Mariateresa Ciommi

Sustainability is a complex multidimensional framework to be evaluated and measurement tools play a crucial role in this challenge. The 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, declines sustainability through 17 objectives (17 Sustainable Development Goals, SDGs), to reach by 2030. Among all Goals, here we focus on climate change, that is on Goal 13 “Take urgent action to combat climate change and its impacts”. With the aim of better monitoring and evaluating sustainability levels of countries and how far they are from achieving their goals, the current study proposes the use of a modified version of the Wroclaw taxonomic method. The proposed index is used to aggregate indicators belonging to Goal 13 for 18 European countries in 2020 and 2021. The effectiveness of the proposed method is assessed by comparing results with the classical indices used for measuring SDG progress.

This paper aims to examine the impact of the Covid-19 pandemic on multidimensional poverty in Italy and its provinces by comparing household poverty levels before and after the outbreak. To capture the multidimensionality of poverty, we analyze various dimensions, including economic well-being, health status, education, neighborhood quality, and subjective well-being. The empirical analysis relies on micro-data from Istat’s aspects of daily life (AVQ) survey, covering the years 2018–2021. As the survey’s direct estimates are reliable only at the regional level (NUTS 2), we apply small area estimation techniques to produce accurate estimates of provincial (NUTS 3) deprivation incidences. Subsequently, we aggregate the deprivation headcounts across the elementary indicators using penalized power mean composite indicators. The empirical findings indicate that overall multidimensional poverty worsened in most of the Italian provinces, particularly during the second year of the pandemic, with higher levels persisting in southern areas. The various dimensions of poverty exhibited different trends, with education, subjective well-being, and health emerging as the most negatively affected in numerous provinces.

An implementation of Gini-based weighting approaches in constructing composite indicators, providing functionalities for normalization, aggregation, and ranking comparison.

The aim of this paper is to measure to which extent income distribution is polarized across European countries by means of polarization measures based on the Bonferroni and De Vergottini indices of inequality. Different from traditional measures of polarization, the indices proposed in this paper are sensitive to progressive transfers, attaching more importance to some part of the income distribution. These indices enriches the analysis and contribute to disentangle the different faces of income polarization. In the empirical application we compare European countries over the period 2010–2019 using EU-SILC data. Results reveal significant changes in polarization over the last decades for most countries.

In this paper, we propose a novel method for ranking items such as countries, individuals, or firms based on two indices. This approach is particularly useful when constructing a composite indicator that combines both dimensions is not feasible. The proposed ranking approach involves an iterative scheme where the Voronoi algorithm is applied in a two-dimensional space at each step. To provide empirical evidence that our approach works satisfactorily, we applied the Voronoi-based iterative scheme to rank 34 European countries based on two dimensions: the Human Development Index (HDI) and the Happiness Index (HI). The correlation coefficient between the rankings based on HDI and HI is lower than the correlation coefficients between the Voronoi-based ranking and HDI, as well as between the Voronoi-based ranking and HI. These results suggest that the new method is capable of better capturing the information from both original indices.

In this work we analyze the vulnerability of people aged 50+ living in 11 European Countries, taking into account for two aspects: a physical-economic dimension and a social one. Data come from the Survey of Health, Ageing, and Retirement in Europe (SHARE) and refer to the Covid-19 period, that is 2019-2020. Results show a geographical path of vulnerability: Mediterranean Countries register the higher vulnerability, especially in the Economic-Health domain.