Presentation IFAD-IFPRI Workshop 1-18-12

Decreasing Vulnerability to Conflict in Arab Countries through Rural

Development Clemens Breisinger, Jean-Francois Maystadt, Olivier Ecker, Perrihan Al-Riffai

Development Strategy and Governance DivisionInternational Food Policy Research Institute

IFPRI-IFAD Workshop

International Fund for Agricultural Development, Rome; January 19, 2012

“How is it that countries in the Middle East and North Africa could face explosions of popular grievances despite, in some cases,

sustained high growth and improvement in social indicators?” (World Development Report 2011 on Conflict, Security and Development)

Arab world is the most conflict-affected region in the world

At least six key questions emerge…• Getting the baseline right– Did the social indicators in the Arab world really improve?– Did economic factors play a role in the Arab Awakening at

all?– Which policies and investments can improve those social

indicators, for example food security?• Linking conflict, rural development and food security– Is the Arab world “special” when it come to development

and conflict (Arab Exceptionalism)?– Are there specific links between conflict, rural development

and food security in the Arab world?– How can rural and agricultural interventions be leveraged

for improving the resilience of the rural poor to conflicts?

IFPRI runs two IFAD-supported projects to find answers to these questions

Decreasing vulnerability to conflict through rural development

• Descriptive: Conflict typology & narratives

• Quantitative: – Cross-country– Country-specific, using ACLED

and other geo-referenced data

– Project-level analysis• Fieldwork, Interviews and

Consultations

Workshop Agenda9:00-9:15 Welcoming remarks9:15-10:00 Beyond the Arab Awakening: Policies and investments

for poverty reduction and food security (Clemens Breisinger and Perrihan Al-Riffai)

10:00-10:30 Is there an Arab exceptionalism when it comes to conflict? Preliminary findings from cross-country analysis (Jean-Francois Maystadt)

10:30-11:00 Coffee break11:00-11:30 Atlas for rural development and conflict: An interactive

GIS-based tool for mapping and analysis (Olivier Ecker)11:30-12:00 Climate change and civil war in Somalia: Does drought

fuel conflict through livestock price shocks? (Olivier Ecker)

12:00-12:30 Discussion and ways forward

Social indicators may not have improved to the extend official data suggest

The Arab growth-nutrition puzzle

Source: Breisinger et al. 2011. http://www.ifpri.org/publication/economics-arab-awakening

http://www.ifpri.org/publication/economics-arab-awakening

What is the extend of food insecurity?

Risk of food insecurity (at the macro level)

Source: Breisinger et al. 2012. “Beyond the Arab Awakening.” IFPRI Food Policy Report 25.

Risk of food insecurity (at the micro level)


Risk of food insecurity in Arab world (plus Iran and Turkey)


Economics did play a role in the Arab Awakening

Yemen

Iraq

Sudan

Djibouti

Morocco

Jordan Algeria

Syria

Tunisia Egypt

Mauritania Lebanon

Libya Bahrain

Saudi Arabia

UAE

Kuwait

Qatar

GDP per capita (PPP, current international $)

Source: Based on Gallup World Poll (2011) and WEO (2011) data.Note: Bubble size: Number of dissatisfied people. Color scale: Change in level of dissatisfaction (time period between first and last surveys undertaken in the country; last survey: 2010, first survey: 2005-2009): green: decrease; orange and red: increase, with red: increase at an annual growth rate of at least 2 percentage points.

Percentage of people dissatisfied with their standard of living

Which policies and investments can improve social indicators, food security?

1. ‘Child health production function’: )H = health status, I = health inputs, E = health environment factors, ψ = genetic health endowment of child k

2. Reduced-form child nutrition model: )N = nutritional status, Y = household income

=> Income elasticity wrt. nutritional status: , approx.: 3. Cross-country nutrition model (in first differences):

N = child nutrition situation, Y = national income of country i

4. Decomposition of growth by sectors: η = sector participation component, s = sector share component of sector x (Ag, non-Ag; Ag, Ma, In, Se value added)

5. Regression model (based on time series data):

N = prevalence of child undernutrition, Y = GDP per capita, t = time period, Z = trend effects

***, **, * statistically significant at the 1%, 5%, and 10% level, respectively.

Growth has to become more pro-poor in Arab countries, also in agriculture


Dep. var.: prevalence changein child stunting

Sector VA share (% of GDP)

Total GDP growth Agricultural and non-agricultural growth Sector value added

growth

1 2 3 4 5 6 Growth (per capita) GDP 100.0 -0.11*** -0.11***AgVA 19.4 -0.40*** -0.47*** -0.28** -0.34***Non-AgVA 80.6 -0.07*** -0.07**MaVA 19.9 -0.43*** -0.52***InVA 14.3 0.05 0.10SeVA 46.4 -0.02 0.00

GDP * Arab-TI 100.0 0.04AgVA * Arab-TI 15.3 1.05** 1.32**Non-AgVA * Arab-TI 84.7 0.00MaVA * Arab-TI 13.3 0.00InVA * Arab-TI 25.0 -0.08SeVA Arab-TI 46.4 -0.28

Initial stunting level -0.29*** -0.29*** -0.31*** -0.30*** -0.30*** -0.30 Observations 406 406 402 402 402 402F-value 1.1 1.1 1.2 1.2 1.3 1.4R-squared 0.32 0.32 0.33 0.35 0.36 0.04R-squared adjusted 0.04 0.04 0.06 0.07 0.08 0.11

One reason why agriculture is not as pro-poor in Arab countries is because it’s no longer the

major source of income for the poor

Public spending in Arab countries is high compared to other world regions

Source: based on Breisinger et al. 2012. “Beyond the Arab Awakening.” IFPRI Food Policy Report 25.

But, there is scope for improving the efficiency of public spending, especially in social sectors

***, **, * statistically significant at the 1%, 5%, and 10% level, respectively.


Three focus areas for a food secure Arab world without poverty

• Improve data and capacity for evidence-based decision making

• Foster growth that enhances food security– At macro level– At household level

• Revisit the efficiency and allocation of public spending

Arab countries are heterogeneous and strategies have to be country specific

Conflict, food security, poverty and rural development: What are the linkages?

Is There an Arab Exceptionalism When It Comes to Conflict?

Preliminary Findings from Cross-Country Analysis

Jean-Francois Maystadt, Clemens Breisinger, Jean-Francois Trinh Tan

Presented by

Jean-Francois Maystadt

Outline1. Introduction

2. Conceptual Framework

3. Is there an Arab exceptionalism? Applying the Collier-Hoeffler framework

4. Arab exceptionalism: A puzzle to be explained

5. Preliminary conclusions, discussion and further work

1. Introduction: The costs of conflict

• -2.2% GDP growth/year of conflict (Collier 2007)• 21 years to recover pre-war GDP level (Collier

2007)• ESCWA: -17.5% per capita GDP/year of conflict• ESCWA: Major backwards in MDGs• Micro : Health, education, assets, physical and

political capital, particularly for the most vulnerable (children, women, marginalized, etc)

The Arab World at a crossroad

• “Power vacuum” : Particularly at risk• But no determinism … also opportunities

Major causes of conflicts and which preventive measures?How best to accompany such

political transition?

2. Conceptual framework ‘Motivation’ Grievances, Inequality, Polarization, etc.

‘Opportunity’Opportunity cost to participate to violence depends on alternative sources of income, the potential loss and rewards (therefore capacity for leaders to finance)

‘Polity’Poor governance and lack of political inclusionState capacity to repress or “pay for peace”

Collier and Hoeffler (2004, OEP)

On a sample of 161 countries between 1960 and 2000 ‘Opportunity’ (‘greed’) matters, not ‘Motivation’

(‘grievance’) Per capita income, GDP growth rate, male secondary

education enrolment (-) Population (+), Primary export commodities (+, non-

monotonic) Inequality, political rights, ethnic polarization and

religious fractionalization are not significant (only ethnic dominance)

The role of ‘Polity’ is not investigated and may be a source of bias

3. Arab Exceptionalism?Sorli et al. (2005, JCR) : 1960-2000• Log(GDP per capita), economic growth : <0• Ethnic dominance• No MENA specific effect : “Conflict is quite well

explained by a general model of civil war” (p.160)

Shortcomings:• Sample of 90 countries (excl. e.g. Libya, Somalia, Yemen)• No Fixed Effect (Djankov and Reynal-Querol,

forthcoming REStat)• Predictive power 30% lower compared to SSA

Applying the Collier-Hoeffler framework

Note: Including Collier-Hoeffler non-significant variables , i.e. Primary Commodity Exports , Primary Commodity Exports (squared), Ethnic Fragmentation, Geographical Dispersion

(1) (2) (3) (4)Major Major Major Major

Conflict Conflict Conflict ConflictLog of GDP per capita -0.310*** -0.377*** -0.391*** -0.322***

[0.101] [0.101] [0.118] [0.0962]Log of GDP per capita*MENA 0.087 -0.490*

[0.288] [0.286]MENA 0.826*** -10.35** 2.156

[0.285] [4.998] [2.735]GDP growth -4.314*** -4.591*** -5.652*** -6.326***

[1.412] [1.422] [1.522] [1.466]GDP growth*MENA 6.181** 10.28***

[2.941] [2.992]Cold War 2.807*** 2.843*** 2.695*** 2.825***

[0.386] [0.393] [0.392] [0.393]Ethnic dominance 0.475* 0.397 0.440* 0.495**

[0.254] [0.256] [0.265] [0.203]Log of population 0.443*** 0.466*** 0.412*** 0.496***

[0.0804] [0.0840] [0.0987] [0.0831]Log of population*MENA 0.607*** 0.109

[0.228] [0.166]Observations 3,452 3,452 3,452 4,600

4. Arab exceptionalism: a puzzle Something specific to explain in the Arab world Collier and Hoeffler framework is inadequate Possible explanations?

Omitted variables: institutions inherited from the past, historical grievances, etc (country fixed effects)

Where the growth is coming from? (‘Opportunity’) Agricultural versus non-agricultural growth Youth bulges Better proxy for natural resource dependency (e.g. oil)

Where the growth is going to? (‘Motivation’) Inequality Micro and Macro Food Security Index (FSI)

Political dimension? (‘Polity’)

Main empirical model𝑃 (𝑐𝑜𝑛𝑓𝑙𝑖𝑐𝑡 𝑖 ,𝑡)=𝑐+𝛼𝑖+𝜙𝑡+𝜂 𝑋 𝑖 ,𝑡− 1+𝜑 𝑋 𝑖𝑡 −1∗ 𝐴𝑟𝑎𝑏+𝜀𝑖 ,𝑡

Economic growth is the only robust finding in Collier and Hoeffler (2004)

Arab exceptionalism is confirmed! ‘Opportunity’

Sectoral growth does not matter Youth bulges (share of urban male aged 15-24 over the

urban (or male) population aged 15) : no region-specific effect

Oil, gas, ores and minerals exports to GDP or dependency (>40%) . Oil dependency increases conflict in a non-monotonic way but the effect is totally driven by the Arab world

Main empirical model𝑃 (𝑐𝑜𝑛𝑓𝑙𝑖𝑐𝑡 𝑖 ,𝑡)=𝑐+𝛼𝑖+𝜙𝑡+𝜂 𝑋 𝑖 ,𝑡− 1+𝜑 𝑋 𝑖𝑡 −1∗ 𝐴𝑟𝑎𝑏𝑖+𝜀𝑖 ,𝑡

‘Motivation’ Gini coefficient is uncorrelated to conflicts but known to

poorly capture time-varying sources of grievances Macro and Micro Food Security Indexes significantly

increase the risk of major conflicts in Arab world

‘Polity’ Economic and political discrimination against minorities

increase conflicts but not specifically for Arab countries Past transitions to full democracy and autocracy reduce the

risk of conflicts (using policyIV data, Persson and Tabellini 2006 AER)

Beyond Collier-Hoeffler framework(1) (2) (3a) (3b) (4) (5)

Major Major Major Major Major MajorConflict Conflict Conflict Conflict Conflict Conflict

GDP growth (t-1) -0.120** -0.197*** -0.0722 -0.25 -0.048 -0.0413[0.0516] [0.0660] [0.170] [0.119] [0.0809] [0.0839]

GDP growth*MENA (t-1) 0.265*** 0.727 0.373*** 0.113 0.252[0.079] [0.689] [0.129] [0.219] [0.161]

Child stunting (t-1) 0.000428 0.0000146[0.00143] [0.00141]

Child stunting*MENA 0.0119* 0.0111*[0.007] [0.0068]

Child mortality (t-1) 0.000134[0.0002]

Child Mortality*MENA 0.0008[0.0005]

P-value (0.128)Food security index (t-1) -0.0407

[0.0462]Food security index*MENA 0.412*

[0.216]Time dummies YES YES YES YES YES YESCountry Fixed Effects YES YES YES YES YES YESObservations 4,896 4,896 536 2,616 1,456 2,958Number of ccode 140 140 130 130 139 131

Beyond Collier-Hoeffler framework(6) (7) (8) (9)

Major Major Major MajorConflict Conflict Conflict Conflict

GDP growth (t-1) -0.339** -0.335** -0.116* -0.117*[0.139] [0.143] [0.0623] [0.0621]

GDP growth*MENA (t-1) 0.437*** 0.434** 0.180** 0.117[0.158] [0.175] [0.0791] [0.0958]

Oil rents (t-1) 0.00265[0.00227]

Oil rents*MENA (t-1) -0.00847*[0.00445]

Oil rents squared (t-1) -3.81E-05[3.33e-05]

Oil rents squared*MENA 0.000114**[5.00e-05]

Oil dependency (t-1) -0.00876[0.0298]

Oil dependency*MENA 0.0902*[0.0486]

Pol. Transition to democracy (t-1) -0.00337***[0.00103]

Pol. Transition to democracy*MENA -0.0256***[0.00849]

Pol. Transition to autocracy (t-1) -0.0019[0.00218]

Pol. Transition to autocracy*MENA -0.0189***[0.00637]

Time dummies YES YES YES YESCountry Fixed Effects YES YES YES YESObservations 2,087 2,087 4,452 4,461Number of ccode 73 73 131 131

Further works Robust to non-linear model, Lagging effects? Robust to the implementation of a dynamic model ? Dealing with missing values (unbalanced panel) … Preliminary results from 2SLS-FE model point to the

vulnerability of food net importers to changes in food international prices for food insecurity and in turn, to the risk of conflict

Preliminary conclusions on the main Arab-specific correlates of war

Food insecurity matters for conflicts in the Arab world Transition to democracy is welcomed but the

transition period is risky Oil dependency increases the risk of conflictLimits: Not a paper on the Arab Awakening : only valid for

major conflict events Cross-country analysis misses the heterogeneity (e.g.

the role of environmental factors in Somalia or Sudan)But what could these results mean for particular countries, at a particularly challenging time in history (risky but potentially providing new opportunities)?

Improving food security Avoid fiscally unsustainable and not well targeted

measures (e.g. subsidies) Smart mix of policies, investments and targeted

programs in the areas of trade, agriculture, water, health and education

Economic growth that generates export revenues and benefits the poor and investments in education are key

Country-level analysis and strategies are needed, in the case of Yemen for example a 7-Point action plan has been developed

How to use oil revenues? Oil revenues create fiscal space and should in principle

be wealth enhancing ‘Paying for peace’ has become unsustainable, given

increased repression (e.g. social media) and redistribution costs (e.g. youth and food prices)

But, many Arab countries show “Dutch disease” symptoms, including low economic diversification and governance issues

Oil rents should be directed to pro-poor growth enhancing investments, such as infrastructure and education, and to targeted transfers to the most food insecure populations

Towards a comprehensive spatial database:Atlas for Rural Development and Conflict: An

Interactive GIS-Based Tool for Mapping and Analysis

Jose Funes

Presented by

Olivier Ecker

Spatial Patterns of Rural Development and Conflict (Work in Progress)

1. Regional overview: a. Population & urbanizationb. Infrastructure & market accessc. Economic activityd. Vegetatione. Conflicts

2. Conflicts—National perspective:a. Sudanb. Somalia

Climate Change and Civil War in Somalia: Does Drought Fuel Conflict through Livestock Price Shocks?

Jean-Francois Maystadt, Olivier Ecker, Athur Mabiso

Presented by

Olivier Ecker

Overview

1. Introduction2. Linkages between drought, livestock prices,

and civil conflict in the context of Somalia3. Identification strategy and empirical model4. Empirical results5. Robustness checks and identifying

assumptions6. Conclusions and policy implications

Climate Change and Civil War in Somalia Extreme weather events have become more frequent and

more severe due to climate change (IPCC 2011). Historical data suggest strong linkages between warming and

civil war in Africa (Burke et al. 2009; Hsiang et al. 2011). Economic factors drive civil conflict (Collier & Hoeffler 1998,

2004; Blattman & Miguel 2010). Economic channel (opportunity costs): Expected income from

participating in conflict relative to conventional activities (Miguel et al. 2004; Bruckner & Ciccone 2010; Ciccone 2011)

Do droughts fuel conflict through lowering the opportunity cost for engaging in conflict?

Given that the livestock sector is the mainstay of the economy, are drought-induced shocks on livestock prices the main driver of conflict onsets?

Civil Conflict-Drought Relationship Both droughts and violent civil conflicts have drastically increased

in Somalia in recent years. Evidence indicate that there is also a spatial overlap of (drought-

induced) hunger and poverty and occurrence of violence. Drought (and famine) is a slow-onset and large-area disaster,

affecting large shares of the rural population concurrently. Coping mechanisms are limited because of widespread poverty

and impaired clan support and due to absent public safety nets, lacking credit and insurance markets, etc.

Selling productive assets (particularly livestock) is often the only remaining alternative.

And, engaging in conflict to make an own living at the expense of others may appear opportunistic for some people.

Somalia’s stateless order facilitates self-seeking behavior.

Variation in Conflict Events and Droughts Over Time

63 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9123 6 9121997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

0

20

40

60

80

100

-2

-1.6

-1.2

-0.8

-0.4

0No. of violent conflicts per month Temperature Drought Index (TDI)Conflicts TDI

Conflicts and Drought-Induced Hunger

Source: FEWSNET/FSNAU (2012).Source: Based on ACLED data (2011).

Violent conflicts by province, 1997-2010

Estimated food security conditions, 4/2011

Livestock Prices-Drought Relationship In the case of Somalia, household incomes can be proxied by

changes in livestock prices. The livestock sector is central to the (rural) economy:

About 40% of national GDP Almost 90% of agricultural GDP More than 50% of all export earners Source of food and income for more than 60% of the

population In pastoral livelihoods, 50-80% of the poor’s income

Livestock prices are largely supply driven and thus prone to weather shocks.

During drought, price depression is amplified by market information asymmetry.

Empirical Model (Opportunity Cost Approach)

Reduced-form regression:

with i = province and t = month, year

Two-stage regression (→ prices as channel of transmission):

(1)

(2)

Fixed-effects to control for region-specific factors () and time-varied factors ()

Time trend effects ()

Data and Measurement = no. of conflicts by province and month (from ACLED)

= Temperature Drought Index (from NASA Power; adjusted from Mutua & Zoltan, 2009)

→ Deviation from normal conditions (measures intensity and frequency of drought months and their accumulation over time)

= monthly goat/cattle/camel prices (from FNSAU market statistics), normalized by petroleum prices

Effects of Droughts on Violent Conflicts

No. of conflictsTemperature Drought Index (TDI) 0.969***

(0.289)F-value 2.03***R-squared 0.081Observations 2,340No. of regions 18

Reduced-form regression:

→ More droughts lead to more violent conflicts.

Effects of Droughts on Livestock Prices and Their Effects on Violent Conflicts

First stage Cattle price Goat price Camel priceTemperature Drought Index (TDI) -0.124*** -0.073*** 0.006

(0.035) (0.024) (0.033)Second stage No. of conflictsCattle price -11.13***

(4.984)Goat price -15.69***

(7.460)Camel price 186.9

(996.1)F-value (of the first stage) 5.62*** 5.01*** 6.87***R-squared 0.345 0.258 0.284Underidentification test 13.72*** 9.80*** 0.04Weak identification test 12.81 9.04 0.03Root mean square error 5.725 5.554 59.75Observations 1,289 1,585 1,560No. of regions 17 18 18

Two-stage regression

Livestock Price-Drought and Livestock Price-Conflict (Semi-)Elasticities

Temperature Drought Index (TDI) No. of conflicts

Increase of TDI by one standard deviationCattle price -3.7% 0.58Goat price -6.3% 0.70

Increase of TDI due to an additional drought month associated with a temperature rise of 0.63⁰CCattle price -8.2% 1.28Goat price -13.9% 1.55

IPCC A1B scenario: 1.8-4.3⁰C increase by 2100 Increase in drought months by 3-7 Increase in violent conflicts by 4-7

Robustness of Estimation Results are entirely driven by changes in temperature,

and the TDI is a good measure for identifying droughts. The model is robust to alternative specifications,

controlling for potential effects of time lags and leads, time sensitivity, and seasonality.

Neighborhood effects seem not to matter for conflict onsets (given the available data)

Normalization of livestock prices does not compromise our results.

Validity of Identifying Assumptions Test statistics (F-test, weak instrumental var. test) suggest

that the TDI is a strong instrument of livestock prices. Yet the possibility that droughts affect conflicts through

channels of transmission other than livestock prices (e.g., non-livestock income) cannot be ruled out completely.

However, tests of the validity of the exclusion restrictions do not reveal effects transmitted through other channels.

Possible violation: Effects of food aid on conflict→ Biases into both directions are conceivable.

But previous studies (Dorosh et al. 1995, Kirwan & McMillan 2007, Mabuza et al. 2009) suggest weak links between food aid and market price movements.

Conclusions and Policy Implications Droughts fuel civil conflicts through livestock price shocks in

Somalia. Climate change adaptation strategies contribute to conflict

prevention. Building resilience through establishing effective coping

mechanisms and generating and diversifying income earning opportunities is critical for both conflict prevention and climate change adaptation.

In the shorter run, income support, weather insurance schemes, market interventions, and investments along the livestock value chain can help to mitigate the impacts of droughts.

More research is particularly needed to analyze practical policy options and programs in terms of their effectiveness to strengthen resilience in (semi-)pastoralist livelihoods.

Discussion and Ways Forward

Moderated by

Clemens Breisinger

Next steps• Cross country analysis report• Expansion of case study countries to 5 – Sudan: natural resources and conflict– Lebanon: rural development and IDPs– Yemen: conflict impact and options for transition – Egypt: preventing conflict through subsidies?– Syria:…– Other:…

• ARC Atlas development – inclusion of IFAD data?• Field trips with interviews

Natural resources & conflict in South Kordofan and Sudan

1. How do changes in environmental conditions affect conflict?

Are pastoralist areas more vulnerable to clashes over the use of pasterland among settled communities and agro-pastoralist groups?

How may the development objectives of mechanized farming and local investment lead to tensions with pastoralist communities and rain-fed small farmers?

2. How do massive human and animal displacements affect environmental degradation and in turn, the risk of conflict?

Food policies for conflict prevention: The case of food subsidies in Egypt

Motivation: Food policies may reduce the risk of conflict but with a very high opportunity cost and with possible negative effects in terms of obesity and micronutrient malnutrition

Research Questions:(1) What is the impact of food policies on the risk of

conflict (violence)? (2) Which policies are suitable to reduce conflict, create

inclusive growth, and improve people’s nutrition and overall well-being?

Impacts of Conflict-induced Displacement on Inequality among Refugees and the Hosting Population and Policy

Options for Inclusive Development

Possible study country: Lebanon; refugees: Palestinians, Iraqis (Syrians) Exclusion is critical in terms of economic (e.g., markets, employment,

land), social (e.g., health, education, basic infrastructure), and political aspects.

Grievances occur among the refugee population, between refugees and the hosting population, and among the hosting population living near the camps (partly because of increased competition over resources).

So, what are the impacts of displacement among and within the populations? In particular, what are the effects on economic and social inequality (i.e. potential source of new conflicts)?

What are effective policy options for refugee integration and mutually beneficial development?

Presentation IFAD-IFPRI Workshop 1-18-12

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