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Calamity, Conflict and Cash Transfers: How Violence Affects Calamity, Conflict and Cash Transfers: How Violence Affects

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Calamity, Conflict and Cash Transfers: How Violence Affects - PPT Presentation

Yashodhan Ghorpade 5 th December 2014 Aid and Violent Conflict Addressing grievances that give rise to conflict Winning hearts and minds Berman Shapiro and Felter 2009 Political Science literature ID: 180815

aid conflict taliban state conflict aid state taliban presence armed affected tehsil present primary killings 7802 estimation level cdcp

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Slide1

Calamity, Conflict and Cash Transfers: How Violence Affects Access to Aid in Pakistan

Yashodhan Ghorpade

5

th

December 2014Slide2

Aid and Violent ConflictAddressing grievances that give rise to conflict“

Winning hearts and minds

Berman, Shapiro and

Felter

2009

Political Science literature:

does aid reduce conflict?

Yes –

Justino - India (2011,

forthcoming

);

Berman, Shapiro and

Felter

(2009) – Iraq

No –

Crost

and Johnston (2014

) –

Phillipines

Mixed evidence -

Beath

,

Cristea

and

Enikolopov

(2012

) NSP, Afghanistan

Development Economics literature:

Does conflict affect programme impact?

Higher conflict makes people use transfer to migrate out –

Mesnard

(2009) – Familias

en

Accion

, Colombia

Higher impact on school enrolment in conflict areas –

Wald and

Bozzoli

(2009),

Familias

en

Accion

, Colombia Slide3

Why is the link between conflict and aid important?Assumptions by both, political actors and development community critical to success

Pathway

to understanding political landscape of areas affected by conflict – actors, incentives, capabilities – and therefore options

Better understand considerations while extending aid to conflict-affected areasSlide4

StructureCase study setting and contextData and Identification StrategyIV Estimation and 1

st

Stage Results

Does conflict reduce access to aid?

YES

Mechanisms: How does conflict reduce access to aid?

ARMED

GROUPS

Conclusions and Policy ImplicationsSlide5

Case Study Setting and ContextPakistan – several forms of violenceMarked increase in violence from 2001 – present

Terrorist, insurgency, sectarian motives for internal political violence

Post 2010 flood period. Soon after democratic transition, marked by high violenceSlide6
Slide7

Fatalities due to Conflict in Pakistan 2001 –2010: BFRS and SATP dataSlide8

Aid Programmes in PakistanReforming Social Protection landscape: democratic transition in 2008

Benazir Income Support Programme (BISP)

UCC based on poverty score card

Regular monthly payments to chronic poor households, women recipients

CDCP (

W

atan

)

- Cash transfer-based flood relief programme in 2010

Universal except in KPK – based on house damageSlide9

Data and MethodologyCDCP Impact Evaluation Baseline data; collected

after the 2010 floods

7802 households, representative for flooded areas at the Province, National levels

Key modules

: Shocks and Coping Strategies, Demographics, Assets, Flood Exposure, SP receipts

Conflict data: sub-district level conflict exposure measures using

SATP

data for 2001 – June 2010 (pre-floods)

Measured as Log (1+n) killings between 2001-10 at sub-district levelSlide10

Identification StrategyConflict not random, not neatly demarcated by an exogenous break: contagion over time Violence over 2000s direct spill-over from War on Terror in Afghanistan, history and politics studied by several authors

(Gul 2009; Rashid 2012; Shapiro and

Gulzar

2012;

Gunaratna

and Iqbal

2010; Jones and Fair 2010;

Hussian

2008)

IV estimation

: Distance to

Afghanistan

Control for confounding factors Slide11

Mapping district-level conflict intensity in PakistanSlide12
Slide13
Slide14
Slide15
Slide16
Slide17
Slide18
Slide19
Slide20
Slide21
Slide22

IV EstimationCausal Relationship of Interest:

IV First Stage:

2

nd

Stage:

 Slide23

IV Estimation: Potential Threats and MitigationAssociation between proximity to Afghanistan and Access to Aid

Remoteness

: Province Dummies, Distance from Administrative Centres

(Provincial, District)

Topography

: Dummy for topography type

(Mountain, Hill, Plateau, Valley, Coastal Plains, Inland Plains)

State Presence

: Community-level

Index

(Govt

. schools, health facilities, immunisation camps, community health workers, post offices administrative HQs)

Infrastructure

: Community-level Index (Bus/wagon stop,

Motorable Road, Railway Station, Retail Shop, Wholesale market, Bank

, Flour mill, Tractor rental centre, Fertiliser depot, Electricity, Gas, Drainage

)Linguistic Fractionalisation: Index a la Alesina et al. (2003)Army Control: Distance to Army Cantonments Province-specific features, capacity: Province DummiesSlide24

IV First Stage Results

 

(1)

(2)

(3)

Distance to Afghan Border

-0.877

***

-

0.494

***

-

0.266

***

(-12.61)

(-10.09)

(-

12.13)

Controls

NO

YES

YES

Province dummies

NO

NO

YES

N

7802

7786

7786

F-statistic (1, 496)

160.93

101.82

14.99

Prob. > F

0.0000

0.0001

0.0001

Adjusted R-squared

0.3373

0.5411

0.5683Slide25

Causal Impact of conflict on likelihood of receiving transfers?

 

 

 

 

 

 

 

CDCP - I (Flood Relief)

BISP

 

probit

IV probit

probit

IV probit

Log (n+1) killings at tehsil level

0.003

-0.438

***

0.002

-0.257

**

 

-0.7

(-3.29)

-0.49

(-2.07)

Controls

Y

Y

Y

Y

Province Dummies

Y

Y

Y

Y

N

7802

7802

7802

7802Slide26

Conflict and Household-level Access to AidConflict reduces access to aid at the household level for both CDCP and BISP programmes

Controlling for a range of characteristics that determine eligibility and enable accessing aid (demand), and factors that facilitate rollout at the community level (supply)

Stronger effect on CDCP than BISP

Effect

NOT driven by differential eligibility

. In fact, on some indicators households in conflict-affected areas more eligible for aidSlide27

How does conflict reduce access to aid? MechanismsImportant to note controls – infrastructure, state presence, remoteness, topography – impact of conflict is over and above the effect of these factors

Test one hypothesis/ plausible mechanisms:

Presence/ Control of Non-State Armed groups

Armed

groups

resent

efforts by the government to win over political support

Gompert

et al.,

2009;

Crost

and Johnston

2014Targeting of state services, development interventions: Attacks on NGOs, abduction of aid workers, attacks on immunisation camps, BISP office (Turbat)

- Gul 2010; Jones and Fair 2011; Gunaratna and Iqbal 2010Slide28

Armed non-State Actors in PakistanAstounding increase not only in violence but also in the presence and influence of extremist and militant groups

, especially in the NW

Avowed aim to overthrow/ transform the nature of the Pakistani state, delink from the US, adopt Sharia, enforce worldview

Groups loosely coalescing under the umbrella of the

Tehrik

-e-Taliban Pakistan

(TTP) since 2007

Several groups

view state as enemy Slide29

Measuring the presence of armed groupsNo published data – NOT straightforward!

Violence not a perfect proxy of armed group presence

; violence erupts where there is contest, not in domain of opponents’ complete dominance

(

Kalyvas

2006; Justino and Ibanez 2014)

Proxied

attempting to model the

influence of TTP groups on girls’ primary schooling

Extensive reportage of TTP opposition to girls’ education in areas of their control

Residual Analysis from Community-level estimations of Girls’ SchoolingSlide30
Slide31

Modelling Community-level Female Primary EnrolmentComplete Model:

Observed Model:

However,

 Slide32

Observed :

If

negative, predicted enrolment higher than observed enrolment

More likely associated with presence of ANSA:

Divide communities by +/- residuals, test effects of conflict on aid over sub-populations

If ANSA more likely in communities with negative residual, negative

could explain effect on aid receipts?

If

is indeed random error, communities with

< 0 similar to communities with

>

0 (random error with mean 0); expect similar effects of conflict on aid

 Slide33

Estimating Community-level Female Primary Enrolment RateDemand Side

Adult Education (Female)

Adult Education (Male)

Sex Ratio (Adult)

Receipt of Remittances

Average Income level

Land Ownership Patterns

Wealth Status

Enterprise Ownership

Displacement status (Flood)

Linguistic Identity

Supply Side

Presence of Govt. and Private Girls’ and Co-Ed Schools in Community

Community InfrastructureState Presence

Remoteness from AdministrationElectricity AccessFormer Princely StateSlide34

Effect of Armed non-State Actors presence on CDCP Receipts

 

Full Sample

Effect of conflict on Receipt of CDCP (Flood Relief Transfers): Over Residuals

of Female Primary

Enrollment

Estimation

 

 

 

>

0

 

< 0

 

 

Taliban likely not present

Taliban likely present

Log (1+n) killings

-0.541***

-0.267

-0.757***

 

(-4.08)

(-1.25)

(-6.31)

N

7786

4254

3532

 

Full Sample

Effect of conflict on Receipt of CDCP (Flood Relief Transfers): Over Residuals

of Female Primary

Enrollment

Estimation

 

 

 

 

Taliban likely not present

Taliban likely present

Log (1+n) killings

-0.541***

-0.267

-0.757***

 

(-4.08)

(-1.25)

(-6.31)

N

7786

4254

3532Slide35

Effect of Armed non-State Actors presence on BISP Receipts

 

Full Sample

Effect of conflict on Receipt of CDCP (Flood Relief Transfers): Over Residuals

of Female Primary

Enrolment

Estimation

 

 

 

>

0

 

< 0

 

 

Taliban likely not present

Taliban likely present

Log (1+n) killings

-0.463***

-0.333

**

-0.645***

 

(-3.81)

(-2.38)

(-3.48)

N

7786

4254

3532

 

Full Sample

Effect of conflict on Receipt of CDCP (Flood Relief Transfers): Over Residuals

of Female Primary

Enrolment

Estimation

 

 

 

 

Taliban likely not present

Taliban likely present

Log (1+n) killings

-0.463***

-0.333

**

-0.645***

 

(-3.81)

(-2.38)

(-3.48)

N

7786

4254

3532Slide36

Effect of Armed non-State Actors presence on BISP Receipts

 

Full Sample

Residuals of Female Primary Enrollment Estimation

Residuals of Primary Enrollment Gender Gap Estimation

 

 

Taliban likely not present

Taliban likely present

Taliban likely not present

Taliban likely present

Panel A

 

 

 

 

 

Conflict-affected tehsil (dummy)

-1.890

***

-1.457

**

-2.184***

-0.207

-2.568***

 

(-3.75)

(-2.20)

(-3.34)

(-1.43)

(-4.06)

N

7786

4254

3532

3651

4135

 

 

 

 

 

 

Panel B

 

 

 

 

 

Log (1+n) killings

-0.463***

-0.333

**

-0.645***

-0.057

-0.576***

 

(-3.81)

(-2.38)

(-3.48)

(-1.53)

(-3.50)

N

7786

4254

3532

3651

4135Slide37

Armed Group Presence and AidStrong and significant results for both programmesEchoed in qualitative, anecdotal references to the presence/ control of armed non state actors limiting access to aid

Armed group presence deters aid workers/ bureaucrats to enter/ operate in areas of their control (

supply

of aid) ?

Inhibits households from overtly seeking state aid (

demand

for aid) ? Slide38

Conclusions & Policy RecommendationsConflict reduces access to both cash transfer programmes

Robustness

: Results hold when using dummy for conflict-affected sub district

Presence of TTP-linked armed groups

lowers access to aid

Reduces supply by threats to aid workers, officials, AND demand by threats of retaliation, reduced mobility of local populations

Robust

to estimation of community-level gender gap in primary schooling

This is worrying: The

lack of access to aid may

exacerbate development shortfalls

, horizontal inequalities – with implications for future peace and

development

Need to question more carefully the ability to implement programmes in conflict-affected areas to achieve development, political goalsNeed for conflict-sensitive analyses

to inform development policy and operations in conflict-affected areas. Realities too distinction for “development as usual”.Reaching households may require striking a deal with/ paying off armed groups – ultimately a political, tactical decision, e.g. Tsunami aid in Sri LankaSlide39

Discussion: Winning Hearts and Minds or Losing Lands and People?Clear intent to use aid to win hearts and minds, foster nation-buildingAid as an instrument for achieving state goals – popular support, redress of historic grievances, and tactical support in fight against militants/ insurgents

“Conflict

in NWFP [old acronym of the Khyber Pakhtunkhwa province], FATA and Balochistan has severely challenged the ability of the state as well as the legitimacy of the idea of a functioning state in Pakistan.

Social protection must be part of the strategy to reclaim the space and legitimacy for the state in Pakistan

, through protection to the basic entitlements of people in the conflict-affected

areas…

“Expanded

social protection programmes, particularly directed at the conflict-affected areas are essential to protect innocent victims of conflict, and to

regain legitimacy for the idea of a functioning state

through creating, expanding and ensuring the delivery of citizenship-based entitlements

.”

GoP

(2010), pp.

145Slide40

… Yet, Ability may curtail intent:

“The

challenge in NWFP and FATA comes from groups that seek to impose their own vision of society on the majority. They violate democratic norms, actively and violently oppose social policy and development initiatives such as

girls’ schooling

, immunization campaigns, and

even income transfers to women

. The armed activities of militants and the state’s armed response has led to large-scale loss of life, displacement, and destruction of infrastructure, particularly social infrastructure. There has been massive disruption to livelihoods and economic activity

.”

(

GoP

2010), pp. 145Slide41

Robustness Tests: Conflict Dummy

 

CDCP – Phase I

BISP

CDCP – Phase I

BISP

probit

probit

probit

probit

IV probit

IV probit

IV probit

IV probit

Conflict-affected tehsil (dummy)

0.118***

 

-0.016

 

-1.619

***

 

-1.100

**

 

-4.36

(-0.24)

(-3.44)

(-2.05)

Controls

Y

Y

Y

Y

Y

Y

Y

Y

Province Dummies

Y

Y

Y

Y

Y

Y

Y

Y

N

7802

7802

7802

7802

7802

7802

7802

7802Slide42

Likelihood of entire community being excluded from programme

 

CDCP - I

BISP

 

Conflict-affected Tehsil

Log (1+n) killings - tehsil

Conflict-affected Tehsil

Log (1+n) killings - tehsil

Conflict-affected Tehsil (dummy)

1.275

 

2.457***

 

 

(1.45)

 

(7.38)

 

 

 

 

 

 

Log (1+n) killings - tehsil

 

0.188**

 

0.613***

 

 

(2.16)

 

(3.88)

N

497

497

497

497Slide43

Community-level coverage rates of programmes

 

CDCP - I

BISP

 

Log (1+n) killings - tehsil

Conflict-affected Tehsil

Log (1+n) killings - tehsil

Conflict-affected Tehsil

Conflict-affected Tehsil (dummy)

-1.475

 

-0.847*

 

 

(-1.41)

 

(-1.75)

 

 

 

 

 

 

Log (1+n) killings - tehsil

 

-0.256**

 

-0.156**

 

 

(-2.30)

 

(-2.48)

N

497

497

497

497Slide44

Estimation of Female Primary Enrolment

N

439

R2

0.517

adj. R2

0.472

F

11.59

Prob. F > 0

0.0000Slide45

Effect of Armed non-State Actors presence on CDCP Receipts

 

Full Sample

Residuals of Female Primary Enrollment Estimation

Residuals of Primary Enrollment Gender Gap Estimation

 

 

Taliban likely not present

Taliban likely present

Taliban likely not present

Taliban likely present

Panel A

 

 

 

 

 

Conflict-affected tehsil (dummy)

-1.959

***

-1.126

-2.344***

-0.367

-2.575***

 

(-4.13)

(-1.22)

(-5.66)

(-1.12)

(-5.38)

N

7786

4254

3532

3651

4135

 

 

 

 

 

 

Panel B

 

 

 

 

 

Log (1+n) killings

-0.541***

-0.267

-0.757***

-0.101

-0.696***

 

(-4.08)

(-1.25)

(-6.31)

(-1.25)

(-5.02)

N

7786

4254

3532

3651

4135Slide46

Effect of Armed non-State Actors presence on BISP Receipts

 

Full Sample

Residuals of Female Primary Enrollment Estimation

Residuals of Primary Enrollment Gender Gap Estimation

 

 

Taliban likely not present

Taliban likely present

Taliban likely not present

Taliban likely present

Panel A

 

 

 

 

 

Conflict-affected tehsil (dummy)

-1.890

***

-1.457

**

-2.184***

-0.207

-2.568***

 

(-3.75)

(-2.20)

(-3.34)

(-1.43)

(-4.06)

N

7786

4254

3532

3651

4135

 

 

 

 

 

 

Panel B

 

 

 

 

 

Log (1+n) killings

-0.463***

-0.333

**

-0.645***

-0.057

-0.576***

 

(-3.81)

(-2.38)

(-3.48)

(-1.53)

(-3.50)

N

7786

4254

3532

3651

4135