Inequality of Opportunity in developing economies A cross-country analysis with LIS harmonised data Ana Suárez Álvarez University of Oviedo Department of Applied Economics LIS Research Visit, 2017
Table of contents Introduction 1 Data and variables 2 Estimation of IOp 3 Bootstrapping methodology 4 Concludes 5 A. Suárez Álvarez IOp in Developing economies LIS Research Visit 2 / 24
Introduction Table of contents Introduction 1 Data and variables 2 Estimation of IOp 3 Bootstrapping methodology 4 Concludes 5 A. Suárez Álvarez IOp in Developing economies LIS Research Visit 3 / 24
Introduction Background I: The concept of Inequality of Opportunity (IOp) � - Circumstances (C) Unfair Inequality Inequality depends on - Efforts (E) Fair Inequality Inequality of Opportunity (IOp) Tries to estimate the part of overall inequality considered unfair since individuals cannot be held responsible for it. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 4 / 24
Introduction Background I: The concept of Inequality of Opportunity (IOp) � - Circumstances (C) Unfair Inequality Inequality depends on - Efforts (E) Fair Inequality Inequality of Opportunity (IOp) Tries to estimate the part of overall inequality considered unfair since individuals cannot be held responsible for it. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 4 / 24
Introduction Background I: The concept of Inequality of Opportunity (IOp) � - Circumstances (C) Unfair Inequality Inequality depends on - Efforts (E) Fair Inequality Inequality of Opportunity (IOp) Tries to estimate the part of overall inequality considered unfair since individuals cannot be held responsible for it. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 4 / 24
Introduction Background II: Temporal framework It is of great important to analyse the evolution of inequality and IOp indicators because we can: Assess the effect of different economic scenarios in Ineq and IOp Understand the relationship between Inequality and IOp indicators Know if the contribution of Circumstances to IOp and Inequality changes over time Improve the design of public policies to soften or eliminate Inequality and/or IOp For this purpose I analyse the significance of over time changes using the bootstrap methodology. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 5 / 24
Introduction Background II: Temporal framework It is of great important to analyse the evolution of inequality and IOp indicators because we can: Assess the effect of different economic scenarios in Ineq and IOp Understand the relationship between Inequality and IOp indicators Know if the contribution of Circumstances to IOp and Inequality changes over time Improve the design of public policies to soften or eliminate Inequality and/or IOp For this purpose I analyse the significance of over time changes using the bootstrap methodology. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 5 / 24
Introduction Background II: Temporal framework It is of great important to analyse the evolution of inequality and IOp indicators because we can: Assess the effect of different economic scenarios in Ineq and IOp Understand the relationship between Inequality and IOp indicators Know if the contribution of Circumstances to IOp and Inequality changes over time Improve the design of public policies to soften or eliminate Inequality and/or IOp For this purpose I analyse the significance of over time changes using the bootstrap methodology. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 5 / 24
Introduction Background II: Temporal framework It is of great important to analyse the evolution of inequality and IOp indicators because we can: Assess the effect of different economic scenarios in Ineq and IOp Understand the relationship between Inequality and IOp indicators Know if the contribution of Circumstances to IOp and Inequality changes over time Improve the design of public policies to soften or eliminate Inequality and/or IOp For this purpose I analyse the significance of over time changes using the bootstrap methodology. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 5 / 24
Introduction Background II: Temporal framework It is of great important to analyse the evolution of inequality and IOp indicators because we can: Assess the effect of different economic scenarios in Ineq and IOp Understand the relationship between Inequality and IOp indicators Know if the contribution of Circumstances to IOp and Inequality changes over time Improve the design of public policies to soften or eliminate Inequality and/or IOp For this purpose I analyse the significance of over time changes using the bootstrap methodology. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 5 / 24
Introduction Background II: Temporal framework It is of great important to analyse the evolution of inequality and IOp indicators because we can: Assess the effect of different economic scenarios in Ineq and IOp Understand the relationship between Inequality and IOp indicators Know if the contribution of Circumstances to IOp and Inequality changes over time Improve the design of public policies to soften or eliminate Inequality and/or IOp For this purpose I analyse the significance of over time changes using the bootstrap methodology. A. Suárez Álvarez IOp in Developing economies LIS Research Visit 5 / 24
Introduction Objectives 1 Estimate Inequality and Inequality of Opportunity 2 Estimate the contribution of each circumstance to IOp 3 Assess changes overtime on income inequality and inequality of opportunity Stratified bootstrap estimation on Inequality and IOp indices A. Suárez Álvarez IOp in Developing economies LIS Research Visit 6 / 24
Introduction Objectives 1 Estimate Inequality and Inequality of Opportunity 2 Estimate the contribution of each circumstance to IOp 3 Assess changes overtime on income inequality and inequality of opportunity Stratified bootstrap estimation on Inequality and IOp indices A. Suárez Álvarez IOp in Developing economies LIS Research Visit 6 / 24
Introduction Objectives 1 Estimate Inequality and Inequality of Opportunity 2 Estimate the contribution of each circumstance to IOp 3 Assess changes overtime on income inequality and inequality of opportunity Stratified bootstrap estimation on Inequality and IOp indices A. Suárez Álvarez IOp in Developing economies LIS Research Visit 6 / 24
Data and variables Table of contents Introduction 1 Data and variables 2 Estimation of IOp 3 Bootstrapping methodology 4 Concludes 5 A. Suárez Álvarez IOp in Developing economies LIS Research Visit 7 / 24
Data and variables LIS Data 6 countries are analysed: 1 Brazil 2006, 2009, 2011 and 2013 2 Egypt 2012 3 Guatemala 2006, 2011 and 2014 4 India 2004 and 2011 5 Peru 2004, 2007, 2010 and 2013 6 South Africa 2008, 2010, 2012 A. Suárez Álvarez IOp in Developing economies LIS Research Visit 8 / 24
Variables Circumstances Variable of Advantage Variables used to approximate the true Inequality of Opportunity Equivalised disposable income Variable for which we measure Gender ⇒ 2 categories inequality and IOp Parental education ⇒ 3 Accurate approximation to the categories truly available income each Immigrant or not ⇒ 2 categories individual benefits from Age group ⇒ 5 categories OECD-Equivalence scale: Density ⇒ 2 categories e = 1 + 0 . 5 ( N 14 + − 1 ) + 0 . 3 N 13 − Ethnic 2 categories for: where N 14 + is the number of Brazil (white & others) HH members with 14 or more Guatemala (non indig.& years old and N 13 − the number others) India (high castes & of HH members below 14 years. others) South Africa (african & others)
Variables Circumstances Variable of Advantage Variables used to approximate the true Inequality of Opportunity Equivalised disposable income Variable for which we measure Gender ⇒ 2 categories inequality and IOp Parental education ⇒ 3 Accurate approximation to the categories truly available income each Immigrant or not ⇒ 2 categories individual benefits from Age group ⇒ 5 categories OECD-Equivalence scale: Density ⇒ 2 categories e = 1 + 0 . 5 ( N 14 + − 1 ) + 0 . 3 N 13 − Ethnic 2 categories for: where N 14 + is the number of Brazil (white & others) HH members with 14 or more Guatemala (non indig.& years old and N 13 − the number others) India (high castes & of HH members below 14 years. others) South Africa (african & others)
Variables Circumstances Variable of Advantage Variables used to approximate the true Inequality of Opportunity Equivalised disposable income Variable for which we measure Gender ⇒ 2 categories inequality and IOp Parental education ⇒ 3 Accurate approximation to the categories truly available income each Immigrant or not ⇒ 2 categories individual benefits from Age group ⇒ 5 categories OECD-Equivalence scale: Density ⇒ 2 categories e = 1 + 0 . 5 ( N 14 + − 1 ) + 0 . 3 N 13 − Ethnic 2 categories for: where N 14 + is the number of Brazil (white & others) HH members with 14 or more Guatemala (non indig.& years old and N 13 − the number others) India (high castes & of HH members below 14 years. others) South Africa (african & others)
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