Chiara Gigliarano

Poverty measures are typically estimated from sample observations and, therefore, they should not be used only as descriptive statistics, but rather as tools for statistical inference. Statistical analysis with explicit tests and confidence intervals is important to ensure that changes in measured poverty levels within or across countries correspond to real changes. The aim of the paper is to provide a comprehensive review of the main developments on the inferential aspects of the unidimensional poverty indices.

The short-term economic dynamics of local districts in light of the increasing regional disparities in Italy is examined. A multidimensional approach of ‘economic development’ is assumed and contextual variables such as the share of agriculture and industry in total value added, labour productivity by sector, per-capita and per-worker value added, have been evaluated jointly adopting an exploratory analysis that includes inferential and non-parametric statistics, integrated in appropriate geographical information systems. Economic dynamics of local districts in two separate phases (mid-1990s and mid-2000s) of the recent Italian development path were evaluated. This approach was preferred to more traditional methodologies centred on convergence analysis of income levels and change over time, allowing a refined discussion of the increasingly complex geography of economic development and ʼnewly emerging’ regional divides. The factors supposed to have a prominent role in such dynamics have been also investigated. The empirical results suggest that the traditional North-South gap consolidated in recent years. Coastal-inland and urban-rural gradients were crucial especially in economically disadvantaged districts, outlining a latent transition from agriculture and state-driven industry towards services with low-value added. The persistence of North-South disparities allowed identification of ‘structural’ dimensions of change as a possible target for integrated social policies.

The idea that high levels of polarization in society can lead to social instability and conflict has motivated an increasing interest in the analysis of income and social polarization. This chapter aims at providing a review of the main empirical findings resulting from the application of income and social polarization indices. The two main approaches to the study of income polarization are introduced. The first focuses on the rise of separated income groups, while the second addresses the decline of the middle class. Both approaches have been applied to the study of social conflict. Alternative methods for monitoring income polarization based on nonparametric density estimation techniques are also illustrated. Empirical applications of social polarization indices are then discussed. Finally, other applications are presented, such as health polarization, effects of taxation on income polarization and the link between wage polarization and labour market mobility.