One of the main theoretical arguments for social justice is the assumption that the chances of “winning” or “losing” in the socioeconomic development process should not be solely determined by family background. Instead, personal effort and the ability to make choices ought to be the pillars that shape our chances to succeed or fail.
For researchers, however, differentiating between the impact of family background and personal effort is not a straightforward analytical exercise. Take the case of education: since well-off parents tend to invest more in their children’s education, educational attainment does not simply reflect one’s ability, it is also the product of cumulative investments made across generations. The same logic applies to income, occupation, and other metrics of socioeconomic status.
Intergenerational mobility is the process of moving up and down the socioeconomic ladder across generations. It is important to examine this when trying to understand up to what extent inequality of opportunities can be transferred from parents to children.
There is also a growing initiative to compile comparable intergenerational mobility data to examine whether mobility is more or less pronounced in some countries, identify commonalities among countries that share an ideal mobility regime, and feed this information into public discussion and policy-planning to minimize unequal distribution of opportunities.
From a data collection perspective, estimating intergenerational mobility requires either longitudinal information that track people over time, or retrospective information about parental income, occupation, or education. Ensuring that the data are comparable across countries entails adopting standardized definitions and metrics. This is challenging due to the high cost of collecting panel data and recall bias issues surrounding the collection of retrospective information about parental characteristics.
Nevertheless, efforts to compile comparable estimates of intergenerational mobility are underway as the importance of this research becomes increasingly recognized. One such effort is the World Bank’s Global Database on Intergenerational Mobility, which contains estimates of intergenerational mobility for 148 economies by 10-year cohorts, covering individuals born between 1940 and 1989.
We have reviewed some of the stylized patterns depicted from estimates of intergenerational mobility in education for individuals born between 1970 and 1979 in 22 Asia-Pacific economies. A more detailed picture of intergenerational mobility across the world is provided by the World Bank report Fair Progress? Economic Mobility across Generations Around the World.
We observed longer schooling from parents to children in almost all economies from this sample. But by how much does an additional year of schooling of a parent impact the educational attainment of his/her children?
The intergenerational mobility estimates—measured by regressing each person’s number of years of education on his/her parents’ education—aim to capture this impact. Higher values suggest higher levels of intergenerational persistence, and hence lower levels of (relative) intergenerational mobility.
We find considerable variation in the estimates across the 22 economies. Uzbekistan, the Republic of Korea, Australia, Azerbaijan, and New Zealand show the least impact of parental education on children’s education; on the other hand, Timor-Leste, Pakistan, Nepal, India, and the Lao People's Democratic Republic have the lowest levels of intergenerational mobility.
Notably, most of the economies with low mobility also have relatively lower educational outcomes for both parents and children, while in those with high mobility—except for Azerbaijan and Uzbekistan—both parents and children are above median average years of schooling.
National wealth may have played a big role in this trend. There is evidence suggesting that richer economies tend to have higher levels of intergenerational mobility in education due to their greater capacity to invest in education.
In the sampled 22 economies, about 35% to 57% of children whose parents’ educational attainment belong to the upper 25% (i.e. the “education-rich” group) have stayed in the same quartile as their parents’, while 15% to 43% of them have fallen to the bottom half. On the other hand, a large portion of children (54% to 73%) whose parents are from the bottom half (i.e. the “education-poor” group) have remained in bottom half (from 54% to 73%), but 27% to 46% of them have managed to reach the top quartile.
Finally, gender differences show mixed results. A lower median level of intergenerational mobility is observed among men, consistent with the reversal of gender inequality in education that started in 1970s. However, cross-country variation is higher among women, and females from more than half of the sampled economies have lower mobility.
In economies where overall average mobility is already relatively low, females are also less mobile than their male counterparts.
Our findings underscore that parental characteristics are not the sole determining factor of one’s future mobility prospects. In Asia and the Pacific, there is evidence of intergenerational mobility in education, with richer economies showing generally higher levels of mobility.
Interestingly, the chances of children with “education-poor” parents to climb the education ladder are not so different among economies with low and high overall mobility.
However, better intergenerational mobility prospects in education may not necessarily be a pre-determined outcome for economies that are moving into a higher income group. To ensure that family background does not become a binding constraint, economic growth should be complemented by policies that promote greater access to high quality education for all – especially for those who do not come from a privileged family background.