Journal of Refugee Studies ß The Author 2015. Published by Oxford University Press.
All rights reserved. For Permissions, please email: journals.permissions@oup.com
doi:10.1093/jrs/feu037

Focus on the Forest, Not the Trees: A
Changepoint Model of Forced Displacement
JUSTIN SCHON
Department of Political Science, Indiana University, Bloomington, Indiana, USA
jschon@indiana.edu
MS received May 2014; revised MS received November 2014

Keywords: displacement, violence, conflict, Somalia

Introduction
Living through conflict can be a horrifying and traumatic experience. Villages
and cities get destroyed, women get raped, soldiers and civilians may gettortured, thousands die from battle, disease and food insecurity tends toproliferate, and countless other evils take place. Facing such horror, civilians
instinctively will want to leave areas affected by conflict, where they or their
loved ones may be harmed. Yet, displacement does not happen at a constantrate throughout a conflict. Displacement ebbs and flows. For example, on
28–29 April 1994, an estimated 250,000 Rwandan Hutus crossed the border
into Tanzania within a 24-hour period (Terry 2002). On 9 November 2012,
Syria experienced one of its largest refugee exoduses of its conflict when
11,000 Syrians crossed the border in one day (Gladstone and MacFarquhar2012). At the same time, there are many time periods during all conflicts

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

What causes forced displacement flows, defined as refugee or internally displaced person (IDP) flows, to vary over time within conflict? While forced
displacement displays clear relationships with conflict dynamics, little is
known about what actually causes forced displacement to vary during a conflict
and when that variation is likely to occur. This article explores whether fluctuations in daily violence levels, structural aspects of conflict or both cause variation in forced displacement within conflict. Analysis of daily displacement data
and violent events data finds that structural aspects, particularly changes in theconflict’s geographical scope and balance of power, drive increases or decreases
in forced displacement. These effects occur due to the portion of the population
affected by conflict, security disruptions and fear. There are two main contributions. First, the findings illustrate the complexity of the violence–
displacement relationship. Second, this article demonstrates the importance ofconsidering structural aspects of conflict even as data and methodologicaladvancements have allowed scholars to zoom in on the details of conflict.

2

Justin Schon

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

when little to no displacement occurs. While progress has been made on what
conditions cause conflicts to produce more or less displacement, little attention has been paid to the variation in displacement within conflicts.
The general consensus to date is that more violence causes more displacement. Numerous case studies have been used to illustrate this relationship(Zolberg et al. 1989). Large-N statistical analyses have also supported
this relationship (Schmeidl 1997; Davenport et al. 2003). Even the individual-level analysis of Prakash Adhikari from civil war in Nepal has foundthat violence is the strongest predictor of displacement during conflict(Adhikari 2013).
However, this research has tended to either use static forms of analysis or
employ monthly or annual data for time-series cross-sectional statistical tests.
Such forms of analysis miss the rapid and dramatic fluctuations in displacement that occur during conflict. Conflict in Somalia since 2008 has seen over
20,000 people displaced on several days, all of which have been followed
shortly by rapid declines in displacement levels. These fluctuations should
not be dismissed as noise. Civilians react to conflict dynamics very quickly(Liu et al. 1979). These reactions can be captured by daily displacement
counts from the United Nations High Commissioner for Refugees(UNHCR) Population Movement Tracker system. Meanwhile, the assessmentof structural factors prevents the analysis from ‘missing the forest for thetrees’. These structural factors include the balance of power and geographicalscope of the conflict. Balance of power and geographical scope certainly are
related to daily violence fluctuations, but they are conceptually distinct because they capture broader trends within a conflict.
Of course, people can become displaced for a plethora of reasons. Drought,
famine, lack of economic opportunities, floods and a number of other reasonscan cause people to leave their homes. However, it is crucial to note that thisarticle focuses exclusively on people who flee their homes explicitly due toviolence and insecurity. Civilians rarely move for one single reason, but there
is usually a primary reason for displacement. The task in this article is toassess what it is exactly about that violence that causes people to flee theirhomes. Results indicate that structural factors, rather than fluctuations indaily violence, are what drive variation in forced displacement within conflict.
Structural factors affect displacement by influencing the proportion of acountry affected by conflict, creating fear or disrupting security.
This article will proceed in the following manner. First, it explains thetheoretical grounding for why violence levels and structural factors should
impact forced displacement. This will lead to the hypotheses. Daily displacement flow data in Somalia from the UNHCR and violent event data fromthe Armed Conflict Location and Event Dataset (ACLED) allow testing of
the hypotheses. After that, results are explained and discussed. Lastly, theconclusion provides implications and thoughts on how to proceed with thisresearch programme.

A Changepoint Model of Forced Displacement

3

TheoryOne of the most troubling but least discussed aspects of Somalia’s recurring
humanitarian crises is the low sense of Somali social and ethical obligation toassist countrymen from weak lineages and social groups. This stands in sharp
contrast to the very powerful and non-negotiable obligation Somalis have toassist members of their own lineage (Menkhaus 2012: 34).

In addition to the potential loss of social support that displaced Somalis may
experience, there are many dangers that displaced Somalis must endure.
Many displaced people eventually get forcibly evicted from their homes orrobbed (Human Rights Watch 2013a). The government-affiliated militias thatare supposed to provide camp security also allegedly divert and steal as muchfood aid as possible, seize control of tents that are supposed to be distributed
freely in order to profit from ‘providing shelter’ and have been known toarrest or beat up those who raise concerns. This is not to mention the prevalence of sexual violence in the displaced persons camps (Human Rights
Watch 2013a: 33). Such abuses have been documented throughout Somalia.
They are also all too common in refugee camps in Kenya and in Somali

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

For this analysis, it is assumed that people make strategic choices about
whether and when to flee their homes during conflict (Davenport et al.
2003; Moore and Shellman 2004, 2006, 2007; Adhikari 2013). People weighthe benefits of fleeing their homes against the costs of becoming displaced.
Within this framework, it is assumed that people have sufficient information
to make these choices. Disagreement exists about the level of realism in thisassumption, but it is reasonable to assume that civilians pay close enoughattention to violence trends during conflict to make informed decisions about
whether to leave their homes.
The clearest benefit of fleeing their homes is that it can allow civilians toescape dangerous areas during conflict. Besides potentially increasing the
likelihood of surviving the conflict, displacement can have many other positive effects on civilians. It can reduce the amount of trauma civilians suffer,
which improves many aspects of psychological health. In addition, displacement can put civilians in a position to receive social services that they would
not have received by staying in their homes (Mels et al. 2010).
However, becoming displaced can be very costly. Many people have familyties to specific areas or even plots of land that have been in their family’s
possession for generations. Displacement can also separate people from theirsocial support structures. For example, Somalis are renowned for their generosity and willingness to share resources with complete strangers. Yet, thisgeneralization overlooks the fact that generosity often does not extend
beyond clan boundaries. When people flee a haven of their clan and moveinto an area that their clan does not control, it can be extremely difficult toobtain social support (Kapteijns 2013). Ken Menkhaus has summarized thissituation very concisely:

4

Justin Schon

H1: An increase in the number of total violent events increases the amount of
displacement.

Specific types of violent events may provide better explanations for displacement. First, battles between armed groups may increase displacement levels

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015neighbourhoods in Kenya like Eastleigh in Nairobi (Human Rights Watch
2013b).
With such substantial costs and risks, civilians clearly have a serious decision about whether circumstances truly justify displacement. Civilians flee
when their likelihood of persecution rises above some threshold. This threshold varies from context to context, likely even from person to person(Davenport et al. 2003; Moore and Shellman 2004; Adhikari 2013). Events
that entail a greater increase in threat to civilians are going to cause moreforced displacement. Once the threat to civilians has passed the threshold,displacement should occur without much delay. In many cases, this shouldmean that displacement should occur on the same day, or at least within a
few days, of the event that pushed the threat level above the threshold. These
responses could be mediated by several factors, including transportation
costs, social networks, variation in how individuals assess risk, degree ofattachment to home and economic opportunity (Czaika and Kis-Katos
2009; Edwards 2009; Harpvicken 2009; Adhikari 2013). Such factors demonstrate that the displacement process is more complex than a simple push–pullmodel would suggest.
Still, there is a strong consensus that violence is most closely related todisplacement. Simply put, more violence causes more displacement (Adhikari2013). Additional nuance has been introduced to this explanation to clarify
the motivations for armed groups to displace civilians and show that battle
deaths are not significantly related to displacement (Valentino et al. 2004;
Melander and Oberg 2007; Lyall 2009; Steele 2009). In other words, thequantity of violent events matters more than their intensity. While there iscertainly variation at the individual level, quantitative work has shown thatgroups as a whole respond more to the quantity of violent events than to theintensity of those events (Melander and Oberg 2007).
Since violence has been shown to have the strongest relationship with displacement, this article focuses on this relationship. However, it is unclear
whether displacement varies in conjunction with variation in total violence,
the amount of certain types of violence or with structural factors. Different
logic for civilians applies with each of these possibilities, so it is important to
explore each of these while laying out the hypotheses to be tested in this article.
The simplest hypothesis would draw a relationship between the number of
total violent events and the amount of displacement. As the amount of violence, no matter the type or severity, increases, civilians may be expected toperceive the conflict as being more threatening. This produces the first
hypothesis:

A Changepoint Model of Forced Displacement

5

because civilians fear getting caught in the crossfire. This dynamic is most
likely to exist in conflicts where one or both of the armed groups lack thecapability or discipline to target the opposing armed group exclusively(Weinstein 2007; Williams 2013). Disciplined and capable armed groups
should be able to minimize civilian casualties. Still, whenever there is alack of capability or discipline, a second hypothesis should hold:
H2: An increase in the number of battles increases the amount of displacement.

H3: An increase in the amount of one-sided violence increases the amount of
displacement.

There is a chance that none of these hypotheses will hold. This is because any
measures of total events are likely to include a lot of minor events that do notaffect a person’s calculation of the level of threat that they face. A moreproductive approach might be to recognize that civilians understand the reality that there is inherently going to be violence during a conflict. Fluctuations
in aggregate amounts of violent events or fatalities might not be of great
concern to civilians if they have this recognition.
Instead, displacement patterns might only be affected when structural
factors change. Specifically, these structural factors include changes in thebalance of power or geographical scope of the conflict. Geographical scopemeans the proportion of the country engulfed in conflict. Conflicts tend to
not affect an entire country in exactly the same way. Many conflicts evenleave parts of the countries in which they occur untouched by violence ordestruction. Conflicts with a small geographical scope inherently have a different structure than conflicts that span an entire country (Blattman andMiguel 2010). An increase in the geographical scope of a conflict should

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

Alternatively, one-sided violence, or violence against civilians, is what increases displacement. There are two potential explanations for this relationship. Violence against civilians sometimes happens due to an intentional
military strategy of displacement. Here, one-sided violence is a clear formof communication from the perpetrator that it wants civilians to leave aparticular area. This is a way for armed groups to remove their opponent’s
source of support and improve their relative tactical position. The perpetrator’s actions intentionally raise the level of threat to civilians until it is satisfied with having displaced enough people (Valentino et al. 2004; Lyall 2009;
Steele 2011). One-sided violence is caused in other situations by indiscipline
among troops on one or both sides of a conflict (Weinstein 2005, 2007). This
indiscipline is hard to predict for civilians. They do not know if or when they
will be attacked by armed groups. This produces a generalized fear everywhere that the armed groups operate. People flee because of this generalized
fear that raises their perceived level of threat. Regardless of which of these
explanations applies, the same hypothesis should hold:6

Justin Schon

H4: An increase in the geographical scope of a conflict increases displacement.
H5a: A change in the balance of power caused by a change in territorial control
decreases displacement.
H5b: A change in the balance of power caused by the start or end of foreignintervention increases displacement.
H5c: An expected change in the balance of power increases displacement.

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

expose more people to conflict and violence (Melander and Oberg 2007). Thisshould increase displacement levels.
Alternatively, a change in the balance of power could affect displacementlevels. This can occur in three ways. Observed changes in territorial control
mark the end of a period of fear, leading to decreased displacement. Foreigninterventions, at both their entry and exit into a conflict, disrupt the security
balance. These disruptions both increase displacement. Expected changes interritorial control create fear, which increases displacement. In sum, security
disruptions and fear are the keys to explaining the potential ways balance ofpower shifts can affect displacement.
First, an important town or strategic location may change hands. Changes
in territorial control increase the amount of resources available to the side
obtaining new territory and decrease the resources available to the side losing
territory. In a relationship that may be somewhat counterintuitive, displacement should decrease after the change in territory has occurred. Thisis because the displacement should primarily occur during the fighting forthe territory. After the change in territorial control, remaining civilians areless likely to flee, since the civilians who wanted to flee would have alreadydone so. Fear arises as civilians anticipate a possible shift in territorial
control. The observed shift in territorial control should mark the end ofthat period of fear. Once the period of fear ends, displacement should
decrease.
Second, foreign intervention can change the balance of power by assisting
one side more than the other. The entrance of a foreign armed group into a
conflict can increase the amount of forced displacement as the unsupportedside in the conflict performs more violence against civilians (Wood et al.
2012). Then, the exit of a foreign armed group from a conflict can increase
the amount of forced displacement by creating a security vacuum that theremaining parties must fight to fill.
Third, expected shifts in the balance of power could also cause variation in
displacement. Here, the balance of power is expected to shift when an offensive is launched. Military offensives are defined simply as coordinated armed
actions that aim to capture territory, or at least weaken the opposing side’scontrol of its territory. Civilians should become displaced in greater numbers
when offensives are launched as they attempt to avoid harm from the coming
violence. They fear the effects of a potential shift in the balance of power.
This leads to the final set of hypotheses:

A Changepoint Model of Forced Displacement

7

Case Description

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

The hypotheses will be tested with a quantitative case study in the context ofconflict in Somalia. Somalia has been in a state of protracted instability eversince the fall of Siad Barre’s regime in 1991. Clan cleansing took place from1991 to 1993. This clan cleansing was primarily between the Darod andHawiye clans, but other major clans such as the Dir, Rahanweyn and Isaq
clans were all involved as well (Kapteijns 2013). There has also been a failed
state since 1991. American and United Nations peacekeeping missions during
the 1990s ended in disaster (Clarke and Herbst 1997; Lewis 2008).
Warlords, political entrepreneurs and Islamist groups have all attempted
to create a fully functioning state apparatus since then, but they have allfailed. In 2004, Colonel Abdullahi Yusuf—formerly president of the semiautonomous north-eastern Somali region of Puntland—was chosen to
become President of Somalia by the delegates at the Mbagathi Conferencein Kenya. However, Yusuf’s Transitional Federal Government (TFG) was
unable to obtain any legitimacy and had to base itself in Jowhar and thenBaidoa, never Mogadishu. In 2006, an alliance of Islamic courts known as
the Islamic Courts Union (ICU) came to power in much of southern andcentral Somalia. At its peak, the ICU eclipsed the TFG in power
and legitimacy.
The ICU was able to combine fundamentalist Islam with clan solidarity,
which has historically proven to be a successful combination in Somalia. Its
downfall came in late 2006 when Ethiopia, provoked by ICU rhetoric ofbuilding a pan-Somali nation, accusations of ICU involvement in bombingsin Kenya and Ethiopia, and appeals for support to Eritreans and Ethiopian
opposition groups, launched an invasion of Somalia. This invasion was supported by the United States as part of its War on Terror, though the UnitedStates limited its support to financial and logistical assistance and periodic
missile strikes (Lewis 2008). Somalis generally resented the presence ofEthiopian troops in Somalia, but relations between Somali civilians andEthiopian troops became especially bad in mid-2007, when the experienced
and relatively well-disciplined Ethiopian troops that initially invaded Somalia
were replaced by a new unit that was far less disciplined (Lewis 2008).
Between the start of this intervention and the end of 2008, two-thirds ofMogadishu’s 1.2 million residents fled (Harper 2012). This observation isimportant because, despite the commonly expressed view of Somalia’s conflict
as being ongoing since Siad Barre’s fall from power, the violence that has
occurred since 2007 has been distinct for civilians (Lindley 2010).
In January 2009, Ethiopian troops withdrew from Somalia, but violence
continued. African Union peacekeeping troops have also been deployed toSomalia. In 2011, after a spate of kidnappings and Al-Shabaab activity in
Kenya tried the patience of Kenya’s military and civilian leaders for the lasttime, Kenya launched an invasion into Somalia in a coordinated offensivewith African Union and Ethiopian troops. The gains made during this8

Justin Schon

Data
Multiple data sources are combined for this analysis. Violence data are usedfrom the ACLED. ACLED includes violent events from 1997 to May 2013
on the African continent. ACLED also has coded selected conflicts that
occurred before 1997, such as the conflict in Bosnia from 1992 to 1995
(Raleigh et al. 2010). As the codebook states on page 4, ACLED covers
events that occur within the context of civil war and violent activity outsideof civil war. Prominent examples of this violent activity include violenceagainst civilians, militia interactions, communal conflict and rioting. This
project only uses the violent events data from Somalia for the 2008–August
2013 time period.
This dataset primarily relies upon news reports of violent events for its
reporting of violent events and the characteristics of those events. Local,
regional, national and continental media sources are reviewed daily.
Consistent non-governmental organization (NGO) reports are also used tosupplement news reports in hard-to-access cases, of which Somalia is certainly one. Third, Africa-focused news reports and analyses are used to supplement daily media reporting (Raleigh et al. 2010). With thesecomplementary sources, ACLED is unlikely to perform differently fromone African country to another.
Therefore, the most important tradeoffs to consider for ACLED’s codingof events within Somalia are the same as the tradeoffs with the dataset as awhole. ACLED uses a very general definition of events that allows it toinclude non-fatal and even non-violent events. This means that ACLED
can capture a large number of events and is unlikely to miss relevant

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

offensive, which included a dramatic peak in its offensive on Al-Shabaab
forces in Kismayo, left many observers thinking that Al-Shabaab had finallybeen defeated and would be forced into obscurity. This thinking has beenchallenged by the September attack on the Westgate shopping mall in
Nairobi, so there is likely to be ongoing insurgency from Al-Shabaab forsome time. Throughout all of this instability, millions of people have beenin need of humanitarian assistance. Droughts, famines and floods have also
all aggravated humanitarian concerns.
This discussion should make two points clear. Somalia’s conflict has
involved a range of actors and has varied in intensity. The variation in
actors is useful for testing expectations about the effects of actor behaviour
on displacement. The variation in intensity of the conflict allows theresearcher to test expectations about the effects of variation in violence, balance of power and geographical scope on displacement. While Somalia hasoften been dismissed by conflict scholars as a weak, failed state whereobserved relationships are not generalizable to other contexts, it actuallypresents an ideal case in which to build and test theories on conflict andhow civilians respond to it.

A Changepoint Model of Forced Displacement

9

Table 1
Summary Violence Statistics from ACLED for Somalia

2008
2009
2010
2011
2012
Jan–May 2013

ACLED total events

ACLED battles

ACLED one-sided violence

911
700
1,337
1,409
2,195
1,129

589
347
813
751
1,227
664

187
176
288
330
590
292

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

events to a conflict. Yet, in order to capture all of these events, ACLED
inherently sacrifices conceptual validity. Additionally, ACLED codes anevent that lasts multiple days as being multiple events. For example, an
event that lasts three weeks is coded as 21 events in ACLED (Eck 2012:
127–128). Table 1 summarizes the violence recorded in Somalia since 2008.
While the analysis is performed on total ACLED events, the most common
types of these events are battles and one-sided violence, so all three are displayed. Readers interested in viewing the data set itself or its codebook can
download them from the ACLED website (www.acleddata.com).
With all of these events, ACLED has plenty of shortcomings. For starters,
ACLED has uneven quality control within countries, which can cause biased
subnational analysis. Some regions receive more attention from media sources
and it can be more difficult to obtain information about some regions thanothers. ACLED also tends to overestimate the precision of its geographic
coordinates for events and mistake villages/towns with the same name (Eck
2012).
In addition, ACLED suffers from the same problems faced by all event
data sets that rely upon news reports of overestimating the proportion ofviolence in urban areas, either including irrelevant events or not including
relevant events, lacking precision in their geocoding of events and media
fatigue during conflict (Davenport 2010; Dulic 2010; Eck 2012). Mediafatigue is the idea that news outlets provide less comprehensive coverage ofconflicts as they drag on because they know that their audiences eventuallylose interest. While ACLED has taken steps to decrease the severity of these
problems, such as drawing from NGO reports as well as daily news reports
for its event coding, these problems have not disappeared.
The displacement data come from UNHCR’s Population Movement
Tracker in Somalia. These data include daily counts of displacement from
1 January 2008 through to August 2013. Currently, Somalia is the only
country in the world for which UNHCR has daily counts of displacement,so these are unique data. Each internally displaced person (IDP) gets coded
as being displaced due to insecurity, clan conflict, flood, drought, lack of10

Justin Schon

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

livelihood, IDP return, fire, forced return, eviction, relocation or cross-border
movement. These counts are done by UNHCR partners in Somalia, of which
there are 48 in total and at least two staff members per location. Since
displaced persons tend to move in groups, interviews are done with thegroup to assess the number of people in the group, reason for their displacement and other relevant information. Based on the author’s personal communications with UNHCR staff at the Somalia office, group discussions with
IDP, religious, opinion and local leaders are also used to obtain information
on displaced groups. There are often multiple factors influencing displacement, but UNHCR partners are trained to identify one single most importantfactor in each case.
As a caveat, this method of counting means that Somalis who do not crosspaths with the UNHCR partners will not be counted. Some people may
intentionally avoid NGOs. Their experience with conflict may create
enough fear or mistrust to motivate them to avoid organizations and authority figures. Others do not use roads or travel along uncommon paths, making
them difficult to detect. These issues should not bias results too severely, sincemost civilians should be travelling along the routes where UNHCR partners
can count them and most people should be capable of distinguishing between
armed groups and humanitarian organizations. Fear and mistrust of armed
groups seem unlikely to systematically translate into fear and mistrust of
humanitarian organizations. Any measurement error that exists should produce underestimates of displacement (UNHCR 2007).
Another potential source of measurement error can occur when there is alarge amount of displacement within a short period of time. These chaotic
periods, when floods of fleeing civilians are attempting to escape the dangers
of conflict, can be very difficult to monitor. Patrick Ball, with the Human
Rights Data Analysis Group, notes this issue in the collection of migration
data from Albanian border guards as they monitored the flows of ethnic
Albanians from Kosovo (Ball 2000). On days when thousands of Kosovar
Albanians crossed the border, the guards’ registry system would break down.
Yet, even with this problem, the guards managed to register more than twothirds of the Kosovar Albanians who entered Albania. So, floods of displacement are not a catastrophic problem. Problems with undercounting thatremain can be overcome by talking to group leaders, rather than each individual. Since displaced individuals tend to travel in groups, group leaders cangive accurate counts of the number of people in their particular group,
regardless of the size of the group.
The dependent variable is the sum of displacement due to insecurity andclan conflict. These two forms of displacement can be referred to as conflictinduced migration. Conflict-induced migration directly results from the violent contest for political and military power between groups. This is a bettermeasure than total displacement because the research question is not concerned with floods, droughts, famines or non-violence-related events. Forced
eviction can be a violent process, but it is not part of the contest for power

A Changepoint Model of Forced Displacement

11

within Somalia. Multiple causes can also be affecting civilians, such as clan
conflict and drought, but instances where there is insecurity or clan conflictare distinct. In these cases, civilians face constraints on the available time tomake displacement decisions, safe paths to use for travel and limitations on
safe destination options that do not exist outside of the context of droughts,
famines, floods or other non-violence-related events. A graph of this timeseries is displayed in Figure 1.

Motivating the Model

Number displaced

80,00040,000

0
2008

2009

2010

2011

Time

Figure 1
Somalia Conflict-Induced migration

2012

2013

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

A Bayesian changepoint model tests the hypotheses (Raftery and Akman
1986; Chib 1995, 1998; Martin and Quinn 2007; Brandt and Sandler 2010).
Details of the model can be found in the cited articles, but a brief explanation
is included here. A changepoint is a time point where the mean or variance ofa time-series changes. In addition, a changepoint occurs when the regression
parameters of a model change. Bayesian changepoint models are estimated byfirst having the user specify a function and a certain number of changepoints.
Then, the MCMCpack package in R estimates the location of those changepoints in the time series of interest so as to create stationary time periods
between the changepoints, also known as regimes (Martin et al. 2011). This
process is repeated several times with different numbers of changepoints.
Once all of the models with different numbers of changepoints are estimated,
Bayes Factors can be calculated that allow the researcher to select the modelwith the appropriate number of changepoints. The determination of the mostappropriate model is made by selecting the model with the largest Bayes
Factor. Once the appropriate model is selected, the researcher can obtainthe mean and variance of the series within each regime. For multivariate
functions, it is also possible to get slope coefficients that show the relationship between the independent variables and the dependent variable withineach regime. This means that this model can assess when changepoints

12

Justin Schon

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

occur, how relationships between variables of interest change over time andwhat the relationships between those variables of interest are.
Detection of changepoints can be useful in identifying when an event happens that changes dynamics in the time series. In the context of this analysis,
detection of changepoints can identify when relevant structural factors
change. Structural factors produce effects on displacement that last as longas those factors do not change. Structural factors can remain constant forlong periods of time, or they can change after mere weeks. This will become
clear in the discussion of results.
As dynamics change from regime to regime, there is the possibility that therelationship between variables changes. This is in fact what is found in
the relationship between responses to terrorist attacks and terrorist targeting(Brandt and Sandler 2010). Since changepoints and relationships between thechangepoints can explain variation in the dependent variable of interest,
Bayesian changepoint models are incredibly valuable when it comes to specifying which fluctuations are due to short-term relationships and which
fluctuations are due to structural dynamics.
In the context of this research project, the relationship between violenceand displacement may be different at different time periods during a conflict,which might mask relationships between violence and displacement. For
example, different phases of a conflict motivate different strategies forarmed groups. Government forces may use violence during one time period
to intentionally displace people from a village or town in order to removesocial support and protective cover for rebel groups (Lyall 2009). In anothertime period, those same government forces may use violence to protect avillage or town from an abusive rebel group. This time period may involvea negative relationship between violence and displacement, whereas the firsttime period would involve a positive relationship between violence anddisplacement. Without a changepoint model, these negative and positive
relationships between violence and displacement may effectively cancel eachother out and show no significant relationship. There are numerous otherplausible scenarios where violence and displacement may exhibit negative andpositive relationships within the same conflict (Valentino et al. 2004;
Lubkemann 2008). This is what makes a Bayesian changepoint model so
useful for testing the hypotheses.
Many different models are estimated for this analysis. A univariate modelwith just displacement is estimated first. Then, subsequent models analyse therelationship between different types of violence and displacement. Eachmodel is estimated with ACLED data. Robustness checks are also conductedusing the Uppsala Conflict Data Program Geo-referenced Event Data. Since
the checks produce similar results, they are not discussed further. Separate
models are run looking at just the relationship between total violence anddisplacement, battles and displacement, and one-sided violence and displacement. There are also models run with total violence, battles and one-sided
violence. All models are also estimated with zero, one, two and three lags.

A Changepoint Model of Forced Displacement

13

Estimating models with up to three lags is a fairly conservative measure
because many existing accounts of displacement indicate that when people
flee from violence, they flee immediately or as soon as the fighting calms
down enough to make it safe to travel (Umutesi 2000; UNMISS 2014). So,
people choose to flee and act on that choice with very little delay, if any. This
is not just a trait of displacement in Somalia. For example, one study ofVietnamese refugees in the 1970s found that 85 per cent of the surveyedrefugees decided to flee their homeland between two hours and two days
before their departure (Liu et al. 1979).
Results

Table 2
Changepoint Models

0 lags

One lag

Two lags

Three lags

Total violence

BattlesOne-sided
violence

Total, battles
and one-sided
violence

No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime

No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime

No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime

No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime
No significant
relationshipin any regime

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

After estimating all of these models, it turns out that none of the coefficientsis statistically significant within any of the regimes. This is regardless of thenumber of lags or controls. This provides evidence that none of the different
types of violence is related on a day-to-day basis to aggregate levels ofdisplacement in Somalia. A summary of these results is displayed in Table 2.
These results clearly indicate that hypotheses 1–3 cannot be accepted. This
motivates a closer examination of the events occurring at the changepoints inthe time series. This facilitates the evaluation of hypotheses 4, 5a, 5b and 5c.
This evaluation begins by estimating changepoint models with different numbers of changepoints to determine the most appropriate number of changepoints for the time series. The determination is made by selecting the modelwith the highest Bayes Factors.

14

Justin Schon

40000

500

1000

1500

2000

0

500

1000

1500

2000

0.6

0

0.0

Probabilities

0

Displaced

Number Displaced in Somalia and Regime Probabilities

Time (in days)

Figure 2
Number Displaced in Somalia and Regime Probabilities

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

Since the model with 14 changepoints has the highest Bayes Factor, this is
the most appropriate model to use for our analysis of displacement. The
dates calculated for these changepoints are displayed in Table 3. Figure 2
displays the probabilities of being in a particular regime or time period between two changepoints. A changepoint occurs every time the graph showsa change in regime.
Importantly, there is some variance in the changepoints. Certainty levels ineach changepoint date can be assessed by calculating 95% confidence intervals for the changepoints. This makes it possible to work with different levelsof certainty for each changepoint, rather than having to select some decision
rule of allowing events within some set number of days to count as causesof the changepoint. The changepoints with the highest certainty have a
confidence interval that stretches plus or minus one day from the meanchangepoint date. The changepoint with the least certainty occurs within a
two-month interval. All 95% confidence intervals for the changepoints are
displayed in Table 3.
To explain this variation from regime to regime, there must be an examination of events occurring in Somalia that could change the mean amount of
displacement. Then, observed patterns in the types of events that cause changepoints can be evaluated, as well as whether the average number ofdisplaced people per day increases or decreases at each changepoint.
Therefore, a timeline of events that could be related to increased displacement

A Changepoint Model of Forced Displacement

15

Table 3
Changepoint Bayes Factors and Estimated Dates and Confidence Intervals
Estimated change- Changepoint
point dateconfidence
intervals

1 Changepoint

0

27 June 2008

2 Changepoint

190

3 Changepoint638

4 Changepoint683

5 Changepoint851

6 Changepoint890

7 Changepoint924

8 Changepoint973

9 Changepoint

1,019

10 Changepoint 1,066

11 Changepoint 1,176

12 Changepoint 1,095
13 Changepoint 1,170

14 Changepoint 1,344

True changepoint
date(17 June 2008)–
27 June 2008(29 June 2008)
24 August 2008
26 July 2008(29 June 2008)–(24 August
2008)
25 December 2008 (23 December
30 December 20082008)–(31December 2008)29 January 2009 (29 January
30 January 20092009)–(31January 2009)
8 May 2009
(7 May 2009)–(11 7 May 2009
May 2009)
27 July 2009(24 July 2009)–(1 24 July 2009
August 2009)31 December 2009
2 January 2010(31 December2009)–(6January 2010)
9 September 2010 (8 September
9 September 20102010)–(12September 2010)
8 October 2011
(3 October 2011)– 16 October 2011(17 October
2011)
13 February 2012 (12 February
16 February 20122012)–(16February 2012)
23 February 2012 (20 February
28 February 20122012)–(28February 2012)
31 May 2012
(22 May 2012)–(9 6 June 2012
June 2012)29 September
30 September(26 September
2012
2012
2012)–(4October 2012)
8 July 2013
(7 July 2013)–(11 July 7, 2013
July 2013)15 Changepoint 1,338
Note: The Bayes Factor column is for diagnostic purposes. It motivates the selection of the 14
changepoint models. The estimated changepoint date, changepoint confidence intervals and thederived true changepoint dates were all found for the 14 changepoint models. This is why there isno entry in these three columns within the 15 Changepoint row.

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

Bayes
Factor16

Justin Schon

Discussion of Events at the Changepoints
Using the timeline in the Appendix, the analysis assesses which events causedchangepoints. This discussion identifies the true dates for changepoints indisplacement. Identifying the true dates facilitates the calculation of themean amount of displacement within each regime, which enables the assessment of hypotheses 4, 5a, 5b and 5c.
As the fighting between TFG-allied forces and Islamist groups continued
into 2008, it became increasingly clear that Ethiopia’s superior firepower was
not going to be enough to defeat the Islamist insurgency. Frustration contributed to the indiscipline of TFG-allied forces. Ethiopian troops especiallydeveloped a reputation for firing indiscriminately into populated areas whenever they were attacked. The brutality of this violence only seemed to growmore severe. Then, the Djibouti Agreement that was formed on 9 June 2008
appeared to provide an opportunity to wind down the violence. In exchange
for a cessation of hostilities, Ethiopia agreed to withdraw its troops from
Somalia. However, disgruntled actors played the role of spoilers to the finalization of the peace deal. Doubts over whether Ethiopia actually would withdraw its troops and what the power hierarchy would be after Ethiopia’s
departure created a lot of unease. By the end of June, fierce fighting had
broken out in Mogadishu, central Somalia and along the Ethiopian border
between the Ogaden National Liberation Front (ONLF) and Ethiopian
troops. All of this violence heralded a transition to a period with substantiallymore displacement. Ethiopian troops knew that they would not be able to
win the war and Somali groups were jostling for position in preparation forthe coming withdrawal. The Islamist groups attacked TFG-allied forces andmade many gains. Ethiopian troops retaliated brutally whenever they could.
The destructive battles between Ethiopians and other TFG-allied forces andthe Islamist groups yielded a lot of civilian casualties. It is unclear whether
violence specifically in Mogadishu or combined violence throughout Somalia

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

levels was created. The timeline was primarily constructed from extensive
searches on Lexis Nexis. These searches narrowed the geographical scope
to Somalia and used the keywords of ‘violence’, ‘attacks’, ‘Al-Shabaab’,‘Hizbul Islam’ and related terms. Information from these searches was supplemented by news stories from BBC, The New York Times and reports fromvarious think tanks. It is displayed in the Appendix.
This is not even close to a complete list of all events in Somalia, nor is it
meant to be. Instead, it is a list of theoretically relevant events that could be
expected to cause increases or decreases in the level of displacement.
Important events are also included regarding the opening and closing ofborders, as well as the economic and humanitarian situation in Somalia, toconfirm that economic and humanitarian events do not influence the amountof displacement. An event is classified as potentially associated with a changepoint if it occurred within the 95% confidence interval of the changepoint.

A Changepoint Model of Forced Displacement

17

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

caused the first changepoint. The timing of this changepoint is very clear
though, since the 95% confidence interval for this changepoint places thechangepoint between 27 June and 29 June. This violence collectively seems
to have convinced civilians that there would be a shift in the balance ofpower between Al-Shabaab and TFG-allied forces. As expected in hypothesis
5c, this expectation led to an increase in the amount of forced displacement.
The second regime, in fact, experienced the highest amount of displacement
per day of any regime.
The timing of the second changepoint has the widest confidence interval of
any of the changepoints, ranging from 29 June to 24 August. With an intervalof almost two months during which the event causing the changepoint could
have taken place, there are naturally a lot of possibilities. However, an examination of events occurring within Somalia provides some intuition on when
the true changepoint is likely to have occurred. Violence at the end of Junemarked the beginning of a period of chaotic jostling for power and vicious
battles between Ethiopian and TFG-allied troops and Somali Islamist groups.
This dynamic appears to have continued at a high intensity until the Islamists
captured Kismayo on 22 August. Therefore, the second changepoint mostplausibly should be around 22, 23 or 24 August. The capture of Kismayo
ended a period of significant growth in the power of Al-Shabaab relative to
TFG-allied forces. This shift in the power balance resulted in a decreasein displacement from the second to the third regime, consistently withhypothesis 5a.
This situation changed when the Ethiopian troops began their withdrawal
from Somalia. The withdrawal constituted the removal of what had been acentral actor to the conflict. It is potentially not intuitive that displacement
increased after Ethiopian troops began their withdrawal. Despite preparations
that all parties had been making for months, Somalia was engulfed in competition to fill the power vacuum left by Ethiopia’s departure. This culminated in Al-Shabaab’s seizing control of the government in Baidoa when
Ethiopia’s withdrawal concluded on 26 January 2009. There was substantial
displacement in the immediate aftermath of this takeover. This takeover is aturning point for putting Al-Shabaab in the position of definitively being themost powerful group in Somalia. The next changepoint occurred between 29
January and 31 January, not 26 January, because civilians needed a couple
days to adjust to the implications of this power shift. With the immediate
positioning for control of Somalia completed, displacement fell dramaticallyin the next regime. This is all consistent with hypothesis 5b.
Al-Shabaab proceeded to consolidate its position over the next several
months. Then, on 7 May 2009, Al-Shabaab began advancing more in thesouth of Somalia and it launched an offensive to take Mogadishu. This offensive marked Al-Shabaab’s reaching its peak of power. Al-Shabaab’s
advance throughout Somalia was very destabilizing, as Al-Shabaab wasable to seize control of many areas of the country from TFG-allied forces.
During this advance, the TFG-led government even had to announce on 20

18

Justin Schon

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

June that it needed additional troops within the next 24 hours or else it was
likely to fall. Civilians certainly would have expected this offensive to resultin the balance of power shifting even further in Al-Shabaab’s favour. The
high displacement levels during this regime are consistent with the expectation from hypothesis 5c.
This instability continued until the TFG government decided to reorganize
the military and launch an offensive of its own to pacify Mogadishu on 23
July. Civilians responded within the following week. The 95% confidence
interval shows this as having taken place between 24 July and 1 August,
but people respond quickly enough to changes in their environment thatthe true timing of the changepoint is on 24 July. Over the next few
months, the TFG was finally able to turn back Al-Shabaab gains andassume a more powerful position in the conflict. The TFG’s success wasstabilizing for Somalia, and that increased stability significantly lowered displacement levels. Civilians were able to revise their expectations so that theyno longer expected a shift in the power balance. The lower displacementlevels were thereby consistent with hypothesis 5c.
This relative calm lasted until between 31 December 2009 and 6 January
2010. This is when Al-Shabaab renewed its efforts to seize control of more ofSomalia. Intense fighting for control of Mogadishu was noted between
1 January and 19 January 2010. Al-Shabaab also expanded its attacks to
Puntland in January 2010. It was trying to rise to its former peak ofpower, but the TFG was able to prevent it from doing so. Al-Shabaab’s
efforts climaxed with the Ramadan offensive in August and early
September. Ramadan ended on 9 September 2010, and it was clear by thatpoint that the offensive had failed. Al-Shabaab had become substantiallyweaker.
This regime featured two important dynamics. First, the offensives
launched by Al-Shabaab made it clear to civilians that a shift in the balanceof power would occur, one way or the other. Second, expanding attacks to
Puntland increased the geographical scope of the conflict. Both of these
dynamics, according to hypotheses 4 and 5c, are expected to produce
increased displacement. It is unclear which factor is more important in thiscontext. Still, it is important to note that this is the clearest example of thegeographical scope of the conflict growing. Since displacement levels
responded in the expected direction during this regime, there is at least limited evidence in support of hypothesis 4.
Al-Shabaab’s weakened state allowed TFG forces to continue engaging it
and to produce a more stable and secure environment. Displacement levels
were therefore relatively low in the next regime. This lasted for about 13
months, until between 3 October and 17 October 2011. This is when the
Kenyan intervention began. Kenyan troops entered Somalia on 16 October
2011. Therefore, the true changepoint occurred on 16 October. The Kenyanintervention did cause a slight increase in displacement, consistently withhypothesis 5b.

A Changepoint Model of Forced Displacement

19

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

Then, in February 2012, displacement suddenly increased dramatically, as
Kenyan forces engaged Al-Shabaab in Afgoye and Baidoa, seizing control ofboth towns. These towns are strategic towns in Somalia, and they showedthat the Kenyan military was making progress towards Kismayo, which was
the most important city for Kenyan forces to take in order to secure southern
Somalia for their own security interests. The fighting over and change incontrol of these towns was enough of a destabilizer to increase displacement.
Even in the next regime, when control of Afgoye and Baidoa had changed
hands, displacement was higher than before the battles. This is because civilians all knew that an offensive on Kismayo was coming, and there were
expectations of this becoming a very bloody offensive. Changes in the balanceof power were expected by all, which means that the increased displacementlevels are consistent with hypothesis 5c.
The next changepoint occurred between 22 May and 9 June 2012.
Afmadow changed hands on 31 May. Al-Shabaab also held a public military
parade in Kismayo on 31 May as a show of strength. Then Biibi, a town 75
kilometres from Kismayo, was taken on 5 June by Kenyan forces. The
coming battle for Kismayo was now inevitable. This is also why 6 June is
the most plausible date for the changepoint. Biibi’s capture by Kenyan forces
marked a change in the power balance between TFG-allied forces and
Al-Shabaab. It showed that Al-Shabaab was likely to lose the battle for
Kismayo. Since there were expectations for a change in the balance ofpower, it goes against hypothesis 5c for displacement levels to have declined.
This is the only regime where hypothesis 4, 5a, 5b or 5c is contradicted.
Then, the battle for Kismayo happened in September 2012. On 29
September, Al-Shabaab surrendered Kismayo. This event marked the beginning of a series of major setbacks for Al-Shabaab. Its apparent defeat andweakening over the next several months made Somalia a relatively stable andsecure place compared to what it had been. Finally, after Al-Shabaab attacks
in June 2013 failed to have much success, the group seemed to have lost forgood. From July through to August 2013, displacement was almost nonexistent, with a mean of only 23 people getting displaced each day. This
was the most stable period of the conflict, with Al-Shabaab clearly much
weaker than the TFG, which explains why this regime would involve theleast displacement. After key failures for Al-Shabaab, there was a patternof displacement levels falling. Territory changes like Al-Shabaab’s losing
Kismayo seem to have decreased displacement, which is consistent withhypothesis 5a (see Table 4).
This analysis finds that specific events do not cause deviations in the baseline level of displacement that is inherently part of conflict. Instead, structural
factors drive increases or decreases in displacement. Ethiopian forces leaving
Somalia and Kenyan forces entering Somalia are two examples of actors’
entering or leaving the conflict and causing long-term changes in displacement. Changes in the power balance between Al-Shabaab and TFG-allied
forces also noticeably affected displacement. There is also some weak

20

Justin Schon

Table 4
Average Daily Displacement within Each True Regime
Average displaced per day

1 Jan–27 June 2008
28 June–24 August 2008
25 August–30 December 2008
31 December 2008–30 January 200931 January 2009–7 May 2009
8 May–24 July 200925 July–31 December 2009
1 January 2010–9 September 2010
10 September 2010–16 October 201117 October 2011–16 February 201217–28 February 201229 February–6 June 2012
7 June–29 September 2012
30 September 2012–7 July 2013
8 July–31 August 2013

919
4,052
2,431
1,678
301
3,189
604
1,227
348
504
2,163
828
297
53
23

evidence that increasing the geographical scope of the conflict, as Al-Shabaab
did by expanding attacks to Puntland in January 2010, can increase forced
displacement.
Rival Explanations
Sceptics of this explanation are likely to suggest several alternative ways tointerpret available data on forced displacement and its causes. Social scientists are justifiably sceptical of parsimonious explanations, so some effort
must be made to show why other explanations do not work. For this analysis, there are four main challenges that may be offered.
First, border closures and openings may influence displacement levels.
Border considerations may enter into an individual’s decision-making process
about whether to flee their home instead of, or in addition to, the decisionmaking process about where to go once the person is displaced. For thischallenge to hold up, openings or closures of Somalia’s borders should
correspond with changepoints or spikes in displacement. Kenya’s borderwith Somalia has been closed officially since January 2007, but there was atemporary opening from 12 March until 6 May 2008. As shown in Table 5,displacement numbers one week before and one week after these dates do notshow any spikes in displacement, and they are not even close to being associated with any changepoints.
Second, timing of the changepoints may be driven by individual events
rather than structural factors. It is possible that the high displacement days

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

Regime 1
Regime 2
Regime 3
Regime 4
Regime 5
Regime 6
Regime 7
Regime 8
Regime 9
Regime 10
Regime 11
Regime 12
Regime 13
Regime 14
Regime 15

True regime dates

A Changepoint Model of Forced Displacement

21

Table 5
Displacement Before and After Border Status Changes
12 March: Border opens

6 May: Border recloses

7 days before
6 days before
5 days before
4 days before
3 days before
2 days before
1 day before
BORDER CHANGE
1 day after
2 days after
3 days after
4 days after
5 days after
6 days after
7 days after

1,700
100
420
0
1,300
840
80
730
520
4,400
1,800
490
750
0
710

280
340
4,500
1,700
7,300
1,100
0
5,300
290
910
480
330
70
500
190

could cause the timing of changepoints to be a mathematical artefact rather
than a substantively important date. Yet, the discussion of Somalia should
illustrate the distinct qualities of structural factors as compared to regular
events. Furthermore, there can be high levels of displacement at the changepoints, making them appear to have similar short-term effects as regular
events that cause high levels of displacement. However, while short-term
spikes in displacement can occur at the changepoints, the structural factorsthat cause the changepoints have effects that last for the duration of theregime, or time period between changepoints. To illustrate this separation,
Table 6 highlights the seven days with more than 20,000 people displaced.
Four out of seven of these dates fall within confidence intervals for changepoints. All of these dates correspond with violence in major cities, whether it
was in Mogadishu or a regional population centre. Yet, through all of theattacks and violence in major cities, only a few of them coincided withchangepoints. This indicates that perhaps violence in major cities should
be expected to cause more displacement than violence in rural or sparsely
populated areas, but it does not necessarily have lasting effects.
Third, people may be more likely to become displaced when there is morehumanitarian aid available for displaced persons. This relationship would
exist because humanitarian aid could be a benefit of becoming displaced.
The converse that less humanitarian aid would lead to less displacement
should also hold by this logic. Again, the timing of events in Somalia does
not support this explanation. Some of the major changes in humanitarian aid
levels occurred in January 2010 when the World Food Program (WFP)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

Day

22

Justin Schon
Table 6
Top Displacement Days 2008–13
Date

Number displaced

28 June 2008
25 July 2008
26 July 2008
11 November 200827 December 200828 December 2008
3 January 2009

75,00037,00039,00026,00084,00032,00028,000Concluding Thoughts and Directions for Future Research
By showing the necessity of focusing on structural factors instead of fluctuations in day-to-day violence to explain variation in forced displacement
within Somalia, this article has made an important contribution to explaining
variation in forced displacement over time within conflict. GeographicalDownloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

withdrew from southern Somalia; August 2010 when World VisionInternational, the Adventist Development and Relief Agency and Diakonia
withdrew from Somalia; 15 September 2010, when Al-Shabaab ordered
Mercy Corps, Med-Air and Horn Relief to close; May 2013 when Barclays
Bank chose to end its operations in Somalia; and on 14 August 2013, when
Doctors Without Borders withdrew from Somalia. The only one of these
events that corresponds with a changepoint is the WFP withdrawal in
January 2010. However, if this had caused the changepoint, then there
should be a decrease in displacement with the decline in humanitarian aid,rather than the increase in displacement that actually happened.
Fourth, explanations of variation in displacement may need to do more toaccount for the different types of behaviour in pro-rebel and pro-government
actors. Rather than focusing on structural factors, it might be more important to determine whether the conflict actors are feared or supported bycivilians. In this explanation, displacement would be expected to increase
whenever an abusive group that is feared by civilians has success or thegroup that civilians support experiences failure. Relatedly, displacement
would be expected to decrease whenever an abusive group experiences
defeat or when the group with popular support has success. There is some
support for this explanation because displacement has tended to decrease
when Al-Shabaab has lost power, but there is not enough support for it torule out the explanation of this article focusing on structural factors. Further
research with additional cases is needed to assess the effect of the armed
group behaviour on forced displacement.

A Changepoint Model of Forced Displacement

23

Appendix: Timeline of Important Events in Somalia

Date

Event

Changepoint or displacement over 20,000?

January 2008

Burundi becomes second
country to join African
Union (AU) force in Somalia
One of the worst Al-Shabaab
attacks in Puntland to date
Somaliland troops push into
Sanaag region
US missiles hit Somalia; atleast the third American
missile attack since thebeginning of 2007

No

6 February 2008
24 February 2008
3 March 2008

No
No
No

(continued)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

scope can affect displacement by determining the portion of the population
affected by conflict. Changes in balance of power can create security disruptions and fear. Cross-national analyses should now be developed to assess thegeneralizability of these claims. While that is in progress, there are other ways
future research could enrich the theory developed here.
Much of this work involves incorporating spatial factors. Displacement
should be more likely closer to violent events, so modelling this spatialaspect could help detect a relationship within regimes between violence anddisplacement. In addition, there are many in-group, out-group dynamics thatneed to be explored. For example, when an armed group of the same ethnicity or clan as the civilians of a given area captures a town in that area, there
should be low levels of displacement. On the other hand, if an armed groupof a different ethnicity or clan captures the town, then there might be highlevels of displacement. This difference would exist because civilians would
perceive a higher likelihood of being harmed by an armed group of a different ethnicity or clan.
In addition, there is clear evidence that many displaced people actually getdisplaced multiple times. It may actually be a rarity for a person to only bedisplaced once. Further research should address the question of whether
people are more likely to become displaced after already having been
displaced.
As observers monitor the events occurring during conflict, it should now beevident that they should monitor when changes in structural factors occur.
This focus may help improve responses to large floods of displaced persons
when they happen, improving the livelihoods of thousands of innocent
civilians.

24

Justin Schon

Continued
Date

Event

Changepoint or displacement over 20,000?

12 March 2008

Kenya opens border with
Somalia
Al-Shabaab leader Aden
Hashi Farah Ayrow was
killed in a US air strike
Kenya recloses border with
Somalia
Islamic Courts Union takes
key town of Jilib in southern
Somalia
Djibouti Agreement includes
agreement between TFG anda wing of Alliance for theRe-liberation of Somalia(ARS) on ceasefire and othermeasures. This includes
withdrawal of Ethiopian
troopsHeavy fighting in Mogadishu.
Fighting in many otherregions as wellSouth-western town
Daynunay taken by AlShabaab after heavy fighting
Central Somali town ofBeledweyne experiences
heavy fighting when
Islamists attacked Ethiopian
troops there. The Ethiopian
response killed many
civilians
Islamists take control ofKismayo after three days ofheavy fighting
Aid groups kicked out or
threatened, high fatality rates
Al-Shabaab lobs rockets at
Burundian AU troops in
Mogadishu. This is part ofmulti-day offensive on AU
troops in Mogadishu. Many
civilian deaths caused byboth sides lobbing rockets ateach otherNo

1 May 2008

6 May 2008
18 May 2008

28 June 2008

9 July 2008

24 July 2008

22 August 2008

8 October 2008
8–9 November 2008

No
No

No

CHANGEPOINT 1
75,000 displaced on
28 JuneNo

37,000 displaced on 25
July; 39,000 displacedon 26 July

CHANGEPOINT 2

No
26,000 displaced on 11
November(continued)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

9 June 2008

No

A Changepoint Model of Forced Displacement

25

Continued
Date

Event

Changepoint or displacement over 20,000?

14 November 2008

President Yusuf admits
Islamist insurgents control
most of the country, raising
the prospect his government
could completely collapse
Al-Shabaab seizes a town incentral Somalia. Appears to
be part of manoeuvring tocontrol as much of Somalia
as possible when Ethiopians
leave
Ethiopia says it has started
pulling its troops out ofSomaliaNo

6 December 200816 January 200926 January 2009

4 February 2009

May 2009

June 2009

Al-Shabaab attacks Ethiopian
troops. Civilians worried
about the violence
Last Ethiopian soldiers leave.
Fighters from Al-Shabaabmove into Baidoa, capturing
an old granary serving as
Somalia’s parliament
Four insurgent groups,
including the Eritrea-based
faction of ARS but not AlShabaab, announced plans
to merge into a new groupcalled Hizbul Islam (Islamic
party) to fight the newly
elected president and theanticipated unity government
Al-Shabaab highpoint.
Islamist insurgents launch
onslaught on Mogadishu andadvance in the south
President Ahmed declares astate of emergency as violence intensifies. Somali officials appeal to neighbouring
countries to send troops toSomalia, as government
forces continue to battle
Islamist insurgents

CHANGEPOINT 3
84,000 displaced on 27
December; 32,000 displaced on 28
December; 28,000 on
3 January
No

CHANGEPOINT 4

No

CHANGEPOINT 5

No(continued)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

2 January 2009

No

26

Justin Schon

Continued
Date

Event

Changepoint or displacement over 20,000?

20 June 2009

Somalia announces it needs
troops within the next 24hours or its government islikely to fall
Kenya reinforces border
patrols and cuts off crossborder trade with Somalia
TFG-led government
announces reform of security
services and new offensive topacify Mogadishu
Many fighters from Hizbul
Islam defect to join AlShabaab. This comes as asurprise to observers
Fighters defect Union ofIslamic Courts to join Hizbul
Islam
Fighting broke out in
Kismayo for the first time
between the two rebel groups
Al-Shabaab and Hizbul
Islam. Al-Shabaab eventually took Kismayo
Al-Shabaab expands attacks
to Puntland
UN’s World Food Programme(WFP) withdraws from AlShabaab-controlled areas ofsouthern Somalia after
threats to lives of its staff
CNN reports that previous 19
days have seen 63,000 people
displaced due to heavy
fighting in Mogadishu andother areas
al-Shabaab confirmed officially for the first time that it
had joined al-Qaida’s ‘international jihad’
al-Shabaab begins to concentrate troops in preparation
for a major assault to capture MogadishuNo

26 June 200923 July 2009

25 September 2009

October 2009

January 2010
January 2010

1–19 January 201029 January 2010

February 2010

CHANGEPOINT 6

No

No

No

CHANGEPOINT 7
No

CHANGEPOINT 7

No

No(continued)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 201523 August 2009No

A Changepoint Model of Forced Displacement

27

Continued
Date

Event

Changepoint or displacement over 20,000?

15 March 2010

The TFG and Ahlu Suna Wal
Jamma (ASWJ), the progovernment Islamist groupthat controls parts of central
Somalia, formally signed acooperation frameworkagreement in Addis Ababa
Hizbul Islam reportedly claim
loyalty to al-Qaida for the
first time and invite Osamabin Laden to Somalia
Al-Shabaab launches
Ramadan Offensive to try
and take Mogadishu. This
offensive failed. Ramadan in2010 was 11 August until 9
SeptemberWorld Vision International(WVI), the Adventist
Development and Relief
Agency (ADRA) andDiakonia were accused by
Al-Shabaab of propagating
Christianity in Somalia andconsequently forced to stop
their operations
On 15 September 2010, Mercy
Corps, Med-Air and Horn
Relief were ordered to close
by Al-Shabaab Banadiradministration, who accusedthem of having too close ties
with the United States
Hizbul Islam merges with AlShabaab
Kenya closes border toSomalia after nearby fighting
between Al-Shabaab rebels
and government-backed
forces
Al-Shabaab pulls out ofMogadishu and other major
cities in what it calls a ‘tactical move’No

7 April 2010

August 2010

15 September 2010

30 December 2010
February 2011

July and August 2011

CHANGEPOINT 8

No

No

No
No

No

(continued)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

August 2010

No

28

Justin Schon

Continued
Date

Event

Changepoint or displacement over 20,000?

16 October 2011

Kenyan troops enter Somalia
to attack rebels they accuseof being behind several kidnappings of foreigners on
Kenyan soil
Kenyan troops engage in theirfirst direct confrontation
with Al-Shabaab forces
Ethiopian troops re-enter
Somalia
Djibouti joins AMISOMTFG-allied forces, supported
by Ethiopian troops, take
Beledweyne
Al-Shabaab loses Baidoa.
7,500 displaced during thefighting
Fighting on outskirts ofMogadishu. Fighting in
Afgoye corridor as well. AlShabaab loses Afgoye. The
fighting displaces about
60,000–66,000 people to
Mogadishu
Kenyan forces take strategic
town of Afmadow on theway to Kismayo. AlShabaab conducts large
military parade to showcase
strength in Kismayo
Biibi, 75 km from Kismayo,
taken by Kenyan forces.
Kismayo very tense
Hizbul Islam splits with AlShabaab
Al-Shabaab gives a call toarms to defend Kismayo in aradio address
Al-Shabaab surrenders
Kismayo
AU troops take Jowhar without a gunshot

CHANGEPOINT 9

28 October 2011

20 November 201122 February 2012

February 2012

31 May 2012

5 June 2012

September 201217 September 201229 September 2012
9 December 2012

No
No
No

CHANGEPOINTS 10
and 11
CHANGEPOINTS 10
and 11

CHANGEPOINT 12

CHANGEPOINT 12No
No

CHANGEPOINT 13
No(continued)

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 201522 December 201131 December 2011

No

A Changepoint Model of Forced Displacement

29

Continued
Date

Event

Changepoint or displacement over 20,000?

May 2013

Barclays Bank announces
decision to withdraw from
Somalia. This move has
major implications formoney transfer services andremittances for Somalis
Spike in violence with various
attacks by Al-Shabaab,
including on presidential
palace and United Nations
Development Program(UNDP) compound in
Mogadishu
Relative calm for Somalia
after violence at the end ofJune. Still tense and somerecurrent violence though
MSF withdraws from Somalia

No

June 2013

14 August 2013

CHANGEPOINT 14

No

Acknowledgements
I would like to thank Karen Rasler, Lauren MacLean, William Thompson,
Patrick Brandt, Jong Hee Park and the anonymous reviewers at the Journalof Refugee Studies for helpful comments and feedback on the paper.

ADHIKARI, P. (2013) ‘Conflict-Induced Displacement, Understanding the Causes of Flight’.
American Journal of Political Science 57(1): 82–89.
BALL, P. (2000) ‘Policy or Panic?’. AAAS/ Human Rights Data Analysis Group Database ofMigrations in Albania and Kosovo.
BLATTMAN, C. and MIGUEL, E. (2010) ‘Civil War’. Journal of Economic Literature
48(1): 3–57.
BRANDT, P.T. and SANDLER, T. (2010) ‘What Do Transnational Terrorists Target? Has It
Changed? Are We Safer?’. Journal of Conflict Resolution 54(2): 214–236.
CHIB, S. (1995) ‘Marginal Likelihood from the Gibbs Output’. Journal of the American
Statistical Association 90(432): 1313–1321.
CHIB, S. (1998) ‘Estimation and Comparison of Multiple Change-Point Models’. Journal of
Econometrics 86: 221–241.
CLARKE, W. and HERBST, J. (eds). (1997) Learning from Somalia: The Lessons of Armed
Humanitarian Intervention. Boulder: Westview Press.
CZAIKA, M. and KIS-KATOS, K. (2009) ‘Civil Conflict and Displacement: Village-Level
Determinants of Forced Migration in Aceh’. Journal of Peace Research 46(3): 399–418.
DAVENPORT, C. (2010) Media Bias, Perspective, and State Repression: The Black Panther
Party. Cambridge: Cambridge University Press.

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

July 2013

No

30

Justin Schon

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

DAVENPORT, C., MOORE, W. and POE, S. (2003) ‘Sometimes You Just Have to Leave:
Domestic Threats and Forced Migration, 1964–1989’. International Interactions 29: 27–55.
DULIC, T. (2010) ‘Geocoding Bosnian Violence’. Paper presented at the International Studies
Association Annual Convention, New Orleans. February 17–20.
ECK, K. (2012) ‘In Data We Trust? A Comparison of UCDP GED and ACLED Conflict Events
Datasets’. Cooperation and Conflict 47(1): 124–141.
EDWARDS, S. (2009) The Chaos of Forced Migration: A Means of Modeling Complexity for
Humanitarian Ends. Saarbruken, Germany: VDM Verlag.
GLADSTONE, R. and MACFARQUHAR, N. (2012) ‘In One Day, 11,000 Flee Syria as War
and Hardship Worsen’. The New York Times, 9 November, http://www.nytimes.
com/2012/11/10/world/middleeast/syrian-refugee-flow-escalates-sharply.html?_r¼2&.
HARPER, M. (2012) Getting Somalia Wrong? Faith, War and Hope in a Shattered State. New
York: Zed Books Ltd.
HARPVICKEN, K.B. (2009) Social Networks and Migration in Wartime Afghanistan. New York:
Palgrave Macmillan.
HUMAN RIGHTS WATCH (2013a) Hostages of the Gatekeepers: Abuses against InternallyDisplaced in Mogadishu, Somalia. Washington DC: Human Rights Watch.
HUMAN RIGHTS WATCH (2013b) You Are All Terrorists, http://www.hrw.org/reports/
2013/05/29/you-are-all-terrorists.
KAPTEIJNS, L. (2013) Clan Cleansing in Somalia: The Ruinous Legacy of 1991. Philadelphia:
University of Pennsylvania Press.
LEWIS, I. (2008) Understanding Somalia and Somaliland. London: Hurst Publishers Ltd.
LINDLEY, A. (2010) ‘Leaving Mogadishu: Towards a Sociology of Conflict-Related Mobility’.
Journal of Refugee Studies 23(1): 2–22.
LIU, W., LAMANNA, M.A. and MURATA, A. (1979) Transition to Nowhere: Vietnamese
Refugees in America. Nashville: Charter House.
LUBKEMANN, S. (2008) ‘Involuntary Immobility: On a Theoretical Invisibility in Forced
Migration Studies’. Journal of Refugee Studies 21(4): 454–475.
LYALL, J. (2009) ‘Does Indiscriminate Violence Incite Insurgent Attacks? Evidence fromChechnya’. Journal of Conflict Resolution 53(3): 331–362.
MARTIN, A. and QUINN, K. (2007) MCMCpack: Markov Chain Monte Carlo (MCMC)
Package. R package version 0.8–1, http://mcmcpack.wustl.edu.
MARTIN, A., QUINN, K. and PARK, J.H. (2011) ‘MCMCpack: Markov Chain Monte Carlo in
R’. Journal of Statistical Software 42(9): 1–22.
MELANDER, E. and OBERG, M. (2007) ‘The Threat of Violence and Forced Migration:
Geographical Scope Trumps Intensity of Fighting’. Civil Wars 9(2): 156–173.
MELS, C., DERLUYN, I., BROEKAERT, E. and ROSSEEL, Y. (2010) ‘The Psychological
Impact of Forced Displacement and Related Risk Factors on Eastern Congolese
Adolescents Affected by War’. Journal of Child Psychology and Psychiatry 51(10): 1096–1104.
MENKHAUS, K. (2012) ‘No Access’. Global Food Security 1(1): 29–35.
MOORE, W. and SHELLMAN, S. (2004) ‘Fear of Persecution: Forced Migration, 1952–1995’.
The Journal of Conflict Resolution 48(5): 723–745.
MOORE, W. and SHELLMAN, S. (2006) ‘Refugee or Internally Displaced Person? To Where
Should One Flee?’ Comparative Political Studies 39: 599–622.
MOORE, W. and SHELLMAN, S. (2007) ‘Whither Will They Go? A Global Study of Refugees’
Destinations, 1965–1995’. International Studies Quarterly 51(4): 811–834.
RAFTERY, A. and AKMAN, V. (1986) ‘Bayesian Analysis of a Poisson Process with a ChangePoint’. Biometrika 73(1): 85–89.
RALEIGH, C., LINKE, A., HEGRE, H. and KARLSEN, J. (2010) ‘Introducing ACLED—
Armed Conflict Location and Event Data’. Journal of Peace Research 47(5): 1–10.
SCHMEIDL, S. (1997) ‘Exploring the Causes of Forced Migration: A Pooled Time-Series
Analysis, 1971–1990’. Social Science Quarterly 78(2): 284–308.

A Changepoint Model of Forced Displacement

31

Downloaded from http://jrs.oxfordjournals.org/ by guest on April 16, 2015

STEELE, A. (2009) ‘Seeking Safety: Avoiding Displacement and Choosing Destinations in Civil
Wars’. Journal of Peace Research 46(3): 419–429.
STEELE, A. (2011) ‘Electing Displacement: Political Cleansing in Apartado, Colombia’. Journalof Conflict Resolution 55(3): 423–445.
TERRY, F. (2002) Condemned to Repeat? The Paradox of Humanitarian Action. New York:
Cornell University Press.
UMUTESI, M. (2000) Surviving the Slaughter: The Ordeal of a Rwandan Refugee in Zaire.
Madison, WI: The University of Wisconsin Press.
UNITED NATIONS HIGH COMMISSIONER FOR REFUGEES (UNHCR) (2007) UNHCR’s
Population Movement Tracking Initiative—FAQs, http://www.unhcr.org/4a9501239.pdf.
UNMISS (2014) Conflict in South Sudan: A Human Rights Report. Human Rights Division of
UNMISS, http://www.unmiss.unmissions.org/Portals/unmiss/Human%20Rights%20Reports/
UNMISS%20Conflict%20in%20South%20Sudan%20-%20A%20Human%20Rights%
20Report.pdf.
VALENTINO, B., HUTH, P. and BALCH-LINDSAY, D. (2004) ‘‘‘Draining the Sea’’: Mass
Killing and Guerrilla Warfare’. International Organization 58(2): 375–407.
WEINSTEIN, J. (2005) ‘Resources and the Information Problem in Rebel Recruitment’. Journalof Conflict Resolution 49(4): 598–624.
WEINSTEIN, J. (2007) Inside Rebellion: The Politics of Insurgent Violence. New York:
Cambridge University Press.
WILLIAMS, P. (2013) ‘The African Union Mission in Somalia and Civilian Protection
Challenges’. Stability: International Journal of Security and Development 2(2): 39.
WOOD, R., KATHMAN, J.D. and GENT, S.E. (2012) ‘Armed Intervention and Civilian
Victimization in Intrastate Conflicts’. Journal of Peace Research 49(5): 647–660.
ZOLBERG, A., SUHRKE, A. and AGUAYO, S. (1989) Escape from Violence: Conflict and the
Refugee Crisis in the Developing World. New York: Oxford University Press.