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IntroductionEmpirical StrategyData and Results

Veterans and ethnic cleansing:evidence from the Partition of India

Saumitra Jha and Steven Wilkinson

Stanford and Yale

BREAD- Alba di Canazei

Jha (Stanford), Wilkinson (Yale) Veterans and ethnic cleansing


Partitions

Partitioning ethnically-diverse regions into homogeneoushomelands often-mooted solution to ethnic conflict,under-development.

▶ Both by policymakers . . .eg Iraq (Hanlon & Joseph 2007), the Holy Land (Downes 2001),Yugoslavia (NATO)

▶ and by academics (though with some debate)(Sambanis & Schulhofer-Wohl 2009, Chapman & Roeder 2007,Humphreys, Posner & Weinstein 2008, Kaufmann 1998, Alesina,Spolaore and Wacziarg 2005, Spolaore 2009)

Much less known about conditions under which partitions canpeaceful and when they result in ethnic cleansing and massviolence.



The Partition of India

Photo: Margaret Bourke-White, 1947

▶ 14.5 million displaced between June1947- 1948

▶ Estimated 100,000 - 1 million killed inPartition violence

▶ But 3.4 million target minorities “missing”-unaccounted for by 1951 census(Bharadwaj, Khwaja and Mian 2008).



Religious mix and the Radcliffe Award

Legend% Muslims 1942 (Deciles)

0.1% - 1

.4%

1.5% - 3

.2%

3.3% - 5

.3%

5.4% - 7

.7%

7.8% - 1

0.5%

10.6%

- 12.9

%

13% - 1

8.5%

18.6%

- 50.3

%

50.4%

- 77.1

%

77.2%

- 100%

source: 1942 Census



Religious demographics and minority outflows

Legend% Muslims 1942 (Deciles)

0.1% - 1

.4%

1.5% - 3

.2%

3.3% - 5

.3%

5.4% - 7

.7%

7.8% - 1

0.5%

10.6%

- 12.9

%

13% - 1

8.5%

18.6%

- 50.3

%

50.4%

- 77.1

%

77.2%

- 100%

Pakistan Border% Outflows per 1951 population

“The principal danger areas are likely to lie in the United Provinces, Bihar andBengal”- C-in-C India, Nov 1945.



State failure to quell violence▶ Horowitz (2001):“Ordinarily, clear and consistent

disapproval of violence deters ethnic riots”e.g. 1942 Quit India rebellion in UP.

▶ But in 1947:

. . . members of the Punjab Boundary Force found acountryside not easily intimidated even by seasonedand heavily armed troops like themselves . . . Whatseems to have been happening was that the army wasbeing challenged by experts, by people who hadformerly served within its ranks . . . . the massacres ofPunjab, in all their gruesome efficiency, bore theimprint of military training and organization.”

- Kamtekar (1986), citing Maj-Gen. Rees, Punjab B.F.



This paper▶ First systematic assessment of political & economic

determinants of ethnic cleansing during the Partition ofIndia.

▶ Exploits arbitrary assignment of units to combat duringWWII to identify effects of combat experience on ethniccleansing in home districts.

▶ Finds that districts that raised units with additional monthof combat experience:

1. Had 1 percentage point fewer targeted minorities in 1951(mean: 9 percent)

2. Increased outflows of minorities by 20,000 people3. Increased inflows of co-religionist refugees by 1

percentage point (of 1951 population) ( 28,000)▶ Effects larger in districts with ex ante more ethnically mixed

populations.



Interpretation

1. Combat experience provides a form of specific humancapital– skills at perpetrating violence and at organisation–that become most valuable during times of crisis.

2. These skills are particularly important in “polarised”situations consistent with the degree of the “public” goodsat stake in the conflict (as opposed to private expropriation)(Esteban and Ray 2009; Horowitz 1985).



Related literature

▶ Partitions▶ Ethnic diversity and public goods, conflict, growth▶ Veterans and post-conflict reconstruction

▶ Mixed psychological literature on trauma vs growth((Dygrove et al 2002, Tedeschi and Calhoun 1996, Powellet al 2003, Street 2003)

▶ Surveys of post-conflict households exposed to violence(Bellows and Miguel 2008), child soldier abductees(Blattman and Annan 2008, Blattman 2009) and educationlevels of veterans (Angrist and Krueger 1990)

▶ Effects are remarkably benign.



Where this paper fits in

1. Assesses the determinants of ethnic cleansing in animportant case: the Partition of India

2. Plausibly identifies effect of combat experience (ratherthan recruitment)

3. Looks at the role of combat experience in a subsequentcrisis rather than in post-conflict peace and reconstruction.

4. Argues that combat experience leads to development ofspecific human capital that becomes valuable in suchmoments of crisis.



Outline

Introduction

Empirical Strategy

Data and Results



Empirical StrategyOLS, district-level regressions of:

Min Ratio51i = �Frontline40−45i+ Casualtiesi+�Min Ratio31i+XB+�i(1)

Minorities Hindus / Sikhs in Pakistan, Muslims in IndiaFrontline the average number of months units raised from a

district spent in combat in WWII.Casualties the number of war casualties.

▶ Can decompose changes in the minority ratio into outflowsand inflows by constructing counterfactuals (BKM 2008).

▶ Identification: arbitrary assignment of troops to combatroles, conditional on recruitment in field army.



WWII experience of 1st Punjab Regiment

Battalion RegimentFirst Campaign

Second Campaign

Third Campaign

Fourth Campaign

Months at the frontline

1 1 Punjab Burma March 1944-July 1945

8

2 1 Punjab The Arakan Operations 1942-1945

Burma March 1944-July 1945

8

3 1 Punjab September 1940 - May 1941 East African Campaign

North Africa 1941

Italy 1943 Italy 1944 21

4 1 Punjab 05 1 Punjab The Retreat

from Burma 1941-1942

The Arakan Operations 1942-1945

Burma May 1945

Japan July 1945-November 1947

8

6 1 Punjab South-east Asia

1

ompare units from the same regiment. 3 Battalion part of unitthat put Haile Selassie back on the throne of Abyssinia, foughtwith the Desert Rats against Rommel in Africa, and assaultedKesselring’s winter line in 1944.Troops were diverted from various offensives particularly in1941 when Japan entered the warIn contrast, the 5th battalion fought mainly in Burma, while the4th Punjab did not enter combat at all, but their units weredispatched to other battalions depending on need.We gathered data on the orders of battle for each campaign ofthe Indian army in World War 2 from the 17 volume officialhistory. This tells us for each unit whether or not they wereengaged in combat.



Qualitative evidence for arbitrary deployment

▶ In internal army correspondence, no evidence for WWIIservice outside India of specific requests for units basedon their ethnicity (with 2 exceptions- Gurkhas)

▶ Transfer and substitution patterns of units without regard toethnicity of unit.

▶ All infantry regiments receive same weapons.▶ Special emphasis that units be ‘interchangeable’ (1921

Reorganisation Report, marked “Confidential”).



Determinants of combat experience(1) (2) (3) (4) (5)OLS OLS OLS OLS OLS

WWII casualties in district, 100s 0.204*** 0.022 0.104 ‐0.068[0.049] [0.080] [0.066] [0.072]

Land revenue, Rs. Lakhs, 1901 0.082 0.024 ‐0.057 ‐0.019 ‐0.039[0.082] [0.068] [0.088] [0.066] [0.070]

Log. distance to Indo‐Pak border ‐0.151 ‐0.099 0.085 ‐0.190 0.132[0.125] [0.108] [0.097] [0.279] [0.192]

% Majority literacy, 1931 ‐0.014 ‐0.023 ‐0.025 0.030 0.023[0.028] [0.026] [0.025] [0.032] [0.026]

% Minority literacy, 1931 0.000 0.008 0.012 ‐0.034* ‐0.039**[0.039] [0.036] [0.033] [0.018] [0.019]

% religious minorities, 1931 0.011 0.010 0.023** ‐0.007 0.005[0.016] [0.015] [0.011] [0.011] [0.008]

Big City Dummy 0.085 0.204 ‐0.317 ‐0.088 ‐0.207[0.346] [0.319] [0.196] [0.248] [0.224]

Population 1931 (lakhs) ‐0.006*** ‐0.005** ‐0.004** ‐0.022 ‐0.002[0.002] [0.002] [0.002] [0.018] [0.015]

Religious pilgrimage site in district ‐0.435 ‐0.519** ‐0.235 ‐0.125 ‐0.150[0.297] [0.207] [0.230] [0.194] [0.101]

Medieval port in district ‐0.257 ‐0.298 ‐0.044 0.103 0.166[0.293] [0.273] [0.204] [0.203] [0.145]

Muslim founded city/ capital in district 0.426 0.275 0.278 0.001 ‐0.012[0.284] [0.238] [0.200] [0.277] [0.236]

Controls for martial race regimental casualtie no no yes no yesNative State/ Province FE no no no yes yesObservations 221 221 221 221 221R‐squared 0.08 0.21 0.40 0.50 0.64Robust standard errors in brackets, clustered at province / native state level. * significant at 10%; ** significant at 5%; *** significant at 1%; + Martial race regiments include: Sikh, Kumaon, Mahratta, Garhwal, Dogra, Punjab, Frontier Force and Gurkha

t might be hard to see anything on this table but that is alsobecause there really isn’t much to see.



Veterans

▶ India in WWII recruited the largest volunteer army in worldhistory, with 2,286,000 serving in army at war’s end.

▶ This was 1.25% of the male Indian population.▶ Disproportionately from martial races (those that, ironically,

did not revolt in 1857).▶ By June 1947, 1,500,000 Indian soldiers had already been

demobilized.



Matching veterans to districts

▶ Commonwealth War GravesCommission: Data on 86,000 Indiancasualties in WWII

▶ Since companies have definedrecruiting grounds, can infer whichdistricts raised which regiments.

▶ 17 Vol Official History yields detailedorders of battle for each combat action-construct unit experience for eachmonth.

▶ We weight wartime unit experience bycasualties per unit in district to createaverage combat experience measure.



A sample entry



Outcomes

Pakistan Border% Outflows per 1951 population

▶ Minority Ratio, 1951▶ Outflows (includes converts,

migrants and “missing” (BKM 2009))

Outflows = m51 − E(m51)

E(m51) = [m31 × gmaj31−51 × gmin

21−31]



Outflows and deaths due to violence0

5000

1000

015

000

2000

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0 20 40 60 80 100

bandwidth = .8

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1500

020

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0 20 40 60 80 100

Minority outflows (10,000s)0

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1000

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0 20 40 60 80 100



The homogenisation of India

Variable Mean SD% Outflows per 1951 population (using native growth rates) 5.902 16.460% Inflows per 1951 population 3.412 7.526% Religious minority, 1951 8.953 9.639% Religious minorities, 1931 13.097 12.208

WWII casualties in district, 100s 1.438 3.203Average months at frontline 1.656 1.471

% Majority literacy, 1931 6.259 4.358% Minority literacy, 1931 10.312 6.861



Table 4: Minority ratio 1951

(1) (2) (3) (4) (5)OLS OLS OLS OLS OLS

WWII casualties in district, 100s ‐0.742*** ‐0.657*** ‐0.424 ‐0.147 0.35[0.225] [0.152] [0.381] [0.091] [0.211]

Average months at frontline ‐1.724*** ‐1.051*** ‐1.364*** ‐0.675*** ‐0.683**[0.629] [0.371] [0.411] [0.232] [0.335]

Frontline months x % minority ‐0.205*** ‐0.176*** ‐0.149*** ‐0.155***[0.027] [0.034] [0.024] [0.031]

% religious minorities, 1931 0.591*** 1.008*** 0.983*** 1.000*** 1.011***[0.124] [0.065] [0.067] [0.048] [0.049]

Controls for martial race regimental casualties+ no no yes no yesNative State/ Province FE no no no yes yesObservations 220 220 220 220 220R‐squared 0.59 0.77 0.79 0.91 0.93

Robust standard errors in brackets, clustered at province / native state level. * significant at 10%; ** significant at 5%; *** significant at 1%; All regressions include controls for: land revenue, big city dummy, log distance to border, minority and majority literacy rates, population, pilgrimage sites, medieval ports, historical patronage centres. + Martial race regiments include: Sikh, Kumaon, Mahratta, Garhwal, Dogra, Punjab, Frontier Force and Gurkha



Table 5: Minority outflows (10,000s)


WWII casualties in district, 100s 1.198*** 1.105*** 1.325 0.465** ‐1.026*[0.416] [0.371] [1.052] [0.200] [0.605]

Average months at frontline 2.680** 1.95 2.567** 0.859*** 0.914***[1.313] [1.170] [1.117] [0.309] [0.316]

Frontline months x % minority 0.222*** 0.124** 0.122* 0.077[0.059] [0.048] [0.070] [0.059]

% religious minorities, 1931 0.494*** 0.042 0.132 0.083 0.146[0.120] [0.116] [0.119] [0.172] [0.181]

Controls for martial race regimental casualties+ no no yes no yesNative State/ Province FE no no no yes yesObservations 220 220 220 220 220R‐squared 0.43 0.49 0.58 0.69 0.74Robust standard errors in brackets, clustered at province / native state level. * significant at 10%; ** significant at 5%; *** significant at 1%; All regressions include controls for: land revenue, big city dummy, log distance to border, minority and majority literacy rates, population, pilgrimage sites, medieval ports, historical patronage centres. + Martial race regiments include: Sikh, Kumaon, Mahratta, Garhwal, Dogra, Punjab, Frontier Force and Gurkha



Table 6: Co-religionist inflows per 1951 pop.


WWII casualties in district, 100s 0.141 0.105 ‐0.159 ‐0.385* 0.029[0.109] [0.093] [0.278] [0.220] [0.278]

Average months at frontline 0.992* 0.902** 0.936* 0.631** 0.499[0.563] [0.411] [0.554] [0.250] [0.361]

Frontline months x % minority 0.105*** 0.097*** 0.068** 0.070**[0.031] [0.035] [0.026] [0.032]

% religious minorities, 1931 0.270*** 0.079 0.073 0.052 0.031[0.073] [0.061] [0.068] [0.067] [0.081]

Controls for martial race regimental casualties+ no no yes no yesNative State/ Province FE no no no yes yesObservations 235 235 235 235 235R‐squared 0.49 0.56 0.59 0.78 0.80Robust standard errors in brackets, clustered at province / native state level. * significant at 10%; ** significant at 5%; *** significant at 1%; All regressions include controls for: land revenue, big city dummy, log distance to border, minority and majority literacy rates, population, pilgrimage sites, medieval ports, historical patronage centres. + Martial race regiments include: Sikh, Kumaon, Mahratta, Garhwal, Dogra, Punjab, Frontier Force and Gurkha



Flexible Visual Multiple Regression-4

0-2

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residuals quadratic fit-4

0-2

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per 1

951

pop.

) | X


residuals quadratic fit



Placebo 1: Hindu-Muslim riots prior to WWIImobilisation

(1) (2) (3) (4) (5) (6)OLS OLS OLS OLS OLS OLS

WWII casualties in district, 100s ‐0.051 ‐0.051 0.052 0.008 ‐0.034 0.197[0.034] [0.034] [0.178] [0.255] [0.065] [0.218]

Average months at frontline 0.076 0.077 0.079 0.055 ‐0.008 0.011[0.086] [0.079] [0.087] [0.143] [0.083] [0.166]

Frontline months x % minority ‐0.001 ‐0.001 0.002 0.001[0.007] [0.009] [0.005] [0.011]

% religious minorities, 1931 0.060* 0.061 0.053 0.014 0.031 0.021[0.030] [0.037] [0.037] [0.034] [0.028] [0.057]

Religious pilgrimage site in district 3.649** 3.650** 3.829** 3.695* 3.435** 3.202*[1.523] [1.528] [1.749] [2.091] [1.484] [1.894]

Medieval port in district ‐1.392*** ‐1.396*** ‐1.362*** ‐0.017 ‐1.646** ‐0.404[0.463] [0.476] [0.461] [0.523] [0.612] [0.525]

Muslim founded city/ capital in district 1.461*** 1.459*** 1.457*** 0.515* 1.679*** 1.034*[0.401] [0.398] [0.393] [0.268] [0.351] [0.581]

Controls for martial race regimental casualti no no yes yes no yesNative State/ Province FE no no no yes no yesObservations 228 228 228 228 234 234R‐squared 0.25 0.25 0.27 0.47 0.23 0.43



Placebo 2: Murders in district, 1938


WWII casualties in district, 100s 30.602** 30.442** ‐4.060 ‐8.763* ‐3.970[9.466] [9.081] [7.490] [4.461] [3.244]

Average months at frontline ‐10.653 ‐9.435 ‐24.671 3.568 6.034[11.724] [12.411] [23.897] [3.283] [5.954]

Frontline months x % minority ‐0.667 1.869 ‐0.401 ‐0.487[0.800] [1.426] [0.406] [0.468]

Controls for martial race regimental casualties+ no no yes no yesNative State/ Province FE no no no yes yesObservations 162 162 162 162 162R‐squared 0.31 0.32 0.61 0.77 0.83

Robust standard errors in brackets, clustered at province / native state level. * significant at 10%; ** significant at 5%; *** significant at 1%; All regressions include controls for: land revenue, big city dummy, log distance to border, minority and majority literacy rates, population, pilgrimage sites, medieval ports, historical patronage centres. + Martial race regiments include: Sikh, Kumaon, Mahratta, Garhwal, Dogra, Punjab, Frontier Force and Gurkha



Interpretation

▶ Combat experience provides a form of specific humancapital: skills at organising and perpetrating violence– thatbecome most valuable during times of crisis or stateweakness.

▶ Particularly important in “polarised” situations consistentwith the degree of “publicness” of the goods at stake in theconflict (Esteban and Ray 2009)

▶ Also consistent with increased co-religionist refugeeinflows.



Role of veterans in violence: further qual evidence

▶ Many attacks in military formation using flankingmanoeuvres

▶ Use of sten guns, light machine guns, even mortars.▶ Helped train ‘volunteer’ paramilitary organisations. (Talbot,

2009)



Role of veterans in organisation

The Sikhs moved in blocks of 40,000 to 60,000 andcover about 20 miles a day. . . The organization ismainly entrusted to ex-servicemen and soldiers onleave who have been caught by the disturbances. Menon horseback, armed with spears or swords, provideguards in front, behind, and on the flanks. There is aregular system of bugle calls. At night a halt is callednear some village where water is available, watch firesare lit, and pickets are posted.

- Ian Morrison, The London Times, August 1947



Discussion

1. First systematic empirical analysis of the political andeconomic determinants of ethnic cleansing during thePartition of India.

2. First study we know of in violence literature that usescontemporary unit data to measure veterans’ wartimeexperiences.

3. Public policy implications:Veterans, even if assimilating in peacetime, may beparticularly important during times of crisis, and possiblyfor fundamental institutional change.



How far does this travel?

Forrest McDonald’s 1951 analysis of

Agrarian Radicalism and American

Revolutionary War Veterans in

France

▶ United Kingdom: post 1815300,000 Napoleonic warveterans demobilized 1816,32,000 in 1817.

▶ Ex-soldiers active in EastAnglian riots of 1816,Pentridge rising 1817. Govt.banned military training in1819. (Gash, 1977)

▶ Temporary threat of revolutionleads to democratisation(Great Reform Act)?



What next? Robustness and extensions

1. (Altonji Elder Taber)- unobservables would have to shiftresults by 1.7 x the shift due to observables to eliminatethe effect on outflows.

2. Physical vs human capital (depots)3. Ethnic composition of units (Costa and Kahn 2007)4. Contested districts- rival proposed boundary plans.5. IV using initial deployment6. Identifying recruitment- distribution of cartridges in the

Indian mutiny.7. Long-term effects: public goods, Green Rev, dams.

The Extension of the Franchise in England, The FrenchRevolution, US Civil War veterans


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