metadata: authors: 0: author: Ghose,Devaki
1: author: Pandey,Divya
count: India
docna: 0: docna: The Eﬀects of Communal Violence on Women’s
            Marital Outcomes
docty: Policy Research Working Paper
abstracts: cdata!: This study examines the effects of
            communal violence, that is violence inflicted upon a
            particular group along ethnic or religious lines, on
            women&#x2019;s marital outcomes. Communal violence, with
            its accompanying psychological and physical trauma, can have
            important socioeconomic consequences. The effects could be
            very different for women who are often disproportionately
            subject to sexual violence during such events. Using
            individual-level survey data from India and a
            difference-in-differences approach, the study shows that
            women&#x2019;s age of marriage decreased, and the
            probability of getting married before the age of 18
            increased after the Hindu-Muslim riots in Gujarat in 2002.
            The Gujarat riots stand out as one of the most significant
            and abrupt occurrences of communal violence in
            post-independence India, marked by widespread violence
            against women, thus providing a setting to study the impacts
            of such violence on women. Event study and synthetic control
            methods suggest that these effects are prominent two years
            after the riots and have increased over time. Women married
            after the riots also had fewer years of education and poorer
            social and economic status, such as a lower probability of
            employment and lower autonomy in household decision-making.
display_title: The Eﬀects of Communal Violence on
            Women’s Marital Outcomes
listing_relative_url: /research/2023/05/34060055/eﬀects-communal-violence-women’s-marital-outcomes
topicv3: Early Marriage m1326033 2444,Gender Based Violence m1504507 2901,Religious Discrimination m1505710 3383
publishtoextweb_dt: 2023-05-10T00:00:00Z
dois: 10.1596/1813-9450-10441
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 47
author_keys: 0: author_key: 1947054
1: author_key: NA
model_extractions: Policy Research Working Paper 10441 The Effects of Communal Violence on Women’s Marital Outcomes _Devaki Ghose Divya Pandey_ Development Economics Development Research Group May 2023
Policy Research Working Paper 10441

# **Abstract**

This study examines the effects of communal violence, that is violence inflicted upon a particular group along ethnic or religious lines, on women’s marital outcomes. Communal violence, with its accompanying psychological and physical trauma, can have important socioeconomic consequences. The effects could be very different for women who are often disproportionately subject to sexual violence during such events. Using individual-level survey data from India and a difference-in-differences approach, the study shows that women’s age of marriage decreased, and the probability of getting married before the age of 18 increased after the Hindu-Muslim riots in Gujarat in 2002. The Gujarat riots stand out as one of the most significant and abrupt occurrences of communal violence in post-independence India, marked by widespread violence against women, thus providing a setting to study the impacts of such violence on women. Event study and synthetic control methods suggest that these effects are prominent two years after the riots and have increased over time. Women married after the riots also had fewer years of education and poorer social and economic status, such as a lower probability of employment and lower autonomy in household decision-making.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at dghose@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# The Effects of Communal Violence on Women’s Marital Outcomes

Devaki Ghose and Divya Pandey<sup>∗</sup> Originally published in the Policy Research Working Paper Series on _May 2023._ This version is updated on _May 2024._ To obtain the originally published version, please email prwp@worldbank.org.

**_Keywords:_** Gender, Early Marriage, Religion, Communal Violence, Riots **_JEL Classification:_** D74, J12, J16, O12, Z12

> ∗Affiliations: Ghose, Development Research Group, The World Bank, Washington DC USA; Pandey, International Initiative for Impact Evaluation (3ie), Delhi Office. . We are immensely grateful to Anjini Kochar, Sheetal Sekhri, S. Anukriti, Tarun Jain, and participants of the Gender Brown Bag at Inclusion Economics for their thoughtful comments and feedback. We thank Jan Oledan for excellent research assistance. This paper is the third chapter of Divya Pandey’s dissertation (available here, and the author acknowledges the Bankard Fund for Political Economy for their financial support). The authors gratefully acknowledge support by the Umbrella Facility for Trade, which is funded by the governments of The Netherlands, Norway, Switzerland, Sweden and the United Kingdom. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors and do not necessarily represent the views of 3ie and the World Bank and its affiliated organizations or those of the Executive Directors or the countries they represent. Any errors are the authors’ responsibility.
# **1 Introduction**

The disruptive impacts of violent conflicts are seldom gender-neutral. Women suffer in very specific ways during times of conflict as existing law and order break down, making them more susceptible to sexual violence. While sexual violence adversely impacts women’s physical, social, and psychological well-being, the death of earning members, loss of wealth, or displacement also exposes them to economic hardships during times of conflict (Annan et al., 2011). These effects can exacerbate further in the presence of existing gender discrimination and disparities in human capital in developing countries.

Rape and sexual atrocities are often viewed as weapons of conflict to create fear and terror (World Bank Blog, 2023). While the direct consequences of violent conflicts on women include rape and other forms of abuse, its indirect consequences could involve unwanted pregnancies and changes in their marital outcomes and agency due to changes in socioeconomic and demographic characteristics of the conflict-affected regions (La Matthina, 2017; Gutierrez and Gallegos, 2016). More specifically, fear of sexual violence, changes in sexratios, and wealth effects in riot-affected regions could drive marriage market outcomes of not just women who were victims of violence during riots, but also the wider community.

While there have been several incidents of communal riots in India, the Hindu-Muslim riots of 2002 in the Indian state of Gujarat are considered one of the most extreme in terms of the systematic nature, geography and duration (Jaffrelot, 2003). During these riots, not only were several killed, injured and displaced, sexual violence against women had become its key feature (Jha and Farasat, 2016). In fact, some studies suggest that during the riots in Gujarat in 2002, women were victims of most extreme forms of sexual cruelty, including rape, gang rape, stripping, insertion of objects into their body, and molestation (Hameed et al., 2002). This paper examines how women’s marriage age and postmarital socioeconomic status evolved in Gujarat after the 2002 riots. Even though several studies have examined the impact of Hindu-Muslim riots on several social, economic and political outcomes of interest, we specifically contribute to the literature by assessing the effect of the riots on women’s marital outcomes.

To examine the effects of the Gujarat riots of 2002 on women’s marital outcomes, we use a retrospective state-year level dataset from the fourth round of the National Family Health Surveys (2015-2016) and a difference-in-differences strategy. Our empirical strategy relies on variation over time in marriages that took place before and after 2002 and the statewise variation in the occurrence of riots. We also use the event study approach to observe differential trends in women’s age at marriage between Gujarat and the other Indian states. The difference-in-differences estimates suggest that age at marriage declined for women 2
in Gujarat relative to other Indian states after the riots of 2002. The probability of women getting married before 18 increased by 4.4 percentage points or 14 percent after the riots in Gujarat compared with the control states. Also, the probability of getting married before the age of 18 is relatively higher among Muslim women, who were some of the primary victims of sexual violence during the riots (Khanna, 2008).

Our event study estimates suggest that the effects are prominent two years after the intercommunal violence, and the gap in terms of women’s age at marriage between Gujarat and the other Indian states has since increased. Our results are robust to synthetic control methods or restricting the control group to states that share their borders with Gujarat. We also conduct a few additional robustness checks to allay concerns about other shocks within Gujarat driving our results.

Next, to understand the implications of early marriage for women’s post-marital socioeconomic status, we check education and autonomy outcomes for women married after the riots compared to women married before the riots. Existing literature has established that marrying young or exposure to conflict can decrease women’s bargaining power within the marriage (Field and Ambrus, 2008; Jensen and Thornton, 2003). We find that women married after the riots had fewer years of education, were more likely to experience domestic violence, had less control over their income, and had lower autonomy regarding household purchases and visits.

Several mechanisms could explain our results. First, in the Indian culture, rape victims face the risks of being socially ostracized, which could worsen their position in the marriage market. Therefore, the fear inflicted by sexual violence on victims, their families, and the community living in the riot-inflicted regions can lead to early marriages of women. Second, distortions in sex ratios due to disproportionately higher mortality for men or women could also affect women’s position in the marriage market by altering their bargaining power (Becker, 1981; Teso, 2018; Abramitzky et al., 2011). Third, negative income shocks caused by the riots can also alter women’s marriage age due to the payment of dowry or bride prices at the time of marriage (Corno et al., 2020; Khanna and Kochhar, 2020). In this paper, we do not attempt to disentangle these different mechanisms but establish the effects of the riots on women’s age at marriage and explore its implications for women’s socioeconomic status and autonomy within the household. Our overall findings shed light on the importance of providing protection to the most marginalized, who also face the risk of sexual cruelty during violent conflicts, particularly women and girls.

The rest of this paper is structured as follows. Sections 2 provides a review of the literature and 3 discusses the background. Sections 4 and 5 discuss the data and the empirical strategy. Sections 6 and 7 discuss our main results and their robustness. Section 8 discusses 3
some of the potential mechanisms that could be driving our results and 9 concludes.

# **2 Literature Review**

This study fits into the broad literature on the effects of violent conflicts. Several studies have analyzed the effect of ethnic conflict on economic growth (Abadie and Gardeazabal, 2003); human capital formation and demographic changes (Camacho, 2008; Duque, 2017; Brunborg and Urdal, 2005); long-term biases in terms of lending behavior and judicial results (Hjort, 2014; Shayo and Zussman, 2011, 2017); and women’s employment rates, fertility and agency (Goldin and Olivetti, 2013; Zárate-Barrera and Rogall, 2020; Thiede et al., 2020).

Of particular relevance is recent work from the broader social science literature that examines the effects of violent conflict on women’s marriages and changes in fertility (Torrisi, 2023; Sieverding et al., 2020; Torrisi, 2020). While one strand of the literature documents decreasing overall marriage rates during conflict (Khawaja and Randall, 2006; Saxena et al., 2004), another strand finds the opposite effects (Valente, 2011; Williams et al., 2012). Given the mixed findings in the literature where the effects of conflicts on marriage rates and age can go either way depending on the costs associated with marriage and the potential use of marriage as a "consumption-saving tool", the effects are not obvious (Saxena et al., 2004; Fussell and Palloni, 2004; Torrisi, 2022). This paper adds to the literature by examining the effects of intercommunal Hindu-Muslim riots on women’s marital outcomes, especially the age of marriage, using state-of-the-art event study designs.

There are several studies that have focused on the evolution, nature, determinants, and effects of the Hindi-Muslim riots in India (Varshney, 2002; BRASS, 2003; Wilkinson, 2004; Corbridge et al., 2012). While there is a relatively large literature on the determinants of Hindu-Muslim riots (Jha, 2013, 2014; Nellis et al., 2016; van Noort and Goyal, 2020; Bohlken and Sergenti, 2010; Mitra and Ray, 2014; Field et al., 2008) and some work on the effects of these riots on electoral votes and lending (Iyer and Shrivastava, 2018; Ticku, 2015; Fisman et al., 2020), there is limited work on the effect of these riots on women’s marital outcomes. To the best of our knowledge, this paper is the first to empirically examine the effect of Hindu-Muslims riots on women’s marriage market outcomes in India.

Examining the impact of communal riots on women’s marital outcomes is important and equally challenging to study as sexual violence against women was a key feature of the Hindu-Muslim riots but abysmally under-reported (Khanna, 2008; Srivastava, 2011; Sen and Jasani, 2021). As pointed out by Srivastava (2011): _“FIRs of women survivors were not lodged. In fact, the police refrained from registering rape as an individual crime. By clubbing rape with complaints of murder, sexual violence was made invisible across the state"_ . Given 4
how widespread the under-reporting or complete lack of crime reporting was, rather than studying reported crimes, we focus instead on women’s socioeconomic outcomes, such as marriage age, education, and autonomy inside a household that can be severely undermined through violence against women.

Our paper also interacts with the literature on the determinants of early marriages of women. Most studies examine the effects of income shock associated with natural disasters on women’s age at marriage (Corno and Voena, 2016; Corno et al., 2020; Khanna and Kochhar, 2020). Corno et al. (2020) show that the interaction of social norms such as bride price and dowry and local income shocks caused by droughts increase the incidence of child marriage in Sub-Saharan Africa and reduce the same in India. While income shocks associated with natural disasters are important drivers of marriage market outcomes, violence against women during communal riots can also determine the incidence of child marriages. Our paper seeks to contribute to this literature by examining the effect of intercommunal conflict on women’s marital outcomes. Further, we also show that communal violence can hurt women’s socioeconomic outcomes, such as education and bargaining power within the marriage.

Finally, this paper relates to the literature that examines the relationship between early marriages and women’s agency. Existing studies have shown that early marriages adversely impact women’s empowerment outcomes, such as educational attainment, health, economic condition, fertility and childbearing age, bargaining power, attitudes towards equitable gender relations, and children’s human capital (Field and Ambrus, 2008; Dahl, 2010; Sunder, 2019; Chari et al., 2017; Sekhri and Debnath, 2014; Jensen and Thornton, 2003; Raj et al., 2009; Yount et al., 2018; Crandall et al., 2016). While our paper does not directly isolate the effect of early marriage on women’s agency, our results suggest that communal violence reduces women’s age at marriage and potentially adversely affects their socioeconomic well-being.

# **3 Background: Gujarat Riots of 2002**

India has had a history of communal riots whereby violence was perpetrated by both Hindus and Muslims. The Hindu-Muslim violence peaked during the partition of India based on religion in 1947 and then settled down to periodic clashes centered on religious festivals and places of worship. These clashes are often determined by the state and nature of intercommunal civic engagements in the case of India (Varshney, 2008; Varshney and Gubler, 2012; Wilkinson, 2009).

The Gujarat riots of 2002 erupted after a carriage carrying Hindu activists was set on 5
fire in Godhra on February 27, 2002. While several theories circulate on who set the train on fire, the dominant one is that a Muslim mob set the train on fire due to an altercation between a Muslim tea seller and the Hindu activists and possibly the attempted molestation of the tea seller’s daughter (Khanna, 2008; Simpson, 2017). Several of the 58 people killed on the train were women and children.

Following this incident, a three-day-long violence was perpetrated by Hindu mobs against the minority Muslim population. The riots were considered one of the most severe forms of Hindu-Muslim violence in post-independent India in terms of both geographical spread and brutalities. While previous Hindu-Muslim violence in India had been an urban phenomenon, in 2002, it spread to rural locations as well (Jaffrelot, 2003). According to official figures, the riots killed 790 Muslims and 254 Hindus. However, unofficial statistics suggest that close to 2000 Muslims were killed over the next three months, and many others were injured (Amnesty International, 2005). More than 200,000 Muslims were displaced because of the looting and burning of their homes and businesses (Srivastava, 2011). There were further outbreaks of statewide violence over the next year.

Women were largely victimized the Gujarat riots of 2002. Several women were raped and killed. Survivors reported sexual violence such as rapes, gang rapes, forced nudity, torching, mutilation of the stomach and sexual organs, and insertion of objects into bodies (Hameed et al., 2002). According to Jha and Farasat (2016), Muslim women were not the only victims of sexual violence in the Gujarat carnage of 2002; Hindus were also targeted in some cases. Many of these cases were not reported to the police because of the fear of further attacks, stigma, and ostracism.

During episodes of communal violence, women are often targeted to create fear and also because they are viewed as transmitters of the culture of a particular community. Exposure to such physical and sexual brutalities can have deep physical and emotional effects on the victims, their families, their communities, and their marital decisions. The fear of sexual violence and stigmatization can lead to early marriages of women. Due to the communal conflict in Gujarat in 2002, we expect a relatively larger effect on Muslim women’s marital age since they were the primary victims of sexual violence. In this paper, we study the effects of the Gujarat riots of 2002 on women’s marital outcomes.

# **4 Data**

This study uses data from the fourth round of the National Family Health Surveys (NFHS-IV), based on the Demographic and Health Surveys (DHS), conducted in India during 2014-15. These are nationwide repeated cross-sectional surveys that are representative at 6
the state level. The survey reports information on the year of marriage, age at marriage, age at cohabitation, age at the consummation of marriage, and age at first birth of ever-married women between ages 15 and 49. We construct a retrospective state-year-level dataset of around 415,000 marriages between 1990 and 2014 across Indian states using this information. This allows us to compare outcomes for women across Indian states married before and after the Gujarat riots of 2002. For a sub-sample of women, the survey also reports information on their socioeconomic statuses, such as their employment status, exposure to intimate partner violence, and their decision-making power, which we use to analyze the effect of the Gujarat riots on women’s post-marital outcomes.

The variables used for analyzing women’s socioeconomic outcomes post riots include women’s years of education and indicators for whether they experienced physical and emotional violence by their husbands. We define physical violence as an indicator for whether the woman was slapped, pushed, kicked, dragged, burned, threatened using weapons, beaten up, physically injured in other ways, or sexually abused by her husband. Emotional violence is an indicator of whether the respondent was humiliated, insulted, or threatened by her spouse. We also include indicators for whether women are employed, have autonomy over their own income, participate in decisions related to household purchases, and make their own decisions about visiting relatives and friends. The sub-sample used for analyzing socioeconomic outcomes consists of around 70,700 women married during 1990-2014.<sup>1</sup> Table 1 reports the sample means of key variables for women married before 2002 across Gujarat and other Indian states. There are some differences between the characteristics of women married before 2002 in Gujarat and other Indian states. For example, in terms of religion, Gujarat has a higher fraction of the Hindu population and a lower fraction of Muslims. Gujarat is also wealthier on average than the other states. The average marriage age for women from Gujarat or other Indian states is approximately 18 years. While the fraction of women married before 18 is lower in Gujarat than in other Indian states, the difference between the two groups is not statistically significant.

# **5 Empirical Strategy**

We use a difference-in-differences strategy to isolate the effect of the Hindu-Muslim riots on women’s marital outcomes. In particular, we rely on spatial variation due to the riots that erupted in the Indian state of Gujarat and the temporal variation in marriages before and after the riots of 2002.

> 1The sample size may vary by the outcome of interest depending on the missing observations.

7
# **5.1 Main Specification**

We first estimate the following equation: where _Yist_ is the outcome of interest such as age at marriage, an indicator for marriage before age 18, age at cohabitation, years of education, a measure of autonomy or domestic violence for woman _i_ in state _s_ married in the year _t_ ; _Postt_ equals 1 if the woman was married after the year 2002 and 0 otherwise; _Riots_ is an indicator for residence in the state of Gujarat;<sup>2</sup> and _Xist_ is a vector of controls that includes indicators for wealth, religion, caste, residence in a rural area, the gender of the household head, and household’s wealth. We also include marriage year fixed effects and district fixed effects. The coefficient of interest, _β_ , measures, depending on the specification, the changes in women’s marital outcomes in Gujarat relative to the rest of India/ neighboring states/ synthetic Gujarat post the 2002 riots.

# **5.2**

We study the effects of communal violence on women’s marital and socioeconomic outcomes using the 2002 Gujarat riots as an event study. The Gujarat riots of 2002 erupted after a carriage carrying Hindu activists was set on fire and the violence lasted for three days. Even though there have been sporadic instances of communal violence throughout history in India, the particular timing and location of the violence was entirely unexpected. While the violence was widespread but confined within the state of Gujarat, it varied in intensity, with some towns and cities even very close to the epicenter not witnessing any violence (Jha, 2014; Varshney, 2004). As pointed out by (Varshney, 2004): It was also argued that the outbreaks of communal violence tend to be highly locally concentrated: many towns, only a few miles away from the worst cities, have insulated themselves from communal riots, entirely or substantially. In contrast to Ahmedabad, Surats old city (not the part where its shantytowns are) was argued to be such an example: yet again in March and April 2002, the violence in Surat was minimal, even as Vadodara and Ahmedabad, neither too far away from Surat, experienced carnage.

> 2Since the survey only provides information on the state of residence, we are unable to account for women who migrated to another state due to marriage. However, this should not significantly affect our results because interstate migration in India is very low (Biswas, 2017). According to the 2011 census, the share of intra-state migration was about 88% and the share of inter-state migration was about 12%.

8
The unexpected time and localized nature of the violence make the 2002 Gujarat riots a suitable setting to study the effects of communal violence. We will carefully discuss our choice of treatment and control groups in the following section and show evidence of parallel trend below, an essential identifying assumption for difference-in-difference.

We check for differential trends in women’s age at marriage and the rate of child marriages by estimating the following event-study equation: where _Y eard_ are year-specific dummies and the omitted year is the year 2002; _βt_ represent the coefficients on interactions between the year dummies and the _Riots_ dummy. Another advantage of estimating the difference-in-differences coefficients by year is that it enables us to investigate how women’s marital outcomes evolved over time after the riots.

# **5.3 Choice of Treatment and Control Groups**

As discussed in section 5.1, we take Gujarat as the treated state and the rest of India or neighboring states or a synthetic amalgamation of states as the control. In principle, one can think of a within Gujarat analysis where we analyze whether women’s marriage market outcomes are correlated with the intensity of riots. There are two major issues with such an analysis: The first is the high mobility of women across districts within the same state, specifically for marriage. According to the 2001 Indian Census data, while the leading cause of migration for men is work, it is marriage for women: 70% of all women who migrate do so for marriage (Kone et al., 2018). In table 2, we see that, among those women who migrate for marriage, more than 70% cross district borders within their states; for Gujarat, this number is more than 80%. Since the available data only records the residence district of the women after marriage, a within Gujarat district-level analysis will be unable to account for the spillover from treated to control districts and vice versa.

The second issue is the widespread prevalence of riots across Gujarat. According to contemporary news articles (Outlook India, 2002, 2022), 16 of 24 districts in Gujarat were affected, namely, Ahmadabad, Anand, Banas Kantha, Bharuch, Bhavnagar, Dohad, Gandhinagar, Junagadh, Kheda, Mahesana, Panch Mahals, Patan, Rajkot, Sabar Kantha, Surat, and Vadodara. Varshney (2020) highlights that the cities of Ahmadabad, Vadodara, and Godhra (in the Panch Mahal district) experienced the worst violence. Given the widespread violence across districts of Gujarat and the high inter-district within state mobility of women for marriage, considering the whole of Gujarat as the affected region offers the most credible 9
analysis.

## **5.4 Heterogeneity**

Next, we examine the effects of the riots by religion. The following equation identifies the effect of the riots by religion: where _Muslimi_ is equal to 1 if woman _i_ belongs to the Muslim community. The coefficient of interest, _γ_ identifies the additional effect of the riots on Muslim women’s marital outcomes relative to the outcomes of women of all other regions. We cluster all our standard errors at the state level or the state-year level in alternative specifications.

# **6 Results**

In this section, we discuss the effects of the Hindu-Muslim riots of Gujarat in 2002 on women’s age at marriage and their post-marital social and economic status.

## **6.1 Women’s Marriage Age**

Using data from NFHS-IV and specification 1, Table 3 presents the changes in women’s age at marriage, probability of child marriage, age at cohabitation, age at consummation, and age at first birth post the 2002 riots compared to the rest of India. Columns (1) and (2) suggest that women’s age at marriage declined by 0.33 years or 4 months after the riots, and the probability of marriage before the age of 18 increased by 4.4 percentage points or 14 percent compared with the rest of India or the control mean. Columns (3) and (4) in Table 3 indicate that the age at cohabitation and age at first sex also declined after the riots. The estimates in the first four columns of Table 3 are significant at the 1 percent level. According to column (5) of Table 3, while statistically insignificant, the effect of violence on women’s age at first birth is negative.

Figures 1(a) and 1(b) present coefficients using the event study specification in 2. Figure 1(a) suggests that the age at marriage decreased for women married after the Gujarat riots of 2002. Figure 1(b) suggests that the probability of child marriage increased for women married after 2002. Nevertheless, these effects are not immediate and are prominent after 10
2004. The coefficients on the years before the riots suggest some differences in a few years between women’s marriage age in Gujarat and the other Indian states even before 2002. Therefore, we will explore the same results using synthetic difference-in-difference and restrict our analysis to only bordering states in section 7.

To put our findings in perspective, we compare our estimates to other studies that investigate the effect of natural disasters on marriage markets. Our estimate of a 4-month decrease in age at marriage and a 14 percent increase in the incidence of child marriages is in line with the findings of other studies that find a decline in women’s age at marriage due to natural disasters. Khanna and Kochhar (2020) find about a 4-month decline in age at marriage and a 9.5 percent increase in the incidence of child marriage due to floods, and Corno et al. (2020) find a 3 percent increase in child marriages in Sub-Saharan Africa due to droughts.

# **6.2 Marriage Age by Religion**

In Table 4, we present results by religion using specification 3. We expect the effect of the riots to be larger on Muslim women because of the widespread violence against the Muslim community during the Hindu-Muslim riots of 2002. According to column (2) of Table 4, Muslim women are 3.1 percentage points more likely to get married before the age of 18 as a result of the riots. The results show that all the other outcomes, such as age at marriage, age at cohabitation, age at first sex, and age at first birth, declined for both Hindu and Muslim women, and there are no significant differences between the two groups. The additional effects of religion, even though negative and substantial for Muslim women, are statistically insignificant.

# **6.3 Women’s Education**

In this section, we examine the effects of communal violence in Gujarat on women’s education outcomes. Table 5 presents estimates of the effect of the riots on women’s education using specification 1. According to column (1) of Table 5, women who were married after the riots in Gujarat have 5 percent fewer years of education than women in the rest of the country or the control average. In terms of years, women have 0.38 fewer years of education in Gujarat. Columns (3) and (4) show that women who married after the riots in Gujarat are 1.8 and 1.5 percentage points less likely to complete secondary and higher education than the rest of India. Our results are consistent with the literature that shows that women married at a younger age are more likely to enter marriages with fewer years of education (Field and Ambrus, 2008).

11
## **6.4 Post-Marital Social and Economic Outcomes**

Next, we examine post-marital social and economic outcomes of women who got married after the Gujarat riots of 2002 using specification 1. Columns (2) and (3) of Table 6 suggest that women who married after the riots in Gujarat were more likely to suffer emotional and physical violence from their husbands compared to women in the rest of the country. Column (5) suggests that women are less likely to make decisions about visits to friends and relatives.

In Table 7, we present the results on women’s economic status after marriage. Columns (1) and (2) of Table 7 suggest that women in Gujarat who were married after 2002 were less likely to be employed and were also less likely to control their income compared to their counterparts in the rest of the country. Column (3) suggests that these women also had lower decision-making power in big household purchases. These findings are consistent with the literature that established that early marriage of women is associated with lower autonomy and bargaining power within the marriage (Jensen and Thornton, 2003), although communal violence can directly affect women’s sense of autonomy through changing notions of safety even outside marriage.

# **7 Robustness Checks**

In this section, we address concerns about the validity of the control group, estimation method deployed, and confounding events through a slew of robustness checks

## **7.1 Gujarat and the Bordering States**

As evident from Table 1, Gujarat is significantly different from other Indian states regarding cultural, social, and economic factors, which are important determinants of women’s age at marriage and agency. Many of these factors are unobserved or lack credible proxies. In this section, we restrict our control group to the states that share their borders with the riots that affected Gujarat since bordering states are likely to be similar across several characteristics due to geographical proximity. The approach restricting the analysis to neighboring states has also been adopted in the previous literature to ensure that the control group consists of regions most similar to the treatment region (Anukriti, 2018).

Figures A.1 and A.2 show the event-study coefficients using specification 2 after restricting the control group to the bordering states of Gujarat, which are Madhya Pradesh, Maharashtra, and Rajasthan. Figure A.1 shows no significant differences in age at marriage between Gujarat and its neighboring states before the riots of 2002. However, women’s age 12
at marriage is consistently declining in Gujarat relative to its neighboring states, 2 years after the riots. According to Appendix A, figure A.2, the probability of women getting married before 18 increased after the Gujarat riots.

# **7.2 Synthetic Controls Approach**

The results from the event study approach (Figures 1(a) and 1(b)) suggest that there were some differential trends between Gujarat and the control states even before the riots of 2002 for a few years. To address this concern, we examine the effects of the Gujarat riots by employing the synthetic controls approach suggested by Abadie and Gardeazabal (2003). Using a combination of other Indian control states or the donor pool, we first construct a synthetic Gujarat that best approximates the characteristics of women in Gujarat before the riots of 2002. More specifically, synthetic Gujarat is constructed as a weighted average of the donor pool, with weights chosen so that the resulting synthetic Gujarat best reproduces the values of a set of predictors of women’s age at marriage in Gujarat before the riots in 2022. We then use the post-riot outcomes for synthetic Gujarat to estimate the outcomes that would have been observed in Gujarat in the absence of the riots of 2002. Next, we compare the outcomes of synthetic Gujarat to actual Gujarat after 2002.

We collapse the individual-level data in a state-year panel for the synthetic controls method. To approximate the outcomes (age at marriage and proportion of child marriages) at the state level, we use the proportion of women who reside in rural areas, reside in households with male heads, belong to rich or poor households, are Hindus, and are scheduled castes/scheduled tribes/other backward classes. Appendix E, table E.1 shows that Gujarat and synthetic Gujarat are similar across several demographic characteristics.<sup>3</sup> The results from the synthetic control methods are presented in Appendix B, figures B.1 and B.2. Figure B.1 suggests that the age at marriage in Gujarat is identical to that in synthetic Gujarat before the riots of 2002 and begins to decrease two years after the riots. These findings are similar to what we find using the event study method in figure 1(a). The probability of child marriage also increased after 2002 (Appendix B, Figure B.2).

# **7.3 Alternative estimator**

An emerging literature documents several problems associated with using the traditional difference-in-difference methods. However, since most of these problems arise in the case of staggered treatment timings, we have used the traditional difference-in-difference methods for our main estimation. The majority of the new methods are mostly applicable only with

> 3Synthetic Gujarat consists of all other Indian states except Gujarat with varying weights.

13
staggered treatment timing, with a few exceptions, such as Borusyak et al. (2021), which can be used in a cross-sectional setting without staggered adoption. In a non-staggered setting with never-treated units (such as all other states than Gujarat), the problem of negative weighting with forbidden comparison groups arises in very specific cases (Borusyak et al., 2021). In appendix C, we still repeat our main estimation using the Borusyak et al. (2021) method and show the effects of women’s marriage age, and the probability of child marriage remain very close to our main findings. This holds whether we use the rest of India as control (Appendix C, figures C.1 and C.2) or only the neighboring states of Gujarat as control (Appendix C, Figures C.3 and C.4).

# **7.4 Gujarat Earthquake**

The massive earthquake that struck the district of Kutch in Gujarat in January 2001 could be confounding our results. According to (Das and Dasgupta, 2020), the Gujarat earthquake reduced men’s and women’s ages at marriage. To address this concern, we drop districts that were affected by the earthquake of 2001 but not by the riots of 2002.<sup>4</sup> Our results in Appendix E, table E.2 suggest that the effect of the Gujarat riots on women’s age at child marriage and child marriage remains large and statistically significant.

# **7.5 Gujarat Floods**

Some districts of Gujarat were severely affected by floods in 2005, and the existing literature suggests that natural disasters can affect marriage markets (Corno et al., 2020; Khanna and Kochhar, 2020).<sup>5</sup> We drop flood-affected districts to address concerns regarding the floods driving our results. Our results are not significantly affected by dropping the floodaffected districts, which allays concerns about weather shocks driving our results (Appendix D, Figures D.1 and D.2; Appendix E, Table E.4).

# **7.6 Change in Political Power**

Changes in political power during our analysis period could also confound our results. There was a change in political power in the year 1995 in Gujarat. Social norms, such as age at marriage within the state, could have been affected by the coming of a new political party based on the party’s ideologies. To address this concern, we restrict our sample to

> 4The earthquake-affected districts were Kutch, Ahmedabad, Jamnagar, Patan, Rajkot, and Surendranagar. We only drop Kachhch, Jamnagar, and Surendranagar since they do not overlap with the riots.

> 5The flood-affected districts of Gujarat in 2005 were Vadodara, Ahmedabad, Navsari, Surat, Surendranagar, Anand, Kheda.

14
marriages before 2002 (before the riots) and estimate equation 1 using 1995 as the _Post_ period to estimate the effect of a change in political power on women’s age at marriage. Our results in Appendix E table E.3 suggest no negative effect of change in the political party on women’s age at marriage, which alleviates concerns about the change in the party within Gujarat driving our results.

# **8 Discussion of Results**

While it is particularly challenging to identify mechanisms that could be driving our results due to challenges related to under-reporting of crimes against women during conflict and data limitations, in this section, we discuss some of the potential drivers of our results based on the existing literature and additional analysis. The potential mechanisms are discussed as follows:

- (a) **Fear of Sexual Violence:** Rape and sexual abuse have often been viewed as tools of conflict and war. Women are often targeted during ethnic conflicts to inflict fear and terror, destroy communities, and, in some cases, change the ethnic composition of the next generation. For example, around 100,000-250,000 women were raped during the three months of genocide in 1994 in Rwanda (Bangura, 2014). Also, more than 60,000 women were raped during the civil war in Sierra Leone (1991-2002), above 40,000 in Liberia (1989-2003), up to 60,000 in the former Yugoslavia (1992-1995), and at least 200,000 in the Democratic Republic of the Congo since 1998 (Bangura, 2014).

Sexual and physical violence against women, which may have been severely underreported, was also widespread during the Gujarat riots of 2002. One potential reason for a decline in women’s age at marriage after communal violence could be the sexual violence inflicted on girls and women. Exposure to such brutalities not only affects the emotional, physical, and psychological health of the victims but can also affect their families and community as a whole.

In societies with rigid gender norms, like India, women’s chastity is prized, and there is a stigma associated with their engagement in sexual activity before marriage (Jayachandran, 2015). Therefore, families may share concerns about sexual safety due to fears about how society will perceive girls and their future marriage prospects if they fall victims to sexual violence (Sarkar, 2021). The fear of being ostracized by the community due to rape may lead to early marriage, as parents feel that an unmarried girl is vulnerable to sexual exploitation. As suggested by our results, sometimes, even 15
after the conflict has ended, its fallout in the form of declining age at marriage could persist due to fear of rapes, unwanted pregnancies, or marginalization.

- (b) **Economic Role of Culture** : In patriarchal and patrilineal societies, where brides move in with the groom’s family after marriage, parents often view daughters as burdens and sons as insurance for old age. The tradition of dowry payments from the bride’s family to the groom’s family at the time of the wedding in South Asian countries, including India, also makes having daughters more expensive. Additionally, studies suggest that the dowry payment increases monotonically with the age of the bride since men prefer younger brides (Field and Ambrus, 2008; Sarkar, 2021). Therefore, in periods of negative income shocks, such as communal conflicts, parents may prefer to marry off their daughters as soon as possible at a younger age.

- Economic theory also suggests that dowry or marriage payments can be used as a coping mechanism during periods of negative income shocks. When earnings are already low, men are more likely to marry younger after an adverse wealth shock to earn some wealth from dowry (Corno et al., 2020; Khanna and Kochhar, 2020). Additionally, since men prefer to marry younger women, this would also reduce women’s age at marriage. We find some support for this mechanism since we find that after the riots, men’s age at marriage decreased by nine months, and the probability of child marriage increased by 2.8 percentage points (Appendix F, Table F.1).

- (c) **Distorted Sex Ratios** : Imbalances in sex ratios are typical in the aftermath of wars and conflicts. Studies suggest that if there are fewer surviving men after conflicts, women’s position in the marriage market deteriorates due to the scarcity of grooms, which increases men’s bargaining power (La Matthina, 2017; Abramitzky et al., 2011). On the contrary, when a shock leads to fewer women relative to men, there is an increase in female bargaining power in the marriage market (Angrist, 2002). Therefore, when sex ratios are distorted, the more prevalent sex is generally induced to delay marriage, marry individuals of less appropriate age, or remain unmarried due to greater competition for spouses (Hacker et al., 2010). We test this hypothesis using Census data of 2001 (before Gujarat riots in 2002) and 2011 (post-riots), using the following difference-in-difference model to examine if the sex ratios changed after the riots for specific age groups:

16
where _ystg_ is the sex ratio (Women/Men) in state _s_ , year _t_ , and age group _g_ ; _Riots_ is a dummy variable, equal to 1 if the State is Gujarat; _Postt_ is a dummy variable, equal to 1 if the year is 2011; I[ _Age_ = _g_ ] is a dummy variable, equal to 1 if the age group is _g_ ; _φs_ are state fixed effects; _γt_ are year fixed effects; _ωg_ are age group fixed effects.

Our results in Appendix F, table F.2 suggest the theory that a decline in sex ratios impacted women’s age at marriage after the Gujarat riots of 2002 does not hold. This is because we find that even though there were relatively fewer women in the marriageable age group of 0-39 after the riots in Gujarat compared to its control state, men (the more prevalent sex) did not delay marriage. (Table F.1).<sup>6</sup>

# **9 Conclusion**

In this paper, we have established that women’s age of marriage decreased, and the probability of child marriage increased in Gujarat after the riots of 2002 compared to the rest of India, neighboring states, or synthetic Gujarat. We show that years after the riots, women in Gujarat continued to be married off early and were less likely to finish secondary and higher education. Early marriage is often associated with lower education, worse household employment outcomes, and bargaining power. Our findings show that post-2002, women in Gujarat have not only a lower probability of employment but also lower autonomy in social and economic decisions within the household.

Our overall results highlight that intercommunal violence threatens the larger community who live in riot-exposed regions, particularly the most vulnerable sections, including women and girls. Our results suggest the need for policy to protect and incentivize women and their families to delay marriage and continue their education in riot-affected regions. It is also important to be mindful of the needs of victims of sexual violence, which could include medical care, psychological and social support, financial assistance, and legal redress (Bangura, 2014).

Our findings have a few limitations in terms of the inability to correlate our outcomes to the intensity of riots within Gujarat and the exact mechanisms that drive these results. First, due to the high migration rates of women for marriage across districts within Gujarat and the widespread prevalence of riots, we do not know whether the riots had worse effects in the directly affected areas. Second, the severe under-reporting of crimes related to sexual violence as documented in the literature (Palermo et al., 2014; Iyer et al., 2012; Sahay,

> 6Please note that one should not view decline in sex-ratios observed through this regression as causal since the data spans over 10 years and several other observable and unobservable factors could be driving the decline in sex ratios.

17
2021) restricts the paper’s ability to investigate the key mechanisms via which communal violence affects women’s martial outcomes. Lastly, it is important to note that while we have used state-of-the-art difference-in-difference design with valid control and treatment groups to understand the impact of communal violence in Gujarat on women, none of the available data records information on victims directly affected by the riots. The effects of communal violence on women’s marital and post-marital social outcomes could be very different depending on the extent of exposure that we are unable to capture (Islam et al., 2023).

Given the effects of communal violence on women’s socioeconomic outcomes that we document, we believe that future research can enhance our understanding of the mechanisms that drive changes in women’s marriage market outcomes due to inter-communal conflict. This is especially challenging since violence against women is severely under-reported, and the social stigma associated with sexual violence is hard to measure.

18
# **References**

- Abadie, A. and Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. _American Economic Review_ 93(1):113–132.

- Abramitzky, R., Delavande, A. and Vasconcelos, L. (2011). Marrying Up: The Role of Sex Ratio in Assortative Matching. _American Economic Journal: Applied Economics_ 3(3):124–57.

- Amnesty International (2005). India: Justice, The Victim - Gujarat State Fails To Protect Women From Violence. _ASA_ : https://www.refworld.org/docid/45c1cb702.html.

- Angrist, J. (2002). How Do Sex Ratios Affect Marriage and Labor Markets? Evidence from America’s Second Generation*. _The Quarterly Journal of Economics_ 117(3):997–1038.

- Annan, J., Blattman, C., Mazurana, D. and Carlson, K. (2011). Civil war, reintegration, and gender in northern uganda. _The Journal of Conflict Resolution_ 55(6):877–908.

- Anukriti, S. (2018). Financial Incentives and the Fertility-Sex Ratio Trade-Off. _American Economic Journal: Applied Economics_ 10(2):27–57.

- Bangura, Z.H. (2014). Sexual violence: A tool of war. United Nations Report https://www.un.org/en/preventgenocide/rwanda/assets/pdf/Backgrounder%20Sexual% 20Violence%202014.pdf.

- Becker, G.S. (1981). _A Treatise on the Family_ . National Bureau of Economic Research, Inc.

- Biswas, N. (2017). Policy or Perception? Womens Political Liberalization and Sex-selection in India.

- Bohlken, A.T. and Sergenti, E.J. (2010). Economic growth and ethnic violence: An empirical investigation of Hindu-Muslim riots in India. _Journal of Peace Research_ 47(5):589–600.

- Borusyak, K., Jaravel, X. and Spiess, J. (2021). Revisiting event study designs: Robust and efficient estimation. _arXiv preprint arXiv:2108.12419_ .

- BRASS, P.R. (2003). _The Production of Hindu-Muslim Violence in Contemporary India_ . University of Washington Press.

- Brunborg, H. and Urdal, H. (2005). The demography of conflict and violence: An introduction. _Journal of Peace Research_ 42(4):371–374.

19
- Camacho, A. (2008). Stress and Birth Weight: Evidence from Terrorist Attacks. _American Economic Review_ 98(2):511–15.

- Chari, A., Heath, R., Maertens, A. and Fatima, F. (2017). The causal effect of maternal age at marriage on child wellbeing: Evidence from India. _Journal of Development Economics_ 127:42–55.

- Corbridge, S., Kalra, N. and Tatsumi, K. (2012). The search for order: Understanding hindu-muslim violence in post-partition india. _Pacific Affairs_ 85(2):287–311.

- Corno, L., Hildebrandt, N. and Voena, A. (2020). Age of Marriage, Weather Shocks, and the Direction of Marriage Payments. _Econometrica_ 88(3):879–915.

- Corno, L. and Voena, A. (2016). Selling daughters: age of marriage, income shocks and the bride price tradition. _IFS Working Papers_ , Institute for Fiscal Studies.

- Crandall, A., VanderEnde, K., Cheong, Y.F., Dodell, S. and Yount, K.M. (2016). Womens age at first marriage and postmarital agency in Egypt. _Social Science Research_ 57:148–160.

- Dahl, G.B. (2010). Early Teen Marriage and Future Poverty. _Demography_ 47(3):689718.

- Das, S. and Dasgupta, S. (2020). Marriage Market Responses in the Wake of a Natural Disaster in India. _Available at SSRN_ : https://ssrn.com/abstract=3266117.

- Duque, V. (2017). Early-life conditions and child development: Evidence from a violent conflict. _SSM - Population Health_ 3:121–131.

- Field, E. and Ambrus, A. (2008). Early Marriage, Age of Menarche, and Female Schooling Attainment in Bangladesh. _Journal of Political Economy_ 116(5):881–930.

- Field, E., Levinson, M., Pande, R. and Visaria, S. (2008). Segregation, Rent Control, and Riots: The Economics of Religious Conflict in an Indian City. _American Economic Review: Papers and Proceedings_ 98(2):505–510.

- Fisman, R., Sarkar, A., Skrastins, J. and Vig, V. (2020). Experience of communal conflicts and intergroup lending. _Journal of Political Economy_ 128(9):3346–3375.

- Fussell, E. and Palloni, A. (2004). Persistent marriage regimes in changing times. _Journal of Marriage and Family_ 66(5):1201–1213.

- Goldin, C. and Olivetti, C. (2013). Shocking Labor Supply: A Reassessment of the Role of World War II on Women’s Labor Supply. _American Economic Review_ 103(3):257–62.

20
- Gutierrez, I.A. and Gallegos, J.V. (2016). The Effect of Civil Conflict on Domestic Violence: The Case of Peru. _RAND Working Paper Series WR-1168_ .

- Hacker, J., Hilde, L. and Jones, J. (2010). The effect of the civil war on southern marriage patterns. _The Journal of southern history_ 76:39–70.

- Hameed, S., Manorama, R., Ghose, M., George, S., Naqvi, F. and Thekaekara, M. (2002). Citizens’ Initiative. Survivors Speak: How has the Gujarat Massacre Affected Minority Women? Fact-finding by a Women’s Panel. _Outlook India_ : https://www.outlookindia. com/website/story/the-survivors-speak/215433.

- Hjort, J. (2014). Ethnic divisions and production in firms. _The Quarterly Journal of Economics_ 129(4):1899–1946.

- Islam, A., Mahanta, R., Mandal, R., Nath, H.K., Ouch, C. and Sarkar, D. (2023). Long-term impact of exposure to violent conflict: Are there gender differences? _Journal of Economic Behavior & Organization_ 208:120–139.

- Iyer, L., Mani, A., Mishra, P. and Topalova, P. (2012). The power of political voice: women’s political representation and crime in India. _American Economic Journal: Applied Economics_ 4(4):165–193.

- Iyer, S. and Shrivastava, A. (2018). Religious riots and electoral politics in India. _Journal of Development Economics_ 131:104–122.

- Jaffrelot, C. (2003). Communal riots in gujarat: The state at risk?

- Jayachandran, S. (2015). The roots of gender inequality in developing countries. _Annual Review of Economics_ 7(1):63–88.

- Jensen, R. and Thornton, R. (2003). Early Female Marriage in the Developing World. _Gender & Development_ 11:9–19.

- Jha, P. and Farasat, W. (2016). _Splintered Justice: Living the Horror of Mass Communal Violence in Bhagalpur and Gujarat_ . Three Essays Collective.

- Jha, S. (2013). Trade, institutions, and ethnic tolerance: Evidence from South Asia. _American Political Science Review_ 107(4):806–832.

- Jha, S. (2014). Unfinished business: Historic complementarities, political competition and ethnic violence in Gujarat. _Journal of Economic Behavior & Organization_ 104:18–36.

21
- Khanna, M. and Kochhar, N. (2020). Do Marriage Markets Respond to a Natural Disaster? The Impact of Flooding of River Kosi in India. _Available at SSRN_ : https://ssrn.com/ abstract=3644052.

- Khanna, R. (2008). Communal violence in gujarat, india: Impact of sexual violence and responsibilities of the health care system. _Reproductive Health Matters_ 16(31):142–152.

- Khawaja, M. and Randall, S. (2006). Intifada, palestinian fertility and women’s education. _Genus_ pp. 21–51.

- Kone, Z.L., Liu, M.Y., Mattoo, A., Ozden, C. and Sharma, S. (2018). Internal borders and migration in India. _Journal of Economic Geography_ 18(4):729–759.

- La Matthina, G. (2017). Civil conflict, domestic violence and intra-household bargaining in post-genocide Rwanda. _Journal of Development Economics_ 124:168–198.

- Mitra, A. and Ray, D. (2014). Implications of an economic theory of conflict: Hindu-Muslim violence in India. _Journal of Political Economy_ 122(4):719–765.

- Nellis, G., Weaver, M. and Rosenzweig, S.C. (2016). Do parties matter for ethnic violence? Evidence from India. _Quarterly Journal of Political Science_ 11(3):249–277.

- Outlook India (2002). Mapping The Violence. _Outlook India_ : https://www.outlookindia. com/website/story/mapping-the-violence/217990.

- Outlook India (2022). History of Communal Violence in Gujarat. _Outlook India_ : https:// www.outlookindia.com/website/story/history-of-communal-violence-in-gujarat/217988.

- Palermo, T., Bleck, J. and Peterman, A. (2014). Tip of the Iceberg: Reporting and GenderBased Violence in Developing Countries. _American Journal of Epidemiology_ 179(5):602– 612.

- Raj, A., Saggurti, N., Balaiahand, D. and Silverman, J.G. (2009). Prevalence of child marriage and its effect on fertility and fertility-control outcomes of young women in India: a cross-sectional, observational study. _The Lancet_ 373(9678):18831889.

- Sahay, A. (2021). The Silenced Women: Can Public Activism Stimulate Reporting of Violence against Women? _The World Bank_ : http://hdl.handle.net/10986/35245.

- Sarkar, S. (2021). Local crime and early marriage: Evidence from india (wp-2021-37).

22
- Saxena, P.C., Kulczycki, A. and Jurdi, R. (2004). Nuptiality transition and marriage squeeze in lebanon: Consequences of sixteen years of civil war. _Journal of Comparative Family Studies_ 35(2):241–258.

- Sekhri, S. and Debnath, S. (2014). Intergenerational Consequences of Early Age Marriages of Girls: Effect on Childrens Human Capital. _The Journal of Development Studies_ 50(12):1670–1686.

- Sen, A. and Jasani, R. (2021). Urban Hopes, Sexual Horrors. _The Copenhagen Journal of Asian Studies_ 39(1).

- Shayo, M. and Zussman, A. (2011). Judicial Ingroup Bias in the Shadow of Terrorism. _The Quarterly Journal of Economics_ 126(3):1447–1484.

- Shayo, M. and Zussman, A. (2017). Conflict and the Persistence of Ethnic Bias. _American Economic Journal: Applied Economics_ 9(4):137–165.

- Sieverding, M., Krafft, C., Berri, N. and Keo, C. (2020). Persistence and change in marriage practices among syrian refugees in jordan. _Studies in Family Planning_ 51(3):225–249.

- Simpson, E. (2017). Communal Violence, Forced Migration and the State: Gujarat since 2002, by Sanjeevini Badigar Lokhande. _South Asia: Journal of South Asian Studies_ 40(2):421–422.

- Srivastava, A. (2011). ‘Engendering’ Communal Violence: An Note On The 2002 Gujarat Communal Riots. _Proceedings of the Indian History Congress_ 72:1400–1404.

- Sunder, N. (2019). Marriage Age, Social Status, and Intergenerational Effects in Uganda. _Demography_ 56(6):2123–2146.

- Teso, E. (2018). The Long-Term Effect of Demographic Shocks on the Evolution of Gender Roles: Evidence from the transatlantic Slave Trade. _Journal of the European Economic Association_ 17(2):497–534.

- Thiede, B.C., Hancock, M., Kodouda, A. and Piazza, J. (2020). Exposure to Armed Conflict and Fertility in Sub-Saharan Africa. _Demography_ 57(6):2113–2141.

- Ticku, R. (2015). Riot Rewards? Religious Conflict and Electoral Outcomes. _Religious Conflict and Electoral Outcomes (May 1, 2016). Graduate Institute of International and Development Studies Working Paper_ (19).

23
- Torrisi, O. (2020). Armed conflict and the timing of childbearing in azerbaijan. _Population and Development Review_ 46(3):501–556.

- Torrisi, O. (2022). Wedding amidst war? armed conflict and female teen marriage in azerbaijan. _European journal of population_ 38(5):1243–1275.

- Torrisi, O. (2023). Young-age exposure to armed conflict and women’s experiences of intimate partner violence. _Journal of Marriage and Family_ 85(1):7–32.

- Valente, C. (2011). What did the maoists ever do for us? education and marriage of women exposed to civil conflict in nepal. _Education and Marriage of Women Exposed to Civil Conflict in Nepal (July 1, 2011). World Bank Policy Research Working Paper_ (5741).

- van Noort, S. and Goyal, T. (2020). Is Ethnic Violence Self-Perpetuating? QuasiExperimental Evidence from Hindu-Muslim Riots in India. _Quasi-Experimental Evidence from Hindu-Muslim Riots in India (April 20, 2020)_ .

- Varshney, A. (2002). _Ethnic Conflict and Civic Life: Hindus and Muslims in India_ . Yale University Press.

- Varshney, A. (2004). Understanding gujarat violence. _Contemporary Conflicts_ 26:1–5.

- Varshney, A. (2008). _Ethnic Conflict and Civic Life_ . Yale University Press.

- Varshney, A. (2020). Understanding Gujarat Violence. Social Science Research Council https://items.ssrc.org/from-our-archives/understanding-gujarat-violence/.

- Varshney, A. and Gubler, J.R. (2012). Does the State Promote Communal Violence for Electoral Reasons? _India Review_ 11(3):191–199.

- Wilkinson, S.I. (2004). _Votes and Violence: Electoral Competition and Ethnic Riots in India_ . Cambridge Studies in Comparative Politics. Cambridge University Press.

- Wilkinson, S.I. (2009). Riots. _Annual Review of Political Science_ 12(1):329–343.

- Williams, N.E., Ghimire, D.J., Axinn, W.G., Jennings, E.A. and Pradhan, M.S. (2012). A micro-level event-centered approach to investigating armed conflict and population responses. _Demography_ 49(4):1521–1546.

- World Bank Blog (2023). Tackling gender based violence in fragile contexts. _The World Bank:_ https://www.worldbank.org/en/news/feature/2023/03/07/ tackling-gender-based-violence-in-fragile-contexts.

24
- Yount, K.M., Crandall, A. and Cheong, Y.F. (2018). Womens Age at First Marriage and Long-Term Economic Empowerment in Egypt. _World Development_ 102:124–134.

- Zárate-Barrera, T. and Rogall, T. (2020). Yes they can: Genocide, political participation, and female empowerment. _HiCN Working Paper No. 338_ 338.

25
# **Tables**

Table 1. Sample Characteristics of Women Married Before 2002

||(1)<br>Other States|(2)<br>Gujarat|(2) - (1)|
|---|---|---|---|
|**Control Variables:**||||
|Hindu|0.75|0.92|0.16***|
|Muslim|0.12|0.07|-0.05**|
|SC/ST/OBC|0.75|0.74|-0.01|
|Male Household Head|0.87|0.89|0.02*|
|Wealth|2.90|3.35|0.45**|
|Rural Resident|0.71|0.64|-0.07***|
|**Outcome Variables:**||||
|Women’s Age at Marriage|17.72|17.98|0.26|
|Women’ Child Marriage|0.49|0.43|-0.05|
|Women’ Age at Cohabitation|17.97|18.24|0.27|
|Women’ Age at First Intercourse|18.03|18.13|0.09|
|Women’s Age at First Birth|20.37|20.59|0.22*|
|Women’s Years of Education|4.71|5.17|0.46|
|Husband Controls|0.48|0.47|-0.02|
|Husband is Emotionally Violent|0.14|0.11|-0.03**|
|Husband is Physically Violent|0.33|0.21|-0.12***|
|Makes Health Decisions|0.78|0.78|-0.01|
|Employed|0.90|0.86|-0.04***|
|Controls Own Income|0.84|0.79|-0.05***|
|Makes Household Purchase Decisions|0.78|0.79|0.02*|
|Makes Decisions About Visits|0.78|0.81|0.02*|
|Men’s Age at Marriage|22.35|21.40|-0.95**|
|No. of women married before 2002|174,226|6,104||
|No. of women married after 2002|227,593|7,518||

_Note_ : This table reports simple differences in means of the characteristics of women living in Gujarat and other Indian states using data from the NFHS-IV. The total sample represents the observations used for the age at marriage and education analysis, and the sub-sample represents observations used for analyzing women’s socioeconomic status. * Significant at 10%; ** Significant at 5%; *** Significant at 1%.

26
Table 2. Summary Statistics: Migration for Marriage Purposes

|State|No. of migrants|Percentage|Out of district, same state|Percentage|Out of state|Percentage|
|---|---|---|---|---|---|---|
|Gujarat|1,937,395|4|1,560,660|81|376,735|19|
|Neighbors of Gujarat|10,416,132|24|8,062,937|77|2,353,195|23|
|Rest of India|31,629,202|72|23,066,868|73|8,562,334|27|
|Total|43,982,728|100|32,690,404|74|11,292,264|26|

_Note:_ This table reports the number and percentages of women migrating out of state and out of the district (same state) in Gujarat, its neighboring states, and the rest of India. Data source is the 2001 Indian Census.

Table 3. Women’s Marriage Outcomes Post the Gujarat Riots of 2002

||(1)<br>Age at<br>Marriage|(2)<br>Married Before<br>Age 18|(3)<br>Age at<br>Cohabitation|(4)<br>Age at<br>First Sex|(5)<br>Age at<br>First Birth|
|---|---|---|---|---|---|
|Post X Riot|-0.330<sup>_∗∗∗_</sup>|0.044<sup>_∗∗∗_</sup>|-0.271<sup>_∗∗∗_</sup>|-0.398<sup>_∗∗∗_</sup>|-0.030|
||(0.085)|(0.016)|(0.074)|(0.062)|(0.083)|
|Observations|415441|425254|405697|418219|389744|
|R-squared|0.248|0.164|0.216|0.228|0.128|
|Control Average|19.57|0.312|19.68|19.52|21.34|
|District Fixed Efects|Yes|Yes|Yes|Yes|Yes|
|Year Fixed Efects|Yes|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|Yes|

_Note_ : This table reports coefficients from specification 1. Standard errors are clustered at the state level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

27
Table 4. Women’s Marriage Outcomes, by Religion Post the Gujarat Riots of 2002

||(1)<br>Age at<br>Marriage|(2)<br>Married Before<br>Age 18|(3)<br>Age at<br>Cohabitation|(4)<br>Age at<br>First Sex|(5)<br>Age at<br>First Birth|
|---|---|---|---|---|---|
|Post X Riot|-0.326<sup>_∗∗∗_</sup>|0.043<sup>_∗∗∗_</sup>|-0.261<sup>_∗∗∗_</sup>|-0.395<sup>_∗∗∗_</sup>|-0.021|
||(0.081)|(0.015)|(0.070)|(0.056)|(0.080)|
|Post X Riot X Muslim|-0.155|0.031<sup>_∗_</sup>|-0.149|-0.065|-0.160|
||(0.234)|(0.018)|(0.243)|(0.205)|(0.253)|
|Observations|415441|425254|405697|418219|389744|
|R-squared|0.247|0.164|0.216|0.228|0.128|
|Control Average|19.47|0.323|19.49|19.41|21.04|
|District Fixed Efects|Yes|Yes|Yes|Yes|Yes|
|Year Fixed Efects|Yes|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|Yes|

_Note_ : This table reports coefficients from specification 3. Standard errors are clustered at the state level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

Table 5. Women’s Educational Outcomes Post the Gujarat Riots of 2002

||(1)<br>Years of<br>Education|(2)<br>At least Completed<br>Primary School|(3)<br>At Least Completed<br>Secondary School|(4)<br>Completed<br>Higher Education|
|---|---|---|---|---|
|Post X Riot|-0.388<sup>_∗∗∗_</sup>|-0.016|-0.018<sup>_∗∗_</sup>|-0.016<sup>_∗_</sup>|
||(0.096)|(0.010)|(0.008)|(0.008)|
|Observations|423957|423957|423957|423957|
|R-squared|0.483|0.330|0.369|0.211|
|Control Average|7.405|0.781|0.648|0.130|
|District Fixed Efects|Yes|Yes|Yes|Yes|
|Year Fixed Efects|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|

_Note_ : This table reports coefficients from specification 1. Standard errors are clustered at the state level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

28
Table 6. Women’s Social Status After Marriage Post the Gujarat Riots of 2002

||(1)<br>Controlled by<br>Husband|(2)<br>Emotional<br>Violence|(3)<br>Physical<br>Violence|(4)<br>Makes Health<br>Decisions|(5)<br>Makes Decisions<br>about Visits|
|---|---|---|---|---|---|
|Post X Riot|0.003|0.028<sup>_∗∗∗_</sup>|0.045<sup>_∗∗∗_</sup>|-0.001|-0.019<sup>_∗∗_</sup>|
||(0.004)|(0.003)|(0.005)|(0.006)|(0.007)|
|Observations|55133|55162|55162|70700|70700|
|R-squared|0.135|0.0557|0.124|0.0643|0.0760|
|Control Average|0.474|0.118|0.280|0.740|0.730|
|District Fixed Efects|Yes|Yes|Yes|Yes|Yes|
|Year Fixed Efects|Yes|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|Yes|

_Note_ : This table reports coefficients from specification 1. Standard errors are clustered at the state level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

Table 7. Women’s Economic Status After Marriage Post the Gujarat Riots of 2002

||(1)<br>Employed in<br>Last 12 months|(2)<br>Controls own<br>Income|(3)<br>Makes Household<br>Purchase Decisions|
|---|---|---|---|
|Post X Riot|-0.017<sup>_∗∗∗_</sup>|-0.022<sup>_∗∗∗_</sup>|-0.050<sup>_∗∗∗_</sup>|
||(0.002)|(0.007)|(0.004)|
|Observations|423957|16043|70700|
|R-squared|0.0208|0.108|0.0687|
|Control Average|0.871|0.817|0.717|
|District Fixed Efects|Yes|Yes|Yes|
|Year Fixed Efects|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|

_Note_ : This table reports coefficients from specification 1. Standard errors are clustered at the state level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

29
# **Figures**

Figure 1. Women’s Marriage Age/Probability of Women’s Marriage Before Age 18 Post the Gujarat riots of 2002

## (a) Womens Marriage Age

<!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>(b) Probability of Women’s Marriage Age Before Age 18<br>Marriage Year<br>Data Source: NFHS-4<br>.5<br>0<br>-.5<br>Diff-in-diff Coefficients<br>-1<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br>.15<br>.1<br>.05<br>Diff-in-diff Coefficients<br>0<br>-.05<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. In subfigure (a), the outcome variable is women’s age at marriage. In subfigure (b), the outcome variable is an indicator for women’s marriage before age 18. Standard errors were clustered at the state-year level for both subfigures.

30
# **A Event Study Approach Using Gujarat and Its Bordering States Only**

Figure A.1. Women’s Marriage Age Post the Gujarat Riots of 2002 <!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>.5<br>0<br>-.5<br>Diff-in-diff Coefficients<br>-1<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. The outcome variable is women’s age at marriage. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level.

31
Figure A.2. Women’s Marriage Before Age 18 Post the Gujarat Riots of 2002 <!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>.2<br>.1<br>0<br>Diff-in-diff Coefficients<br>-.1<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. The outcome variable is an indicator of women’s marriage before age 18. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level 32
# **B Synthetic Controls**

Figure B.1. Synthetic Controls: Women’s Age at Marriage Post the Gujarat Riots of 2002 <!-- Start of picture text --> 1990 1995 2000 2005 2010 2015<br>year<br>gujarat synthetic gujarat<br>21<br>20<br>19<br>age_marriage<br>18<br>17<br><!-- End of picture text --> _Note_ : This figure plots the estimates using synthetic controls approach and NFHS-IV. The outcome variable is women’s average age at marriage.

33
Figure B.2. Synthetic Controls: Effect of Gujarat Riots on Women’s Marriage Before Age 18 <!-- Start of picture text --> 1990 1995 2000 2005 2010 2015<br>year<br>gujarat synthetic gujarat<br>.5<br>.4<br>.3<br>child_marriage<br>.2<br>.1<br><!-- End of picture text --> _Note_ : This figure plots the estimates using synthetic controls approach and NFHS-IV. The outcome variable is the fraction of women who got married before age 18.

34
# **C Alternative Estimates**

Figure C.1. Women’s Marriage Age Post the Gujarat Riots of 2002: Borusyak et al. (2021) Estimation <!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>.5<br>0<br>-.5<br>Diff-in-diff Coefficients<br>-1<br>1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. The outcome variable is women’s age at marriage. The control states include all other states of India. Standard errors were clustered at the state-year level.

35
Figure C.2. Probability of Women’s Marriage Before Age 18 Post the Gujarat Riots of 2002: Borusyak et al. (2021) Estimation <!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>.1<br>.05<br>0<br>Diff-in-diff Coefficients<br>-.05<br>-.1<br>1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. The outcome variable is an indicator of women’s marriage before age 18. The control states include all other states of India. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level 36
Figure C.3. Women’s Marriage Age Post the Gujarat Riots of 2002: Borusyak et al. (2021) Estimation Using Neighboring States as Control <!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>1<br>.5<br>0<br>Diff-in-diff Coefficients -.5<br>-1<br>1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. The outcome variable is women’s age at marriage. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level. Standard errors were clustered at the state-year level.

37
Figure C.4. Women’s Marriage Before Age 18 Post the Gujarat Riots of 2002: Borusyak et al. (2021) Estimation Using Neighboring States as Control <!-- Start of picture text --> Marriage Year<br>Data Source: NFHS-4<br>.2<br>.1<br>0<br>Diff-in-diff Coefficients<br>-.1<br>1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV. The outcome variable is an indicator of women’s marriage before age 18. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level 38
# **D Dropping Flood Districts**

Figure D.1. Women’s Marriage Age Post the Gujarat Riots of 2002 <!-- Start of picture text --> .5<br>0<br>-.5<br>-1<br>Marriage Year<br>Data Source: NFHS-4<br>Diff-in-diff Coefficients<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV dropping all flood affected districts. The outcome variable is women’s age at marriage. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level.

39
Figure D.2. Probability of Women’s Marriage Before Age 18 Post the Gujarat Riots of 2002 <!-- Start of picture text --> .2<br>.1<br>0<br>-.1<br>Marriage Year<br>Data Source: NFHS-4<br>Diff-in-diff Coefficients<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014<br><!-- End of picture text --> _Note_ : This figure plots the difference-in-differences estimates from specification 2 using NFHS-IV dropping all flood affected districts. The outcome variable is an indicator of women’s marriage before age 18. The control states only include the bordering states of Gujarat, which are Maharashtra, Rajasthan and Madhya Pradesh. Standard errors were clustered at the state-year level 40
# **E Additional Tables**

Table E.1. Balance for Predictors of Marriage Age Across Gujarat and Synthetic Gujarat

||(1)<br>Gujarat|(2)<br>Synthetic Gujarat|
|---|---|---|
|Muslim|0.073|0.073|
|SC/ST/OBC|0.740|0.739|
|Male Household Head|0.890|0.889|
|Poor|0.282|0.281|
|Rich|0.491|0.491|
|Rural Resident|0.637|0.637|

_Note_ : This table reports means of variables that are used to predict age at marriage from 1990 to 2001 across Gujarat and Synthetic Gujarat. The variables represent the proportion of muslims, SC/ST/OBC, Male Household Heads, Poor, Rich and Rural Resident in Gujarat and Synthetic Gujarat.

41
Table E.2. Women’s Marriage Age (Dropping Earthquake Districts) Post the Gujarat Riots of 2002

||(1)<br>Age at<br>Marriage|(2)<br>Married Before<br>Age 18|
|---|---|---|
|Post X Riot|-0.279<sup>_∗∗∗_</sup>|0.061<sup>_∗∗∗_</sup>|
||(0.102)|(0.016)|
|Observations|93826|95530|
|R-squared|0.219|0.151|
|Control Average|18.63|0.388|
|District Fixed Efects|Yes|Yes|
|Year Fixed Efects|Yes|Yes|
|Controls|Yes|Yes|

_Note_ : This table reports coefficients from specification 1 only including Gujarat and its neighboring states. Standard errors are clustered at the state-year level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male houshold head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

Table E.3. Effect of Political Power Change on Women’s Marriage Age

||(1)<br>Age at<br>Marriage|(2)<br>Married Before<br>Age 18|
|---|---|---|
|Post 1995 X Gujarat|0.180<sup>_∗_</sup><br>(0.107)|0.013<br>(0.017)|
|Observations|42046|43237|
|R-squared|0.152|0.102|
|Control Average|16.96|0.560|
|District Fixed Efects|Yes|Yes|
|Year Fixed Efects|Yes|Yes|
|Controls|Yes|Yes|

_Note_ : This table reports coefficients from specification 1 only including Gujarat and its neighboring states. Standard errors are clustered at the state-year level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

42
Table E.4. Women’s Marriage (Dropping Flood Districts) Post the Gujarat Riots of 2002

||(1)<br>Age at<br>Marriage|(2)<br>Married Before<br>Age 18|
|---|---|---|
|Post X Riot|-0.346<sup>_∗∗∗_</sup>|0.068<sup>_∗∗∗_</sup>|
||(0.089)|(0.016)|
|Observations|91781|93416|
|R-squared|0.219|0.151|
|Control Average|18.63|0.388|
|District Fixed Efects|Yes|Yes|
|Year Fixed Efects|Yes|Yes|
|Controls|Yes|Yes|

_Note_ : This table reports coefficients from specification 1 only including Gujarat and its neighboring states. Standard errors are clustered at the state-year level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

43
# **F Discussion of Mechanisms**

Table F.1. Effect of Gujarat Riots on Men’s Marriage Outcomes

||(1)<br>Age at<br>Marriage|(2)<br>Married Before<br>Age 18|
|---|---|---|
|Post X Riot|-0.861<sup>_∗∗∗_</sup>|0.028<sup>_∗∗_</sup>|
||(0.078)|(0.012)|
|Observations|56436|58122|
|R-squared|0.280|0.115|
|Control Average|24.35|0.0554|
|District Fixed Efects|Yes|Yes|
|Year Fixed Efects|Yes|Yes|
|Controls|Yes|Yes|

_Note_ : This table reports coefficients from specification 1. Standard errors are clustered at the state level. Control Variables include indicators for religion, sc/sct/obc, rural residence, wealth quintiles, and male household head.

* Significant at 10%; ** Significant at 5%; *** Significant at 1%.

44
Table F.2. Heterogeneous Treatment Effect on Sex Ratio by Age Groups

|Sex Ratio (Women/Men)|Sex Ratio (Women/Men)|
|---|---|
|(1)|(2)|
|_Post × Riot × Age_||
|0-9<br>-0.114***<br>|-0.0537**<br>|
|(0.0136)|(0.0219)|
|10-14<br>-0.117***|-0.0515**|
|(0.0137)|(0.0208)|
|15-19<br>-0.0861***|-0.0141|
|(0.0213)|(0.0192)|
|20-24<br>-0.0898***|-0.0294|
|(0.0259)|(0.0190)|
|25-29<br>-0.117***|-0.0693***|
|(0.0226)|(0.0210)|
|30-34<br>-0.0748***|-0.0627***|
|(0.0186)|(0.0194)|
|35-39<br>-0.0846***|-0.0469**|
|(0.0164)|(0.0214)|
|40-44<br>-0.00877|0.0194|
|(0.0130)|(0.0213)|
|45-49<br>-0.0300***|-0.00814|
|(0.00923)|(0.0198)|
|50-54<br>-0.0137**|0.0270|
|(0.00662)|(0.0203)|
|55-59<br>-0.0477***|-0.0842***|
|(0.0131)|(0.0251)|
|60-64<br>-0.0393***|-0.0712*|
|(0.0128)|(0.0402)|
|65-69<br>0.0144|-0.0302|
|(0.0121)|(0.0184)|
|70-74<br>0.0767***|0.0831***|
|(0.0214)|(0.0274)|
|75-79<br>0.137***|0.0745**|
|(0.0209)|(0.0335)|
|80+<br>0.192***|0.119**|
|(0.0298)|(0.0463)|
|Constant<br>0.723***|0.879***|
|(0.0149)|(0.0282)|
|Observations<br>1,190|136|
|R-squared<br>0.501|0.882|
|Num. Clusters<br>35|-|
|Sample<br>Complete|Neighboring States|
|Robust SE<br>No|Yes|
|Year FE<br>Yes|Yes|
|State FE<br>Yes|Yes|
|Age Group FE<br>Yes|Yes|

_Note:_ This table reports coefficients from specification 4. The first column reports the results using the rest of India as control, and the second column reports results using only the neighboring states as controls. While column (1) standard errors clustered at the state level, column (2) reports the robust standard error since, with neighboring states, there are only 4 clusters. * Significant at 10%; ** Significant at 5%; *** Significant at 1%.

45