Domestic violence affects one in three women in their lifetime
Domestic violence affects one in three women in their lifetime worldwide. Women who suffer domestic violence experience serious adverse health consequences including injury, emotional distress, suicidal thoughts, physical symptoms of severe illness, sexually transmitted diseases, and unintended pregnancies (see, for example, Campbell 2002, Coker et al. 2002). The cost of domestic violence to an economy in terms of victim’s suffering, medical bills, lost productivity, judicial expenditures, and the lost productivity from the incarcerated offender, is massive.1 In Dhamija and Roychowdhury (2018), we provide the first causal analysis of the impact of women’s age at marriage on their exposure to domestic violence – and more specifically spousal violence. Our study uses newly available nationally representative data from India, where according to a 2014 BBC report, one incident of domestic violence is reported in every five minutes (which, of course, is only a fraction of how much actually occurs).
In theory, the causal impact of women's age at marriage on domestic violence could be either negative or positive. On the one hand, women who marry early are likely to be unassertive, naive, and less resistive to domestic violence, and hence ‘safer’ to victimise. They are also likely to be less educated since early marriage often interrupts the accumulation of formal education for women due to family responsibilities (Field and Ambrus 2008). This limits their options outside marriage and the economic and social resources at their disposal, influencing their empowerment within marriage (Farmer and Tiefenthaler 1996, Stevenson and Wolfers 2006, Aizer 2010, Hidrobo and Fernald 2013, Erten and Keskin 2018). All these factors would suggest a negative relationship between women’s age at marriage and domestic violence. On the other hand, although women who marry late might be better placed to advocate for their preferences in the spousal household, be more resistive to domestic violence, and have greater bargaining power, they might face a stronger backlash from their partners (Field et al. 2016). Moreover, since education is positively correlated
Data and empirical strategy
We use data from the National Family Health Survey of India (NFHS), 2015-16. This survey includes detailed information on the prevalence of domestic violence, gender role, health, and marriage market indicators. As noted by Golder et al. (2016), the NFHS collects information on domestic violence with utmost caution following both Indian and international guidelines (more specifically the World Health Organization (WHO) ethical
The main empirical challenge in identifying the causal effect of age at marriage on
To address this issue, we employ the empirical strategy proposed by Field and Ambrus (2008), who ‘instrument’ women’s age at marriage by their age at menarche. This instrument is motivated by the observation that has been made by sociologists and anthropologists that parents become extremely anxious to get their daughters married once they have reached menarche, partly to avert any unwanted pregnancies. Thus, variation in the age at menarche generates a quasi-random difference in the age at which a girl enters the marriage market.
Our results indicate a strong negative effect of women's age at marriage on less severe and severe forms of physical violence. Specifically, we find that a delay in women's marriage by a year causes the probability of less severe physical violence to decrease by 7 percentage points and that of severe physical violence to decrease by 4 percentage points.3 However, the effect of women’s age at marriage on sexual violence and emotional violence are not statistically significant. If one is willing to extrapolate these results from our sample to the entire country, the implications of our findings are extremely striking. Given that the female population in India is 586 million (2011 Census) of whom 50% are married, and that 25% and 6% of these married women are exposed to less severe and severe forms of domestic violence respectively,4 our findings imply that a nationwide delay in women’s age at marriage by a year would cause the number of women exposed to less severe physical violence to fall from 73 million to 53 million, and the number of women exposed to severe physical violence to fall from 18 million to 6 million. Our findings, therefore, confirm the relevance of the existing conditional cash transfer programmes and other social policies that seek to delay marriages of women in India (for example ‘Kanyashree Prakalpa’ programme in West Bengal, ‘Apni Beti Apni Dhan’ programme in Haryana, etc.) and provides rationale for designing newer ones, in order to reduce the prevalence of domestic violence.
- According to an article published in The Washington Post (22 February 2018) in the US
alonethis cost is about US$460 billion annually.
- Late marriage, by itself, carries a lot of taboos especially for women in India. Women who do not marry young are perceived as failures (see, for example, https://www.bbc.com/news/magazine-26341350 and https://medium.com/@Michael_Spencer/leftover-women-how-millennial-women-must-fight-tradition-d0170c5b6e62). On top of marrying late, if a woman also seeks divorce after marriage, it is likely that the social stigma would be higher for such a woman compared to someone who marries at the ‘right age’ (or marries early) because the first woman is already at ‘fault’ for getting married late.
- Both these effects are significant at 5% level of significance.
- The estimates of the prevalence of less severe and severe forms of domestic violence are based on our analysis sample.
- Aizer, Anna (2010), “The Gender Wage Gap and Domestic Violence”, American Economic Review, 100(4): 1847-1859.
- Bloch, Francis and Vijayendra Rao (2002), “Terror as a Bargaining Instrument: A Case Study of Dowry Violence in Rural India”, American Economic Review, 92(4): 1029-1043. Available here.
- Bobonis, Gustavo J, Melissa Gonzalez-Brenes and Roberto Castro (2013), “PublicTransfers and Domestic Violence: The Roles of Private Information and Spousal Control,” American Economic Journal: Economic Policy, 5, 179-205. Available here.
- Campbell, Jacquelyn C (2002), “Health Consequences of Intimate Partner Violence”, Lancet, 359(9314): 1331-1336.
- Coker, Ann L, Keith E Davis, Ileana Arias, Sujata Desai, Maureen Sanderson, Heather M Brandt and Paige H Smith (2002), “Physical and mental health effects of intimate partner violence for men and women”, American Journal of Preventive Medicine, 23(4): 260-268. Available here.
- Dhamija, G and P Roychowdhury (2018), ‘The causal impact of women’s age at marriage on domestic violence in India’, SSRN Working Paper. Available here.
- Eswaran, Mukesh and Nisha Malhotra (2011), “Domestic Violence and Women's Autonomy in Developing Countries: Theory and Evidence”, Canadian Journal of Economics, 44(4): 1222-1263.
- Erten, Bilge and Pinar Keskin (2018), “For Better or for Worse?: Education and the Prevalence of Domestic Violence in Turkey”, American Economic Journal: Applied Economics, 10(1): 64-105.
- Farmer, Amy and Jill Tiefenthaler (1996), “Domestic Violence: The Value of Services as Signals”, American Economic Review, 86(2): 274-279.
- Field, Erica and Attila Ambrus (2008), “Early marriage,
ageof menarche, and female schooling attainment in Bangladesh”, Journal of Political Economy, 116(5): 881-930.
- Field, Erica, Rohini Pande, Natalia Rigol, Simone Schaner and Charity T Moore (2016), ‘On Her Account: Can Strengthening Women's Financial Control Boost Female Labor Supply?’, Working Paper.
- Golder, Sakti, Nisha Agrawal, Ranu Kayastha Bhogal, Prabhakar Reddy Tada, Rajini R Menon, Julie Thekkudan, Mary Thomas and Ritesh Laddha (2016), ‘Measurement of Domestic Violence in NFHS Surveys and Some Evidence’, Oxfam India.
- Hidrobo, Melissa and Lia Fernald (2013), “Cash Transfers and Domestic Violence”, Journal of Health Economics, 32(1): 304-319.
- Stevenson, Betsey and Justin Wolfers (2006), “Bargaining in the Shadow of the Law: Divorce Laws and Family Distress”, Quarterly Journal of Economics, 121: 267-288.