韩国对外经济政策研究院（KIEP）：人口结构红利和经济增长：印度的案例

September6,2023

Vol.13No.32

ISSN2233-9140

DemographicDividendand

EconomicGrowth:ExploringtheCaseofIndia

YoonJaeRoAssociateResearchFellow,IndiaandSouthAsiaTeam,CenterforAreaStudies(yjro@kiep.go.kr)

JiwonParkAssociateResearchFellow,EmergingCooperationAgendaTeam,CenterforInt’lDevelopmentCooperation(jiwonpark@kiep.go.kr)

I.Introduction

Indiahasemergedasthemostpopulouscoun-tryin2023,surpassingevenChina,whichwaspreviouslyknownforitshighpopulation.In-dia'sgrowingpopulationhasgeneratedcon-siderableinterest,promptingcomparisonswithChina'sdemographiclandscape.ThecomparisonbetweenIndiaandChinaholdsaninherentinterestbeyondjusttheirsheerpopu-lationsizes,asthedynamicofIndia'spopula-tiongettingyoungerwhileChina'sisgettingoldercontributessignificantlytotheongoingcontrastbetweenthesetwonations.

Therelationshipbetweenpopulationandeco-nomicperformancehasbeenanongoingtopicofresearch.Initially,thefocuswasonthesizeandgrowthrateofthepopulation.Morere-cently,however,attentionhasshiftedtoun-derstandinghowagestructureaffectseco-

nomicgrowth.Developednationsarecur-

rentlymakingstructuraladjustmentstoad-

dresstheconsequencesofdecliningfertility

ratesandagrowingelderlypopulation.Incon-

trast,manydevelopingnationsareexperienc-

inggrowthintheiryouthandworking-age

populations,offeringthepotentialforademo-

graphicdividend.Thisdividendcouldfuel

short-termeconomicexpansion.Whenthe

shareoftheyoungworking-agegroupin-

creases,itcanhaveapositiveimpacton

growthduetotheirhigherproductivityand

greatercontributiontotheeconomy.Thisde-

mographicdividendmanifestsitselfina

higherproportionofeconomicallyactiveindi-

vidualswithinthepopulation,resultingin

lowerdependencyratiosandhighereconomic

growthrates.

September6,2023

2

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

ThisstudylooksatIndia'ssituation.India'spopulationhasbeenchanging,includinghowmanypeoplethereare,howfastthepopulationisgrowing,andhowoldthepeopleare.ThenumberofpeopleinIndiahasgrownquickly,from446millionin1960toabout1.42billionin2022.

1

It'sprojectedtoreach1.7billionby2060.

2

Theageofthepopulationisalsochanging.India'sagegroupshavebeenchang-ingforthepast50years.Currently,about26%ofthepeopleinIndiaareunder15yearsold,about68%arebetween15and64yearsold(workingage),andabout7%are65orolder.By2050,thesefiguresareexpectedtochangeto18%,67%,and15%,respectively.

3

Inthiscontext,thispaperexamineshowchangesinthepopulationwillaffectIndia'seconomy.Specifically,weexaminehowshiftsinagedistributionaffectIndia'seconomicdrivers.

Since1990,numerousstudieshaveexploredtheconnectionbetweenpopulationchangeandeconomicgrowth.Theconvergencegrowthmodel,whichincorporatesdemo-graphictransition,aidsintheeconomicgrowthanalysis.

4

Thedemographictransitionwillreshapethelaborforce,impactingthela-bormarketandindustrystructureovertime.Indiahasasubstantialyounglaborforce,withabout67%ofthepopulationintheworkingagecategory.Weexaminehowthegrowthof

1WorldBankDataPortal(accessedAugust15,2023)2UN,WorldPopulationProspects2022.

3WorldBankDataPortal(accessedAugust15,2023)4BloomandWilliamson(1998)demonstratedhowit boostedEastAsianeconomiesin1965-1990via workforceexpansion.BloomandCanning(2004) foundthesamepositivelinkacrosscountries.CaseslikeBloom,Canning,andMalaney(2000)andMason

thisworkingagepopulationaffectsIndia's

economicgrowthandlabormarket,using

state-leveldata.SeveralpapersexploreIndia's

demographicdividendimpact,likeAiyarand

Mody(2011),Kumar(2014),andLadusingh

andNarayana(2012),focusingonIndia'seco-

nomicbenefits.Mostimportantly,Aiyarand

Mody(2011),analyzeIndia'sNationalSample

Survey(NSS)dataandfindthata1%increase

inpopulationleadstoa0.2percentagepoint

riseinpercapitaincome.Despiteexistingre-

search,agappersistsinunderstandingIndia's

potentialdemographicdividend.Priorstudies,

likethosementioned,focusedontheopportu-

nitiestiedtodemographicshiftsuntilaround

2000.AiyarandMody(2011)exploredpopu-

lation-economicgrowthlinkusing1980-2001

data,andotherstudiesfollowedsuitwithearly

2000sdata.Thislimitationstemsfromthe

scarcityofrecentdata.TheNationalSample

Survey(NSS)wasdiscontinuedafter2011-

2012,andthelatestcensuswasin2011,which

wasdelayedto2020duetoCovid-19.Thispa-

perextendsthescopeofthestudytoinclude

dataupto2019,achievedbymergingtwoda-

tasetswiththemostrecentinformation.Fur-

thermore,ouranalysisencompassesdiverse

economicdimensionswithinIndia.Inaddition

toexamininggrowthinpercapitaGDPatthe

statelevel,wedelveintotheshiftsinemploy-

(2001)attributedtheEastAsiansuccesstopopula-

tion.Persson(1999)linkedagecompositiontoUSper-

formance.Feyrer(2007)foundarelationshipbetween

workerageandproductivityusingOECDanddevelop-

ingcountrydata,explaining25%oftheOECD-low-in-

comeproductivitydifferenceandthedivergencedur-

ingthe1960-1990period.Kδgel(2005)linkedthe

youthdependencyratiotolowproductivitygrowth.

3

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

mentpatternsacrosssectorsandthevalueaddedbydifferentsectors.

Theremainderofthearticleisorganizedasfollows.SectionIIoutlinesdataandmethod-ology.SectionIIIestimatesthedemographicdividendacrossIndianstatesduringthe1999–2019period.SectionIVconcludes.

II.EmpiricalStrategy

Weusethedevelopmentaccountingframe-workasatooltoexploretherelationshipbe-tweendemographiccharacteristicsandpercapitaoutputinIndia.Oneofthefundamentaltenetsofthedevelopmentaccountingframe-workisthatthedemographicagestructureplaysapivotalroleinshapingpercapitaout-putbyinfluencingbothfactoraccumulationandefficiency(HallandJones1999;Caselli2005;HsiehandKlenow2010).Multiplethe-oreticalpathwaysdemonstratehowtheagestructuresignificantlyinfluencespercapitaoutputbyinfluencingbothfactoraccumula-tionandefficiency.First,theagestructureim-pactsaggregatesavingrates,drivenbyhetero-geneoussavingbehavioracrossagegroupsinlinewiththelifecyclehypothesis.Second,theemploymentrateisprofoundlyaffectedbytheagestructureduetotheheterogeneityinlaborsupplyobservedacrossdistinctagegroups.Fi-nally,theheterogeneityineducationandex-periencelevelsamongdifferentagegroupsisassociatedwiththeaveragehumancapitalofthelaborforce,therebyfurtheraffectingpercapitaoutput.

Toanalyzetheinteractionbetweendemo-

graphicstructureandeconomicgrowth,we

usethefollowingmodel:

logyit=Ditβ+μi+τt+εit(1)

Here,yitrepresentstheeconomicstatusof

stateiinyeart,Ditdenotestheexplana-

toryvariablerelatedtodemographicstructure,

andμi,τtstandforstateandyearfixedef-

fects,respectively.Theerrortermisdenoted

asεit.

Animportantconsiderationintheaboveanal-

ysisistheselectionofappropriatedemo-

graphicvariables.Includingalargenumberof

agegroupsintheregressioncouldleadtomul-

ticollinearityissues,whichcouldhinderob-

tainingthedesiredresults.Therefore,itiscru-

cialtometiculouslychoosetheoptimalsubset

ofagestructurevariablestouncoverthegenu-

inerelationshipbetweendemographicstruc-

tureandeconomicgrowth.Followingthe

methodologyoutlinedbyGomezandDeCos

(2008)andZhang,Zhang,andZhang(2015),

weincludetwocrucialvariables:theshareof

theworking-agepopulationandtheshareof

prime-ageindividualswithintheworking-age

group.Forthepurposeofthisstudy,wedefine

theworking-agepopulationasindividuals

aged15to64,andtheprime-agepopulationas

thoseaged30to49.

Theregressionmodelcombiningthetwopa-

persisasfollows:

logyit=γlogwit+δpit+λcit

+θxit+μi+τt+εit(2)

4

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

witrepresentstheproportionofthework-ing-agepopulation,whilepitdenotestheshareofprime-ageindividualswithintheworking-agepopulation.xitincorporatestwocriticalcontrolvariables:laborcost,whichincludesbothwageandassociatedcosts,andstate-levelelectricitysupply,servingasaproxyfortheproductioncapacity.Addition-ally,citreflectstheproportionofcollege-ed-ucatedindividualswithintheworking-agepopulation,capturingtheinfluenceofhigh-ed-ucatedworkersoneconomicgrowth.Forthedependentvariables,weusetotalstateproduc-tionpercapita,sectoralvalue-added,andsec-toralemploymentrate.

III.Data

1.PopulationandLaborMarketData

Thedemographicandemploymentdataatthestatelevelaredrawnfromacollectionofma-jordatasets.Firstly,weusetheEmploymentandUnemploymentSurveys(EUS)conductedbytheNationalSampleSurveys(NSS).Initi-atedin1950,theNSSisacomprehensivena-tionwidesurveydesignedtocovervariousso-cio-economicaspectsofthecountry'spopula-tion.Thesurveyaimstoprovidereliableandup-to-dateinformationonawiderangeoftop-ics,includingincome,employment,education,health,consumption,housing,andmore.TheEmploymentandUnemploymentsurveysare

conductedaspartofspecificrounds,withir-

regularfrequency.Inthispaper,weutilize

datafromthe55th(1999)and66th(2009)

roundsoftheEUStoexamineIndia’slabor

marketdynamicspost-2000.Duetothecessa-

tionoftheEmploymentandUnemployment

SurveybytheNSSOfficein2012,wesupple-

mentourdatasetwiththeConsumerPyramids

HouseholdSurvey(CPHS)conductedbythe

CenterforMonitoringIndianEconomy

(CMIE).CPHSisoneofthelargesthousehold

panelsurveysinIndia,followingover170,000

householdseachyeartoprovideinformation

onconsumerspending,income,employment,

education,andothersocioeconomicindicators.

Ouranalysisfocusesontheroundconducted

in2019.

5

Thetwosurveysdonotprovideweightsto

preciselyestimatethetotalpopulation.Toes-

timatethecountofindividualsemployedin

eachsectorandstate,wederivethesector-

wisepopulationdistributionwithineachstate

usingsurveydata.Thisshareisthenmulti-

pliedbythestate-level(estimated)population

forthecorrespondingyear,sourcedfromthe

CEICGlobalDatabase.Thenumberofwork-

ingage(15-64)andprimeage(30-49)ineach

stateisalsoestimatedusingthesharederived

fromourdatasetandthestate-levelpopulation

figuresfromtheCEIC.

Indiahasundergonesignificantchangesinits

administrativeboundariessincetheyear2000.

5OtherroundsofEUSandCPHSareusedtocalculatethetrendsoftotalpopulationandagestructureofIn-

dia.

5

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

Notableinstancesincludethecreationofthreenewstatesin2000:Chhattisgarh,Jharkhand,andUttarakhand,whichemergedasdistinctentitiesfromMadhyaPradesh,Bihar,andUt-tarPradeshrespectively.In2014,TelanganawasestablishedthroughthebifurcationofAn-dhraPradesh.Additionally,in2019,JammuandKashmirunderwentareorganization,leadingtotheformationoftwoseparateterri-tories:JammuandKashmir,andLadakh.TheNSSandCPHSdataarealignedwiththead-ministrativeboundariesinthecorrespondingyears.Toensuredatacomparabilityovertime,wecombineUttarPradeshandUttarakhand,BiharandJharkhand,andMadhyaPradeshandChhattisgarh,basedontheadministrativeboundariesexistingin1999.

It'sworthnotingthattheCPHSdoesnotinclude

certainsmallerborderstatesandUnionTerrito-

ries(UTs)locatedinthenortheast,specificis-

lands,andasinglesmallmainlandUT.Theseex-

cludedregionsconsistofstatessuchasAruna-

chalPradesh,Manipur,Meghalaya,Mizoram,

Nagaland,Sikkim,andTripura,aswellasUTs

likeAndamanandNicobarIslands,Dadraand

NagarHaveliandDamanandDiu,Ladakh,and

Lakshadweep.Thisexclusionmarginallyim-

pactsthesurvey'srepresentativenessbecause,

collectively,thesestatesandUTsaccountfor

only1.5%oftheIndia’stotalpopulation(Vyas

2020).Notably,JammuandKashmir,account-

ingfor1.01%ofthepopulation,isalsonotin-

cludedinoursample.Asaresult,ourfinalsam-

pleincludes14stategroups.

Table1.NSSvsCPHSComparisons

NSS

CPHS

All

Y=1999

Y=2004Y=2009

Y=2011

Y=2014Y=2017

(1)

(2)

(3)(4)

(5)

(6)(7)

Age

27.73

25.53

26.4027.66

28.08

29.8831.92

[18.96]

[18.85]

[18.96][19.00]

[19.08]

[18.57][18.53]

Male

0.52

0.51

0.510.52

0.51

0.530.53

[0.50]

[0.50]

[0.50][0.50]

[0.50]

[0.50][0.50]

Hindu

0.83

0.82

0.820.82

0.81

0.840.86

[0.38]

[0.38]

[0.39][0.38]

[0.39]

[0.37][0.35]

Muslim

0.12

0.12

0.130.13

0.14

0.100.11

[0.33]

[0.33]

[0.33][0.33]

[0.35]

[0.30][0.31]

SC/ST

0.29

0.29

0.280.29

0.28

0.300.32

[0.45]

[0.45]

[0.45][0.45]

[0.45]

[0.46][0.46]

HighSchool

0.11

0.07

0.090.12

0.13

0.140.17

[0.31]

[0.25]

[0.28][0.32]

[0.34]

[0.35][0.38]

Observation

3,273,902

595,529

602,832459,784

456,999

633,288525,470

6

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

2.State-levelProductandValue-addedData

WeemploythetotalNetStateDomesticProduct(NSDP)andthesectoralNetStateValue-AddedprovidedbytheReserveBankofIndia(RBI)todepictboththeoverallandsectoraleconomicgrowthatthestatelevel.

Thesevaluesarepresentedinrealterms;how-ever,it'simportanttonotethatthereferenceyearchangesfrom2004to2011.Tomakethedatacompatibleoverdifferenttimeperiods,westandardizetherealNSDPandvalue-addedfiguresin2011rupees.Wealsodividethefiguresbythestate-leveltotalpopulationfromCEICtoacquireper-capitavalues.Theeconomicdataatthestatelevelareaggregatedintothe14stategroupstomatchthedemo-graphicdata.

3.SummaryStatistics

Figure1illustratestherisingproportionofworking-agepeopleintheoverallpopulation,alongwiththeshareofprime-ageindividualswithintheworking-agepopulationinourdata.Theworking-agepopulationratiowas56%in1984,butithasdemonstratedrapidgrowth,reaching61%in1999andfurthersurgingto65%in2009.Notably,thisratiohassurpassed75%inboth2017and2019,particularlyintheyearsusingCPHSdata.ThisdeviationislikelyattributabletoCPHS'sinclinationtooversampletheworking-agegroupincompar-isontoNSS.Simultaneously,theshareofprime-ageindividualswithintheworking-age

demographichasexhibitedconsistentgrowth,

expandingfrom38%in1984to42%in2017.

Whencomparing2011and2017,thereisno

pronouncedjumpsimilartothesurgeob-

servedintheworking-ageproportion.This

suggeststhattheCPHSismorecompatible

whenfocusingontheworking-agepopulation.

Table2illustrateschangesinworking-ageand

prime-agepopulationproportionsacrossstate

groupsduring1999-2009and2009-2019.All

statessawpositiveshiftsinworking-agepopu-

lationsincolumns1-2,withlargerchangesin

2009-2019.For1999-2009,theaveragechange

was4.25percentagepoints,withamaximumof

8points.Incontrast,thelaterperiodaveraged

8.7points,withamaximumof17.Changesin

prime-ageproportionswithinworking-age

populationsvariedmoreacrossstatesthan

thoseincolumns1-2.For1999-2009,theaver-

agechangewas2points;for2009-2019,theav-

eragechangewas0.06points.

Thetablehighlightstwomaininsights.

Firstly,whiletheworking-agepopulationis

growinginallcountries,differentchangesin

theprimeageshareleadtovariationsinage

structure,potentiallyaffectingthedemo-

graphicdividend.Secondly,anincreaseinthe

prime-agepopulationdoesn'tnecessarily

translateintoacorrespondingriseinworking-

agepopulation.Forinstance,inRajasthanand

UttarPradesh,wherethereweresignificant

shiftsinworking-agesharesduring2009-2019,

theprime-ageshareoftheworkingagepro-

portionactuallydeclined.

7

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

Figure1.TheProportionofWorkingAgeandPrimeAgePopulation

Source:Roetal.(2022).

Table2.ChangeinWorking-AgePopulation

ChangeinWorkingAgePopulation(p.p)

ChangeinPrimeAgePopulationwithin

WorkingAgePopulation(p.p)

1999~2009

(1)

2009~2019

(2)

1999~2009

(3)

2009~2019

(4)

Punjab

6.15

11.99

-0.29

-1.28

Delhi

4.89

3.98

2.80

-3.49

Rajasthan

4.57

17.47

0.84

-0.27

UttarPradesh,Uttarakhand

4.66

14.47

1.17

-1.38

Bihar,Jharkhand

3.26

12.58

1.83

-0.62

WestBengal

5.68

5.25

1.11

-1.26

Odisha

5.42

6.97

2.81

0.28

MadhyaPradesh,Chhattisgarh

5.59

13.81

1.68

0.83

Gujarat

2.51

8.49

1.10

-0.72

Maharashtra

4.93

8.03

-0.24

0.27

AndhraPradesh

5.20

11.15

1.89

5.25

Karnataka

4.72

12.44

0.69

5.04

Kerala

0.79

6.86

1.51

-0.48

TamilNadu

1.89

7.08

3.26

-3.16

8

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

IV.Results

Table3presentsanalysisresultsonIndia'sdemographicimpactonstatedomesticproductpercapita.Theanalysisincludeshouseholdandyearfixedeffects.Columns(2)and(3)de-tailresultswithstatecharacteristicsandcol-legegraduateratioasexplanatoryvariables.Controlvariablescompriselaborcostsidenti-fyingstatelabormarketsandpowersupplyca-pacityrepresentingproductionenvironment.

Theproportionofstatecollegegraduatesisin-cludedtocontrolhigh-skilledimpact.Inthecomprehensiveanalysisshownincolumn(3),findingsindicatenoeffectofincreasedpro-ductiveandcoreworkingpopulationpropor-tionsonpercapitaeconomicgrowth.Con-versely,ariseinhigh-skilledworkerpropor-tionpositivelyaffectspercapitaoutput.

PreviousstudieshavefoundthatIndia'sin-

creaseintheproportionoftheworking-age

populationhasa"demographicdividendef-

fect"thatpromoteseconomicgrowth,butthis

studyhasshownthatsucheffectdoesnotexist.

Thereisareasonwhytheresultsofthisstudy

differfromAiyarandMody(2011),whocal-

culatedtheincreaseintheproportionofthe

working-agepopulationeverydecadefrom

1980to2001usingIndia'sNSSdata.India's

populationgrowthratebegantodeclineafter

the1980s.India'saverageannualpopulation

growthratehasfallenfrom2.3%tolessthan

2%sincethe1990s.Whencalculatingthe10-

yearpopulationgrowthratebystate,itcanbe

seenthatthegrowthratehasdeclinedsignifi-

cantlysincethe1990s.Therefore,itcanbein-

terpretedthatthedemographicdividendeffect

hadnotbeenfoundinthisstudyusingrela-

tivelyrecentdata,comparedtotheanalysisof

datafromtheperiodwhentheexistingexplo-

sivepopulationgrowthrateoccurred.

Table3.PopulationChangeandEconomicOutput

(1)

(2)

(3)

W

-0.124

0.0882

-0.189

(0.692)

(0.828)

(0.696)

P

0.709

(1.197)

0.0133

(1.335)

0.286

(1.023)

C

3.498***

(0.995)

Observations

79

79

79

R-squared

0.976

0.978

0.982

Control

YES

YES

9

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

Table4.PopulationChangeandSectoralValueAdded

(1)

Agriculture

(2)

Manufacturing

(3)

Construction

(4)

Services

W

0.282

-0.283

-0.805

-0.567

(0.931)

(1.451)

(0.752)

(0.462)

P

5.559**

(2.165)

-2.472*

(1.338)

1.931

(1.351)

4.455***

(1.153)

C

-0.382

(2.513)

5.821***

(2.079)

1.949

(1.581)

3.551***

(1.154)

Observations

79

79

79

79

R-squared

0.904

0.970

0.954

0.983

Control

YES

YES

YES

YES

TheanalysisexaminedhowchangesinIn-dia'sdemographicstructureimpactedoutputintheindustrysector.Demographicshiftshadnoinfluenceonpercapitaoutput,butsignifi-cantsectoralresultsemerged.Consistentwithpreviousfindings,anincreaseintheproduc-tivepopulationdidn'tsignificantlyalterindus-tryvalue-added.However,anincreaseinthecoreageshareenhancedvalueaddedinagri-culturalandservices.A1%pincreaseintheproductivepopulationtransitioningtothecoreageincreasedagriculturalandserviceaddedvalueperpersonby5.60%and4.46%,respec-tively.Moreover,ahigherproportionofcol-legegraduateswascorrelatedwithhigherpercapitavalueaddedinmanufacturingandser-vices.

Duetotheexpectedimpactofchangesinde-mographicstructureonindustriesintermsofemployment,anadditionalempiricalinvesti-gationwasconductedontheproportionofin-dustry-wiseemploymentinthetotaleconomy.

Thisemploymentratioperindustryisthe

numberofemployeesinagivenindustrydi-

videdbythetotalnumberofemployeeswithin

astate.AsshowninTable5,itwasfoundthat

theincreaseintheratioofthecoreagepopu-

lationhadapositiveeffectontheemployment

oftheservicesector.Specifically,ifthereisa

1percentagepointincreaseintheproportion

oftheworking-agepopulationtransitioning

fromanon-coreagetoacoreage,theemploy-

mentwithintheserviceindustrygrowsby5.18%

Analyzingtheresultsofthepreviouschange

inthevalue-addedratio,itcanbeseenthatthe

increaseinthecoreageratiotendstoincrease

thevalue-addedpercapitaofagriculture,

whiletheemploymentratio(althoughnotsta-

tisticallysignificant)inagriculturetendstode-

crease.Thiscanbeinterpretedasaresultof

theincreaseinpercapitaproductionduetothe

developmentofagriculturaltechnologyand

theincreaseintheskillsofagriculturalwork-

ers.

10

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

Table5.PopulationChangeandSectoralEmployment

(1)

Agriculture

(2)

Manufacturing

(3)

Construction

(4)

Services

W

2.489

-1.047

-0.306

1.354

(2.417)

(2.312)

(1.476)

(1.266)

P

-4.443

(4.549)

0.271

(3.436)

-1.820

(2.729)

5.181**

(1.989)

cs_N2

-7.199

(6.208)

2.980

(5.163)

0.826

(6.094)

0.790

(2.608)

Observations

78

79

79

79

R-squared

0.470

0.593

0.687

0.535

Control

YES

YES

YES

YES

V.Conclusions

Inconclusion,thispaperhasexaminedthepo-tentialforIndia'sgrowingyouthandworking-agepopulationtostimulateshort-termeco-nomicexpansion.Byanalyzingstate-leveldatafrom1999-2019,wehavefoundevidenceofademographicdividendinIndia,withagrowingworking-agepopulationcontributingtoincreasedeconomicoutput.Thisdemo-graphicdividendcomesprimarilyfromtheprimeagepopulation,whichisdefinedasthoseaged30-49yearsold,andisconcen-tratedincertainsectorssuchasagricultureandservices.Thefindingsofthisstudyarecon-

sistentwithpriorresearchonIndia’sdemo-

graphicdividendandsuggestthatthecountry

iswellpositionedtobenefitfromitsyouthful

population.However,itisimportanttonote

thatsustainingthisgrowthwillrequirecontin-

uedinvestmentineducationandinfrastructure,

aswellaspoliciesthatpromoteinclusive

growthandaddressissuesofinequalityand

socialexclusion.Overall,thepotentialfora

demographicdividendinIndiaisanexciting

development,andonethatpolicymakers

shouldtakemoreseriously.Byinvestingin

educationandinfrastructure,andpromoting

inclusivegrowth,Indiacancontinuetobuild

onitseconomicsuccessesandbecomeamajor

playerintheglobaleconomy.

11

DemographicDividendandEconomicGrowth:ExploringtheCaseofIndia

References

Aiyar,S.andA.Mody.2011.“Thedemographicdividend:EvidencefromtheIndianstates.”IMFWorkingPaper,no.WP/11/38.InternationalMonetaryFund.

Bloom,D.E.andD.Canning.2004.“Globaldemographiccha