• Energy Research

Transition risk disclosure facilitates investors' understanding of the potential company-level risks associated with a low-carbon transition. Among the others, stricter regulations could undermine companies' financial performances, affecting operations costs and revenues and their impact being proportional to the business carbon intensity. Transition risk disclosure takes two forms. One is a textual description of transition risk in compulsory and voluntary non-financial disclosure. The other is the disclosure of carbon emissions and intensity, which is implicitly associated with transition risk exposure. We empirically assess the impact of the two transition risk measures on shareholder returns to test the “carbon premium” hypothesis. We consider shareholder return as the sum of capital gain and dividend paid and analyse the impact of transition risk on both. Evidence supports the “carbon premium” hypothesis but suggests such a premium is transferred to shareholders primarily via dividend payouts. One possible explanation consistent with this evidence is that boards in highly polluting companies use dividends to compensate investors for the relatively lower capital gain, dissuading them from divesting due to low returns, stigmatisation effects and regulatory risks.

We propose an empirical approach to estimate the impact of climate transition risk on corporate revenues that specifically accounts for reputational risk. We employ the information on disclosed Scope 3 emissions to proxy companies’ carbon footprint along the value chain. A threshold regression is employed to identify the emission level above which reputational risk impacts revenues, and we link this impact to a climate policy stringency indicator. We estimate the threshold regression on a sample of companies within the European Union (EU), and find the threshold at around the 70th percentile of the Scope 3 emissions distribution. We find that companies with Scope 3 emissions beyond the threshold experienced substantially lower revenue growth as climate policies have become more stringent, compared to other companies.

In representing urban sprawl, the decline in population and employment density from the city centre to the periphery has been identified as the main character associated with the spatial expansion of built-up areas. Urban spatial discontinuity, which occurs when the urban fabric includes built-up or green areas and a relevant share of vacant spaces, has gained recent attention. In this paper, we use Global Human Settlement Layer data to track urbanisation dynamics in European Functional Urban Areas (FUAs) from 1990 to 2014. We represent urban sprawl as the spatial expansion of FUAs associated with either or both declining population density and increasing built-up area discontinuity. We also consider the association with the demographic trends that have been described as the primary driver of urban spatial expansion. We use configural frequency analysis to explore the local association between the different characters of sprawl. We found evidence that urban sprawl effectively took differentiated forms across European FUAs. Even though FUAs have generally become less dense and more disperse, our results show that the extent of these phenomena appears to be more contained in recent years than in previous decades. Both elements of sprawl characterise FUAs with a shrinking population, confirming the decoupling of urban development policies and demographic trends in cities. The results call for better controlled urban development, favouring compact cities and subjecting land-use changes to a perspective of urban population growth.

This paper empirically explores the extent to which European cities are on track to sustainable development by examining the environmental performance of a large sample of cities observed during the last two decades. The paper builds on the Environmental Kuznets Curve framework and leverages satellite data to build a set of environmental indicators as varied and as granular as possible. Evidence suggests that European cities are, on average, on track to sustainable development, meaning that the contribution of their economic growth to environmental degradation is already negative or close to becoming so. The paper also examines Transnational City Networks as accelerators of environmental transition. The results suggest that cities participating in such networks anticipate the transition with respect to their peers.

This work projects future residential electricity demand in Italy at the local (1 km grid) level based on population, land use, socio-economic and climate scenarios for the year 2050. A two-step approach is employed. In the first step, a grid-level model is estimated to explain land use as a function of socio-economic and demographic variables. In the second step, a provincial-level model explaining residential electricity intensity (gigawatt hours [GWh] per kilometre of residential land) as a function of socio-economic and climatic information is estimated. The estimates of the two models are then combined to project downscaled residential electricity consumption. The evidence suggests not only that the residential electricity demand will increase in the future but, most importantly, that its spatial distribution and dispersion will change in the next decades mostly due to changes in population density. Policy implications are discussed in relation to efficiency measures and the design of green energy supply from local production plants to facilitate matching demand with supply.

AbstractThis paper examines the dynamic of income distribution in European regions and attempts to relate movements within this distribution to regional structural characteristics and to the impact of cohesion policy (CP). There is evidence that CP supports advanced economic development in lagging and peripheral regions, hence contributing to the ‘convergence objective’. The effectiveness of CP, however, depends on the manner in which funds are managed by single regions: the likelihood of progressing in the income distribution is associated, in fact, to the balance between investments in infrastructure and the productive environment, favouring the former. Evidence presented in this paper also relates regional economic performance to the educational level and innovation in regions, providing useful insights for the current debate about reshaping EU cohesion policy toward a more place‐based approach.

We present a tractable methodology to estimate climate change costs at a 1 × 1 km grid resolution. Climate change costs are obtained as projected gross domestic product (GDP) changes, under different global shared socio-economic pathway–representative concentration pathway (SSP-RCP) scenarios, from a regional (multiple European NUTS levels) version of the Intertemporal Computable Equilibrium System (ICES) model. Local costs are obtained by downscaling projected GDP according to urbanized area estimated by a grid-level model that accounts for fixed effects, such as population and location, and spatially clustered random effects at multiple hierarchical administrative levels. We produce a grid-level dataset of climate change economic impacts under different scenarios that can be used to compare the cost – in terms of GDP loss – of no adaptation and the benefits of investing in local adaptation.