combating crime and violent extremism using...

$: Combating Crime and Violent Extremism using …pubdocs.worldbank.org/pubdocs/publicdoc/2016/4/...Forensic economics Crime and public economics The \crime market" Quantity Price D S$
Combating Crime and Violent Extremismusing Forensic Economics

Quy-Toan Do

Policy Research Talk, 18 April 2016http://econ.worldbank.org/policyresearchtalks

Quy-Toan Do Economics of Crime PRT 2016 1 / 38

http://econ.worldbank.org/policyresearchtalks

Forensic economics What is forensic economics?

What is forensic economics

The application of economic tools to the study of crime

Theory: criminals respond to incentives (Becker 1968)

“Supply” of crime/criminals“Demand” for crime = supply of opportunities to commit crime

Empirical investigations of market for crime (Ehrlich 1973)

Identification of supply versus demandPolicy: level of apprehension and punishment


Forensic economics Crime and public economics

The “crime market”

Quantity

PriceD

S

Q̂

S: Incentives to commitcrime

D: Opportunities tocommit crime



Combating crime is a public economics problem

Supply-side intervention:increase [opportunity] cost forcriminals

Quantity

PriceD

S

S’

Q∗Q̂

Demand-side intervention:decrease opportunities tocommit crime

Quantity

Price

D

D’

S

MSC

Q∗Q̂



Measuring demand/supply price elasticity to guide policy

Impact of supply-side policies depend on (i) size of the curve shift,and (ii) slope of the demand curve

Quantity

Price D

D’

SS’

Q̂

P̂

Q̃+

P̃+

Q̃−

P̃−



Three case studies

1 The African elephant poaching crisis

2 Piracy off the coast of Somalia

3 Violent extremists of Daesh


The African elephant poaching crisis The magnitude of the problem

The African elephant poaching crisis



The African elephant poaching crisis

with

Julian Blanc (CITES)

Andrei Levchenko (U Michigan)

Lin Ma (National University Singapore)

Tom Milliken (TRAFFIC)



Poaching

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Africa

14606 carcasses

Est

imat

ed P

IKE

0.0

0.2

0.4

0.6

0.8

1.0

419-650,000 elephants inAfrica (2013)

3-5 million in early 20th

century

2011: estimated 7.4percent of elephantpopulation killed(monitored sites)



Quantity and prices

Price and quantities are two sides of the same coin

Price a necessary variable to estimate price elasticity of poaching

Law enforcement affects poaching through prices



Real elephant ivory prices (1970-2015)3

45

67

Ivory

price (

Chin

a−

HK

G; lo

g)

1970 1980 1990 2000 2010 2020year

CITES trade ban: 1989

Post-ban price growth:14% per annum

Ivory behaves like afinancial asset (store ofvalue)



Supply elasticity: poaching vs. ivory prices

2002

2003

2004

2005

2006

2007

20082009

2010

2011

2012

2013

20142015−

2−

1.5

−1

−.5

Avera

ge p

oachin

g index (

log)

4.5 5 5.5 6 6.5Ivory price (CHina−HKG, log)

Supply price inelastic: Elasticity ≈ .4



What did we learn?

Low supply price elasticity

price needs to drop a lot to bring poaching to sustainable levels

Decentralization of law enforcement and the role of communities

Ability and incentives to enforce lawFinancial benefits conditional on conservation: negative prices


Pirates of Somalia

The pirates of Somalia


Pirates of Somalia

The Pirates of Somalia

with

Jean-Baptiste Blanc (Shekere Ltd)

Aurelien Kruse (World Bank)

Trung Dang Le (Real Time Analytics)

Andrei Levchenko (U Michigan)

Lin Ma (National University Singapore)

Farley Mesko (Sayari Analytics)

Claudia Ruiz (World Bank)

Anja Shortland (King’s College)


Pirates of Somalia Piracy in numbers

Somali piracy 2005 - ?

As of June 2015:

1,099 attacks

216 vessels hijacked

US$338m inransoms

4 years of captivity

Attack and Hijack Locations

AttackedHijacked

Legend



Attacks and hijacks0

50

10

01

50

20

02

50

Num

ber

of A

ttacks

2005 2006 2007 2008 2009 2010 2011 2012

Year

Somalia Indonesia

West Africa Caribbean

Others

.1.1

5.2

.25

.3.3

5

Success R

ate

50

100

150

200

250

Num

ber

of A

ttacks

2005 2006 2007 2008 2009 2010 2011 2012

Year

Number of Attacks Success Rate



Hijacking and ransoms

50

100

150

200

250

Ave

rag

e N

eg

otia

tio

n L

en

gth

(D

ays)

01

23

4

Ave

rag

e R

an

so

m (

Mil.

$)

2005 2006 2007 2008 2009 2010 2011 2012

Year

Average Ransom Average Negotiation Length


Pirates of Somalia Offshore law enforcement

Modelling crime and deterrence on the high seas

Data limitations does not allow earlier methodology:

Alternative: take a modelliterally and choose coefficientsthat best explain:

pace of pirates improvedability

suddenness of attacks/fall

trends in ransom andlengths of captivity, etc.

2006 2007 2008 2009 2010 2011 20120

50

100

150

200

250

Year

Nu

mb

er

of

Att

acks

Data Model

2006 2007 2008 2009 2010 2011 2012−4

−2

0

2

4

6

Year

Ave

rag

e R

an

so

m

Data Model Confidence Interval

2006 2007 2008 2009 2010 2011 20120

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Year

Su

cce

ss R

ate


2006 2007 2008 2009 2010 2011 2012−0.2

0

0.2

0.4

0.6

0.8

Year

Ave

rag

e R

ela

tive

De

lay




Policy counterfactuals

Crime elasticity w.r.t. police

Optimal combination of navies/onboard security

Counterfactual 1:no onboard security

2006 2007 2008 2009 2010 2011 20120

50

100

150

200

250

Year

Num

ber

of A

ttacks

Data Model Counter−factual

Counterfactual 2:no navies

2006 2007 2008 2009 2010 2011 20120

50

100

150

200

250

300

350

Year

Num

ber

of A

ttacks

Data Model Counter−factual



Navies and onboard security guards

Security guards critical to explaincollapse of piracy in 2012

75% of large vessels to be equippedwith armed guards is sufficient

US$50,000 per trip = US$500mannually (or US$10+ bn in NPV)

Significant “pecuniary externality”Ransom totals approx US$50m/year

% Armed Guards

Social Costs MPBMPC


Pirates of Somalia Rebuilding on-shore institutions

Using AIS to locate hijackedvessels

Mooring locations



Implication



And alas...


The violent extremists of Daesh

Daesh – ISIL/ISIS

with

Mohamed Abdel-Jelil (World Bank)

Kimberly Baugh (U of Colorado)

Shanta Devarajan (World Bank)

Chris Elvidge (National Oceanographic and Atmospheric Admin.)

Jamie Hansen Lewis (Brown U)

Jake Shapiro (Princeton U)

Mikhail Zhizhin (NOAA & Russian Space Research Institute)



Daesh – ISIL/ISIS

Islamic State in Iraq and the Levant

Origin in 1999 with Islamic State in Iraq (ISI): part of the Iraqiinsurgency against Western forces

Al-Nusra front in Syria following outbreak of civil war (2011)

Self-proclaimed ISIL/ISIS in April 2013



A short history

Ibrahim Khalil

Al Yarubie

Abu Kamal

Azaz

Al Karama

Al Omari

Masnaa

Aboudiye

Attanf

Homs

Dar'a

Hamah

Idlib

Al-Kut

Samarra

An Najaf

Ba qubah

Al-Hillah

As-Samawah

Al 'Amarah

As Suwayda

Ad Diwaniyah

As-Sulaymaniyah

Mosul

Bayji

Duhok

Dayr az Zawr

Al Mayadin

Abu Kamal

Sa`dah

Basra

An-Nasiriyah

Irbid

ZarqaAzraq

Kirkuk

AleppoAr Raqqah

Karbala'

Ar-Ramadi Al Fallujah

Al-Hasakah

Shadadi

SinjarTall`Afar

Arbil

Aqaba

Latakia

Tartus

Tripoli

Um Qasr

BEIRUT

AMMAN

DAMASCUS

KUWAIT

BAGHDAD

KUWAIT

SYRIANARAB REPUBLIC

I R A Q

LEBANON

West Bank

Gaza

JORDAN

S A U D IA R A B I A

I S L A M I CR E P . O F

I R A N

T U R K E Y

ISRAEL

ARABREP. OFEGYPT

Homs

Dar'a

Hamah

Idlib

Al-Kut

Samarra

An Najaf

Ba qubah

Al-Hillah

As-Samawah

Al 'Amarah

As Suwayda

Ad Diwaniyah

As-Sulaymaniyah

Mosul

Bayji

Duhok

Dayr az Zawr

Al Mayadin

Abu Kamal

Sa`dah

Basra

An-Nasiriyah

Irbid

ZarqaAzraq

Kirkuk

AleppoAr Raqqah

Karbala'

Ar-Ramadi Al Fallujah

Al-Hasakah

Shadadi

SinjarTall`Afar

Arbil

Aqaba

Latakia

Tartus

Tripoli

Um Qasr

BEIRUT

AMMAN

DAMASCUS

KUWAIT

BAGHDAD

KUWAIT

SYRIANARAB REPUBLIC

I R A Q

LEBANON

West Bank

Gaza

JORDAN

S A U D IA R A B I A

I S L A M I CR E P . O F

I R A N

T U R K E Y

ISRAEL

ARABREP. OFEGYPT

Med

iter

rane

an S

ea

Euphrates

Tigris

ThartharLake

HabbānīyahLake

RazzazaLake

Euphrates

40°E 45°E

35°E 40°E 45°E

35°N

30°N

35°N

0 150 300

KILOMETERS

IBRD 42122 | MARCH 2016This map was produced by the Map Design Unit of The World Bank.The boundaries, colors, denominations and any other informationshown on this map do not imply, on the part of The World BankGroup, any judgment on the legal status of any territory, or anyendorsement or acceptance of such boundaries.

GSDPMMap Design Unit

DAESH CONTROLLED FLARES

NON-DAESH CONTROLLED FLARES

MAXIMUM EXPANSION OF DAESHDURING PERIOD OF CONCERN

DAESH TERRITORY BY EARLYSEPTEMBER 2015

MAIN CITIES

NATIONAL CAPITALS

SECONDARY ROADS

PRIMARY ROADS

INTERNATIONAL BOUNDARIES

DAESH STUDY


The violent extremists of Daesh How does Daesh finance itself?

Its financial sustainability

Oil

Smuggling and taxes

Looting and confiscation

Foreign donors

Kidnapping

Leakage of Iraq’s Central Bank foreign reserves


The violent extremists of Daesh How does Daesh finance itself?

Oil revenues: what has been said?


The violent extremists of Daesh Remote sensing

Estimating oil production


The violent extremists of Daesh Remote sensing

The case of Ajil


The violent extremists of Daesh Inference

Pre-war oil production

2015 2014

2013

2012

-20

24

6Lo

g(oi

l out

put)

-1 0 1 2 3 4Log(radiant heat)

95% confidence interval Point estimateIraqi fields Syria total

Beta=0.7999 Linearity test (p-value) = 0.1749 R-squared=0.4809



Daesh oil production



Revenues and production

We estimate an upper-bound of oil production that peaked at 31,000barrels per day in August 2014

Production then fell to a 2015 average of 18,000 barrels per day,yielding an approximate daily revenue of US$454,000



A similar supply/demand dichotomy

Dealing with the jihadistgroup’s finances

Oil is not (has neverbeen) a significant sourceof revenues

Extortion and taxes

External support

Fight radicalization in MENAcountries and beyond

Inclusive institutions andpolicies

Youth employment

Rebuilding the socialcontract


Conclusion What did we learn?

Conclusion

What did we learn?


Conclusion What did we learn?

International crime and violent extremism: thecommonalities

Crime and violent extremism: a labor intensive “sector”

Decentralization of law enforcement: capital/labor substitution andcommunity-driven enforcement

Ability of communities to enforce the lawIncentives for communities to enforce the law

Global spillovers

Mechanisms to solve collective action problemRole of multilateral institutions


Conclusion On Forensic economics

Forensic economics and policy

Unconventional data collection for policy analyses of anunconventional economic activity

3 cases where evidence brings new perspective to policy consensus


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