Educational inequality is vast. Figure 1 compares average scores from the 2015 wave of the OECD’s Programme for International Student Assessment (PISA) by country to the average scores for children from families in the top and bottom quarter of a measure of socioeconomic status. The socioeconomic gap in test scores amounts to almost a standard deviation. Even in the best-performing countries, the scores of students from disadvantaged backgrounds are below the OECD average.
Figure 1 PISA scores by country and socioeconomic background
Notes: The figure reports the mean PISA 2015 results for OECD countries and the mean scores in the top and bottom quarters of the PISA index of economic, social, and cultural status (ESCS). The numbers refer to the gap between the mean scores in the top and bottom quarters for each country. Source: OECD (2016).
These large socioeconomic gaps imply that educational inequality is a key element in the reproduction of inequality from one generation to the next. Economic inequality contributes to large gaps in the investments that parents from different parts of the income distribution make in their children’s education. Given high economic returns to education, educational inequality in turn implies both economic inequality and low social mobility.
Indeed, the ‘Great Gatsby Curve’ shows that countries with more income inequality also tend to have lower income mobility (Corak 2013, Blanden 2013), and a similar association is observed across regions within country (Chetty et al. 2014, Güell et al. 2018). This pattern is also reason to be concerned about future social mobility. Income inequality has been rising in many countries, and the Great Gatsby Curve suggests that this might result in lower social mobility and in an economically divided society in the future. But how likely is such an outcome of ever-lower social mobility?
The educational Great Gatsby Curve
To get an answer, one should first consider the link from economic to educational inequality. Conceptually, there are good reasons to expect economic inequality to increase educational inequality. By raising the stakes, it spurs well-off parents to double down on investing money and time in their children, while those of lesser means may not be able to keep up.
Indeed, there is evidence for rising socio-economic gaps in parental investments in recent decades (Doepke and Zilibotti 2019). In the US, upper-middle-class parents have increased their time and money investments in children compared to less fortunate families. However, even though gaps in inputs have risen, the evidence for gaps in outputs is less clear. For example, socioeconomic gaps in tests scores in the US appear to have been broadly stable over the past few decades (Hanushek et al. 2019, 2020).
This tension motivates us to look for evidence of an ‘educational’ Great Gatsby Curve. In a new chapter for the Handbook of Economics of Education (Blanden et al. 2022), we assess whether more unequal countries also display greater educational inequality. In terms of educational attainment (e.g. years of schooling), there is indeed a clear relationship: as shown in the right panel in Figure 2, more unequal countries have lower intergenerational mobility in terms of years of schooling, in both developing and high-income economies. But the relationship between income inequality and test scores is less clear: as shown in the left panel of Figure 2, more inequality is not systematically related to larger socio-economic gaps in test scores.
Figure 2 The educational Great Gatsby Curve
Notes: Scatter plot of the 2012 World Bank Gini (or nearest available year) against the gap in average 2015 PISA scores in reading and mathematics between the top and bottom quarters of socio-economic background (Source: OECD 2016) in Panel (a) and of the intergenerational correlation in parents’ highest and child’s years of schooling (Source: Global Database on Intergenerational Mobility, The World Bank 2018) in Panel (b).
One way to reconcile these trends is that investments of well-off parents run into strongly diminishing returns, while the investments of less fortunate parents are highly productive. Then, rising investment gaps are consistent with stable achievement gaps. But even for given achievement, well-off parents may find other ways to give their children a leg up – and hence, the Great Gatsby Curve in educational attainment. From this point of view, there is indeed reason to be concerned about the future of social mobility, even if the test score gaps remain stable.
Amplifying this concern is that simple summary statistics such as the parent-child correlation in schooling may understate the true persistence of educational advantages from one generation to the next. Years of schooling is only a coarse measure of learning, which abstracts from achievement gaps between students attending the same grade and from horizontal segregation in institutional quality (Chetty et al. 2017) or field of study (Hällsten and Thaning 2018).
Educational inequality in the long run
Indeed, recent studies tracking multiple generations imply that persistence is higher than indicated by conventional parent-child correlations in years of schooling. One way to show this is to note that the outcome of other ancestors remain predictive of child education, even after conditioning on parent education (e.g. Lindahl et al. 2015, Braun and Stuhler 2018, Anderson et al. 2018, Adermon et al. 2021).
That parent-child correlations may understate the role of family background is also consistent with earlier evidence from sibling correlations (Björklund and Salvanes 2011, Björklund and Jäntti 2012) or recent studies of regression to the mean on the surname level (Clark 2014a, 2014b and Barone and Mocetti 2016, 2020).
The role of educational policy
While educational inequality might therefore be quite persistent, the literature is also clear about the fact that policy matters. None of these patterns and trends are unchangeable laws of nature, but they are contingent on policy choices for early childhood education, schooling and higher education, and family support.
This does not mean, however, that it is straightforward to design simple policies that comprehensively counteract educational inequality. Some of the most obvious policy instruments, such as increasing school funding or instruction hours, appear to have only modest effects (e.g. Jackson and Mackevicius 2021). Other inputs such as teacher quality appear more important, but are also less directly malleable by policy.
Given the role of economic inequality, our chapter also revisits the different ways that financial constraints affect attendance in higher education. One important insight is that student loans cannot fully eliminate the investment gap between children from families with more and less resources.
Educational inequality in the COVID-19 pandemic
The final part of our chapter addresses the impacts of the COVID-19 pandemic on educational inequality. Of the world’s student population, 94% was affected by school closures in the spring of 2020 (UNESCO), which often lasted for months and, in some cases, for more than a year. Such school closures are likely to impact children from different socioeconomic backgrounds differentially.
First, the incidence of school closures themselves varied by social background, for instance when public schools close while private schools attended by richer families stay open. Second, children from disadvantaged backgrounds might experience greater learning loss if their school closes, as the ability of parents or peers to compensate is likely to differ across families. In particular, the ability of low-income parents to respond is hampered by the fact they are much less likely to have jobs that can be done from home.
The evidence so far indeed shows that pandemic school closures have increased educational inequality. For example, Engzell et al. (2020, 2021) find that in the Netherlands, eight weeks of online rather than in-person learning led to 0.08 of a standard deviation lower test scores for students aged eight to 11. The impact is 40% larger among those in the least educated homes, suggesting that the pandemic not only increased educational inequality, but that disadvantaged children’s skills actually deteriorated.
Given that the consequences of the pandemic are ongoing, the empirical literature has so far been able to quantify only a subset of the potential channels via which it will affect educational inequality. However, learning is a cumulative process, where learning losses at one life stage may be difficult to compensate for later in life. To examine the potential long-run repercussions of the crisis, recent studies draw on structural modelling that is disciplined by both current and pre-pandemic data (Jang and Yum 2020, Fuchs-Schündeln et al. 2021, and Agostinelli et al. 2022). These studies suggest that unless there is a strong policy response, the pandemic loss of human capital will be reflected in lower lifetime earnings at the individual level, lower national income at the aggregate level, and higher educational inequality for decades to come.
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