The Future of the Eurozone: Towards a European Benchmark*

The European sovereign debt crisis has demonstrated the need for a rethinking of the European Integration Project. The strong variety between member countries prevented the Eurozone to become a fiscal and political union and the asymmetric architecture of the European Monetary Union (EMU) revealed different weaknesses. The outbreak of the Covid-19 emergency may represent a turning point for the EU and makes even more evident that the future of the Eurozone will depend also on the ability of member countries to make their institutional frameworks coexist. Helping member countries to achieve sustainable and stable outcomes, although in idiosyncratic ways, is the task of the European benchmark. It is a framework, inspired by European treaties, that aims to identify inefficiencies in terms of market, state and social failures and negative externalities inside economic, social, and political institutions. This benchmark represents a new tool for a correct evaluation of the economic, social, and political performance of the European member countries.   Note: * A non peer-reviewed version of this article was published as TIGER Working Paper Series No. 143, Warsaw, February 2021).   Cite this paper: Casagrande, Sara; & Dallago, Bruno (2022). "The Future of the Eurozone: Towards a European Benchmark" Journal of World Economy: Transformations & Transitions (JOWETT) 1(03):14. DOI: https://doi.org/10.52459/jowett1314012

The seasonality structure of demand in the portuguese hotel industry before the COVID-19 pandemic

The purpose of this paper is to study the monthly seasonality structure of demand in the hotel industry in continental Portugal before the outbreak of the COVID-19 pandemic in 2020. The tourism sector accounts for more than 10% of Portugal’s GDP, as well as being a key factor for regional development and employment. Understanding the seasonality structure of the hotel sector provides useful insight about business viability and aids operational decisions, namely concerning the post-pandemic recovery. Therefore, we analyze time-series data collected from Statistics Portugal, concerning net bed occupancy rates for continental Portugal, as well as according to region and hotel category, for the pre-pandemic period between 2014 and 2019. This allows us to identify the seasonal peaks according to region and compare the differences in demand for hotels according to hotel category. We also analyze the relationship between the seasonality coefficients and the average income per night (room rate)

A stigmergy-based analysis of city hotspots to discover trends and anomalies in urban transportation usage

A key aspect of a sustainable urban transportation system is the effectiveness of transportation policies. To be effective, a policy has to consider a broad range of elements, such as pollution emission, traffic flow, and human mobility. Due to the complexity and variability of these elements in the urban area, to produce effective policies remains a very challenging task. With the introduction of the smart city paradigm, a widely available amount of data can be generated in the urban spaces. Such data can be a fundamental source of knowledge to improve policies because they can reflect the sustainability issues underlying the city. In this context, we propose an approach to exploit urban positioning data based on stigmergy, a bio-inspired mechanism providing scalar and temporal aggregation of samples. By employing stigmergy, samples in proximity with each other are aggregated into a functional structure called trail. The trail summarizes relevant dynamics in data and allows matching them, providing a measure of their similarity. Moreover, this mechanism can be specialized to unfold specific dynamics. Specifically, we identify high-density urban areas (i.e hotspots), analyze their activity over time, and unfold anomalies. Moreover, by matching activity patterns, a continuous measure of the dissimilarity with respect to the typical activity pattern is provided. This measure can be used by policy makers to evaluate the effect of policies and change them dynamically. As a case study, we analyze taxi trip data gathered in Manhattan from 2013 to 2015.Comment: Preprin

Climate transition risk and bank lending

We investigate whether and how banks in the global syndicated loan market adjusted the pricing and supply of credit to account for higher climate transition risk (CTR) in the years following the 2015 Paris Agreement. We measure CTR by considering the pollution levels of borrowers and the engagement of countries where borrowers are headquartered in addressing climate change issues. The evidence is mixed and points to non-linear relations between lending variables and CO2 emissions. Policy events such as the Paris Agreement and government environmental awareness are significant climate risk drivers that, when combined, may amplify banks’ perception of CTR

Unique health care utilization patterns in a homeless population in Ghent

Background: Existing studies concerning the health care use of homeless people describe higher utilisation rates for hospital-based care and emergency care, and lower rates for primary care by homeless people compared to the general population. Homeless people are importantly hindered and/or steered in their health care use by barriers directly related to the organisation of care. Our goal is to describe the accessibility of primary health care services, secondary care and emergency care for homeless people living in an area with a universal primary health care system and active guidance towards this unique system. Methods: Observational, cross-sectional study design. Data from the Belgian National health survey were merged with comparable data collected by means of a face-to-face interview from homeless people in Ghent. 122 homeless people who made use of homeless centres and shelters in Ghent were interviewed using a reduced version of the Belgian National Health survey over a period of 5 months. 2-dimensional crosstabs were built in order to study the bivariate relationship between health care use (primary health care, secondary and emergency care) and being homeless. To determine the independent association, a logistic model was constructed adjusting for age and sex. Results and Discussion: Homeless people have a higher likelihood to consult a GP than the non-homeless people in Ghent, even after adjusting for age and sex. The same trend is demonstrated for secondary and emergency care. Conclusions: Homeless people in Ghent do find the way to primary health care and make use of it. It seems that the universal primary health care system in Ghent with an active guidance by social workers contributes to easier GP access

Stigmergy-based modeling to discover urban activity patterns from positioning data

Positioning data offer a remarkable source of information to analyze crowds urban dynamics. However, discovering urban activity patterns from the emergent behavior of crowds involves complex system modeling. An alternative approach is to adopt computational techniques belonging to the emergent paradigm, which enables self-organization of data and allows adaptive analysis. Specifically, our approach is based on stigmergy. By using stigmergy each sample position is associated with a digital pheromone deposit, which progressively evaporates and aggregates with other deposits according to their spatiotemporal proximity. Based on this principle, we exploit positioning data to identify high density areas (hotspots) and characterize their activity over time. This characterization allows the comparison of dynamics occurring in different days, providing a similarity measure exploitable by clustering techniques. Thus, we cluster days according to their activity behavior, discovering unexpected urban activity patterns. As a case study, we analyze taxi traces in New York City during 2015