A shadow pandemic of domestic violence: The potential role of job loss and unemployment benefits

Sonia Bhalotra 13 November 2020



Social distancing in the wake of the global pandemic has led to millions of families being ‘locked down’ together in their homes and to widespread job and income losses. This has coincided with a substantial global surge in domestic violence, which the United Nations has described as a “shadow pandemic” (UN Women 2020).

Identifying the behavioural causes is key for devising potential solutions. It seems plausible that both job loss and mobility restrictions have fuelled domestic violence, but there is limited evidence. Our research analyses administrative data from Brazil that pre-date the pandemic, but which demonstrate the relevance of these causes (Bhalotra et al. 2020). Our study also provides the first evidence on the mitigating potential of unemployment benefits.

Mechanisms that potentially link job loss to domestic violence 

The literature on domestic violence suggests alternative mechanisms by which job loss of either partner may influence domestic violence:

  • Job loss can alter the balance of bargaining power within the couple by modifying ‘outside options’ (Anderberg et a.l 2016, Aizer 2010).
  • It can challenge gender stereotypes by changing the relative earnings of the man, and domestic violence can emerge as a manifestation of ‘male backlash’ (Macmillan and Gartner 1999). 
  • Job loss of women can blunt domestic violence motivated by instrumental control (Bloch and Rao 2002, Anderberg and Rainer 2011, Carr and Packham 2020). 
  • Job loss will tend to lead to the couple spending more time together, increasing ‘exposure’ or opportunities for violence (Dugan et al. 2003). 
  • Job loss constitutes a significant shock to household income. This can trigger renegotiation of the allocation of a shrunken pie, with stress lowering the bar for conflict. Previous work has demonstrated an association of job loss with psychological stress and substance abuse (Black et al. 2015, Schaller and Stevens 2015) consistent with job loss tightening liquidity constraints, generating uncertainty about future income and/or creating a sense of failure. Stress can, in turn, lead to domestic violence. Card and Dahl (2011) highlight the relevance of emotional cues for violence, and several studies show that substance abuse is a proximate determinant (Lee Luca et al. 2019).

Data for Brazil

We gained access to court registers for Brazil that contain every domestic violence case between 2009 and 2017. There were two million cases, representing 11% of all criminal justice cases. We linked the plaintiff and defendant in these cases to administrative data containing longitudinal employment records. The data contain about 100 million workers, 60 million employment spells and 10 million layoffs per year. 

Identification of causal relationships

To identify causal impacts of unwarranted individual job loss, we track individuals who lose their jobs in mass layoffs. For each individual suffering job loss, we generate matched controls defined as individuals of the same birth cohort, earnings category, tenure, industrial sector and state, who do not lose their jobs in the same year.

This facilitates identification of dynamic heterogeneous treatment effects (De Chaisemartin and D’Haultfoeuille 2019). It also purges region-industry level shocks, which we test by additionally controlling for municipality-industry-year fixed effects. We conduct a number of robustness checks, on selection, anticipation, judicial lags, missing data and, importantly, the concern that job loss changes reporting behaviour. Our analysis of unemployment insurance exploits a discontinuity in eligibility criteria to achieve identification.

Job loss of men and women leads to higher domestic violence

Male job loss results in a roughly 30% increase in the chances that a man perpetrates violence. Female job loss delivers a percentage increase in the chances that a woman is victimised that is almost twice as large.

These effects persist through the three years in our frame. They hold across the distribution of age, education and income. The same pattern of results emerges when we use data identifying couples. We find the same pattern when we measure domestic violence by women’s use of public shelters rather than as judicial cases. 

The results are unlikely to be driven by reporting bias

A common problem with analysing data on reported acts of violence is that it can be difficult to disentangle changes in the occurrence of violence from changes in reporting behaviour. Women may be more likely to report violence when the man loses his job, and less likely to report it when they lose their jobs – for example, because they are financially reliant on their partners. 

Consider the direction of the likely bias. If job loss influences reporting in the hypothesised direction and reporting drives our results, then we expect to see an increase in reported violence following male job loss, but a decrease following female job loss. Since we find an increase in reported violence (and use of public shelters) following female job loss, it seems unlikely that this result is driven by reporting. But it remains possible that the results for male job loss are. 

We conducted further checks for male job loss. The most informative involves restricting the sample to in flagrante cases in which the perpetrator is ‘caught in the act’, so the case is filed without the woman having to report. Male job loss continues to be followed by a large increase in domestic violence in this restricted sample.

The shock of income loss, bargaining, and exposure seem to be relevant mechanisms

We propose the following explanation. Job loss of either partner constitutes a major shock to household income. This disturbs the equilibrium, leading the couple to renegotiate allocation of a tighter household budget, creating grounds for conflict. Additional stresses deriving from income uncertainty and a sense of unworthiness potentially aggravate this. At the same time, the couple tends to spend more time together if either is unemployed, and this increases exposure or opportunities for violence.

The manner in which any conflict is resolved depends on which partner loses their job. If the woman loses her job then, in line with the household bargaining model, she is more likely to be victimised. But if the man loses his job, then he is less likely to perpetrate violence. This can explain our finding of a larger increase in domestic violence following female compared with male job loss.

On its own the bargaining model would seem inconsistent with our findings because it predicts a decline in domestic violence following male job loss. But combined with our hypothesis that an income shock increases the potential for conflict, it helps explain the findings.

Unemployment benefits compensate income losses but can increase exposure

Unemployment is synonymous with a decline in income and an increase in time at home, and our estimates capture the joint effect of these two changes. With a view to isolating the income the role of income loss, we exploit experimental variation generated by unemployment insurance (UI) eligibility rules in Brazil. Workers who have previously received benefits in Brazil need to have at least a 16-month gap before they can claim benefits again (Gerard et al 2019). We compare the risk of domestic violence among unemployed men who are just eligible versus those who are just ineligible for UI using a regression discontinuity design. Unemployment benefits in Brazil cover, on average, about 80% of former earnings and last three to five months. 

While benefits are being paid, men eligible and ineligible for UI are equally likely to commit domestic violence. Once benefits expire, eligible men are more likely to commit violence. The reason is that eligibility lengthens unemployment durations (Katz and Meyer 1990, Lalive 2008), increasing exposure. While benefits are being received, exposure effects are offset by an income effect. Overall, while we have a natural experiment that, in principle, identifies the impact of a policy designed to relax income constraints, in practice UI has behavioural effects that reintroduce the relevance of time spent at home.

In a separate exercise using all men, we confirm that income transfers mitigate by leveraging the fact that severance pay and UI increase with tenure. We find impacts of job loss on domestic violence attenuate at high tenure.

The upshot for policy 

Our main findings are that job loss influences domestic violence first through generating an income shortfall, and second by increasing exposure. So, the ideal policy intervention would compensate the income shortfall and get people out of the home and back to work. 

Unemployment benefits can help but need to be combined with active policies aimed at getting the unemployed back to work (e.g. through training or support with job search). Experiments conducted in Kenya (Haushofer et al. 2019) and Mali (Heath et al. 2020) show that cash transfers to men reduce violence against female partners, highlighting the potential for welfare payments to be effective if incentive effects can be avoided by design. 


As the pandemic has led to earnings losses and to families spending more time together, our research potentially illuminates the recent surge in domestic violence. 

Media coverage of the Covid-19 surge has highlighted the role of exposure. Brazilian official Luciana Azambuja recently wrote in the popular press that “[s]ocial isolation will make families spend more time together. This can generate more conflicts.” In addition to forcing couples together for longer, lockdown has limited contact with social networks and this may have contributed to domestic violence (Gelles 1983, 1993, Usher et al. 2020). Etheridge and Spantig (2020) find a deterioration in mental health in the UK during the pandemic that is larger among women, and the decline in social interactions appears to be an important factor. 

Lockdown has been eased in many countries. But unemployment rates look set to rise, potentially increasing exposure even in the absence of mobility restrictions. Unemployment also tightens income constraints. Our research therefore suggests that domestic violence may persist beyond lockdown.

The policy infrastructure has been primarily concerned with providing support to victims in the shape of shelters, counselling and protection orders. Interventions designed to prevent domestic violence have focused on the economic empowerment of women, though they sometimes misfire (Angelucci 2008, Heath 2014, Bhalotra et al. 2019, Tur-Prats 2019, Estefan 2019, Kotsadam and Villanger 2020, Carr and Packham 2020). Our research suggests the relevance of compensating both men and women for income losses.


Aizer, A (2010), “The Gender Wage Gap and Domestic Violence”, American Economic Review 100: 1847–1859.

Anderberg, D, H Rainer, J Wadsworth and T Wilson (2016), “Unemployment and Domestic Violence: Theory and Evidence”, The Economic Journal 126: 1947–1949.

Anderberg, D and H Rainer (2011), “Economic Abuse: A Theory of Intrahousehold Sabotage”, Journal of Public Economics 97: 282-295.

Angelucci, M (2008), “Love on the Rocks: Domestic Violence and Alcohol Abuse in Rural Mexico”, The B.E. Journal of Economic Analysis and Policy 8(1).

Bhalotra, S, D Britto, P Pinotti and B Sampaio (2020), “Job Displacement, Unemployment Benefits and Domestic Violence”, mimeo, July (available from the authors).

Black, S E, P J Devereux, and K G Salvanes (2015), “Losing heart? The effect of job displacement on health", ILR Review 68(4): 833-861.

Bloch, F and V Rao (2002), “Terror as a Bargaining Instrument: A Case Study of Dowry Violence in Rural India”, American Economic Review 92(4): 1029-1043.

Card, D and G Dahl (2011), “Family Violence and Football: The Effect of Unexpected Emotional Cues on Violent Behavior”, The Quarterly Journal of Economics 126(1): 103–143.

Carr, J and A Packham (2020), “SNAP Schedules and Domestic Violence”, Journal of Policy Analysis and Management.

De Chaisemartin, C, and X D’Haultfoeuille (2020), “Two-way fixed effects estimators with heterogeneous treatment effects", American Economic Review, forthcoming.

Dugan, L, D Nagin and R Rosenfield (2003), “Exposure Reduction or Retaliation? The Effects of Domestic Violence Resources on Intimate‐Partner Homicide”, Law and Society 37(1): 169-198.

Estefan, A (2019), “Female Labour Market Access, Divorce, and Intra-Domestic Violence: Evidence from Mexico”, mimeo, UCL.

Etheridge, B and L Spantig (2020), “The Gender Gap in Mental Well-Being During the Covid-19 Outbreak: Evidence from the UK”, ISER Working Paper No 2020-08.

Gelles, R J (2007), “Family violence”, in D J Flannery, A T Vazsonyi, and I D Waldman (eds), The Cambridge handbook of violent behavior and aggression, Cambridge University Press. 

Gerard, F, M Rokkanen, and C Rothe (2019), Bounds on treatment effects in regression discontinuity designs with a manipulated running variable", Technical Report, National Bureau of Economic Research.

Haushofer, J, C Ringdal, J P Shapiro, and X Y Wang (2019), “Income Changes and Intimate Partner Violence: Evidence from Unconditional Cash Transfers in Kenya", NBER Working Paper No. 25627.

Heath, R (2014), “Women’s access to labor market opportunities, control of household resources, and domestic violence: Evidence from Bangladesh”, World Development 57: 32–46.

Heath, R, M Hidrobo and S Roy (2020), “Cash transfers, polygamy, and intimate partner violence: Experimental evidence from Mali”, Journal of Development Economics, March.

Katz, L F and B D Meyer (1990), “The impact of the potential duration of unemployment benefits on the duration of unemployment," Journal of Public Economics 41(1): 45-72.

Kotsadam, A and E Villanger (2020), “Jobs and intimate partner violence – Evidence from a Field Experiment in Ethiopia”, CESifo Working Paper 8108.

Lalive, R (2007) “How do extended benefits affect unemployment duration? A regression discontinuity approach", Journal of Econometrics 142(2): 785-806.

Lee Luca, D, E Owens and G Sharma (2019), “The Effectiveness and Effects of Alcohol Regulation: Evidence from India”, IZA Journal of Development and Migration 2019: 9-4.

Macmillan, R and R Gartner (1999), “When She Brings Home the Bacon: Labor-Force Participation and the Risk of Spousal Violence against Women”, Journal of Marriage and Family 61(4): 947.

Schaller, J, and A H Stevens (2015), “Short-run effects of job loss on health conditions, health insurance, and health care utilization”, Journal of Health Economics 43: 190-203.

Tur-Prats, A (2019), “Unemployment and Intimate-Partner Violence: A Cultural Approach”, mimeo, University of California Merced. 

UN Women (2020), “COVID-19 and Ending Violence Against Women and Girls”, briefing.

Usher, K, N Bhullar, J Durkin, N Gyamfi and D Jackson (2020), “Pandemic‐related behaviours and psychological outcomes; A rapid literature review to explain COVID‐19 behaviours", International Journal of Mental Health Nursing 20 April.



Topics:  Covid-19 Gender Labour markets

Tags:  COVID-19, job loss, domestic violence, lockdown

Professor of Economics, University of Essex


CEPR Policy Research