OIT - Trends in educational and income mobility

 ILO Brief 1 Trends in educational and income mobility Research Brief February 2025 Trends in educational and income mobility by Rossana Merola (ILO)

 Since the 1980s, by increasing the number of university places, American society has created opportunities for the worse-off to achieve higher educational attainments.  Educational mobility has increased but has translated into a modest increase in income mobility.  At the same time, downward mobility has decreased because the American system has ensured that children in highly educated and wealthy families are protected from intergenerational income falls.  The empirical analysis of income mobility in developing countries faces several challenges because of the lack of very long panel data.  In India, there is a high persistence in the family status. However, mobility has increased at the lower end of the fathers’ educational distribution, while has decreased at the top end of that distribution. Educational mobility is increasing for girls.  Policies – such as public child-care programs, tax credit schemes and education subsidies – may be beneficial, especially for children from low-income families. Governments should ease high-quality education and labour market access for disadvantaged people and increase the protection of workers against discrimination by race.  Definitions and global outlook Social mobility is the movement of individuals through a system of social stratification. This movement can be downward or upward; the movement can also be absolute or relative; the social stratification may refer to education, occupation, income or some other measure of social status; and the movement may be within a person’s lifetime or between one generation and another. This brief will analyse intergenerational educational and income mobility. Breaking down barriers to social mobility is essential to fostering equal access to opportunities for all, which is one of the four pillars of social justice. Moreover, social mobility has also implications for inequality and growth. There is an

analyse intergenerational educational and income mobility. Breaking down barriers to social mobility is essential to fostering equal access to opportunities for all, which is one of the four pillars of social justice. Moreover, social mobility has also implications for inequality and growth. There is an empirical correlation between social mobility and income inequality. The common wisdom says that countries with higher income inequality tend to have lower intergenerational income mobility. In other words, in unequal societies, the worse off are more likely to rema in at the bottom of the economic ladder also for future Key findings ILO Brief 2 Trends in educational and income mobility generations, while the rich are more likely to stay at the top. The relationship between social mobility and inequality is known as the “Great Gatsby curve” (e.g. , Corak, 2013; Blanden, 2013).  Figure 1: The Great Gatsby curve

Source: Corak, 2012 (see https://milescorak.com/2012/01/12/here-is-thesource-for-the-great-gatsby-curve-in-the-alan-krueger-speech-at-thecenter-for-american-progress/).

Cross-country studies point out that the negative impact of inequality on growth is higher in those countries where social mobility is lower (Aiyar and Ebeke, 2019). While educational mobility has a significant relationship with income mobility, the connection is complex and can be influenced by structural factors (e.g. , economic policies, labour market conditions, discrimination and social inequalities), which can hinder the ability of individuals to translate their educational achievements into higher incomes. The existing literature points out that the role of education mobility on income mobi lity varies across regions. So far, the evidence is scarce. In Latin America, the role of education in economic mobility is strong (Torche, 2014). In contrast, Assaad and Saleh (2018) and Binzel and

education mobility on income mobi lity varies across regions. So far, the evidence is scarce. In Latin America, the role of education in economic mobility is strong (Torche, 2014). In contrast, Assaad and Saleh (2018) and Binzel and Carvalho (2017) show that educational mobility – respectively in Jordan and Egypt – has not led to more income mobility, suggesting that the educational pathway plays a limited role in economic mobility.

1 The NLSY79 Cohort is a longitudinal project that follows the lives of a sample of American youth born between 1957 -64. The cohort originally included 12,686 respondents ages 14 -22 when first interviewed in 1979. Data are now available from Round 1 (1979 s urvey year) to Round 29 (2020 survey year). Similarly, the NLSY97 Cohort is a longitudinal project that follows the lives of a sample of American youth born between 1980Both educational and income mobility are higher in advanced economies than in developing countries (Hertz et al., 2007) due to a lack of opportunity in the domestic labour market in developing countries . Educational and income mobility is particularly low in South Asia and SubSaharan Africa, where family income and educational background matter the most for youths (van der Weide et al., 2024).  Social mobility in the US Investing in education is crucial to improve the life chances of children and their educational mobility, that is, children can succeed and complete tertiary or advanced research programmes regardless of their parental educational attainment and family bac kground. In this view, Ernst, Langot, Merola and Gonzalez Pulgarin (2024) measure whether increasing the number of university places and hence opening universities to a larger number of students has improved educational opportunities for children born in low-income families. Using different measures (i.e., IGE, rank-rank correlation and matrix analysis), the authors assess intergenerational education and income mobility in

whether increasing the number of university places and hence opening universities to a larger number of students has improved educational opportunities for children born in low-income families. Using different measures (i.e., IGE, rank-rank correlation and matrix analysis), the authors assess intergenerational education and income mobility in the US for children born between 1957 and 1964 and for those born between 1980 and 19 84, using the 1979 and 1997 versions of the National Longitudinal Survey of Youth (NLSY79 and NLSY97), a programme of the US Bureau of Labor Statistics. 1 The analysis shows that since the end of the 1980s educational mobility has increased, this phenomenon being observed at the time when the U.S. universities were opened to all. The authors find that the probability of a young person achieving a higher degree than his/her parents has significantly increased – on average – from 15.7 per cent in the NLSY79 to 26.2 per cent in the NLSY97. Figure 2 reports the estimated probability that a child may achieve a bachelor's degree even though his/her parents have not graduated. The authors observe individuals 30 years after birth, since they may have fewer incentives to 84; 8,984 respondents were ages 12 -17 when first interviewed in 1997. This ongoing cohort has been surveyed 20 times to date and is now interviewed biennially. Data are now available from Round 1 (1997-98) to Round 20 (2021-2022). ILO Brief 3 Trends in educational and income mobility invest in their education beyond this age. Figure 2 shows that educational mobility has increased: the probability that a child born to low -educated parents will achieve a bachelor's degree has increased from 15 per cent for those born in 1957 (being 30 years old in 1987) to 30 per cent for those born in 1984 (being 30 years old in 2014).

a child born to low -educated parents will achieve a bachelor's degree has increased from 15 per cent for those born in 1957 (being 30 years old in 1987) to 30 per cent for those born in 1984 (being 30 years old in 2014).  Figure 2: Mobility in educational attainment

Source: Ernst, Langot, Merola and Gonzalez Pulgarin (2024) based on data from the NLSY79 and NLSY97.

However, this increase in educational mobility has translated into a modest increase in income mobility . Figure 3 reports the estimate of the correlation between parents’ and youths’ income ranks. This is a measure of the impact of parents’ income quartile position on the income quartile position of youth at the age of 30. 2 A strong correlation means lower income mobility. Figure 3 shows the correlation between parents’ and youth’s quartile income position has decreased, but only slightly. This result is confirmed by Chetty et al. (2014a) who − based on data from the Statistics of Income, a different data source from Ernst, Langot, Merola and Gonzalez Pulgarin (2024) − find tha t intergenerational elasticities of income did not change significantly between the 1950 and 1970 birth cohorts.

2 Another widely used measure of income mobility is the Inter -Generational Elasticity (IGE) which however may be affected by widening inequalities  Figure 3: Correlation between parents’ and children’s income between 1987 and 2013

Source: Ernst, Langot, Merola and Gonzalez Pulgarin (2024) based on data from the NLSY79 and NLSY97.

Higher education does not translate into higher possibilities of moving up the income ladder. One possible explanation is th at the signal on the labo ur market is no longer just the level of the degree , rather than the quality of the degree. While children from relatively less educated

Higher education does not translate into higher possibilities of moving up the income ladder. One possible explanation is th at the signal on the labo ur market is no longer just the level of the degree , rather than the quality of the degree. While children from relatively less educated families pursue higher-level studies, those from relatively more educated families turn to more prestigious institutions or higher -quality degrees. This would explain why higher educational mobility does not translate into higher income mobility. When considering the combination of income and educational mobility, Ernst, Langot, Merola and Gonzalez Pulgarin (2024) consider two extreme cases of mobility: extreme upward mobility (defined as the probability of moving from the lowest quartile of the distribution to the highest quartile after one generation) and extreme downward mobility (defined as the probability of moving from the highest quartile of the distribution to the lowest quartile after one generation). The authors show that upward mobility has increased from 0.91 per cent in the NLSY79 to 3.16 per cent in the NLSY97 survey (Figure 4, panel A) . At the same time, downward mobility has also increased from 5.63 per cent in the NLSY79 to 4.61 per cent in the NLSY97 (Figure 4, panel B) . These latter results among parents. Another limitation of IGE is that it is sensitive to extreme values of the distribution (see Chetty et al. , 2014a). ILO Brief 4 Trends in educational and income mobility further confirm that while upward mobility has risen over time, downward mobility has decreased. Ernst, Langot, Merola and Gonzalez Pulgarin (2024) assess also the impact that generations prior to parents could have on children's outcomes through the inheritance of financial assets and social networks.  Figure 4: “Extreme” cases of upward and downward mobility after 1, 2 and 3 generations in the 1979

also the impact that generations prior to parents could have on children's outcomes through the inheritance of financial assets and social networks.  Figure 4: “Extreme” cases of upward and downward mobility after 1, 2 and 3 generations in the 1979 cohort and 1997 cohort of the National Longitudinal Survey of Youth

Source: Ernst et al. , 2024 (National Longitudinal Survey of Youth and authors’ calculations).

Figure 4 points out a certain degree of social fluidity in the US: starting from the second generation, the initial family social condition influences descendants’ condition in society to a minor extent. The American system has given more opportunities to lowincome children having parents who have not graduated from college and has pushed them out of the immobility

3 These results confirm those in Oreopoulos et al. (2006) who used U.S. Census data for the period 1960-1980. They find that one additional year of education for either mother or father reduces the probability of grade retention anywhere from 2 to 17 percentage points. trap. At the same time, the American system has ensured children of highly educated and wealthy parents against intergenerational income fall. Ernst, Langot, Merola and Gonzalez Pulgarin (2024) find that the impact of parents’ income on children’s income is much higher when parents are highly educated: increases in parental education lead to better educational and economic outcomes for children, especially reduces the probability of very low achievements.3 To summarize, results in Ernst, Langot, Merola and Gonzalez Pulgarin (2024) point out that for those born to an elite, the family’s status has a strong impact on their welfare and that of future generations. Even in a society where people have in principle the opportunity to move upwards, the perpetuation of privileges creates "stickiness" at the top of the distribution. This is because it is more likely for wealthy students to have access to more prestigious

welfare and that of future generations. Even in a society where people have in principle the opportunity to move upwards, the perpetuation of privileges creates "stickiness" at the top of the distribution. This is because it is more likely for wealthy students to have access to more prestigious colleges. 4 Chetty et al. (2020) argue that most of the students at Ivy League colleges come from families in the top one per cent of the income distribution, while only 3.8 per cent of students come from the bottom quintile of the income distribution. In this view, Sandel (2020) writes that "American higher education is like an elevator in a building that most people enter on the top floor". To increase intergenerational mobility, Chetty et al. (2020) suggest that colleges should give low - and middle -income students a sliding-scale preference in the application and admission process similar to that implicitly given to legacy students at elite private colleges.  Social mobility in developing countries. The case of India In advanced economies, researchers can often rely on panel data to measure income mobility . In contrast , in developing countries it is difficult to find sufficiently long panels providing information on the income of parents and children living in the same household . Also, youth 4 The New York Times website gives complete information on the correlation between university attended by children and parental income (see hrttps://www.nytimes.com/interactive/2017/01/18/upshot). 0.91% 3.46% 4.34%3.16% 7.90% 1.48% 0% 5% 10% 1 generation 2 generations 3 generations

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5.63% 12.25% 15.93% 4.61% 7.95% 10.46% 0% 10% 20% 1 generation 2 generations 3 generations

M O B I LI Y

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NLSY97

5.63% 12.25% 15.93% 4.61% 7.95% 10.46% 0% 10% 20% 1 generation 2 generations 3 generations PA N E L B : D O W N WA R D

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NLSY79

NLSY97 ILO Brief 5 Trends in educational and income mobility emancipation is a rapid process and households can likely change more rapidly in developing than in advanced countries if a child forms a new household. For this reason, most panels are only 4 to 6 years long. Moreover, getting reliable data on household income is difficult because of the large incidence of informal income and the lack of bookkeeping. The lack of a very long panel structure has forced researchers to develop several methods to proxy panel data (e.g., synthetic panels, copula approximation or hybrid approaches). 5 Recently, Ray and Genicot (2023) have proposed an axiomatic approach proposed by to measure upward mobility without relying on panel data. Another limitation is the sample truncation. Most existing household surveys covering developing countries , such as the World Bank’s Living Standards Measurement Surveys , rely on co -residency criteria to define household membership at the time of the survey . According to these criteria, those children from rural areas attending colleges or working in a large city are not counted as part of the household. The resulting sample truncation excludes those individuals who, on average, are likely to be the most educated or occupationally successful in developing countries. This generates a bias in the estimates of intergenerational educational, occupational, and income mobility. Due to these difficulties , the empirical evidence on social mobility in developing countries is scarcer than in advanced economies. However, some recent considerable progress in data availability is noteworthy. One example is the Indian

intergenerational educational, occupational, and income mobility. Due to these difficulties , the empirical evidence on social mobility in developing countries is scarcer than in advanced economies. However, some recent considerable progress in data availability is noteworthy. One example is the Indian Human Development Surveys (IHDS) of 2004–05 and 2011– 12, as well as the Human Development Profile of India survey of 1993–94, which has allowed economists to study intergenerational income mobility in India.6 Mohammed (2019) finds that intergenerational income persistence in rural India is lower compared to other developing countries. However, t he between -caste coefficient indicates that India is progressing towards cross-caste equality albeit at a relatively slow pace. Concerning educational mobility in India, Azam and Bhatt

5 See Iversen, Krishna and Sen (2021) for more details on different methods to proxy panel data. 6 Other examples worth mentioning are the China Family Panel Studies survey and the Indonesian Family Life survey. Moreover, Alesina et al. (2021) analyse intergenerational mobility in Africa using co -resident (2015) find that for the birth cohorts of 1940 –1985, the average intergenerational correlation in educational attainment in India is 0.52, which suggests significant persistence, although not so strong as in other developing countries. This average correla tion has remained steady over time, though they find different trends at different levels of education. Mobility has increased at the lower end of the fathers’ educational distribution, while has decreased at the top end of that distribution. Similarly, Emran and Shilpi (2015) find different trends at the gender level: educational mobility is steady only for boys while increasing for girls.  Policy recommendations From a policy perspective, social mobility, to support children in their economic success, should be achieved by applying a bundle of inclusive and non -discriminatory policy measures to ensure that all children have access to

increasing for girls.  Policy recommendations From a policy perspective, social mobility, to support children in their economic success, should be achieved by applying a bundle of inclusive and non -discriminatory policy measures to ensure that all children have access to quality education, health care, safe environments, housing, and social protection. Outlining policy recommendations to advance intergenerational mobility is more challenging in developing than in advanced countries, due to a limited understanding of the drivers of social mobility in developing countries, which may include multiple and simultaneous factors such as poor schooling, segmented labour markets, credit constraints, income uncertainty, biased expectations about the returns to education , a scarcity of role models in the neighbourhood, and various forms of group -based discrimination (for a more comprehensive understanding, see Iversen, Krishna and Sen, 2021). Another factor limiting individual opportunities is low aspirations (e.g. , Genicot and Ray, 2017; La Ferrara, 2019). Children belonging to poor households may anticipate that they will have fewer chances than children belonging to wealthy households . This anticipation can push down their aspirations and push them to choose lower levels of human capital investment, thus samples from census data of 26 African countries. Some Latin American countries have also long panel surveys since the Inter -American Development Bank, the World Bank and the United Nations Economic Commission for Latin America and the Caribbean launched the MECOVI project in 1996. ILO Brief 6 Trends in educational and income mobility perpetuating their economic disadvantage. Moreover, if an individual’s aspirations are too far from his/her current standard of life, the incentive to try to close the gap is low as he/she will remain far from their goal . Another factor limiting social mobility and potentially pushing people back into poverty is the high dependence on commodity exports, which can create a volatile economic environment due to fluctuations in global commodity prices . Benefits from

as he/she will remain far from their goal . Another factor limiting social mobility and potentially pushing people back into poverty is the high dependence on commodity exports, which can create a volatile economic environment due to fluctuations in global commodity prices . Benefits from commodity exports are also unequally distribu ted. Finally, the existence of dual labour markets can exacerbate income inequality, as those in the formal sector accumulate wealth and social capital, while those in the informal sector remain marginalized. This inequality limits the ability of individuals and families in the informal sector to move up the social ladder. In this respect, policies paving the way to formalization are crucial for enhancing social mobility and ensuring higher wages, job security, and social benefits also to those at the bottom of the social ladder. In advanced economies, fiscal policies , targeted for disadvantaged groups, can promote inclusivity and social mobility (for more details, see Ernst, Merola and Reljic, 2025). Public investments in childcare facilities and early education programs reduce financial barriers for lowincome families and improve school readiness, setting children on a stronger academic trajectory . Conditional cash transfers tied to school attendance and healthcare visits incentivize families to prioritize their children’s education. Tax credits for l ow-income families free up resources for educational expenses, extracurricular activities, and better living conditions, all of which are linked to improved educational attainment. Other policies can also have negative effects on upward mobility: Blundell et al. (2016) and Albertini et al. (2020), show that in -work benefits and the Earned Income Tax credit (EITC) may affect educational choices and labour market trajectories over the life cycle. In particular, Albertini et al. (2020) show that by making low -skilled jobs more attractive, the EITC reduces the return on education, thereby discouraging some youths from pursuing further studies beyond high school. Some studies warn that universal subsidy schemes have only limited redistributive effects. To promote mobility, public spending in education

more attractive, the EITC reduces the return on education, thereby discouraging some youths from pursuing further studies beyond high school. Some studies warn that universal subsidy schemes have only limited redistributive effects. To promote mobility, public spending in education needs to be properly targeted and generate better access to education, as well as better quality of education mostly for disadvantaged groups (Narayan et al., 2018). Moreover, fostering employment opportunities and fighting discrimination may have beneficial effects on intergenerational mobility. To equalize opportunities in the labour market governments should ease labour market access for dis advantaged people and increase the protection of workers against discrimination by race. Neighbourhood characteristics such as income segregation and concentrated poverty, inequality, racial segregation, quality of schools and crime rates are important determinants of social mobility. Reducing the concentration of poverty and the socioeconomic segregation of neighbourhoods can be particularly beneficial for mobility. An illustrative example is the US “Moving to Opportunity” program which vouchers to help poor families move to better neighbourhoods. This project has highlighted that better neigh bourhoods and local environments benefit long -term outcomes for children, including their incomes as adults. Chetty and Hendren (2018) have shown that low -income boys (girls) who grew up in disadvantaged neighbourhoods earn about 35 per cent (25 per cent) less on average than otherwise similar low-income children who benefited from the mobility program and moved to better areas at the age of 10. Finally, Artificial Intelligence (AI) has the potential to shape social mobility. For instance, AI -powered platforms like personalized learning apps (e.g., Khan Academy, Duolingo) can offer tailored education to people from disadvantaged backgrounds, helping them gain skills and qualification s that improve their career prospects. On the other side, AI can exacerbate existing inequalities because those from disadvantaged backgrounds have limited access to technology and digital literacy and hence could be le ft behind. Investing in digital infrastructure , e xpanding

backgrounds, helping them gain skills and qualification s that improve their career prospects. On the other side, AI can exacerbate existing inequalities because those from disadvantaged backgrounds have limited access to technology and digital literacy and hence could be le ft behind. Investing in digital infrastructure , e xpanding affordable internet access and digital literacy programs is essential to share the benefits of AI more broadly and ensure everyone benefits from AI advancements (Ernst, Merola and Samaan, 2019).

Acknowledgements The author is grateful to Sergei Suarez Dillon Soares and Juan Chacaltana for their helpful comments. All remaining errors are the author's responsibility. ILO Brief 7 Trends in educational and income mobility References Aiyar, Shekhar and Christian Ebeke, 2019. Inequality of opportunity, inequality of income and economic growth. IMF Working Paper 19/34, International Monetary Fund, Washington DC. Albertini, Julien, Arthur Poirier and Anthony Terriau, 2020. The impact of EITC on education, labor market trajectories, and inequalities. Working Papers 2020-36, Gate, University of Lyon. Alesina, Alberto, Sebastian Hohmann, Stelios Michalopoulos and Elias Papaioannou, 2021. Intergenerational mobility in Africa. Econometrica, 89(1): 1– 35. Assaad, Ragui and Mohamed Saleh, 2018. Does improved local supply of schooling enhance intergenerational mobility in education? Evidence from Jordan. The World Bank Economic Review 32 (3): 633–655. Azam, Mehtabul and Vipul Bhatt, 2015. Like father, like son? Intergenerational educational mobility in India. Demography, 52(6): 1929–1959. Binzel, Christine and Jean -Paul Carvalho, 2017. Education, social mobility and religious movements: The Islamic

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