The lens applied by feminist economists has gained much traction in times of global crises, including the Covid-19 pandemic where globally. The pandemic has exacerbated inequalities across socio-economic indicators, and women have been disproportionately impacted. Implicit in this are cultural norms that influence and determine the persistence of gender inequalities in different countries.
It calls to reason that key economic and development indicators that might potentially inform policy apply this lens of analysis, yet we often fail to do this. The measure of “intergenerational mobility” is an example of a measure of inequality that might fail to consider nuances of gender inequality in its measurement and interpretation.
What is Intergenerational Educational Mobility?
The measure of intergenerational mobility has gained much popularity in inequality literature as a means for gauging ‘inequalities of opportunity’ within and among populations. Measures of intergenerational mobility compare incomes of individuals and their parents. Where the correlation is statistically significant, we can say that socio-economic background is a strong determinant of socio-economic performance of the next generation. In other words, intergenerational mobility is “low”; and there is high persistence of disadvantage, resulting from inequality of opportunities.
Intergenerational educational mobility (herafter, mobility) is commonly used as a proxy of the ideal income mobility measure, due to unavailability of quality income data in many developing countries. It measures the extent that an individual’s educational attainment can be explained by their parents’ education, reflecting ability to pursue opportunities to improve economic status.
Women in India, compared to their male counterparts, are found to have lower mobility, exacerbated by belonging to lower-caste groups, conservative religious communities, and rural (compared to urban) regions. Given what we know about caste, religious and regional inequalities in India, such results lead us to believe mobility is a valid measure of inequality.
A cause for concern is however, the assumptive link between mobility and equality of opportunity - premised on the human capital approach- when comparing populations or population sub-groups on absolute mobility. Few have empirically quantified or tested this assumption, while questions are increasingly being raised about its applicability to low-income and developing contexts.
For women in India, the human capital approach is held ransom to cultural values of ‘women’s purity’ and ‘status’ that work together to protect patriarchal notions that women belong at home and men at work. Women who participate in paid-work outside the household disproportionately belong to the lowest caste groups and the most economically vulnerable households. When economic necessity dictates behaviour, it hardly reflects exercising of agency. This is further true when these women are also most likely to participate in lower-paying, dangerous and exploitative jobs.
The Research Question
In this study, I question the validity of mobility as a measure of women’s inequality, and more specifically equality of opportunity, in the context of India. To assess this, I break down a key implication of the measure– those with greater mobility in a population should be more able to pursue opportunities to improve their economic status. The existence of such an association, or lack thereof, would reflect the efficiency of mobility as a measure of women’s inequality.
Using the nationally representative dataset IHDS-2 (Indian Human Development Survey) conducted in 2011-12, I test the association between two simple measures of IEM and two indicators that represent a women’s ability to pursue a higher economic status, on a population of approximately 39,000 women (where educational data was available for the woman and her father).
Variables of mobility used are Intergenerational Regression Coefficient (IGRC) and a categorical variable of absolute mobility that splits the population into upward mobility (where women had higher education than their father) downward mobility (where women had lower education than their fathers) or no mobility (where educational attainment was the same).
The dominant view in conceptualization of equality of opportunity was proposed in Roemer (1998), where equality of opportunity is desirable as individuals’ attainment of well-being, economic status and other achievements is based only on factors reflecting effort, cognitive ability and choice. I equate this to the concept of ‘agency freedom’. Two indicators capturing economic agency and agency of women to be physically mobile were accordingly selected, representing actions that any individual might value and pursue, in the eyes of a neutral observer.
Keeping in mind the sensitivity of such measures to treatment of variables, this study only suggests possible mixed associations between women’s mobility and indicators of their agency, with a call to further investigate the validity of this measure for women’s inequality in a country like India.
Findings
Two crucial findings of this study warrant discussion.
The first finding is that the association proposed in literature between women’s mobility and equality of opportunities premised on the human capital approach, does not appear to hold for women in India. It is worthwhile to note that solely a positive association between women’s mobility and agency outcomes would confirm this link. Instead, this study finds mixed results.
Women with high economic agency and physical mobility had significantly lower intergenerational mobility (reflected by higher IGRC values) than women with low agency. On the categorical measure of absolute mobility, women with upward mobility, compared to the rest were least likely to be allowed to participate in paid-work or be physically mobile, followed by women with no change, and downward mobility. This association is found to differ across caste and religious groups, with a sharp decline in magnitude on the introduction of a geographical dummy (state or province).
However other theories, more accurately placed in the cultural context, might serve to link mobility and women’s equality of opportunity. Educated women are desired in Indian society for their perceived superior ability to fulfil socially expected roles of household-management and raising children. Based on this, if women with upward mobility are able to leverage educational attainment to marry into households that are educationally and economically better-off than their natal homes this would confirm both, the positive association of women’s mobility and economic status, and the efficiency of mobility as a measure of women’s inequality in India.
This study then considers an alternate model based on assortative mating. Assortative mating theories suggest individuals with highly-valued characteristics will partner together, and those with lower-valued characteristics will partner together, which increasingly happens in India. Such a practice could link women’s educational attainment and economic status post-marriage. It further has implications for intergenerational inequality as it can lead to a concentration of wealth within sections of society, whose advantages would be transmitted and reproduced through their children.
The second finding of this study is that women’s mobility was found to be positively associated with the educational and economic status of their post-marital households. To measure this I looked at the association of the categorical mobility variable on relative educational and economic status of a woman’s natal and post-marital households.
Women with upward mobility belong to post-marital households that are educationally better-off than women in the rest of the sample, while women with no change in mobility belong to the poorest post-marital households, educationally and economically. Finally, significantly more women with downward mobility report having natal families that were economically better-off than their post-martial household at the time of marriage. We know from evidence however, that with the exception of the uppermost income quintile, higher social and economic background does not result in greater agency for women.
What does Intergenerational Educational Mobility Truly Capture About Women’s Inequality in India?
There is a need to disentangle what might explain both these findings, and how they might influence the interpretation of intergenerational educational mobility.
For women with upward mobility, some part of the inverse association between mobility and agency might be explained by them living in socioeconomically better-off households that might also adhere to more traditional and patriarchal attitudes towards women.
These might be the economically better-off post-marital households we find women with upward mobility belong to in our model of assortative mating. Interconnected with the above, having a natal family that is of relatively lower status to the husband’s family might adversely influence women’s bargaining power in the post-marital household, and vice-versa. The latter might explain why women with downward mobility had greater agency.
It is also well established that intra-household resource allocation in countries like India greatly disadvantages women. Therefore, household-level analysis of women’s post-marital household might not accurately reflect her individual economic standing.
The link drawn through the theory of assortative mating might then also reflect lower agency of women.
Mobility is then simultaneously associated with higher economic status of women’s households, and higher restrictions imposed on women. This puts to question whether the current interpretation of mobility captures the whole spectrum of women’s subordination in India, or rather what we are measuring when we say “inequality”.
In the absence of greater contextualization of definitions and roots of women’s inequality, our interpretation of measures of the same can be misleading.
Nisha Vernekar is a Team Lead in Inclusive Education at Vidhi Centre for Legal Policy, New Delhi, India. You can reach her on Twitter or nisha03100@gmail.com
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