The Long-term Effects of Genocide on Antisocial

Preferences

Lata Gangadharan

Asadul Islam

Chandarany Ouch

Liang Choon Wang

October 2018

Abstract

We conduct a field experiment to examine the long-term effects of exposure to the Cambodian

genocide (1975–1979), during childhood and adolescence, on individuals’ antisocial behaviors.

Our research strategy uses plausibly exogenous variations in the intensity of genocide across

regions and individuals’ direct or indirect exposure to violence. The results indicate that as the

intensity of exposure to the genocide increases, individuals directly exposed to violence during

childhood and adolescence become significantly more antisocial and less altruistic in the long

term.

Keywords: Civil Conflict, Khmer Rouge, Intensity of Exposure, Social Preferences, Field

Experiment

JEL Codes: C91, C93, D74, O12

We thank Richard Akresh, Damien de Walque, participants at the Australasian Development Economics

workshops and the ESA World meetings and seminar audiences at Monash University and Cambodian

Development Research Institute for their helpful comments. Ethics (IRB) clearance for the project was obtained

from Monash University. We are grateful for generous funding support from the Australian Research Council,

AusAID (DFAT) and Monash University. The usual disclaimer applies.

Affiliations: Department of Economics, Monash Business School, Monash University, Australia (Gangadharan,

Islam and Wang); Cambodia Development Research Institute, Cambodia (Ouch).

Email addresses: lata.gangadharan@monash.edu; asadul.islam@monash.edu; chandarany.ouch@gmail.com;

liang.c.wang@monash.edu.

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1 Introduction

There is a growing body of literature documenting the social costs of civil conflicts, particularly

their impacts on prosocial and risk preferences of adults shortly after the end of the conflict.

However, less attention has been paid to the impacts of conflict on antisocial behavior.1

Antisocial behaviors, such as violating social rules, being deceitful, thieving and being reckless,

reflect explicit decisions to harm others, sometimes even when such actions create no obvious

private or societal gain. Being antisocial is therefore a distinct step away from being less

prosocial as these undeniably harmful decisions can impact the moral fiber of society, leading

to inefficiencies in social and economic exchange (Basurto et al., 2016).

Early childhood conditions have been shown to significantly affect health and economic

outcomes later in life (see, for example, Heckman et al., 2012 for a review).While the papers in

this literature have provided very useful insights, these studies do not examine whether early

childhood experiences shape social preferences during adulthood. This paper investigates the

long-term impacts of exposure to the Cambodian genocide during childhood and early

adolescence on antisocial behaviors in adulthood. Under the Khmer Rouge (KR) regime (1975–

1979), Cambodia experienced one of the worst genocide events in human history, resulting in

the deaths of about 1.7 million people (about 21% of the country’s population) and leaving

millions more traumatized. We use experimental methods in the field to assess the impact of

direct and intense exposure to civil conflict during childhood and early adolescence on

individuals’ antisocial behaviors about four decades after the genocide. We also assess the

effects of this exposure on prosocial and risk preferences since individuals may simultaneously

exhibit antisocial and prosocial traits (Basurto et al., 2016).2

The Cambodian genocide provides a unique setting to examine the impacts of direct and

intense exposure to civil conflict, during childhood and early adolescence, on antisocial

behaviors in adulthood for a number of reasons. First, death toll data collected by the

1 Blattman and Annan (2010) and Cecchi, Leuveld, and Voors (2016) provided survey-based evidence of

antagonism among those exposed to severe war violence. Blattman and Annan (2010) find that child soldiers in

Uganda display more hostile attitudes. Cecchi et al. (2016) find that among young street football players in Sierra

Leone, those that have had more intense exposure to violence were more likely to receive a yellow or red foul

card. 2 Some studies show that individuals more affected by violent conflicts tend to exhibit prosocial behaviors, such

as trust, altruism (Gilligan et al., 2014; Gneezy & Fessler, 2012; Voors et al., 2012; Whitt & Wilson, 2007) and

egalitarianism (Bauer et al., 2014), and are more socially and politically engaged (Bellows & Miguel, 2009;

Blattman, 2009; Gilligan et al., 2014). Cassar et al. (2013), Rohner et al. (2013) and Nunn and Wantchekon (2011),

on the other hand, highlight the negative consequences of exposure to conflict on trust, fairness and willingness to

engage in impersonal exchanges. Risk preferences among individuals affected by war or political violence have

also been examined (Callen et al., 2014; Jakiela & Ozier, 2015; Voors et al., 2012). We discuss this literature in

more detail in Section 3.

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Cambodian Genocide Program provide an independently verified measure of intensity of

exposure to the genocide. Second, given the scale and extent of the genocide, there is

considerable variation in the intensity of genocide across geographical areas, as well as in

individuals who directly witnessed violence. Third, because our research subjects were exposed

to the genocide as children, 34 to 39 years ago, our empirical strategy allows us to estimate the

long-term effects depending on individuals’ personal exposure to the genocide and the

concentration of violence in their geographic locations. In our estimation strategy, we exploit

geographical variations in intensity of exposure to the Cambodian genocide and individuals’

direct and indirect experiences of violence during this period to identify the effects of the

conflict.

The participants in our experiments consist of individuals who were both directly and

indirectly exposed to the genocide. The directly exposed individuals include people born before

or during the KR regime (1960–1979 birth cohorts) and those who reported experiencing or

witnessing violence during this period. The indirectly exposed group consists of individuals

who did not directly witness or experience this violence and includes both individuals who were

born before or during the KR regime and individuals who were born after (1979–1982 birth

cohorts).3 These participants take part in a number of behavioral games, including money-

burning (capturing financially vindictive behavior), self-reporting (dishonesty), dictator (with

taking and giving), trust, and risk games which enable us to measure their antisocial behaviors

as well as other preferences such as prosocial behaviors, and risk attitudes. To identify

individuals who were directly exposed to violence, we conduct surveys to collect data on

personal experiences relating to violence during the KR period. Further, to examine the

sensitivity of our results, we consider different birth cohorts in the directly and indirectly

exposed groups.

We find that exposure to genocide during childhood and adolescence has different long-

term effects on antisocial behaviors depending on the intensity of the genocide and whether an

individual is directly or indirectly exposed to violence. In particular, our results show that direct

exposure to violence in areas with more intensive killings led to more financially vindictive,

more opportunistic behaviors, whereas indirect exposure to violence in areas with more

intensive killings made individuals less dishonest. We find that individuals’ prosocial behaviors

3 Note, however, while these individuals did not directly witness or experience violence, they were either present

during the genocide period or experienced its aftermath. Our definition of levels of exposure builds on that

proposed by Bauer et al. (2014) for Sierra Leone. We use the Cambodian Genocide Database (CGD) on deaths of

individuals in different regions to go a step further and exploit the geographical intensity of war. In sections 4.3

and 4.4, we explain in detail our definitions of direct and indirect exposure and intensity of exposure to genocide.

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and risk attitudes are also affected by direct and intense exposure to violence and they become

less altruistic and risk-seeking.

Our main findings are robust across a variety of sensitivity checks and specifications.

In particular, we demonstrate that our results are not affected by any differences in the observed

characteristics of participants, such as age or education. Our results are also robust to alternative

assumptions about the reliability of early childhood memory, potential survivor bias, the

inclusion (or not) of post-genocide birth cohorts and the inclusion (or not) of controls for post-

genocide relocation.

This study provides unique insights into the lasting effects of conflict and violence on

social behaviors and risk. It builds on recent evidence related to the impacts of civil conflicts

on the social behaviors of affected individuals and contributes to the literature in a number of

ways. Unlike most of the prior studies in this field, our study focuses on the long-term effects

of different degrees of exposure to genocide during childhood and early adolescence on

antisocial behaviors in adulthood. Existing literature tends to focus on the impact of recent civil

conflicts and on the link between civil conflicts and prosocial behaviors and risk preferences.

A number of experimental studies show that individuals’ social preferences develop over the

course of childhood and adolescence (Eckel et al., 2011; Fehr et al., 2013; Harbaugh et al.,

2002; Sutter & Kocher, 2007; Sutter et al., 2013). Exposure to violent conflicts during this

crucial stage, during which significant behavioral development takes place and after which

behavior becomes less malleable, can have long-term repercussions.

Social psychologists have documented the impacts of exposure to violence during

childhood and adolescence on several social and behavioral outcomes, such as delinquency and

aggression (Dubow et al., 2009; Loeber, 1990; Miller et al., 1999; Slone et al., 1999). However,

there is little evidence of the impacts of conflict and exposure to violence during childhood and

early adolescence on dishonesty and financially vindictive behaviors decades later. Dishonesty

encourages corruption (Collier et al., 2003) and creates fraud and inefficiencies that are harmful

to development. Similarly, vindictive behaviors in the form of financial sabotage are costly to

the economy (Murphy, 1993). This study provides new evidence, using incentivized economic

experiments, that exposure to violence during childhood and adolescence can have lasting

impacts on the prevalence of these destructive behaviors depending on how individuals are

exposed. The antisocial actions in our experiment include, relevant yet underexplored,

situations in which individuals are willing to incur a personal cost to harm others, with no

financial benefit to themselves or to society.

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Our findings contribute to current knowledge by showing that direct and greater

exposure to genocide during childhood and early adolescence makes individuals significantly

more vindictive and opportunistic later in life. Indirect exposure, on the other hand, leads to

less dishonesty. Specifically, as the intensity of exposure increases, the difference between the

directly and the indirectly exposed tends to increase, such that individuals who are not directly

exposed are more likely to be less dishonest.

Finally, by distinguishing the degree of individual exposure (direct and indirect) from

the degree of the intensity of genocide in one’s region, we differentiate between different types

of conflict experiences of children and how these experiences impact long-term behavior. Thus,

our estimates potentially inform the differential effects between large-scale conflicts where

children are directly and continuously exposed to violence and killings and small-scale isolated

conflicts where children are indirectly exposed.

The paper proceeds in the following way. In Section 2, we provide a brief background

of the genocide in Cambodia. In Section 3, we present a conceptual framework that relates

conflict with social preferences and risk to the direct exposure and indirect exposure channels

and informs our research design and hypotheses. Section 4 discusses the research strategy.

Sections 5 and 6 report the results, and Section 7 concludes.

2 Background of the Cambodian Genocide

The KR took power in 1975 and ruled Cambodia until 1979. Between April 1975 and January

1979, Cambodia suffered a period of genocide under the KR regime, which was characterized

by massive destruction, violence, torture and death. The KR attempted to impose an extreme

form of Maoist communism, forced all citizens to participate in rural work projects, often

without adequate food, to build a new Cambodia based on an agrarian model. To achieve this

goal, the KR aimed to destroy traditional Cambodian social norms, cultures, religions,

organizations, networks and even family structures (Collier et al., 2003). The regime closed

schools, hospitals, and factories, abolished banking, finance and currency, isolated the country

from all foreign influences and barred Western medicine (UNESCO, 2011). It banned all

religions, and people seen taking part in religious rituals or services were executed. The KR

also confiscated all private property and relocated people from urban areas to collective farms

through agricultural labor.

The regime forced people to live in communal work camps under the control of the

Angka (organization) with extremely strict rules and policies and no freedom of movement.

Under the KR regime, most Cambodians had to work long hours each day with insufficient

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food, no material rewards, limited access to their spouses and children and very little free time

(Chandler, 2008). At the age of eight, most children were sent to live with other children,

supervised by two or three senior KR officials. Community and family members were

encouraged to spy and report on each other, which destroyed trust and established deep-rooted

fear (Collier et al., 2003). During its four years in power, the KR executed select groups it

believed to be enemies of the state. KR cadres carried out arbitrary executions and torture

against perceived subversive elements. The KR also targeted and killed suspected political

opponents, educated individuals, individuals from high social and professional classes and

individuals who did not share the KR vision for a new Cambodia. To avoid being targeted,

people hid their identities and tried to be as inconspicuous as possible.

According to the Cambodian Genocide Database established by Yale University,

approximately 1.7 million Cambodians were killed or died from starvation or exhaustion during

the KR regime. The intensity of the killing and death differed across regions of Cambodia

(Islam et al., 2017). Adult males were the demographic group most likely to die (de Walque,

2006). Many Cambodians who survived this period either were direct victims of the regime or

witnessed violence during the KR’s rule. They experienced threats to and the loss of loved ones

and faced prolonged parental absence.

3 Violence Exposure, Social Preferences, and Risk

In this section, we conceptualize how direct and indirect exposure to violence of different levels

of intensity may influence social behaviors of individuals by drawing on theories and evidence

from studies across different disciplines. The discussion informs the research design and

identifies outcome measures of interest.

3.1 Conceptual Framework

The effect of violence exposure on a person’s social preferences can be conceptualized by the

following simple production function approach:

𝐵 = 𝐹(𝑥, 𝑛),

where social behavior, B, is expressed as a function of the violence experience, x, the person

directly suffers or witnesses, and the environmental or indirect influence of violence, n, the

person experiences. The indirect influence of violence comes from the person’s parents, peers,

community, and other environmental factors. Social behavior, B, is viewed as multi-

dimensional and may be influenced in different ways given Basurto et al.’s (2016) findings that

antisocial and prosocial behaviors can coexist.

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We are interested in understanding how the intensity of violence, v, which varies

continuously, influences social behavior through the direct experience channel and the indirect

experience channel. By differentiating social behavior with respect to v, we obtain the following

expression:

𝑑𝐵

𝑑𝑣=

𝜕𝐵

𝜕𝑥

𝜕𝑥

𝜕𝑣+

𝜕𝐵

𝜕𝑛

𝜕𝑛

𝜕𝑣

The above expression indicates that the effect of an increase in violence intensity on social

behavior manifests through the direct exposure channel,𝜕𝐵

𝜕𝑥

𝜕𝑥

𝜕𝑣, and the indirect exposure

channel, 𝜕𝐵

𝜕𝑛

𝜕𝑛

𝜕𝑣. This framework shows that for an individual who witnesses and experiences

violence (i.e., a directly-exposed person), the total effect on social behavior due to an increase

in violence intensity consists of both the direct and indirect exposure channels, while for an

individual who does not personally witness or experience violence, the total effect on social

behavior due to an increase in violence intensity consists of the indirect exposure channel only.

3.2 Negative Impact of Violence Exposure on Social Behavior

Studies in the psychological and epidemiological literature indicate that direct exposure to

violence or stress and trauma due to fear of loss, torture or violence during childhood and

adolescence can influence individuals’ behaviors and development either by provoking

aggression and negative social behaviors or by subduing positive social behaviors. For example,

Bandura’s (1973) social learning theory suggests that, during wartime, children may learn

aggressive behaviors by observing the violence committed by others, who are often aggressive

“role models” perceived as national heroes (Kerestes, 2006). Thus, according to these theories,

as intensity of violence increases, children who directly experience violence would become

more antisocial (i.e., 𝜕𝐵

𝜕𝑥

𝜕𝑥

𝜕𝑣> 0 where B measures antisocial behavior) and less prosocial (i.e.,

𝜕𝐵

𝜕𝑥

𝜕𝑥

𝜕𝑣< 0 where B measures prosocial behavior).

Children’s social behaviors may also be indirectly affected by violence without

witnessing it or experiencing it first-hand. For example, Huesmann’s (1988) social information-

processing theory suggests that children may become more aggressive during wartime given

the abundance of stimuli perceived to be threatening, leading to aggressive behavioral responses

(Kerestes, 2006). Dubow et al. (2009) argue that the constant threat of losing loved ones or

being killed during wartime can have contemporaneous and long-term impacts on affected

children’s mental wellbeing and aggressive behaviors. Similarly, Prediger et al. (2014) show

that persistent resource scarcity increases antisocial behavior, implying that conflict-induced

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resource scarcity can also indirectly lead to antisocial behavior. Moreover, parents may also

indirectly transfer the direct negative effect of violence they face, to their children through

intergenerational transmission (Islam et al., 2017). Therefore, even though children may not

directly witness any violence, they may become more antisocial or less prosocial as a result of

these negative environmental influences. That is, 𝜕𝐵

𝜕𝑛

𝜕𝑛

𝜕𝑣> 0 when B measures antisocial

behavior and 𝜕𝐵

𝜕𝑛

𝜕𝑛

𝜕𝑣< 0 when B measures prosocial behavior.

3.3 Mixed Evidence of Violence Exposure on Social Behaviors

Using survey data from classroom assessments, Kerestes (2006) finds that children’s direct

exposure to violence in Croatia increased their aggressive behavior and decreased their

prosocial (altruistic) behavior. Using clinical case studies, McAuley and Troy (1983) report that

children affected by riots in urban areas of Northern Ireland experienced higher rates of

antisocial behavior. Farver and Frosch (1996) find that children exposed to the Los Angeles

riots of 1992 included more aggressive words and thematic content in stories than similar

children from other parts of the country who had no direct exposure to the riots. Evidence to

the contrary also exists. For example, Raboteg-Saric et al. (1994) report that after the war in

Croatia, children showed increased prosocial tendencies in classroom surveys that elicited

instances of sharing, comforting and helping each other and exhibited no change in instances

of aggressive verbal or physical behaviors. The differences in these studies findings’ could be

due to differences in the intensity of the children’s exposure to violence and whether the

exposure was direct or indirect, aspects that we focus on in our research. Specifically, it is

possible that as the intensity of violence increases, its positive effect on behavior via the indirect

exposure channel more than compensates its negative effect via the direct exposure channel.

Several studies, primarily in the economics and political science literature, have

provided interesting insights on the impact of violence and conflict exposure on prosocial

preferences. Some indicate that experiences of war and threats may lead to more cooperative,

prosocial behavior as a result of increased empathy for victims. Sympathy may also evolve

from a sense of connectedness with others. Groups with a shared fate may experience mutual

identification, which can become a source of support. Gneezy and Fessler (2012) argue that

violent intergroup conflict elicits behaviors that enhance intra-group cooperation and strengthen

the group’s chances of victory. Bauer et al. (2016) conducted a meta-analysis of nearly 20

studies from more than 40 countries to re-analyze and weigh different theoretical explanations

(economic, social and psychological mechanisms), finding a strong, persistent pattern of a

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positive legacy of war in terms of local cooperation and civic engagement. This pattern is

observed primarily among adults—and, in some circumstances, children—who were exposed

to violence.4 Individuals affected by conflict are observed to be more politically and socially

engaged (Gilligan, Pasquale, & Samii, 2014; Bateson, 2012; Blattman, 2009; Bellows &

Miguel, 2009).5 Voors et al. (2012) find that adults who were directly exposed to violence or

who lived in communities that were violently attacked during the civil war in Burundi display

more altruistic giving to members of their communities.

Cassar et al. (2013), on the other hand, show that a greater intensity of direct exposure

to violence during the civil war in Tajikistan lowers trust within communities and decreases

willingness to engage in impersonal exchange. They argue that exposure to conflicts and

violence may reduce prosocial behaviors towards out-group in inter-ethnic or inter-group

conflicts or even towards members of own communities when group allegiances are not easily

observable, a feature of the civil war in Tajikistan.

3.4 Mixed Evidence of Violence Exposure on Risk Attitudes

Numerous studies also demonstrate that exposure to conflict and violence influence risk-taking

behaviors, since risk attitudes are determined by both individual (e.g., personality, cognitive

ability, genetics and emotions) and environmental (e.g., friends, parents and learning

circumstances) factors (Kim & Lee, 2014). A number of recent studies show that adults’ risk

preferences are altered by traumatic experiences, which can trigger fear and/or anger; however,

evidence showing the direction of this impact is mixed. Callen et al. (2014) argue that fearful

recollections induce more pessimistic likelihood judgements and find evidence consistent with

this in Afghanistan. Another study finds an association between self-reported fear and less risky

decisions (Lerner & Keltner, 2001). Jakiela and Ozier (2015) show, using evidence from

hypothetical lottery choices, that experiencing Kenya’s post-election violence sharply increased

risk aversion. Sacco et al. (2003) find that after the 9/11 terrorist attack, individuals (in a

different country) who were not directly exposed to the attacks made more conservative and

4 Bauer et al. (2014) conducted experiments with children in Georgia six months after the end of the war between

Russia and Georgia over South Ossetia. They ran the same games among adults in Sierra Leone following an 11-

year civil war that ended in 2002. They find that experiencing war during childhood and early adulthood increases

people’s motivations towards equality for or cooperation towards their own groups but less cooperation with or

antagonism against members of out-groups. 5 A number of studies in other related contexts, such as post-election violence (Becchetti, Conzo, & Romeo, 2014)

and earthquake and tsunami damage (Caló-Blanco, et al., 2015; Cassar, Healy, & Von Kessler, 2011; Rao et al.,

2011), also find that survival threats tend to enhance local cooperation.

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less risky decisions. Voors et al. (2012), on the other hand, find that exposure to violence during

the civil war in Burundi increased risk-seeking behaviors.

3.5 The Impacts on Social and Risk-taking Behaviors Decades Later

Though adverse effects on antisocial behaviors as a result of exposure to the Cambodian

genocide during childhood and early adolescence are expected based on other findings in the

psychology literature discussed above, it is yet to be established whether we will observe effects

on opportunistic taking and destructive envious behaviors, whether these effects persist into

adulthood decades after initial exposure, and whether the effects differ by the intensity and type

of exposure. Given Basurto et al.’s (2016) findings that antisocial behaviors and prosocial

behaviors coexist and the mixed evidence in the literature, it is also unclear whether greater

antisocial tendency will necessarily mean lesser prosocial tendency. Furthermore, it is possible

that the effects due to the direct exposure channel and the indirect exposure channel as well as

the effects on antisocial and prosocial measures may differ in direction.

We hypothesize that both the severity and the proximity type (i.e., direct or indirect) of

exposure to the Cambodian genocide influence a person’s social and risk preferences, resulting

in significantly different revealed behaviors. We use the intensity of genocide at the district

level interacted with the direct exposure measure to estimate whether the extent of exposure

differentially affected the directly and indirectly exposed groups. This allows us to examine the

differential impact of exposure to the Cambodian genocide on measures of antisocial, prosocial

and risk-taking behaviors and constitutes a significant contribution to the literature.

In the realm of antisocial behaviors, we consider acquisitive aggression, destructive

envy and dishonesty, since the Cambodian genocide (like other similar civil conflicts) created

many opportunities to aggravate these behaviors. Envious attitudes are pervasive in all societies

and can impact decision-making (Beckman et al., 2002). In particular, destructive envious

behavior, which involves decreasing others’ outcomes even at a cost for oneself, can be harmful

to the operation of competitive markets and can impede innovation and economic development.

Similarly, dishonesty encourages corruption, which is well documented to be harmful to

development. To survive in an environment of civil conflict, such as during the KR, people

must often hide and lie about their families’ backgrounds and identities. Once an honest

reputation is lost, the incentive for honest behavior in the future is greatly weakened (Collier et

al., 2003). Thus, we conduct a dictator game with taking options, a money-burning game and a

self-reporting game to elicit behaviors of opportunistic taking, destructive envy and dishonesty.

The Cambodian genocide was primarily an inter-group conflict. The KR regime

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encouraged people to spy upon and sabotage each other, potentially eroding such prosocial

preferences as trust and altruism. The consequences of being reported to the regime were often

torture and death. Survivors, hence, frequently developed tendencies towards mistrust and

selfishness. Thus, we conduct a dictator game with giving and a trust game to examine trust

and altruism within our sample. Lastly, as both fear and anger are drivers for risk evaluations

in violent settings, and both figure prominently in the Cambodian genocide, we examine

whether different levels of exposure to genocide under the KR regime are associated with

differences in risk preferences using a risk elicitation task.

4 Research Design

4.1 Recruitment of Survey and Experimental Participants

We conducted the field experiment in several locations: Phnom Penh, Cambodia’s capital city,

and six rural districts in Cambodia’s Kampong Cham province.6 The districts were selected

from a list of districts in the Cambodian Genocide Database (CGD), which includes a district

identifier for each KR mass gravesite and the estimated number of bodies in each mass grave.7

These districts were chosen to reflect the representativeness of the CGD in terms of intensity

and exposure to genocide. We show in section 4.4 that these districts are similar to the overall

CGD districts.

We recruited participants through the survey contact lists from the local statistical

organization. To encourage participation we also posted flyers at local coffee shops and in the

market place, and also advertised on social media. We hired local research assistants who

received help from school-teachers, principals and village elders to recruit participants. This

helped in ensuring the representativeness of the sample, as they were familiar with the age and

gender distribution of their communities. In all locations, participants were required to meet the

age criterion (born between 1960 and 1982). The participants in our experiment are

representative in terms of age and gender with respect to the population in Cambodia (see Table

1 and Section 4.4 for more details).

During the recruitment process, participants were informed that they would be involved

in decision making in different contexts and that they would be paid based on their decisions.

6 Kampong Cham is one of the five largest provinces in Cambodia based on population and is 123 km from Phnom

Penh. 7 The database was developed by Yale University and has been updated by the Documentation Center of Cambodia

(DC-Cam). We use both information from the original Yale database and data on additional mass gravesites and

estimates of death numbers from the DC-Cam updates. For details on the original Yale database and the

Cambodian Genocide Program, see http://www.yale.edu/cgp/ and

http://www.d.dccam.org/Database/Index1.htm for data kept by DC-Cam.

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We invited eligible individuals to register for the experiment a week before the actual

experiment started. 659 individuals showed up on the day of the experiment. We again verified

their age, and randomly selected individuals if more than the required number of participants

(to conduct a session in a district) showed up in a particular location. Individuals who did not

participate in this experiment but showed up were given a show up fee.8 The final sample of

participants consist of 492 individuals who participated in the survey and the experiment in

February 2014.

Overall, the districts and the individual participants in the experiment are similar to the

rest of the Cambodian population of the relevant age and sex groups in terms of intensity and

exposure to genocide.

4.2 Experiment Design

Our outcome variables are drawn from incentivized experimental games. To measure antisocial

and prosocial behaviors and risk preferences, we conduct money burning, self-reporting,

dictator, trust, and risk games. The money-burning game is designed to understand participants’

inclinations to destroy, at a cost, other players’ payoffs. The self-reporting game, which uses a

simple task and requires participants to pay themselves when there is no probability of being

detected for over-payment, can be interpreted as an indicator of dishonesty. We conduct the

dictator game in two stages. The dictator game with giving is designed to measure the extent of

altruism among participants, which might indicate their concern for the well-being of others

(rather than self-interest). The dictator game with the option to give or take indicates

opportunism and selfishness. The trust game, for example, elicits the degree to which

participants can trust one another and the extent of their trustworthiness. The risk task measures

risk-taking behaviors.

These games have been used extensively in the extant literature in this field. We briefly

describe the games below. We also detail the design and procedure used in each game in

Appendix A and present the instructions seen by the participants in Appendix B. To capture

envious and financially vindictive behaviors, we use a simpler two-player version of the money-

burning game developed by Zizzo and Oswald (2001). Participants simultaneously decide how

much, if any, of the other player’s total endowment to eliminate. Participants must pay from

their own endowment to eliminate the other player’s endowment. The fee incurred for

8 The final sample of individuals who participated in each session varied slightly across locations, depending on

the geographic location of the community and number of rooms available to run a session in a school. This

difference is, however, not correlated with exposure to genocide (mortality rate at the district level).

12

eliminating the other’s endowment is charged at three levels: 5, 10 and 20% of the amount of

the other player’s endowment a player wants to eliminate.

Attitudes towards dishonesty are measured using a variant of the self-reporting matrix

task (Mazar et al., 2008). We design a simple task with pictures instead of numerical or word

tasks to accommodate Cambodia’s low literacy level. The task involves finding the picture of

a star on a sheet with 10 tables, each of which has 9 images (see Appendix B). Each participant

is given an envelope containing a sheet of 10 tables and is instructed to find the stars within one

minute and pay themselves accordingly. To ensure that there are considerable and different

opportunities for cheating, not all of the 10 tables have a star. We design two different sheets:

a sheet with 7 stars in the 10 tables and a sheet with only 4 stars in the 10 tables. These maximum

numbers are not known to the participants. The maximum number of either 4 or 7 stars per

sheet allows considerable scope for cheating, even for top performers.

In the dictator game, there are two stages: 1) giving and 2) giving or taking (List, 2007).

Each participant plays as both player 1 (dictator) and player 2 (recipient). All participants

receive an initial endowment. The dictator receives an additional endowment, while the

recipient does not. In the dictator game with giving, the dictator can transfer any positive

amount x of the additional endowment to the anonymous recipient. The recipient must simply

accept it and is only informed of how much the dictator sends if the game is selected for the

final payment. In the dictator game with giving or taking, the dictator can send the additional

endowment to other players or take other players’ initial endowments. This means that the

dictator can send either a negative amount or a positive amount. As in stage 1, the recipient is

only told the amount the dictator sends or takes if the game is selected for final payment.

We use the trust game (introduced by Berg et al., 1995) protocol in which each

participant plays as both player 1 (sender) and player 2 (receiver) and is matched with different

participants in each role. In the first stage, all participants are senders and can send any positive

amount x of the total endowment to an anonymous receiver, knowing that the experimenter

triples the amount sent, such that the receiver receives an amount of 3x. In the second stage, all

participants play as receivers. To reduce logistical issues in the field, each receiver decides on

an amount y of 3x to return to the sender for all the corresponding amounts the receiver might

receive. The sender is only informed of the amount sent back by the receiver if the game is

selected for final payment.

To elicit risk preferences, we use a risk task with a 50% chance of winning or losing

(Gneezy & Potters, 1997). Each participant receives an endowment and can invest any positive

13

amount in a risky business. The investment yields triple the amount invested with 50%

probability and nothing with 50% probability. The outcome is decided by tossing a coin.

After completing all of the experimental games, participants are requested to complete

a survey questionnaire. The survey covers information about participants’ personal

characteristics and experiences during the KR period. 9 Participants with limited reading and

writing abilities are interviewed.

They were matched anonymously with another participant for payment purposes. We

set different endowments and participation fees for Phnom Penh and for the rural areas in

Kampong Cham province. In Phnom Penh, the endowment and participation fees are set to

twice those of the rural areas, since the average earnings of workers in Phnom Penh (based on

CSES, 2011) are approximately twice those of workers in rural areas.

4.3 Measures of Genocide Exposure

We use a number of measures of genocide exposure. First, we ask participants born between

1960 and 1979 two questions in the survey: “Did you ever see or experience physical torture

during the KR regime?” and “Did you ever see someone killed during the KR regime?” If the

response to either of these two questions is ‘yes’, we classify an individual as having been

directly exposed to the Cambodian genocide. Roughly 55% of those who were born before or

during the KR regime (born between 1960 and 1979), or 40% of the overall sample, responded

positively to this question. Note that individuals who were not directly exposed to the genocide

were, by construction, indirectly exposed to it, since they were either present during the

genocide period or experienced the genocide’s aftermath. These individuals include those born

after the KR regime ended and those who responded ‘no’ to the question above.

Second, the Cambodian Genocide Database (CGD) provides information about the

intensity of the Cambodian genocide in various areas of Cambodia, which allows us to construct

a district-level measure of the intensity of genocide exposure. The construction of this measure

is detailed in Appendix C. Briefly, to construct district-level KR mortality rates, we divide the

estimated deaths under the KR in a given district (based on information from the CGD) by the

sum of the total estimated deaths under the KR, the number of living individuals (based on

Census 1998 data) residing in each district at the beginning of the KR regime (1975) and the

number of living individuals (based on Census 1998 data) born in each district during the KR

9 We also collect attitudinal questions and personality measures. These measures do not vary systematically with

the intensity of genocide exposure for either the directly exposed group or the indirectly exposed group. Our main

results from the experimental games are robust to using these measures as control variables.

14

period.10 The geographical distribution of KR mortality rates (shaded blue) is illustrated in

Figure 1. According to the information available in the CGD, KR mortality rates in the 145

districts fall between 0 and 0.857. For districts in five provinces (Kaoh Kong, Preah Vihear,

Otdar Mean Chey, Krong Kaeb and Krong Pailin; shaded white in Figure 1), no information is

available in the CGD.11

[Figure 1]

Since we ask participants whether they have lived in the same district since birth and, if

not, in which district they resided during the KR regime, we are able to link the direct exposure

measure with the intensity of exposure measure, as well as to construct an intensity of indirect

exposure measure. Thus, among those individuals who were exposed directly to violence, we

can estimate the impact using the intensity of the direct exposure. Among those individuals

who were not exposed directly to violence, the intensity of exposure measure enables us to

estimate the impact of the extent to which they were indirectly exposed to the genocide (e.g.,

through family members, neighbors and so on).

4.4 Exogenous Variations in Violence Exposure

Table 1, Panel A, reports summary statistics of participants’ demographic characteristics and t-

tests of the means between those who were directly exposed and those who were not. The right

hand side of Panel A of Table1 shows the representativeness of the sample by comparing the

demographic characteristics of the experiment sample to data from the 2011 Cambodia Socio-

economic Survey (CSES 2011). The characteristics of respondents of the two samples are

similar, as indicated by column 8 in Panel A.

[Table 1]

The mortality rate in an individual’s district of residence during the KR regime is, on

average, 22.1% for a directly exposed individual and 21.5% for an indirectly exposed individual

(p = 0.63). This result means that a person’s type of exposure (i.e., direct or indirect) to a high

level of violence is plausibly exogenous. The average ages of the directly exposed group and

the indirectly exposed group are approximately 48 and 39, respectively (p = 0.000). This

10 Since we do not have information on the number of individuals who survived the KR regime but died between

1980 and 1998 at the district level, the estimated KR mortality rates are noisy. Note that we are able to identify

districts of residence both in 1975 and at birth because Census 1998 contains information regarding birth district,

years of residence in current district and previous district of residence. Islam et al. (2017) show that alternative

ways of constructing mortality rates do not differently affect the estimated impact of KR mortality rates on

education, earnings, fertility and health measures. 11 Only three participants in our sample were in these provinces during the KR regime. We assume that the intensity

of genocide they faced during the KR regime was zero. The results are not sensitive to dropping these participants

from the sample or using the genocide intensities of the districts in which they currently live.

15

difference in age is because indirectly exposed group includes individuals who were born

before, during, or after the KR regime. On the other hand, the directly exposed group were born

before the KR regime and older individuals are more likely to directly experience and

remember violence due to being exposed to the KR regime for a longer period of time and

having more mature memories at the time of exposure.12 Individuals in the directly exposed

group are more likely to be male (55.6%) than indirectly exposed group (39.5%) (p = 0.0004).

This difference is reasonable as males were more likely to be targeted by the KR regime and

hence directly exposed to violence given past findings by de Walque (2006), Islam et al. (2017)

and Neupert and Prum (2005), who show that males were the demographic group most likely

to die under the KR regime. Note that among those who were born between 1960 and 1979 and

were alive during the KR regime, the proportion in our sample is 48.7% and similar to the

distribution in the population (47%). The average years of schooling of the directly exposed

group and the indirectly exposed group are six and eight years, respectively (p = 0.000). This

is again consistent with Islam et al.’s (2016) finding that education and age are positively

correlated because the civil conflict and genocide in Cambodia disrupted schooling.

In our regression analysis, we control for these differences and examine the robustness

of our results to excluding age and education as control variables. The percentage of married

participants is approximately 87% in the directly exposed group and 82% in the indirectly

exposed group (p = 0.144). The majority of participants in the experiment are from the Khmer

ethnic group (99% in the directly exposed group and 99.7% in the indirectly exposed group, p

= 0.342). Only a small number of Cambodian Muslims participate in the experiment.

Overall, Panel A of Table 1 suggests that the demographic and educational

characteristics of our sampled individuals are similar to those of the national representative

sample. More importantly, given that our analysis exploits the intensity of genocide measure,

the directly exposed group and the indirectly exposed group do not differ in their intensities of

genocide exposure, as shown in row 1 (KR mortality rate).

[Table 2]

Table 2 demonstrates that the variation in the intensity of the genocide across districts

is exogenous by showing that district-level KR mortality rates are uncorrelated with a range of

proxies for pre-KR social and economic conditions. In particular, Census 1962 and the

geographical information system data allow us to construct the following proxies for pre-KR

social and economic conditions: the (1) pre-KR sex ratio, (2) pre-KR population density and

12 The number of retained memories of an event increases with an individual’s age at the time of the event, and

mature memories begin forming around the age of seven (Howe, 2013).

16

(3) geographical distance of a district to an urban center.13 The estimates in panel A are based

on the full sample of districts for which the CGD provides mortality figures. The estimates in

panel B are based on the sample of districts in which the participants in this study resided during

the KR period. Both panels show that the 1962 sex ratios are unrelated to the KR mortality rates

at the district level (column 1). The KR mortality rates are also not correlated with various

measures of 1962 population density (columns 2 through 4). Similarly, district mortality rates

under the KR are not correlated with distance from the provincial capital (column 5). Panel C

shows that the variables used to test for exogeneity in panels A and B are indeed correlates of

the current economic, educational and health outcomes of older adults who were excluded from

our sample selection criteria. Thus, taken together, the evidence from panels A, B and C

suggests that geographical variations in KR mortality are exogenous.

5 Results

5.1 Descriptive Analysis

In this section, we first present the average behaviors observed in the experimental games of

the directly exposed groups and the indirectly exposed group and then separate these groups

according to the degree of intensity of the genocide during the KR regime.

In Panel B of Table 1, we report the mean outcomes and the p-values of the differences

in these outcomes between the directly exposed and indirectly exposed groups. In appendix

Figure A1, we also graphically depict the difference in outcomes. Overall, we find that the

directly exposed group exhibits greater preferences for dishonesty than the indirectly exposed

group, and lower trust, trustworthiness and altruism. We describe these results in more detail

in appendix D.

Intensity of violence exposure is a continuous variable. For simplicity, we classify

intensity of violence exposure into three categories based on the distribution of KR death rates

within our sample. The first is the low intensity category, in which KR mortality rates fall

between the 0th and 33rd percentile. The second is the medium intensity category, in which KR

mortality rates fall between the 33rd and the 67th percentile. The third is the high intensity

category areas, in which KR mortality rates are in the 67th percentile or above. This

categorization allows us to clearly demonstrate the impact of the intensity of exposure to

13 The General Population Census 1962 provides data on commune-level population by gender. First, we match

the commune codes in Census 1962 with the district codes in Census 1998. Next, we match the commune-level

population with the district-level population based on the district codes in Census 1998. To merge Census 1962

with the CGD, we replace the sex ratios and population densities for district codes not available in Census 1962

with neighboring districts’ sex ratios and population densities.

17

violence before delving into the richer and more continuous variation in the intensity measure

in a regression framework.

We construct nine outcome variables from the experimental games described above.

The first is a variable for vindictive behavior, measured by a dummy variable that takes the

value of 1 if a person burns other players’ money for at least one of the three prices of burning

(5, 10 or 20%) in the money-burning game. The second is a binary variable measuring

dishonesty, which takes the value of 1 if a participant takes more money than that to which he

or she is entitled. The third is a variable for opportunistic taking, which takes the value of 1 if

an individual takes some or all of the other player’s endowment in the dictator game. The fourth

is a variable for altruism, measured by the percentage given to other players in the dictator

game. The fifth is a variable for trust, measured by the percentage sent to other players in the

trust game. The sixth is a variable for trustworthiness, measured by the percentage returned

from other players in the trust game. The seventh is a variable for risk preferences, captured by

the percentage of endowment a person invests in the risk game.

We also construct a simple index for antisocial and prosocial behavior using the

approach outlined by Gneezy, Leibbrandt and List (2016). The index for antisocial behavior

correspondingly comprises the behaviors in the dictator game with opportunities for giving or

taking, the money-burning game and the dishonesty games, as follows:

𝐼𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 𝑎𝑛𝑡𝑖𝑠𝑜𝑐𝑖𝑎𝑙 𝑏𝑒ℎ𝑎𝑣𝑖𝑜𝑟 𝑖𝑛𝑑𝑒𝑥

= [1

3(

𝑎𝑚𝑜𝑢𝑛𝑡 𝑡𝑜𝑜𝑘 𝑖𝑛 𝑑𝑖𝑐𝑡𝑎𝑡𝑜𝑟 𝑔𝑎𝑚𝑒 𝑔𝑖𝑣𝑖𝑛𝑔/𝑡𝑎𝑘𝑖𝑛𝑔

𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑛𝑒 𝑐𝑜𝑢𝑙𝑑 𝑡𝑎𝑘𝑒)

+ 1

3(

𝑡𝑜𝑡𝑎𝑙 𝑎𝑚𝑜𝑢𝑛𝑡𝑠 𝑏𝑢𝑟𝑛𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑡ℎ𝑟𝑒𝑒 𝑝𝑟𝑖𝑐𝑒𝑠 𝑖𝑛 𝑚𝑜𝑛𝑒𝑦 𝑏𝑢𝑟𝑛𝑖𝑛𝑔 𝑔𝑎𝑚𝑒

𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑛𝑒 𝑐𝑜𝑢𝑙𝑑 𝑏𝑢𝑟𝑛)

+1

3(

𝑎𝑚𝑜𝑢𝑛𝑡 𝑡𝑜𝑜𝑘 𝑖𝑛 𝑠𝑒𝑙𝑓 − 𝑟𝑒𝑝𝑜𝑟𝑡𝑖𝑛𝑔 𝑔𝑎𝑚𝑒

𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑛𝑒 𝑐𝑜𝑢𝑙𝑑 𝑡𝑎𝑘𝑒)] × 100

The index for prosocial behavior is composed of participants’ behaviors in three

experiments (amount sent in the trust game, total amount returned in the trust game for all

possible levels of trust and amount sent in the dictator game with giving), as follows:

18

𝐼𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 𝑝𝑟𝑜𝑠𝑜𝑐𝑖𝑎𝑙 𝑏𝑒ℎ𝑎𝑣𝑖𝑜𝑟 𝑖𝑛𝑑𝑒𝑥

= [1

3(

𝑎𝑚𝑜𝑢𝑛𝑡 𝑠𝑒𝑛𝑡 𝑖𝑛 𝑡𝑟𝑢𝑠𝑡 𝑔𝑎𝑚𝑒

𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑛𝑒 𝑐𝑜𝑢𝑙𝑑 𝑠𝑒𝑛𝑑)

+ 1

3(

𝑎𝑙𝑙 𝑝𝑜𝑠𝑠𝑖𝑏𝑙𝑒 𝑎𝑚𝑜𝑢𝑛𝑡 𝑟𝑒𝑡𝑢𝑟𝑛𝑒𝑑 𝑖𝑛 𝑡𝑟𝑢𝑠𝑡 𝑔𝑎𝑚𝑒

𝑡𝑜𝑡𝑎𝑙 𝑝𝑜𝑠𝑠𝑖𝑏𝑙𝑒 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑛𝑒 𝑐𝑜𝑢𝑙𝑑 𝑟𝑒𝑐𝑒𝑖𝑣𝑒)

+1

3(

𝑎𝑚𝑜𝑢𝑛𝑡 𝑠𝑒𝑛𝑡 𝑖𝑛 𝑑𝑖𝑐𝑡𝑎𝑡𝑜𝑟 𝑔𝑎𝑚𝑒 𝑔𝑖𝑣𝑖𝑛𝑔

𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑛𝑒 𝑐𝑜𝑢𝑙𝑑 𝑠𝑒𝑛𝑑)] × 100

Figure 2: Means of behavioral outcomes of directly exposed and indirectly exposed

groups according to degree of exposure to violence during the KR regime

Figure 2 shows that the directly exposed group tends to exhibit lower antisocial and

prosocial preferences and risk attitudes than the indirectly exposed group at low levels of

violence exposure. As the intensity of violence exposure increases, the directly exposed group

engages in more taking, more money-burning, and more risk-seeking. By contrast, the

behaviors of the indirectly exposed groups generally does not vary much with the extent of

violence exposure, with the exception of the behavior of dishonesty, which decreases with the

intensity of violence experienced by the participants’ communities and then levels off.

40

50

60

70

% B

urn

ers

Low Medium HighIntensity of KR mortality

Money Burning Game1

02

03

04

05

0

% C

hea

ters

Low Medium HighIntensity of KR mortality

Self-Reporting Game

20

30

40

50

% T

akers

Low Medium HighIntensity of KR mortality

Dictator Game: Give or Take

10

20

30

40

Ave.

%G

ive

n

Low Medium HighIntensity of KR mortality

Dictator Game: % Given

10

20

30

40

Ave.

%S

en

t

Low Medium HighIntensity of KR mortality

Trust Game: % Sent

10

20

30

40

Ave.

%R

etu

rne

d

Low Medium HighIntensity of KR mortality

Trust Game: % Returned

40

50

60

70

Ave.

% I

nveste

d

Low Medium HighIntensity of KR mortality

Risk Game: % Invested

10

12

14

16

Ave.

Inde

x

Low Medium HighIntensity of KR mortality

Anti-social Pref. Index

18

24

30

36

Ave.

Inde

x

Low Medium HighIntensity of KR mortality

Pro-social Pref. Index

Indirectly Exposed Directly Exposed

19

5.2 Regression Specification

We are particularly interested in examining the differential effects of direct and indirect

exposure to violence of different intensity levels. We exploit the exogenous variation in the

intensity of genocide across different geographic locations. Furthermore, individuals within a

given region have either direct or indirect experiences of the conflict. Hence, we use

interactions of these two variables as a source of identification. Such an interaction term gives

us individual-specific variation in exposure (directly or indirectly) as well as intensity of

exposure that map to the framework discussed in section 3. Thus, we rely on an interaction term

of (i) intensity of exposure; and (ii) whether an individual was directly exposed to the

violence.14 In Section 4.3 and Section 4.4, we have already shown that the intensity of exposure

term is plausibly exogenous and that the intensity is similar across the directly and indirectly

exposed groups. Below we examine the effects of genocide exposure, using a regression

framework to control for covariates that could potentially correlate with outcomes:

𝑌𝑖𝑘𝑗 = 𝛽0 + 𝛽1𝐾𝑅𝑘 + 𝛽2𝐸𝑥𝑝𝑖𝑘𝑗 + 𝛽3𝐸𝑥𝑝𝑖𝑘𝑗 ∗ 𝐾𝑅𝑘 + 𝛿′𝑿𝑖𝑘𝑗 + 휀𝑖𝑘𝑗 (1)

where 𝑌𝑖𝑘𝑗 includes the experimental behavioral outcomes for individual i who resided in

district k during the KR regime and participates in the experiment in district j. The dummy

variable 𝐸𝑥𝑝𝑖𝑘𝑗 takes the value of 1 if individual i was directly exposed to genocide and the

value of 0 if individual i was indirectly exposed. A set of control variables 𝑿𝑖𝑘𝑗 includes age,

gender and education for individual i, as well as an indicator for whether the experiment took

place in Phnom Penh (dummy for urban). 휀𝑖𝑘𝑗 is the error term. Standard errors are clustered at

the level of the district of residence at the time of the KR regime. As we mentioned before,

individuals who were directly exposed to the genocide are somewhat older, less educated and

more likely to be male than those who were not directly exposed to the genocide. Thus,

controlling for these variables takes these differences into account. We have also addresses

identification using a strategy that relies solely on age and cohort differences. The results can

be interpreted as the average differences in social and risk behavior between those who were

directly affected vs. not directly affected. We omitted the results in this version of the paper for

14 Our empirical strategy is similar to Akresh, Lucchetti and Thirumurthy (2012), who use intensity of exposure

and whether someone was exposed or not-exposed (or duration of exposure) to violence to identify the effects on

health outcomes.

20

brevity. While the magnitudes of the coefficients are not comparable the results are qualitatively

similar to what we report in the paper.15

Let us now examine the interpretation of the regression coefficients. (𝛽1 + 𝛽3)

corresponds to the total effect of violence exposure on the behavior of directly-exposed group

as the intensity of violence increases (as discussed in section 3.1). 𝛽1 captures the indirect

(environmental) effect of violence exposure (𝜕𝐵

𝜕𝑛

𝜕𝑛

𝜕𝑣) while 𝛽3 captures the direct effect of

violence exposure (𝜕𝐵

𝜕𝑥

𝜕𝑥

𝜕𝑣). The sum of these two effects measures how a directly-exposed

individual’s antisocial behavior, prosocial behavior, or risk-taking behavior varies with the

intensity of genocide exposure. For an indirectly-exposed individual, 𝛽1 measures the total

effect of violence exposure on behavior as the intensity of violence increases. Since indirectly-

exposed individuals did not personally witness or suffer any violence, the total effect of

violence exposure for them measures how their antisocial behaviors, prosocial behaviors, and

risk attitudes respond to environmental influences as intensity of violence exposure increases.

The coefficient 𝛽3 is also of interest, as this measures how the behaviors of directly-exposed

individuals vary relative to those of indirectly-exposed individuals as the intensity of

experienced violence increases. This informs us about the counterfactual behaviors of indirectly

exposed individuals, had they been directly exposed to the genocide within their localities.

We further assess the credibility of our identification strategy in the following ways:

First, we allow the effects of indirect exposure to differ for those born before the end of the KR

regime and those born after the end of the regime. If the behaviors of these two groups of

individuals are similar, then we have evidence that both are robust control groups to the directly

exposed and that our results are unlikely to be biased by any self-reporting error in the

measurement of direct exposure (by those born before the end of the KR regime). Second, the

direct exposure measure can be sensitive to adult memories of early childhood. To explore the

robustness of the main results, we assume memories of direct violence exposure below certain

ages to be unreliable and code these cases as indirect exposure. Third, since individuals who

relocated after the KR regime provide us with additional variation in the intensity of the

violence exposure, we include in our regressions a control variable indicating whether an

individual has been living in the same district or location since birth. Robustness in the

estimates provides evidence that the estimated behavioral differences by direct exposure and

exposure intensity are not sensitive to displacement during or after the KR regime. Fourth, we

15 These results are available upon request.

21

exclude education as a control variable to examine whether genocide exposure may influence

outcomes through education. Finally, we add risk attitudes as an additional control variable

when examining the impact on social preferences because risk preferences may be correlated

with social preferences, including, particularly, measures of dishonesty and trust. We report

these measures to examine robustness in the section on sensitivity analysis.

5.3 Regression Results

We estimate equation (1) using a Probit estimation approach for antisocial behavior and an

Ordinary Least Squares (OLS) regression for prosocial behavior and risk and present the results

in Table 3. Columns 1 and 2 report the marginal effects on the likelihood of burning other

players’ money (evaluated at the means). Columns 3 and 4 present the marginal effects on

dishonesty (evaluated at the means). Column 5 reports the marginal effects on taking behavior

in dictator game (evaluated at the means). Column 6 reports the effects on altruism. Column 7

reports the effects on an individual’s trust. Column 8 reports the effects on an individual’s

trustworthiness. Column 9 reports the effects on a person’s risk-taking attitude. Column 10

reports the effects on the antisocial behavior index. Column 11 reports the effects on the index

of prosocial behavior.

[Table 3]

Of particular interests are- (i) the coefficient for KR mortality rates, which measures

how the behaviors of indirectly exposed individuals vary with the intensity of genocide, (ii) the

sum of the coefficients for the KR mortality rates, and (iii) the interaction between these

mortality rates and direct exposure (reported in the bottom row in bold), which measures how

the behaviors of directly exposed individuals vary with the intensity of the genocide. We find

that high levels of direct exposure to violence have a statistically significant impact on

individuals’ vindictive behaviors. Column 1 shows that as the intensity of violence exposure

increases, those directly exposed to the genocide are more likely to destroy others’ wealth. The

vindictive behaviors of those indirectly exposed to the genocide, however, do not vary

significantly with the intensity of violence in their communities.16

Columns 3 and 4 report the impact of exposure to violence on attitudes towards

dishonesty. These attitudes are invariant to the intensity of genocide exposure for individuals

16 Column 2 shows that these results are not sensitive to the inclusion of a binary indicator for whether a participant

is an advantaged player (i.e., received a gift in the money-burning game). Further, the magnitude of the estimated

coefficients is smaller when using different measures of the burning decision (e.g., burn in at least two prices of

burning and burn in all three prices of burning). The main effect remains negative and significant.

22

directly exposed to the genocide (bottom rows). However, as the intensity of genocide in the

community increases, individuals who were indirectly exposed become significantly less

dishonest than those who witnessed lower intensities of genocide. When we control for

differences in opportunities to cheat (i.e., the maximum number of possible correct answers,

either 4 or 7) in the regression, the results remain similar. These findings suggest that

individuals who were not directly affected by violence but witnessed intense chaos and the

aftermath of the conflict might appreciate their relative good fortune and perhaps develop a

stronger sense of moral integrity.

Columns 5 and 6 of Table 3 indicate that directly exposed individuals are more likely

to take some or all of other players’ endowments and give less when exposed to a high level of

violence, respectively.17 On the other hand, those who are not directly exposed to violence

experience little variation in opportunistic and altruistic behaviors with the intensity of the

violence experienced by the community. Thus, greater direct exposure to violence makes a

person significantly more opportunistic and significantly less altruistic.

Columns 7 and 8 in Table 3 (the bottom row) show that individuals directly exposed to

the genocide exhibit less trust and less trustworthy behaviors according to the intensity of the

genocide they experienced, but not significantly so. Similarly, for individuals indirectly

exposed to the genocide, trust and trustworthy behaviors do not vary significantly with the

intensity of the genocide experienced by their communities (first row).

Next, we examine the effects of genocide exposure on risk preferences. Column 9 of

Table 3 (the bottom row) shows that as the intensity of exposure to violence increases,

individuals who were directly exposed to the genocide invest significantly more in the risky

option. In contrast, individuals who were not directly exposed to violence do not vary their risk-

taking attitudes with the intensity of violence in their communities. Thus, our results indicate

that high levels of direct exposure to violence make individuals more risk-seeking.

Columns 10 and 11 of Table 3 present the effects of genocide exposure on the indexes

for antisocial and prosocial behaviors, respectively. Column 10 shows that antisocial behaviors

vary significantly with intensity of genocide exposure for directly exposed individuals, but not

for indirectly exposed individuals. The results indicate that a high level of direct exposure to

violence during adolescence increases antisocial attitudes and behaviors in the long term.

17 An ordered probit or a multinomial logit/probit regression model in which the dependent variable takes the value

of 0 (takes some or all of the other player’s endowment), 1 (does not give to or take from the other player) or 2

(gives some or all of the endowment to the other player), provides results similar to those in column 4. These

unreported results are available upon request.

23

Column 11 shows that prosocial behaviors do not vary significantly with intensity of genocide

exposure for either directly exposed or indirectly exposed individuals, although the intensity of

genocide exposure somewhat reduces prosocial behaviors for both groups.

Overall, the results show that members of the directly exposed group are more

financially vindictive, less altruistic, likely to take more from others and risk seeking if they

were residing in areas of intensive killing during the genocide. There is also some evidence that

indirectly exposed individuals may be less dishonest if the level of violence in their

communities was higher.

6 Sensitivity Analysis

In this sensitivity analysis section, we demonstrate that our results are robust to alternate

specifications and explanations.

6.1 Split Sample by Post-Genocide Birth Cohorts

There are two types of indirectly exposed individuals in our sample: individuals born before

and during the KR period and individuals born after the KR period. It is conceivable that the

individuals who were physically present during the genocide but did not directly experience

any violence might develop prosocial and antisocial preferences and risk attitudes that differ

from those of individuals who only heard about the violence and saw the aftermath of the

genocide years later. For example, individuals who were physically present during the genocide

are likely to have faced a constant threat of losing loved ones or being killed or tortured,

whereas individuals who were born after the KR period are not. To ascertain whether these two

types of indirectly exposed individuals respond differently to the intensity of genocide

experienced by their communities, we estimate equation (1) for the sample of individuals born

before the fall of the KR regime and estimate a variant of equation (1) that omits the direct

exposure variable and the interaction between direct exposure and the KR mortality rate for the

sample of individuals born after the end of the genocide.

[Table 4]

Panel A in Table 4 shows that the estimated marginal effects of KR mortality on both

the indirectly exposed group and the directly exposed group are similar to those reported in

Table 3. Likewise, the estimated marginal effects of KR mortality on the dishonesty measure

of the group of indirectly exposed individuals who were born after the KR period are very

similar to those reported in Table 3 (Panel B, Table 4). Thus, the marginal effects of the

intensity of genocide on the tendency for indirectly exposed individuals to be dishonest are

24

negative and the effects are almost the same for groups of individuals who were born just before

or after the genocide. These results also indicate that the both types of indirectly exposed

individuals provide similar counterfactuals and serve as good control groups for the directly

exposed individuals. Moreover, because the behaviors of these two groups of indirectly

exposed individuals are similar, it is unlikely that any self-reporting error in the direct exposure

measure for those who were physically present during the KR period might bias our results.

6.2 Reliability of Memories of Early Childhood Experience

We collect information on direct violence exposure through surveys. While this approach offers

a unique and individual-specific measure of exposure to violence, the information collected

may be sensitive to the reliability of adult memories and recalls of early childhood experiences.

For example, the literature on childhood amnesia and autobiographical memory development

indicates that children can remember very few events before the age of two and only some

events that occurred between the ages of two and three (Howe, 2013). The number of retained

memories of events increases with an individual’s age at the time of the event, and mature

memories begin forming around age seven (Howe, 2013). Bauer et al. (2014) also find that

greater exposure to war has no measurable impact on children below the age of seven, but that

the effects are pronounced beginning at around seven years of age.

To examine the sensitivity of our results, we recode direct experience of violence as 0

for the various birth cohorts whose early childhood memories of exposure to violence are less

reliable and report the re-estimated results in Table 4. We do this systematically by

progressively recoding the direct exposure variable to 0 for: (A) individuals born between 1978

and 1979 (less than 1.5 years old during the KR period); (B) individuals born between 1977

and 1979 (less than 2.5 years old during the KR period); (C) individuals born between 1976

and 1979 (less than 3.5 years old during the KR period); and (D) individuals born between 1975

and 1979 (less than 4.5 years old during the KR period). Table 5 demonstrates that our main

findings are robust irrespective of how we treat the adult memories of early childhood

experience. 18 The results suggest that our main conclusion concerning direct exposure to

genocide is driven by the sample of children and adolescents who were born before the KR

regime began (i.e. born before 1975).

[Table 5]

18 Results are similar even when we expand the birth cohorts to those younger than 6.5 years old during the KR

period.

25

6.3 Robustness to Post-Genocide Relocation

The variation in the intensity of genocide comes primarily from the number of districts in which

we conducted the experiments (7 in total) and the number of individuals who resided in districts

during the KR period or at birth that differ from the districts in which they participate in the

experiments (61 additional districts). Roughly 68% of the full sample and 66% of those born

before the end of the KR regime indicate that they have lived in the same districts since the KR

period. It is possible that post-genocide relocation might have influenced individuals’ prosocial

and antisocial behaviors and risk attitudes. For example, relocation may disrupt social

networks. It is also possible that individuals who are more mobile differ from those who are not

in terms of their social preferences and risk attitudes.

We assess the sensitivity of our results to the effects of relocation by including a

relocation dummy that takes the value of one if a respondent’s district of residence during the

KR period or at birth (if they were born after the KR period) differs from the district in which

they currently live. The results reported in Table 6 are very similar to those reported in Tables

3. Thus, our results are not sensitive to post-genocide relocation or the inclusion of individuals

who moved away from their birth districts. Finally, we also show that the estimated coefficients

are similar for a sub-sample of individuals who lived in the same district throughout their lives.

The results are reported in Appendix Table A1.

[Table 6]

6.4 Exclusion of Education and Age as Controls and Potential Survivor Bias

So far, we have included participants’ completed years of schooling and ages as controls in our

regression analyses. However, education is a potential channel through which the effects of

civil conflict exposure can affect individual preferences. Many existing studies examining civil

conflicts in different countries (e.g., Akresh & de Walque, 2008; Chamarbagwala & Morán,

2011; Dabalen & Paul, 2012; Islam et al., 2016; Leon, 2012; Shemyakina, 2011) find a negative

relationship between exposure to conflict and educational attainment. Similarly, age and

educational attainment are highly correlated in the Cambodian context (Islam et al., 2016).

More importantly, as the KR targeted prime-age and relatively more educated individuals (de

Walque, 2005) and educational attainment and age correlated with a wide range of behaviors

and outcomes, the sensitivity of our estimates to the exclusion of educational attainment and

age can provide an assessment of whether the estimates are biased by the unobserved selection

of genocide survivors. Thus, we estimate equation (1) for all measures based on the

experimental games, first excluding only completed number of years of schooling from the

26

regression and then excluding both years of schooling and age. As reported in panels A and B

of Table 7, the signs, magnitudes and significance levels of the coefficients of interest are

similar to the main results in Table 3.19 Thus, there is no evidence that the documented effects

of exposure to violence operate through education, are confounded by cohort differences, or

are potentially biased by the unobserved traits of survivors.

[Table 7]

6.5 Effects of Risk Attitudes on Behaviors in Experiment

Risk attitudes are likely correlated with prosocial and antisocial behaviors. Since we find strong

effect on risk attitudes, we include risk attitudes as a control variable when estimating the

impact on social preferences. Compared to Table 3, which shows the main results, Table 8

shows little change in the magnitudes of the estimated coefficients and the significance levels,

suggesting that exposure to genocide directly affects the individual behaviors observed in the

experiments.20

[Table 8]

7 Conclusion

KR’s violent enforcement of social engineering policies with the goal of transforming

Cambodia into a classless agrarian utopia produced one of the worst genocides in human

history. We examine the long-term effects of this genocide on the social behaviors of

individuals. To our knowledge this is the first study that explicitly examines the exposure to

violent conflict and its effects on antisocial behavior.

We exploit the intensity of genocide across different geographic locations where

individuals either directly or indirectly experienced or witnessed conflict-related violence

during their childhood and early adolescence in order to identify the impact of genocide on

social preferences and risk. First, we use plausibly exogenous variations in the degree of

concentration of deaths during the KR regime across districts in Cambodia. Second, we use

individuals’ direct and indirect personal experiences of war during the important developmental

window of childhood and adolescence. We show that personal experiences with violence are

not correlated with economic conditions and geographical characteristics.

19 Using Census 1998 data, we also find that the intensity of genocide variable is uncorrelated with the educational

attainment of individuals born between 1960 and 1966 (who had surpassed their schooling age in the post-genocide

period). The results are available upon request. 20 Our main results are also not affected by controlling for behavior in the previous games the participants played.

As described in the experimental procedure in appendix A, the games were conducted in two different orders. Our

results remain robust controlling for the game order.

27

We find that individuals who directly experienced or witnessed the genocide in areas of

intensive killings 30-40 years ago are now more opportunistic, more vindictive, less altruistic,

and more risk-taking. Overall, these people exhibit more antisocial preferences. Individuals

who lived in the same area as the genocide but who did not have direct experience with it are

found to be less dishonest when given the option to cheat. The results suggest that genocide has

differential long-term effects on prosocial and antisocial preferences and risk-taking behaviors

depending on whether an individual directly witnessed or experienced extreme violence during

the genocide period. Our findings also suggest that direct and intense exposure to genocide

during childhood and early adolescence can alter individuals’ social preferences and that the

effects persist decades after the genocide ends. Our results are robust to a variety of checks,

such as, among other sensitivity measures, restricting the sample size to different cut-off ages

for exposure to genocide, differences in education levels, living in the same locality since birth

and individual personalities.

We argue that the KR forced people to adopt norms and institutions that created feelings

of fear and horror, provoked antisocial behaviors and discouraged prosocial motivations. While

the KR regime could be dismissed as a uniquely horrific historic event of little general relevance

to the world today, the extreme ideology and the general disregard for human life which were

the defining characteristics of the Cambodian genocide and which led to human catastrophe

can still be seen in several places around the world today.21 Similar extreme events, for example,

have been experienced in China during the Cultural Revolution, in Rwanda, in Yugoslavia and,

in recent years, in Syria.

While more research is needed to explore the generalizability of our findings to other

contexts, we expect our results to improve the understanding of the long-term effects of extreme

violence and how these effects can be influenced by the proximity and intensity of violence.

The specific motivations of perpetrators may be unique to each conflict; however, the

encouragement of animosity, repression and murder on a massive scale are all common

elements. In sum, the lessons of the Cambodian genocide may apply well beyond the country’s

borders and could have implications for current events and their effects on long-term behaviors

in a post-conflict society.

21Extreme state ideologies have also been found to impact individuals’ behaviors in other (non-violent) settings.

For example, Cameron et al. (2013) find that individuals who were single children due to the One Child Policy in

China exhibit different behavioral characteristics than individuals who had siblings.

28

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Figure 1: Distribution of KR mortality rates across districts in Cambodia

Note: Blue shaded areas are districts with information of mortality under the

Khmer Rouge regime available. White circles with a red marker denote districts

in which the participants in our experiment resided during the Cambodian

genocide period.

33

Table 1: Demographic characteristics of experiment participants

Experimental sample CSES 2011

Mean differences

between Experiment and

CSES 2011 samples

Main Variables All

Std.

Dev. Range

Direct

Exposure

Indirect

Exposure

p-value

of diff.

(t-test)

All p-value of diff. (t-test)

(1) (2) (3) (4) (5) (6) (7) (8)

Panel A

KR mortality rate 0.217 0.153 0-0.542 0.221 0.215 0.633

Age 42.31 7.290 32-54 47.8 38.7 0.000 41.88 0.194

Male (=1) 0.46 0.499 0-1 0.556 0.395 0.000 0.47 0.689

Education (years) 7.32 4.459 0-22 6.20 8.05 0.000 7.13 0.311

Married (=1) 0.84 0.369 0-1 0.87 0.82 0.144 0.82 0.477

Khmer (=1) 0.99 0.078 0-1 0.99 0.997 0.342

Observations 492 196 296 4601

Panel B

Burn 0.467 0.499 0-1 51.0 43.9 0.123

Dishonest 0.309 0.462 0-1 41.3 24.0 0.000

Take 0.350 0.477 0-1 33.7 35.8 0.627

% Given 24.309 25.259 0-100 21.1 26.4 0.023

% Sent 30.955 27.858 0-100 27.3 33.4 0.018

% Returned 30.908 24.782 0-100 28.1 32.8 0.000

% Invested 46.443 27.727 0-100 45.2 47.3 0.402

Observations 492 196 296

Note: Age originally reported in CSES 2011 is recoded to reflect the age in February 2014. Column (6) tests the differences of means reported

in columns (4) and (5). Column (8) tests the differences of means reported in columns (1) and (7).

34

Table 2: Exogeneity of mortality rates under the Khmer Rouge regime

Sex ratio

in 1962

Density

in 1962

Density —Men in

1962

Density — Women

in 1962

Distance to capital

district (1) (2) (3) (4) (5)

Panel A: CGD sample

Test of exogeneity of mortality rates under the Khmer Rouge regime

KR mortality rates -0.022 -814.459 -417.384 -397.075 4.054

(0.017) (663.015) (335.879) (327.192) (9.648)

R-squared 0.008 0.008 0.008 0.007 0.001

Observations 145 145 145 145 145

Panel B: Experiment sample

Test of exogeneity of mortality rates under the Khmer Rouge regime

KR mortality rates -0.005 -577.343 -290.417 -286.926 16.750

(0.022) (1172.329) (592.270) (580.062) (16.325)

R-squared 0.001 0.003 0.003 0.003 0.014

Observations 68 68 68 68 68

Panel C: CSES 2004 sample of individuals born before 1950

Correlation of test of exogeneity variables and actual outcomes

Mean years of

schooling

Mean monthly

earnings

Mean monthly

household income

Illness/injury during

the past 30 days Disabled

(1) (2) (3) (4) (5)

Dependent Variable:

Sex ratio in 1962 4.469** 5.728*** 5.834*** -0.314 -0.231

(1.760) (1.791) (0.794) (0.273) (0.287)

Density in 1962 (in 10,000) 3.521*** 1.140*** 1.794*** 0.105** -0.054*

(0.245) (0.334) (0.153) (0.049) (0.028)

Density—Men in 1962 (in 10,000) 6.925*** 2.233*** 3.527*** 0.206** -0.106*

(0.507) (0.675) (0.315) (0.097) (0.056)

Density—Women in 1962 (in 10,000) 7.160*** 2.327*** 3.649*** 0.216** -0.110*

(0.476) (0.662) (0.298) (0.098) (0.058)

Distance to capital district (in 10,000) -288.508*** -113.597** -148.448*** 3.122 2.543

(42.899) (43.645) (27.979) (6.579) (6.315)

Observations 141 125 141 141 141

Note: All observations are measured at the district level. The values for the dependent variables in columns 1–4 of panels A and B are from Census 1962. In panel B,

KR mortality rates are assumed to be zero for the three districts in which KR mortality data are not available (the results are similar if the three districts are excluded).

In panel C, each estimate came from a separate regression with one explanatory variable. Panel C shows whether the variables used for the test of exogeneity are

predictive of actual outcomes. Robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.10

35

Table 3: Estimates of effects of exposure to genocide on prosocial and antisocial behaviour and risk Money Burning Self-reporting Dictator Trust Risk Index

Dependent variable: Burn Burn Dishonest Dishonest Take % Given % Sent % Returned % Invested Antisocial

Preferences

Prosocial

Preferences

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

KR mortality rate (β1) -0.055 -0.057 -0.678*** -0.701*** -0.244 -5.373 -9.932 -5.274 8.264 -8.650 -6.531 (0.153) (0.152) (0.216) (0.215) (0.245) (7.933) (12.105) (12.265) (8.825) (6.992) (9.972)

Direct exposure (β2) -0.077 -0.079 0.060 0.055 -0.124* -0.752 -5.014 -3.050 -5.721 -2.070 -3.151

(0.073) (0.072) (0.056) (0.056) (0.074) (4.782) (4.094) (3.226) (3.448) (2.292) (3.213)

KR mortality rate × Direct exp. (β3) 0.563*** 0.571*** 0.596** 0.587** 0.585*** -20.634 0.706 4.959 23.501** 18.627*** -4.264

(0.162) (0.159) (0.259) (0.261) (0.210) (16.011) (11.202) (13.703) (9.256) (6.947) (11.937)

Age 0.006 0.006 -0.003 -0.003 -0.001 0.070 -0.013 -0.204 -0.104 -0.071 -0.045

(0.004) (0.004) (0.003) (0.003) (0.004) (0.298) (0.201) (0.181) (0.212) (0.079) (0.176)

Education (years) 0.018*** 0.017*** -0.017*** -0.018*** 0.003 0.536 0.601* 0.280 0.980** 0.041 0.496*

(0.005) (0.005) (0.006) (0.006) (0.005) (0.381) (0.324) (0.230) (0.399) (0.131) (0.272)

Male -0.037 -0.036 -0.092** -0.097** -0.121*** 9.398*** 8.376*** 3.043** 8.900*** -2.129 6.867***

(0.050) (0.051) (0.044) (0.041) (0.039) (2.272) (2.300) (1.501) (2.451) (1.898) (1.389)

Phnom Penh -0.148* -0.147* -0.190*** -0.192*** -0.168* 18.726*** 21.808*** 13.328*** 5.883 -6.896*** 18.347***

(0.085) (0.085) (0.073) (0.072) (0.099) (4.409) (4.132) (3.329) (4.371) (2.121) (3.380)

Advantaged player -0.016

(0.043)

Maximum number of correct answers -0.122***

(0.041)

R-squared 0.140 0.132 0.059 0.088 0.039 0.180

Observations 492 492 492 492 492 492 492 4920 492 492 492

KR mortality rate +

KR mortality rate × Direct exp. (β1+ β3) 0.508*** 0.514*** -0.082 -0.114 0.341** -26.007** -9.226 -0.315 31.765*** 9.977** -10.795

(p-values) (0.000) (0.000) (0.572) (0.453) (0.011) (0.050) (0.460) (0.977) (0.000) (0.017) (0.290)

Note: Columns 1 and 2 report the marginal effects evaluated at the mean from the Probit estimation where dependent variable equals 1 if the player decides to reduce (burn) the other player’s money for at least 1 of the 3

prices of burning and 0 if player decides not to burn any amount. Columns 3 and 4 report the marginal effects evaluated at the mean from the Probit estimation where dependent variable equals 1 if the player takes extra

money to which he or she is not entitled and 0 otherwise. The advantaged player equals 1 if the player receives a gift and 0 otherwise. The maximum number of correct answers equals 1 if the total number of correct answers

in the self-reporting game is 7 and 0 if total number of correct answers is 4. Column 5 reports the marginal effects evaluated at the mean from the Probit estimation when the dependent variable equals 1 if the player decides

to take some or all of the other player’s endowment and 0 otherwise. Column 8 includes 10 observations per person as there are 10 possible values that each sender might send. Column 10 reports the index for antisocial

behaviour which comprises of the behaviour in the dictator game -giving or taking, money burning and dishonesty games. Column 11 reports the index for prosocial behaviour, which is composed of the behaviour in three experiments (amount sent in the trust game, total amount returned in the trust game for all possible levels of trust, amount sent in the dictator game - giving). Robust standard errors clustered by districts (68 districts) are

reported in parentheses. *** significant at 1%, ** significant at 5%, * significant at 10%.

36

Table 4: Splitting the Sample by Post-Genocide Birth Cohorts

Money Burning Self-reporting Dictator Trust Risk Index

Dependent variable: Burn Burn Dishonest Dishonest Take % Given % Sent % Returned % Invested Antisocial

Preferences

Prosocial

Preferences

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

Panel A: Birth cohorts: 1960-KR Period

KR mortality rate (β1) -0.100 -0.098 -0.489** -0.564*** -0.371 -1.024 -7.562 8.573 13.953 -9.208 0.618

(0.265) (0.264) (0.229) (0.217) (0.419) (9.266) (15.769) (10.004) (13.423) (10.656) (8.552)

Direct exposure (β2) -0.101 -0.105 0.110* 0.094 -0.146* 0.026 -4.527 -0.357 -5.029 -2.189 -1.744

(0.077) (0.078) (0.063) (0.062) (0.088) (4.950) (4.897) (3.308) (4.171) (2.946) (3.342)

KR mortality rate × Direct exp. (β3) 0.623** 0.632** 0.417 0.456* 0.686* -25.160* -2.083 -8.970 18.120 18.734* -11.685

(0.250) (0.254) (0.260) (0.247) (0.380) (13.044) (15.271) (12.958) (12.927) (9.954) (11.183)

Age 0.003 0.003 -0.007 -0.006 -0.002 0.120 0.069 -0.177 -0.102 -0.111 0.024

(0.006) (0.006) (0.006) (0.006) (0.003) (0.296) (0.293) (0.153) (0.276) (0.093) (0.173)

Education (years) 0.010 0.010 -0.023*** -0.024*** 0.009* 0.574* 0.554 0.195 0.954** 0.095 0.477*

(0.007) (0.007) (0.008) (0.007) (0.005) (0.300) (0.399) (0.240) (0.423) (0.165) (0.241)

Male 0.012 0.013 -0.112** -0.119*** -0.114** 9.733*** 9.505*** 4.340** 10.256*** -1.953 7.722***

(0.070) (0.071) (0.048) (0.045) (0.051) (2.589) (2.605) (1.830) (3.573) (2.404) (1.275)

Phnom Penh -0.163 -0.161 -0.280*** -0.289*** -0.135 18.832*** 20.074*** 12.592*** 7.857 -7.164*** 17.484***

(0.114) (0.113) (0.103) (0.103) (0.099) (5.946) (5.669) (4.682) (5.360) (2.069) (4.790)

Advantaged player -0.033

(0.050)

Max. no. of correct answers -0.125***

(0.045)

R-squared 0.134 0.104 0.045 0.104 0.040 0.152

Observations 358 358 358 358 358 358 358 3580 358 358 358

KR mortality rate +

KR mortality rate × Direct exp. (β1+ β3) 0.523*** 0.534*** -0.072 -0.108 0.315** -26.184* -9.645 -0.397 32.073*** 9.526** -11.067

(p-values) (0.001) (0.000) (0.572) (0.424) (0.015) (0.057) (0.450) (0.972) (0.000) (0.018) (0.304)

Panel B: Post-Genocide Birth Cohorts

KR mortality rate -0.016 -0.006 -0.706*** -0.676*** -0.146 -10.938 -12.656 -20.844 -0.024 -8.321 -14.801

(0.205) (0.208) (0.192) (0.216) (0.146) (15.167) (14.521) (17.567) (9.999) (6.676) (14.397)

R-squared 0.148 0.197 0.093 0.052 0.041 0.235

Observations 134 134 134 134 134 134 134 1340 134 134 134

Notes: See notes in Table 3 for details about the dependent variables and specifications used. Post-genocide birth cohorts are those born in 1980 and after. Robust standard errors clustered by districts (68 districts) are

reported in parentheses. *** significant at 1%, ** significant at 5%, * significant at 10%.

37

Table 5: Robustness to Potential Unreliability of Adult Memories of Childhood Experience

Money Burning Self-Reporting Dictator Trust Risk Index

Burn Dishonesty Take % Given % Sent % Returned % Invested Antisocial Prosocial

(1) (2) (3) (4) (5) (6) (7) (8) (9)

A. Birth cohorts 1978-1979 recoded

KR mortality rate -0.055 -0.678*** -0.244 -5.373 -9.932 -5.274 8.264 -8.650 -6.531

(0.718) (0.002) (0.319) (0.501) (0.415) (0.669) (0.352) (0.220) (0.515) KR mortality rate +

KR mortality rate × Direct exp. 0.508*** -0.082 0.341** -26.007** -9.226 -0.315 31.765*** 9.977** -10.795

(0.000) (0.572) (0.011) (0.050) (0.460) (0.977) (0.000) (0.017) (0.290) B. Birth cohorts 1977-1979 recoded

KR mortality rate -0.049 -0.666*** -0.237 -5.793 -10.099 -5.570 7.922 -8.410 -6.823

(0.749) (0.002) (0.336) (0.466) (0.405) (0.650) (0.378) (0.238) (0.494) KR mortality rate +

KR mortality rate × Direct exp. 0.499*** -0.099 0.330** -25.316* -8.878 0.205 32.397*** 9.620** -10.277

(0.001) (0.482) (0.010) (0.053) (0.481) (0.985) (0.000) (0.017) (0.312) C. Birth cohorts 1976-1979 recoded KR mortality rate -0.042 -0.617*** -0.255 -5.490 -8.489 -5.603 7.016 -8.645 -6.210

(0.772) (0.003) (0.291) (0.496) (0.521) (0.649) (0.435) (0.223) (0.553) KR mortality rate +

KR mortality rate × Direct exp. 0.495*** -0.136 0.361*** -26.115* -11.308 0.228 33.91*** 10.178** -11.319

(0.001) (0.269) (0.008) (0.052) (0.321) (0.983) (0.000) (0.016) (0.261) D. Birth cohorts 1975-1979 recoded KR mortality rate -0.020 -0.631*** -0.214 -5.970 -9.611 -6.697 6.449 -7.981 -7.082

(0.892) (0.001) (0.354) (0.468) (0.468) (0.593) (0.468) (0.253) (0.507)

KR mortality rate + KR mortality rate × Direct exp. 0.475*** -0.107 0.334** -26.339* -9.845 1.937 35.369*** 9.900** -10.360

(0.001) (0.364) (0.040) (0.067) (0.396) (0.860) (0.000) (0.038) (0.319)

Note: All regressions include controls for age, gender, education and Phnom Penh as in columns 1, 3, 5, 6, 7, 8, 9, 10, and 11 in Table 3. We assume that various birth cohorts born during the

KR period have unreliable memory of direct exposure to violence and recoded the value of their direct exposure measure as zero. P-values based on robust standard errors clustered at the district

level (68 districts) are reported in parentheses. *** significant at 1%, ** significant at 5%, * significant at 10%.

38

Table 6: Robustness to Post-Genocide Relocation

Money Burning Self-Reporting Dictator Trust Risk Index

Burn Dishonesty Take % Given % Sent % Returned % Invested Antisocial Prosocial

(1) (2) (3) (4) (5) (6) (7) (8) (9)

KR mortality rate (β1) -0.018 -0.688*** -0.249 -4.398 -10.130 -6.102 10.369 -8.461 -6.443

(0.162) (0.210) (0.247) (8.392) (11.538) (11.800) (8.338) (7.170) (9.792) Direct exposure (β2) -0.063 0.056 -0.126 -0.395 -5.086 -3.353 -4.950 -2.000 -3.119

(0.080) (0.059) (0.080) (4.969) (4.193) (3.117) (3.474) (2.425) (3.253)

KR mortality rate × Direct exp. (β3) 0.577*** 0.591** 0.584*** -20.389 0.657 4.751 24.028** 18.675** -4.242

(0.166) (0.259) (0.208) (15.694) (11.334) (13.999) (9.379) (7.069) (11.929)

Age 0.004 -0.003 -0.001 0.032 -0.005 -0.172 -0.186 -0.078 -0.049

(0.005) (0.003) (0.005) (0.303) (0.200) (0.163) (0.220) (0.090) (0.166) Education (years) 0.017*** -0.017*** 0.003 0.512 0.606* 0.300 0.929** 0.036 0.494*

(0.005) (0.006) (0.006) (0.387) (0.315) (0.220) (0.410) (0.137) (0.268)

Male -0.041 -0.091** -0.121*** 9.297*** 8.397*** 3.129** 8.682*** -2.149 6.858***

(0.051) (0.045) (0.039) (2.289) (2.373) (1.451) (2.566) (1.953) (1.418)

Phnom Penh -0.206** -0.172** -0.160 17.275*** 22.102*** 14.560*** 2.750 -7.178*** 18.215***

(0.093) (0.078) (0.103) (4.130) (3.900) (3.336) (4.679) (2.024) (3.070) Relocation 0.098 -0.029 -0.013 2.406 -0.488 -2.042 5.193* 0.467 0.218

(0.061) (0.047) (0.068) (2.930) (3.704) (2.455) (2.898) (2.177) (2.640)

R-squared 0.141 0.132 0.060 0.094 0.040 0.180 Observations 492 492 492 492 492 4920 492 492 492

KR mortality rate +

KR mortality rate × Direct exp. (β1+ β3) 0.559*** -0.097 0.335** -24.787* -9.473 -1.351 34.397*** 10.214** -10.685

(p-values) (0.000) (0.515) (0.013) (0.055) (0.435) (0.897) (0.000) (0.035) (0.285)

Note: All regressions include controls for age, gender, education and Phnom Penh as in columns 1, 3, 5, 6, 7, 8, 9, 10, and 11 in Table 3. Relocation is coded as one if the participant’s current

district of residence differs to the district of residence during the KR period or at birth (post-KR cohorts). Robust standard errors clustered at the district level (68 districts) are reported in

parentheses. *** significant at 1%, ** significant at 5%, * significant at 10%

.

39

Table 7: Robustness to the Exclusion of Education and Age Controls Money Burning Self-Reporting Dictator Trust Risk Index

Burn Dishonesty Take % Given % Sent % Returned % Invested Antisocial Prosocial

(1) (2) (3) (4) (5) (6) (7) (8) (9)

A. Excluding education control

KR mortality rate (β1) -0.007 -0.712*** -0.236 -3.905 -8.286 -4.507 10.948 -8.539 -5.174 (0.158) (0.212) (0.239) (7.570) (12.029) (11.920) (9.158) (6.837) (9.701)

Direct exposure (β2) -0.078 0.065 -0.124* -0.856 -5.130 -3.104 -5.911 -2.078 -3.247 (0.068) (0.061) (0.074) (4.708) (4.162) (3.244) (3.594) (2.288) (3.206)

KR mortality rate × Direct exp. (β3) 0.601*** 0.536** 0.592*** -19.177 2.339 5.720 26.163** 18.738*** -2.918

(0.158) (0.268) (0.211) (16.164) (11.721) (14.040) (9.955) (6.984) (12.292)

Age 0.002 0.001 -0.002 -0.061 -0.160 -0.273* -0.345** -0.081 -0.167

(0.004) (0.003) (0.004) (0.233) (0.201) (0.147) (0.162) (0.079) (0.136)

Male -0.015 -0.112** -0.118*** 10.052*** 9.110*** 3.385** 10.096*** -2.080 7.472***

(0.050) (0.045) (0.043) (2.346) (1.997) (1.458) (2.520) (1.967) (1.183) Phnom Penh -0.073 -0.242*** -0.156* 20.936*** 24.285*** 14.482*** 9.921** -6.728*** 20.389*** (0.071) (0.063) (0.093) (4.625) (4.502) (3.404) (4.204) (1.922) (3.704)

R-squared 0.133 0.125 0.057 0.070 0.039 0.171 Observations 492 492 492 492 492 4920 492 492 492

KR mortality rate +

KR mortality rate × Direct exp. (β1+ β3) 0.594*** -0.176 0.356*** -23.082* -5.947 1.213 37.111*** 10.199** -8.092

(0.000) (0.253) (0.004) (0.083) (0.641) (0.910) (0.000) (0.012) (0.431)

B. Excluding age and education controls

KR mortality rate (β1) -0.010 -0.713*** -0.233 -3.822 -8.070 -4.138 11.415 -8.430 -4.948

(0.156) (0.209) (0.241) (7.638) (12.075) (11.945) (9.154) (6.984) (9.752) Direct exposure (β2) -0.064 0.073 -0.141** -1.417 -6.595** -5.603** -9.069*** -2.816 -4.774*

(0.052) (0.055) (0.061) (4.045) (3.304) (2.640) (3.170) (2.153) (2.746)

KR mortality rate × Direct exp. (β3) 0.601*** 0.535** 0.593*** -19.142 2.431 5.877 26.362** 18.784** -2.822

(0.159) (0.267) (0.214) (16.044) (11.554) (13.672) (9.988) (7.127) (12.038)

Male -0.015 -0.112** -0.117*** 10.056*** 9.120*** 3.402** 10.118*** -2.075 7.482***

(0.050) (0.045) (0.043) (2.345) (1.976) (1.413) (2.444) (1.964) (1.162) Phnom Penh -0.076 -0.244*** -0.153 21.048*** 24.577*** 14.981*** 10.552** -6.581*** 20.694***

(0.069) (0.063) (0.095) (4.505) (4.560) (3.314) (4.243) (1.928) (3.616)

R-squared 0.133 0.124 0.053 0.065 0.038 0.169

Observations 492 492 492 492 492 4920 492 492 492

KR mortality rate +

KR mortality rate × Direct exp. (β1+ β3) 0.591*** -0.178 0.360*** -22.964* -5.639 1.739 37.777*** 10.354** -7.770

(p-values) (0.000) (0.245) (0.004) (0.082) (0.660) (0.871) (0.000) (0.010) (0.448)

Note: Robust standard errors clustered at the district level (68 districts) are reported in parentheses. *** significant at 1%, ** significant at 5%, * significant at 10%

40

Table 8: Robustness to the Inclusion of Risk Attitude Money Burning Self-Reporting Dictator Trust Risk Index

Burn Dishonesty Take % Given % Sent % Returned % Invested Antisocial Prosocial

(1) (2) (3) (4) (5) (6) (7) (8) (9)

KR mortality rate (β1) -0.055 -0.687*** -0.229 -6.602 -11.245 -6.801 8.264 -8.624 -7.909 (0.154) (0.221) (0.244) (8.327) (12.467) (12.525) (8.825) (7.100) (10.340)

Direct exposure (β2) -0.077 0.064 -0.135* 0.098 -4.105 -1.993 -5.721 -2.088 -2.197 (0.074) (0.057) (0.072) (4.697) (3.983) (3.029) (3.448) (2.207) (3.048)

KR mortality rate × Direct exp. (β3) 0.565*** 0.586** 0.629*** -24.128 -3.025 0.616 23.501** 18.702*** -8.182

(0.164) (0.261) (0.214) (16.022) (11.144) (13.660) (9.256) (6.758) (11.885)

Age 0.006 -0.003 -0.001 0.086 0.004 -0.185 -0.104 -0.071 -0.028

(0.004) (0.003) (0.004) (0.294) (0.192) (0.186) (0.212) (0.080) (0.172)

Education (years) 0.018*** -0.018*** 0.005 0.391 0.445 0.099 0.980** 0.044 0.332

(0.005) (0.006) (0.005) (0.404) (0.339) (0.267) (0.399) (0.124) (0.298) Male -0.036 -0.099** -0.106*** 8.074*** 6.963*** 1.398 8.900*** -2.101 5.383***

(0.050) (0.046) (0.038) (2.420) (2.517) (1.471) (2.451) (1.817) (1.482)

Phnom Penh -0.148* -0.196*** -0.161 17.852*** 20.873*** 12.241*** 5.883 -6.877*** 17.366*** (0.086) (0.073) (0.100) (4.256) (4.000) (3.158) (4.371) (2.210) (3.213)

Risk - % Invested -0.000 0.001 -0.002*** 0.149*** 0.159*** 0.185*** -0.003 0.167***

(0.001) (0.000) (0.001) (0.042) (0.030) (0.032) (0.021) (0.026) R-squared 0.164 0.155 0.098 0.088 0.039 0.228

Observations 492 492 492 492 492 4920 492 492 492

KR mortality rate +

KR mortality rate × Direct exp. (β1+ β3) 0.510*** -0.101 0.400*** -30.730** -14.270 -6.185 31.765*** 10.078** -16.091

(p-values) (0.001) (0.494) (0.000) (0.021) (0.277) (0.585) (0.000) (0.024) (0.132)

Note: All regressions include controls for age, gender, education and Phnom Penh as in columns 1, 3, 5, 6, 7, 8, 9, 10, and 11 in Table 3. Robust standard errors clustered at the district level (68

districts) are reported in parentheses. *** significant at 1%, ** significant at 5%, * significant at 10%

41

NOT FOR PUBLICATION

Appendix Table

Table A1: Estimates of effects of exposure to genocide on prosocial and antisocial behaviour and risk

Money Burning Self-reporting Dictator Trust Risk Index

Dependent variable: Burn Burn Dishonest Dishonest Take % Given % Sent % Returned % Invested Antisocial

Preferences

Prosocial

Preferences

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

KR mortality rate (β1) -0.306 -0.317* -0.933*** -0.960*** -0.487** -12.369 -5.516 -8.608 23.033** -13.163 -8.113 (0.194) (0.180) (0.240) (0.246) (0.221) (10.916) (14.458) (16.740) (8.376) (8.327) (13.502)

Direct exposure (β2) -0.098 -0.112 0.048 0.032 -0.135 -1.507 -3.554 -5.751 -7.037 -1.618 -3.865 (0.135) (0.140) (0.070) (0.071) (0.095) (6.288) (3.396) (4.574) (3.893) (3.038) (3.228)

KR mortality rate × Direct exp. (β3) 0.923*** 0.957*** 0.809*** 0.862*** 0.711*** -8.591 -11.727** 5.093 15.316* 21.241** -4.117

(0.243) (0.232) (0.288) (0.286) (0.159) (13.344) (4.041) (15.162) (8.351) (6.664) (9.202)

Age -0.001 -0.001 -0.003 -0.003 -0.004 -0.336 0.115 -0.045 -0.074 -0.130 -0.087

(0.007) (0.007) (0.005) (0.005) (0.008) (0.349) (0.249) (0.168) (0.329) (0.108) (0.185)

Education (years) 0.014* 0.014* -0.022*** -0.025*** 0.001 0.204 0.763* 0.596 0.885 -0.088 0.541

(0.007) (0.007) (0.009) (0.009) (0.009) (0.442) (0.415) (0.347) (0.639) (0.161) (0.367)

Male 0.018 0.018 -0.117* -0.131** -0.108** 9.494*** 8.458** 3.756** 8.282** -1.641 7.203***

(0.074) (0.074) (0.063) (0.055) (0.055) (2.112) (2.995) (1.399) (2.658) (2.525) (1.092)

Phnom Penh -0.268 -0.273 -0.092 -0.155 0.000 16.533** 15.397*** 13.121 16.330 -12.523*** 14.978*

(0.337) (0.344) (0.205) (0.205) (.) (7.003) (3.425) (16.813) (10.423) (2.750) (7.728)

Advantaged player -0.037

(0.052)

Maximum number of correct answers -0.177**

(0.074)

R-squared 0.088 0.055 0.032 0.086 0.033 0.093

Observations 316 316 316 316 312 316 316 3160 316 316 316

KR mortality rate +

KR mortality rate × Direct exp. (β1+

β3) 0.617** 0.64** -0.124 -0.098 0.224** -20.96** -17.243 -3.515 38.349*** 8.078** -12.23

(p-values) (0.004) (0.004) (0.266) (0.383) (0.046) (0.011) (0.257) (0.801) (0.000) (0.013) (0.252)

Note: This Table reports results for the same set of variables as in Table 3. However, the sample includes individuals who have been in the same district since the beginning of

the KR regime. The estimation method, control variables are all the same as in Table 3.

42

NOT FOR PUBLICATION

Appendix A: Experimental Game Design and Procedure

The following section describes the experimental games with the endowment and participation

fees used in the rural areas. One of the first four tasks was randomly chosen for payment

purposes, in addition to the earnings in the self-reporting task.

Game 1: Trust

We use the standard trust game protocol to measure trust and trustworthiness. Each participant

plays both as player 1 (sender) and player 2 (receiver). The sender receives an endowment of

10,000 riel22, while the receiver is endowed with 0 riel. In the first stage, all participants are

senders and can send any positive amount x {0, 1,000, 2,000, …, 9,000, 10,000} to the

anonymous receiver, knowing that the experimenter triples the amount sent and that the receiver

receives an amount of 3x. In the second stage, all participants play as receivers. We aimed to

minimize the logistical issues in the field, so the receiver was not informed of the amount sent

by the sender. Thus, the receiver decides on an amount y {3x} to return to the sender for all

the corresponding amounts the receiver might receive. The sender is also not informed of the

amount sent back by the receiver unless the game is selected for the final payment. If the trust

game and the sender’s role are selected for the final payment, all participants receive (10,000 –

x + y). Otherwise, all participants receive (3x – y) if the receiver’s role is chosen.

Game 2: Dictator

In the dictator game, there were two stages: 1) giving; and 2) giving or taking. Each participant

plays as both player 1 (dictator) and player 2 (recipient). All participants receive an endowment

of 10,000 riel. The dictator receives an additional endowment of 10,000 riel, while the recipient

does not receive the additional endowment.

1) In dictator game giving, the dictator is asked to decide how much of the additional

endowment to give to the recipient. The dictator can transfer any positive amount x {0, 1,000,

2,000, …, 9,000, 10,000} to the anonymous recipient. The recipient must simply accept it and

is only informed of how much the dictator sends if the game is selected for the final payment.

All participants receive (10,000 + 10,000 – x) if the dictator game, part 1, and the dictator’s role

are selected for the final payment. However, if the dictator game, part 1, and the recipient’s role

are chosen, the payoffs for all participants are (10,000 + x).

2) In dictator game giving or taking, the dictator can send the additional endowment to

other players or take other player’s initial endowment. This means that the dictator can send a

negative or positive amount x {–1,000, –2,000, …, –10,000, 0, 1,000, 2,000, …, 10,000}. As

in part 1, the recipient is only told the amount the dictator sends or takes if the game is selected

for the final payment. The payoffs of all participants are (10,000 + 10,000 –/+ x) depending on

the dictator’s decision to take or give if the dictator game, part 2, and the dictator’s role are

selected and (10,000 –/+ x) if the dictator game, part 2, and the recipient’s role are selected.

22 The exchange rate was 1USD = 4037.5Riel (2014).

43

Game 3: Risk

We use a simple risk game which involves a 50% chance of winning or losing. Each participant

receives 10,000 riel and can invest any positive amount x {0, 1,000, 2,000, …, 9,000, 10,000}

in a risky business. The investment yields triple the amount invested with 50% probability and

0 with 50% probability. The outcome is decided by tossing a coin. If the coin shows heads, the

investment is successful, and all participants gain (10,000 – x + 3x). If the coin shows tails, the

payoff for all players is (10,000 – x + 0).

Game 4: Money Burning

In the money burning game introduced by Zizzo and Oswald (2001), each player is given an

opportunity to pay a fee to reduce the income of the other player. We use a simpler two player

version of this game.

All participants receive 20,000 riel. Half of them receive an additional amount called a

gift. Those who have odd identification (ID) numbers receive a gift of 5,000 riel, and those with

even ID numbers do not receive any gift. The gift is known to all participants. Participants

simultaneously decide how much of the other player’s total endowment to eliminate or not to

eliminate any. Participants have to pay from their own endowment to eliminate the other

player’s endowment. The fee incurred for eliminating other’s endowment is charged at three

levels: 5%, 10%, and 20% of the amount a player wants to eliminate of the other player’s

endowment. We study different costs of eliminating to test whether the cost has any influence

on an individual’s behaviour. In the payment stage, if this game is chosen, the odd-numbered

participants chose an even-numbered partner by randomly selecting an even ID number, and

vice versa.

Game 5: Self-reporting

In the self-reporting game, we aim to measure dishonesty using an individual-level decision-

making environment. We design a simple self-reporting task with pictures instead of games

with numerical or word tasks to accommodate the low literacy level in Cambodia. The game

involves finding the picture of a star from a sheet of 10 tables which each has 9 images (see

Appendix B). Each participant is given an envelope containing a sheet of 10 tables and is

instructed to find the stars within 1 minute.

To ensure that considerable and different opportunities for cheating, not all of the 10

tables have a star. We design 2 different sheets: a sheet with 7 stars in the 10 tables and a sheet

with only 4 stars in the 10 tables. These maximum numbers are not known to the participants.

The maximum number of 4 or 7 stars for each sheet allows considerable scope for cheating,

even for top performers. In rural areas, participant can earn 1,000 riel23 for each star found.

Participants record the total number of stars they find at the end of the sheet, place the sheet

back into the envelope, and pay themselves for this task from a small envelope containing ten

1,000 riel notes given to them at the beginning of the task. Participants place any remaining

money in the small envelope, seal it, and leave it on their desk for the experimenters to collect.

The envelopes are not opened until the experimental session is completed. To reduce scrutiny

bias, the experimenters leave the room while participants perform this task.

23 It was 2,000 riel in Phnom Penh.

44

Experimental Procedure

All the tasks were conducted with paper and pen. Clear instructions with tables and diagrams

in Khmer were provided to all participants. Before starting the experiment, participants were

randomly assigned to 1 of 3 separate rooms in a local school.24 On average, there were 24

participants per session. One session was smaller (14 participants) because of the small size of

the room available and 3 sessions were larger (30–32 participants). We ran 3 sessions (rooms)

simultaneously in Phnom Penh and in each district in Kampong Cham to reduce the spillover

effects between sessions.

Participants played with other participants in the same session. They were informed that

their partner was another participant in the session and selected their partner during the payment

stage by choosing the ID number of another participant in the same session. Participants were

also informed that they would be paid for 1 of the first 4 tasks picked at random, plus their

earnings in task 5 and participation fees of 20,000 riel in Phnom Penh and 10,000 riel in the

rural areas. At the end of the entire experiment, the experimenter rolled a dice in front of the

participants to determine for which game participants were paid. Participants did not receive

any feedback between the tasks or on the tasks not chosen for the final payment.

The games were conducted in two different orders. Game order 1 followed the sequence

of trust, dictator, risk, money burning, and self-reporting games. This order was followed in

odd-numbered districts (4 of 7 districts). In game order 2, we used the sequence of risk, money

burning, trust, dictator, and self-reporting games in even-numbered district (3 districts). We

altered the order of the games mainly to test whether participating in the antisocial games first

might influence participants’ behaviour differently.25 Participants had to make decisions in a

booth during each game, except for the self-reporting game. An experimenter was in the booth

to assist participants if they could not read or write.

24 In Phnom Penh, we conducted the experiment at a research institute: the Cambodia Development Resource

Institute. 25

Our results are robust when we control for game order instead of experimental district fixed effects. The self-

reporting task was always conducted last as participants paid themselves in this task and the amount they earned

in this task could potentially influence their decisions in other tasks if this task were conducted before the others.

45

Appendix B: Instructions and Decision Sheets

Instructions for Participants

Dear Participant,

Thank you for participating in this experiment.

There will be two main parts of today’s experiment: performing some tasks and answering the

questionnaires. There are five tasks; and we are going to ask you to make some decisions in

each task. You will have an opportunity to earn a considerable amount of money depending on

the decisions you and everyone else make during each task. You will be paid for ONE of the

first four tasks plus your earnings in the Task 5. We will invite one of the participants in the

room to draw 1 ball out of the box of 4 balls (representing the four tasks). The number of the

ball defines which game will be paid to EVERYONE in the room at the end of the entire

experiment. In addition, you will also be given an additional 10,000 riels for your participation

in this research.

Before we start, we will read the consent form. If you agree to participate in this experiment,

you are required to sign the form. Then we will collect the signed form from you. If you do not

agree, you can leave and will not receive the 10,000 riels participation fee.

The experiment will last approximately 2-2.5 hours depending on your cooperation. You can

decide not to participate at any time if you think that you are not happy with the experiment.

All decisions that you make in the tasks and responses that you provide during the interview

will be completely anonymous and will be recorded only by anonymous ID number.

You will be invited to randomly select a small envelope before we start. In the envelope, there

is a paper with your ID number. Please do not remove the ID number from the envelope and

keep this envelope (ID number) with you all the times and do not show this ID number to

anyone during and after this experiment. You will need to present your ID number to the

research assistant who will collect the decision sheet and will interview you after you complete

all the five tasks and to the cashier to receive your payment at the end of the entire experiment.

We are about to begin the first task. We will explain the task and give you some examples.

When we finish reading the instruction, you will have a chance to ask questions. During

performing each task, you also can raise your hand if you are unclear and one of our team will

come by to help you. It is very important that you understand how to do in each task. If you do

not understand, you will not be able to participate effectively. While you are waiting for other

participant to make his/her decision during this experiment, please wait at your seat and do not

communicate with other participants. Also, please do not share your decision with other

participants during this experiment to ensure the confidentiality.

If you are ready, then we will proceed. Please follow the experimenter.

46

Instructions for Task 1 (Trust Game)

In Task 1, there will be two stages as shown in this diagram. You will be asked to make a

decision involving money. This task will be played by pairs of individuals. Each pair is made

up of a “Sender” and a “Receiver”. Each of you will be paired randomly with another participant

in this room. You will not be told who you are matched with during or after the experiment.

You will play as both Sender and Receiver in the Task 1. In Stage 1, you will play as “Sender”

and will be paired with one of the participants in this room. In Stage 2, you will play as

“Receiver” and will be paired with different partner in Stage 1.

If this task is chosen for payment at the end of the experiment, we will decide which role

(Sender or Receiver) for the payment for EVERYONE in the room by tossing a coin. We will

invite one person from your group to come out here and toss the coin. If the head shows up,

the role as Sender will be chosen for the payment. If the tail shows up, the role as Receiver

will be chosen for the payment.

Stage 1: Sender

In the first stage, each of you plays as a “Sender” and has been allocated 10,000 riels. No money

will be given at this point. All actual payments will be made at the end of the experiment if this

task is chosen for the final payment when the experiment finishes.

Your decision: Decide how much of your endowment (10,000 riels) you would allocate

to your partner (Receiver) who is also the participant in this session. You can decide to

keep all money for yourself or allocate some or all of it to your partner. The experiment

will multiply what you gave by three and pass the money to your partner. Then, in the

second stage, your partner will have an opportunity to keep all of the money you sent

to him/her or to return some or all of it to you.

As shown in the decision sheet #1 that we just distribute to you, you can choose ONLY

one option.

For example, if you choose to allocate 5000 riels to your partner, your partner will get

15,000 riels (= 5000 riels x 3 times). Your partner will make decision to send the money

back to you in the second stage. If he/she sends back 4000 riels. Then you will have

9000 riels (=10,000 riels – 5000 riels + 4000 riels) to bring home if this game is chosen

for the final payment. Your partner will bring home 11,000 riels (=(5000 riels x 3 times)

– 4000 riels).

If you decide to give nothing (zero) to your partner, the first stage for you ends. Your

pay-off from this stage is 10,000 riels and your partner’s pay-off is 0 riel.

Please note that these are only examples. The actual decisions are up to you.

47

Procedure:

You will be asked to go to the private booth at the corner and bring with you the “ID

number” and the “decision sheet”. In the booth, you decide how much money you want

to allocate to your partner by choosing one of the options in the decision sheet.

Then, the research assistant will ask you the amount of money you want to allocate to

your partner to confirm your decision, write down your ID number on the decision sheet

and put the decision sheet inside a box. Then you can go back to your seat. Please keep

in mind that you are not allowed to discuss or let other participants know about your

decision.

Do you have any question? If you are ready, we will proceed. Please remain seated until we

invite you to the booth.

Stage 2: Receiver

In the second stage, each of you has been assigned as “Receiver”. Each of you is now paired

randomly with other participant in this room. Remember your partner in this stage is different

from the first stage. You will not be told who you are matched with during or after this task.

Your partner in the first stage has made a decision of how much of his/her endowment

(10,000 riels) he/she is willing to allocate to you. He/she was told that the amount he

would give will be tripled and given to you. So you would have an opportunity to return

money that you receive.

Your decision: Indicate how much of the money you are willing to return conditional

on how much you received. To be specific, how much you are going to return to your

partner, if you received 3000 riels, 6000 riels, 9000 riels, 12,000 riels, 15,000 riels,…,

30,000 riels. This means you have to complete all these blanks as shown in this decision

sheet #2. You can keep all the money, return all or some of it.

For example:

o If your partner in Stage 1 sent you 3000 riels (already triple), you decide to

return to your partner 0 riel.

o If your partner in Stage 1 sent you 12,000 riels (already triple), you decide to

send back 8000 riels.

o If your partner in Stage 1 sent you 30,000 riels (already triple), you decide to

return to your partner 10,000 riels.

Please note that these are only examples. The actual decisions are up to you.

48

Procedure:

You will be asked to go to the private booth at the corner and bring with you the “ID

number” and the “decision sheet”. In the booth, you indicate how much you will return

to your partner (please fill in all blanks).

The research assistant will ask you the amount you want to return in each blank to

confirm your decision and write down your ID number in the decision sheet, and put

the decision sheet inside a box. The research assistant will assist you to write the amount

based on your decision in each blank if needed. Then you can go back to your seat.

Please keep in mind that you are not allowed to discuss or let other participants know

about your decision.

Do you have any question? If you are ready, we will proceed. Please remain seated until we

invite you to the booth.

49

Decision Sheet of Trust Game: Sender’s Role

DECISION SHEET #1

PARTICIPANT ID: _______________

TASK 1

STAGE 1

Please decide: “how much would you like to allocate to your partner?”

Please select only one option from the following:

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

50

Decision Sheet of Trust Game: Recipient’s Role

DECISION SHEET #2

PARTICIPANT ID: _______________

TASK 1

STAGE 2

The amount in column A is the amount you received from your partner. The amount is already tripled.

Please decide: “how much would you like to return to your partner?” Please write down your decision in

each row in column B according to the amount you received from your partner in column A.

A B

Amount received from your partner (already tripled) Amount you wish to send

back to your partner

3,000

__________________Riel

6,000

__________________Riel

9,000

__________________Riel

12,000

__________________Riel

15,000

__________________Riel

18,000

__________________Riel

21,000

__________________Riel

24,000

__________________Riel

27,000

__________________Riel

30,000

__________________Riel

51

Instructions for Task 2 (Dictator Game)

There will be two parts in Task 2. You will be asked to make a decision involving money. This

task will also be played by pairs of individuals. Each pair is made up of a “Sender” and a

“Receiver”.

If Task 2 is chosen for payment at the end of the experiment, we will decide which part (PART

I or PART II) for the payment for EVERYONE in the room by tossing a coin. We will invite

one person from your group to come out here and toss the coin. If the head shows up, PART I

will be chosen for the payment. If the tail shows up, PART II will be chosen for the payment.

Then, we will decide which role (Sender or Receiver) in the chosen PART above for the

payment for EVERYONE in the room by tossing the coin again. We will invite another person

from your group to come out here and toss the coin. If the head shows up, the role as Sender

will be chosen for the payment. If the tail shows up, the role as Receiver will be chosen for the

payment.

Part I: Giving

Each of you is assigned the role as a “Sender”. You are now paired randomly to anyone in this

room. You will not be told who you are matched with during or after the experiment.

Both you and your partner have been allocated 10,000 riels in this part of the

experiment. In addition, only you as “Sender” have been allocated an additional 10,000

riels. No money will be given at this point. All actual payments will made at the end of

the experiment if this task is chosen for the final payment when the experiment finishes.

Your decision: Decide how much of your additional endowment (10,000 riels) to

allocate to your partner. You can choose any amount from as shown in the decision

sheet #3.

Your partner will not make any decision. He/she will take home whatever amount you

allocate to him/her plus his/her initial 10,000 riels allocation, and you are as “Sender”

will take home whatever amount you keep for yourself plus your initial 10,000 riels

allocation.

For example, you choose to allocate 4000 riels to your partner. Then your partner will

go home with 14,000 riels (=10,000 riels + 4000 riels) and you will go home with 16,000

riels (10,000 riels +10,000 riels – 4000 riels).

Please note that this is an example only. The actual decision is up to you.

Procedure:

You will be asked to go to the private booth at the corner and bring with you the “ID

number” and the “decision sheet”. In the booth, you decide how much money you want

to allocate to your partner by choosing ONLY one option in the decision sheet #3.

Then, the research assistant will ask you the amount of money you want to allocate to

your partner to confirm your decision, write down your ID number on the decision sheet

and put the decision sheet inside a box. Then you can go back to your seat. Please keep

52

in mind that you are not allowed to discuss or let other participants know about your

decision

Do you have any question? If you are ready, we will proceed. Please remain seated until we

invite you to the booth.

Part II: Giving or Taking

In the second part, there is the same procedure as in Part I. You are assigned the role as a

“Sender”. You are now paired randomly to a new partner from anyone in this room. You will

not be told who you are matched with during or after the experiment. Please keep in mind that

your partner in this part is different from your partner in Part I.

You and your new partner have been allocated 10,000 riels. In addition, only you as

“Sender” have been allocated an additional 10,000 riels. No money will be given at this

point. All actual payments will be made at the end of the experiment if this task is chosen

for the final payment.

Your decision: Decide how much of your additional endowment (10,000 riels) to

transfer to your partner. Moreover, you can also transfer a negative amount. This means

that you can take up to 10,000 riels from your partner. You can choose any amount from

the options in the decision sheet #4.

The minus amount means you take your partner’s endowment instead of dividing your

endowment to your partner.

For example, if you decide to choose – 6000 riels, it means you take 6000 riels from

your partner’s endowment. So your partner will take home 4000 riels (=10,000 riels –

6000 riels) and you will have 26,000 riels (=10,000 riels + 10,000 riels + 6000 riels).

If you decide to choose 5000 riels to transfer to your partner, he/she will take home

15,000 riels (=10,000 riels + 5000 riels) and you will take home 15,000 riels (=10,000

riels + 10,000 riels – 5000 riels)

Please note that these are only examples. The actual decisions are up to you.

Procedure:

You will be asked to go to the private booth at the corner and bring with you the “ID

number” and the “decision sheet”. In the booth, you decide how much money you want

to allocate to OR take from your partner by choosing one of options in the decision sheet

#4.

Then, the research assistant will ask you the amount of money you want to allocate to

OR take from your partner to confirm your decision, write down your ID number on the

decision sheet and put the decision sheet inside a box. Then you can go back to your

seat. Please keep in mind that you are not allowed to discuss or let other participants

know about your decision.

Do you have any question? If you are ready, we will proceed. Please remain seated until we

invite you to the booth.

53

Decision Sheet of Dictator Game: Giving

DECISION SHEET #3

PARTICIPANT ID: _______________

TASK 2

PART 1

Please decide: “how much would you like to allocate to your partner (using additional money

10,000 Riel)?” Please select only one option from the following:

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

54

Decision Sheet of Dictator Game: Giving or Taking DECISION SHEET #4

PARTICIPANT ID: _______________

TASK 2

PART II

Please decide: “how much would you like to transfer to your partner or how much would you like to take from your partner?”

Please select only one option from the following:

- 10,000 minus

- 9,000 minus

- 8,000 minus

- 7,000 minus

- 6,000 minus

- 5,000 minus

- 4,000 minus

- 3,000 minus

- 2,000 minus

- 1,000 minus

0

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

55

Instructions for Task 3 (Risk Game)

In Task 3, once again, you will be asked to make a decision involving money in this Task.

You have been allocated 10,000 riels. No money will be given at this point. All actual

payments will be made at the end of the experiment if this task is chosen for the final

payment..

You have an opportunity to invest all, some or none of these 10,000 riels.

There is 50% chance of successful investment and 50% chance of unsuccessful

investment. If the investment succeeds, you will receive 3 times the amount of money

you invested. If the investment fails, you will lose the amount you invested.

We will decide the outcome of the investment by tossing a coin at the end of the entire

session if this task is chosen for payment. We will invite one person from your group to

come out here and toss the coin in front of all of you. If the coin shows head,

EVERYONE in this room get 3 times of the amount that each participant invested. But

if the coin shows tail, EVERYONE in this room will get nothing.

For examples:

- If you choose to invest nothing, you will get 10,000 riels if this task is chosen for

payment at the end of the experiment.

- If you choose to invest all of the 10,000 riels, you get 30,000 riels (=10,000 riels x 3

times) if head shows up or nothing (zero riels) if it’s tail.

- If you choose to invest 4000 riels, you receive 18,000 riels (= [4000 riels x 3 times] +

6000 riels) if the head shows up and 6,000 riels (=10,000 riels – 4000 riels) if the tail

shows up.

Please note that these are only examples. The actual decisions are up to you.

Procedure:

You will be asked to go to the private booth at the corner and bring with you the “ID

number” and the “decision sheet”. In the booth, you choose how much you want to

invest from the decision sheet #5.

Then, the research assistant will ask you the amount of money you want to invest to

confirm your decision, write down your ID number on the decision sheet and put the

decision sheet inside a box. Then you can go back to your seat. Please keep in mind that

you are not allowed to discuss or let other participants know about your decision

Do you have any question? If you are ready, we will proceed. Please remain seated until we

invite you to the booth.

56

Decision Sheet of Risk Game

DECISION SHEET #5

PARTICIPANT ID: _______________

TASK 3

Please decide: “how much would you like to invest in a risky business?” Please select only one option

from the following:

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

57

Instructions for Task 4 (Money Burning Game)

In Task 4, you are now paired randomly to a new partner from anyone in this room. You will

not be told who you are matched with during or after the experiment.

You and your partner have been allocated 20,000 riels.

We divide you into two groups: Group 1 has Odd ID number and Group 2 has Even ID

number.

The person who has Odd ID number receives a gift of 5000 riels.

We will pair the person who has Odd ID number with the person who has Even ID

number. Please remember that you will not be told who you are matched with during or

after the experiment.

Your and your partner’s incomes are public knowledge, meaning that you can know

how much your partner’s income is, and vice versa your partner will learn about your

income too.

Your decision: Decide how much you would like to reduce your partner’s total income.

But you have to pay from your income for reducing other person’s income. There are

three prices of reducing other person’s income: 5%, 10% and 20% of the amount you

want to reduce.

The gray box in the “decision sheet #6/7” is your and your partner’s total income. The

price of reducing is at 5% in Case 1, 10% in Case 2, and 20% in Case 3. You have to

choose ONLY ONE option in Case 1, Case 2 and Case 3.

For example: you have Odd ID number, you receive gift (5000 riels) and your partner

does not. So your total income is 25,000 riels and your partner’s total income is 20,000

riels.

In Case 1 (5% price of reducing), you decide to reduce 10,000 riels of your partner’s

income. Thus, you will have to pay from your income by 500 riels (= 5% * 10,000 riels).

Your partner decides to reduce 20,000 riels of your income; hence, he/she will have to

pay from his/her income by 1000 riels (= 5% * 20,000 riels).

Your income will remain 4500 riels (= 25,000 riels – 500 riels – 20,000 riels) and your

partner’s income will be 9000 riels (= 20,000 riels – 1000 riels – 10,000 riels).

Please note that these are only examples. The actual decisions are up to you.

Other participant has been told to make the same decision. This means that your partner

can do the same thing as you are being told.

Both you and your partner make decision simultaneously, but only the choice of one

player (your partner or your choice) will be randomly selected for the payment if the

task is chosen for the final payment. Then, we will also randomly select which

case/price of reducing (5%, 10% or 20%) for the final payment.

58

Procedure:

You will be asked to go into the private booth at the corner and bring with you the “ID

number” and the “decision sheet”. In the booth, you decide how much money you want

to reduce other person’s income in Case 1, Case 2 and Case 3. Then, you estimate how

much do you think your partner decides to reduce your income.

Next, the research assistant will ask you the amount of money you want to reduce other

person’s income in each case to confirm your decision, write down your ID number on

the decision sheet and put the decision sheet inside a box. Then you can go back to your

seat. Please keep in mind that you are not allowed to discuss or let other participants

know about your decision.

Do you have any question? If you are ready, we will proceed. Please remain seated until

we invite you to the booth.

59

Decision Sheet of Money Burning Game

DECISION SHEET #6

(For ODD ID number)

PARTICIPANT ID: _______________

TASK 4

YOU Your Partner

Initial endowment: 20,000 Riel 20,000 Riel

Gift: 5,000 Riel 0 Riel

Total income:

25,000 Riel

20,000 Riel

Case 1: At 5% price of reducing other person’s income

How much do you want to reduce other

person’s income?

Please select only one option from the

following:

if the price for eliminating is:

0 0

5,000 250

10,000 500

15,000 750

20,000 1,000

60

Case 2: At 10% price of reducing other person’s income

How much do you want to reduce other

person’s income?

Please select only one option from the

following:

if the price for eliminating is:

0 0

5,000 500

10,000 1,000

15,000 1,500

20,000 2,000

Case 3: At 20% price of reducing other person’s income

How much do you want to reduce other

person’s income?

Please select only one option from the

following:

if the price for eliminating is:

0 0

5,000 1,000

10,000 2,000

15,000 3,000

20,000 4,000

61

Decision Sheet of Money Burning Game

DECISION SHEET #7

(For EVEN ID number)

PARTICIPANT ID: _______________

TASK 4

YOU Your Partner

Initial endowment: 20,000 Riel 20,000 Riel

Gift: 0 Riel 5,000 Riel

Total income:

20,000 Riel

25,000 Riel

Case 1: At 5% price of reducing other person’s income

How much do you want to reduce other

person’s income?

Please select only one option from the

following:

if the price for eliminating is:

0 0

5,000 250

10,000 500

15,000 750

20,000 1,000

25,000 1,250

62

Case 2: At 10% price of reducing other person’s income

How much do you want to reduce other

person’s income?

Please select only one option from the

following:

if the price for eliminating is:

0 0

5,000 500

10,000 1,000

15,000 1,500

20,000 2,000

25,000 2,500

Case 3: At 20% price of reducing other person’s income

How much do you want to reduce other

person’s income?

Please select only one option from the

following:

if the price for eliminating is:

0 0

5,000 1,000

10,000 2,000

15,000 3,000

20,000 4,000

25,000 5,000

63

Instructions for Task 5 (Self-reporting Game)

In Task 5, each participant will be given a large envelope and you will find a sheet of 10

matrices like the one below:

You will get different sheet of matrices.

Your role is to tick in the box if you see a “star” in the matrix.

There are 10 matrices and you have 1 minute for this Task. You will get 1000 riels

(USD0.25) for each “star” you found.

However, some of the matrices have no “star”.

When you find the matrix that does not have “star”, please mark in the box.

You will not receive the money for the matrix that does not have “star”. But you will

receive money based on number of star you found.

Please write down the total number of star you found in this box. For example, if you

find six stars, please write 6.

64

Total : ………… 6 ………

On your table, there is a small envelope containing ten 1000 riel notes.

Please pay yourself for this task based on the total number of stars you found.

When you finish, please put the matrix sheet and any remaining money in the small

envelope in this box.

Our team will leave the room for 1 minute.

Please note that we will not open the matrix sheet and count the remaining money until

you leave the room (the session finishes).

Do you have any question? If you are ready, we will proceed.

65

Decision Sheet of Self-reporting Game

TASK 5

- Please tick in the box if you find a star in the matrix.

- Please cross in the box if you do not find star in the matrix.

Example:

Total number of stars found:

…………………………

Appendix C: Construction of the District Level Morality Rates

We use geographic variation in KR mortality rates across districts to examine the impact of the

genocide on children’s outcomes. We construct KR mortality rates using information sourced

from the CGD and Census 1998. The CGD includes a district identifier of each KR mass

gravesite and the estimated number of bodies at each mass grave.1 Some graves have minimum

and maximum estimates of bodies and, in such situations, we use the average of the two

estimates to construct district-level KR-related deaths. To obtain our preferred measure of KR

mortality rates, we divide the estimated deaths under the KR in a district (based on information

in the CGD) by the sum of the estimated deaths under the KR and the number of individuals

who were in the district at the start of the KR regime (in 1975) and were still alive in 1998

(based on Census 1998 data).2 As we do not have information on the number of individuals

who survived the KR regime, but died between 1980 and 1998 at the district level, the estimated

KR mortality rates are noisy. Districts in five provinces (Kaoh Kong, Preah Vihear, Otdar Mean

Chey, Krong Kaeb, and Krong Pailin) are excluded from the analysis because no information

on the estimated deaths under the KR regime is available in the CGD.

1 The CGD was initially developed by Yale University and has been updated by the Documentation Center of

Cambodia (DC-Cam). We use data from both sources.

See http://www.yale.edu/cgp/ and http://www.d.dccam.org/Database/Index1.htm for details on the Cambodian

Genocide Program and DC-Cam database. 2 Living persons who were born between 1975 and 1979 are allocated to their districts of birth and included in the

denominator.

1

Appendix D: Directly Exposed and Indirectly Exposed Groups

Panel B of Table 1 shows that, in the trust game, individuals directly exposed to genocide send

on average less of their endowment to the other players (27.3% versus 33.4%; p = 0.018) and

return less (28.1% versus 32.8%; p = 0.000) than those indirectly exposed. The directly exposed

group also shares less of the endowment in the giving part of the dictator game, compared to

the indirectly exposed group (21.1% versus 26.4%; p = 0.023). In the dictator game giving or

taking, each individual has 3 options: (1) take some or all of the other player’s endowment; (2)

do not give to or take from the other player; and (3) give some or all of one’s endowment to the

other player. Overall, 33.7% of the directly exposed group (66 out of 196) chose option 1,

compared to 35.8% of individuals (106 out of 296) in the indirectly-exposed group. The figures

are similar for options 2: 31.6% for the directly exposed group and 27% for the indirectly

exposed group. However, 34.7% of the directly exposed group chose option 3, compared to

37.2% of the indirectly exposed group. We define a simple binary variable as equal to 1 if the

individual takes some or all of the other player’s endowment (option 1); otherwise, it is equal

to 0. Panel B of Table 1 and Figure A1 show that directly exposed individuals do not differ

significantly from indirectly exposed individuals in the dictator game taking.

[Appendix Figure A1]

Regarding risk-taking behavior, individuals directly exposed to genocide invest less than

indirectly exposed individuals (45.2% versus 47.3%) but the difference is not significant

statistically (p = 0.402). Figure A1 also shows the differences in the means in the anti-social

games. In the money burning game, we measure the burning decision by the choice to reduce

(burn) the other player’s money for at least 1 of the 3 prices (costs) of burning (5%, 10%, and

20%). More participants in the directly exposed group (51%) than the indirectly exposed group

(43.9%) choose to eliminate the other player’s money for at least 1 of the 3 prices. In the self-

reporting game, 41% of the directly exposed group takes extra money, compared to 24% of the

indirectly exposed group (panel B, Table 1). This difference is strongly statistically significant

(p = 0.000), suggesting that exposure to genocide can lead to dishonest behavior.

2

Figure A1: Percentage points of mean differences in experimental outcomes between

directly exposed and indirectly exposed groups

Note: The directly exposed group and the indirectly exposed group are defined in section 4.3 of the paper. The

burn variable equals 1 if the player decides to reduce (burn) the other player’s money for at least 1 of the 3 prices

and 0 if player decides not to burn any money. The dishonest variable equals 1 if the player takes extra money to

which he or she is not entitled and 0 otherwise. The giving or taking variable equals 1 if the player decides to take

some or all of the other player’s endowment and 0 otherwise.

p=0.123

p=0.000

p=0.627

p=0.023 p=0.018p=0.000

p=0.402

18

16

14

12

10

8

6

4

2

0

-2

-4

-6

-8

Burn

DishonestTake

% Given

% Sent

% Returned

% Invested