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Mobility implies initial and final distributions and a transition process linking the observations of these two distributions. An inequality index describes properties of the intitial or final distribution. A mobility index describes the transition. In most cases, mobility indices have been developed using properties of transition matrices independently of the concepts of inequality and equity that may also be used in the analysis. This paper presents a new tool – the Gini index of mobility – that provides an overall consistent framework for the analysis of mobility, inequality, and horizontal equity. The theoretical concepts are illustrated empirically using panel data from rural Mexico.

In the typical study comparing the evolution of economic inequality among different territorial units, an inequality indicator is chosen, and its value is calculated from sample data. Thus, the problem turns out to be the selection of the inequality indicator.

This paper shows that there is no need for a selection of a single inequality indicator. A whole set of inequality indicators are considered and calculated for the European Countries, using income data from European Community Household Panel (ECHP). The information they provide is then collapsed into a composite inequality indicator, through an adaptation of Principal Component Analysis (PCA). We analyze the conditions needed to make longitudinal comparisons possible. Results obtained with this composite indicator are used to compare and analyze the trends in economic inequality in the EU Countries.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

This chapter develops a set of two-step identification methods for social interactions models with unknown networks, and discusses how the proposed methods are connected to the identification methods for models with known networks. The first step uses linear regression to identify the reduced forms. The second step decomposes the reduced forms to identify the primitive parameters. The proposed methods use panel data to identify networks. Two cases are considered: the sample exogenous vectors span Rn (long panels), and the sample exogenous vectors span a proper subspace of Rⁿ (short panels). For the short panel case, in order to solve the sample covariance matrices’ non-invertibility problem, this chapter proposes to represent the sample vectors with respect to a basis of a lower-dimensional space so that we have fewer regression coefficients in the first step. This allows us to identify some reduced form submatrices, which provide equations for identifying the primitive parameters.

Purpose: Most of the characterizations of inequality or poverty indices assume some invariance condition, be that scale, translation, or intermediate, which imposes value judgments on the measurement. In the unidimensional approach, Zheng (2007a, 2007b) suggests replacing all these properties with the unit-consistency axiom, which requires that the inequality or poverty rankings, rather than their cardinal values, are not altered when income is measured in different monetary units. The aim of this paper is to introduce a multidimensional generalization of this axiom and characterize classes of multidimensional inequality and poverty measures that are unit consistent.

Design/methodology/approach: Zheng (2007a, 2007b) characterizes families of inequality and poverty measures that fulfil the unit-consistency axiom. Tsui (1999, 2002), in turn, derives families of the multidimensional relative inequality and poverty measures. Both of these contributions are the background taken to achieve our characterization results.

Findings: This paper merges these two generalizations to identify the canonical forms of all the multidimensional subgroup- and unit-consistent inequality and poverty measures. The inequality families we derive are generalizations of both the Zheng and Tsui inequality families. The poverty indices presented are generalizations of Tsui's relative poverty families as well as the families identified by Zheng.

Originality/value: The inequality and poverty families characterized in this paper are unit and subgroup consistent, both of them being appropriate requirements in empirical applications in which inequality or poverty in a population split into groups is measured. Then, in empirical applications, it makes sense to choose measures from the families we derive.

The chapter suggests two methodologies to measure inequality of opportunity in health in Israel, an ex-ante and an ex-post approach. In both cases, following the strategy recently suggested by Trannoy, Tubeuf, Jusot, and Devaux (2010), the chapter starts by introducing the production function of health, taking into account circumstances (the father’s years of education, his country of birth, the religion of the individual, his or her country of birth, age and gender) as well as effort variables (the level of education of the individual, his or her occupation and a variable describing his or her smoking habits).

The chapter also suggests then a decomposition of the overall health inequality into a legitimate and an illegitimate component, using the mean logarithmic deviation as inequality index, such a breakdown being applied to both the ex-ante and the ex-post approaches to equality of opportunity.

This chapter discusses the empirical application of a class of strategic network formation models, using the approach to identification introduced by de Paula, Richards-Shubik, and Tamer (2018). The author emphasizes the interplay between model specification and computational complexity, and suggests tactics to make empirically realistic models become tractable. Two detailed examples, on friendship networks and coauthorship networks, are used to illustrate these issues and to demonstrate the performance of the approach with both simulation and empirical evidence. Also, the author presents extensions to the estimation method, which expand the potential range of applications, and which provide statistical inference with minimal computational burden.

A concise introduction to the normalized quadratic expenditure or cost function is provided so that the interested reader will have the necessary information to understand and use this functional form. The normalized quadratic is an attractive functional form for use in empirical applications as correct curvature can be imposed in a parsimonious way without losing the desirable property of flexibility. We believe it is unique in this regard. Topics covered include the problem of cardinalizing utility, the modeling of nonhomothetic preferences, the use of spline functions to achieve greater flexibility, and the use of a “semiflexible” approach to make it feasible to estimate systems of equations with a large number of commodities.