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The Persistent Effect of Exposure to Civil Conflict on Political Beliefs and Participation: Evidence from the Peruvian Civil War
THE EFFECT OF EXPOSURE TO CIVIL CONFLICT ON
POLITICAL BELIEFS AND PARTICIPATION:
EVIDENCE FROM THE PERUVIAN CIVIL WAR
Benjamin Anderson and Ramiro Burga
1. Aims and Motivation
2. Relevant Literature
4. Historical Overview
5. Data Description
6. Identification Mechanism
7. Assumptions & Threats to Identification
9. Specific Comments
Aims & Motivation
◻ Political beliefs of citizens have broad
implications as to the effects on society
◻ Preferences of voters heavily influence
policy-making processes and even the
◻ Conflict is prevalent and recurring in many
parts of the world
◻ Relatively little is known about the effects
of conflict on citizens’ political beliefs and
participation compared to other outcomes
such as human capital and labor market
◻ Undesirable effects on political beliefs of
conflict exposed citizens can negatively
impact social welfare
◻ People exposed to conflict are highly resilient in political beliefs and tend to
recover in the long-run; only in voting turnout is a very slight increase detected
(Adhvaryu and Fenske, 2014)
◻ Exposure to ethnic conflict slightly increases political participation (Bellows &
Miguel, 2009; Blattman, 2009)
◻ Exposure to the Peruvian civil conflict has been shown to decrease human capital
(Leon, 2012) → Lower education is associated with lower political participation
◻ Exposure to conflict in Peru also has negative effects on labor market outcomes and
domestic violence (Galdo, 2010)
◻ Early-life trauma and macroeconomic shocks have been shown to increase
individuals’ risk aversion in the long-run (Kim and Lee, 2012; Moya, 2012)
◻ Exposure to violence → lower generalized trust (Jaeger and Paserman, 2008;
Rohner et al., 2013)
◻ Cause → “status inconsistency” (CVR, 2004)
◻ Geographic and temporal variation 1980-1993
◻ Main perpetrators: PCP-SL; Peruvian State
◻ Guerrilla strategy → move from highlands toward
the ultimate target, Lima
◻ ~0.31% of pop. killed
◻ ~75% of provinces
◻ ENAHO (Encuesta Nacional de Hogares):
◻ We used the 2007-2014 waves of this nationally-representative sample of
households and individuals.
◻ It includes: (i) current demographic and socioeconomic information, (ii) citizens’
opinions regarding government institutions, (iii) civil rights issues, (iv) democracy,
(v) voting actions and (vi) civic participation.
◻ CVR (Truth and Reconciliation Commission)
◻ The CVR information comes from the reconstruction of violent acts that took place
between 1980 and 2000.
◻ Each act of violence attributable to the civil conflict was coded as an event in a
given space and time
◻ In total, the CVR recorded more than 36,000 violent acts in its database.
◻ District and date of birth obtained from ENAHO is linked to civil conflict data. We limit
our analysis to individuals over the age of 18 and that were born after 1955.
◻ (i) Distrust of government institutions; (ii) negative opinions about democracy; (iii)
negative opinions about civil rights; (iv) voting turnout and submission of blank
ballots; and (v) participation in civic organizations.
◻ Distrust index: sums the number of government institutions in which the
respondent indicates he/she has little or no trust (from 0 to 16).
◻ Democracy: sums the number of responses indicating a negative opinion toward
democracy (from 0 to 3).
◻ Civil rights: number of responses in this category indicating a lack of regard for
civil rights (from 0 to 4).
◻ Civic Participation: participation in political party, union or community group.
◻ Exposure to violence:
◻ Years of exposure to violence in one’s district during different sensitive stages of
life for an individual: -1-3 years old, 4-6 years old, 7-12 years old and 13-17.
Table 1: Exposure to violent
We will focus our analysis on
individual who are still
leaving in the same states
where they were born.
◻ Fixed effects at district and year of birth levels are included.
◻ Clustered standard error at district level
Table 2: Mean comparison Tests
◻ i: Individual, t:year of birth, r: district, p: province, T: wave, s: stages.
is the average effect of exposure for an individual who experiences conflict during
control for specific differences across districts which are time-invariant.
control for any common shock that affect respondents of the same age similarly.
control for the province-specific divergences over time.
control for any common shock that affect respondents in the same wave similarly
◻ The standard errors are clustered at the district level to deal with the geographic and
temporal correlation in the error terms.
◻ What this strategy does is comparing different cohorts within districts and comparing
them with other districts that were exposed to different levels of violence.
1. Conditional Independence: After controlling for the fixed effects and the province
trends, the error is orthogonal to the exposure. This could be sustained if:
a. Cohorts’ differences in outcomes across many districts are not significant
(parallel trends) in years previous to the conflict.
b. The predetermined characteristics of the population settled in a district are
similar in violent and nonviolent years compared with other districts. Leon
(2012) tests this using census data and shows no significant differences in
demographics (cohort sizes, age, gender, migration, asset index, etc.)
2. Effect of our exposure variables is separable.
3. Effect of exposure varies based on sensitive stages of life.
Threats to Identification
1. Sample selection due to underreporting of victims.
a. Direction unclear
b. Most likely, attenuation
a. Direction unclear; positive vs. negative selection into migration
b. It does not seem to be the case that people who migrate are different from the
ones who stay (Leon, 2012)
3. Previous research suggests education, HH expenditure, may be endogenous to
exposure (Leon, 2012; Galdo, 2010)
◻ Specification 1: ind.
were born after
◻ Specification 2: ind.
were born after
◻ We only find effects
Table 3: Main results
Table 4: Restricting the number of waves
◻ Columns (1) and (2) includes one
additional variables of exposure: 18-
25 years old.
◻ Columns (3) and (4) have number of
violent acts in logs.
◻ In both specification, the significance
of the exposure variables is kept.
1. Further Research and Robustness of Results
a. Analyze violence by type
b. Violence by perpetrator
c. Allow effect of exposure to vary by year
d. Assign exposure by month of violent act to reduce measurement error in
e. Usage of actual voting records to eliminate reporting bias (preferably
referendums and local elections)
2. External Validity
a. Conflicts with different motivations (e.g. political, resource, ethnic, etc.),
perpetrators (State, rebel groups, gangs, etc.), violent tactics (murder, torture,
landmines, forced labor, etc.) → likely different outcomes in PBP
b. Does the initial situation matter (i.e. poor vs. middle income country,
democratic vs. autocracy, country education level, etc.)
1. Persistent effects of exposure to conflict on political beliefs and participation may
2. Due to the various sources of downward / attenuation bias, our results should be
interpreted as lower bounds
3. We increase support suggesting that people who are exposed to conflict are
resilient in their political beliefs and participation
4. Future research should follow up on the true magnitude of these effects and the
temporal persistence in the short and long-run (i.e. severity of effects might be
quite large in the short-run
5. Inter-generational effects, hereditary transmission
6. Channels through which these changes occur (erosion of trust, risk attitudes, etc.)
7. Mechanisms to facilitate the healing process of affected citizens