Phoebe Koundouri, Konstantinos Dellis, Anna Triantafyllidou (p), Maria Chourdaki

Miquel-Angel Garcia-Lopez

Adapting to climate change and building regional resilience is one of the greatest challenges facing modern societies. Fostering green innovation and benefiting from cutting-edge environmental technologies is pivotal in this aspect. Nonetheless, different regions face unique difficulties and vulnerabilities, therefore requiring adaptation measures and tools tailored to local needs. Regional innovation strategies are most efficient when they harness local competitive advantages and skills, as epitomized by the EU Smart Specialization Strategy (S3). This paper examines how regional technological competence and knowledge can diversify the innovation portfolio of the Attica region in Greece, focusing on technologies associated with climate adaptation. This will, in turn, provide a roadmap for moving towards new technological domains which are (i) within the region’s reach based on embedded capacities and (ii) aligned with the region’s priorities to build environmental and socioeconomic resilience.
The main objective of the research is to map the technological advantages of Attica in relation to the climate change adaptation priorities identified in Attica's regional plan (RCAP - PESPKA). By analyzing patent data at the regional level from the OECD REGPAT database, we calculate the Revealed Technological Advantage (RTA) for the Attica region. We leverage the IPC/CPC classification system to earmark patent classes associated with climate adaptation technologies and calculate the relatedness with the areas of Attica’s technological specialization by analyzing co-occurrence patterns across technological fields. We then use the two sets of information to shape the knowledge space, in the form of a network, identifying the links and distances between current technological capabilities and technologies aligned with transformational adaptation. Finally, we prioritize technological diversification based on the combination of two criteria: (i) relation to Attica’s adaptation priorities and (ii) technological relatedness to current technological specialization. Our results assist in shaping the innovation agenda to meet resilience targets and shape the policy agenda through a parsimonious approach aiming at technological advances concomitant with local capabilities.
Regional economic diversification relies on enhancing economic complexity using technological relatedness, and serves as a key driver of regional development. In order to bridge the innovation gap in the green transition, the paper suggests concrete policy approaches, such as targeted funding for green startups, strengthening regional and national innovation systems, and the promotion of public-private partnerships to accelerate innovation. By utilizing regional patent data and analyzing technological classifications, the study provides useful tools for the formulation of integrated regional development and sustainability strategies.

Miquel-Angel Garcia-Lopez (p), Hugo Carpena Barranco

Nejla Ben Arfa

This paper investigates the impact of teleworking and e-commerce on air pollution, using the COVID-19 pandemic as a natural experiment. Our analysis combines mobility data, government imposed restrictions, and ground-level air pollution measurements to examine the concentration of various pollutants. Employing a high-dimensional model with time- and city-fixed effects, we estimate the daily and hourly effects of teleworking and e-commerce in major Spanish cities. The results indicate that during the pandemic, significant reductions in certain pollutants occurred on both daily and hourly timescales compared to non-pandemic periods. These reductions can be attributed to the increased adoption of teleworking and e-commerce, driven by mobility restrictions during the pandemic.

Nejla Ben Arfa (p), Giffona Justinia Hanitravelo

HwuiKwon Ahn

In 2020, metropolitan France had only 389,800 remaining agricultural farms, approximately 270,000 fewer than in 2000. This decline has disproportionately affected farms specializing in dairy and/or beef production compared to those focused on plant production. This study investigates the factors influencing the cessation of agricultural farms in metropolitan France, with a particular emphasis on the Pays de la Loire region—an area known for its agricultural diversity but also facing unique challenges. Understanding the determinants of farm survival requires a robust analytical framework based on original, high-quality longitudinal data.
To achieve this, we utilize unique datasets obtained through secure access to individual farm records from the French agricultural censuses of 2000, 2010, and 2020, complemented by data from the agricultural social security system (MSA). The integration of these data sources enables precise tracking of both farm cessations and farmer mobility over time. Unlike traditional cross-sectional analyses, this longitudinal approach provides a more accurate assessment of the factors influencing farm survival and structural changes in the agricultural sector. By leveraging this innovative, data-driven methodology, we aim to identify key economic, structural, and policy-related factors contributing to farm resilience, offering valuable insights for researchers and policymakers.
For this analysis, we employ the Cox regression model, which is particularly well-suited for examining time-to-event data while accounting for covariates that may influence the risk of farm cessation. The model’s semi-parametric nature allows for the estimation of hazard ratios, quantifying the relative risk associated with specific variables. Factors such as farm size, legal status, and modernization efforts are assessed for their impact on survival probabilities.
Farms in the Pays de la Loire region face a significantly higher risk of cessation compared to those in other regions. This elevated risk may result from region-specific challenges, including market saturation, environmental constraints, and policy frameworks that may disadvantage certain types of farming operations. Within the region, farm survival rates vary by department, with farms in Maine-et-Loire exhibiting a slightly lower risk, while those in Mayenne, Sarthe, and Vendée show minor variations in risk.
These findings highlight the need for region-specific interventions to enhance farm sustainability. Policymakers should consider implementing financial aid programs for at-risk farms, establishing regional advisory services focused on resilience strategies, and promoting market diversification initiatives to reduce dependency on volatile agricultural sectors.

Soojeong Kang, HwuiKwon Ahn (p), Yewon Choi, DongHwui Kim, Donghwan Ahn, Kwansoo Kim

Marco Modica

Hwuikwon Ahn, Soojeong Kang, Yewon Choi , Donghwan An, Kwansoo Kim

An increase in the magnitude and frequency of extreme weather events is one of the major effects of climate change. The variability of climate factors often causes immediate detriment to society. In particular, heavy rainfall events have intensified recently, resulting in an increase in costs related to economic damages, infrastructure failures, and losses of human life. While climate resilience-improving measures are widely recognized as essential adaptation strategies, there is not much empirical research done in empirically evaluating the effects of such policy measures in the context of resilience. In evaluating these effects, assessing the marginal effects of a relevant policy measure is useful in that it allows us to thoroughly investigate policy effects on the reduction of damage costs. In this study, we aim to develop an empirical model allowing the estimation of policy effects on damage costs. This would provide valuable information to policy makers who need to make decisions on the choice of policy measures across time and across region.
In this paper, we constructed a panel dataset integrating historical rainfall-induced disaster records, economic losses, and climate adaptation measures across region in South Korea. Using a structural equation approach, we estimated how both disaster vulnerability and adaptation capacity influence ex-ante and ex-post damages.
Our preliminary results demonstrate that regions with higher adaptation capacity experience significantly lower actual damages relative to expected losses, indicating the effectiveness of policies targeted to boost up resilience capacity. Moreover, policies related to ex-ante adaptation strategies (e.g., infrastructure investments, disaster preparedness programs) yield greater long-term economic benefits than ex-post recovery efforts. By quantifying the avoided losses through climate resilience, this study will provide robust empirical evidence to support targeted adaptation policies and optimized disaster risk management strategies.
This research advances climate adaptation literature by presenting an empirical modeling approach that integrates unobservable ex-ante damages and observable ex-post damages into estimable total damages when it comes to the effects of policy measures targeting to improve the resilience capacity of a certain region. Our findings are expected to highlight the importance of policy-driven resilience investments in reducing climate-induced economic vulnerabilities. Our framework provides valuable insights for policy makers and urban planners to design data-driven climate resilience strategies, ensuring more effective adaptation strategies against extreme weather events such as heavy rainfalls.

Marco Modica (p), Maria Giovanna Brandano, Lorenzo Biferale

Anna Triantafyllidou

With the ever increasing quantity and intensity of extreme natural phenomena, there is a growing need to ensure that communities in vulnerable areas are prepared for the effects of these natural disasters. In the context of disaster studies, research has placed growing interest on the role of a community’s social resources in relation to disaster resilience.
As the number of extreme natural events rapidly increases, it becomes increasingly important to better understand the processes that make communities more resilient. As it is well-documented by now that social cohesion and social capital are positively related to recovery rates, what remains to be better investigated is their durability across time, as well as the impact that exogenous disastrous events have on civic participation. In fact, there is by now well documented positive relation between social cohesion and recovery rates in the event of a natural disaster, but less is known about the durability of such social processes across time and even less about their resilience following disastrous events and external shocks. Although some recent studies have investigated the effect of natural disasters on pro-social behaviors, results remain limited and scattered, partly due to the difficulty of conducting causal studies with a pre/post-disaster design.

This paper aims to fill such gaps by exploring the extent to which natural disasters influence civic participation? The paper focuses on England as a case study and on six separate flooding events that hit different areas between 2007 and 2012. Through the analysis of the information collected by the Taking Part Survey (TPS), a continuous governmental survey on individual’s cultural and civic participation patterns, the paper adopts a geographic approach by transposing the variable of interest at the level of Local Authority District (LAD) and Unitary Authorities (UA). Focusing on six flooding events in England, the paper adopts a dynamic difference-in-differences (DiD) approach over a ten-year time span (2005-2015). Results show that civic participation is variables positively impacted after a natural disaster.