Big question in this lecture

(1)

Stockholm Doctoral Course Program in Economics

Development Economics II: Lecture 4

Civil Conflicts

Masayuki Kudamatsu IIES, Stockholm University

(2)

Big question in this lecture

• Why do civil conflicts occur?

• 56% of countries experienced civil conflicts (25+ deaths per annum)

• 20% of countries had 10+ years of civil conflicts

• Source: Armed Conflict Database 1960-2006 (Fig. 1 in Blattman and Miguel 2010)

• Conflicts: detrimental to welfare

• Convincing evidence hard to come by, though

⇐ Pre-conflict micro data hardly available

cf. Blattman and Miguel (2010, section 4)

(3)

Why do civil conflicts occur?

(cont.)

Literature (mainly) proposes the following three reasons:

• Economic factors (sec.1)

• Asymmetric information (sec.2)

• Commitment problem (sec.3)

Also ethnic diversity is often

(4)

1. Economic factors

• Poverty often cited as a cause of civil wars

• Is this true theoretically

• Use a contest model to illustrate

• Is this true empirically?

• Search for exogeneous variation

(5)

1.1 Model

• Players: groups A & B

• Collective action problem: ignored

• Endowment: 1 unit of labor for both

A & B

• Actions: both groups

(6)

1.1 Model (cont.)

Technologies

• Production: group i produces

wi(1 −li)

• li: labor allocated to fighting

• wi: labor productivity for group i

• Fighting: probability of group A

winning given by

(7)

1.1 Model (cont.)

• Victory payoff: V

• Resources unaffected by labor allocation (e.g. natural resource export revenue, foreign aid, etc.)

• Main results: robust to including labor output in victory payoff (see Garfinkel & Skaperdas 2006)

• If no fighting (lA = lB = 0), V is

shared by the two groups according to some exogenous formula

(8)

The contest model has been used in other contexts:

• Rent-seeking (Tullock 1980) • Endogenous property rights

(9)

1.2 Analysis

Peace (lA = lB = 0) cannot be an

equilibrium

⇐ If lj = 0, li = ε > 0 makes group i

(10)

1.2 Analysis (cont.)

• Group A solves

max

l_A

lA lA + lB

V + (1 −lA)wA

• Group B solves

max

l_B

lB

(11)

(12)

1.2 Analysis (cont.)

• Deleting V

(l_A+l_B)2 yields

lA lB

= wB wA

• Less productive group spends more

time in fighting

(13)

1.2 Analysis (cont.)

l_A∗ = wB (wA +wB)2

V

l_B∗ = wA (wA +wB)2

V

Conflict level (l_A∗ + l_B∗ = ₍_w V

A+wB)) ↑ if

• V ↑ (resource curse)

• (wA +wB) ↓ (poverty as a cause of

(14)

1.3 Evidence

Tons of cross-country regressions using

• GDP per capita as a proxy for poverty

• natural resource export as a proxy for V

Endogeneity is a major concern

(15)

Miguel et al. (2004)

• Rainfall as instruments for GDP per capita in African countries

• GDP in Africa depends on rain-fed agriculture

• Find GDP ↓ ⇒ civil conflicts ↑ • But the mechanism is not clear

e.g. GDP↓ ⇒ Govt forces weaker

• Also it’s LATE

(16)

• Also the resource curse channel is not tested

• Recently 3 papers tackle both channels

i. Besley & Persson (2009): use export commodity price as resource effect & import price as poverty effect

ii. Besley & Persson (2011): use UN Security Council membership as resource effect & natural disaster as poverty effect

(17)

• Recently 3 papers tackle both channels

(18)

1.4 Dube & Vargas (2013)

• Use 978 municipality panel data on

conflict incidents from Colombia (1988-2005) (based on newspapers & reports by Catholic priests)

• where civil wars ongoing since 1960s

• 3-way conflict (govt, guerilla, &

paramilitary), but govt & paramilitary collude

• Columbia exports oil & coffee

• Oil price: proxy for V

(19)

1.4 Dube & Vargas (2013) (cont.)

yjrt = λ(OPt ∗ Oilj) +ρ(CPt ∗ Cofj) +_x�_jtρ + αj +βt

+δrt +γ(Cocaj ∗ t) +εjrt

• yjrt: # of guerilla attacks,

paramilitary attacks, clashes, or casualties in municipality j of region

(20)

1.4 Dube & Vargas (2013) (cont.)

yjrt = λ(OPt ∗ Oilj) +ρ(CPt ∗ Cofj)

+x�jtρ + αj +βt

• OPt: int’l price of oil in year t

• Oilj: oil production level in

(21)

1.4 Dube & Vargas (2013) (cont.)

yjrt = λ(OPt ∗ Oilj) +ρ(CPt ∗ Cofj)

+x�jtρ + αj +βt

• CPt: domestic coffee price in year t

• Cofj: hectares of land devoted to

coffee production in municipality m

(22)

(23)

1.4 Dube & Vargas (2013) (cont.)

yjrt = λ(OPt ∗ Oilj) +ρ(CPt ∗ Cofj) +x�jtρ + αj +βt

• _xjt: vector of controls, incl. log population

(24)

1.4 Dube & Vargas (2013) (cont.)

• δrt: region-specific linear trends

• Cocaj ∗ t: linear trends for

(25)

1.4 Dube & Vargas (2013) (cont.)

Theoretical predictions

• λ > 0: resource curse effect

(26)

yjrt = λ(OPt ∗ Oilj) +ρ(CPt ∗ Cofj) +_x�_jtρ + αj +βt

(27)

1.4 Dube & Vargas (2013) (cont.)

• No need to instrument OPt • Int’l price is used

• Columbia produces <1% of world oil production

• No need to instrument Oilj • measured at the 1st year of the

sample

⇒ No endogenous change in response

(28)

1.4 Dube & Vargas (2013) (cont.)

Instrument for CPt

• Int’l coffee price: not suitable

• Columbia is a major coffee exporter

• Log foreign coffee exports from 3 largest producers (Vietnam, Brazil, Indonesia), denoted by FEt

(29)

(30)

1.4 Dube & Vargas (2013) (cont.)

• Need to instrument Cofj

• Measured in 1997, whenCPt peaked

(i) Usually low-production municipalities may produce coffee a lot in 1997 ⇒

Non-classical measurement error

(ii) Municipalities w/ downward pre-1997 trend inεmt

e.g. Govt effort in security

may have started coffee production by 1997, because P_tC �

⇒Spurious corr. btw CPt & yjrt for

(31)

1.4 Dube & Vargas (2013) (cont.)

Instrument for Cofj:

rainfall and temperature at j

⇐ Coffee grows well if

• Tm < 26 (degrees Celcius)

(32)

1.4 Dube & Vargas (2013) (cont.)

⇒ CPt ∗ Cofj is instrumented by: • FEt

• FEt ∗Rj

• FEt ∗Tj

• FEt ∗Rj ∗Tj

Rj : mean annual rainfall in municipalityj

Tj : mean annual temperature in

(33)

First-stage

(page 20)

• Kleibergen-Paap F statistic: 15.94

(34)

Digression: Detecting weak

instruments

• Stock & Yogo (2005) provide critical values of F-statistic or

Cragg-Donald statistic (if # of endogenous variables > 1) for

• Bias in 2SLS is > 10% of bias in OLS (available only for # of instruments ≥

3)

• Actual size of 5% test being less than 10%

(35)

• Stata ivreg2 authors (Baum, Schaffer, Stillman 2007: 489-491) take the i.i.d. assumption seriously, and if you cluster standard errors, it reports Kleibergen-Paap statistics

(36)

1.4 Dube & Vargas (2013) (cont.)

Findings (Tables II, III):

• ρ <ˆ 0 for all types of conflict

• λ >ˆ 0 for paramilitary attacks only • ρ >ˆ 0 if yjrt is agricultural wage

⇒ Evidence for opportunity cost mechanism

• λ >ˆ 0 if yjrt is municipality govt

revenue

⇒ Evidence for resource mechanism

yjrt = λ(OPt ∗Oilj) +ρ(CPt ∗Cofj)

(37)

1.5 Recent studies on

opportunity cost mechanism

• Jia (2012): Sweet potato mitigated

the impact of droughts on peasant revolts in China (1470-1900)

• Bueno de Mesquita (2013):

(38)

1.6 Limitation of the contest

model

• Fighting is always an equilibrium • Does not distinguish arming from

fighting

• By setting s = l_A∗/(l_A∗ + l_B∗), both parties should prefer peace

⇒ Need for other explanations for

(39)

2. Asymmetric information

War breaks out if

• you overestimate your strength

• you underestimate the opponent’s strength

(40)

2.1 Model (Fearon 1995)

• V: Pie to share or fight over

• Actions:

• A proposesV −x as transfer to B

• B then decides whether to accept V −x or go to war

• p: Probability of group A winning if war breaks out

• cA,cB: Cost of war for A & B,

(41)

2.1 Model (cont.)

Payoffs {uA,uB}:

• If B accepts A’s offer, {x,V − x}

• If B fights, {pV − cA,(1 − p)V − cB}

With complete info., peace achieved by

(42)

2.2 Analysis

• Suppose A does not know cB: only

knows its distribution F(cB)

• B accepts peace if

V − x ≥ (1 −p)V − cB

⇐⇒ cB ≥ x − pV

• A solves

max

(43)

FOC (assuming interior solution)

1 − F(K)

f(K) = K + cA

where K ≡ x − pV

• RHS: increases w/ K

• LHS: decreases w/ K if F yields the monotone increasing hazard rate.

⇒ Unique K satisfying FOC

⇒ War breaks out w/ prob. F(K)

(44)

2.3 Limitation

• Information story may explain the onset of a war

• But both parties should learn about each other over time

⇒ cannot explain a long-lasting war

(45)

3. Commitment

• In the previous model, peace is achieved w/ complete info.

• This, however, assumes group A’s

ability to commit to x

• If A’s winning probability goes up tomorrow, it will renege on the promise

(46)

3.1 Model (Powell 2006)

• 2-period model

• V: Pie to share or fight over in each period

• If war breaks out in period t:

• A wins w/ prob. pt

• Fraction(1−d) of V: destroyed forever

• The loser eliminated forever (payoff 0)

(47)

Each period t

1. A proposes a transfer schedule

{s_τ}2_τ₌_t to B

2. B decides whether to accept or to go to war

(48)

3.2 Analysis

In period 2:

• A’s payoff from war: p2(1 −d)V

⇒ Credible s2 must be at most

(1 −p2(1 − d))V In period 1:

• A’s maximum credible concession to avoid war:

s1 = V

(49)

• B’s payoff from war

(1 − p1)(1 − d)(1 +δ)V

⇒ War cannot be avoided in period 1 if

(1 − p1)(1 − d)(1 +δ)V

> [1 +δ(1 − p2(1 −d))]V

(50)

3.3 Intuition

• Key: large shifts in future

distribution of power (p2 >> p1)

• Party whose power will increase cannot commit to a large transfer in future

• They’d rather fight otherwise

• Opponent then prefers a

(51)

3.4 Evidence

Yet to come

• How to measure future shifts in

(52)

3.5 Implications on political

institutions

• Acemoglu & Robinson (2000, 2001, 2006): model democratization as commitment device to future transfer

• Bruckner & Ciccone (2011): rainfall shock led to democratization in Africa

(1980-2004)

(53)

4. Other explanations of war

• Leader bias (Jackson and Morelli 2007)

• Jones & Olken (2009) for evidence that leaders matter

• Grievances (key to solve collective

action problem?)

(54)

5. Ethnic diversity

• Viewed as the leading source of civil conflict (& govt failure)

• Is this empirically true? (sec. 5.1

-5.3)

• What’s the theoretical rationale? (sec. 5.4-5.5)

(55)

5.1 Measurement

• Ethnic diversity often measured by the prob. that 2 randomly chosen individuals in a country belong to different ethnic groups

(56)

5.1 Measurement (cont.)

• This measure has become popular

among economists because of its presumed exogeneity

• Political scientists do not agree, though. (e.g. Posner 2004)

• Michalopoulos (2012) provides evidence against exogeneity

• Found to be negatively correlated w/ govt & economic performances

cf. Easterly & Levine (1997), La Porta et al. (1999), Alesina et al. (2003)

(57)

5.1 Measurement (cont.)

• But no robust association w/ civil

conflicts

cf. Collier & Hoeffler (1998), Fearon and Laitin (2003)

• But is this the correct measure of

ethnic diversity to predict conflict?

• This measure: highest if many ethnic groups of equal size

(58)

5.2 Polarization

Esteban & Ray (1994) derive an index of polarization from two ideas:

1. Identity (how many people you are identified with) ↑ ⇒ Conflict ↑

(59)

5.2 Polarization (cont.)

• Polarization index:

K

• K > 0: constant for normalizing index

(60)

Property 1: Polarization ↑ if

π_i

π_j π_k

0 _ν_ij _νik

(61)

π_i

π_j

π_k

0 _ν_ij _νik

π_i > π_k

(62)

π_i

π_j

π_k

0 _ν_ij _νik

(63)

5.3 Montalvo & Reynal-Querol

(2005)

• Adopt this polarization index into ethnic conflict by setting

• νij = 1,∀i,j (distance between any

two ethnic groups: same)

• _α ₌ 1 (perhaps for simplicity)

(64)

5.3 Montalvo & Reynal-Querol

(2005) (cont.)

• In pooled sample of country by

5-year-period (1960-1999): Ethnic polarization ↑

(65)

5.4 Esteban & Ray (2011)

• Provide a theory that links

fractionalization and polarization indices to conflict

• Theory also tells when which

measure is more important to predict conflict

(66)

5.4.1 Model: Players

• N agents

• m groups of agents

• Size of group i: Ni (⇒ �_i Ni = N)

• Denote group i’s population share

(67)

5.4.1 Model: Actions

• Agent k of group i expends effort

(68)

• R is our measure of conflict

(69)

5.4.1 Model: Public good

• Winning group spends fraction λ

(fixed) of the budget to produce the public good they prefer

• Group i’s payoff from public good is

λuii if they win

λuij if groupj �= i wins

• δij ≡ uii − uij: “distance” between i

(70)

5.4.1 Model: Private goods

• Fraction 1 − λ of the budget will be shared equally by winning group members to produce private goods

• Group i member’s payoff is: (1−λ)N/Ni if group i wins

(71)

5.4.1 Model: Payoff

• Each individual’s payoff is therefore:

πi(k) = pi

• We assume player k ∈ i maximizes:

(72)

• α is an extent of altruism to other

fellow members of the same group

• α can also be the bargaining power of the group leader who maximizes �

l∈i πi(l)

(73)

(74)

(75)

max

• Rewrite this term by using

(76)

σi�pi1 − λ

(77)

So agent k of group i’s maximization

Now we have

(78)

Therefore, the FOC is

σi R

�

j�=i

pj∆ij = c�(ri(k))

where ∆ij ≡ λδij + 1−_nλ

i for j �= i

• LHS is the same for all k ∈ i

(79)

5.4.3 Linking conflict to

population distribution indices

σi R

�

j�=i

pj∆ij = c�(ri)

Now we transform this FOC

under the assumption of pi = ni, to derive per capita conflict intensity

(80)

(81)

σi R

�

j�=i

nj∆ij = c�(ρ)

Now multiply both sides by ρni and sum

(82)

�

i σi N

�

j�=i

ninj∆ij = ρc�(ρ)

• RHS: Monotonically increases with per capita conflict intensity ρ

(83)

(84)

�

i

�

j�=i

ninj[(1 − α) + αNi][λδij + (1 −λ)/ni]

N

• Polarization: �_i �_j_�₌_i n_i2njδij

(85)

�

i

�

j�=i

ninj[(1 − α) + αNi][λδij + (1 −λ)/ni]

N

• Fractionalization: �

i

�

j�=i ninj

(86)

In summary, conflict increases with

(1 − α)λ

N G + α[λP + (1 − λ)F]

• If α > 0 (altruism to other members

of the same group), P & F matter

(87)

5.5 Esteban, Mayoral, & Ray

(2012)

• Estimate this equation with cross-country data

• To measure δij, use linguistic

distances on language trees

(88)

• To measure λ by country, use

PUB ∗ GDP PUB ∗ GDP + OIL

• PUB: degree of un-democraticness of

government

• OIL: per capita value of oil reserves

(89)

• To measure α by country, use World Value Surveys in which

respondents answer to the questions on:

• Adherence to social norms

• Identification to local community

(90)

• Then estimate

ρc =βPαcλcPc + βFαc(1 − λc)Fc

+βGλc(1 − αc)Gc/Nc + x�cκ+ εc

• Results: βP & βF positive and

significant

(91)

• For the onset of conflict,

polarization does correlate, but fractionalization does not robustly (Table 6)

• But Esteban and Ray (2011) use the contest model, which has no

predictive power on the initiation of conflict

(92)

5.6 Esteban & Ray (2008)

• Why is ethnic conflict more prevalent than class conflict?

• Many conflicts these days are ethnic in nature

• Show higher income inequality

increases the likelihood of ethnic conflict

(93)

Model: Players

1. ph: Poor ethnic majority

2. rh: Rich ethnic majority

3. pm: Poor ethnic minority

4. rm: Rich ethnic minority

e.g h: Hindu, m: Muslim in India

(94)

Model: Demography & Endowment

• nij: Population share of class i of

ethnicity j

• np ≡ nph+npm

• nr ≡ nrh +nrm

• nh ≡ nph+nrh > nm ≡ npm+ nrm

• Per-capita income

• Rich yr

• Poor yp(< yr)

• nrh/nh = nrm/nm

⇒ Same per-capita income for each

(95)

Model: Public goods

• C: class budget

• used for funding class public good

• health care

• education

• infrastructure

• E: ethnic budget

• used for funding ethnic public good

• religious festivals

• temples

(96)

Model: Group

ij

’s Payoff

• If peace is achieved,

u(yi) + siC + sjE

• i ∈ {r,p},j ∈ {h,m}

• si ∈ [0,1]: class i’s share of class

budget in peace time

• sj ∈ [0,1]: ethnicity j’s share of

(97)

Model: Group

ij

’s Payoff (cont.)

• If class alliances form,

u(yi −

wiAi ni ) +

Ai

Ap + ArC +sjE

• Ai: # of activists financed by class i

• wi: compensation for each activist

in class alliance i

(98)

Model: Group

ij

’s Payoff (cont.)

• If ethnic alliances form

u(yi −

wjAij

nij ) + siC +

Aj

Ah + AmE

• Aij: # of activists financed by class i

in ethnic alliance j

• Aj ≡ Aij + A(−i)j

(99)

• Notice: in ethnic alliances,

compensation is shared equally within each class of an ethnic group

⇐ Otherwise, forming an ethnic alliance involves regressive redistribution, which is unlikely

• Utility cost of being an activist: fully compensated by wi or wj ⇒ Doesn’t

(100)

Model: Timing of events

1. Players form alliances.

• Randomly chosen player: either proposes (i) class alliance, (ii) ethnic alliance, or (iii) peace

• If an alliance proposed, the other player in the proposed alliance decides whether to accept or reject

e.g. Ifrhproposes class (ethnic) alliance, thenrm (ph) responds

• If accepted, move to stage 2 (ie. conflict).

(101)

Model: Timing of events (cont.)

1. Players form alliances (cont.)

• If all the 4 players propose peace or if proposals rejected endlessly, peace payoffs realize

• Assumption D:

• Players reject or never make a proposal yielding the worst possible payoff

ie. Delaying such a proposal so the worst payoff is discounted

(102)

Model: Timing of events (cont.)

2a. If class alliances are formed, each alliance simultaneously chooses Ak (k = {p,r})

⇐ There’s no asymmetry between h & m in terms of payoffs.

2b. If ethnic alliances are formed, each class in each alliance simultaneously chooses Aik

(103)

Analysis: how to proceed

1. Prove that, under Propositions 2-5, ethnic conflict is unique outcome of the game (Proposition 6)

2. Check if a higher income inequality makes propositions 2-5 more likely to hold

(104)

Preference conditions for ethnic

conflict to be unique outcome

P2. ph: ethnic � class

P3. If ph: class � peace

⇒ rh: ethnic � class

P4. r: peace � class

P5. p: class � peace

(105)

Peace won’t be an eq. outcome

• Suppose otherwise

• ph prefer proposing class

• By P5, ph: class �peace

• pm accepts this proposal

• ph: ethnic �peace (by P2, P5)

⇒σh > sh ⇒σm < sm

⇒pm: peace � ethnic

⇒pm’s best outcome: class (by P5)

⇒Accepts immediately (by D)

(106)

Class won’t be an eq. outcome

• Suppose otherwise

• r never initiate class conflict

• rh: ethnic � class (by P5 & P3)

⇒rh’s worst outcome: class (by P4)

⇒rh never proposes/accepts class (by D)

• ph prefers proposing ethnic

• ph: ethnic �class (by P2)

• rh accepts this proposal

• Peace won’t be an eq. outcome

• rh: ethnic � class (by P5 & P3)

(107)

Intuition

• Poor ethnic majority: want ethnic

conflict (P2)

• Issue: whether rich ethnic majority accept this even when rich prefer peace the most

• When poor can credibly threaten rich with class conflict (1st part of the proof), peace no longer possible

(108)

Propositions 2-5

• Paper shows P2-P5 hold under

reasonable set of parameter values

• Here we focus on why

within-ethnicity inequality helps satisfying P2

• Proposition 1a: specifies condition for conflict � peace

• Proposition 1b: specifies condition

(109)

Proposition 1a

• Assume that contributions x are small relative to income yi.

ie. u(yi)−u(yi −x) ≈ u�(yi −x)x

• Then class i in alliance k prefers conflict to peace iff

λikσ_k2 + (1 −λik)σk > sk

• λik ≡ Aik/Ak

• σk ≡ Ak/(Ak +Al)

(110)

Proposition 1a: Intuition

• λik = 1 if k is class alliance

• Then the condition boils down to

σ_k2 > sk

(111)

Proposition 1a: Intuition (cont.)

• λik = 0 if class i in ethnic alliance k

does not contribute

• Then the condition boils down to

σk > sk

• Conflict should increase the budget

(112)

Proof of Proposition 1a

• LHS: Gain from conflict

(113)

• Conflict �ik Peace if

(114)

• Conflict �ik Peace if

�

σk − sk

�

G > λik

AkAl (Ak + Al)2

G

= λikσk(1 − σk)G

• Rearranging this inequality yields:

λikσk2 + (1 −λik)σk > sk

(115)

• Notice: this proof only uses the inequality that compares the payoffs from conflict and peace

⇒ Difference between both sides of inequality: Net payoff of conflict

• This allows us to derive Proposition

(116)

Proposition 1b

• Class i of ethnicity j prefers ethnic alliance to class alliance iff

[λijn2_j + (1 − λij)nj − sj]µ > σ_i2 − si

where µ ≡ E/C

• LHS: Gain from ethnic conflict relative to peace

(117)

Proposition 1b: intuition

• Class i prefers class conflict (so

λik = 1) to peace iff

σ_i2 > si

• Class i of ethnicity j prefers ethnic conflict to peace iff

λijn2j + (1 −λij)nj > sj

• If ethnic alliances form, σj = nj

(118)

λ

pk

=

0 as an implication of

within-ethnicity inequality

• λik = 0 if class i in ethnic alliance k

does not finance any activists:

u��yi−

⇒ If income inequality very high (yr >> yp), then

(119)

• Condition for ethnic � class,

[λijnj2 + (1 − λij)nj − sj]µ > σ2i − si,

is easier for ph to satisfy if λph = 0.

⇐ If they don’t need to contribute, the increase in the share of ethnic

(120)

5.7 Recent studies on causes of

ethnic conflict

• Rohner et al. (2013): ethnic conflict

persists as conflict destroys inter-ethnic trust and trade

• Jha (2013): historical inter-ethnic

trade reduces conflict in India

• Yanagizawa-Drott (2012): radio

(121)

6. Future research (in my view)

• Theory-motivated empirics to explain the initiation of conflict

• For a theory survey, see Jackson and Morelli (2011)

• Open the black box of group behavior of rebels

e.g. Bueno de Mesquita (2013)

• Synthesize other forms of political violence (repression, coups, riots, etc.) with civil wars

(122)

Acemoglu, Daron, and James A. Robinson. 2000. “Why Did the West Extend the Franchise? Democracy, Inequality, and Growth in Historical Perspective.” Quarterly Journal of Economics 115: 1167-1199.

Acemoglu, Daron, and James A. Robinson. 2001. “A Theory of Political Transitions.” American Economic Review 91(4): 938-963.

Acemoglu, Daron, and James A. Robinson. 2006. Economic Origins of Dictatorship and Democracy. Cambridge University Press.

Alesina, Alberto et al. 2003. “Fractionalization.” Journal of Economic Growth 8: 155-194.

Baum, Christopher F, Mark E. Schaffer, and Steven Stillman. 2007. “Enhanced routines for

instrumental variables/generalized method of moments estimation and testing.” Stata Journal 7(4): 465–506.

Besley, Timothy, and Torsten Persson. 2009. “Repression or Civil War?.” American Economic Review 99(2): 292-297.

Besley, Timothy, and Torsten Persson. 2011. “The Logic of Political Violence.” The Quarterly Journal of Economics 126(3): 1411 -1445.

Blattman, Christopher, and Edward Miguel. 2010. "Civil War." Journal of Economic Literature, 48(1): 3–57.

Bueno de Mesquita, Ethan. 2013. “Rebel Tactics.” Journal of Political Economy 121(2): 323–57.

Robin Burgess, Rémi Jedwab, Edward Miguel, Ameet Morjaria, Gerard Pardo-i-Miquel. 2013. “The Value of Democracy: Evidence from Road Building in Kenya.” http://sticerd.lse.ac.uk/dps/

seminarpapers/eopp45.pdf

Chaney, Eric. 2013. “Revolt on the Nile: Economic Shocks, Religion, and Political Power.” Econometrica 81(5): 2033–53.

Collier, Paul, and Anke Hoefﬂer. 1998. “On Economic Causes of Civil War.” Oxford Economic Papers 50(4): 563-573.

Desmet, Klaus, Ignacio Ortuño-Ortín, and Romain Wacziarg. 2012. “The political economy of linguistic cleavages.” Journal of Development Economics 97(2): 322-338.

Dube, Oeindrila, and Juan F. Vargas. 2013. “Commodity Price Shocks and Civil Conﬂict: Evidence from Colombia.” The Review of Economic Studies 80(4): 1384–1421.

Easterly, William, and Ross Levine. 1997. “Africa's Growth Tragedy: Policies and Ethnic Divisions.” Quarterly Journal of Economics 112: 1203-1250.

Esteban, Joan, Laura Mayoral, and Debraj Ray. 2012. “Ethnicity and Conﬂict: An Empirical Study.” American Economic Review 102(4): 1310–1342.

Esteban, Joan-Maria, and Debraj Ray. 1994. “On the Measurement of Polarization.” Econometrica 62 (4): 819-851.

Esteban, Joan, and Debraj Ray. 1999. “Conﬂict and Distribution.” Journal of Economic Theory 87: 379-415.

(123)

Esteban, Joan, and Debraj Ray. 2011. “Linking Conﬂict to Inequality and Polarization.” American Economic Review 101: 1345-1374.

Fearon, James D. 1995. “Rationalist Explanations for War.” International Organization 49(3): 379-414.

Fearon, James D., and David D. Laitin. 2003. “Ethnicity, Insurgency, and Civil War.” American Political Science Review 97(1): 75-90.

Garﬁnkel, Michelle R., and Stergios Skaperdas. 2006. “Economics of Conﬂict: An Overview.” In Handbook of Defense Economics, eds. T. Sandler and K. Hartley. Elsevier.

Jackson, Matthew O., and Massimo Morelli. 2007. “Political Bias and War.” American Economic Review 97(4): 1353-1373.

Jackson, Matthew O., and Massimo Morelli. 2011. "The Reasons for Wars - an Updated Survey," in the Handbook on the Political Economy of War edited by Chris Coyne and Rachel Mathers, Elgar Publishing. http://www.stanford.edu/~jacksonm/war-overview.pdf

Jia, Ruixue. 2012. “Weather Shocks, Sweet Potatoes and Peasant Revolts in Historical China.” The Economic Journal, forthcoming.

Jones, Benjamin F, and Benjamin A Olken. 2009. “Hit or Miss? The Effect of Assassinations on Institutions and War.” American Economic Journal: Macroeconomics 1(2): 55-87.

La Porta, Rafael et al. 1999. “The Quality of Government.” Journal of Law, Economics, & Organization 15(1): 222-279.

Morelli, Massimo, and Dominic Rohner. 2013. "Resource Concentration and Civil Wars." https:// sites.google.com/site/dprohner/research

Michalopoulos, Stelios. 2012. “The Origins of Ethnolinguistic Diversity.” American Economic Review 102(4): 1508–1539.

Montalvo, José G., and Marta Reynal-Querol. 2005. “Ethnic Polarization, Potential Conﬂict, and Civil Wars.” American Economic Review 95(3): 796-816.

Posner, Daniel N. 2004. “Measuring Ethnic Fractionalization in Africa.” American Journal of Political Science 48(4): 849–863.

Powell, Robert. 2006. “War as a Commitment Problem.” International Organization 60: 169-203.

Ray, Debraj. 2009. "Costly Conﬂict Under Complete Information" http://www.econ.nyu.edu/user/ debraj/Papers/CostlyConﬂict.pdf

Skaperdas, Stergios. 1992. “Cooperation, Conﬂict, and Power in the Absence of Property Rights.” American Economic Review 82(4): 720-739.

Tullock, G. “Efﬁcient Rent Seeking.” In Toward a Theory of the Rent Seeking Society, eds. J. M. Buchanan, R. D. Tollison, and G. Tullock. Texas A&M University Press.