different types (or ‘doses’) of 'treatment' in terms of Cohesion Policy. To do so, we borrow methodologically from the wage-decomposition techniques typically utilised in the applied labour economics literature. We specify an extended growth equation which we estimate separately for different groups of regions and then implement a detailed Blinder-Oaxaca decomposition in order to identify the contribution of two different components to each group’s growth performance: an ‘endowment’ component, which accounts for differences in performance due to differences in endowments (e.g., regional level of education or investment) and a ‘productivities’ component, which accounts for differences in performance that are due to the productivity of each of the different endowments considered. This analysis helps us unveil the fundamental differences in the growth process between Cohesion Policy’s beneficiary and non-beneficiary regions. Drawing on this, we engage in a critical discussion of the ‘suitability’ of EU Cohesion Policy to support balanced growth across the EU, within the context of the wider EU industrial policy objectives (digital and green transitions, economic sovereignty, strategic autonomy).