Ana Suárez Álvarez

Abstract: The aim of this paper 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. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporate a wide variety of personal harmonised variables, allowing comparability with other countries. The availability of this database for the period 2004 and 2010 is particularly relevant for assessing changes over time in the main inequality indices and the contribution of circumstances to inequality of opportunity. We find that the effect of circumstances on income distribution has significantly intensified between the two years. To test the significance of the differences between years we perform bootstrap estimations.

Abstract: The aim of this chapter is to shed some light on the behavior of Income Inequality and Inequality of Opportunity over time for 26 European countries. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporates a wide variety of personal harmonized variables, allowing comparability between countries. The availability of this database for years 2004 and 2010 is particularly relevant to assess changes over time in the main inequality indices and the contribution of circumstances to inequality of opportunity. Furthermore, a bootstrap estimation is performed with the aim of testing whether the differences between both years are statistically significant.

Abstract: The aim of this paper is to shed some light on the behaviour of Inequality of Opportunity (IOp henceforth) in developing countries. The analysis is carried out using microdata collected by national surveys and harmonised by the Luxembourg Income Study (LIS). The LIS database incorporates a wide variety of personal harmonised variables, which allow us to made 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. Looking back to Amartya Sen´s famous question “Equality of what?” we compare IOp with economic inequality to obtain relative indicators of inequality of opportunity for each country analysed. Moreover, we use several indicators of income and consumption to assess if different aggregates lead to different conclusions both in the evolution of IOp and overall inequality and in the relative weights of the circumstances that conform IOp. In particular, we analyse IOp and Inequality for five different income aggregates: Equivalised Disposable Income using the OECD-modified scale, Personal Income, Labour Personal Income, Consumption and Monetary Consumption. We find that the use of an aggregate is not as important as it at first seems, leading in most cases to the same conclusions.

Abstract: The aim of this paper is to contribute both theoretically and empirically to the study of Inequality of Opportunity in Spain. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporate a wide variety of personal harmonised variables, allowing comparability with other countries. The availability of this database for years 2004 and 2010 is particularly relevant to analyse the impact of the economic crisis, the empirical evidence shows significant increases in both income inequality (17.24\%) and, more significantly, inequality of opportunity (62.34\%). According to our findings, the effect of circumstances on income distribution has intensified between the two years.

Abstract: We show that, when measuring inequality of opportunity with survey data, scholars face two types of biases. A well-known downward-bias, due to partial observability of cir- cumstances that affect individual outcome, and an upward bias, which is the consequence of sampling variance. The magnitude of the latter distortion depends on both the empirical strategy used and the observed sample. We suggest that, although usually neglected in em- pirical contributions, the upward bias may be significant. We propose a simple criterion to select the best specification which balances between the two sources of bias. Our method is based on cross validation and can be easily implemented to survey data. In order to show how this method can improve our understanding of the inequality of opportunity measure- ment, we provide an empirical illustration based on income data of 26 European countries. Our evidence shows that estimates of inequality of opportunity are extremely sensitive to model selection. Alternative specifications lead to significant differences in the absolute level of inequality of opportunity and to a number of substantial countries’ re-ranking. This in turn clarifies the need of an objective criterion to select the best econometric model when measuring inequality of opportunity.

Abstract: Egypt and Tunisia are perceived to have high levels of inequality, yet based on standard measures, inequality in these two countries is not unusually high. In this study we explore a different dime...

Abstract: We develop a normative approach to the measurement of inequality of opportunity. That is, we measure inequality of opportunity by the welfare gain obtained in moving from the actual income distribution to the optimal income distribution of the total available income. Our study brings together the main approaches in the literature: we axiomatically characterize social welfare functions, we obtain prominent allocation rules as their optima, and we derive familiar classes of inequality of opportunity measures. Our analysis captures moreover the key philosophical distinctions in the literature: ex post versus ex ante compensation, and liberal versus utilitarian reward.

Abstract: Inequality of opportunity (IOp) in any society is defined as that part of overall inequality which arises from factors beyond the control of an individual (circumstances) such as parental education, caste, gender, religion etc. and is thus considered unfair and is against the meritocratic values of a society. Hence, it needs to be controlled and compensated. We estimate the IOp in economic outcomes among Indian women by using the nationally representative India Human Development Survey 2011–2012. We include parental education, caste, religion and region of birth as circumstances. The overall IOp in income ranges from 18–25% and 16–21% (of total income inequality) in urban and rural areas, respectively. The corresponding figures for consumption expenditure are 16–22% and 20–23% in urban and rural areas, respectively. We also estimate the partial contributions of the circumstances to the overall IOp. We find that the parental education is the most significant contributor to IOp in urban areas, whereas, region of birth is the most significant contributor to IOp in rural areas. Fortunately, findings imply that socially and culturally imbedded factors like caste and religion which are more persistent do contribute to the IOp, but, the largest contribution is due to factors like parental education and region which can be relatively easily tackled and addressed with policy interventions.

Abstract: The aim of this chapter is to shed some light on the behavior of Income Inequality and Inequality of Opportunity over time for 26 European countries. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporates a wide variety of personal harmonized variables, allowing comparability between countries. The availability of this database for years 2004 and 2010 is particularly relevant to assess changes over time in the main inequality indices and the contribution of circumstances to inequality of opportunity. Furthermore, a bootstrap estimation is performed with the aim of testing whether the differences between both years are statistically significant.