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Rural wages in AsiaSteve Wiggins and Sharada Keats

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October 2014

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ISSN: 2052-7209

Cover photo: © World Bank Photo Collection: Rice fields in Mai Chau, Vietnam

October 2014

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• RuralwagesarerisingacrossmuchofAsia,andinsomecaseshaveacceleratedsincethemid2000s.

• Thetwomaindriversareaslow-downinthegrowthoftherurallabourforce,probablymainlyfromlowerfertilityrates,andthegrowthofmanufacturingthatattractsworkersfromruralareas.

• MostpeopleonverylowincomesinAsiaworkinagriculture:risingwagespromisetoliftmostofthemoutofextremepoverty.

• Higherruralwagesaredrivingupthecostoffoodproduction,therebycreatingopportunitiesforothercountriestoexporttoAsia.

• Theyalsocontributetohigherwagesinmanufacturing.AscostsriseinChina,forexample,itislikelythatsomeplantswillrelocatetolow-incomeAsiaandtoAfrica.

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Rural wages in AsiaSteve Wiggins and Sharada Keats

Contents

Abbreviations 5

Acknowledgements 5

Executive summary 6

1. Introduction: aims of this study 8

1.1 Motivation for this study 9

1.2 Questions posed 9

2. Background: influences on rural wages 10

2.1 Theories of rural wage formation 11

2.2 Recent studies of changing wages in rural Asia 12

2.3 Summary 19

3. Study approach, data and methods 20

3.1 Research questions 21

3.2 Approach 21

3.3 Data sources 23

4. Results 27

4.1 Description of key variables 28

4.2 Causes of changes in rural wages 28

5. Conclusions and implications 40

5.1 Discussion of findings 41

5.2 Implications 41

References 43

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Rural wages in Asia 3

Figures

Figure A: Changes in real daily wages for agricultural labour (US$ constant 2010 PPP) in four Asian countries 8

Figure 1: Bangladesh, agricultural wages, real, 1950-2006 12

Figure 2: Bangladesh, urban and rural wages, deflated by the general consumer price index, 2001-2011 13

Figure 3: China, population by age and sex, 2010 14

Figure 4: China, workforce, 1950-2050 14

Figure 5: India, real wage rates of rural casual labourers in India, 1983, 1987/88, 1993/94 and 1999/2000 at 1999/2000

prices 15

Figure 6: India, average farm wages, constant at 2011/12 prices, 1990/91 to 2011/12 16

Figure 7: India, sector-wise distribution of employment, 1983-2009/10 16

Figure 8: Indonesia, real agricultural wage rate in Java, 1983-2009, rupiah a day 18

Figure 9: Most populous Asian developing countries east of the Khyber Pass and south of Central Asia 22

Figure 10: Pathways to urbanisation in selected Asian countries, 1980/82-2010/12 23

Figure 11: Agricultural wage changes, 13 Asian countries, early and late 2000s, average annual rates 32

Figure 12: Changes in the gender wage gap in four Asian countries 33

Figure 13: Changing agricultural labour productivity, 12 Asian countries, 1995-2012, gross value production per worker,

constant US$ 2004/06 34

Figure 14: Average annual growth rate of agricultural labour productivity, 12 Asian countries, 1997-2004 and 2005-2012

34

Figure 15: Changes in value of manufacturing across 12 Asian countries, 1995-2012 35

Figure 16: Average annual growth rate of manufacturing in 12 Asian countries, 1997-2004 and 2005-2012 36

Figure 17: Changing rural working population, 12 Asian countries, 1995-2012 37

Figure 18: Average annual growth rate of rural working population in 13 Asian countries, 1997-2004 and 2005-2012 38

Figure 19: Changes in rural wages compared with those for agricultural labour productivity, manufacturing and rural

workers over two periods 38

Tables

Table 1: Population, proportion rural and agriculture’s contribution to GDP 22

Table 2: Description of data and sources on rural wages by country 24

Table 3: Time spans covered by data 25

Table 4: Data on key variables influencing rural wages and sources 26

Table 5: Real rural wages and changes for 13 Asian countries, 1995/96-2013 29

Table 7: Multivariate regression of changes in rural wages 39

Table 6: Correlation matrix between variables 39

Boxes

Box 1: Varying transitions from agrarian to industrial economies 21

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AbbreviationsBBS Bangladesh Bureau of Statistics

CCAP Centre for Chinese Agricultural Policy

CPI Consumer Price Index

FAOSTAT Food and Agriculture Organization Statistical Service

GDP Gross Domestic Product

ILO International Labour Organization

IRRI International Rice Research Institute

ISIC International Standard Industrial Classification

LSMS Living Standards Measurement Study

MGNREGA Mahatma Gandhi National Rural Employment Guarantee Act [India]

PPP Purchasing Power Parity

RMG Ready-Made Garment

UN United Nations

UNDESA UN Department of Economic and Social Affairs

UNDP UN Development Programme

Acknowledgements


WearegratefulforhelpfulcommentsprovidedbypeerreviewersProfessorRickBarichelloandAndrewNorton.OurthanksalsotoDrFutoshiYamauchiforsharingdataonIndonesianwages.

ThisreporthasbeenproducedbyODIaspartoftheproject‘Shockwatch:ManagingRiskandBuildingResilienceinanUncertainWorld’,supportedbytheUKDepartmentforInternationalDevelopment(DFID).

Executive summaryRuralwagesindevelopingcountriesmatter.Ruralwagesnotonlydirectlyaffectthewelfareofmanyofthe(very)poor,butalsoaffectthewelfareofothersthroughtheirimpactoncostsoffoodproductionandhencefoodprices.Sincemanufacturinginlow-incomecountriesoftenrecruitslabourfromthecountryside,ruralwagessettheminimumleveloffactorywagesnecessarytoattractlabour,andhencecostsofproductionandtherebythegrowthofmanufacturing.

ReportsindicatethatruralwagesinpartsofAsia,incountriessuchasBangladesh,ChinaandIndia,havebeenrisingsincethemid-2000s,andprobablyatafasterratethanbefore:SeeFigureA.Hencethisstudy:tocheckhowruralwagesarechangingforothercountriesin(East,SouthandSoutheast)Asia;tolookatpotentialcauses;andtoconsidertheimplications.Specifically,thefollowingquestionsareposed:

• What trends can be seeninruralwagesinAsiaduringthe2000s?Howmuchisthereacommonpatternacrosstheregion?

• What factors are driving the increases seen?Aboveall,dotheystemfromincreasedagriculturalproductionandproductivity,fromchangingdemography,orfromurbanisationandindustrialisation?Towhatextentdotheyreflectpublicpolicysuchasminimumwagesandpublicemploymentschemes?Whatmaybeexpectedintermsoftrendsinruralwagesoverthenextfivetotenyears?

• Ifruralwagesarerising,thenwhat are the implicationsforruraldevelopmentandpoverty,forfoodpricesandfoodsecurityandforeconomicgrowth,bothinAsiaandinotherpartsofthedevelopingworld?

Ruralwagescanbeseenasinfluencedprimarilybysupplyanddemandinlabourmarkets–albeitwithimperfections–orasonesideofadualeconomy,wherelabourinatraditional(largelyrural)economyworksatlowproductivity,separatedfromthelabourmarketsofamoreproductivemodernsector.DualismmayhavecontributedtoAsianindustrialisationbyprovidingapoolofverycheaplabourfromthecountryside,butincreasinglyprobablydoesnotapplyinthe2000s.

Recentliterature,bothdescriptiveandanalytical,reportssimilarfindingsinseveralcountriesofAsia:

• InBangladesh,China,IndiaandIndonesia,ruralwagesarerising,apparentlyfasterinthesecondhalfofthe2000sthanbefore.

• Growthinmanufacturingandjobsoffthefarm,especiallyconstructionincities,isdrawinglabouroffthefields.

• ForChina,atleast,thepullofthecityiscoincidingwithreductionsinthelabourforceasthelowfertilityofthepast30yearscomesintoplay.

• Itislesscleartowhatextentthegrowthoftheruralnon-farmeconomyorincreasesinagriculturalproductivityhaveledtoincreaseddemandforlabourinruralareas.

• Althoughpublicemploymentprogrammesmaycontributetohigherruralwages,theymaynotdrivethemasstronglyaseconomicgrowth.Thatsaid,theIndianMahatmaGandhiNationalRuralEmploymentGuaranteeAct(MGNREGA)schememaybedisproportionatelyvaluabletofemaleworkersandtothoseineconomicallylaggingregions.

Dataonruralwages,agriculturallabourproductivity,growthofmanufacturingandruralworkingpopulationwerecollectedfromsecondarysourcesforthe13mostpopulouscountriesofEast,SouthandSoutheastAsia,forthe2000s.Ruralwageserieswereincompleteinseveralcases,soonlyforsixcountrieswasitpossibletolookatchangesinwagesintheearlyandlate2000s.

ResultsRural wagesroseinthe2000sinalmostallcasesobserved.Inseveralcountries,includingChinaandIndia,theriseacceleratedfromthemid-2000s.Forexample,inBangladesh,theaverage(male)ruralwageroseinrealtermsby45%between2005and2010,inIndiaby35%between2005and2012andinChinaby92%between2003and2007.Similartrendscanbeseenforothercountrieswheredataareavailable,suchasIndonesiaandVietnam.

Despitegrowth,levelsofpaystillremainedlowintheearly2010s,withfewcountriesseeingmorethan$5adaypaid.Ruralwagesforwomenwereinmostcasesbetweenaquarterandone-thirdlessthanthosepaidtomen,althoughinmostcountriesthegaphasnarrowed.

Forpotentialdriversofruralwages,thefollowingpatternswereseen:

• Agricultural labour productivityroseinallcasesexceptPakistaninthe2000s,inmostcountriesfasterinthelatterhalfofthedecade,withsevencountriesseeingaveragegrowthof2.5%ayearormore.

• Manufacturing outputgrewrapidlyacrossmostoftheregioninthe2000s.Growthofmanufacturingacceleratedbetween1997-2004and2005-2012forChina,India,Indonesia,Bangladesh,thePhilippinesandSriLanka.Infivecases,growthslowed,althoughfortheRepublicofKoreaandVietnamratesremainedhigh.

• Inthemid-1990s,rural working populationsroseinallcasesotherthantheRepublicofKorea.By2012,numberswerefallinginChina,Malaysia,ThailandandSriLanka–withIndonesiarisingslightlyafterseveralyearsoffalls.Inthesecases,aturningpointhasbeenpassed.Anothergrouphasseenruralworking

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populationrisingthroughouttheperiod:Burma/Myanmar,Philippines,VietnamandSouthAsia.

Whatexplainschangesinruralwages?Across-countryregressionsuggestsruralwagesriseasruralworkingpopulationsdecline,andasmanufacturingoutputgrows.Changesinagriculturallabourproductivitymaybeassociatedwithhigherwages,buttheestimateprovedinsignificantandlowinthepresenceofthesetwomaindrivers.Asmallbutsignificanttimeshiftersuggestswagesgrewfasterinthesecondhalfofthe2000s,independentlyofchangeinothervariables.

Demographyplaysasignificantrole,moresothanmighthavebeenexpected.Indeed,thelargestdifferencesbetweencountriesariseintheruralworkingpopulation,withasharpdistinctionbetweenthosecountrieswheretheruralworkforceisnowshrinkingandthosewhereitcontinuestoincrease.Changesinruralworkingpopulationmaybethesinglemostpowerfuldriver,but,sincemigrationisincorporatedwithinthevariable,itisnotapurelyexogenousdriver.Asmanufacturinggrows,itisexpectedthatsomefactoryworkerswillberecruitedfromthecountryside,sothemigrationcomponentislinkedtomanufacturing.

ImplicationsWillruralwagesinAsiacontinuetoincreaseinthefuture?Theywillifthetwomaindriverscontinuealongrecenttrendsintothefuture.Fallingfertilityratessincethe1970sacrossAsiamoreorlesslockinreducedruralpopulationsforthefuture,anditishardtoimaginethatmanufacturingwillceasetogrow.Hence,itseemsruralwagescanbeexpectedtoriseinthefuture.

Thiscouldhaveprofoundimplicationsforpoverty,agricultureandfoodpricesandmanufacturing.

Rising rural wages will put a floor to low rural incomes–atleastforthoseabletowork–and,indeed,probablytoincomesthroughouttheeconomy,sinceruralwageshavetendedtomarkthelowestreturnstolabouronoffer.Hence,risingruralwagesshouldgreatlyreducepovertyformosthouseholdsthathaveworkingmembers.Thatsaid,ruralwagesinmanycountriesarestilllowandneedtorise–perhapstodoubleinsomecases–beforehouseholdsthatdependonthemcanescapepoverty.

Rising rural wages will push up costs of production in agriculture–alreadyincreasedbytheeffectofhigheroilpricesseensince2007–andspuronmechanisationforthosetaskswheremachineryischeaperthantheincreased

costofmanualoperations.Thatmayleadtolargerfarmsizesaswell.Asianfoodpriceswillrise,limitedtosomeextentbythepossiblelowercostofimportsfromtheworldmarket–moderatedbythewillingnessofgovernmentstoallowimportsofcheapfoodthatmightthreatenfarmers’incomes.Risingfoodpricesthreatenaccessofthoseonlowincomestofood,but,giventhateventhoseonlowincomesdonotspendalltheirincomesonfood,thebenefitofhigherwagesshouldoutweighthehardshipofhigherfoodcosts.

Perhapsthemost intriguing implication is for manufacturing.Asruralwagesrise,somanufacturingwageswillhavetoincreasetorecruitnewworkers.ThiseffectisalreadybeingseenstronglyinChina,wherebothphenomenaarelinkedtoanationalworkforcethatisnowshrinkingeveryyear.Manufacturershavetwooptionsastheircostsrise:tomechaniseandtherebyeconomiseonlabour;ortorelocatetoregionsandcountrieswithlowerlabourcosts.Giventhescaleofitsmanufacturing,China’sdecisionswillbecritical.Ifthemostfrequentanswerisrelocation,thenitislikelythatplantsincoastalChinawillnotonlymoveinlandtolessprosperousareaswithlowerwages,butalsorelocateoutsideofChina.NeighbouringcountriesinAsiawithlowwagesmaybethefirsttobenefitfromthis,withBangladesh,Burma/Myanmar,CambodiaandVietnamclearcandidates.

Thereis,however,afurtherprospect:thatofcompaniesmoving to Africainsearchoflowerwages.TheWorldBankreportsEthiopianfactorywagesforunskilledlabourasbeingone-quarterthoseofChinesewages.Logisticscostsarehigher,butoverallcostsarelower.OutsideAddisAbaba,thefirstpioneerwaveofrelocatedChineseplantscanbeseen.Nowthesehavebrokentheice,howmanymorewillfollow?Lin(2014,inWonacott,2014)speculatedthat85millionfactoryjobscouldleaveChinainthecomingyears.IfhalfofthosecametoAfrica,itwouldtransformacontinentwherethereisasurgeinyouthenteringthelabourmarket.Ofcourse,relocationtoAfricawillonlyhappenifroads,powersuppliesandportsareadequateandifthereispoliticalstability.

Africa’seconomicunderperformancehassincethe1970sbeenfargreaterinmanufacturingthaninfarming.Iftherightconditionscanbecreated,renewedgrowthofmanufacturinginAfricaledbyAsianindustrialistspromisesprosperousurbanisationwithvibrantmarketsforthosefarmersstayingontheland.Thatwouldbewelcomenewsallround,includingforagriculture.


Figure A: Changes in real daily wages for agricultural labour (US$ constant 2010 PPP) in four Asian countries

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1. Introduction: aims of this study

1.1 Motivation for this studyRural wages matter in developing countries …Ruralwagesinthedevelopingworldmatter:manyofthepoorestpeopledependonthemtosomedegree.Itisstillthecasethatthemajorityoftheworld’spoor—perhapsasmanyas75%,andespeciallythosewithincomesbelowextreme-povertylevelsof$1.25aday–liveinruralareas.Forexample,inIndiain2009/10,39%oftheruralworkforcedependedoncasuallabouring–upfrom36%in1993/94(AlhaandYonzon,2011).Thismayunderstatethenumbersthatdependoncasualwork:therearealsothosewhoareself-employed,butinoccupationssuchasbarberingorcollectingfirewood,wherethefeepaidistantamounttoawage.Levelsofrural(unskilled)wagesthusheavilyaffectpovertyinruralareas.

Moreover,ruralwagelevelsaffectthecostsofagriculturalproduction–aboveallthoseofgrowingfood–andthereforehaveanimpactonfoodprices.Notonlydofoodpricesmatterforthewelfareofthoseonlowincomes,butalsofoodpricesaffectthewagesofferedinindustryandservices.Simplytoensureworkersarefedwellenoughtowork,mostfactoryownerswillbereluctanttopaywagesbelowthelevelatwhichstaffcanaffordtoeat1.However,thescopebothtosubstitutemachineoperationsforlabouronfieldsandtoimportfoodatlowercostthanusingdomesticsuppliesmoderatestheinfluenceofruralwagesonfoodprices.

Lastly,forlow-incomecountriessomeoftheworkersformanufacturingandserviceswillcomefromtherurallabourforce.Henceruralwagesmarktheminimumwagesthathavetobepaidinthesesectors.Henceruralwagesinfluencecostsofmanufacturingandwiththistheprospectsforgrowthofthatsector.

… and in Asia they are risingReportsindicatethatruralwagesinpartsofAsia,incountriessuchasBangladesh,ChinaandIndia,havebeenrisingsincethemid-2000s,andprobablyatafasterratethanbefore.

Ifthisrepresentsatrend,ratherthananexceptionalshort-livedincrease,andespeciallyifthesameweretoapplytoothercountriesoftheregion,theimplicationsfordevelopmentinAsiaandevenbeyondAsiawouldbelittleshortofmomentous.Hence,thisstudyaimstoreviewchangeinruralwagesinAsiaduringthe2000s,investigatethecausesofchangesandconsidertheimplications.

ThestudyhereisrestrictedtoAsia,sinceeconomicgrowthhasbeenstronginmostcountriesthereoverthepastfourormoredecades,anditisthecontinentwhere

thetransitionfromagrariantoindustrialsocietiesismostevident.WithinAsia,theparticularfocusisonEast,SouthandSoutheastAsia:experiencesinCentralandWestAsiahavelessincommonwiththoseoftherestofcontinent.

1.2 Questions posedThisstudyaddressesthefollowingquestions.

• What trends can be seeninruralwagesinAsiaduringthe2000s?Howmuchisthereacommonpatternacrosstheregion?

• What factors are driving the increases seen? Aboveall,dotheystemfromincreasedagriculturalproductionandproductivity,fromchangingdemographyorfromurbanisationandindustrialisation?Towhatextentdotheyreflectpublicpolicysuchasminimumwagesandpublicemploymentschemes?Whatmightbeexpectedfortrendsinruralwagesoverthenextfivetotenyears?

• Ifruralwagesarerising,thenwhat are the implicationsforruraldevelopmentandpoverty,forfoodpricesandfoodsecurityandforeconomicgrowth,bothinAsiaandinotherpartsofthedevelopingworld?

Thesearesubstantialquestions,castmoreoveracrossalargecontinentwithdiversecountryexperiences.Toanswerthemfullywouldtakefarmoretimeandfundsthanwehadforthisstudy.Hence,thisreportisexploratory.Aswillbeapparent,theevidencecanbeinterpretedtogiveacompellingaccount,althoughquitewidemarginsofconfidenceapplytosomefindings.Thismeansthat,whilewecanbereasonablyconfidentofthetrendsandtheirdrivers,wearelessconfidentoftheexactdegreeoftherelationsobserved.

Restrictingobservationstooneortwocountrieswouldhaveallowedformoreprecision,butalsowouldhavelimitedthegeneralityofthefindings,leavingdoubtsthatthecountrieschosenwereexceptionalinsomerespects.

Therestofthisreportisarrangedasfollows.Section2reviewssomeexistingliteratureonruralwagesinAsia,toidentifychangesandfactorsthatmayexplainthem.Section3reportsontheapproachtaken,datausedandanalysescarriedoutinthisstudy.Results,bothdescriptiveandanalytical,appearinSection4.Section5concludes,withconsiderationofthepotentialimplicationsfordevelopmentbothinAsiaandfurtherafieldinthedevelopingworld.


1 Thisisthe‘efficiencywage’hypothesis:payingmoretoworkersonverylowwagessotheycanbebetternourishedleadstoadditionalproductivitythatexceedsthecostofincreasedwages.

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2. Background: influences on

rural wages

2.1 Theories of rural wage formationIdeasaboutruralwageformationfallintotwobroadcamps:oneseeswagesastheoutcomeofdemandandsupplyoperatinginrelativelyfreemarkets;theotherseesrigiditiesofinstitutionsandlocationsthatcanleadtooutcomessignificantlydifferenttothoseexpectedfromamarketanalysis.

A market approachDemandforlabourisderivedfromthescaleofproductionandthereturnstolabourinproduction.Thislatterinturndependsonthemarginalphysicalproductivityoflabour,comparedwiththeproductivityofotherfactorsofproductionsuchasmachineryorland(inthecaseofagriculture)andthecostofthosefactors.Hence,demandforlabourshouldriseifi)productionincreasesandii)labourproductivityrises.Iftheeconomicreturnstootherfactorsrise,becauseeithertheirphysicalproductivityincreasesortheirunitcostsfall,thiswilltendtodepressthedemandforlabour,asincreasedproductioncanbeachievedbytheiruse.

Intheshortterm,productivityofallfactorsmaynotchangemuch,sodesiredlevelofproductionbecomesthemainelementofdemand.Inthelongerrun,alltheseelementscomeintoplay.

Supplyoflabourinruralareasisafunctionof:

• Growthofruralpopulation,dependinginlargepartonfertilityandthemortalityofminors;

• Migrationoutofruralareas,eithertocitiesoroutofthecountry.Someruralareas,usuallythosewithhighlyproductivefarming,mayseemigrantsarrivingfromotherruralareas;

• Prevailingnormsregardingparticipationintheworkforce.Theseincludetheageatwhichyouthenterthelabourmarketandtheelderlyleaveit,andtheextenttowhichwomenworkoutsideofthehomeandthejobsseenassuitableforthem;and

• Costofliving:iflocalwagesfallbelowsomeacceptablecostofliving,peoplemayeitherworklessorelseworkwithresentmentthatmaymanifestitselfinprotestandsabotage.

Thismodelassumesmarketsworkwellandthattherearemanyemployersofferingjobs,manyworkersseekingthemandplentyofinformationtoparticipantsongoingwagelevels.Inreality,andevenincaseswherelabourmarketscomeclosetothisideal,wagedeterminationisusuallycomplicatedbythefollowingfactors:

• Bargainingabilitiesmayaffectwages.Monopolypowermaybeexercisedtosomedegreeonbothsidesofthemarket,byemployers—forexampleinavillagewherea

landlordorasmallcabaloflandlordsdominatesthejobsmarkets—orbyworkersunionisedtonegotiatecollectively.

• Wages may be ‘sticky’:theydonotimmediatelyadjusttochangesindemandandsupply.Whendemandforlabourfalls,orsupplyincreases,wagesmaynotfall,astheremaybesocialreluctancetocutthemorbecauseworkersareoncontractsthatcannotberevisedintheshortterm.Whendemandpicksup,orsupplyfalls,andespeciallywhenthiscorrespondswithrisingcostsofliving,itmaytaketimeforwagestocatchup–owingpartlytosocialexpectationsofwhatafairwageisandpartlytowagebargainingsometimesbeingepisodic.Stickinessalsorespondstoimperfectinformation:itcantaketimeforbothemployersandemployeestoappreciatechangedconditionsinthemarket.Stickiness,however,isperhapslesslikelyinthelargelyinformallabourmarketsofruralareas,wherewagesmayadjustrapidlytochangedconditions.Ruralwagesmayappearinflexiblewhenworkerstakeintoconsiderationwhattheymightearnfrommigrationandhencerefusetoworkforlessthanthisreservationwage.Somewagedifferencescanbeexplainedonlybysocial relations and expectations.Themostprominentexampleconcernswomen,whotendtobepaidlessthanmen,evenwhereskillsandlabourproductivityareequivalent,owingtotraditionandgenderdiscrimination2.Suchdiscriminationmayalsoaffectthewagesofothergroups,includingtheelderly,thedisabledandthosebelongingtoanyothergroupstigmatisedbylanguage,class,creed,raceetc.

Labour market dualism Dualismpositstwosectors–amodernandatraditionalsector,thelatteroftenseenassynonymouswithsmallholderagriculture.Themodernsectorhashigherlabourproductivitythanthetraditionalsector.Indeed,inthelatter,labourproductivitymaybesolowthat,evenifnotzero,wagespaidmayexceedthemarginalvalueproductoflabour—sincealivingwagehastobepaid.Imagineahouseholdthatworksasmallfarm,sosmallthatthemarginaladditionsoflabouryieldverylittle,withnoopportunitiestoworkoffthefarm.Thehouseholdheadallocatestaskstothevariousmembersofthehousehold,butwhenitcomestorewardingthemtheyallgetthesamefoodandotherrewards.Thetraditionalsectorthusbecomesareserveofunder-employedlabour.Thetwolabourregimesexistinparallel,operatingtodifferentlogics.Distancefromvillagestocitieswithmanufacturingplantsfurtherprevents,oratleastdelays,integrationofthetworegimes,asmaydifferencesintheskillsoffarmlabourersandthoserequiredinfactories.

ThisconceptbecamethebasisforLewis’(1954)modelofdevelopmentwithunlimitedsuppliesoflabour.

2 AsignificantgendergapinwagesexistsinAsiaandthePacificcountries,withwomentendingtoearn54-90%ofwhatmenearn(DasguptaandKim,2011,citingUNDP,2010).

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Amodernsectorsuchasmanufacturingcouldattractlabourfromthetraditionalsectoratarelativelylowwage:thiswouldallowmanufacturingtoproduceatlowcostwithprofitssufficientforhighlevelsofreinvestmentandhencerapidgrowth.Transfersoflabourwouldcostthetraditionalsectorlittle:indeed,withsomereorganisationandperhapsaccesstocapital,productivitycouldrisetocoverthelossoflabour(Ranis,2012).Hence,theeconomycouldgrowveryquickly,asthemodernsectorexpands,employinglabouratlowcostfromthetraditionalsectoruntilthelaboursurplusisexhausted.Thispoint,wherethemarginalvalueproductoflabourinbothsectorsshouldbeequalised,hasbeencalledthe‘Lewisturningpoint’.

Ranis(2012)hasaddedthepossibilitythat,althoughinitiallywagespaidinthetraditionalsectorexceedmarginalproduct,asagriculturaldevelopmenttakesplaceandlabourproductivityrisesfarmwageslagandfallbelowthemarginalvalueproductoflabour.TheyonlystarttocatchupastheLewisturningpointnears.

AlthoughLewis’smodelhasbeenquestionedandmodified–see,forinstance,Ho(1972),Jorgenson(1967)ormorerecentlyFields(2004)–itseemstodescribetheconditionsofAsianindustrialisationinthelastquarterofthe20thcentury.Chinainparticularhasbeenabletorecruitlabourformanufacturingatlowcostfromruralareaswhereworkersonverysmallfarmshadlowmarginalproductivity.Atleastthisiswhatapplieduntilthemid-2000s,whenitseemsChinamayhavestartedtoapproachtheLewisturningpoint.

Theextentofdualismisindebate:ruralhouseholdsusuallyhavemorethantheirfarmsonwhichtodeploylabour–non-farmsharesoffarmhouseholdincomesareoftenfoundtobe40%ormore.Hence,theLewismodelmayapplyonlyintheveryearlystagesofdevelopment,whenruralareasaredifficulttoaccess,whenlittlecapitalisavailable,soreturnstorurallabourareverylow.Butasdevelopmenttakesplaceandruralareasarebetterconnectedtocities,asmorecapitalbecomesavailableandasalternativestoworkingonfarmsmultiply,thendualismrecedesandlabourmarketsmaybegintoworkasexpected.Inthe2000s,functioninglabourmarketsmayexplainbetterwhatisobserved,whileelementsofdualismhelpexplainpreviousdevelopments.

Public policyPublicpolicycanalsoinfluenceruralwages.Someofthemorepertinentpoliciesthatmightaffectruralwagesincludethefollowing:

• Legislatingminimumwages,althoughtheyarenotoriouslydifficulttoenforceinthelargelyinformalworkplacesofruralAsia;

• Publicworksemploymentschemes,whichcanprovideafloortoruralwages;

• Legislationtoimproveruralworkingconditions,whichmayhavetheeffectofraisingcostsofemploymenttoemployers

andhencereducedemand.Thesameappliestopayrolltaxes,althoughtheseusuallyapplyonlytoformaljobs.

Byandlarge,itisnoteasyforpolicytoaffectruralwagesdirectly,sincesomuchruralemploymentisself-employmentorcasualhiring,bothunderinformalarrangementsthattakesplaceoverlargeandsometimesremoteareaswherethestatelacksthecapacitytoact.

2.2 Recent studies of changing wages in rural Asia

Bangladesh Lookingbackoverthelongertermfromtheperspectiveofthelate1990s,Palmer-JonesandParikh(1998)reportthatagriculturalwages,deflatedbythepriceofrice,fellbetweenthelate1940sandtheearly1970s,thenrosethroughthe1980sand1990s.Theyfoundthisrisetobeassociatedwithincreasesinbothrealmanufacturingwagesandagriculturalproductivity.

Morerecently,Hossain(2008)constructedanindexofrealagriculturalwagesfrom1950to2006(seeFigure1).Farmwagesinitiallyrose,butthentheydeclinedsharplybetweenthemid-1960sandmid-1970s–presumablyonaccountofthepoliticalturmoilofthoseyearsleadinguptoandimmediatelyfollowingindependence–butsubsequentlytheyhavebeenrisinginmostyears.Increasedagriculturalproductivityandthegrowthofthenon-farmruraleconomyprobablyaccountfortheincreases.ThisserieshasbeenfurtherupdatedbyZhangetal.(2013),whofindthatruralwageshaveacceleratedsince2005–somuchsothatthegapbetweenurbanandruralwageshasnarrowed(seeFigure2).

Sincethe1990s,anotherdriverofrisingruralwageshasbeenthegrowthofmanufacturing,especiallythegarments

Figure 1: Bangladesh, agricultural wages, real, 1950-2006

Source: Hossain (2008)

industry,whichemploys3millionworkers,mainlywomen,manyrecruitedfromvillages.Atfirst,whenlabourersmovedoutoftheagriculturesector,therewasonlyasmallimpactonruralwagesbecausesurpluslabourexisted.Overtime,however,thesupplyoflabourhasbeendrawndown,shiftingadvantageinthelabourmarketinfavourofworkers.

Escalationofrealwageshasenhancedtheearningsofthepoorandcontributedtoreducedpoverty.Povertyincidencefellfrom51%in1995to49%in2000to32%in2010,sothepaceofreductionofpovertyacceleratedinthe2000s.‘Risingrealwagesarelikelymajordriversbehindthisrapidpovertyreduction’(Zhangetal.,2013).

Otherdriversofhigherruralwageshavebeenthegrowthoftheruralnon-farmeconomyandmaleemigrationtotheGulfandothercountries,whichhavedrawnmenoutofthefarmlabourforce.

Hence,farmlabourisrunningshort.Intriguingly,Zahid(2014)claimswomenarenowincreasinglyfindingagriculturaljobsmoreattractivethanlow-skilledjobsinthegarmentindustry,aswagesinagriculturehaverisen.

According to the latest labour survey conducted by the Bangladesh Bureau of Statistics (BBS), in 2010, out of the estimated 25.6 million farm labourers in the country, 10.5 million were women, meaning that 6.7 million women joined the farm labour market over a period of ten years. […] The RMG [ready-made garment] industry is losing its shine to the female workers, mainly because of the low wage. The farm sector has emerged as a very prospective alternative sector of employment for rural womenfolk. With more and more male farmhands migrating to urban centres to take up better paying jobs

or rickshaw pulling, a void has been created in the rural farm labour market. The women have started to fill up the vacuum since the daily wage of a farm labourer is higher than the average daily wage of a RMG worker.

Comparingwagesinvillageswithhighandlowlandproductivity,Hossainetal.(2013)seeagriculturalwageratesrisingonaccountofhigheragriculturalproductivity.Atthesametime,newtechnologyinricegrowing–presumablylabour-saving–hasallowedlabourtomoveoutofagricultureintonon-farmwork:

[…] in villages with high land productivity, the proportion of household heads with farming as main occupation was 39% in 2008 compared with 47% observed in villages with low land productivity. In contrast, those who are engaged in trade were more prominent in high land productivity villages (17% as opposed to 10%).

Internationalmigrationplaysarole,notjustbecauseitreducesthesupplyoflabour,butalsobecauseremittancesarespentlocallyonconstruction,amongotherthings,creatingextrademandforlabour:

[…] wage growth tends to be higher in villages experiencing high growth in overseas remittances. Thus, high agricultural wage growth has been associated more with villages experiencing high remittance growth compared with villages experiencing low remittance growth. Overseas remittance indirectly supported the growth of construction sector in general and real estate sector in particular.

China

RecentChinesestudiesfocusontheever-reducingnumbersenteringtheworkforceasChina’sdemographictransitionproceeds.Thismeansfast-growingmanufacturingplantsneedtorecruitmigrantlabourfromthecountryside.Migrationismediatedbyurbanregistrationofresidents(hukou).Theeffectofminimumwagesisindebate.WithinruralChina,increasingnumbersworkofftheland,innon-farmactivities.

Chinese demography and workforceChina’spopulationstructureisstriking:theagepyramidfor2010(seeFigure3)showsapyramidfortheelderlydowntothoseinthe40-44-year-oldcohort,typicaloffastpopulationgrowthinthepast.Foryoungercohorts,thepyramidinverts,especiallybelowage20.ThisistheresultofarapiddeclineinfertilityaftertheOneChildPolicywasintroducedinthelate1970s.Hence,itwillnotbelongbeforethenumbersenteringtheworkforce–conventionallythosereaching15years–arefewerthanthoseleaving–conventionallythosereaching65years.Indeed,itisprojectedthatin2015thenumberofChinese

14 ODI Report

Figure 2: Bangladesh, urban and rural wages, deflated by the general consumer price index, 2001-2011

Note: Urban wages are for unskilled workers (such as helpers on

construction sites and other sectors). The base year is set to 2009/10.

Source: Zhang et al. (2013).


aged15-64yearswillpeak,afterwhichtimethenumberswilldecline(seeFigureA14inAnnexA)3.Somesourcesputthisturningpointearlier,in2010,sothat,between2010and2020,thenumbersaged15-59wouldfallbymorethan29million(Drysdale,2014).Insimilarvein,Knightetal.(2013)estimatethatthe

[…] urban-born labour force will fall by 6.4% over the 15 years between 2005 and 2020, with the fall starting in about 2010 and accelerating in the following years. The rural-born labour force will rise by only 2.6% over these 15 years, but the rise will be confined to the first five years and there will be a fall in the last five.

DasandN’Diaye(2013)alsoseeChinaasrunningoutoflabour,butitmaybeasmuchasadecadelater,inthe2020s,beforeabsolutenumbersfall:seeFigure4.Thenumbersofunderemployed(‘excesssupply’)arefalling,althoughtheLewisturningpointwhenunderemployedlabourinruralChinawillfinallyhavebeenabsorbedintomoreproductiveworkmaybereachedonlyafter2020:

[…] we estimate that China’s excess supply of labor already peaked in 2010 and is on the verge of a sharp decline: from 151 million in 2010, to 57 million in 2015, to 33 million in 2020. China is expected to reach the Lewis Turning Point between 2020 and 2025 — that is, sometime in that five-year period, demand for Chinese labor will exceed supply. The rapid rate of decline in the excess supply of workers closely follows the projected path of the dependency ratio, which reached its historical trough in 2010 and is projected to rise rapidly hereafter.

Migration from rural areas and hukou registration

Itseems(seetheKnightquoteabove)thatnewjobsinurbanareaswillincreasinglyhavetobefilledbymigrantsfromruralareas.Liang(inKnightetal.,2013)reportsrecordnumbersofinformalmigrantsinurbanareas:

Second, the data from the 2010 Chinese population census show China’s floating population (loosely defined as migrants who do not possess local household registration) reached 221 million in 2010, another new record. In fact, the two statistics are closely related: the rise of migration and China’s floating population have overwhelmingly contributed to China’s rising level of urbanisation and urban growth. These migrant workers also contributed enormously to China’s economic miracle in the past three decades as they built China’s skyscrapers and laboured in China’s factories supplying goods across the globe.

Migrationtothecitiesisbynowthemostprevalentoff-farmactivityforruralChinese,especiallyforthoseunder40yearsold.Increasingly,thefarmsareworkedbyolderpeoplewhoremaininthevillages(Lietal.,2013).Ingeneral,farmhouseholdsincreasinglyhaveotherworkofftheland(Rozelle,2007).

Nevertheless,migrationmaynothavereacheditsfullpotential,impededbyregistration(hukou)ofpeople’sresidenceineitherruralorurbanareas.Someoneregisteredinaruralareawhomovestoacitycannotobtaineducation,healthcareandotherbenefits,orobtainaformalurbanjob,withoutanurbanpermit.Theresultisthatmigrantssufferdiscriminationinwages:in2009,migrantearningswereonaverageonly45%oftheaverageurbanhukouworker’shourlywage.Thishas,perhapssurprisingly,notimprovedinrecenttimes,asthespecificcaseof

3 Annexesareavailablefordownloadat:www.odi.org/rural-wages

Figure 3: China, population by age and sex, 2010

-65 -55 -45 -35 -25 -15 -5 5 15 25 35 45 55 65 0-4

10-14

20-24

30-34

40-44

50-54

60-64

70-74

80-84

90-94

100+

Female

Male

Source: Compiled from UNDESA (2005; 2006).

Figure 4: China, workforce, 1950-2050

Source: Das and N’Diaye (2013), using UN data.

migrantstoShanghaiillustrates.In1995,migrantworkersinShanghaiearned50%ofthehourlyearningsofurbanhukouworkers;by2009,migrantsearnedonly40%ofthehourlyearningsoftheirurbancounterparts(Meng,2013).

Restrictionsonmovement,however,havebeenrelaxedinrecentyears,andarelikelytobecomeevenmoreso,asurbanjobdemandoutstripssupplyoflabour(Zheng,2013).

Wages and minimum wage policy

Inthesecondhalfofthe2000s,wageshavebeenrisingveryrapidlyindeed(Fang,2011):

In the period 2003 to 2008, the annual growth rate of monthly wages in real terms was 10.5 % in manufacturing, 9.8% in construction, and 10.2% for migrant workers. The real daily wages of paid agricultural workers in the same period rose even faster — 15.1% in grains, 21.4% in larger pig farms, and 11.7% in cotton.

Itisofficialpolicytoraiseminimumwages:the‘12thFive-YearPlantargetsanannualincreaseintheminimumwagelevelofnolessthan13%’(Fang,2011).Moreover,therearereportsthatlocalauthoritiesinthePearlRiverDeltamayberaisingtheminimumevenhigherinabidtoencouragehighertechnologyindustry(LauandGreen,2013):

Localities are free to set their wages above the national level. In fact, provinces have increased minimum wages by an average of 16 per cent this year, after a 20% increase last year. Shenzhen in the Pearl River Delta tops the list in terms of minimum wage levels, with minimum monthly pay of 1,600 yuan (US$258). This has forced more than half the companies in our survey to raise wages more than they had planned, particularly for the least skilled part of their workforce.

AsmanufacturingwagesriseinChina,itisexpectedthateitherfirmswillmechanisemore,orshiftfactoriesfromthehigher-wagecoasttolower-wageinlandlocations,orelsemovetocountrieswithlowerwages,withBangladesh,CambodiaandVietnamaslikelyplaces(LauandGreen,2013):

Around 30% of the companies surveyed said they planned to move factories inland, while 10% said they planned to move out of China altogether. Both of these figures more than doubled from last year. Within China, many companies in the Pearl River Delta want to move westward to Guangxi province, where wages are 30% lower. Other popular destinations include Jiangsu, Hunan, Hubei and Jiangxi provinces. The favoured overseas destinations are Cambodia, Bangladesh and Vietnam.

India

RuralwagesinIndiahavebeenrisingsinceatleastthelate1970s(seeFigure5).Bytheturnofthenewcentury,44%ofworkersinruralIndiadependedoncasualwages.Womenearnlessthanmen,althoughthedifferencenarrowedmarginallybetweentheearly1980sand2000.

Earlierstudiesassociaterisingruralwageswithincreasedyieldsonfarms(DattandRavallion,1998),aswellaswithpublicinvestmentsinphysicalinfrastructureofroadsandirrigationandinhumancapitalintheformofschools(Bhallaetal.,2004).

WagesonIndianfarmsthatweregrowingsteadilyinthe1990sat3.7%ayearfellbackintheearly2000sat-1.8%ayear,onlytoriserapidlyinthesecondhalfofthe2000s,at6.8%ayear(Gulatietal.,2013)(seeFigure6,overleaf).

Gulatietal.(2013)seesomecorrespondencewitheconomicgrowth,especiallywithincreasesinconstruction,whichtendstoattractrurallabour.About43%ofmaleruralmigrantsenduponbuildingsites.Constructionhasboomed:alabour-intensivesector,itsshareofIndianemploymenthasrisenjustasagriculture’ssharehasfallen.Indeed,itseemsthatfinally–studiesofruralIndiahavelonglamentedhowlittlechangehasbeenseeninthefractionoftheworkforceinagriculture–agricultureisrelinquishingitsshareofemploymentinfavourofothersectors,particularlyconstructionandservices(seeFigure7),overleaf.

Public employment schemesPartsofIndiahavelongusedpublicemploymentasawaytoalleviateruralpoverty.TheMaharashtraEmploymentGuaranteeScheme,inoperationsince1975/76,providesjobsforthepooronalargescale,withhalfoftheemploymentgiventowomen.Fundedequallybyataxonprofessionalandformaljobsandbygeneralrevenues,theschemelegallyentitlespeopletowork:whenever50jobseekersdemandwork,jobsmustbeprovided.

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Figure 5: India, real wage rates of rural casual labourers in India, 1983, 1987/88, 1993/94 and 1999/2000 at 1999/2000 prices

10

20

30

40

50

60

Farm male Farm female Non-farm male Non-farmfemale

Rs

a da

y, 1

999/

2000

con

stan

t

19831987-881993-941999-00

Source: Bhalla et al. (2004), using Himanshu (2003).


Basedonfavourableevaluationsofthis,anationalschemewasintroducedin2006,throughtheMahatmaGandhiNationalRuralEmploymentGuaranteeAct(MGNREGA).Theschemeoffers100daysofworkataguaranteedwage–by2011atRs120-179aday–varyingbystate.Sinceitsintroduction,considerableinteresthasbeenshowninitseffectsonrurallabourmarkets,withtheexpectationthatitwillputafloorintherurallabourmarket,leadingtohighercasualunskilledwages.Gulatietal.(2013)summarisefindingsfromstudiesonitseffects:

Some recent research seems to support the idea of a rise in real casual labourer wages due to MGNREGA, with estimates ranging from 4% to 8% (Berg et al 2012, Azam 2012, Imbert and Papp 2012). NSSO data too indicate that the advent of MGNREGA has resulted in a significant structural break in rural wage increases. Between 1999 and 2005, pre-MGNREGA, nominal wages in the rural economy grew at an average annual rate of 2.7%. Post-MGNREGA, average wage increases almost quadrupled to 9.7% between 2006 and 2009-10.

Figure 6: India, average farm wages, constant at 2011/12 prices, 1990/91 to 2011/12

Source: Gulati et al. (2013), based on data from the Indian Labour Bureau.

Figure 7: India, sector-wise distribution of employment, 1983-2009/10

0

10

20

30

40

50

60

70

Agriculture Manufacturing Construction Trade, hotels,transport and

communication

Financing, real estateand business

services

Community, socialand personal service

Sha

res

in e

mpl

oym

ent (

%)

1983 2009-10

Source: Thomas (2012).

There are, however, studies which argue that rise in casual wage rates cannot be wholly attributed to MGNREGA (Dutta et al, 2012). Mukherjee & Sinha (2011) have conceived a microeconomic model that establishes that the fact of a guarantee of employment at a given wage through the MGNREGA would introduce contestability in the rural labour market. In other words, in the presence of MGNREGA scheme the large land holders in rural areas may now need to raise wage of workers they hire in order to ensure the necessary supply of labour.

AlhaandYonzon(2011)seetheschemeasespeciallyimportantforfemalelaboursincemalescanmoreeasilymigratetofindwork.InThanjavurdistrict,TamilNadu,verylargeincreasesinruralwages,fromRs60toRs110adayfrom2006to2008/09,havebeenreported,ashavecomplaintsfromlargefarmersofnotbeingabletorecruitlabourforpaddyplantingorharvesting(SelvaMaheswariandGangwar,2011).

Eveniftheschemeemploysonly10%casuals,itseemstoaffectlocalwagerates,whichhavegrownmostwheretheschemeismostactive.

ButhowmuchhastheMGNREGAschemepushedupruralwagescomparedwithotherdrivers?AregressionofaveragedaysofemploymentperhouseholdbytheMGNREGAscheme,productivityoffoodgrainsandroaddensityonruralwagesshowallthesehaveraisedthegrowthrateofwagesforbothmaleandfemalefarmlabourers(NarayanamoorthyandBhattarai,2013).Gulatietal.(2013)regresstheincidenceoftheschemeandgrowthoftheeconomyonruralwagestofindeconomicgrowthisamuchstrongerdriverthantheemploymentscheme.Theythereforearguethatfundsinvestedintheschememightbetterbespentonmeasurestostimulateeconomicgrowth–althoughiftheemploymentprojectscreateusefulphysicalinfrastructure,theschememightcontributetowardsthis.

IndonesiaRuralwagesinIndonesia4rosegraduallyfromtheearly1980s,butsunkforfivequartersin1998/99duringtheAsianfinancialcrisis;theyrecoveredslightlyinthelate1990s.Theychangedverylittleinrealtermsforthefirsthalfofthe2000s,butgrewinthesecondhalf,withapronouncedupwardsshiftbeginninginthethirdquarterof2005.Wagesagainrosedramaticallyaroundthe2007/08period,butfellfrompeaksofoverRph20,000perdayafter2008.Nonetheless,in2009theyweresomeRph5,000perday(50%)higherthantheirlevelsformostofthefirsthalfofthe2000s(seeFigure8).

ResearcherslookingatwhetherIndonesia’sagriculturalwageratewouldberaisedmorebyeitherincreased

industrialdemandorincreasedagriculturaldemandforlabourfoundthat,althoughbothhadapositiveinfluenceonraisingwages,industrialdemandplayedafargreaterrole(HarahapandBarichello,2014).

AgriculturalwagesweremodelledasafunctionofJava’sriceprice(aproxyforagriculturaldemandforlabour),Indonesia’smanufacturingwage(aproxyfortherealurbanwage)andquarterlymanufacturinggrossdomesticproduct(GDP)(aproxyforurbansectordemandforlabournotcapturedbythemanufacturingwage).Theirresultssuggestedthemanufacturingwageratewashighlyimportantindeterminingfarmwages,withestimatesoffarmwageratesrisingby0.3%fora1%riseinmanufacturingwage.Theeffectofrisesinthericepricewasonlyone-thirdaslarge,withfarmwagesrisingonly0.1%fora1%riseinthericeprice.ThegrowthinmanufacturingGDPwasalsofoundtohaveastronginfluenceonfarmwages,raisingthembyalmostasmuchasthemanufacturingwageratechanges.

Arias-Vazquezetal.(2013)comparedimpactsofgrowthinhigh-productivitysectors–manufacturing,transportandcommunications,finance,electricityandutilitiesandmining–andlow-productivitysectors–otherservices,agriculture,retailandwholesaletrade,governmentandpublicadministrationandconstruction–onannualchangesinaveragewagesacrossIndonesia,usingpaneldatafrom1988to2007.Thisgavealargepositiveandsignificantcoefficientongrowthfromhigh-productivitysectors,butonlyasmallpositive,butinsignificant,coefficientongrowthoflow-productivitysectors.

Theyalsousedacross-provinceregressiontodeterminehowmuchannualisedchangesinwages(amongother‘employmentoutcomes’)wereinfluencedbyshare-weightedgrowthindifferentsectorsoftheeconomy.Thisgavepositivecoefficientsonotherservices,agriculture,manufacturingandtransport,althoughonlymanufacturingwassignificant.Miningwasalsosignificant,butwithanegativeandsmallcoefficient.

Education, road quality and rural wagesOtherresearchhasexaminedtheimpactofimprovingruralroadsonruralwagesinIndonesia.Usingwagedataoverthe1995-2007period,Yamauchietal.(2011)showedimprovementsinroadinfrastructure(transportationspeed)increasednon-agriculturalwagesinruralIndonesiabyconnectingworkerstoemploymentopportunitiesoutsidevillages.Moreeducatedindividualswereabletotakeadvantageoftheopportunitiesraisedbybetterconnectivitytogainhigher-wageemploymentoutsidetheagriculturesector.

Morerecently,Yamauchi(2014)showedbetterroadsandfastertransportpositivelyinfluencedbothagriculturalandnon-agriculturalwagesinIndonesiabetween2007and

4 Here,agriculturalwagesinJavaareusedtoillustrateIndonesianwages.TheyareanaverageoftheprovincialaverageforWestJava,CentralJavaandEastJava,whichtogetherincludesome70%ofIndonesia’spopulation.

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2010.Moreover,betterroadsandschoolinginteractedtoimproveagriculturaldailywagessignificantly.

Across-countryanalysis(Wintersetal.,2008)appearstocorroboratetheseresults,findingeducationalandinfrastructureinvestmentwerecriticalforprovidingopportunitiesinthelabourmarketthatledtohigherwagesacrossasampleof14countries,includingIndonesia.5Theywrote:

The key to participating in high value wage employment activities appears to be education. Generally, there is a positive relationship between education and participation in rural labour markets suggesting that education is linked to labour markets and that labour markets are used as a pathway out of poverty for the educated.

Andonagriculturalwagesspecifically:

While agriculture is not chosen as the sector to participate in by the educated, the educated workers that find the right opportunities do receive higher wages.

ForIndonesiaspecifically,usingdatafroma2000survey,theyfoundthatwagesinrurallabourmarketsrespondedstronglyandpositivelytoeducationandinfrastructure,butwithalargenegativecoefficientforfemaleworkers(seeTable3inWintersetal.,2008).Foragriculturealone,theyfoundastrongernegativecoefficientforfemaleworkersandapositiveeffectforeducation:infrastructurewasnotfoundtobesignificant(seeTable5inWintersetal.,2008).

Other parts of AsiaInMalaysia,ithasbecomeincreasinglydifficulttorecruitworkersforoilpalmestates.Indonesiausedtobeasourceofmigrantlabour,filling80%ofsuchjobs.ButthishasdwindledasaresultofhigherwagesandrapidurbanisationinIndonesia.ApplicantsforjobsinMalaysia’spalmoilsectorplungedto38,000in2013,frommorethan120,000ineachoftheprevioustwoyears,accordingtodatafromtheIndonesianEmbassyinKualaLumpur(Raghu,2014).

Malaysiaseemstobetakinginmigrantsfromothercountries.Asmanyas250,000BurmesemaybeworkinginMalaysia,oftentakinglow-paidjobs,includingatrestaurantsandconstructionsites,withhelpfromrecruitmentagencies.About110,000Burmanationalsinthecountrylackproperlegaldocumentation,accordingtotheLabourMinistry(ThaiPBS,2014).

BangladeshandMalaysiasignedanagreementinNovember2012formigrantlabour,withsofar4,000BangladeshistravellingtoMalaysiatofilljobsunderthedeal(Ara,2014).

InBurma,farmlabourshortagesarereportedascasuallabourersleavethelandforconstructionjobsinRangoon(Htike,2014).

InThailand,theshoppingmalls,factoriesandconstructionsitesinThailand’snortheastareattractinglabour,sincetheeconomyoftheregionisbooming.In2013,anationalminimumwageof$10adaywasintroduced,whichtranslatedtoa35%riseintherelativelypoornortheast.ThishasapparentlyevenledtosomeworkersreturningtotheirhomeregionfromBangkok(CarstenandTemphairojana,2013).

5 CountrysurveystheyusedwereAlbania(2005),Bangladesh(2000),Bulgaria(2001),Ecuador(1995),Ghana(1998),Guatemala(2000),Indonesia(2000),Malawi(2004),Nepal(2003),Nicaragua(2001),Nigeria(2004),Panama(2003),Tajikistan(2003)andVietnam(1998).

Figure 8: Indonesia, real agricultural wage rate in Java, 1983-2009, rupiah a day

Note: Wages have been deflated by the rural Consumer Price Index (CPI) to constant 2007 levels. Source: Quarterly data from Harahap and

Barichello (2014) (horizontal axis labels added).

Lesspositivereportscomefromeconomiesthathavenotbeengrowingasquickly,suchasPakistan(Dawn.com2014;OmanTribune,2014)andthePhilippines(ReyesandTabuga,2011).

2.3 SummaryRecentliterature,bothdescriptiveandanalytical,reportssimilarfindingsinseveralcountriesofAsia:

• InBangladesh,China,IndiaandIndonesia,ruralwagesarerising–andapparentlyfasterinthesecondhalfofthe2000sthanbefore.

• Growthofmanufacturingandjobsoffthefarm,especiallyconstructionincities,isdrawinglabouroffthefields.

• ForChina,atleast,thepullofthecitycoincideswithreductionsinthelabourforce,asthelowerfertilityofthepast30yearscomesintoplay.

• Itislesscleartowhatextentthegrowthoftheruralnon-farmeconomyorincreasesinagriculturalproductivityhaveledtoincreaseddemandforlabourinruralareas.

• Althoughpublicemploymentprogrammesmaycontributetohigherruralwages,theymaynotdrivethemasstronglyaseconomicgrowth.Thatsaid,theIndianMGNREGAschememaybedisproportionatelyvaluabletofemaleworkersandtothoseineconomicallylaggingregions.

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3. Study approach, data and methods

3.1 Research questions Fromthegeneralquestionsposed,thefollowingtwowereselectedfordetailedinvestigation,giventhelimitsofsecondarydataavailableandtimeforstudy:

1. What trends can be seeninruralwagesinAsiaduringthe2000s?Inhowmanycaseswereincreasesinruralwagesmorerapidinthesecondhalfofthedecadecomparedwiththefirsthalf?

2. What factors are driving the increases seen?Whataretherelativesignificanceandweightofincreasesinagriculturalproductivityandmanufacturingoutputthatshouldraisedemandforlabour,orofchangesinnumbersofworking-agepopulationinruralareasthataffectthesupplyoflabour?

3.2 ApproachThefirstquestionwasansweredbycollectingdataonruralwagesinAsiaduringthe2000s,thencomparingtheratesofincreaseseenfortheearlyandlatepartofthedecade.

DatawerecollectedforthemostpopulousdevelopingcountrieseastoftheKhyberPassandsouthofCentralAsia.Thereare13countriesinthisregionwithmorethan20millioninhabitants;indecliningorderofpopulation,theseareChina,India,Indonesia,Pakistan,Bangladesh,Philippines,Vietnam,Thailand,Burma/Myanmar,RepublicofKorea,Nepal,MalaysiaandSriLanka.DPRKoreawasomittedowingtoitsunusualcharacteristicsandlackofdata.TaiwanChinawasomittedforlackofreadilyavailabledataonruralwages.6

Figure9showsthelocationofthecountries,whileTable1providessomebackgroundcharacteristics:population,proportionofresidentsclassifiedasruralandagriculture’scontributiontotheeconomyin2000comparedwith2012.

Forrural wages,theaimwastofindaseriesthatrepresentstrendsinunskilledruralwages.Thereis,ofcourse,nosinglenationalruralwage.Wagesvarybylocation,byseason,bythejobcarriedoutandusuallyalsobysex,withwomentypicallybeingpaidlessthanmen.Givenlimitationsoftimeandaccesstodata,afairlystrongassumptionhadtobemadeinseveralcases:thatthedataseriesselectedtorepresentruralwagesineachcountrywereconsistentintrendwithotherpotentialdataseriesforthatcountry.

Tolookatpotentialdriversofchangesinruralwages,asimplemodelhasbeenadopted:

Δ Rural wage = f[Δ agricultural labour productivity, Δ rural working age population, Δ manufacturing output, dummy for first half of the 2000s]

—whereΔindicateschangeinannualaveragerate.

Thisassumesthemaininfluencesonruralwageswillcomefromchangesindemandfromfarmingoralternativelyfromgrowthofmanufacturingoutput,andfromchangestothesupplyoflabour.Changesfortwotimeperiods,earlyandlate2000s,weremodelled,withadummytoseewhethertherewasanysignificantchangeintherelationsseenbetweenthetwoperiods.

Severalsimplifyingassumptionsweremade,including:1. Demandforagriculturallabourwillvarymainly

accordingtothemarginalproductivityoflabour.Increasesinareatilledmayalsoincrease,butthiswasomittedonthegroundsthatincreasesinareacultivatedhavebeenlimitedinmostofthesecountriesduringthe2000s.

2. Growthofmanufacturingwastakentorepresentgrowthofdemandforlabourinactivitiesotherthanagriculture.Clearly,servicesalsorequirelabour.Manufacturingwas,however,thoughttorepresenta

6 GivenTaiwan’slevelofindustrialisation,ruralwageratesprobablyrosesubstantiallypriortotheperiodofinterestforthisstudyinanycase.

22 ODI Report

Box 1: Varying transitions from agrarian to industrial economies

Theselectedcountriesrangefromthosestillheavilyreliantonagriculture–particularlyNepalandBurma/Myanmar–tothosetransitioningtowardsbeingmoreurbanandlessdependentonagriculture–withPakistan,Vietnam,BangladeshandIndiaintheearlierstagesofthetransitionandChina,IndonesiaandthePhilippinesinlaterstages–toafewcountrieswhereagricultureisnowarelativelysmallpartoftheeconomy(RepublicofKoreaandMalaysia).

Figure10illustratesthesetransitionsfromruraltourban,fromagriculturetoothersectors,throughtimefromtheearly1980sto2010/12.Thegeneraltrendrunsfromtopleft(ruralandagricultural)tobottomright(urbanandnon-agricultural),withmostcountriesseeingadeclineintherelativeimportanceofagricultureandtheproportionofpeoplelivinginruralareas.Therearefewexceptions.SriLankaaloneshowsarisingruralproportionofpopulation;someothercountriesgoagainstthetrendfortheodd10-yearperiod.

Theratesatwhichthesecountriesaremakingthetransitionvarysharply.Overthepast30years,somehaveincreasedtheproportionofthepopulationlivinginurbanareasbymorethan25percentagepoints(China,Malaysia,IndonesiaandRepublicofKorea);othershaveseenmuchslowerurbanisation(Pakistan,IndiaandThailand,withincreaseslimitedto7-8percentagepoints).SimilardifferencesapplytochangesintheshareofagricultureinGDP,withverystrongfallsseeninChina,NepalandVietnam.LesserreductionsapplyforPakistan,whiletheshareinBurma/Myanmaractuallyrose.


sourceofjobsbetterpaidthanagriculture,sinceservicescanincludeactivitiesthatarebadlyrewarded:informal,refugeactivitiesundertakenbypoorpeoplewhocannotaffordunemployment.

3. Growthofworking-agepopulationrepresentsthesupplyoflabour.Thisvariableshouldencompassbothpopulationgrowthinruralareasandnetmigrationoutofruralareas.Itassumestheratesatwhichdifferentpartsoftheworking-agepopulationparticipatedonotchangesignificantly.Inpractice,itmaybethatthischangesbyage–withincreasingincomes,adolescentsmayfeeltheycanspendmoretimeinschoolbeforeseekingajob,whileolderworkersmaybeabletoretireearlier–andbysex–womenmayprefertostayhomeasincomerises,oralternatively,astheyspendlongerinschool,mayactivelyseekcareers.Overadecade,however,weassumedsuchchangeswouldnotaffectthenumbersseekingworkasmuchasthedemographicfactors.

Thefirsttwoassumptionsmayseemquitestrong.However,giventhatthemodeloperatesbyratesofchangeratherthanbylevels,itisnotnecessarythatthevariablesselectedcompletelydescribedemandforrurallabour,butratherthattheyrepresentthemainforcesofdemandandthatomittedvariableswouldnotshowadifferenttrend.Toexpand:inthecaseofagriculture,theassumptionisnotthatincreasesinareadonotraisedemandforlabour;ofcoursetheydo.Theassumptionisthatsuchincreasesarenotgreaterthanthoseinagriculturallabourproductivity.Similarly,theomissionoflabourdemandinservicesassumesanyincreaseinservicejobs(betterpaidthaninagriculture)isnotgreaterthanthatofmanufacturing.

Table 1: Population, proportion rural and agriculture’s contribution to GDP

Population 2013 (millions) % rural Agriculture, value added, % of GDP, 2000

Agriculture, value added, % of GDP, 2012

China 1,417 46 15 10

India 1,252 68 23 18

Indonesia 250 48 16 14

Pakistan 182 63 26 24

Bangladesh 157 71 26 18

Philippines 98 51 14 12

Vietnam 92 68 23 20

Thailand 67 65 9 12

Burma/ Myanmar 53 66 57 48*

Korea, Republic of 49 16 5 3

Malaysia 30 26 9 10

Nepal 28 82 41 37

Sri Lanka 21 85 20 11

Note: National classifications of the rural/urban divide may not be fully comparable as different countries have different thresholds for village/

town size classified as ‘urban’. * Data for agriculture, value added as a proportion of GDP for Burma/Myanmar are for 2004 as later data are

not available.

Sources: Population data from FAOSTAT. Agriculture (% of GDP) from World Bank World Development Indicators.

Figure 9: Most populous Asian developing countries east of the Khyber Pass and south of Central Asia

Sources: Map from Wikimedia commons.

3.3 Data sources

Recent rural wage dataLiterature,databases7andsurveys(nationallyrepresentativeorotherwise)wereconsultedtosourcedataonruralwagetrendsinthe13focuscountries,lookingfornationallyrepresentative rural agricultural wage data spanning 2000 to 2014.

Databeginningbefore2000werealsoconsideredincaseswhereavailabledatawouldotherwisespantooshortaperiod.Subnationaldata,thosedisaggregatedbygenderofworker,typeofcrop,seasonofproduction,statesectorworkersandskilledagriculturalworkerwages,werealsocollectedwhereavailable:insomecases,onlysuchdisaggregateddatawereavailable.8

Table2presentsthewagedatacollectedforthe13countriesoverthepast15orsoyears.9Whiletherearelimitstothecomparisonsthatcanbemadeacrosscountries,givendifferencesinwagescovered,withincountriescomparisonsthroughtimeshouldbevalid.

Adjustments to wage data

Wherewageswerenotpresentedasdayrates,thesewereimputedfrommonthlywagesusingtheconventionappliedintheILO’sOccupationalWagesaroundtheWorlddatasetof25workingdayspermonth.

WagesinnominallocalcurrencyunitsweredeflatedbythenationalCPIre-basedto2010.Toallowforcomparisonacrosscountries,theywerethenconvertedtoUSdollarsusingthe2010exchangerate–marketexchangerate,sonotcorrectedforpurchasingpower.BothCPIsandexchangeratesweretakenfromtheWorldBank’sDevelopmentIndicatorsdatabase.Burma/Myanmarisanexception:wageshereweredeflatedto2012levelsandconvertedto2012USdollars:theofficialexchangerategrosslyovervaluedtheBurmesekyatpriorto2012,soa2010conversionwouldmakedailywageratesimplausiblyhigh.

Foranalysis,ruralwagedatawereselectedtobeasrepresentativeaspossible.Wherenationallyrepresentativeaveragewageswerenotavailable,thelargestavailableaggregateswereused(geographicallyorintermsofcrops).Whenwageswereavailableonlydividedbysex,men’s

7 SuchasthosefromnationalstatisticalservicesorinternationalorganisationsincludingtheWorldBankortheInternationalLabourOrganization(ILO).

8 Therearenointernationaldatabasesthatregularlyreportondailywagesforthesampleofcountriesofinterestthathaveconsistentlydonesoforthetimeperiodofinterest.Nationalsurveysthatcollectthistypeofdataarefewandfarbetween.

9 AnnexBpresentsmoredetailonindividualcountrydata.Availablefordownloadat:www.odi.org/rural-wages

24 ODI Report

Figure 10: Pathways to urbanisation in selected Asian countries, 1980/82-2010/12

Bangladesh

China

India

Indonesia

Malaysia

Myanmar

Nepal

Pakistan

Philippines

Korea, Rep

Sri Lanka Thailand

Vietnam

0

10

20

30

40

50

60

5 15 25 35 45 55 65 75 85

Con

trib

utio

n of

agr

icul

ture

to G

DP,

%

% of population that is urban

Bangladesh ChinaIndia IndonesiaMalaysia MyanmarNepal PakistanPhilippines Korea, Rep.Sri Lanka ThailandVietnam

Rural and agrarian

Transitioning

Urban and non-agricutlural

Note: Four data points for each country are shown to represent trends in time: 1980/82, 1990/92, 2000/02 and 2010/12. Vietnam is missing the

first data point and Burma/Myanmar the last, since data were unavailable.

Source: Constructed from data in World Bank WDI and FAOSTAT


Table 2: Description of data and sources on rural wages by country

Country Type of data Source

China Peak and slack season daily wage data for agricultural labour in poor areas in Gansu province 1998, 2003 and 2006

Zhang et al. (2010), using village surveys in poor countries in Gansu province

Average male and female daily wages in five provinces: Jiangsu, Hebei, Shaanxi, Jilin and Sichuan 1998, 2004 and 2007

Zhang et al. (2010), based on village surveys conducted by the Centre for Chinese Agricultural Policy (CCAP) in the five provinces

India Average male and female rural daily wages in India 1998/99-2012/13

India Labour Bureau, presented in Usami (2012), updated from the Labour Bureau site

Indonesia Average daily wages of animal husbandry workers 2007-2013

Bureau of Statistics Indonesia

Village-level agricultural worker daily wages in 98 villages across 7 provinces (selected for an agro-ecological zone spread) 2007 and 2010

Survey data from Dr Futoshi Yamauchi

Pakistan National monthly wages on average and for males and females involved in agriculture, forestry, hunting and fishing 2007/08-2010/11 and 2012/13

Pakistan Bureau of Statistics, available in Labour Force Participation survey reports

Daily wages for crop workers in Pakistan 1999 to 2004

Occupational Wages around the World database

Bangladesh Average daily wage rates for males and females in peak and lean seasons 2000, 2005 and 2010

Zhang et al. (2013), using Household, Income, and Expenditure Surveys by Bangladesh Bureau of Statistics

Philippines Average daily wage rates of farm workers involved in all crops, as well as for specific crops: rice, maize, coconut, and sugarcane 1991-2012

Philippine Industry Yearbook of Labour Statistics 2013

Wage rates in Central Luzon (the ‘rice bowl’ of the Philippines) 1998/99, 2003/04, 2007/08 and 2011/12

Calculated from surveys from International Rice Research Institute (IRRI) Farm Household Survey Database, Central Luzon Loop surveys

Vietnam Monthly average income per employee in state agriculture, forestry and fishing sector in Vietnam 2005-2012

General Statistics Office of Vietnam, website

Average daily wage for agricultural labourers 1993, 1998 and 2002

Nguyen (2006), using Vietnam Living Standards Survey and Vietnam Household Living Standards Survey data

Average income of wage workers in rural areas 2007 and 2009-2012 (included to compare between state sector wage and average rural incomes)

Vietnam General Statistics Office Reports on the 2011 and 2012 Vietnam Labour Force Surveys

Thailand Average monthly wage for skilled agriculture and fishery workers in Thailand 2001-2013

Bank of Thailand for quarterly wages, averaged annually

Burma/ Myanmar

Daily wage rates for rice production labour in Ayeyarwardy: transplanting, weeding, fertilising, carrying, harvesting, threshing, winnowing and the average of these 1996 and 2004

Calculated from surveys from IRRI Farm Household Survey Database, ‘Survey for Assessing Changes in Agriculture and Livelihood in Ayeyarwardy Division, Myanmar’

Republic of Korea

National average monthly wage rates for agricultural crop workers 2000-2006 and for dairy product processors 1996-2006

World Development Report 2013, Occupational Wages around the World database

Malaysia Annual national average agricultural sector monthly wages 2010-2012

Malaysian government statistics, Salaries and Wages Survey Report 2012

Nepal Mean daily wage in agriculture nationally 1995/96, 2003/04 and 2010/11

Nepal Living Standards Measurements – in Nepal LSMS Report 2011

Sri Lanka Agricultural daily wages in Sri Lanka nationally 2007-2012

Department of Census and Statistics Sri Lanka Labour Force Survey Annual Reports

wagesweretaken;whenwagesweregivenonlyseasonally,peakseasonwageswereused.Wagedatawereseparatedintotwotimeperiods–earlytomid-2000sandmid-2000stoearly2010s10–tocompareaverageannualchangesinruralwages–dependentvariable–toaverageannualchangesacrossthesametimeperiodinthreeindependentvariables:agriculturalproductivity,manufacturingandtheruralworkingpopulation.

Burma/Myanmarwasexcludedasdataonindependentvariableswerelacking.Malaysiawasexcludedaswagedatawerereadilyavailableonlyfor2010-2012.

Thedatasetendedupcomprising11countries,6ofwhichcoveredbothtimeperiods,giving17observationsinall.Table3showsthecountriesandyearsofobservations:greytogreenrepresentingthefirstperiodandgreentoredthesecondperiod.

Potential factors affecting rural wagesNationaldatarepresentingagricultural labour productivity, the value of manufacturingandthesizeoftherural working populationwerecompiled,asTable4shows.

10 Thesetimeperiodsvaryslightlydependingonavailabilityofdata.

26 ODI Report

Table 3: Time spans covered by data


Table 4: Data on key variables influencing rural wages and sources

Variable Description of data Source

Agricultural labour productivity Agricultural productivity per worker was constructed by taking gross production value of all agriculture in constant 2004/06 US dollars, divided by the estimated total economically active population in agriculture

Data not available for Burma/Myanmar

FAOSTAT

Value of manufacturing Manufacturing, value added in constant 2005 US dollars Manufacturing refers to industries belonging to International Standard Industrial Classification (ISIC) divisions 15-37(https://unstats.un.org/unsd/cr/registry/regcst.asp)Data not available for Burma/Myanmar

World Bank Development Indicators

Rural working population Constructed from data for rural population and the proportion of the total population between the ages of 15 and 64Applying the fraction of the total population aged 15-64 to the rural population gives an estimate of the rural working population. Ideally, the fraction of the rural population aged 15-64 would be used, but these data were not readily available

World Bank Development Indicators

4. Results


4.1 Description of key variables

Rural wagesTable5summarisesthewagedatafoundoverthreeperiodswhereavailable:i)early2000s,ii)mid-2000sandiii)late-2000stoearly2010s.Wagesarepresentedinconstant2010USdollars,withpercentagechangesbetweentheperiodsshownintheright-handcolumns.

Ruralwagesroseinmostcountriesandoverbothperiods(seeFigure11).Theexceptionsarefew:Pakistaninthesecondperiod;thePhilippinesformostcropsintheearlyperiodandallcropsexceptriceinthelaterperiod;andBangladeshinthefirstperiod.China,VietnamandsomeprovincesofIndonesiasawthemostpronouncedincreases.Attheotherendofthespectrum,PakistanandthePhilippinessawstagnantorfallingwages.Rural wages increases accelerated in the 2000sforthemajorityofcountrieswherethetwoperiodscouldbecompared.AccelerationwasclearforallseriesfromBangladesh,China,India,NepalandtheRepublicofKorea.WageincreaseshadslowedinThailandandVietnam.TheresultsforthePhilippinesweremixed.

Evenwithincreasesinthe2000s,levels of wages in rural areas in the early 2010s remained low,withfewexceptions.Onlytwoobservationsexceeded$10aday:farmworkersinMalaysiaanddairyprocessworkersintheRepublicofKorea.Indeed,manyobservationswerebelow$5aday.Considerwhatthatmeansforhouseholdsthathavetodependonsuchearnings.Ifaworkerwereemployedforsixdaysaweek,yearround–astrongassumption,whensomuchruralworkisseasonal–thenannualwageearningswouldbe$1,560.Assumingonedependantforeveryworker,thenaveragepercapitaincomeswouldcometojust$2.14aday.Thismayjustclearthepovertyline,butnotbymuch.Twoqualificationsapply,however.Oneisthatsomeruralhouseholdscouldhaveearningsfromnon-farmenterpriseswithhigherreturnstolabour;theotheristhattheconversiontoUSdollarshasbeendoneatmarket,ratherthanpurchasingpowerparity(PPP),rates–seeAnnexC11forPPPconversionsthatshowmanymorecaseswherewagesexceed$10aday.

Forfourofthecountries,China,India,PakistanandBangladesh,availablewage data are differentiated by gender.Ruralwagesforwomenareinmostcasesbetweenaquarterandone-thirdlessthanthosepaidtomen.Comparingdifferencethroughtime,thewagegapappearstobenarrowing,withrelativeincreasesinfemalewagesslightlyoutstrippingincreasesinthewagesoftheirmalecounterparts(seeFigure12).FemalewagesasaproportionofmalewagesgrewinmostofthefiveprovincesinChina,inIndiaslightlyandinBangladeshoverthelastperiodinparticular.NoprogressisapparentinPakistan,wherethewagegapisthe

worstofthesample,withfemaleagriculturallabourwageslessthanhalfofmalewagesin2012.

Agricultural labour productivity From1995to2012,agricultural labour productivity improvedinallofthesamplecountries,theexceptionbeingPakistan(seeFigure13).

Increasesfrom2005to2012canbecomparedwiththoseseenfortheprecedingsevenyears–1997-2004(seeFigure14).Mostcountriesshowanaccelerationintheaveragerateofgrowth:China,India(fromalmostnogrowthtoalmost3%ayear),Indonesia,Pakistan(fromnegativetopositive),Bangladesh,Thailand,RepublicofKorea,NepalandSriLanka(alsofromnegativetopositive).Incontrast,thePhilippines,VietnamandMalaysiasawaverageannualratesofgrowthshrinkfromthefirsttosecondperiod,althoughtherateremainedrelativelyhighinthecasesofVietnamandMalaysia.

Value of manufacturing outputFrom1995to2012,thevalueofmanufacturingoutputgrewacrossallcountries(seeFigure15),albeitatconsiderablydifferentrates.

Comparingmanufacturinggrowthin1997-2004withthatfor2005-2012(seeFigure16),showsitacceleratedforChina,India,Indonesia,Bangladesh,thePhilippinesandSriLanka.Infivecases,growthslowed,althoughfortheRepublicofKoreaandVietnamtheratesstillremainedhigh.

Rural working population Inthemid-1990s,ruralworkingpopulationswererisinginallcasesotherthanfortheRepublicofKorea.By2012,thenumberswerefallinginChina,Malaysia,ThailandandSriLanka–withIndonesiarisingslightlyafterseveralyearsoffalls.Inthesecases,aturningpointhasbeenpassed.Incontrast,anothergrouphashadruralworkingpopulationrisingthroughouttheperiod:Burma/Myanmar,Philippines,VietnamandSouthAsia.

Allcountriessawratesofgrowthfallbetween1997-2004and2005-2012,exceptfortheRepublicofKorea,whichexperiencedaconstantrateofdecline(seeFigure18).ThemostdramaticchangeoccurredinChina,wheretheruralworkingpopulationchangedlittleintheearlierperiodbutshrankonaverage,by1.7%ayear,inthelatter.InIndonesia,thegrowthratebecamenegativeinthesecondperiod,whileinThailand,MyanmarandSriLankaitdeclinedtohalfapercentperyearorless.

4.2 Causes of changes in rural wages

Examining the dataAmultivariatesimplelinearregressionwasconducted,withdatafromapanel,unbalancedowingtodata

11 Annexesareavailablefordownloadat:www.odi.org/rural-wages

30 ODI Report

Table 5: Real rural wages and changes for 13 Asian countries, 1995/96-2013

US$ real daily wages (constant 2010a) Change in wages (%)

Average daily wages

Early 2000s Mid-2000s 2010s Early 2000s-mid-2000s

Mid-2000s-2010s Early 2000s- 2010s

China 1998 2003 2006 1998-2003 2003-2006 1998-2006

Gansu province, poor areas, farm labour, harvest season

2.32 2.89 4.50 25 56 94

Gansu province, poor areas, farm labour, slack season

1.73 2.17 3.21 25 48 85

Agricultural labour, male, five-province average

1998 2003 2007 1998-2003 2003-2007 1998-2007

3.02 3.73 7.18 23 92 137

Jiangsu 3.26 4.30 7.11 32 65 118

Sichuan 2.35 3.29 6.60 40 101 181

Shaanxi 2.20 2.79 7.02 27 152 219

Jilin 4.67 4.64 8.37 -1 80 79

Hebei 2.55 3.60 6.72 41 87 163

Agricultural labour, female, five-province average

2.30 2.76 5.51 20 100 139

Jiangsu 2.49 3.33 5.76 34 73 132

Sichuan 1.92 2.39 4.99 25 109 161

Shaanxi 1.71 2.08 5.29 22 154 209

Jilin 3.58 3.53 6.52 -1 85 82

Hebei 1.71 2.37 4.92 38 108 187

India 2000/01 2005/06 2012/13 2000-2005 2005-2012 2000-2012

National, agricultural labour, male

2.13 2.15 2.91 1 35 36

National, agricultural labour, female

1.59 1.61 2.21 1 37 38

Indonesia n/a 2007 2010 n/a 2007-2010 n/a

98 villages, survey data, 7 provinces, median

2.92 3.64 25

Lampung 2.55 3.58 40

Central Java 2.27 2.67 18

East Java 2.36 2.84 20

West Nusa Tenggara

3.00 3.05 2

South Kalimantan 3.29 4.76 44

North Sulawesi 5.08 9.00 77



Average daily wages


Mid-2000s-2010s Early 2000s- 2010s

South Sulawesi 3.05 3.44 13

National average, animal husbandry workers

n/a 2007 2013b n/a 2007-2013 n/a

3.25 4.05 25

Pakistan n/a 2007 2012 n/a 2007-2012 n/a

National, agricultural workers

2.77 2.35 -15

Male 3.36 2.97 -12

Female 1.68 1.46 -13

Average daily wage, crop workers

2000 2004 n/a 2000-2004 n/a n/a

2.33 2.63 13

Bangladesh 2000 2005 2010 2000-2005 2005-2010 2000-2010

National, peak season, male

1.92 1.92 2.78 0 45 44

National, lean season, male

1.53 1.52 2.21 -1 46 45

National, peak season, female

1.32 1.22 2.02 -8 66 53

National, lean season, female

1.10 1.02 1.62 -7 58 48

Philippines 2000 2005 2012 2000-2005 2005-2012 2000-2012

National, farm labour all crops

4.61 4.47 4.54 -3 2 -2

Rice 4.77 4.58 5.09 -4 11 7

Corn 4.21 4.03 3.91 -4 -3 -7

Coconut 4.37 4.56 4.32 4 -5 -1

Sugarcane 5.39 4.95 4.38 -8 -11 -19

Central Luzon (rice bowl) rice labour

1998/99 2007/08 2011/12 1998/99- 2007/08 2007/08-2011/12 1998/99-2011/12

8.83 9.00 8.20 2 -9 -7

Vietnam 2005, 2009 2012 2005-2009, 2009-2012

2005-2012

National, agriculture, forestry and fishing work, state sector

4.05, 6.29 8.63 55,37 113

Daily wage agricultural labourer 1993 = 1.45; 1998 = 2.13

2002

2.16

Average income of wage worker in rural areasc

2007, 2010 2012 2007-2010, 2010-2012

2007-2012

3.92,4.69 5.26 20, 12 34

Thailand 2001 2007 2013 2001-2007 2007-2013 2001-2013

32 ODI Report


Average daily wages


Mid-2000s-2010s Early 2000s- 2010s

National, skilled agriculture and fishing workers

4.02 5.36 6.81 33 27 69

Burma/Myanmar 1998 2004 1998-2004

Ayeyarwardy, rice labour

1.55 2.26 45

Republic of Korea 2000 2006 2000-2006

National, field crop worker

41.21 56.20 36

National, dairy product processor

1996 2001 2006 1996-2001 2001-2006 1996-2006

39.12 44.52 51.03 14 15 30

Malaysia 2010 2012 2010-2012

National, agriculture sector

10.82 11.75 9

Nepal 1995/96 2003/04 2010/11 1995/96-2003/04 2003/04-2010/11 1995/96-2010/11

National, agriculture sector

1.39 1.73 2.22 24 29 60

Sri Lanka 2007 2012 2007-2012

National, agriculture daily work

2.24 3.08 38

Notes: a) Values all in constant 2010 values except for Burma/Myanmar, which is in constant 2012 values, owing to currency valuation; b)

2013 data for Indonesian animal husbandry workers goes to June; c) data on average income of wage workers in rural areas — included to

show the contrast between state sector wages and average worker incomes.

The three dates over which the data are presented vary by country depending on availability, hence the subheadings that list the actual dates.

Where male or female is not specified, wages are not disaggregated by gender.

Source: Data from various sources, as described in Table 2. See Annex B for detailed sources and wages in local currency. (Annexes are availble

for download at: www.odi.org/rural-wages).


Figure 11: Agricultural wage changes, 13 Asian countries, early and late 2000s, average annual rates

-5 0 5 10 15 20 25 30

Philippines: SugarcanePakistan: National agPakistan: Female ag

Pakistan: Male agPhilippines: Central Luzon rice

Philippines: CornPhilippines: All cropsPhilippines: Coconut

Indonesia: West Nusa TenggaraPhilippines: Rice

Pakistan: Crop workersIndonesia: Animal husbandry

Indonesia: South SulawesiMalaysia: ag sector

India: MaleIndia: Female

South Korea: Field crop workerSouth Korea: dairy prod. processor

Indonesia: Central JavaIndonesia: East Java

Nepal: Ag sectorMyanmar: Ayeyarwardy rice

Sri Lanka: Ag dailyIndonesia: 98 villages, 7 prov, median

Bangladesh: Lean season, maleBangladesh: Peak season, male

Bangladesh: Lean season, femaleVietnam: Ag daily

Thailand: Skilled ag & fishingBangladesh: Peak season, female

Indonesia: LampungVietnam: Avg inc. wage worker, rural

Indonesia: South KalimantanChina: Jilin male

China: Jilin femaleChina: Gansu poor areas, slack season

China: Jiangsu maleChina: Gansu poor areas, harvest

China: Jiangsu femaleIndonesia: North Sulawesi

China: 5 province average maleChina: 5 province average female

Vietnam: Ag, forest, fishing, state sectorChina: Hebei male

China: Sichuan femaleChina: Sichuan maleChina: Hebei female

China: Shaanxi femaleChina: Shaanxi male

Average annual wage change period 2 Average annual wage change period 1

Source: Constructed from data in Table 5.

34 ODI Report

Figure 12: Changes in the gender wage gap in four Asian countries

76 76

82

78 77

67

74

77

73

75 76

66

77

81

76 75

78

73

60

65

70

75

80

85

0

1

2

3

4

5

6

7

8

95

prov

ince

ave

rage

Gia

ngsu

Sic

huan

Sha

anxi

Jilin

Heb

ei

5 pr

ovin

ce a

vera

ge

Gia

ngsu

Sic

huan

Sha

anxi

Jilin

Heb

ei

5 pr

ovin

ce a

vera

ge

Gia

ngsu

Sic

huan

Sha

anxi

Jilin

Heb

ei

1998 2003 2007

%

Dai

ly w

age,

US$

, con

stan

t 201

0

Male Female Female wage (% of male)

75 75 76

60

65

70

75

80

85

0

0.5

1

1.5

2

2.5

3

3.5

National National National

2000/01 2005/06 2012/13

%

Dai

ly w

age,

US$

, con

stan

t 201

0 India

50 49

3537394143454749515355

00.5

11.5

22.5

33.5

4

2007 2012

%

Dai

ly w

age,

US$

, con

stan

t 20

10

Pakistan

69

64

73 72

67

73

60

65

70

75

80

85

0

0.5

1

1.5

2

2.5

3

2000 2005 2010 2000 2005 2010

Peak season Lean season

%

Dai

ly w

age,

US$

, con

stan

t 201

0 Bangladesh

Source: Constructed from data in Table 5.


Figure 13: Changing agricultural labour productivity, 12 Asian countries, 1995-2012, gross value production per worker, constant US$ 2004/06

Source: Data from FAOSTAT.

Figure 14: Average annual growth rate of agricultural labour productivity, 12 Asian countries, 1997-2004 and 2005-2012

3.2

0.1

2.9

-0.7

2.62.2

5.0

3.1

4.0

4.9

0.9

-0.7

3.6

2.73.3

0.5

3.0

1.6

3.0

3.7

5.7

4.3

2.1 2.4

-1

0

1

2

3

4

5

6

%

Average annual growth rate 1997-2004 Average annual growth rate 2005-2012

Source: Data from FAOSTAT, simple linear growth rates computed.

Figure 15: Changes in value of manufacturing across 12 Asian countries, 1995-2012

Note: Data for China stop at 2010.

Source: Data from World Bank WDI.

36 ODI Report


availabilityforsomecountries.Averageannualchangeinruralwageswasthedependentvariable,whileindependentvariableswereaverageannualchangesinagriculturalproductivity,valueofmanufacturingandnumberofruralworkers,aswellasadummyvariabletodifferentiatebetweentheearly(1)andlate2000s(0).

Scatterplotsshowrelationsbetweenthedependentandindependentvariables(seeFigure19).Visually,itseemstheexpectedrelationsapply:increasesinagriculturallabourproductivityandmanufacturingoutputcorrespondwithincreasesinruralwages,whileincreasednumbersofruralworkerscorrespondwithslowergrowthofruralwages.

Acorrelationmatrixofthevariables(seeTable6)showschangesinruralwagesdoindeedcorrelatequitestronglywiththeindependentvariables,withcoefficientsintherange0.60-0.66.Thematrix,however,alsoshowstheindependentvariablesalsocorrelatequitestrongly.Thatchangestoruralworkforceshouldcorrelateinverselywithagriculturallabourproductivitydoesnotsurprise:iftherearefewerruralworkers,onemightexpectmechanisationandotherinvestmentsonthelandmightcompensate.Similarly,theinversecorrelationbetweenruralworkforceandgrowthofmanufacturingoutputmightbeexpectedsincesomeoftheworkersinmanufacturingmaycomefromruralareas.Neitheroftheserelations,however,areautomatic:theresultofpeopleleavingruralareascanbeabandonedfieldsratherthanhigherlabourproductivity;formanufacturing,labourmaycomefromurbanratherthanruralareas.

Thecorrespondencebetweenagriculturallabourproductivityandmanufacturingoutput,however,wasunexpected,sinceitishardtoseeadirectcausalrelation.Presumably,factorsthatdrivegrowthofmanufacturingalsoencouragehigherproductivityoflabouronfarms–suchasavailabilityofcapitalandspreadoftechnicalknowledge,expertiseandskills.

ThecorrelationmatrixhintsatsomepositivedevelopmentprocessesinAsia,inwhichvigorousgrowthofmanufacturingdrawslabourfromruralareas,whilefarmersthenusemachineryandintensifyuseofotherinputstocompensateforlostlabourandhenceraiseoutputperagriculturalworker.

Regression to explain changes in rural wagesResultsoftheregressionprovedhighlysignificant(AnovaFtest99%significant)(seeTable7),withahighadjustedR-square,indicatingtheindependentvariablescouldexplainalmosttwo-thirdsofthevariationinchangesinruralwages.Giventhelackofdegreesoffreedomfortheregression,thisisapleasingresult.

Thecoefficientsontheexplanatoryvariablesalsocarrytheexpectedsigns.Thatonagricultural labour productivityispositive,butnotsignificantinthepresenceofothervariables.Thevalue of manufacturing,incontrast,hasalargeandsignificantpositivecoefficient.Thecoefficientonruralworkersisstronglynegativeandsignificant,whilethecoefficientonthetime dummyisasmallnegative,andalsosignificant.

Thestrongestdriverofchangestoruralwagesturnsouttobenumberofruralworkers,afunctionofpopulationgrowthinruralareaslessnetmigrationfromruraltourbanareas.Thisisanintriguingresult,sinceitbegsthequestionofwhetherthevariationsingrowthoftheruralworkforceresultsprimarilyfromthedemographyofruralfertilityandlifeexpectancy,orwhetherout-migrationfromruralareasplaysasignificantrole.Becauseofalackofreadilyavailabledata,wecannotaddressthisquestionnow.12Changeinruralworkersseemstobethevariablethatmostsharplydifferentiatesthesamplecountries.

Growthofmanufacturingoutputisthenextstrongestdriverofruralwages.Themostlikelycausallinkisthat

Figure 16: Average annual growth rate of manufacturing in 12 Asian countries, 1997-2004 and 2005-2012

9.6

5.4

3.4

5.9 5.7

3.1

10.3

5.3

8.4

5.3

2.1 3.2

10.5

7.9

4.2 2.9

7.8

3.6

8.3

3.1

5.5

2.4 1.6

5.6

0

2

4

6

8

10

12

%


Source: Data from World Bank WDI, simple linear growth rates computed.

Figure 17: Changing rural working population, 12 Asian countries, 1995-2012

Source: Data from World Bank WDI

12 Datamightbefoundbylookingatindividualcountrycensusdata,andifnecessaryconstructingdemographicmodels.Apreliminarylookatfertilityratesshowssomestrikingreductionsinfertilitysince1970:allcountrieshaveseenhavelargereductions,althoughsomestartedthereductionsearlierthanSouthAsia.

38 ODI Report


Figure 18: Average annual growth rate of rural working population in 13 Asian countries, 1997-2004 and 2005-2012

3.2

0.1

2.9

-0.7

2.62.2

5.0

3.1

4.0

4.9

0.9

-0.7

3.6

2.73.3

0.5

3.0

1.6

3.0

3.7

5.7

4.3

2.1 2.4

-1

0

1

2

3

4

5

6

%


Source: Data from World Bank WDI, simple linear growth rates computed.

Figure 19: Changes in rural wages compared with those for agricultural labour productivity, manufacturing and rural workers over two periods

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

-2% 0% 2% 4% 6% 8% 10% 12% 14%

Ave

rage

ann

ual c

hang

e in

rura

l wag

es

Average annual change, independent variables

Agricultural productivity period 1

Agricultural productivity period 2

Manufacturing period 1

Manufacturing period 2

Rural workers period 1

Rural workers period 2

Linear (Agricultural productivity)

Linear (Manufacturing)

Linear (Rural workers)

Source: Constructed from various sources, see Tables 2 and 3 for details.

higherwagesinmanufacturingdrawworkersfromfarmstofactoriesandtherebydriveupruralwages.

Changestoagriculturallabourproductivitywouldbethenextstrongestinfluence,buttheresultisinsignificant.Thiscouldbebecausetherearetoofewobservationstoconfirmtheexpectedrelation,oritmaybethat,afteraccountingfortheeffectsofthetwopreviousvariables,itaddslittletoexplainchangesinruralwages.

Lastly,thedummyforthefirsthalfofthe2000sisbothsignificantandnegative,althoughthevalueofthecoefficientissmall.Presumably,itpicksouttheinfluenceofsomeomittedvariable,orelsetheinfluencesmodelledonruralwageshaveintensifiedsincethemid-2000s.Givenhowsmallthecoefficientiscomparedwiththoseontheotherexplanatories,whateverthedummyrepresentsisnotthatimportant.

Overall,itseemsthemodelsupportsinitialhypothesesaboutthefactorsexplainingchangesinruralwages.Themain

qualificationisthatthepullofmanufacturingoutperformsthatofhigheragriculturalproductivity,andbysomeconsiderablemargin.

Table 6: Correlation matrix between variables

Agricultural labour productivity

Manufacturing Rural workers

Rural wage 0.65 0.6 -0.66

Agricultural labour productivity

1.00 0.65 -0.56

Manufacturing 1.00 -0.44

Rural workers 1.00

Table 7: Multivariate regression of changes in rural wages

Dependent: change in rural wages

Coef. Std. err. T.stat. P>│t│ 95% conf. interval

Agricultural output per worker

.194 .844 0.23 0.822 -1.65 2.03

Value manufacturing

.808 .363 2.23 0.046 0.17 1.599

Rural population 15-64

-1.754 .909 -1.92 0.079 -3.72 .235

Dummy for period -.045 .017 -2.68 0.020 -.081 -.008

Constant .028 .025 1.15 0.271 -.025 .082

Note: F(4,12) = 7.95, Prob > F = 0.0023; R-squared = 0.7260, Adj R-squared = 0.6347.

Source: Regression analysis in STATA.

40 ODI Report

5. Conclusions and implications

5.1 Discussion of findingsTheresultsfromthisstudybroadlyconfirminsightsfromtheliteratureandhenceourexpectations.Insum:

• InmostcountriesofAsia,ruralwagesroseduringthe2000s.Evenso,typicalruralwagesremainlow,atlevelsthatwouldbarelyallowhouseholdsthatdependonlabouringforincomestoescape($2aday)poverty.

• Insomecountries,includingBangladesh,ChinaandIndia,increasesinruralwagesacceleratedinthesecondhalfofthedecade.WageincreasesslowedonlyforThailandandVietnam,andforsomealthoughnotallwageseriesforthePhilippines.

• Itseemschangesinruralwagesareassociatedinverselywithchangesinruralworkingpopulation,anddirectlywithgrowthofmanufacturing.Changesinagriculturallabourproductivitymaybeassociatedwithhigherwages,buttheestimateprovedinsignificantandlowinthepresenceofthesetwomaindrivers.Asmallbutsignificanttimeshiftersuggestswagesgrewfasterinthesecondhalfofthe2000s,independentlyofchangeinothervariables.

Changesinruralworkingpopulationmaybethesinglemostpowerfuldriver,but,sincemigrationisincorporatedwithinthevariable,itisnotapurelyexogenousdriver.Asmanufacturinggrows,itisexpectedthatsomeofthefactoryworkerswillberecruitedfromthecountrysidesothemigrationcomponentislinkedtomanufacturing.Itisnotsurprising,then,thatgrowthofmanufacturingappearsasthenextmostpowerfulinfluenceonagriculturalwages.

Hence,theanalysissupportsideasaboutthepullofmanufacturingonruralwages,butalsosuggestsdemographyplaysasignificantrole.Indeed,whentheexplanatoryvariablesconsideredhereareexamined–seeSection4.1–thelargestdifferencesacrosscountriesariseintheruralworkingpopulation,withasharpdistinctionbetweenthosecountrieswheretheruralworkforceisnowshrinkingandthosewhereitcontinuestoincrease.CountriesofEastAsiabelongtotheformergroupandthoseofSouthAsiatothelatter,withcountriesinSoutheastAsiafallingineither.

Thisbroadlysupportstheliteraturethatreportsthesamepullofmanufacturingasdrivingupruralwages.Demographyfeatureslessintheliterature,exceptforChina,wheretheeffectsoftheOneChildPolicyhavearousedkeeninterest.

5.2 ImplicationsWillruralwagesinAsiacontinuetoincreaseinthefuture?

Demographyclearlymatters.FertilityrateshavefallendramaticallyacrossAsiasincetheearly1960s.In1960,

rateswerehigh,withcountryratespackedinabandbetween5.5andjustover7childrenonaveragetowomenintheirreproductivelife.By2012,thebandranfrom1.2to3.3,withseveralcountriesincludingChinabelowtherateof2.1neededtosustainpopulationinthelongterm.Mostofthetransitioninfertilityratestookplacebetweentheearly1970sandlate1990s.Forthosecountriesthatmadethetransitionlater,itistobeexpectedthattheeffectofthosefallingfertilityrateswillworktheirwaythroughinthesecondhalfofthe2010s,sincetheimpactontheworking-agepopulationwillbefelt15yearsormoreafterthereductioninfertility.Itisthushighlylikelythat,evenforcountriesthatstillhavegrowingruralworkforces,growthrateswillslowandsoonerorlaterturnnegative.

Therateoffuturegrowthofmanufacturingmaybemoredifficulttoforesee,althoughitishardtoimaginethatmanufacturingwillceasetogrowinthenearfuture.Anyslowdowningrowthofmanufacturingmaybecompensatedforbyincreasesinservicesinurbanareas.

Ifthetwomaindriversofrisingruralwagesarelikelytocontinuetheirrecenttrends,itseemsthatruralwagescanbeexpectedtoriseinthefuture.Theimplicationsofrecentincreasesandthoselikelytocomecouldhaveprofoundimplicationsforpoverty,foragricultureandfoodpricesandformanufacturing.

Rising rural wages will put a floor to low rural incomes –atleastforthoseabletowork–and,indeed,probablytoincomesthroughouttheeconomy,sinceruralwageshavetendedtomarkthelowestreturnstolabouronoffer.Hence,risingruralwagesshouldgreatlyreducepovertyformosthouseholdsthathaveworkingmembers.Mostofthepoorwillthenbethoselivinginhouseholdsthatlackmembersearning,wherethereareonlytheold,infants,thechronicallysickandthebadlydisabled.

Althoughruralwagesroseinmostcountriesthroughoutthe2000s,andoftenprobablyforsometimebeforethat,levelsremainlowinmostcountries.Itwilltakesometimemorebeforetheyreachalevel–perhapsUS$10aday13–thatliftsatypicalworkinghouseholdcomfortablyoutofpoverty.

Rising rural wages will push up costs of production in agriculture–alreadyincreasedbytheeffectofhigheroilpricesseensince2007–andspuronmechanisationforthosetaskswheremachineryischeaperthantheincreasedcostofmanualoperations.Asmachinesreplacelabour,theadvantageofsmall-scalefarmsinlaboursupervisionwillweaken,soaconsequencemaybeanincreaseinfarmsizes(Otsukaetal.,2014).

Butthelargereffectwillbeonfood prices.Asianfoodpriceswillrise,limitedtosomeextentbythepossiblelowercostofimportsfromtheworldmarket–moderatedbythewillingnessofgovernmentstoallowimportsofcheapfoodthatmightthreatenfarmers’incomes.Risingfoodpricesthreatenaccessofthoseonlowincomesto

13 Assumeonedependantforeveryworker.Assumerurallabourcangetworkfor250daysayear.$10adayinwagesthenequatestojustoverUS$3adayincomeperperson.

42 ODI Report

food.Thequestionthenistheextenttowhichhigherruralwagesmorethanoffsetthiseffect.Giventhateventhoseonlowincomesdonotspendalltheirincomesonfood–70%atmost–thenthewageseffectshouldoutweighthatofhigherfoodcosts.

Perhapsthemost intriguing implication is for manufacturing.Untilrecently,mostmanufacturersinAsiahavebeenabletorecruitunskilledlabourfromruralareasatlowcost,givenlowruralwages.But,asruralwagesrise,soitislikelymanufacturingwageswillhavetoincreasetorecruitnewworkers.ThiseffectisalreadybeingseenstronglyinChina,wherebothphenomenaarelinkedtoanationalworkforcethatisnowshrinkingeveryyear.Manufacturershavetwooptionsasthistakesplace:tomechaniseandtherebyeconomiseonlabour;ortorelocatetoregionsandcountrieswithlowerlabourcosts.Giventhescaleofitsmanufacturing,China’sdecisionswillbecritical.Ifthemostcommonanswerisrelocation,thenitislikelythatplantsincoastalChinawillmoveinlandtolessprosperousareaswithlowerwages,butalsorelocateoutsideofChina.NeighbouringcountriesinAsiawithlowwagesmaybethefirsttobenefitfromthis,with

Bangladesh,Burma/Myanmar,CambodiaandVietnamclearcandidates.

Thereis,however,afurtherprospect:thatofcompaniesmovingtoAfricainsearchoflowerwages.TheWorldBankreportsEthiopianfactorywagesforunskilledlabourasonequarterthoseofChinesewages.Logisticscostsarehigher,butoverallcostsarelower.OutsideAddisAbaba,thefirstpioneerwaveofrelocatedChineseplantscanbeseen.Nowthesehavebrokentheice,howmanymorewillfollow?Lin(2014,inWonacott,2014)speculatedthat85millionfactoryjobscouldleaveChinainthecomingyears.IfhalfofthosecametoAfrica,itwouldtransformacontinentwherethereisasurgeinyouthenteringthelabourmarket.Ofcourse,relocationtoAfricawillonlyhappenifroads,powersuppliesandportsareadequateandifthereispoliticalstability,

Africa’seconomicunderperformancehassincethe1970sbeenfargreaterinmanufacturingthaninfarming.RenewedgrowthofmanufacturinginAfricaledbyAsianindustrialistspromisesprosperousurbanisationwithvibrantmarketsforthosefarmersstayingontheland.Thiswouldbewelcomenewsallround,includingforagriculture.


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46 ODI Report

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