Inequality analysis is a field of research of great relevance within economic science. However, until the publication of the renowned paper of Kuznets (1955), Economic Growth and Income Inequality, it was not considered of pretty much interest from an academic viewpoint. Thereafter, its study has gained relevance and research studies trying to measure and understand inequality, its dynamics and evolution became numerous.
The distributive analyses, and in particular inequality measurement, have been performed from the utilitarian perspective. Consequently, inequality has been usually measured in reference to income or wealth, using as indicators variables such as consumption, income or labour income. However, even though the utilitarian approach has been the mainstream paradigm in economic science since the 18th century, from the second half of the 20th century onwards its ethical basis began to be questioned by a wide range of scientist and philosophers. The space in which equality and justice should be evaluated became the central discussion point, leading to the renowned question posed by Amartya Sen in the Tanner lectures on human values: Equality of What? The concept of Equality of Opportunity was first formalised from an economic viewpoint by Roemer (1998). He called the factors that produce "fair inequalities" efforts and the group of factors that produce "unfair inequalities" circumstances. From this classification he argued that equality of opportunity is a situation in which the outcome of reference (e.g. income, wealth or consumption), called variable of advantage, is independent of the circumstances.
Within this framework, the aim of this thesis is to contribute to the analysis of income inequality and Inequality of Opportunity analysing them for different geographical territories and from different perspectives. Chapter 1 is focused on the analysis of inequalities for European countries, Chapter 2 provides a detailed analysis of inequalities in Spain, Chapter 3 analyses regional inequalities in the Spanish Regions and finally, Chapter 4 is focused on Developing Countries.
The aim of Chapter 1 is to analyse in depth inequalities within European countries since they constitute a major driver of overall inequality in Europe, and also spatial inequalities between countries. For this purpose, we use the European Survey of Income and Living Conditions (EU-SILC). We put in the spotlight the short-term analysis of inequalities, since its implications are of great interest to shape public policy and correct disturbing imbalances on individuals' welfare. In addition, we are also focused on the analysis of Inequality of Opportunity since it has been proved that individuals' circumstances have a great effect in individuals' outcomes. Finally, we assess overtime changes using a bootstrap methodology.
The goal of Chapter 2 is to contribute both theoretically and empirically to the analysis of Inequality of Opportunity over time, providing some significant findings referred to the Spanish case. In this chapter we provide evidence of how income inequality and IOp have behaved in a context of economic crisis. Likewise, in Chapter 2 we apply three different methodologies to measure Inequality of Opportunity and two procedures to measure the contribution circumstances have in IOP and we analyse their suitability.
Spanish regions differ widely from each other in many dimensions, e.g. economic size, per capita GDP, unemployment rate and demography. Overall, the broad goal of Chapter 3 is to analyse income inequality and Inequality of Opportunity within the 17 Spanish Autonomous Communities (CCAA), which corresponds to EU NUTS II regions using the European Survey of Income and living Conditions (EU-SILC). We also analyse mobility in education and the situation of immigrants for the different territories.
Finally, the aim of Chapter 4 is to shed some light on the behaviour of Inequality of Opportunity in developing countries. The analysis is carried out using microdata collected by national surveys and harmonised by the LIS Cross-National Data Center (LIS). The LIS database incorporates a wide variety of personal harmonised variables, which allow us to make cross-country comparisons for developing countries. More specifically, we analyse six countries: Brazil, Egypt, Guatemala, India, Peru and South Africa and the periods of time covered vary from 2004 to 2014.
Summarising, the main empirical findings of the analysis performed are that, concerning to the contribution of circumstances, for the European countries, the most remarkable fact is the increase of the contribution of Immigrant in most countries. In the case of developing countries, Chapter 4 shows that Parental Education is the most relevant circumstance in all the countries analysed. Likewise, in the regional analysis for Spain carried out in Chapter 3, we show that in most regions income variations affect more negatively those individuals at the bottom of the distribution, aggravating their already unfavourable condition.
With regard to the methodological findings. it has been shown that the bootstrap procedure allows us to corroborate and to present a robust evidence of the overtime changes observed in the inequality estimates.
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