Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu Despite a recent surge in the number of studies attempting to measure inequality of opportunity in various countries, methodological differences have so far prevented meaningful international comparisons. This paper presents a comparison of ex-ante measures of inequality of economic opportunity (IEO) across 41 countries, and of the Human Opportunity Index (HOI) for 39 countries. It also examines international correlations between these indices and output per capita, income inequality, and intergenerational mobility. The analysis finds evidence of a "Kuznets curve" for inequality of opportunity, and finds that the IEO index is positively correlated with overall income inequality, and negatively with measures of intergenerational mobility, both in incomes and in years of schooling. The HOI is highly correlated with the Human Development Index, and its internal measure of inequality of opportunity yields very different country rankings from the IEO measure. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SJEL Classification: D71, D91, I32Keywords: equality of opportunity, income inequality, social mobility, mobility NON-TECHNICAL SUMMARYMany different indices to measure inequality of opportunity have been proposed, but only two have been applied to enough countries to permit reasonably meaningful international comparisons. The inequality of economic opportunity index (IEO) estimates the (lower bound) share of income inequality that can be attributed to differences in people's pre-determined circumstances (such as race, gender and family background). It has been applied to 41 countries, and ranges from 2% in Norway to 34% in Guatemala. The second approach is known as the Human Opportunity Index (HOI): an index of children's access to basic services, penalized by unequal opportunities in that access. Like the IEO, the HOI must lie between 0 and 100%. In the 39 countries where it has been computed, it ranges from 10% in Niger to 91% in Chile. The IEO is positively correlated with income inequality, and negatively with intergenerational mobility -both in incomes and in years of schooling. The HOI is highly correlated with the Human Development Index. Its internal measure of inequality of opportunity -the dissimilarity index -yields very different country rankings from the IEO, highlighting the differences between the two methods. The IEO and the HOI may well be complementary, but users should be cautious to understand what each...

Despite a recent surge in the number of studies attempting to measure inequality of opportunity in various countries, methodological differences have so far prevented meaningful international comparisons. This paper presents a comparison of ex-ante measures of inequality of economic opportunity (IEO) across 41 countries, and of the Human Opportunity Index (HOI) for 39 countries. It also examines international correlations between these indices and output per capita, income inequality, and intergenerational mobility. The analysis finds evidence of a "Kuznets curve" for inequality of opportunity, and finds that the IEO index is positively correlated with overall income inequality, and negatively with measures of intergenerational mobility, both in incomes and in years of schooling. The HOI is highly correlated with the Human Development Index, and its internal measure of inequality of opportunity yields very different country rankings from the IEO measure

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 circumstances 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 empirical 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 measurement, 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.

We propose a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. In particular, we illustrate how these methods represent a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, they minimize the risk of arbitrary and ad-hoc model selection. Second, they provide a standardized way of trading off upward and downward biases in inequality of opportunity estimations. Finally, regression trees can be graphically represented; their structure is immediate to read and easy to understand. This will make the measurement of inequality of opportunity more easily comprehensible to a large audience. These advantages are illustrated by an empirical application based on the 2011 wave of the European Union Statistics on Income and Living Conditions.

In 2001 the Italian tertiary education system embarked in a broad process of reform. The main novelty brought by the reform was a reduction of the length of study to get a first level degree together with the introduction of a 2-years, second level, master degree. This paper aims at studying the effects of the reform in terms of fairness in educational opportunity. In order to do so we first define fairness criteria following a well developed responsibility sensitive egalitarian literature, we then discuss existing inequality of opportunity measures consistent with these criteria, we show their relationship, and we adapt them to the educational framework. We finally employ this set of measures to show the evolution of fairness in the access to university in Italy before and after the reform.