614 quarterly journal of economics duflo and pande...

productivity are also likely to make more of these investments,implying a spurious positive relationship between poverty reduc-tion and agricultural growth and dam building. Indeed, Mer-rouche [2004] finds larger poverty reductions for states that builtmore dams, but these findings cannot be given a causalinterpretation.

Our identification strategy, therefore, relies on within-statedifferences in dam construction, specifically differences acrossdistricts in a state. We can, therefore, examine spillover effectsfrom dams in neighboring districts but not state-wide economiceffects of dam construction, such as their effect on prices deter-

FIGURE IDistribution of Dams across Indian Districts, 1970

Data on the number of completed dams per district is from the World Registryof Dams published by the International Commission on Large Dams (ICOLD). SeeAppendix for further details.

614 QUARTERLY JOURNAL OF ECONOMICS

Jorge Aguero

Text Box

Duflo and Pande (QJE, 2007)

mined at the state level. We discuss the possible direction of suchstate-wide effects as we interpret our results.

Consider the following regression:

(1) yist � �1 � �2Dist � �3DistU � �4Zit � �5Zit

U � �i � �st � ist,

where Dist denotes the number of dams in the district and DistU the

number of dams located upstream from district i. �i is a districtfixed effect, �st is a state-year interaction effect and ist a dis-trict-year specific error term. Zit and Zit

U are a set of time varyingcontrol variables for the district and for upstream districts (thelist of relevant control variables is discussed below).

FIGURE IIThe Distribution of Dams across Indian Districts, 1999

Data on the number of completed dams per district is from the World Registryof Dams published by the International Commission on Large Dams (ICOLD). SeeAppendix for further details.

615DAMS

while most of western India, which has seen the maximum damconstruction, has rivers with moderate gradient.

In column (1) of Table II, we formally examine the relation-ship between the number of dams built in a district by 1999 anddistrict river gradient. Our regressions include state fixed effects,district elevation, river length, and district gradient as controls.The omitted river gradient category is the proportion of river in

FIGURE IVAverage River Gradient (in Percentage), by District

The average river gradient is computed using a digital elevation map whichprovides information on surface elevation. We have elevation data for multiplecells per Indian district. To compute river gradient we restrict attention to cellsthrough which a river passes. River gradient is a measure of the steepness of theground surface in the vicinity of district rivers and is defined as the tangent of thesurface. See Appendix for further details.


the flat gradient category (0–1.5 percent). Our results confirm theimportance of engineering considerations: A gentle river gradient(1.5–3 percent) increases the number of dams, while a steepgradient reduces it. However, a very steep river gradient (morethan 6 percent) increases dam construction. The last effect isattributable to some multipurpose dams in our sample that pro-vide both irrigation and hydroelectricity.11

Our panel regressions build on these findings. To predict the

11. We exclude purely hydroelectric dams but cannot identify predominantlyhydroelectric multipurpose dams. Excluding the fraction of area in very steepgradient from the instrument set provides qualitatively identical results.

TABLE IIGEOGRAPHY AND DAM CONSTRUCTION

Number of dams

Cross-section(1999) Poverty sample Production sample

Notinteracted

Interacted with predicted number ofdams in the state

(1) (2) (3)

Fraction river gradient1.5–3%

0.278(0.122)

0.153(0.040)

0.176(0.094)

Fraction river gradient3–6%

�0.210(0.127)

�0.191(0.065)

�0.219(0.128)

Fraction river gradientabove 6%

0.014(0.033)

0.075(0.031)

0.097(0.043)

F-test for river gradient 1.764 6.372 7.68[p-value] [0.15] [0.000] [0.053]Geography controls Yes Yes YesState*year and river

gradient*yearinteractions No Yes Yes

Fixed effects State District DistrictN 374 1855 7743

Geography controls are river length (in kilometers), district area (in sq. kms), three elevation variables(fraction district area with elevation 250–500 m, 500–1,000 m, and above 1,000 m, respectively), three districtgradient variables (fraction district area with gradient 1.5–3%, 3–6%, and above 6%, respectively). Columns (2)and (3) regressions also include a full set of state*year interactions and river gradient*year interactions. Columns(2) and (3) regressions include a full set of state*year interactions and river gradient*year interactions. For theseregressions the geography controls and the river gradient measures are all interacted with predicted dams. Thecolumn (2) regression is estimated by OLS with standard errors clustered by NSS region*year and the column (3)regression by GLS with standard errors clustered by district. Regression coefficients are multiplied by 100.Standard errors are in parentheses. In columns (1) and (2) the sample includes 374 districts as defined by 1981census. The poverty sample includes the years 1973, 1983, 1987, 1993, and 1999. The production sample includesannual data for 271 Indian districts (using the 1961 Indian census definition) for the years 1971–1999. Missingdistrict-year observations account for actual sample size.

619DAMS

TA

BL

EII

ID

AM

SA

ND

AG

RIC

UL

TU

RE

Are

aIn

puts

Agr

icu

ltu

ral

prod

uct

ion

Gro

ssir

riga

ted

area

Gro

sscu

ltiv

ated

area

Fer

tili

zer

use

Pro

duct

ion

Yie

ldP

rodu

ctio

n

Lev

elL

ogL

evel

Log

All

crop

sW

ater

-in

ten

sive

crop

sN

on–w

ater

-in

ten

sive

crop

s

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Par

tA

.FG

LS

Dam

sO

wn

dist

rict

14.5

28(1

3.30

0)0.

131

(0.1

56)

114.

493

(47.

838)

0.09

4(0

.059

)0.

231

(0.3

42)

0.18

4(0

.334

)0.

152

(0.1

96)

0.06

3(0

.334

)0.

640

(0.5

85)

Ups

trea

m17

.830

(12.

639)

0.19

8(0

.162

)77

.641

(48.

233)

0.02

8(0

.054

)0.

256

(0.3

39)

0.53

0(0

.155

)0.

227

(0.1

41)

0.56

9(0

.243

)0.

801

(0.3

07)

Par

tB

.Fea

sibl

eO

ptim

alIV

Dam

sO

wn

dist

rict

232.

092

(235

.847

)0.

728

(1.0

02)

325.

358

(263

.509

)0.

875

(0.5

90)

0.56

3(1

.244

)0.

085

(0.6

99)

�0.

033

(0.4

51)

0.36

6(0

.782

)�

0.10

5(1

.349

)U

pstr

eam

49.7

54(2

2.33

9)0.

328

(0.1

54)

58.6

02(3

5.67

4)0.

088

(0.0

62)

0.16

9(0

.175

)0.

341

(0.1

18)

0.19

3(0

.097

)0.

470

(0.1

54)

0.18

1(0

.307

)N

4,53

64,

536

4,52

24,

522

4,52

17,

078

7,07

77,

143

6,78

6F

irst

stag

eF

-sta

tist

ic(o

wn

dist

rict

)8.

488.

488.

518.

518.

59.

229.

229.

039.

14

Reg

ress

ion

sin

clu

dedi

stri

ctfi

xed

effe

cts,

stat

e*ye

arin

tera

ctio

ns,

inte

ract

ion

ofth

en

um

ber

ofpr

edic

ted

dam

sin

the

stat

ew

ith

dist

rict

grad

ien

t,ki

lom

eter

sof

rive

r,di

stri

ctar

ea,

and

dist

rict

elev

atio

nan

dri

ver

grad

ien

t*ye

arin

tera

ctio

ns

(see

not

esto

Tab

leII

for

afu

llde

scri

ptio

nof

geog

raph

yva

riab

les)

.Th

eyal

soin

clu

dein

tera

ctio

nof

the

nu

mbe

rof

pred

icte

dda

ms

inth

est

ate

wit

h(a

vera

ge)g

radi

ent,

kilo

met

ers

ofri

ver,

area

and

elev

atio

nin

ups

trea

mdi

stri

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rive

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adie

nt

inu

pstr

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dist

rict

s*ye

arin

tera

ctio

n,a

nd

anin

dica

tor

for

wh

eth

erth

edi

stri

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asan

yu

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dist

rict

s.R

egre

ssio

nco

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cien

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ult

ipli

edby

100.

Sta

nda

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,clu

ster

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dist

rict

,are

repo

rted

inpa

ren

thes

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rodu

ctio

nan

dyi

eld

vari

able

sar

ein

logs

.W

eu

seth

em

onet

ized

valu

eof

prod

uct

ion

for

six

maj

orcr

ops

(des

crib

edin

not

esto

Tab

leI)

.Y

ield

isde

fin

edas

crop

prod

uct

ion

per

un

itof

lan

d(R

s.pe

rh

ecta

re).

Non

wat

er-i

nte

nsi

vecr

ops

are

sorg

hu

m(j

owar

),pe

arlm

ille

t(b

ajra

),an

dm

aize

,an

dw

ater

-in

ten

sive

crop

sar

ew

hea

t,ri

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nd

suga

rcan

e.T

he

sam

ple

incl

ude

san

nu

alda

tafo

r27

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stri

cts

in13

stat

es(d

efin

edby

1961

cen

sus

bou

nda

ries

).A

rea

and

fert

iliz

erda

taco

ver

1971

–198

7an

dpr

odu

ctio

nan

dyi

eld

data

1971

–199

9.D

evia

tion

sin

sam

ple

size

are

due

tom

issi

ng

data

.T

he

last

row

prov

ides

the

F-s

tati

stic

sfr

omth

ere

gres

sion

ofth

en

um

ber

ofda

ms

inth

edi

stri

cton

the

pred

icte

dn

um

ber

ofda

ms

inth

eow

ndi

stri

ct.


TA

BL

EV

ID

AM

SA

ND

RA

INF

AL

LS

HO

CK

S

Agr

icu

ltu

ral

prod

uct

ion

Hea

dcou

nt

rati

oP

over

tyga

p

(1)

(2)

(3)

(4)

(5)

(6)

Rai

nsh

ock

0.06

5(0

.030

)0.

008

(0.0

44)

�0.

041

(0.0

19)

�0.

036

(0.0

26)

�0.

012

(0.0

07)

�0.

0001

(0.0

10)

Dam

s�

0.01

1(1

.227

)0.

109

(1.2

28)

0.76

5(0

.324

)0.

713

(0.3

20)

0.29

4(0

.111

)0.

255

(0.1

08)

Dam

s*ra

insh

ock

0.89

8(0

.364

)�

0.24

3(0

.191

)�

0.20

3(0

.088

)U

pstr

eam

dam

s0.

722

(0.1

97)

0.73

4(0

.195

)�

0.14

9(0

.067

)�

0.13

0(0

.068

)�

0.03

8(0

.019

)�

0.03

0(0

.019

)U

pstr

eam

dam

s*ra

insh

ock

�0.

184

(0.0

92)

0.10

9(0

.059

)0.

034

(0.0

22)

N7,

078

7,07

81,

799

1,79

91,

799

1,79

9

All

colu

mn

sre

port

2SL

Sre

gres

sion

s.R

egre

ssio

ns

incl

ude

dist

rict

fixe

def

fect

s,st

ate*

year

inte

ract

ion

s,in

tera

ctio

nof

the

nu

mbe

rof

pred

icte

dda

ms

inth

est

ate

wit

hdi

stri

ctgr

adie

nt,

kilo

met

ers

ofri

ver,

dist

rict

area

,an

ddi

stri

ctel

evat

ion

and

rive

rgr

adie

nt*

year

inte

ract

ion

s(s

een

otes

toT

able

IIfo

ra

full

desc

ript

ion

ofge

ogra

phy

vari

able

s).

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eyal

soin

clu

dein

tera

ctio

nof

the

nu

mbe

rof

pred

icte

dda

ms

inth

est

ate

wit

h(a

vera

ge)

grad

ien

t,ki

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eter

sof

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r,ar

eaan

del

evat

ion

inu

pstr

eam

dist

rict

s,ri

ver

grad

ien

tin

ups

trea

mdi

stri

cts*

year

inte

ract

ion

s,an

dan

indi

cato

rfo

rw

het

her

the

dist

rict

has

any

ups

trea

mdi

stri

cts.

All

coef

fici

ents

are

mu

ltip

lied

by10

0.S

tan

dard

erro

rsre

port

edin

pare

nth

eses

.Th

ese

are

clu

ster

edby

dist

rict

inco

lum

ns

(1)–

(2),

and

byN

SS

regi

on*y

ear

inco

lum

ns

(3)–

(6).

Rai

nsh

ock

isth

efr

acti

onal

ann

ual

devi

atio

nof

dist

rict

rain

fall

from

its

his

tori

cm

ean

(defi

ned

over

1971

–199

9).

Agr

icu

ltu

ralp

rodu

ctio

nis

inlo

gs.W

eh

ave

ann

ual

agri

cult

ura

ldat

afo

r27

1di

stri

cts

and

the

year

s19

71–1

999,

and

pove

rty

data

for

374

dist

rict

san

d19

73,1

983,

1987

,199

3,an

d19

99.

Mis

sin

gdi

stri

ct*y

ear

obse

rvat

ion

sac

cou

nt

for

actu

alsa

mpl

esi

ze.


TA

BL

EV

III

DA

MS

AN

DR

UR

AL

WE

LF

AR

E

Hea

dcou

nt

rati

o

Per

-cap

ita

expe

ndi

ture

Ori

gin

alA

ssu

me

poor

in-m

igra

nts

Ass

um

eri

chin

-mig

ran

tsP

over

tyga

pG

ini

coef

fici

ent

Agr

icu

ltu

ral

wag

egr

owth

Mal

aria

inci

den

ce

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Par

tA

.O

LS

/F

GL

SD

ams

Ow

ndi

stri

ct�

0.28

9(0

.115

)0.

273

(0.0

84)

0.40

7(0

.083

)0.

174

(0.0

81)

0.08

1(0

.030

)0.

014

(0.0

27)

0.01

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.043

)0.

60(0

.89)

Ups

trea

m0.

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(0.0

57)

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083

(0.0

39)

�0.

079

(0.0

38)

�0.

082

(0.0

38)

�0.

027

(0.0

13)

0.00

7(0

.013

)0.

057

(0.0

20)

0.20

(0.6

5)

Par

tB

.2S

LS

/F

easi

ble

Opt

imal

IVD

ams

Ow

ndi

stri

ct�

0.45

7(0

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)0.

772

(0.3

24)

0.87

9(0

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)0.

651

(0.3

15)

0.29

7(0

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)0.

104

(0.1

39)

�0.

045

(0.2

42)

�0.

40(2

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Ups

trea

m0.

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(0.0

84)

�0.

154

(0.0

68)

�0.

149

(0.0

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150

(0.0

66)

�0.

039

(0.0

20)

0.00

0(0

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)0.

069

(0.0

31)

0.07

(0.5

2)N

1,79

91,

799

1,79

91,

799

1,79

91,

794

4,27

27,

001

Fir

stst

age

F-s

tati

stic

(ow

ndi

stri

ct)

7.71

7.71

7.71

7.71

7.71

7.71

8.71

10.9

5

Reg

ress

ion

sin

clu

dedi

stri

ctfi

xed

effe

cts,

stat

e*ye

arin

tera

ctio

ns,

rive

rgr

adie

nt*

year

inte

ract

ion

s,an

din

tera

ctio

nof

nu

mbe

rda

ms

inth

est

ate

wit

h(i

)di

stri

ctgr

adie

nt

vari

able

s,(i

i)ki

lom

eter

sof

rive

ran

ddi

stri

ctar

ea,a

nd

(iii

)ele

vati

onva

riab

les

and

rive

rgr

adie

nt*

year

inte

ract

ion

s(s

eeT

able

IIfo

ra

full

desc

ript

ion

ofth

ege

ogra

phy

vari

able

s).T

hey

also

incl

ude

inte

ract

ion

ofth

en

um

ber

ofda

ms

inth

est

ate

wit

h(a

vera

ge)g

radi

ent,

kilo

met

ers

ofri

ver,

area

and

elev

atio

nin

ups

trea

mdi

stri

cts,

rive

rgr

adie

nt

inu

pstr

eam

dist

rict

s*ye

arin

tera

ctio

ns,

and

anin

dica

tor

for

wh

eth

erth

edi

stri

cth

asan

yu

pstr

eam

dist

rict

s.R

egre

ssio

nco

effi

cien

tsar

em

ult

ipli

edby

100.

Col

um

ns

(1)–

(6)

regr

essi

ons

repo

rtO

LS

(Par

tA

)an

dIV

(Par

tB

)es

tim

ates

.Sta

nda

rder

rors

,clu

ster

edby

1,97

3N

SS

regi

on*y

ear,

are

inpa

ren

thes

es.T

he

un

itof

anal

ysis

isth

eIn

dian

dist

rict

asde

fin

edby

1981

cen

sus,

we

hav

eda

tafo

r37

4di

stri

cts

and

year

s19

73,1

983,

1987

,199

3,an

d19

99.C

olu

mn

(7)r

egre

ssio

nco

ver

1971

–198

7fo

r27

1di

stri

cts

(as

defi

ned

by19

61ce

nsu

s).C

olu

mn

(8)r

egre

ssio

nco

vers

1975

–199

5fo

r41

3di

stri

cts

(defi

ned

by19

81ce

nsu

s).I

nbo

thco

lum

ns

we

repo

rtF

GL

S(P

art

A)

and

Fea

sibl

eO

ptim

alIV

(Par

tB

)es

tim

ates

wit

hst

anda

rder

rors

clu

ster

edby

dist

rict

.Per

-cap

ita

expe

ndi

ture

isin

loga

rith

ms.

Agr

icu

ltu

ral

wag

egr

owth

isde

fin

edas

log

(wag

e(t)

�w

age(

t�

1)).

Col

um

n(2

)u

ses

hea

dco

un

tra

tio

figu

res

asco

mpu

ted

from

NS

Sda

ta.C

olu

mn

s(3

)an

d(4

)ad

just

this

usi

ng

the

Tab

leV

in-m

igra

tion

esti

mat

es.C

olu

mn

(3)a

ssu

mes

in-m

igra

nts

are

poor

,an

dco

lum

n(4

)in

-mig

ran

tsar

eri

ch.M

alar

iain

cide

nce

ism

easu

red

aslo

gan

nu

alP

aras

ite

Inci

den

ce(A

PI)

�lo

g(N

o.of

bloo

dsm

ears

fou

nd

posi

tive

for

mal

aria

/tot

alpo

pula

tion

un

der

surv

eill

ance

).


organize themselves and obtain compensation in nonlandlorddistricts, then the poverty impact of dam construction should bemuted in these districts. To examine this, we construct and use anonlandlord dummy that equals one: The tax revenue system ofthe district was not landlord-based prior to independence.

In Table IX, we report regressions, which include the sepa-rate interactions of the dam’s variable with the 1971 districttribal population share and the nonlandlord district dummy asadditional regressors (our instrument set is as before, plus theinteraction with the tribal and landlord variables). Our sample isrestricted to districts that were under direct British rule.

Column (1) shows that the impact of dams on agriculturalproduction did not differ across landlord and nonlandlord dis-tricts. Nor did it vary with the tribal population share. Thissuggests that technological rather than institutional factors de-

TABLE IXINSTITUTIONS AND DAMS: 2SLS ESTIMATES

Agriculturalproduction

Headcountratio Poverty gap

(1) (2) (3)

Dams �0.439(2.129)

1.072(0.539)

0.332(0.178)

Dams*nonlandlorddummy

�0.125(1.067)

�0.639(0.309)

�0.193(0.102)

Dams*tribalpopulation share

1.354(2.637)

0.711(0.790)

0.087(0.276)

Upstream dams 1.015(0.708)

�0.393(0.293)

�0.131(0.102)

Upstream dams*Nonlandlorddummy

0.160(0.705)

0.196(0.264)

0.061(0.085)

Upstream dams*tribalpopulation share

�0.609(0.701)

�0.057(0.191)

�0.015(0.060)

N 4,090 914 914

The regressions include district fixed effects, state*year interactions, river gradient*year interactions,and interaction of (i) district gradient variables, (ii) kilometers of river and district area, and (iii) elevationvariables (see Table II for a full description of the geography variables) with number of dams in the state (weuse the predicted number in column (1) and actual number in columns (2) and (3)). They also includeinteraction of the number of dams in the state with (average) gradient, kilometers of river, area and elevationin upstream districts, an indicator for whether the district has any upstream districts and river gradient inupstream districts*year interactions. In column (1) we use predicted number of dams in a state. Standarderrors in column (1) are clustered by district and in columns (2) and (3) by NSS region*year. The sample isrestricted to the 151 districts under British direct rule. The nonlandlord dummy is a district-level dummywhich equals one if the majority of land in the district was under nonlandlord arrangements for land taxationpurposes (from Banerjee and Iyer [2005]). The tribal population share is the fraction of district populationthat belongs to a tribal group, as measured in 1971. All coefficients are multiplied by 100.


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