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The Pirates of Somalia Coastguards of Anarchy

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					    The Pirates of Somalia: Coastguards of Anarchy∗

                                         Sarah Percy
                                   International Relations
                                    University of Oxford

                                     Anja Shortland
                                 Economics and Finance
                                Brunel University and DIW


Abstract

This paper analyses the underlying factors driving piracy off the coast of Somalia and
examines the effectiveness of the international naval anti-piracy mission with respect
to its declared aims. We show that while the navies perform well with respect to their
short-term aims, they failed to contain the escalation of the piracy problem through
2009: pirates have not been deterred from attacking ships in the Gulf of Aden and
have expanded their operations in the Indian Ocean and the Arabian Sea. Evidence
from domestic conditions in Somalia suggests that economic development and greater
stability might in fact aid pirates.


1: Introduction
Piracy off the Horn of Africa has grown substantially in recent years. Data from the
International Maritime Bureau reveals that there were 22 pirate attacks in 2000, rising
to 108 in 2008 and 143 in the first half of 2009.1 The types of incident involving
pirates in the region have ranged from small-scale captures as in the recent capture of
a British couple sailing round the world in their yacht (October 2009),2 to large
attacks with potential implications for international security, as when the Ukrainian
tanker MV Faina was captured along with its cargo of battle tanks, artillery shells and
grenade launchers.3 The estimated additional costs of specialty marine risk insurance
for ships using the Gulf of Aden trade route in 2009 were estimated to be US$
400mn.4 Several shipping companies are diverting vulnerable ships around the Cape
of Good Hope to avoid the Gulf of Aden altogether.5

In November 2008 the European Union mounted its first ever joint naval operation in
response to increasing pirate activity off the coast of Somalia. In addition NATO’s

∗
   We would like to acknowledge the excellent research assistance from Josiah Kaplan, as well as
helpful comments from Tilman Brueck, Jan Fidrmuc, Olaf de Groot, Diego Gambetta, John Hunter and
seminar participants at the DIW Berlin, Oxford and Brunel Universities.
1
   See Diagram 1. The figures include incidents carried out by Somali pirates in the Arabian sea
2
   http://news.bbc.co.uk/1/hi/england/kent/8330406.stm
3
   http://edition.cnn.com/2008/WORLD/africa/12/18/somalia.pirate/index.html#cnnSTCText
4
  http://www.begbies-traynorgroup.com/investigations/news/08-12-
15/surge_in_marine_piracy_likely_to_hit_costs.aspx
5
  http://www.focus.de/politik/deutschland/piraten-reeder-verband-schickt-brandbrief-an-
merkel_aid_350280.html

                                               1
Operation Allied Protector and Operation Allied Provider and Combined Task Force
150, a joint task force led by the United States, are operating in the area. The aims of
the naval intervention are to ensure that vessels of the World Food Programme (WFP)
can deliver food aid to displaced people in Somalia, to protect shipping in the Gulf of
Aden and deter pirates from operating in the region.

In this paper we aim to address three questions: Firstly, how has piracy in Somalia
evolved in recent years and what have been its determinants? We observe a number of
developments in Somali piracy. The number of attacks carried out has risen and the
targets and methods used have changed. Initially men in skiffs armed with machetes
attacked fishing vessels claiming to be “Somali coastguards” letting their victims go
after extracting a “fine”. Pirates then moved on to hijacking cargo ships and yachts for
ransom. Today’s pirates are armed with automatic weapons and operate from so
called “mother-ships”, greatly increasing the potential range of operations. We show
that piracy grows in response to past successful hijacks, probably because ransoms are
used to acquire new equipment and because young men are drawn to the extremely
lucrative opportunities in piracy.

Secondly, we examine to what extent the naval counter-piracy initiatives of the EU
and NATO can be considered successful. We argue that while the navies correctly
highlight their achievements in terms of deterring attacks on specific ships and in
guarding food deliveries these are essentially short term successes.6 We analyse
monthly attack data from 2000-2009 and daily attack data in 2008 and 2009. These
show that disruption events do not appear to have a negative effect on pirate activities
in the long term. We show that, at best, the arrival of naval forces on the scene of an
attempted hijack postpones further pirate activities by a matter of days. In addition
pirates have extended their sphere of operation from the Gulf of Aden where shipping
traffic and naval forces are concentrated into areas that are not easily monitored, such
as the open waters off the coast of Somalia, the Arabian Sea and the Indian Ocean off
the coast of Kenya, Tanzania and the Seychelles. This mirrors classic results from
research on counter-terrorism where the securing of specific facilities diverts terrorists
to soft targets.7

Thirdly, we attempt to answer the question to what extent Somali piracy is linked to
the absence of authoritative government and lack of economic opportunity in Somalia.
If piracy is linked to internal chaos in Somalia it is likely that the exclusively sea-
based naval operations will have limited success as long as Somalia remains a failed
state. Our results suggest that pirates benefit from local improvements in governance,
which can occur even without the presence of an effective central government.8 A
substantial gain in centralized stability might well reduce the incidence of piracy, but
it is likely that short-term gains in local stability could increase pirate attacks. This
result could thus have implications for how state reconstruction in Somalia ought to
proceed.

The paper is structured as follows. Section 2 provides some background material on
Somalia, an overview of how Somali piracy developed over time and how the multi-
lateral naval missions have attempted to resolve the piracy problem. Section 3
6
  http://www.eunavfor.eu/category/press/feed/
7
  Enders and Sandler (2004)
8
  Menkhaus (2007)

                                                2
discusses the data and methodology of the statistical analyses, section 4 provides and
analyses the results. Section 5 concludes.


2: Somalia, Somali Piracy and the Multilateral Naval Missions
2:1 Somalia: a failed state

The United Republic of Somalia was formed from the former British protectorate of
Somaliland and Italian Somalia and became independent in 1960. The first years of its
independence were marred by border disputes with Ethiopia and Kenya and politics
were characterised by fighting among various clans for political supremacy.

From 1969 to 1991 Somalia was governed by Mohammed Said Barre, who replaced
the assassinated elected president Abdi Rashid Ali Shermake after a coup. His corrupt
administration was based on cold-war fuelled foreign aid and “divide-and- rule”
tactics, which generated deep animosities between clans.9 Around 75% of Somalis
belong to the six major clan families: the Darod, Digil, Dir, Hawiye, Isaaq and
Rahanwein. Of these the Darod clan has tended to be the most influential.10 When
Western aid was drastically reduced after 1989, state failure was almost inevitable and
clan battles erupted in 1991. Including the victims of the famine of 1991/92 (caused
by widespread looting and banditry) an estimated quarter of a million Somalis died
and a million fled to other countries during the civil war. 11

The US and UN failed in their missions to restore order and safeguard relief supplies
and ended their engagement in 1994 and 1995 respectively. In the resulting security
vacuum Somali clan families strengthened their hold on political and economic life.
Local polities emerged with Islamic courts backed by clan elders, business people and
Muslim clergy re-establishing the rule of law in many communities. 12 At the central
government level, however, it has proved impossible to find a way to find a way past
the clan divisions and find a formula for power sharing.

Each attempt at building a government of national unity has ended in a narrow
coalition taking power. In August 2000 clan leaders meeting in Djibouti appointed a
transitional national parliament. Its elected president entered Mogadishu in October
2000 and announced the first government since 1991. However, the parliament was
dominated by Mogadishu-based clans and elsewhere the government was not
accepted as a government of national unity. The administration was fiercely opposed
by those clans who had not done well in the distribution of posts as well as factions
that were opposed to central government altogether.13

In October 2004 after two years of fresh peace talks a new transitional federal
government (TFG) was inaugurated in Kenya and managed to meet in Somalia for the
first time in February 2006. This time the TFG excluded the Mogadishu-based clans
which had dominated the previous government and the Islamist groups from positions

9
  Menkhaus (2007a)
10
   Soerensen (2008)
11
   Menkhaus (2007a)
12
   Menkhaus (2007a)
13
   Menkhaus (2007b)

                                          3
of power, reflecting at least partially the preferences of Ethiopian mediators. Islamist
groups immediately began to contest the peace deal. From March to May 2006
fighting erupted between militias loyal to the Union of Islamic Courts (UIC) and the
TFG.

In June 2006 the militias of the UIC took control of Mogadishu and parts of Southern
Somalia. In December 2006 they were driven out of Mogadishu by Ethiopian troops
and troops of the transitional government. However, fighting between insurgents and
Ethiopian and government troops continues into 2009, with Mogadishu seeing the
greatest disruption. All attempts at establishing a government in the capital continue
to be disrupted by fierce gun battles, suicide bombings and political assassinations.
More than 1.5 million people are estimated by the World Food programme to be
internally displaced within Somalia and 2.87 million received food aid in 2009.14


2:2 Somali Pirates
Pirates in Somalia operate in this context of general lawlessness. A low level of
opportunistic and small scale pirate activity has taken place in the Gulf of Aden and
the Red Sea for many years. Geographical opportunity is an important factor in
piracy: attacks are more likely to be successful where geographical features dictate
that international shipping traffic moves close to the shore and is highly concentrated.
Slow boats are easier to board.15 Initially the attacks were based on acts of theft or
extortion and often targeted fishing vessels, which were (illegally) fishing off the
Somali coast. Pirates used small boats (skiffs) and basic weaponry and were therefore
restricted in their operations. They can be repelled by crews taking the initiative
spraying water from fire-hoses and throwing items overboard.16

The collapse of political and civil order in Somalia and the absence of central law
enforcement in the coastal regions meant that pirates could vastly increase the
profitability of their activities by hijacking and holding ships for ransom. Attacks
increased in frequency and audacity. Ships can be held mostly unchallenged by the
authorities in the ports of Eyl, Hobyo and Gharardeere until ransom negotiations are
concluded.17 Increasing returns from piracy appear to have funded technological
improvements, such as small arms, automatic weapons and rocket propelled grenades.
This has raised the stakes for crews who want to resist pirates.

The other main innovation has been the use of motherships from which the small
skiffs (which are still being used for attacks) are launched. The use of motherships
extends the radius of operations well beyond the coastal waters off Somalia. Pirates
can move unnoticed in the shipping lanes until ready to launch an attack and are no
longer confined to harbour during the monsoon season. Motherships are mostly



14
   http://www.wfp.org/countries/somalia
15
   Murphy (2007)
16
   For example the IMB piracy reports provide the following examples: on 13 February 2002, an attack
on the bulk carrier Altair was aborted after the “duty officer … increased speed, zigzagged the ship’s
course and activated fire hoses.” On 24 April 2009 pirates left when the crew of the cargo ship
Boularibank “activated water hydrant and released timber baulks into the sea.
17
   BBC (18/09/2008) Life in Somalia’s Pirate Town http://news.bbc.co.uk/1/hi/7623329.stm

                                                  4
fishing vessels and diving-boats, which are hijacked and used for a period until their
stores run out, the crew is ransomed or the vessel’s use as a mothership is suspected.18

Below we model the drivers of piracy in the Gulf of Aden and off the coast of
Somalia. We build the model on the hypotheses outlined by Murphy (2007), who
stresses that piracy is first and foremost an issue of opportunity and promise of reward
and only secondarily an issue of poverty. We look at opportunity, costs, risks,
resources and poverty as the potential determinants of piracy. We add variables on the
activities of the international naval forces to examine whether they have been able to
significantly change the incentives for pirates by increasing the risks associated with
carrying out acts of piracy.


2:3 The Multilateral Naval Mission

As the Gulf of Aden presents a perfect geographical opportunity for piracy there is a
history of attacks on ships in this area. However, the problem has escalated in recent
years and naval security patrols have been formally operating in the Gulf of Aden and
off the coast of Somalia since August 2008 (diagram 1).

Even before formal security patrols started naval vessels provided occasional
assistance to attacked ships and the navy mounted a small number of rescue
operations of hijacked vessels.19 In response to these rescue operations pirates adapted
their strategies, threatening to kill hostages if attacked and holding at least part of the
crew on land during ransom negotiations to discourage rescue attempts of boats in
Somali harbours. The navies’ focus has therefore shifted to prevention and disruption
, with ever more international naval vessels present in the Gulf of Aden coming from
EU and NATO countries as well as Japan, Russia and China.20

In December 2008 the EU formalised its engagement in the region with operation EU
NAVFOR Atalanta. The three declared aims of the EU NAVFOR are 1) “the
protection of vessels of the World Food Programme (WFP) delivering food aid to
displaced persons in Somalia”, 2) the “protection of vulnerable vessels” transiting
through the area and 3) to “bring an end to acts of piracy and armed robbery” in the
region.21 In what follows we analyse the success of the naval mission with respect to
the three aims above.

Somalia is one of the poorest countries in the world. It has probably the world’s
highest need for food relief relative to the size of its population: out of a total
population of around 10 million Somalis the World Food Programme aims to support
3.64 million people suffering malnutrition because of conflict, displacement and
drought. 90% of the food aid is transported by sea. 22 After attacks on a number of
18
   See for example http://www.eunavfor.eu/2009/11/eu-navfor-assists-indian-dhow-released-by-pirates/
19
   For example: January 2002, September 2003, march 2005 and January 2006. IMB piracy reports
20
   See Appendix 1
21
   “bring an end to acts of piracy and armed robbery” used in the original wording of the Atalanta
mission – see for example: http://www.medicalnewstoday.com/articles/133184.php                    and
http://www.german-info.com/press_shownews.php?pid=1010. However, this seems to have been
amended recently to “deterrence, prevention and repression of acts of piracy and armed robbery off the
Somali coast” http://www.consilium.europa.eu/showPage.aspx?id=1518&lang=en
22
   http://www.wfp.org/countries/somalia

                                                  5
WFP deliveries all captains of large cargo ships bringing in food supplies have
requested protection.23 A naval escort system was implemented in November 2007
and there have been no attacks on WFP transports under escort. The WFP was
therefore able to scale up its operations from delivering 10,000MT of food supplies in
2007 to 35,000MT in 2008 and an estimated 50,000MT in 2009.24 There is therefore
no doubt about the success of the naval mission in this respect.25

To achieve the second aim of protecting vulnerable shipping the naval forces provide
a number of services. The first is advice to ship-owners about security measures to
minimise the risk of attacks such as speed and route of travel, evasive actions and
securing decks, based on detailed analysis of past attacks.26 Secondly, ships are
advised to travel through the Gulf of Aden in a specific transit corridor patrolled by
naval vessels. There are also group transits with naval escorts based on ship speed.27
Finally, ships that come under attack can request assistance from naval vessels;
though there is no guarantee that assistance will be rendered in time to prevent pirates
from boarding. Once pirates have successfully boarded a ship, the naval forces do not
intervene to avoid risking the lives of the crew or endangering the cargo.28 Navies
monitor the progress of hijacked vessel and sometimes render assistance after a vessel
is ransomed.29

The success of the above measures in protecting vulnerable shipping is debatable. On
the one hand the IMB reports 50 attacks abandoned at the arrival of naval ships and
helicopters from January 2008 to June 2009. On the other hand deterrence was not
perfect because there were 251 attacks during this period (143 of these in 2009). 72 of
the 251 attempts resulted in a successful hijacking.

The naval mission’s third aim referred to the long-term goal of deterring Somali
pirates from operating. The measures taken here are the presence of naval vessels to
aid attacked ships, confiscation of pirates’ equipment and boats and the detention and
trial of pirates caught in the act of piracy. Due to the operation of forces from
different nationalities it is difficult to collate data on the number and timing of events
when pirates intercepted, detained and tried. In any case, the effect of detentions and
trials on subsequent acts of piracy is debatable. On the one hand arrested pirates are
prevented from committing acts of piracy, but on the other hand detention followed
by political asylum in a Western country could be an attraction in itself.30 Given the
lack of economic opportunity in Somalia and the potential rewards of pirate activity

23
     For   example   see   http://www.eunavfor.eu/2009/11/eunavfor-warship-louise-marie-protects-wfp/   and
http://www.eunavfor.eu/2009/11/eu-navfor-escorts-amisom-vessel/
24
   http://www.wfp.org/stories/wfp-logistics-somalia-2009
25
   However, there is a question of whether using frigates to escort slow cargo ships to Mogadishu at an
estimated cost of US$300,000 a day is the most cost effective solution or whether private security firms
could provide protection more cheaply.
26
   http://www.mschoa.eu/
27
   http://www.icc-ccs.org/index.php?option=com_content&view=article&id=70&Itemid=58
28
   Ransoms have so far been very much lower than the combined value of cargo and ships. See BBC
(18/09/2008) Life in Somalia’s Pirate Town http://news.bbc.co.uk/1/hi/7623329.stm and Soerensen
(2007)
29
   Released ships are vulnerable to being attacked again as they are low on stores and fuel, run by an
often traumatised crew and slowed down by soiling from long periods in harbour.
30
    Based on interviews with naval officers and risk consultants. Some governments have made
arrangements that pirates will be prosecuted in Kenya to lower the attractiveness of being arrested.
http://www.nytimes.com/2009/04/24/world/africa/24kenya.html

                                                    6
(or arrest!), there is unlikely to be a shortage of recruits to replace any arrested
pirates.31 In any case as the burden of proof required for a conviction is high, most
pirates are released either immediately or after trial.32

The destruction of equipment is likely to have a less ambiguous effect on subsequent
pirate activities. Arms, boats and GPS / telephone equipment are likely to represent a
significant capital outlay for pirate groups. The case is less clear for motherships,
however, which are thought to be hijacked and used for limited periods only. We will
therefore try answering the question to what extent the naval mission was successful
by statistical analysis: can we find evidence that there were fewer attacks because of
naval disruption events or the institution of the transit corridor?33


3: Model, Data and Methodology
We model piracy off the coast of Somalia from January 2002 to June 2009. The
model is loosely based on the “reasons for piracy” outlined by Murphy (2007).34 A
number of the factors are, however, time invariant in Somalia and we therefore focus
on those variables where we see variation over time. Our initial hypotheses are the
following:

     1. Piracy is a function of opportunity: the more shipping traffic there is and the
        easier it is to attack them the higher the number of pirate attacks.
     2. Piracy is a function of risk: piracy will be lower during monsoon seasons and
        when there is greater law enforcement through international naval forces.
     3. Piracy is a function of resources: The more equipment can be funded, the
        higher the incidence of piracy.
     4. Piracy is a function of poverty: If conditions in the Somali economy
        significantly worsen or households are in need of additional resources to make
        specific expenditures, more men may be attracted to piracy.
     5. Piracy is a function of institutions: piracy is an economic activity which
        benefits from (local) political stability and contract enforcement mechanisms.

We test a number of models, taking a general to specific approach to modelling, i.e.
we use a wide set of variables initially and then test down to a specific model by
eliminating insignificant variables. In the results section we report the preferred
specifications as well as commenting on the variables which were eliminated. We use
a number of different geographical and temporal aggregations to shed light on the
connections between piracy and its potential determinants.

Dependent variable:

31
   Somali Pirates living the high life http://news.bbc.co.uk/1/hi/world/africa/7650415.stm
32
   See Times Online November 29, 2009 Navy releases Somali pirates caught red-handed
http://www.timesonline.co.uk/tol/news/world/africa/article6936318.ece. The Combined Maritime
Forces reported on 23 October 2009 that 611 pirates were encountered between 22 August 2008 and 23
October 2009. Of these 358 were immediately released. 242 were turned over for prosecution. Out of
59 trials, 24 resulted in the release of the pirates. Only 11 pirates were killed.
33
   We are lacking data about the timing and scale of arrests, but are working on this.
34
   Legal and jurisdictional weakness, favourable geography, conflict and disorder, under-funded law
enforcement, permissive cultural environment and promise of rewards.

                                                7
The analysis is based on the database published annually by the International
Maritime Bureau (from 1997 to 2008 and quarterly reports for Q1 and Q2 in
2009).The IMB provides narratives on all incidents of piracy reported (voluntarily) by
captains and ship-owners. From the narratives we can distinguish between successful
raids, successful boarding with subsequent rescue and unsuccessful attempts (diagram
2). The latter includes incidents of various degrees of severity ranging from
suspicious (unidentifiable) vessels spotted by radar 35 to actual attempts where shots
were fired and boarding was attempted. The dependent variable is a count of the
number of all the reported incidents in the relevant time period (daily and monthly).

There is a clear time trend in the data with overall piracy around Somalia and Aden
increasing over time and the series also becomes more volatile (diagram 1). There is
no obvious impact from the naval counter-piracy missions building up through 2008
on the total number of incidents. During 2009 incidents off the coast of Somalia
clearly increase, while the pattern in Aden remains comparable to the previous year.

It is, however, likely that the dependent variable is measured inaccurately.
(Attempted) Piracy is often not reported, because it is thought to reflect badly on
shipping companies.36 Additionally, reported incidents of successful boarding may
lead to lengthy forensic investigations during which the ship will be confined to
harbour.37 However, once the naval forces arrived in the Gulf of Aden in recognition
of the piracy problem, the “stigma effect” of reporting piracy was reduced. Indeed the
presence of the Navy makes skippers more likely to report suspicious vessels either to
request help or to help with the counter-piracy effort.38 The massive increase in
reported attempts in 2008 / 2009 is therefore likely to be a combination of a rise in
pirate activity and an increase in reporting.

Monthly analysis
We use the following 4 dependent variables in the monthly analysis
  1) Monthly number of incidents in region (Red Sea, Aden and Somalia)
  2) Monthly number of incidents in Aden
  3) Monthly number of incidents in Somalia
  4) Change in the number of attacks from one month to the next

Short run model
We use the following 2 variables in the daily analysis
   1. Dummy of whether or not an attack occurred on a given day
   2. Ordered variable whether none, one or more than one attack occurred on a
       given day


Methodology


35
   E.g. 13.06.2009 “Two skiffs were detected on radar by the tanker underway. Tanker made evasive
maneuvers, increased speed warned other ships…”
36
   Murphy (2007)
37
   Chalk (2008) reports delays of up to several weeks while police investigations take place
38
   See footnote 35 above: Tuna and dolphin congregate in the pressure wave and other fish mass in the
air-rich wake of large ships passing through fishing grounds. The “suspicious” skiffs following large
vessels may therefore have been either fishing boats or pirate vessels.

                                                 8
The first series of tests looks at the monthly number of incidents of piracy. The
dependent variable is a therefore “count variable”, with just under a third of total
observations being zero observations– i.e. no attack took place. Diagram 3 shows the
distribution of the variable, which is not in the classic shape of count data, due to a
large number of zero observations and some observations with an unusually large
number of events (i.e. the series exhibits zero inflation and over-dispersion compared
to the classic Poisson distribution). It is therefore not clear what the preferred
estimation method should be and we use a series of estimation methods to check the
robustness of our results.

We start with a basic OLS regression. Given our concern about the measurement
error, especially over-reporting in the latter part of the period, we experimented both
with the raw data series and taking natural logs of (1+ events) to compress the
distribution and give less weight to the large observations. Below we report the results
for the series with the logarithmic transformation, which shows a significantly better
fit than the raw data series.

There is a clear time trend in the data with overall piracy around Somalia and Aden
and its volatility increasing over time (diagram 1). We therefore include a lagged
dependent variable in the model and we use robust standard errors to correct for
heteroskedasticity. We check that the residuals do not exhibit a time trend and are
normally distributed. As an additional robustness check we also model the Change in
attacks from one month to the next. This difference variable makes the series
stationary, but the variance of the series increases towards the end. Again, we correct
for this heteroskedasticity problem by using robust standard errors.

Secondly we employ a time series Tobit to take into account that all observations are
positive and a significant proportion are zero. In the censored regression (or Tobit)
model the observed variable takes the form

Yj = max (Yj*, 0)

The latent variable Yj* is only observed when Yj* > 0. Yj*is generated by the classic
linear regression

Yj* = β Xj* + εj

Where Xj* is a vector of regressors and βthe corresponding vector of parameters. If
we assume that the same process governs whether or not there is an attack and how
many attacks occur when there is pirate activity, Tobit analysis is appropriate. Once
again we use both raw data and a logarithmic transformation.

Thirdly we use two estimation methods developed specifically for count data. These
are characterised by a prevalence of zeros and small values of the dependent variable,
which is also clearly discrete. By taking these characteristics into account we are
likely to improve on the linear model. Also, the zero observations are treated as a
discrete choice, which is different from the positive number of decisions an individual




                                           9
makes once he has decided to carry out a specific activity.39 We firstly use the
Poisson regression model, which has been widely used to study such data, using
maximum likelihood. However, its drawback in this context is that it assumes that the
observations are drawn from a Poisson distribution, where the variance equals the
mean. In the actual distribution the mean exceeds the variance. We therefore also use
the negative binomial model for count data as an alternative. This introduces an
additional individual unobserved effect into the conditional mean.

We model three series in the monthly analysis: firstly we model Somali piracy as one
phenomenon. Secondly, we split the series into attacks in the Gulf of Aden and
attacks made in the Indian Ocean off the Somali coast, the Arabian Sea and as far
South as the Seychelles. The reason for this approach is that while all attacks are
presumed to be carried out by Somali pirates we want to check whether the factors
explaining piracy vary between the two regions and whether pirates substitute
between areas in response to naval patrols.


The second set of tests is based on daily Observations of attacks 2008 / 2009: We
analyse daily data for the period of the naval intervention. We analyse the factors
which determine whether or not pirates chose to attack on a given day using logit
analysis, i.e. we construct a model of the probability of an attack occurring on a
specific day based on prevailing circumstances. Given that there are a few (22 /545)
occasions when there is more than one attack in a day we also use an ordered logit to
analyse the three possible outcomes. Again we analyse the total sample and the Gulf
of Aden and the rest of Somali piracy separately. The following section describes the
data.


Independent variables
Opportunity:
   1) Suez shipping: We have collected data from 2000-2009 on the number of
      ships, the cargo tons and the revenues collected through Suez as a proxy for
      the volume and value of shipping passing through the Gulf of Aden.40 More
      ships not only mean more potential targets but crowded shipping lanes force
      ships to slow down, making boarding easier.
   2) Fullmoon and Clearfullmoon: This set of variables is based on the 5 days
      around each full moon during which navigation is easiest.41 For the second
      variable we interacted a dummy of whether or not there was rainfall on the
      Somali coast (Afgoi) with the fullmoon variable to remove full moons during
      which there was likely cloud cover and hence no additional advantage for
      pirates.

Risk


39
   e.g. being a pirate or being a fisherman. Modern pirate activity requires very different equipment
from fishing. Even though captured pirates mostly claim to be innocent fishermen, their captors often
cannot find any evidence of fishing equipment.
40
   it is likely to be less good as a proxy for shipping along the coast of Southern Somalia
41
   Trade Winds: Pirate Moon Party30 September 2009
http://www.tradewinds.no/andalso/article545237.ece

                                                  10
The main risks to pirates in addition to those of being killed or wounded by a resisting
crew (which we assume to be constant) are those of navigating in small vessels in
potentially rough seas and the risk of encountering a naval patrol.42 Because of
endogeneity issues we cannot use the presence of naval forces in the region as an
explanatory variable: the navies are present because of the piracy problem, not the
other way round. The naval forces do not publish consolidated accounts of how many
pirates they have neutralised or arrested and we therefore rely on the IMB for data on
disrupted attacks. We therefore do not have information on arrests which were not
linked to a specific attempt at piracy.43 We use the following variables:
    1) North-East monsoon: We enter a dummy variable for the windy period in
        Aden from January-March. Low visibility due to sandstorms over the desert
        and coastal areas and high swells make it dangerous to navigate in skiffs.
    2) Southwest Monsoon: There is a second monsoon period in Aden from June-
        August. Again, low visibility due to sandstorms over the desert and coastal
        areas and high swells make it dangerous to navigate in skiffs
    3) Disruption: we class a disruption event as one in which a hijack attempt was
        reported to have been interrupted by a naval ship or helicopter arriving on the
        scene. We have not included incidents in which it is clear that the naval forces
        appeared well after the attempt had been abandoned. In the monthly series we
        use a count of the number of disruption events in the month.44
    4) Rescue: A rescue is any incident in which the pirates boarded a ship but the
        ship was then taken over by security forces and the hostages were released
        without ransom. Sometimes pirates were taken prisoner in the process.
    5) Transit corridor: From February 2009 the naval forces advised shipping to
        use a specific corridor through the Gulf of Aden, which is patrolled by naval
        vessels. Ships are given information on when it is best to enter the transit
        corridor and there is also the option of joining convoys based on ship speed.
        However, convoys are not routinely escorted; instead a system of “area
        protection” is used.

Resources and technology
The first two variables broadly capture the amount of resources available for pirate
activity. Unfortunately we have not been able to find data on transfers from the
Somali expatriate community to Somalia, which may or may not have provided
additional funds. The “mothership” (dummy) variable indicates a technological
development which greatly increased the range of pirate attacks.
    1. Lagged dependent variable: This is a proxy for the level of resources
        accumulated in previous periods.
    2. Success: we class as a success any reported incident where the pirates either
        stole property from the ship or (more often) extracted a ransom from the

42
   Risks vary greatly depending on the nationality of the naval vessel encountered. EU NAVFOR
patrols interview suspected pirates (after a medical and a meal) and release them with enough food,
water and fuel to get them home. Pirates are passive on being arrested, minimizing risk of injury. They
only lose the incriminating equipment they throw overboard on being approached, which may or may
not be a significant problem for them on their return home. The Chinese take a more “robust” approach
with suspected pirates and indeed Chinese flagged vessels have a much lower risk of being attacked
(interview with naval officer).
43
   However, criminal proceedings are only possible where pirates are caught in the act, so any
additional events would only be “catch and release” incidents.
44
   In 2008 there were 50 incidents where the arrival of naval forces prevented an attack or where ships
were freed by naval forces. 48 of these incidents occurred in the Gulf of Aden.

                                                  11
        owners. We use several lags of this variable, as ransom negotiations take some
        time to conclude.
     3. Motherships We use a dummy taking the value one from the point when
        “motherships” are first mentioned in an annual IMB report (2005 – the dummy
        takes the value 1 from January 2005). Motherships allow pirates to launch
        piracy attacks further from the coast and perhaps make them less dependent on
        weather conditions.


Poverty
Few specific details are known about the Somali economy. The IMF’s 2009
assessment of Somalia simply states that the Somali government “has not been able to
restore order” and that the “absence of an internationally recognised government and
official information about economic and financial developments precludes a full
assessment…”.45 The CIA Factbook estimates that 65% of GDP comes from
agriculture and fishing. The principal agricultural products are bananas, sorghum,
corn, coconuts, rice, sugarcane, mangoes, sesame seeds, beans; cattle, sheep, goats.46
We therefore use rainfall as a proxy for economic activity, given that much of the
economy is based on agriculture, which is mostly rainwater-fed or based on irrigation
from the Juma and Shabelle Rivers.47
    1. Rainfall: We have records of monthly and daily rainfall for three weather
        stations in central Somalia for the period 1997-2009 (with two minor
        interruptions for one of these weather stations).48 We constructed: average
        rainfall per month, difference from long run monthly average (1997-2008),
        monsoon dummies for average rainfall exceeding 20 for a month, a “missing
        rain” dummy if there is a shortfall of rain compared to the long run average by
        30mm and a “wet” dummy for months in which there was any rainfall.49
    2. Ramadan: Ramadan could have a positive effect on piracy if resources are
        needed to finance the festivities.50 We used the dates of Ramadan for daily
        analysis, for the monthly series we constructed one dummy if there were more
        than 10 Ramadan days in the month and a dummy if there were any Ramadan
        days in the month. A negative effect would be observed if illicit activity was
        shunned during the religious festival.51


Institutions

45
   IMF (2009)
46
    https://www.cia.gov/library/publications/the-world-factbook/geos/so.html There is also a service
sector estimated to produce ca 25% of GDP. It is based around the intermediation of remittances from
Somalis abroad and telecommunications with said community. Lindley (2009) and Seikh and Healy
(2009) provide overviews of this sector, which may also provide finance for pirate activity. We are
currently in the process of sourcing data on remittance flows.
47
   SWALIM Streamflow data are not yet available
48
   Beletweyne, Bulo Burti and Jowhar. Jowwjar data are missing from September to December 2004
and have been estimated based on rainfall in the other stations.
49
   We additionally used the International food price indices from the FAO for cereal, sugar and oil
prices to proxy for import costs, but this was not significant in any of the regressions.
50
   Pirates appear to be able to get credit on the basis of a successful hijack. . See BBC (18/09/2008) Life
in Somalia’s Pirate Town http://news.bbc.co.uk/1/hi/7623329.stm
51
   Attacks could, however, be increased if a high proportion of the target vessels are believed to be
staffed with observant Muslims.

                                                   12
The prevalent opinion is that piracy thrives on lawlessness and disorder.52 It is
doubtlessly true that pirates need safe havens outside the control of the government
and hence with a low probability of security force interventions. However, piracy is
also an economic activity that potentially suffers from disorder, as hostages need to be
fed, kept in reasonable condition and under the pirates’ control for ransoming.
Outbreaks of civil unrest can disrupt food supplies, but perhaps more importantly they
would raise the cost of guarding prey from other groups who could extract ransoms.

Throughout the period under investigation there has not been an effective central
government in Somalia, though there have been variations in the degree of civil
conflict. Unfortunately the data situation on violent conflict in Somalia mirrors that on
economic activity. The PRIO dataset on civil war is extremely vague on the total
number of fatalities in the civil conflict. For example the entries for 1993 and 1994
have lower and upper bounds of 25 and 6000 respectively. There are no data at all
between 1997-2001 and 2003-2005.53 Somalia clearly did not have sufficient security
to allow foreign observers to operate effectively or at all. The only concrete
information we have about civil conflict directly impacting on piracy is during the
brief period during which the UIC replaced the transitional government in Mogadishu
in 2006.54 The UIC took some drastic and highly visible measures against pirates.
Perhaps more importantly they conquered the ports of Hobyo and Gharardeere in late
2006 directly disrupting pirate activity.

As for the business environment, Menkhaus (2003, 2007a) argues persuasively that
absence of government does not necessarily mean absence of governance. After years
of political instability, local governance has emerged based around clans, elders,
businesspeople and mosques. In many areas these structures are strong enough for
people to transact with confidence, as the experience of money transfer companies in
Somalia shows.55

In the absence of concrete information on governance we take an innovative approach
to proxying for violent conflict and the ease of contracting. We use data collected by
the Somalia Water and Land Information management agency (SWALIM).56
SWALIM is funded by development agencies, the EU and the United Nations and is
rebuilding the data collection network for rainfall and river stream-flow data in
Somalia following the civil war. The organisation has attempted to revive the 54 pre-
war weather stations. Data collection simply requires locating a measuring gauge in a
particular way, reading daily data and sending a monthly report in the post.

In the Somali context the well resourced SWALIM must be an exceptionally
attractive employer. However, SWALIM has found it very difficult to reach many of
the old stations and in several cases has had to site stations in alternative locations.
Once a station is under contract, rainfall data are often patchy. Occasionally
contracted stations simply do not submit a report to SWALIM, so that days or whole

52
   Murphy (2007)
53
   Lacina and Gleditsch (2005).
54
   While Mogadishu saw relative stability and an improvement in public order under UIC rule in 2006,
the rest of the country suffered instability as the UIC expanded its range of influence into Southern
Somalia and towards Puntland.
55
   Lindley (2009)
56
   www.faoswalim.org/

                                                 13
months are missing (diagram 4). Apparently this is generally linked to a worsening
security situation – i.e. staff cannot leave their homes or have fled the area because of
territorial disputes.57 Several stations were discontinued after reporting lapsed for a
number of months, which explains the occasional drop in the number of stations
contracted.

We therefore use the following three rough proxies for local conditions in which
(pirate) business is carried out.
    4. Contractual environment: We use the percentage of pre-war stations
        contracted as a proxy for the feasibility of entering into a long-term contract /
        supply relationship and building (very) basic infrastructure.
    5. Civil conflict: We use the number of contracted stations which are not
        reporting rainfall data as a (rough) proxy for the intensity of civil conflict.
    6. UIC dummy: We also use a dummy for the period of the UIC control in
        Mogadishu from June to December 2006.

In Appendix 1 we present OLS results showing the relationship between the three
institutional quality proxies above and a variable which arguably serves as a proxy for
economic activity. The variable is based reported by the Food Security Analysis Unit
in Somalia, which tracks the prices of commodities traded in 18 regional centres in
Somalia.58 Depending on time and location 14, 15 or 16 commodity prices are tracked
on a monthly basis. As with the rainfall data, the price records are very patchy with
trading in specific commodities suspended and entire markets closed over significant
periods. So for each month we counted the number of available prices and divided
this by the total number of prices tracked.

The regressions show clearly that improvements in the contracting environment result
in an increase in trading activity, while instability diminishes the amount of goods on
offer in local markets. The UIC period in addition significantly reduces trading. While
the coefficient on the instability variable is now lower, it is still statistically
significant, indicating that the variables are complementary and not substitutes. We
are therefore reasonably confident that our unconventional proxies allow us to get a
handle on variations in institutional quality and stability in Somalia over time.


4: Results and Discussion
The first thing to note is that despite the difficulty of settling on the most appropriate
estimation strategy the results are extremely robust to the actual methodology
employed. While the coefficients are not directly comparable across the different
methodologies (we are using a log transformation for the OLS and Tobit regressions
and raw data for the Poisson and negative binomial regressions), there is little
variation in which variables are statistically significant. Given our awareness that the
coefficients may be biased we comment mostly on the signs and significance levels in
the discussion below.59


57
   Information reported by SWALIM
58
   http://www.fsausomali.org/
59
   In addition all our variables are measured with error or are imperfect proxies. For this reason it could
be misleading to use the coefficients for forecasting or to make policy conclusions.

                                                    14
4:1 Monthly observations: total incidents

Table 2 about here

The lagged dependent variable (i.e. the number of incidents in the preceding period) is
highly significant and positive in all models. This provides support for the hypothesis
that once groups acquire resources suitable for piracy, they will continue in the
business. There is also some (weak) evidence that a success in the previous month
increases pirate effort (small positive coefficient), but this is generally not significant.
There is, however, robust evidence that a success 4 months ago increases current
piracy levels. This makes perfect sense given that it generally takes around 2 months
to negotiate a ransom and then presumably some time for the new boats / weapons to
arrive. We thus have support for the hypothesis that piracy is a lucrative business,
which attracts new entrants and that profits are reinvested to fund additional
equipment.

Improvements in the contracting environment also appear to benefit pirates (5%
significance, small positive coefficient). This contradicts the common assertion that
pirates thrive on domestic chaos. Instead the suggested interpretation is that pirates
need an infrastructure of some sort to look after hostages, negotiate ransoms and get
their own supplies. Similarly civil strife reduces piracy (significant negative
coefficient). Again this contradicts the hypothesis that pirates benefit from disorder.
Instead it could be argued that with a limited supply of weapons, warlords deploy
their armed men either in piracy activities or in battles of resources on land.
Alternatively in times of disorder more resources might be tied up in guarding the
hostages.

These results are robust to the methodology used, the definition of the dependent
variable (i. e. in OLS / Tobit either the raw data or ln(1+total number)) and the
inclusion of additional, insignificant variables. There is no statistically significant
evidence for seasonal or weather patterns at the monthly level. Similarly we cannot
find any statistically significant effects of any of the naval intervention variables at
the aggregate level.


4:2 Monthly observations: Incidents in the Gulf of Aden

Table 3 about here

The models estimated for Aden underline the importance of resources in driving
piracy: both the past level of piracy and past successes drive current piracy levels.
Again the effect of successes 4 periods ago dominates the immediate effect, giving
credence to Bossasso's police chief, Osman Hassan Uke’s statement: "Whenever 10
guys get paid ransom money, 20 more pirates are created."60 The previous result that
civil conflict disrupts piracy is also backed up, but the indicator for the contracting
environment (or the UIC dummy) is only statistically significant in the count models.
This suggests that the problems with violence are mostly a phenomenon of Southern


60
     quoted in Postcard from Somali pirate capital http://news.bbc.co.uk/1/hi/world/africa/8103585.stm

                                                    15
Somalia.61 Coalition disruption events are on the boarder of statistical significance
(12%) – but with an unexpected positive coefficient. This suggests that pirates who
are driven away from one boat may move on to the next prey, increasing the total
number of attacks. Pirates who are arrested and prosecuted on the other hand may
simply be replaced by new pirate crews, an issue we revisit in the analysis of the open
seas piracy.

We do not find a statistically significant effect of disrupted attacks and the
implementation of the convoy system in the Internationally Recommended Transit
Corridor (IRTC) in the Gulf of Aden on the number of attempted attacks.62 This is a
surprising result, given the emphasis and faith of the international navies in this
particular measure.63 While convoys are not routinely escorted, naval assistance is
generally not far away.

Our interpretation of the result that the IRTC has not deterred pirates from attacking
in the Gulf of Aden is that there are two effects which balance each other. On the one
hand the risk of disruption by naval forces has risen. But on the other hand the
efficiency of pirates in locating suitable targets has improved as ships have been using
the narrow transit corridor rather than picking their own route through the Gulf of
Aden. Pirates in skiffs rely on line-of-sight technology to identify suitable target
vessels, with a radius of around 6nm. In addition they need to keep a low profile and
conserve fuel: i.e. they move relatively slowly. Pirates would therefore spend much of
their tim waiting for a suitable target.64 However, now pirates can use the IRTC to
minimise the search time for their targets, as this is where ships will be concentrated.


4:3 Monthly observations: Incidents in the Indian Ocean and Arabian Sea

Table 4 about here

In the Indian Ocean we again see persistence in pirate activity from one month to the
next. However, in this area we do not have significant effects from past successes.65
Instead we have a positive association between piracy off the coast of Somalia and in
Aden. This suggests that the profitability of piracy in Aden may decline with the
number of boats and additional capacity is deployed off the coast of Somalia. This
backs up the hypothesis that piracy is first and foremost a business. In addition it




61
   Indeed the (unrecognised) “Republic of Somaliland” which declared its independence from Somalia
in 1991 has enjoyed relative stability. In Somaliland SWALIM managed to significantly improve on
the pre-war weather station network, but there is no statistical benefit from splitting the institutional
proxies into Somaliland and rest of Somalia
62
   Model 3 in table 3
63
   Interview with naval commander
64
   Some of the targets then would not turn out to be suitable after all – see for example the attack on the
German naval supply ship Spessart, bristling with armed guards.
http://www.eunavfor.eu/2009/03/seven-pirates-in-custody-after-attacking-eu-vessel/
65
   In some specifications past successes in Aden enter with a positive and borderline significant
coefficient, suggesting that successful pirates invest in additional capacity in the open seas. While the
result is not very robust, it fits in well with the business model of piracy developed here.

                                                    16
suggests that it is ultimately run by a small number of entrepreneurs which control
entry into the most profitable business area.66

Further evidence for this comes from our findings on the effect of the naval
intervention. The number of disruption events, or (alternatively) a dummy for the
presence of EU NAVFOR, are significant and reduce the number of attacks in the
Indian Ocean ceteris paribus. Given that the disruptions primarily take place in Aden
where the international naval forces have congregated this is an unexpected result.67 A
possible explanation is that a significant number of disruptions result in the loss of
piracy equipment and the arrest and detention of pirates. The owners of a diversified
piracy business could be calling in crews from the low profitability area (i.e. the open
seas) and redeploy them in the high profitability area (the Gulf of Aden).68 This ties in
perfectly with the observation above that piracy in Aden (or overall) is not affected by
naval disruption efforts.

Equally interesting is that the institution of the IRTC in February 2009 appears to
have greatly increased piracy in the open waters around Somalia. The most likely
explanation is that there was a significant shift in the relative profitability of the two
locations. If the transit corridor makes piracy in Aden more risky, we would expect to
see a substitution effect: Pirates (like criminals and terrorists) substitute “soft” targets
for the protected prey. This is consistent with the observed positive effect of the IRTC
on piracy in the open seas. The result suggests that the IRTC in the Gulf of Aden may
have had a deterrent effect after all, with some pirates choosing to relocate to the
Somali Basin instead. In the absence of the naval forces the “explosion” of pirate
activity may well have occurred in the Gulf of Aden.

The technological advance of using “motherships” also seems to have made piracy in
this region more feasible. We also get a (less robust) result pirates volunteers are
drawn from the agricultural sector: a severe “missing rain” (which is a predictor of a
failed harvest) increases pirate activity. This result supports the hypothesis that piracy
is to some extent driven by poverty. Finally both increases in civil conflict (non-
reporting stations, but in particular the UIC dummy) have a detrimental effect on
pirate activity in this region.


4:4 Monthly observations: Change in incidents from month to month

Table 5 about here

In the models looking at the change in piracy from one month to the next, the number
of ships through Suez has a positive effect on piracy, but not the value or weight of
cargo. This is consistent with reports of ransom payments which are well below the
value of the cargo and ships. A success in the previous month reduces incidents in the

66
   Individual pirates would ignore the negative externality their presence in Aden confers on other
pirate crews in the area and fail to co-ordinate.
67
   Only 2 of 50 naval interventions in 2008 and the first half of 2009 were reported for the coast of
Somalia
68
   While the types of boats used in Aden are very different from those used in the open seas, there is
good evidence that many pirates do not own their ships but have hired them (possibly with a fisherman
as skipper). In that case it is very easy to redeploy arms and crew.

                                                 17
current period. This may be a sign that pirates are guarding their prey rather than
necessarily handing over to land-based teams. Four months after a successful hijack
pirate activity again increases significantly. Again, the civil disorder proxy has a
negative and significant coefficient and a severe “missing rain” increases the number
of attacks in the month, providing support for the poverty hypothesis. There is no
statistically significant effect of naval disruption or rescue activities.


Daily Observations

Table 6 about here

With the daily observations we can explore the issues of the IRTC more fully. The
IRTC dummy takes the value 1 from 1 February 2009. We see an increase in attacks
in both areas following the IRTC implementation, which is highly statistically
significant. Again we come back to the explanation that shipping traffic in Aden
travelling along a narrow lane improves pirates’ ability to select a target. Some pirates
took advantage of this and were not deterred by the higher probability of being chased
off by naval vessels or arrest with consequent loss of equipment. Others chose to
relocate to the Somali basin instead, raising the overall level of attacks there.

In the short-term models we also observe a clear effect of disruption events. A
disrupted attack today lowers the probability of an attack tomorrow. Pirates who get
away seem to lie low or change position. After an unsuccessful attempt without naval
intervention, however, another attack tends to follow the next day. In addition a
success on the previous day increases the probability of a further attack in Aden. This
could either be an “encouragement effect” (if pirates communicate with each other) or
reflect that successes tend to occur in particularly pirate-friendly conditions.

Pirates are significantly less likely to attack on any given day during the Southwest
and Northeast Monsoon seasons. When we split the sample into Somalia and Aden,
both monsoon seasons matter in Aden, but for Somalia it is only the Southwest
monsoon which matters. As we do not observe this monsoonal pattern in the monthly
figures, presumably pirates do attack on the more clement days within the monsoon
season. With more precise wind-speed data we could probably get better explanatory
power here. In addition clear full moons increase the probability of attacks occurring,
indicating that these nights are indeed preferred by pirates. Finally there appears to be
a higher probability of attacks during Ramadan, possibly indicating a greater need for
resources.69


5: Conclusions

There are a number of clear messages from the data analysis above. Firstly, piracy is a
business. Piracy increased over time as pirates demonstrated the potentially huge
rewards from hijack and ransom. Profits appear to be (at least partially) re-invested
and new people are attracted into the “business”. Given the apparent importance of
successes / ransoms in fuelling piracy perhaps there is a policy implication about not

69
     Or, alternatively, an expectation that ships will be less well defended.

                                                      18
negotiating ransoms or at least keeping them to a minimum. However, as in long as
ransoms remain below the (insured) value of the cargo and hull ship owners are likely
to resist such policies. 70

Secondly, the way in which the naval forces operated until June 2009 did not deter
pirates from operating in the region. Efforts to secure specific shipping lanes have not
reduced the number of attacks in the Gulf of Aden. Instead any deterrent effect seems
to have been offset by an efficiency gain for the pirates, who no longer incur “search
costs”. This does not mean that the policy is ineffective overall: the success rate of
pirate attacks in Aden has been reduced as navies have been better able to assist ships
under attack.71 However, encountering a naval patrol and being caught was not
considered a sufficient deterrent by Somali pirates under the current rules of
engagement.72 It is, of course, possible to make the transit corridor even more
effective if crews were more proactive in holding off pirate attacks. However, it is
common knowledge that passive crews fare better than crews which resisted if the
attack is ultimately successful.73 For crews on short-term contracts who have no
emotional ties to the ship they have been hired to sail on, instructions to risk their
lives in its defence are likely to fall on deaf ears.

Thirdly, the implementation of the IRTC has led to an explosion of the number of
incidents of piracy in the Somali basin. The analogy to “substitution effects” towards
“soft targets” in the terrorism literature appears clear. This vast sea area is nearly
impossible for the world’s navies to patrol. The solution may therefore lie in either
negotiation or in a “land-based” approach, which would deny pirates safe anchorages
in Somalia’s territorial waters.

On balance our evidence suggests that piracy is organised by a relatively small
number of individuals, who decide where to deploy their pirate crews and control
entry into the highly profitable Gulf of Aden. The existence of a “Mr Big” or an
oligopoly may be a positive feature for a negotiated resolution of the problem in
which former pirates are turned into a Somali coastguard (at a price).

Finally, we can link piracy to developments within Somalia. Pirates appear to benefit
from political stability and improved governance, as long as the authority (which may
be fairly local) is tolerant of pirate activity. Partial success with stabilisation might
then be counterproductive, resulting in an improved business environment for pirates.
A “land-based” approach to resolving the piracy problem would therefore need to do
much more than establish a government in Mogadishu: it would need to establish
Western style law and order throughout the country. However, the regions have a
serious incentive to resist such measures. Anecdotal evidence suggests that clan elders
receive a significant proportion of the ransoms.74. In addition, the evidence for links
between poverty and piracy, suggests that any intervention would have to ensure that


70
    Additionally companies need to staff their ships and do not want to be seen abandoning or
endangering their crews.
71
   In 2008 about one in three attempts in Aden was successful, in the first half of 2009 only one in five.
72
   The total number of attacks in the two periods was 89 in all of 2008 compared to 85 in the half year
to June 2009.
73
   Interview with risk analyst
74
   http://news.bbc.co.uk/1/hi/world/africa/8061535.stm

                                                   19
reasonably lucrative alternative occupations are provided for former (and aspiring)
pirates.

Future work in this area will focus on improving the proxies for the naval efforts at
deterring pirates in the long term through arrests and destruction / confiscation of
equipment. There is also some indication that pirates have upgraded their equipment
and are using tracking devices, which would greatly improve their efficiency in the
Somali Basin.75 However, we have not included this in the present analysis, as there is
no information on timing - or indeed any hard evidence for pirates using the
automated transmission system or radar.76 Another fruitful research avenue would be
to analyse the role of the Somali diaspora in financing pirate activity, and their role in
the intermediation / safeguarding of profits arising from piracy. Finally, it may be
possible to predict probability of attack occurring on a given day more precisely with
detailed wind-speed and wave height data.


Bibliography

Chalk, P. (2008) The Maritime Dimension of International Security, RAND
Corporation http://www.rand.org/pubs/monographs/2008/RAND_MG697.pdf
Enders W and Sandler T (2004): What do we know about the substitution effect in
trans-national terrorism? In A Silke (ed); “Researching Terrorism: Trends,
Achievements, Failures” pp 119-137 Frank Cass Ilford
International Maritime Bureau: Piracy and Armed Robbery Against Ships annual
Reports 2000-2008
International Maritime Bureau: Piracy and Armed Robbery Against Ships Quarterly
Reports 2009 Q1 and Q2
INTERNATIONAL MONETARY FUND. Review of the Fund's Strategy on Overdue
Financial Obligations. August 2009
https://www.imf.org/external/np/pp/eng/2009/081809.pdf
Lindley, A (2009): Between Dirty Money and Development Capital: Somali Money
Transfer Infrastructure under Global Scrutiny, African Affairs 108/433 pp 519-539
Menkhaus, K (2003): State Collapse in Somalia: Second Thoughts; Review of African
Political Economy Vol30, # 97 pp405-422
Menkhaus, K (2007a): Governance without Government in Somalia, International
Security vol31 number 3, pp74-106
Menkhaus, K (2007b): The Crisis in Somalia: Tragedy in five Acts, African Affairs
106/204 pp 357-390


75
   The Maritime Security Centre has been advising ships to switch off their AIS when transiting the
Gulf of Aden since April 2009. The annual IMB annual report for 2009 also quotes from an Interpol
report saying that pirates “…managed to extend their range by acquiring tracking devices…” (p44)
76
   The AIS is a transponder system, which broadcasts data relating to one’s ship in a localised area (the
published range is about 20 nautical miles but it can extend to up to 180 nm). The system interfaces
with ships’ radar systems and correlates radar with actual ships positioning data to generate a clear plot
of activity in one’s vicinity. The AIS provides information on name and type of vessel, position, speed
and destination.

                                                   20
Murphy, M. (2004): Contemporary piracy and maritime terrorism: the threat to
international security; ISS Adelphi Paper #388
Seikh H and Healy S (2009): "Somalia's Missing Million: The Somali Diaspora and
its Role in Development", UNDP
http://www.qaranimo.com/2009/nov/undp_report_onSomali_Diaspora.pdf)
Soerensen K. (2008): State Failure on the High Seas – Reviewing Somali Piracy
Swedish Defence Academy OFI report number 2610-SE




                                       21
Diagram 1
                                           Somali Piracy in Aden and Indian Ocean

    40



    35



    30



    25



    20
                                                                                                            Somalia incident
                                                                                                            Aden incidents
    15



    10



     5



     0
         Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M
         n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay-
         00 00 00 01 01 01 02 02 02 03 03 03 04 04 04 05 05 05 06 06 06 07 07 07 08 08 08 09 09




Diagram 2

                                                     Pirate and Naval Successes

    18


    16


    14


    12


    10


                                                                                                              coalition deterrence event
     8
                                                                                                              Success

     6


     4


     2


     0
         Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M Se Ja M
         n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay- p- n- ay-
         00 00 00 01 01 01 02 02 02 03 03 03 04 04 04 05 05 05 06 06 06 07 07 07 08 08 08 09 09




                                                              22
                                 Number of stations
     Ja
       n-
                                                                                                                                                          Density




               0
                   5
                       10
                            15
                                  20
                                              25
                                                             30
                                                                  35
                                                                       40
                                                                            45
                                                                                 50
          0
     M 2                                                                                                                                         0   .1             .2   .3
      ay
        -0




                                                                                                                    Diagram 4
                                                                                                                                                                              Diagram 3


     Se 2
       p-
         0




                                                                                                                                      0
     Ja 2
       n-
          0
     M 3
      ay
        -0
     Se 3
       p-
         0
     Ja 3
       n-
          0
     M 4
      ay
        -0
     Se 4
       p-
         0
     Ja 4
       n-




                                                                                                                                      10
          0
     M 5
      ay
        -0
     Se 5
       p-
         0
     Ja 5
       n-
          0
     M 6
      ay
        -0
     Se 6
       p-
         0




23
     Ja 6
       n-
          0
     M 7




                                                                                                                                       20
      ay
        -0
     Se 7
       p-
         0




                                                                                                                                totalincidents
     Ja 7




                                                                                      Weather Stations in Somalia
       n-
          0
     M 8
      ay
        -0
     Se 8
       p-
         0
     Ja 8
       n-
          0
     M 9
      ay
                                                                                                                                      30

        -0
     Se 9
       p-
          0
     Ja 9
       n-
          10
                                                                                                                                      40




                                       non-reporting
                                       reporting stations
                                       contracted stations
Diagram 5
Number and nationality of Naval forces present off Somalia in June 2009




Source: EU NAVFOR




                                        24
Table 1
Variable Definitions and Sources
Variable Name             Source                               Definition
Incidents                 International Maritime    Bureau     Number of incidents
                          Piracy reports                       reported in relevant
                                                               region
Success                    International Maritime   Bureau     Incidents which result
                           Piracy reports                      in      a      successful
                                                               hijacking      and       no
                                                               subsequent          rescue
                                                               attempt is made
Attempt                    International Maritime   Bureau     Incidents in which the
                           Piracy reports                      crews        successfully
                                                               prevented boarding
Rescue                     International Maritime   Bureau     Hijackings which were
                           Piracy reports                      ended by security or
                                                               naval                force
                                                               interventions
Disruption events          International Maritime   Bureau     Incidents in which
                           Piracy reports                      naval              vessels
                                                               successfully prevented
                                                               boarding
% pre-war          stations SWALIM      Hydromet       data    Number of stations
contracted                  inventory                          under            contract
                                                               compared to pre-war
                                                               total of 52
Non-reporting stations     SWALIM       Regional    rainfall   Number of stations
                           reports                             under contract which
                                                               are not reporting
UIC                        BBC news timeline of Somalia        Dummy from June-
                                                               December 2006
EU NAVFOR                  EU NAVFOR website                   Dummy                 from
                                                               December 2008
Transit Corridor           http://www.mschoa.eu/               Dummy from January
                                                               2009
Motherships                International Maritime   Bureau     Dummy from January
                           Piracy reports                      2005                 when
                                                               motherships are first
                                                               mentioned       in      the
                                                               context of Somalia
Rainy Months               SWALIM       Regional    rainfall   Months during which
                           reports                             there      is     rainfall
                                                               reported in the three
                                                               stations for which data
                                                               (mostly) exists from
                                                               1997
Missing rain               SWALIM       Regional    rainfall   Actual rainfall average
                           reports                             compared to long term
                                                               monthly          average
                                                               (1997-2008). Dummy
                                         25
                                                       for months in which
                                                       rainfall was lower than
                                                       l-t average by more
                                                       than 30mm.
Commodities traded in Food Security Analysis Unit Number                     of
regional centres      Somalia                          commodities for which
                                                       market price data are
                                                       available     /    total
                                                       number                of
                                                       commodities tracked
Clearfullmoon         SWALIM rainfall reports Afgoi    5 days centred on full
                                                       moon interacted with
                                                       dummy of whether or
                                                       not there was rain
                                                       recorded at Afgoi
                                                       weather station.
Suezshipping          http://www.suezcanal.gov.eg/     Number of vessels
                      TRstat.aspx?reportId=1           going through Suez in
                                                       a give month
Ramadan                                                Dates of Ramadan
Northeast monsoon     http://www.nrlmry.navy.mil/      January-March
                      sat_training/world_wind_regimes
                      /GulfOfAden/
                      fall_transition/index.html
Southwest monsoon     http://www.nrlmry.navy.mil/      June-August.
                      sat_training/world_wind_regimes/
                      GulfOfAden/SW_Monsoon
                      /index.html




                                      26
Table 2
Monthly observations: total incidents
The dependent variable is ln(1+ total number of incidents in Aden and Somalia)

                       Model 1:1            Model 1:2           Model 1:3   Model 1.4
Dependent              Ln (1+ incidents)    Ln (1+ incidents)   Raw count   Raw count
variable
# of incidents         0.419***             0.575***            .057***     0.049**
in      previous       (0.094)              (0.146)             (008)       (0.023)
       77
month
Previous               0.075**              0.059               -0.012      0.069
success                (0.031)              (0.052)             (0.022)     (0.073)
Success        4       0.128***             0.129**             0.193***    0.166***
periods ago            (0.043)              (0.059)             (0.022)     (0.052)
%        pre-war       0.007**              0.008*              0.017***    0.014***
stations               (0.003)              (0.004)             (0.003)     (0.005)
contracted
Non-reporting  -0.06**                      -0.068*             -0.118***   -0.081**
stations       (0.029)                      (0.039)             (0.023)     (0.040_
constant       0.397**                      0.086               0.346**     0.260
               (0.169)                      (0.224)             (0.174)     (0.248)
Observations   90                           90                  90          90
R-squared    / 0.604                        0.245               0.507       0.143
pseudo R2
Method         OLS                          Tobit               Poisson     Negative
               Robust SE                                                    Binomial
* denotes significance at the 10% level. ** denotes significance at the 5% level. *** denotes
significance at the 1% level.




77
     lagged ln (1+incidents) in models 1 and 2

                                                    27
Table 3
Monthly observations: Incidents in the Gulf of Aden
The dependent variable is ln(1+ total number of incidents in Aden)

                  Model 1            Model 2          Model 3          Model 4     Model 5
Dependent         Ln           (1+   Ln         (1+   Ln         (1+   Raw count   Raw count
variable          incidents)         incidents)       incidents)
# of incidents    0.353***           0.491***         0.357***         0.080***    0.111***
in     previous   (0.112)            (0.171)          (0.111)          (0.017)     (0.043)
month
Previous          0.104***           0.108*           0.073**          0.048*      0.081
period            (0.035)            (0.060)          (0.342)          (0.027)     (0.093)
successes
Successes 4       0.164***           0.227***         0.128***         0.262***    0.286***
periods ago       (0.040)            (0.072)          (0.039)          (0.030)     (0.073)
Non-reporting     -0.079***          -0.150***                         -0.217***   -0.259***
stations          (0.028)            (0.051)                           (0.034)     (0.065)
%       pre-war   0.003              0.006                             0.014***    0.010*
stations          (0.003)            (0.005)                           (0.004)     (0.006)
contracted
Disruption                                            0.12
events                                                (0.077)
IRTC                                                  -0.318
                                                      (0.319)
constant     0.410***                0.062            0.200***         0.134       0.241
             (0.151)                 (0.270)          (0.066)          (0.229)     (0.309)
Observations 90                      90               110                          90
R-squared / 0.5762                   0.2354           0.589            0.5106      0.1836
pseudo R2
Method       OLS                     Tobit            OLS              Poisson     Negative
             Robust SE                                Robust SE                    Binomial
* denotes significance at the 10% level. ** denotes significance at the 5% level. *** denotes
significance at the 1% level.




                                                28
Table 4
Monthly observations: Incidents in the Indian Ocean and Arabian Sea
The dependent variable is ln(1+ total number of incidents in the Indian Ocean)

                          Model 1          Model 2        Model 3     Model 4

Dependent variable        Ln         (1+   Ln       (1+   Raw count   Raw count
                          incidents)       incidents)
# of incidents       in   0.388***         0.552***       0.085***    0.098***
previous month            (0.082)          (0.143)        (0.022)     (0.035)
Ln (1+Incidents      in   0.191***         0.294**        0.211*      0.236*
Aden)                     (0.083)          (0.119)        (0.122)     (0.147)
Motherships               0.437***         0.659***       1.470***    1.430***
                          (0.132)          (0.199)        (0.229)     (0.259)
Deterrence       events   -0.208***        -0.272**       -0.341***   -0.317***
(lagged)                  (0.047)          (0.090)        (0.087)     (0.109)
Transit corridor          1.431***         1.547***       2.075***    1.773***
                          (0.386)          (0.528)        (0.355)     (0.494)
UIC                       -0.532**         -0.686*        -1.745**    -1.705**
                          (0.168)          (0.398)        (0.722)     (0.754)
Missing rain              0.300            0.352          0.739***    0.741***
                          (0.217)          (0.270)        (0.230)     (0.302)
constant                  0.070            -0.473***      -1.026***   -1.038***
                          (0.061)          (0.151)        0.206)      (0.221)
Observations              113              113            113         113
R-squared / pseudo        0.5495           0.2468         0.4048      0.2019
R2
Method                   OLS             Tobit          Poisson        Negative
                         Robust SE                                      Binomial
* denotes significance at the 10% level. ** denotes significance at the 5% level. *** denotes
significance at the 1% level.




                                               29
Table 5
Monthly observations: Change in incidents from month to month

                   Model 1            Model 2
# ships through    0.004*             0.0034*
Suez               (0.002)            (0.002)
Previous           -0.858***          -0.598
period             (0.267)            0.389)
successes
Successes     4    1.158*             1.306**
periods ago        (0.598)            (0.648)
Non-reporting      -0.343*            -0.341*
stations           (0.188)            (0.187)
Missing rain       2.251*             2.169*
                   (1.200)            (1.190)
Rescue                                0.175
(lagged)                              (0.171)
Disruption                            -0.631
(lagged)                              (0.755)
constant       -4.186                 -3.651
               (2.788)                (2.645)
Observations   90                     90
R-squared    / 0.2438                 0.2652
pseudo R2
Method         OLS                    OLS
               Robust SE              Robust SE
* denotes significance at the 10% level. ** denotes significance at the 5% level. *** denotes
significance at the 1% level.




                                             30
Table 6
The dependent variable is whether or not an attack occurred in Models 1-3 and
whether 0, 1 or more than 1 attacks occurred on a given day in Model 4

                  Model 1            Model 2            Model 3           Model 4
                  Total              Aden               Somalia           Total
Previous day’s                       0.730**
success     (in                      (0.358)
region)
Previous day’s    -1.365***          -0.957**                             -1.128***
Disruption        (0.448)            (0.449)                              (0.406)
Previous day’s    0.875***           0.773***           1.059***          0.719***
attempt           (0.188)            (0.207)            (0.393)           (0.154)
Transit           1.338***           1.049***           1.767***          1.335***
corridor          (0.233)            (0.236)            (0.364)           (0.221)
Northeast         -0.906***          -0.890***                            -0.948**
monsoon           (0.254)            (0.267)                              (0.241)
Southwest         -0.974***          -0.848***          -1.279***         -1.005***
monsoon           (0.299)            (0.308)            (0.623)           (0.291)
Clear      full   0.552*             0.493*             0.729*            0.589**
moon              (0.295)            (0.302)            (0.391)           (0.276)
Ramadan           1.222***           0.891**            1.338**           0.936***
                  (0.411)            (0.412)            (0.581)           (0.373)
constant          -1.208***          -1.211***          -3.309***
                  (0.182)            (0.173)            (0.310)
Cut 1                                                                     1.151
                                                                          (0.177)
Cut 2                                                                     2.558
                                                                          (0.213)
Observations      546                546                546               546
Pseudo R2         0.1617             0.1203             0.1777            0.1224
Method            Logit              Logit              Logit             Ordered logit
denotes significance at the 10% level. ** denotes significance at the 5% level. *** denotes
significance at the 1% level.




                                            31
Appendix 1

Relationship between commodities traded / total commodities tracked in regional
centres and the proxies for institutional quality based on presence / absence of rainfall
data.

                     Commodities        Commodities
                     traded in regional traded in regional
                     centres            centres

% pre-war stations 0.0586***              0.0339***
contracted         (0.0098)               (0.007)

Non-reporting        -0.231**             -0.480**
stations             (0.0965)             (0.199)


UIC period           -4.6387**
                     (2.1922)

constant             14.5191***           15.175***
                     (0.4675)             (0.697)
R-squared            0.354                0.1941
Observations         91                   91


Robust standard errors in parenthesis. * denotes significance at the 10% level. ** denotes
significance at the 5% level. *** denotes significance at the 1% level.




                                           32

				
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