Suchergebnisse

The European Emission Trading System (EU ETS) is commonly regarded as the key pillar of the European climate policy and as the main unifying tool to create a unique carbon price all over Europe. The UK has always played a crucial role in the EU ETS, being one of the most active national registry and a crucial hub for the exchange of allowances in the market. Brexit, therefore, could deeply modify the number and directions of such exchanges as well as the centrality of the other countries in this system. To investigate these issues, the present paper exploits network analysis tools to compare the structure of the EU ETS market in its first two phases with and without the UK, investigating a few different scenarios that might emerge from a possible reallocation of the transactions that have involved UK partners. We find that without the UK the EU ETS network would become in general much more homogeneous, though results may change focusing on the type of accounts involved in the transactions. ; Simone Borghesi received funding from the University of Siena (2017-2019 Research Grant) and by the Italian Ministry of Education (PRIN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Data Availability: The data underlying the results presented in the study are available from the European Transaction Log, URL: http://ec.europa.eu/environment/ets/transaction.do;EUROPA_JSESSIONID=2ftK1xBz5n1BQ3AYKj_nZtcOdTm8NlFWJPCFpAN92yYt61TtXe1t!1363888161.

Published online in September 2018 ; In this work, we investigate which countries have been more central during Phases I and II of the European Emission Trading Scheme (EU ETS) with respect to the different types of accounts operating in the system. We borrow a set of centrality measures from Network Theory's tools to describe how the structure of the system has evolved over time and to identify which countries have been in the core or in the periphery of the network. Performing partitions on the different types of accounts and transactions characterizing the EU ETS, we investigate whether intermediaries have affected the overall structure of the system. From the analysis of the European Union Transaction Log data over the period 2005–2012, we find that some national registries (France, Denmark, Germany, United Kingdom, The Netherlands) were much more central than others in the network. Empirical evidence, moreover, shows that some account holders strategically opened additional accounts in the more central registries, thus reinforcing their centrality in the network. Finally, it turns out that Person Holding Accounts (PHAs) have played a prominent role in the transaction of permits, heavily influencing the configuration of the system. This motivates further research on the impact of non-regulated entities in the EU ETS design.

In this work, we investigate which countries have been more central during Phases I and II of the European Emission Trading Scheme (EU ETS) with respect to the different types of accounts operating in the system. We borrow a set of centrality measures from Network Theory's tools to describe how the structure of the system has evolved over time and to identify which countries have been in the core or in the periphery of the network. In doing this, we investigate by means of extensive partitions on the different types of accounts and transactions characterizing the EU ETS whether the role of intermediaries (approximated by Person Holding Accounts - PHAs) has affected the overall structure of the system. Preliminary findings over the period 2005-2012 suggest that PHAs have played a prominent role in the transaction of permits, heavily influencing the configuration of the system. This motivates further research on the impact of non-regulated entities in the EU ETS design.

To reduce the spread and the effect of the COVID-19 global pandemic, non-pharmaceutical interventions have been adopted on multiple occasions by governments. In particular lockdown policies, i.e., generalized mobility restrictions, have been employed to fight the first wave of the pandemic. We analyze data reflecting mobility levels over time in Italy before, during and after the national lockdown, in order to assess some direct and indirect effects. By applying methodologies based on percolation and network science approaches, we find that the typical network characteristics, while very revealing, do not tell the whole story. In particular, the Italian mobility network during lockdown has been damaged much more than node- and edge-level metrics indicate. Additionally, many of the main Provinces of Italy are affected by the lockdown in a surprisingly similar fashion, despite their geographical and economic dissimilarity. Based on our findings we offer an approach to estimate unavailable high-resolution economic dimensions, such as real time Province-level GDP, based on easily measurable mobility information.

In response to the coronavirus disease 2019 (COVID-19) pandemic, several national governments have applied lockdown restrictions to reduce the infection rate. Here we perform a massive analysis on near-real-time Italian mobility data provided by Facebook to investigate how lockdown strategies affect economic conditions of individuals and local governments. We model the change in mobility as an exogenous shock similar to a natural disaster. We identify two ways through which mobility restrictions affect Italian citizens. First, we find that the impact of lockdown is stronger in municipalities with higher fiscal capacity. Second, we find evidence of a segregation effect, since mobility contraction is stronger in municipalities in which inequality is higher and for those where individuals have lower income per capita. Our results highlight both the social costs of lockdown and a challenge of unprecedented intensity: On the one hand, the crisis is inducing a sharp reduction of fiscal revenues for both national and local governments; on the other hand, a significant fiscal effort is needed to sustain the most fragile individuals and to mitigate the increase in poverty and inequality induced by the lockdown.