What do we need to know about social mobility in the Global South?
The volume, Social Mobility in Developing Countries: Concepts, Methods and Determinants, brings together leading scholars from several disciplines to advance research practice on social mobility. Three sets of motivations guide this joint effort: identifying important knowledge gaps; bringing together innovations and improvements in research practice; and offering policy advice to enhance social mobility in developing countries. In this brief, we identify the major knowledge gaps and propose ways to overcome them.
Three major knowledge gaps for the Global South
A comprehensive examination of social mobility studies reveals major knowledge gaps on developing countries.Three major limitations stand out.
First, the data used in high-income settings is not available in most of the Global South. Most countries lack long-term longitudinal surveys needed to study intergenerational mobility
Second, where surveys include information about parental characteristics, they usually exclude women or mothers
Third, the current conventional methods do not produce an adequately complete picture of the levels and drivers of social mobility in developing countries
First, there is not enough data to examine social mobility across the countries of the Global South using conventional measures. Furthermore, these measures, used to study high-income contexts, are not necessarily meaningfully comparable in or across Global South countries (and over time), even if there were enough data. Second, data on women and women’s characteristics are largely absent from intergenerational data. This prevents the study of intergenerational mobility — whether for education, occupation, income, status, or some other characteristic — of daughters or sons relative the positions of their mothers, instead relying solely on data about fathers. This is less than half the picture. Finally, the methods economists use to understand the drivers of social mobility are less useful in Global South contexts, meaning that without methodological advancements, we will not know the primary determinants of social mobility levels in the Global South.
Overcoming data limitations
Without better data, a clear understanding of which countries in the Global South are doing well (and which are not) at increasing levels of intergenerational mobility will not emerge. It may take a considerable amount of time before researchers who work on social mobility in low- and middle-income countries get access to the type of administrative tax and other data that form the bedrock of social mobility analysis in high-income countries; for example, the pioneering work by Chetty et al. (2014) on intergenerational mobility in the United States.
Some recent gains in data availability are noteworthy. The nationally representative Indian Human Development Surveys (IHDS) of 2004–05 and 2011–12, as well as the Human Development Profile of India survey of 1993–94, — and the panel study these databases support — has allowed economists to study intergenerational income mobility in India (see Mohammed 2019). This effort is additionally useful for measuring other kinds of mobility, since the survey instrument includes retrospective questions that allow for the measurement of educational and occupational mobility, too.
Including such questions on parental educational level and occupational status should be routinely asked in household and labour force surveys in developing countries. However, given the data gap, we need new, innovative ways to exploit existing, nationally-representative datasets. For instance, a study of educational mobility in sub-Saharan Africa by Alesina et al. (2019) uses microdata extracted from 68 national censuses from 26 countries to demonstrate some possibilities. There are further possibilities in alternate methods, for example, we can look at the representation of individuals from lower-income groups in prestigious occupations — such as engineering, law, medicine — for insights about social mobility. The chapter by Krishna and Rains presents other innovations that have been gainfully used to understand patterns of social mobility.
Bringing women back into the analysis of social mobility
The second gap relates to gender differences in social mobility. As Luke makes clear, and both Torche and Vaid reiterate, we know very little about mother–daughter mobility, even compared to the limited information on father–son mobility in low- and middle-income countries (but see the chapter from Li for a rich characterization of social mobility among women in China). The IHDS data for India, for all its other strengths, does not inquire into the educational levels and occupational status of respondents’ mothers, asking only about their fathers’ educational level and occupational status.
This is a deeply unsatisfactory state of affairs, both because it is one-sided and incomplete, and because at a time when an increasing number of women are progressing through secondary schooling and on to university, and female labour force participation has increased sharply, we need to know: Are the opportunities of economic and social progress available to daughters substantially different from those of their mothers (or brothers)? How does social mobility among women differ across regions, social class, race, and ethnicity within countries? What theoretical perspectives can explain these differences? Household and labour force surveys need to be modified, as has been done in Cameroon, to gain information about daughters’ and mothers’ educational and occupational achievements.
Furthermore, ethnographic methods, such as genealogies and life histories, need to be employed for generating deeper insights about the constraints that daughters face in upward mobility as compared to their male siblings (see the chapter by Vaid).
What drives changes in social mobility
The third critical knowledge gap is in our understanding of the drivers of social mobility in developing countries. As the chapters by Piraino, Berhman, Krishna and Rains, Mani and Riley, and Funjika and Gisselquist show, there is a multiplicity of environmental factors that help explain why improving intergenerational mobility is a greater challenge in the Global South.
For a child born in a slum in Mumbai, Nairobi, or Rio de Janeiro, there can be multiple and simultaneously operating determinants of weak intergenerational mobility. A short list includes poor schooling, lack of well-paid jobs, a scarcity of role models in the neighbourhood, and various forms of group-based discrimination.
Methods commonly used by economists to study the determinants of intergenerational mobility (such as experimental or quasi-experimental methods) attempt to identify the causal effect of one factor relative to others, and these methods are less useful in situations where complex and interactive causes inhibit social mobility. Historical methods can be more revealing in some kinds of situations (see the chapter from Clark) in addition to case-studies of individual countries or regions that have witnessed recent spurts in social mobility (see the chapter on China from Li).
Crucial steps to overcome the major knowledge gaps
So what needs to be done to address the knowledge gaps in social mobility studies for developing countries? First, there has to be a concerted effort by multilateral development agencies such as the World Bank and bilateral aid agencies in collaboration with national statistical organizations to collect reliable data on incomes, educational levels, and occupations over multiple generations, especially for low-income countries.
Major multilateral efforts are needed to improve data collection — and its quality and availability — in the Global South
Surveys need to be improved to enable a picture of intergenerational mobility that includes all genders
Research on social mobility needs to rely on a greater diversity of methods in the future
Second, questions on incomes, educational levels, and occupations for mothers and daughters similar to the questions asked about fathers and sons should be routinely asked in labour force and household surveys. Finally, there needs to more innovation in research methods, combining qualitative methods such as life histories and archival resources with quantitative methods such as quasi-experiments to understand the drivers of social mobility.