Two seemingly opposite studies on the Mother-In-Law effect

The “Kyunki” Studies Duo (IYKYK)

Aditi Roy Bhowmick
3 min readSep 11, 2022

Two remarkable studies on the effect of a coresident mother-in-law on outcomes of the daughter-in-law in the Indian context dropped last year. Both made waves. However, their findings are seemingly at odds with each other. On one hand, Anukriti et al. find that a coresident mom-in-law (or “mummy-ji”) acts as a gatekeeper of patriarchy in Jaunpur, Uttar Pradesh. Specifically, “ co-residence with the mother-in-law restricts her daughter-in-law’s mobility and ability to form social connections outside the household, especially those related to health, fertility, and family planning.” On the other hand, Divya Pandey and Madhulika Khanna find “a 10 percent decrease in women’s labor force participation following their mother-in-law’s death, while no change following the father-in-law’s death”. They propose that the channel of impact is that mom-in-law helps with sharing the childcare burden and housework.

But wait, how is it possible for both things to happen? How come mom-in-law is preventing mobility of daughter-in-law and yet increasing her female labor force participation?

My suspicion is that the devil is in the details.

Disclaimer: The purpose of this article is not to discredit either of these truly fabulous studies as much as a taking stock/reconciliation effort.

First, I think it is important that the bad mom-in-law effect comes from a sample in rural Uttar Pradesh, specifically Jaunpur district. On the other hand, good mom-in-law effect is seen in a study with a nationally representative sample. However, I do not see a disaggregation of results between rural and urban areas. This may be unnecessary since they have all sorts of fixed effects but there may be interesting heterogeneity … based on my fast and dry exploration of the IHDS!

Employed = 0 if daughters in law report either housework or unemployment as their primary activity; Non-cores: Non-coresident MIL, Cores: Coresident MIL

These reverse directions of effects across rural/urban areas holds even if I set up the Y axis as share of women with non-zero earnings…

Second, how we define the Y axis is non-trivial. For instance, if I throw out Allied agriculture, Ag wage labor, Non-ag wage labor, Artisan/Independent work, Small business (which could often be home-based & doesn’t necessarily depend on mobility outside the home) and organized business out of the definition of employed, in effect limiting employment to salaried/professional women, the picture changes.

When I read the good mom-in-law effect on FLFP paper, the image I had in my head was of a woman going to work at a bank, school, 9–5 job in an urban area. I was not thinking household production of patchwork quilts or woven dupattas for instance. I was also not thinking of agriculture wage labor. There is also “cultivation” on own farm to consider, which is barely an agency-inducing occupation since the woman more often than not doesn’t get paid directly.

Finally, picture a scenario where there is a coresident mummy-ji, a drunk good-for-nothing husband, and kids. The daughter-in-law needs to go do her cleaning jobs to make enough money to make ends meet. I’m not so sure that situation is emancipatory either.

To sum up, I think the two MIL papers are excellent. Forever grateful to the authors for opening this can of worms with careful empirical analyses. I think their seemingly opposite findings may have to do with the rural versus rural and urban inclusive sample, or even the geographic restriction. I also think that findings may vary based on how we are defining employment.

As always, I may be entirely wrong and would love inputs.


  • IHDS, 2012.
  • Khanna, M., & Pandey, D. (2021). Reinforcing gender norms or easing housework burdens? the role of mothers-in-law in determining women’s labor force participation.
  • Anukriti, S., Herrera‐Almanza, C., Pathak, P. K., & Karra, M. (2020). Curse of the Mummy‐ji: the influence of mothers‐in‐law on women in India. American Journal of Agricultural Economics, 102(5), 1328–1351.