MultiLocal: Multi dimensional inequality and optimization in a local perspective

The evaluation of human well-being is one of the most relevant issues in economics: the methods chosen for defining and measuring the individual well-being support and affect the political evaluation process in planning policy interventions. In order to understand the economic and social implications deriving from an heterogeneous distribution of well-being in a given society, it is necessary to analyse the distributions of the various relevant individual attributes (e.g. income, education, resources, health, etc.) and study the heterogeneous allocation of well-being across individuals in a given population, measuring poverty and inequality. This project will contribute by drawing new evidence for Italy and local territories for understanding and analyzing poverty and inequality among Italian young people using a multidimensional approach based on five dimensions: 1. education (including Early leavers from education and training, Level of digital competence of students, Level of literacy); 2. material living standard (including income, housing condition); 3. health status; 4. labour market participation (including youth employment, gender inequalities in average remuneration of employees, NEET status); 5. social connections and relationships (including also volunteering, meeting friends and relatives). Education inequality is a key dimension in the analysis of young poverty and inequality and it is the determinant of subsequent inequalities (of income, labour market participation, social connections, health, material living standard). At the same time, inequality in income, health and living standard affect educational inequality. The complexity of these relationships calls for a multidimensional investigation of inequality. The analysis will be carried out at different subnational levels (mainly regional and provincial levels with a focus on Lombardy and Piedmont) in order to have a clear understanding of territorial inequalities. The methodology consists of five main phases: 1. Exploring education inequalities and poverty across territories and education cycles, by focusing on student learning outcomes, as key determinants of individual human capital development, and providing evidence about factors shaping educational inequality and poverty in different territories and education cycles. 2. Analysing the relationship between school features and education inequality, by exploring the role played by schools’ characteristics (autonomy, activities, practices, teaching staff) in reducing inequalities in learning outcomes and raising student inclusiveness. 3. Evaluating income inequality and monetary poverty effects of public support to families with children, with the aim of analysing the redistributive impact of public support to families with children (including the Assegno Unico Universale which) in the Italian regions and within regions (Lombardy and Piedmont). 4. Assessing multidimensional poverty and inequality of young people, by aggregating the different dimensions that constitute the well-being of individuals and households: besides income and education, we will also include material living standard (including housing), health status, labour market participation (including NEET), social connections. 5. Ranking groups and territories according to multiple inequality and poverty dimensions, for assessing how differently societies are experiencing inequalities at national and local level. The project aims to enhance the understanding of the complex and socially relevant topic of multidimensional poverty and inequality among young people through robust and evidence-based data analysis implemented through the following innovative methodologies: - Fiscal tax-benefit microsimulations using EUROMOD, the EU-wide tax-benefit microsimulation model; - Small sample estimation and simulation; - Construction of appropriate composite poverty indicators; - Spatial microsimulation analysis for comparisons across Italian regions and sub-regional territories; - Estimating poverty and vulnerability risk at local level (focus on Lombardy and Piedmont regions and their provinces) with the means of advanced statistical techniques based on small areas estimation; - Optimization-based ranking techniques. A truly multidisciplinary and interdisciplinary approach will be adopted, with experts from public economics, statistics and mathematics, debating ideas, working together and discussing results on the different themes of our work program. The project will integrate different quantitative techniques, from econometric and statistical analysis to microsimulation modelling and optimization techniques.