Fairness in Skill Acquisition

In this paper we try to determine which policy implements fairness in the distribution of educational outcomes, in a framework in which skills arise from the combination of circumstances, effort and transfers, and determine individual utility. Our definition of fairness relies on two ethical principles, liberal reward and compensation, which have been well defined and studied by many authors in the last decade, and is linked to the philosophical debate that, since the late '60, has debated about the meaning of educational opportunities. According to this definition, to be fair an allocation should remove inequalities not due to individuals' responsibility.

Fairness in education: The Italian university before and after the reform

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.Equality of opportunity, higher education.

The Economic effects of a Local Minimum Income Support Program

Since Reddito Minimo d'Inserimento pilot experiment ended, a number of papers have attempted to study minimum income policies in Italy. Contributions have aimed at providing insight for possible future program implementations. In this paper we present a case study as an applied contribution to this debate. We analyze a minimum income support program implemented in a small town in the South of Italy, Mola di Bari, by using a new dataset which has been designed and collected for the purpose. With respect to the program, we describe the policy intervention and we analyze such issues as (i) the eligibility criteria, (ii) the targeting choices and results, (iii) the distributive and the welfare effects on the beneficiaries and on the overall town population (iv) the incentive effects, i.e. the effects on the labour market partecipation.minimum income; policy evaluation; poverty trap

The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach

We show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.Centro de Estudios Distributivos, Laborales y Sociale

The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach

We show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.Centro de Estudios Distributivos, Laborales y Sociale

The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach

We show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.Centro de Estudios Distributivos, Laborales y Sociale

The roots of inequality: estimating inequality of opportunity from regression trees

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

Biases in inequality of opportunity estimates: measures and solutions

In this paper we discuss some limitations of using survey data to measure inequality of opportunity. First, we highlight a link between the two fundamental principles of the theory of equal opportunities – compensation and reward – and the concepts of power and confidence levels in hypothesis testing. This connection can be used to address, for example, whether a sample has sufficient observations to appropriately measure inequality of opportunity. Second, we propose a set of tools to normatively assess inequality of opportunity estimates in any type partition. We apply our proposal to Conditional Inference Trees, a machine learning technique that has received growing attention in the literature. Finally, guided by such tools, we suggest that standard tree-based partitions can be manipulated to reduce the risk of compensation and reward principles. Our methodological contribution is complemented with an application using a quasi-administrative sample of Italian PhD graduates. We find a substantial level of labor income inequality among two cohorts of PhD graduates (2012 and 2014), with a significant portion explained by circumstances beyond their control

Inequality of opportunity and intergenerational persistence in Latin America

How strong is the transmission of socio-economic status across generations in Latin America? To answer this question, we first review the empirical literature on intergenerational mobility and inequality of opportunity for the region, summarizing results for both income and educational outcomes. We find that, whereas the income mobility literature is hampered by a paucity of representative datasets containing linked information on parents and children, the inequality of opportunity approach – which relies on other inherited and pre-determined circumstance variables – has suffered from arbitrariness in the choice of population partitions. Two new data-driven approaches – one aligned with the ex-ante and the other with the ex-post conception of inequality of opportunity – are introduced to address this shortcoming. They yield a set of new inequality of opportunity estimates for twenty-seven surveys covering nine Latin American countries over various years between 2000 and 2015. In most cases, more than half of the current generation’s inequality is inherited from the past – with a range between 44% and 63%. We argue that on balance, given the parsimony of the population partitions, these are still likely to be underestimates

Nitric oxide, cytochrome c oxidase and myoglobin: Competition and reaction pathways

AbstractIt is relevant to cell physiology that nitric oxide (NO) reacts with both cytochrome oxidase (CcOX) and oxygenated myoglobin (MbO2). In this respect, it has been proposed [Pearce, L.L., et al. (2002) J. Biol. Chem. 277, 13556–13562] that (i) CcOX in turnover out-competes MbO2 for NO, and (ii) NO bound to reduced CcOX is “metabolized” in the active site to nitrite by reacting with O2. In contrast, rapid kinetics experiments reported in this study show that (i) upon mixing NO with MbO2 and CcOX in turnover, MbO2 out-competes the oxidase for NO and (ii) after mixing nitrosylated CcOX with O2 in the presence of MbO2, NO (and not nitrite) dissociates from the enzyme causing myoglobin oxidation