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Title: Global trends in educational inequality
Citation Type: Miscellaneous
Publication Year: 2017
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Abstract: It is difficult to underestimate the importance of education for individuals‟ lives. Educational attainment is a key characteristic of individuals with a strong positive impact on virtually all relevant life cycle events that social scientists are interested in (e.g. union formation and dissolution, fertility, getting a job, salary, migration, health status and, finally, age at death). Therefore, the spectacular expansion of education we have witnessed all over the world during the last decades has to be welcomed as a major social improvement. This expansion includes rising literacy rates (Crafts 2002) as well as increases in school enrollment rates and in completed years of primary, secondary and college education (Benavot and Riddle 1988, Benavot et al. 1991; Meyer, Ramirez, and Soysal 1992; Ramirez and Meyer 1980; Barro and Lee 2000; Cohen and Soto 2007; Morrisson and Murtin 2009). These worldwide gains on virtually all education indicators are exhaustively described in a recent book by Barro and Lee (2015). While the levels and trends of overall educational attainment indicators have been well documented, the study of educational inequality has received far less attention in the literature. Yet, the way in which education is distributed across the population does have direct implications for individuals‟ life chances. High levels of educational inequality today will typically generate and amplify inequalities in other welfare domains in the future, hindering social mobility and strengthening the intergenerational transmission of social exclusion and disadvantage (Breen and Jonsson 2005; Esping-Andersen 2009). In this context, it is therefore important to document the levels and trends of educational inequality and to explore whether inequality declines together with educational expansion or not. In the last years, some studies have aimed to estimate educational inequality measures around the globe and/or its regions (e.g. Castelló and Doménech 2002, Benaabdelaali et al. 2012, Dorius 2013, Meschi and Scervini 2013, Morrisson and Murtin 2013). Virtually all these studies are based on different versions of the dataset from Barro and Lee (see www.barrolee.com), which groups data in 4 or 7 broad educational attainment categories, depending on whether we consider both complete and incomplete educational stages. Unfortunately, by grouping the data in these coarse categories we lose sight of important variations that might be occurring both within and between education distributions, therefore downwardly biasing the estimated inequality levels – an issue we address in this paper. For the first time, we aim at unraveling global trends in education inequality using micro-level information about individuals‟ years of schooling. Such fine-grained information will allowus to describe global education inequality levels and trends with unprecedented accuracy. For that purpose, we have assembled a large dataset from different – yet comparable – data sources: the census micro-data samples from the IPUMS project, the Demographic and Health Surveys (DHS), the European Social Surveys (ESS) and the International Social Survey Programme (ISSP). Our database consists of 153 census samples and 1,011 household surveys covering 126 countries from the period 1960-2014. With this wealth of information, we aim to gain understanding on the nature of the variation in years of schooling among countries and recent time periods in several ways. First, we disclose the full pattern of variation in educational inequality and mean years of schooling for all 1164 country-year combinations. Recently, some authors suggested that a J-shaped relationship between average years of education and inequality emerges, as expansion at higher levels of education is likely to cover more selective parts of countries‟ populations (Meschi and Scervini 2013). Our relatively precise measurement of years of education should be particularly suited to identify such a J-shaped curve. Second, we select a consistent sample of 85 countries for the periods 1995-2004 and 2005-2014 to estimate global educational inequality and decompose this inequality into its within and between-country components. This kind of decomposition has already been explored in the domains of income (Anand and Segal 2014) and health (Edwards 2011), but remains to be unraveled and analyzed for the case of education. Finally, we investigate the contribution that the different educational stages (primary, secondary and tertiary education) have had on global educational inequality – a contribution that changes substantially across countries and over time as education expands. Also here, the precision of our years of education measure should give relatively accurate estimates of the relative role of educational stages in creating global educational inequality.
User Submitted?: No
Authors: Permanyer, Iñaki
Publisher: Centre d'Estudis Demogràfics
Data Collections: IPUMS Health Surveys - NHIS
Topics: Education, Fertility and Mortality, Labor Force and Occupational Structure, Migration and Immigration
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