Reassessing The Unequal Burden of War: The Effect of Armed Conflict on the Gender Gap

in Life Expectancy

Abstract

What impact does civil conflict have on the health of women? While fewer women are directly in the line of fire on the battlefield, civilian populations are now bearing a greater proportion of the violence associated with these wars. In this article, we explore how that burden is distributed in societies. Using a new dataset (Centre for Research on the Epidemiology of Disasters 2014; Gleditsch et al. 2002; Marshall, Gurr, and Jaggers 2014; OECD 2009; Pemstein, Meserve, and Melton 2010; World Bank 2014), we find evidence that women are not bearing a disproportionate share of the health costs associated with war, which has policy implications for policies designed to create particular protections for women and children. Our analysis complements and builds on the emerging literature on the public health effects of armed conflict (Allen and Lektzian 2013; Ghobarah, Huth, and Russett 2003b; Iqbal 2006) and offers a new view on the human costs of war.

1 Introduction

Whether we immediately realize it or not, armed conflict is a public health problem (Murray et

al. 2002). As more under-developed countries experience civil conflict, the challenge of

responding to these public health problems becomes greater and the burden falls more and

more on the civilian population. Foege (2000, p. 4) notes that “in recent conflicts, it has been

reported that nine civilians have died for every soldier killed, and UNICEF reports that in the

past decade two million children have died because of conflicts, more deaths in children than in

soldiers.” These tragic facts paint a stark picture of the risks created by armed conflict today. In

2012, thirty-one of the thirty-two active conflicts in the world were intrastate conflicts

(Themner and Wallensteen 2013). These conflicts have greater public health consequences than

interstate conflicts as all the fighting is done on home territory, which raises the social costs of

civil war (Collier 2003).

Numerous UN and NGO reports have emphasized the health risks that modern conflict

poses to women (e.g., Bouta, Frerks, and Bannon 2005; Rehn and Sirleaf 2002). According to

Major General Patrick Cammaert, who served as the Deputy Force Commander of the United

Nations Mission to the Democratic Republic of Congo, “It is now more dangerous to be a

woman than to be a soldier in modern wars,” (quoted in (Behuria 2014)). To support this claim,

many point to the fact that now more than 90% of those who die in conflict are noncombatants

as proof of the increased risk of mortality and morbidity of women. If women are suffering more

during war, we should expect the life expectancy gap between men and women (who naturally

live longer) to decrease.

On the other hand, the empirical research is mixed on the relative health effects of conflict

by gender. Plümper and Neumayer (2006) finds evidence that women bear a greater burden,

but Li and Wen (2005) finds that in interstate wars, the immediate health costs are greater for

men but that lingering effects may impact women more over time. The results of Hoddie and

Smith (2009) vary by age cohort. Several of these studies did not concentrate on the issues of

gender and civil war, so we turn the focus more directly to these issues.

The arguments in favor of armed conflict diminishing the life expectancy gap between men

and women can be categorized in three ways – the economic effects, the health risks associated

with displacement (either internal or for refugees), and sexualized violence. Indirect

consequences are important, but we argue that men and women behind the battle lines suffer

these consequences in fairly similar ways. We also assert that changes in recruitment strategies

also influence the inference that can be drawn concerning the increased threat that civil conflict

poses to non-combatants. While we do not wish to downplay the risks associated with

displacement and sexual violence, we question the evidence that suggests a gender imbalance

towards in the suffering associated with armed conflict.

When wars are fought, lives are lost on the battlefield, infrastructure is damaged or

destroyed, and long-term damage is done to the economic, educational, and public health

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systems (Allen and Lektzian 2013; Ghobarah, Huth, and Russett 2004; Iqbal 2006; Lai and Thyne

2007). In addition, resources are diverted way from public programs that will influence health

outcomes. Militarized conflicts have both direct and indirect consequences on the morbidity

and mortality of a society. War damages infrastructure, breaks down health care systems, and

degrades societies. These indirect costs can negatively impact a country’s standard of health for

many years following the termination of fighting.

The indirect consequences of conflict on health and survival are an important part of the

story of conflict, and we agree with Lacina and Gleditsch (2005, p. 7) that direct conflict fatalities

do “not provide a remotely adequate account of the true human costs of conflict.” We do,

however, raise questions about who is suffering these indirect costs and challenge the evidence

presented by Plümper and Neumayer (2006, p.724) that “women are overall more negatively

affected by armed conflict than men.” The indirect costs of conflict will be spread throughout a

country’s population and will harm men and women alike (Buvinic et al. 2013).

Additionally, little attention has been paid to changes in the fighting forces that have

accompanied the changes in conflict form. A recent survey of combat participants in 55

countries found that women were actively involved in violence in 38 of them (cited in (Stewart

2010)). Women participated in the Rwanda genocide (Wood 2009); belong to paramilitaries and

self-defense groups in Haiti (Faedi 2010); and engaged in acts of sexual violence in Liberia

(Specht 2006) and in the Democratic Republic of Congo (Johnson et al. 2010). Whether they are

abducted as child soldiers or are recruited directly, women are participating in conflict more.

These facts are only important for determining who is and is not considered a combatant when

making inferences about increased violence against civilians.

In this article, we discuss the concept of human security and explore the indirect costs of war

as well as changes in patterns of conflict recruitment and participation that have accompanied

the changes in conflict. Utilizing new and more complete data to further examine the gender

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balance of the burden of civil conflict. The analysis presented here complements and builds on

the emerging literature on the public health effects of armed conflict, as severe conflicts can

affect major public health indicators for years after the fighting has ceased (Davis and Kuritsky

2002; Ghobarah, Huth, and Russett 2003a). Our analysis demonstrates that while conflict

continues to be associated with high levels of mortality and morbidity, the increased burden of

war on civilians has not caused the risks for women to surpass those for men.

This article will proceed as follows: first, we examine the impact of civil conflict on health.

Next, we look more closely at the gendered effects, challenging some of the conventional

wisdom about how the burden is distributed within civil war states. To compare traditional

arguments with our updated perspective, we introduce new data. Empirical analysis is

presented and conclusions are discussed.

2 The Impact of Civil Conflict on Health

The inter-relationship between health and security runs deep and forms part of the foundation

of the concept of development (Sen 1999). Civil wars harm economic growth and weaken both

social and physical capital, which can have far-reaching effects for the population’s well-being

(Collier 1999; Minoiu and Shemyakina 2012).1 Resources needed to fund these conflicts are

drawn disproportionately from public goods programs like health services, education, and

policing. Even after the fighting ends, resources are seldom immediately restored to their

previous levels causing civilians to continue to suffer negative consequences during and after

the fighting (Collier et al. 2003).

The damage to social capital and social networks is often under-appreciated as families are

separated or destroyed. In developing countries, where families often constitute the primary

1 A civil conflict is defined by the UCDP/PRIO data project as a contested incompatibility that concerns a government and/or territory where the use of armed force between a government and a non-government party that results in at least 25 battle-related deaths (Gleditsch et al. 2002).

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form of insurance, the death of workers and displacement of individuals away from other family

members and family land can have an adverse effect on health and security in the society even

after the conflict ends (Blattman and Miguel 2010). Thus, the impacts of conflict may extend far

into the future, well after armed conflict ceases.

Because of the growing number of humanitarian crises that accompany civil conflict as well

as the increased attention given to them, the international community’s definition of security

has broadened to reflect this link with health and well-being. No longer is the cessation of

hostilities sufficient to renew a sense of security; the new concept of security is the more

inclusive idea of human security, which includes political security, economic security, food

security, health security, environmental security, personal security (United Nations

Development Program 1994). This is a much more individualized view of security, moving away

from traditional state-based concepts.

When civil war causes an increase in mortality and morbidity, the labor force and the stock

of human capital is damaged (Blattman and Miguel 2010). This damage diminishes economic

growth and also weakens physical and social capital in conflict states (Minoiu and Shemyakina

2012). Civil wars are particularly damaging because not only are the direct effects of conflict

concentrated within a single society, the indirect effects are also concentrated in a similar

manner, and these indirect effects have far-reaching consequences for the civilian population.

3 Gender and Mortality in Civil Conflict

Should we expect differences in mortality based upon gender in civil conflicts? The effects of

armed conflict in developing countries are unlikely to be gender-neutral (Minoiu and

Shemyakina 2012). On the one hand, the number of men whose deaths are associated with

armed conflict typically exceed the death toll for women (Burnham et al. 2006; Das Gupta and

Shuzho 1999; Newth 1964; Roberts et al. 2004). As a programme officer for the US Office of

Disaster Assistance noted, “Men are more vulnerable to getting killed. That’s a pretty big deal.

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Getting sick, getting raped, getting attacked are all pretty bad things but dead is dead,” (quoted

in Carpenter (2006b)).

On the other hand, the health effects of conflict on men may be more concentrated in the

short and medium-term, while the effects for women have the potential to be longer term

(Ghobarah, Huth, and Russett 2003a). Yet, several existing studies do suggest that on balance

that the impact of civil conflict is disproportionately felt by women (Plümper and Neumayer

2006; Rehn and Sirleaf 2002). Gates et al. (2010) find a deleterious effect in fragile states, but it

is unclear whether the conflict or state fragility is the driving factor.

Why should women suffer more in civil conflict than men? The existing literature posits

three mechanisms to explain the greater impact of conflict on women: the economic damage

effect, the displacement effect, and the sexual violence effect.

The death of men in civil conflict increases the percentage of female-headed households in

society. These women face increased challenges of survival as clean water, food, fuel, electricity,

and medicine are likely to be scarce (Ashford 2008). In societies where women lack political

rights or legal protections for basic rights like property ownership, these challenges are

magnified.

Civil conflict can have long term effects on marriage markets, fertility, and the availability

and quality of public health provision (Minoiu and Shemyakina 2012). Women are more likely to

be displaced than men. Often health conditions in refugee or IDP camps are poor, and

reproductive health services are unlikely to be provided in these facilities as the primary

concerns tend to be on essential needs like food, water, shelter, and the most basic health care

(McGinn 2000).

The economic damage effect is potentially the most potent. When infrastructure is damaged

or destroyed, long-term devastation is done to the economic, educational, and public health

systems (Allen and Lektzian 2013; Ghobarah, Huth, and Russett 2003a; Iqbal 2010; Lai and

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Thyne 2007). Diminished and diverted resources from public program negatively influence

health outcomes. Famine and malnutrition may arise due to damage to the agricultural system,

and clean water may be compromised.

Once a conflict concludes defense spending does not immediately return to its pre-war levels.

For at least a decade following the conflict military spending hovers around 4.5% of GDP on

average (Collier and Hoeffler 2002). In addition, Knight, Loyaza, and Villanueva (1996) predict a

permanent loss of roughly two percent of GDP because of the destructive nature of military

spending for civil war, and this only considers the government side of the equation. Indirectly,

civil wars lead to degraded public health systems, capital flight, and brain drain – all of which

inhibit a country’s ability to recover from civil war. Anyone living in a post-conflict society will

face the limitations.

All of these indirect economic costs of war have potentially large consequences for

morbidity and mortality. On their own, infectious diseases are the biggest cause of morbidity

and mortality. When armed conflict is added to the mix, it can serve as an amplifier of disease

(Price-Smith 2002). Disease and conflict can also create a vicious circle as they both serve to

lower state capacity, level of economic productivity, and increase inequality. There is no reason,

however, to expect that the indirect costs of war will not also affect men. Carpenter (2006a)

points to flaws in the hypothesis that all able-bodied men are likely to be mobilized in these civil

conflicts; many remain home or desert in an effort to return home. These men are just as likely

to suffer from the economic damage of war as women.

The second mechanism we consider is the displacement effect, and here women may be at a

disadvantage. Women and children comprise about three quarters of the refugees worldwide.

Refugee camps have notoriously poor health care conditions. Toole (1997) reports mortality

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rates that are up to 100 time higher in these camps than the normals rates in the affected

countries.

Single-parent households led by women dominate the populations in refugee camps (Rehn

and Sirleaf 2002). A lack of health services plus conditions that are favorable to disease and the

spread of disease dominate these camps. For example, Montalvo and Reynal-Querol (2007)

finds that for every 1,000 refugees received an additional 2,700 cases of malaria occur in the

receiving country. Congested camps in Ethiopia in the late 1980s had a huge outbreak of typhus,

and dysentery and cholera devastated Rwandan refugees in 1994 (WHO 2003, 223).

Related to displacement, immunization rates often drop precipitously during conflict. Davis

and Kuritsky (2002) reports a 26% decrease in DPT immunizations in sub- Saharan Africa from

1980-1997 in conflict countries. Similarly decreased rates were also seen in Latin American

conflicts of the late 1980s like that in El Salvador (Ugalde et al. 2000).

Finally, sexualized violence in conflict is often targeted against women. Cohen (2013)

suggests that while wartime rape may be devastating for both the victims and the perpetrators,

it should be considered independently from lethal uses of force, building on Wood (2009) which

notes that patterns of rape are distinct from those associated with homicide and displacement

in war. In addition, as has been noted above, rape is often the alternative for mass killings of

male populations, especially in circumstances of ethnic conflict. Neither alternative is a healthy

outcome, but the mortality effects for men are greater in these situations.

4 The Changing Face of War

We argue that the theoretical basis of the unequal burden arguments are flawed because they

fail to take into account the reality of civil conflict. More specifically, we argue that the previous

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research has underestimated the extent to which women participate as combatants in conflict

and overestimated the impact of long-term effects of conflict on both men and women.

To begin, the assumption that men are combatants and women are noncombatants is

flawed. As the concept of security has evolved, so too have the battlefields. War may be the

most gendered of all human behaviors (Goldstein 2001), but the majority of the literature on

gender and conflict focuses on the experiences of women in war (Carpenter 2006a). While we

do not aim to denigrate the experiences of women, we instead posit that men in conflict zones

also face unique challenges due to their gender. Adult males are rarely perceived as civilians in

conflict zones, which goes against the spirit of the laws of war that suggest that innocence

should be determined by what an individual does rather than who an individual is (Carpenter

2006a). Women and adolescents can easily be combatants (Dombrowski 1999; Moser and Clark

2001), and men can also be civilians.

Despite a burgeoning research agenda on civil wars, very few efforts have been made to

quantitatively assess who participates in these conflicts. Notable exceptions in political science

include Arjona and Kalyvas (2006), Humphreys and Weinstein (2008), and Verwimp (2005).

While all of these studies show that men make up the majority of both rebel and government

forces in civil conflict, they also demonstrate that these armies are not universally male. There is

variation in gender and in age. The assumption that all armies are composed of young men 18-

35 is outmoded. Too often women are only considered as victims of conflict, neglecting the role

that they can and often do play as agents of conflict. In Uganda, for example, during the “Bush

War”, women not only fought as combatants for the National Resistance Army but served in

leadership positions (Tripp 2015). A variety of studies have noted that between 5-15% of

government military personnel are women, and the rates are often higher in guerrilla groups

(Goldstein 2001). It is estimated that between 20-30% of combatants were women in the

Liberian civil conflict of the 1990’s (Tripp 2015). Women’s roles vary greatly across conflict

contexts (Thomas and Bond 2015; Thomas and Wood 2017; Wood and Thomas 2017).

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Despite this evolution of conflict, the shorthand assertion continues to be that women and

children make up the civilian population and the men are the combatants – an assumption that

Sjoberg and Gentry (2007) take issue with, for good reason. Empirically, this is not the case.

Women also engage in violence as well. “Almost all soldiers are men, but most men are not

soldiers,” (Connell 2000, p. 215). The majority of adult males are not mobilized in the average

conflict (Carpenter 2006a). Age and gender are too often employed as proxies for determining

who is a civilian and who is a combatant.

Men who are not direct participants in civil wars are frequently the targets of mass killing

and a range of other atrocities. The mass killing of men who are of the age to be fighters has a

long history (Jones 2002). In antiquity as is described in the defeat of the city of Troy, the men

were killed, women raped, and children enslaved (Kurper 1981). Modern civilian victimization

often follows this pattern. While the perpetrators of these acts tend to be male, strategies of

genocide and other types of civilian victimization prioritize male victims (Carpenter 2003,

2006a). Adult males were the non-combatants most likely to be targeted in the Balkan Wars,

despite the international community’s focus on atrocities towards women and children

(Carpenter 2003). Because young men and adolescents are perceived to be potential or future

combatants, they are aggressively targeted in civilian victimization campaigns and genocides.

Not every citizen can be effectively mobilized by either rebel or government forces. The

portion of population that is mobilized in conflict varies. The issues at stake and the incentives

that the groups can provide to entice individuals to overcome the collective actions problem will

influence who fights and who does not.

Recruitment strategies play a big role in determining mobilization. Drawing on testimony

from Sierra Leone’s Truth and Reconciliation Commission, Humphreys and Weinstein (2008, p.

3) provides a quote from former Liberian leader Charles Taylor describing the Revolutionary

United Front’s strategy:

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Look, whenever you are fighting war, the strength of any revolutions, it depends on the manpower, the manner in which you carry out your recruitment ...They have to recruitwhoever they meet: old people, young people, young girls, young boys.

As the conflict continued, RUF recruits included captives from raids and abducted children, both

boys and girls, from refugee camps (Humphreys and Weinstein 2008). Typically, men and boys

are more frequent targets for forced recruitment, but clearly this is not always the case.

Gender-based violence during war can also be directed toward men during conflict, but it

typically may not take a sexual form the way that gender-based violence toward women does.

Instead men are more likely to be the victims of gender-specific massacres and forced

recruitment (Carpenter 2006b). Men may also be the victims of sexual violence, and women can

also be the perpetrators of such crimes (Cohen 2013). Norms regarding gender roles during

conflict have created a false dichotomy between men as warriors and women as victims.

These generalizations about who is a combatant and who is a civilian have policy

implications. Every social group other than adult men tend to get special attention in terms of

humanitarian protection. United Nations Security Council Resolution 1325 focuses on combating

violence against women and girls in conflict zones. Belligerents are more likely to target men

than women, but males, even civilian men, are less likely to be offered protections by non-

governmental organizations or international organizations. Civilian males remain “the big

forgotten ones, the ones nobody talks about” (ICRC Interview 2002 quoted in Carpenter

(2006a)).

Combatant men die on the battlefield, but civilian men are dying behind the front lines.

These deaths are often ignored as we focus on the deaths of “innocents” – women and children.

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By ignoring the presence of large groups of civilian males and the violence perpetrated against

them, we under-estimate the mortality risks for men in conflict zones.

It is also problematic to assume that the long-term effects of conflicts fall only on women.

Efforts to examine the human consequences of war are relatively new in political science. In

economics, it has been recognized that the social and economic costs of civil conflict are deep

and long lasting (Collier and Fosu 2005), but much of the scholarly attention has been on the

costs that accrue during the fighting rather than those which are persistent (Chen, Loayza, and

Reynal-Querol 2008). In general, there is little empirical analysis on the residual effects of

conflict – either for civil or interstate wars. The exceptions have focused on post-conflict

economic recovery (examples include (Collier and Hoeffler 2004; Organski and Kugler 1977;

Przeworski et al. 2000).

Within political science, recent work examining the health consequences of war begins to

address post-conflict political implications. Murray et al. (2002, p. 346) emphasizes that war

should be considered a public health problem that continues to have negative effects even after

the fighting ends through “the displacement of populations, the breakdown of health and social

services, and the heightened risk of disease transmission.” While the direct deaths from conflict

peaked around 1994 and have begun to decline, the rate of indirect deaths continues to

increase (Stockholm International Peace Research Institute 2007).

Ghobarah, Huth, and Russett (2003b) demonstrates that both international and civil wars

reduce quality of life and lower the life expectancy when countries engage in war. Fighting a

civil war requires an allocation of state resources as government spending is shifted away from

public services and into the military. Collier and Hoeffler (2002) notes that military spending

typically grows from roughly 2.8% of GDP to around 5% in developing countries where civil war

occurs. This shifting take funding away from governmental programs like public health and

education that typically benefit the economy or the general population. Often this reallocation

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begins even before shots are fired. These economic consequences affect the entire population

after the find ends.

When the shooting stops and combatants return home, the indirect effects of conflict often

remain. Damage to croplands leads to food shortages, wrecked infrastructure curtails the

transportation of goods and labor, a degraded health sector cannot tend to all the needs of the

population – the list could go on. Returning to pre-war status-quo economic growth and public

good spending is difficult to achieve (Rehn and Sirleaf 2002), particularly because governmental

institutions are also weakened by conflict. Not only has money been allocated away from social

programs during the conflict, even after the war ends it is clear that civil wars disrupt the state’s

ability to provide basic social services (Lai and Thyne 2007). These effects have an impact on

both men and women.

Civil wars occur more frequently in low-income countries with weak economies, and conflict

only serves to compound their economic difficulties (Collier 2006). Conflict increases the risks of

mortality and morbidity in these states while at the same time diminishing their ability to cope

with the problems (Foege 2000). Such states are also at greater risk for conflict recurrence

(Collier and Hoeffler 2004). The period after a civil war is challenging for governments looking to

build a stable recovery. One of the most important factors in whether or not violence will recur

is the strength of the economy, and its ability to bounce back from the conflict (Collier 1999).

The uncertainty associated with civil war tends to alter the economic activities that society

engages in and the subsistence focus that is often adopted is less productive over the long-term.

Unlike earlier studies that found evidence of a “Phoenix Factor”, or economic resurgence

often experienced by states immediately following interstate wars (Organski and Kugler 1977,

1980), Kang and Meernik (2005) finds little support for the idea that the economy of civil war

states will rebound quickly following conflict. Very few countries that have experienced lengthy

and violent civil conflict have the capacity to rebuild their infrastructure – either politically or

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economically. When taken with the fact that poverty is often a driving cause of civil war (Collier

and Hoeffler 2002), the economic conditions in post-conflict societies are often very poor. This

has direct implications for the health and well-being of these populations.

Once the fighting has ended, states that have engaged in civil wars must carefully begin to

rebuild their economies, their governments, and societies. Because of the high risk of renewed

violence, societies must thoughtfully manage these transitions (Quinn and Gurses 2007).

Spending to enhance primary health care and education takes on greater importance for growth

in post-conflict settings (Collier 2006). The transition away from conflict provides an important

opportunity for reassessing social policies overall, and health policy in particular (Macrae, Zwi,

and Gilson 1996).

Historically, men on the front lines and women on the home front have suffer differently in

war. They died different deaths in war; their injuries were different; and their vulnerabilities to

disease were distinct. The indirect health effects of war come about due to reduced access to

food, health services, and clean water. War damages infrastructure – destroying hospitals and

the roads and bridges needed to get to those hospitals. Fighting damages crops and agricultural

land. This damage is not easily or quickly fixed; thus these consequences of war are likely to

affect non-combatants for many years following the cessation of fighting. But as the line

between combatant and non-combatant has become blurred, so too has the line between

men’s deaths and women’s deaths in war. We question whether or not the indirect effects of

conflict are only affecting women. Civilian males are also suffering these deaths, which

contribute to the mortality risks for men in conflict zones.

Based on the above logic, we question whether women will suffer the costs of conflict more

than men. If our logic is correct, then we expect the impact of civil conflict to affect the health of

both men and women. Consequently, we expect to that there is no “unequal” burden of conflict

on women’s health.

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5 Data and Methods

To test our argument, we created a cross-sectional time-series dataset that includes data from

153 countries between 1961 and 2011. Following previous research (Plümper and Neumayer

2006; Smith and Haddad 2002), we measure the gendered impact of conflict on health using the

ratio between female and male life expectancy.2 Differences in the ratio can indicate the

existence of gender inequalities (Beer 2009). This measure allows us to measure the overall

effect of conflict though life expectancy. By using a ratio of female to male life expectancy, we

can determine whether differences in the effect of conflict exist. Increases in the life expectancy

ratio would indicate that women are living longer relative to men. Decreases in the ratio would

indicate that men are living longer relative to women.

Figure 1 plots the global mean female to male life expectancy ratio and its standard

deviation in our dataset. Across time, the average life expectancy ratio has remained relatively

stable between 107 and 106; however, since the late 1970’s, there has been a slight, but

consistent, movement towards a more equal life expectancy ratio. Yet, the standard deviations

plotted around the yearly global means are quite large, indicating significant variability across

countries in our sample.

We estimate our equations using a multilevel linear regression model. We include random

intercepts for each individual country. Thus, we can control for different error variances across

countries. We found significant evidence of serial autocorrelation in our data (Drucker 2003;

2 The life expectancy data are taken from the World Bank’s World Development Indicators (World Bank 2014).

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Figure 1: Global Mean Life Expectancy Ratio

Wooldridge 2002). Thus, we specify an AR(1) residual structure for all models (Rabe-Hesketh

and Skrondal 2012).

We use two variables to measure conflict, “Interstate Conflict” and “Civil Conflict,” taken

from the UCDP/PRIO Armed Conflict Dataset v.4-2012, 1946-2011 (Gleditsch et al. 2002). The

“Interstate Conflict” dummy variable indicates whether there was an interstate conflict on the

territory of the country in a given year that resulted in at least 25 battlefield deaths. The “Civil

Conflict” variable indicates whether the country was engaged in a civil conflict that resulted in

at least 25 battlefield deaths.

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All of our models include the following control variables. We include the change in overall

life expectancy from the previous year (World Bank 2014). We include a measure of regime

stability, “Durable,” that measures the number of years since the last major regime change

taken from Polity IV (Marshall, Gurr, and Jaggers 2014). We code all country-years with the

median democracy

Figure 2: Impact of Civil and Interstate Conflict

score, “UDS Median,” taken from the Unified Democracy Score project (Pemstein, Meserve, and

Melton 2010). We included a logged version of real GDP per capita (“Log of GDP per Capita”) to

control for wealth (World Bank 2014). We also include the percentage of female labor force

participation, “Female Labor Force Participation” (OECD 2009; World Bank 2014). We include

the percentage of the population who lost their lives due to natural disasters in a given year,

“Pct. Death due to Natural Disaster.” The disaster data was taken from the Centre for Research

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% C.I.95First Difference

International ConflictCivil Conflict

Ratio

.2

.1

0

−.1

−.2

on the Epidemiology of Disasters (2014) and the population data were taken from World

Development Indicators (World Bank 2014). We also include a dummy variable, “Aids Infection,”

that codes as one all country-years where the rate of HIV/AIDS infection exceeded 10 percent of

the population. The HIV/AIDS prevalence data were taken from World Development Indicators

(World Bank 2014).

Table 1 presents the detailed parameter estimates. Figure 2 plots the first difference of

the impact on our ratio dependent variable of the “Civil Conflict” and “Interstate Conflict”

covariates from model 1.

To estimate the first differences, we set the values of all control variables at their means

and modes. We estimated the first differences using 10,000 Monte Carlo simulations to account

for uncertainty around the estimations. The results show little, if any, impact of conflict on the

ratio between female to male life expectancy ratio. On average, a civil conflict increases the

ratio, i.e. women live longer than men, by just over 0.1 percent. This difference is statistically

significant. There is no statistically significant impact of international conflict. The estimated first

difference is only -0.013 percent.

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Table 1: Impact of Conflict on Life Expectancy Ratio

Independent Model 1 Model 2 Model 3Variable b, (s.e.) b, (s.e.) b, (s.e.)Durable 0.001 -0.001 0.001

(0.002) (0.002) (0.002)

UDS Median -0.031 -0.026 -0.032(0.043) (0.042) (0.044)

Log of GDP per Capta -0.247* 0.276* -0.250*(0.113) (0.118) (0.113)

Female Labor Force Participation 0.001 0.001 0.001(0.002) (0.002) (0.002)

Pct. Death due to Natural Disaster -0.001 -0.000 -0.001(0.014) (0.013) (0.014)

AIDS Infection (1,0) 0.045 0.050 0.044(0.060) (0.057) (0.060)

Civil Conflictt 0.111*** 0.167*** 0.111***(0.033) (0.036) (0.033)

Civil Conflictt−1 0.184***(0.038)

Civil Conflictt−2 0.172***(0.039)

Civil Conflictt−3 0.158***(0.039)

Civil Conflictt−4 0.128***(0.037)

Civil Conflictt−5 0.044(0.035)

International Conflictt -0.012 0.007 -0.040(0.067) (0.064) (0.077)

International Conflictt−1 -0.063(0.088)

International Conflictt−2 -0.045(0.087)

International Conflictt−3 -0.030(0.086)

International Conflictt−4 -0.022(0.081)

International Conflictt−5 -0.013(0.069)

Intercept 108.593*** 104.337*** 108.612***

18

(0.980) (1.009) (0.982)

Σcountry 5.45E-10 6.57E-16 2.88E-132.04E-09 3.12E-15 5.43E-12

Ρ 0.996 0.996 0.9960.001 0.001 0.003

N 4464 4362 4463Countries 154 153 153

* p < 0.05, ** p < 0.01, *** p < 0.001

19

Figure 3: Lagged Impact of Civil Conflict

The impact of conflict may be felt beyond the initial time period of the conflict. To test this, we

ran two separate models that include lags of our main independent variables, “Interstate

Conflict” and “Civil Conflict,” going back 5 years. Figure 3 plots the first differences of our civil

conflict variable and its lags, model 2. The estimates were simulated as in the previous analysis.

We find statistically significant first differences for all variables except for the 5th year lag. The

results are all positive, meaning that civil conflict, in our sample with our estimations, increases

the ratio by over .1 percent per year through the initial year of the conflict until four years after.

The cumulative impact is just over 0.81 percent. This is, at best, a modest increase in the ratio.

20

% C.I.95First Difference

Incident Lagt−5t−4t−3t−2t−1t

Ratio

.25

.2

.15

.1

.05

0

Figure 4: Lagged Impact of Interstate Conflict

Figure 4 contains simulated estimates of the first differences of the interstate conflict

variable and its lags. As we found in previous models, there appears to be no impact of

interstate conflict on the female to male life expectancy ratio. While the first differences are all

slightly below 0, none of the effects are statistically significant. This provides even more

evidence that an incidence of interstate conflict does not affect women’s life expectancy more

than men’s.

The only control variable that independent affects the life expectancy ratio is the log of GDP

per capita. Based on the results of model 1, we simulated the effect of an increase in the log of

GDP per capita on the female male life expectancy ratio. If we increase the log of GDP per capita

21

% C.I.95First Difference

Incident Lagt−5t−4t−3t−2t−1t

Ratio

.2

.1

0

−.1

−.2

from one standard deviation below its mean to one above, the life expectancy ratio decreases

by 0.799 percent.

To test the robustness of our findings, we re-estimated our equations with two different

methods. First, we employed OLS models with Panel-Corrected Standard Errors and an AR(1)

correction (Beck and Katz 1995). Second, we estimated fixed-effects regression models with an

AR(1) disturbance. The results of these models are found in table 2. The results are not

significantly different from those presented previously.

22

23

Countries154153153152152152Variableb,(p.c.s.e.)b,(p.c.s.e.)b,(p.c.s.e.)b,(f.e.)b,(f.e.)b,(f.e.)

IndependentP.C.Std.E.P.C.Std.E.P.C.Std.E.FixedEffectsFixedEffectsFixedEffects

Model4Model5Model6Model7Model8Model9

Table2:ParameterEstimatesofRobustnessChecks

Discussion of Results and Conclusion

The changing nature of conflict in recent years has altered our understanding of its costs.

Increasingly, we observe how the costs of conflict are not limited simply to the battlefield, and

touch every part of society. These changes have spurred a number of studies that have

attempted to assess the true consequences of modern conflict. One area of research asks the

questions–do the effects of conflict impact women and men equally? One important work in

this area, Plümper and Neumayer (2006), finds that the costs of intrastate conflict fell

disproportionately on women, but results by others including Iqbal and Zorn (2010) cast doubt

on these findings. Empirical studies of this nature are an important testing ground for the

growing body of positivist gender/IR scholarship (Reiter 2014).

In this article, we examine a variety of assumptions concerning gender and conflict. Building

on previous work by (Carpenter 2003, 2006a,b), we assert that the risks facing men, especially

civilian men, are an essential part of the conflict story. We argue that the indirect costs of

conflict, such as the destruction of key infrastructure, the damaging economic problems, and

even the collapse of the state itself, are just as likely to affect men as women. In addition, the

changing nature of conflict that sees greater numbers of women on the front lines of conflict

undermines our classic understanding of the gendered nature of conflict (Sjoberg and Gentry

2007).

Empirically, our results find no support for the contention that women’s life expectancy is

disproportionately undermined by conflict. In fact, our analysis suggests the exact opposite–

men’s life expectancy is disproportionately undermined by conflict in comparison with

women’s. These contradictory findings open the door for future research about the long-term

impacts of civil conflict on health, and whether or not women continue to suffer from the

consequences for years after the conflict ends.

24

In addition, these findings also raise questions about whether or not greater variability exists

within individual conflict countries that could be examined in future work. Are there gendered

effects of conflict depending on the intensity of conflict in a given region? Scholars in economics

have begun engaging in this type of research. For example, Minoiu and Shemyakina (2014) finds

regional differences in the health effects on children in Côte d’Ivoire. Work by Thomas and

Wood (2017) also shows that the ideological underpinnings of rebellion affect the roles that

women play in conflict, which in turn should affect the consequences of the fighting. In future

research, we plan to move away from the large N, cross national time-series approach to

studying this topic in order to uncover the variation we believe that exists at lower levels of

aggregation.

We believe our findings have important implications not only for the research, but also the

policy community. The belief that women are disproportionately impacted by conflict is one

that many scholars take for granted. Our work questions this assumption. Clearly, more work

needs to be done on this topic to establish better the gendered costs of conflict. Nonetheless,

our research suggests that we need to be careful about our conclusions concerning the costs of

conflict.

In terms of policy, the implications of our research raise doubts about the wisdom of

focusing too much on the impacts of conflict on women and children. If the risks posed to

civilian men are ignored in favor of only protecting women and children, a key segment of the

population may be put at a greater risk. The point is not to minimize the costs of war on any

segment of the population. Everyone agrees that the costs of war are horrible for all who suffer

them. Yet, given limited resources, states, NGOs, and other actors are forced to make decisions

on where to focus their limited resources. Our analysis suggests that men may suffer from the

pains of war at a similar, or even a potentially greater level, than women.

25

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