國(guó)際勞工組織（ILO）：城鄉(xiāng)就業(yè)和工資差距

International

Labour

Organization

ILOWorkingPaper107

February/2024

?Employmentandwagedisparitiesbetweenruralandurbanareas

Authors/SévaneAnanian,GiuliaDellaferrera

二—=Q

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01?ILOWorkingPaper107

Abstract

Statisticalevidencefrom58countriesshowsthatalthoughpeopleinruralareasaremorelikelytobeinemploymentthanthoseinurbanones,theyalsotendtohavejobsthatcanputthematriskofexperiencinginadequatelabourprotectionaswellaslowpay.Inparticular,ruralwork-ersarepaid,onaverage,24percentlessthantheirurbancounterpartsonanhourlybasis,andonlyhalfofthisgapcanbeexplainedbyrural-urbandiscrepanciesineducation,jobexperienceandoccupationalcategory.Developingcountriesexhibitarelativelywidergap,withtheunex-plainedpartalsobeinglarger.Furthermore,inmanycountries,certaingroupsofruralworkersareatgreaterdisadvantage,suchaswomen,who,onaverage,appeartoearnlessthanmeninruralareas.However,institutionalandregulatoryframeworks,notablythosethatsetminimumwagesorseektopromoteequalopportunities,canhelptoreducelabourmarket-relatedine-qualitiesacrosstherural-urbandivide.

Abouttheauthors

SévaneAnanian

SévaneAnanianjoinedtheResearchDepartmentoftheInternationalLabourOrganization(ILO)inSeptember2021.Hisfieldsofstudiesincludeinequalitiesandwagesettinginstitutions.HepreviouslyworkedasawagespecialistbasedattheILOCairooffice,whereheprovidedsup-portonwagepoliciestoAfricancountries.Formerly,heservedasaneconomistatthestatisticalserviceoftheFrenchministryoflabour(DARES)andasarapporteurfortheFrenchminimumwageexpertgroup.

GiuliaDellaferrera

GiuliaDellaferrerajoinedtheResearchDepartmentoftheILOinAugust2023,whereshefocus-esonwork-relateddiscrimination,inequalities,violenceandharassment,aswellasoccupation-alsafetyandhealth.Previously,sheworkedonforceddisplacementatUNHCRProtectionUnitforBelgiumandLuxembourg,andasalegalassociateatICRCRegionalDelegationinParisandGenocideWatch.Sheisspecialisedinhumanrightsandinternationalhumanitarianlaw.

02?ILOWorkingPaper107

Tableofcontents

Abstract

01

Abouttheauthors

01

Acronyms

07

Introduction08

1Dataanddefinitions

Asampleofhouseholdsurveysfrom58countries

Nationaldefinitionsofurbanandruralareas

10

10

11

2Employmentinruralandurbanareas

12

Amethodologyforanalysingthedifferencesinlabourmarketoutcomesbetweenruraland

urbanareaswhileaccountingforthecharacteristicsofpopulations

12

Evenaftercontrollingforageandeducation,livinginaruralareaincreasesthelikelihoodof

employmentacrossallcountryincomegroups

13

Workersinruralareasaremorelikelytobeself-employed

14

?3Wagesinruralandurbanareas

Higherproportionoflowpaidworkersinruralareas

Ruralemployeestendtohavelowereducationalattainmentandlessexperiencethanurbanemployees,especiallyindevelopingcountries

Aspecificoccupationalprofileofruralemployees

Ruralemployeesearnonaverage24percentlessthanurbanemployees,withhalfofthatgapexplainablebydifferencesintermsofeducation,experienceandoccupation

Onaverage,ruralfemaleemployeesearnlessthantheirmalecounterparts

Rural-urbanpaygapandminimumwages

19

19

20

21

23

27

28

4Legalframeworksfortacklingrural-urbanimbalancesinemployment

andwages

32

Theroleofinternationallabourstandards

32

Internationallabourstandardsonequalityandtheeliminationofdiscriminationinrespect

ofemploymentandoccupation

33

Internationallabourstandardsonminimumwagesandwage-setting

34

Otherinternationallabourstandardsdealingwithwages

36

Nationalpracticesrelatedtoinequalitiesinruralareas

37

India'sNationalRuralEmploymentGuaranteeSchemes:Theimpactofruralpublicworkson

agriculturalwages

37

03ILOWorkingPaper107

Austrianlegislationongenderequalityinruralareas38

Conclusions

40

Appendix

41

References

47

Acknowledgements

52

04?ILOWorkingPaper107

ListofFigures

Figure1.Shareofwomenamongemployees,bycountryincomegroup,2019orlatestavaila-bleyear(percentage)

Figure2.Shareofwomenamongself-employedworkers,bycountryincomegroup,2019orlatestavailableyear(percentage)

FigureB.2.1Distributionofselfemployedworkersinruralandurbanareasaccordingtotheirnumberofhoursworked,bycountryincomegroup,2019orlatestavailableyear(percentage)

FigureB.2.2Distributionofemployeesinruralandurbanareasaccordingtotheirnumberofhoursworked,bycountryincomegroup,2019orlatestavailableyear(percentage)

FigureB.2.3.Shareoftemporarycontratctsinruralandurbanareas,bycountryincomegroup,2019orlatestavailableyear(percentage)

Figure3.Shareofruralemployeesineachquintileofthewagedistribution,bycountryin-comegroup,2019orlatestavailableyear(percentage)

Figure4.Shareoflow-paidworkersamongruralandurbanemployees,bycountryincomegroup,2019orlatestavailableyear(percentage)

Figure5.Distributionofruralandurbanemployeesaccordingtotheireducationallevel,bycountryincomegroup,2019orlatestavailableyear(percentage)

Figure6.Distributionofruralandurbanemployeesaccordingtotheiragegroup,bycountryincomegroup,2019orlatestavailableyear(percentage)

Figure7.Distributionofoccupationsamongruralandurbanemployees,bycountryincomegroup,2019orlatestavailableyear(percentage)

Figure8.Averagepaygapbetweenruralandurbanemployees,bycountry,decomposed,2019orlatestavailableyear(percentage)

Figure9.Genderpaygapinruralandurbanareas,bycountryincomegroup,2019orlatestavailableyear(percentage)

Figure10.Averagewagegapbetweenruralandurbanworkers,incountrieswithaspecific

minimumwagefortheagriculturalsector,2019orlatestavailableyear(percentage)

FigureB.5.1.Shareofruralself-employedworkersineachquintileofthedistributionofin-comefromemployment,2019(percentage)

FigureB.5.2.Averaageemploymentincomegapsbetweenruralandurbanself-employedworkers,decomposed,2019(percentage)

FigureB.5.3.Genderemploymentincomegapamongruralandurbanself-employedwork-ers,2019,(percentage)

FigureA1.Shareofworking-agepopulationlivinginruralareasinthesampledcountries,2019orlatestavailableyear(percentage).

FigureA2.Shareoflow-paidemployeesinruralareasinthesampledcountries,2019orlat-estavailableyear(percentage)

FigureA3.Distributionofmaleandfemaleruralemployeesaccordingtotheirlevelofedu-cationincountrieswithanegativeruralgenderpaygap,2019orlatestavailableyear(percentage)

15

15

17

17

18

20

20

21

21

22

25

27

29

30

30

31

41

42

43

05?ILOWorkingPaper107

ListofTables

Table1.Effectoflivinginaruralareaontheprobabilityoflabourforceparticipation,unem-

ploymentandwageemployment(percentagepoints)14

TableA1.Nationaldatasourcesusedtoanalyseruralandurbanemploymentandwages43

06?ILOWorkingPaper107

ListofBoxes

Box1.Estimatingtheeffectoflivinginaruralareaontheprobabilityofselectedlabour

marketoutcomes

12

Box2.Workingtimeinruralandurbanareas

15

Box3.Analysingtherural-urbanwagegap

23

Box4.Examplesofrecenttrendsinruralrealwages

26

Box5.Employmentincomesfromself-employmentinruralandurbanareasinAngolaand

Brazil

29

Box6.Internationallabourstandardsrelevanttoemploymentandwagesinruralareas32

07?ILOWorkingPaper107

Acronyms

CBOCongressionalBudgetOffice(oftheUnitedStatesofAmerica)

CEACRCommitteeofExpertsontheApplicationofConventionsandRecommendations

(oftheILO)

CPIConsumerPriceIndex

IBGEBrazilianInstituteofGeographyandStatistics

ICLSInternationalConferenceofLabourStatisticians

ICSEInternationalClassificationofStatusinEmployment

INSEENationalInstituteofStatisticsandEconomicStudies(ofFrance)

ISCOInternationalStandardClassificationofOccupations

NREGSNationalRuralEmploymentGuaranteeSchemes(inIndia)

OECDOrganisationforEconomicCo-operationandDevelopment

08?ILOWorkingPaper107

?Introduction

Livelihooddisparitiesbetweenruralandurbanareashavebeenobservedworldwide.Globally,thepovertyrateinruralareasisestimatedat17.2percent,whichismorethanthreetimestherateinurbanareas(5.3percent)(UN2019).Thismeansthataround79percentoftheworldspoorliveinruralareas.

Thesedisparitiesbetweenruralandurbanareasstemtosomeextentfromdifferencesinlabourmarketoutcomes.Morespecifically,combinationsofvariousoutcomesintermsofemploymentandlabourincomescouldexplaininparttherelativedisadvantagefacedbypeoplelivingout-sidecities.Existingevidenceshows,forinstance,thatwhileurbanandruralempioymentratesareusuallyquitesimilarinhigh-incomecountries,peopleinruralareasinpoorercountrieshaveastrongertendencytoparticipateinemployment,asthelackofsocialprotectionorfinan-cialsupportmaypromptthemtotakeupanyavailablejobregardlessofitsquality(ILO2020a).Significantly,oneintenagriculturalworkerswereininformalemploymentin2016-aratethatmaybeindicativeofjobqualitydeficitsintherurallabourmarket.

However,notmanyglobalstudieshavesoughttomeasurerural-urbandiscrepanciesinlabourmarketoutcomeswhiletakingintoaccountthespecificsocio-demographiccharacteristicsofpeo-plelivinginthesetwotypesofarea.Rawassessmentsofrural-urbangapsinlabourforcepar-ticipationandunemploymentcouldgiveapartialpictureoftherural-urbandivideinthelabourmarket,asthesegapsarelikelytoreflecttoacertainextentthedifferentcompositionsofruralandurbanpopulations-includingintermsofageandeducation.Forinstance,employmenthasbeenfoundtodependoneducationandexperienceinmanycases,asinmembercountriesoftheOrganisationforEconomicCo-operationandDevelopment(OECD),wherepeoplewithhigh-ereducationalattainmentare,onaverage,morelikelytohaveajob(OECD2014).Inthatregard,disentanglingtheeffectsofpeople'ssocio-demographiccharacteristicsfromotherdimensionsthatmaymanifestthemselvesalongtherural-urbandivideiscriticalwhenanalysingthelabourmarketoutcomesofruralpopulations.

Furthermore,onlyafewinternationalstudieshaveinvestigatedrural-urbangapsinworkingconditions,indludingearnings.Thereareseveralfactorsthatmaygiverisetosubstantialrural-urbandifferencesinlabourincomeacrosscountries,suchasarelativelylowerruralproductivi-ty.Empiricalevidencefromdevelopingcountriesindeedpointstoproductivityintheagriculturalsector,whichaccountsforalargeshareofemploymentinruralareas,beingsubstantiallylowerthaninothersectors(Gollin,LagakosandWaugh2014).InOECDcountries,productivitylevelsinruralareaswere,onaverage,20percentlowerthanthoseinurbanareasin2015,withanaver-agegapof46percentbetweenthemostandleastproductiveregionsinacountry(OECD2019).!

Asforthefactorsthatshaperural-urbandiscrepanciesinproductivity,theavailableempiricalevidenceshowsthatthespatial"sorting"offirmsandworkersislikelytoplayacriticalrole.Forexample,skilledworkersmaywanttomovetoareasthathavefeatureswhichtheyregardasvaluableorthatofferhigherreturnstoeducation,whilelargefirmsmaybepromptedbyvari-ousincentivestorelocatetheirfacilitiestoareaswithbigmarkets,wheretheirproductivitycanbeboostedthroughimprovedworker-firmmatching(MionandNaticchioni2009;Verstraten,VerweijandZwaneveld2018).

Nevertheless,causesnotdirectlylinkedtoproductivityandworkers'skillsmayalsoexplainpartoftheobservedrural-urbangapinearnings.Forinstance,spatialinequalitiesinrelationtothetreatmentofpeopleinthelabourmarketmayhaveanimpactonemploymentandwage

Amongthereasonsforrural-urbanproductivitygapsaretheeconomicopportunitiesthatcitiesofferrelativetoruralareas.Inthatregard,urbanagglomerationshavebeenfoundtoinherentlycontributetoincreasedproductivity,forinstancebecausetheycanfa-cilitatethe"sharing"ofindivisiblegoodsandfacilitiesorthematchingbetweenworkersandfirms(DurantonandPuga2004).

09?ILOWorkingPaper107

outcomes.InasampleofLatinAmericancountries,theethnicwagegapwasthusfoundtobehigherinruralareasthaninurbanones,evenaftercontrollingforworkersindividualcharacter-sticssuchaseducationandage(Atal,NopoandWinder2009).Focusingonspecificpopulationgroups,somestudieshavehighlightedincomegapsbetweenindigenousandnon-indigenouspopulations,whichtendtobelargerinruralorremoteareas(WilsonandMacdonald2010;AIHW2023).Empiricalstudieshavealsopointedtotherural-urbandivideasasourceofdiscriminationimpactingontheemploymentandwageprospectsofpeoplefromruralareasinsomecountries,suchasChinabecauseofthehukousystem(Chengetal.2013).?

Thepresentstudyseekstoprovideaglobaloverviewofrural-urbandisparitiesinlabourmar-ketoutcomeswhiletakingintoconsiderationthespecificitiesofruralpopulationsintermsofsocio-demographiccomposition,particularlythoserelatingtohumancapitalsuchaseducationandexperience.Aprecisedelineationofthefactorsthatmayshaperural-urbandisparitiesinthelabourmarketiscrucialforthedesignofpoliciesaimedathelpingpeopleinruralareas.

ThisstudyisintendedtocontributetotheILO'seffortstosupportruraldevelopment-atopicthathasbeenontheOrganization'sagendaeversinceitsestablishmentin1919,andwhoseimpor-tancewasreaffirmedbytheInternationalLabourConference'sadoption,in2008,oftheresolu-tionandcondlusionsonpromotingruralemploymentforpovertyreduction.Sincetherenewalofitscommitment,theILOhasbeenassistinggovernmentsandemployers'andworkers'organiza-tionsintheirtransformationofruraleconomies.Inaddition,theSustainableDevelopmentGoalsadoptedin2015bytheUnitedNationsGeneralAssemblycallfortheeradicationofextremepov-ertyforallpeopleeverywhere,includingpovertyassociatedwiththerural-urbandivide(Goal1).3

Afterabriefdescriptionofthedataandthedefinitionofurbanandruralareasusedforthepreparationofthisworkingpaper(section1),theanalysisfocusesonthelabourmarketout-comesthatdescribemaleandfemaleemploymentinbothgeographicalareas,namely,labourforceparticipation,unemploymentandstatusinemployment(section2).Drawingonabroadsampleofcountriesatvariouslevelsofdevelopment,thisoverviewseekstotakeintoaccountthespecificsocio-demographiccharacteristicsofruralpopulations,includingeducationandage.Forthesamecountries,anassessmentofthegapsinearningsbetweenruralandurbanareasisundertakeninsection3withaviewtoidentifyingtheshareoftheearningsgapthatcannotbeascribedtoruralspecificitiesintermsofhumancapitalandtheoccupationsheldbyworkers.Section4providesareviewofthelegalframeworksthatcanbeusedtotacklerural-urbanine-qualitiesinemploymentandwages.Anumberofconclusionsareofferedaftersection4.

Underthehukoufhouseholdregistration")system,individualsmustregisterwithlocalauthorities,whichentailscertainlimitationsondomesticmigration.

Asspecifiedbyindicator1.1.1oftheglobalindicatorframeworkfortheSustainableDevelopmentGoalsandtargetsofthe2030AgendaforSustainableDevelopment,progresstowardstheachievementofGoal1ispartlymeasuredthroughtheproportionofthepopulationlivingbelowtheinternationalpovertylinebygeographicallocation(urban/rural).

10?ILOWorkingPaper107

?1Dataanddefinitions

Asampleofhouseholdsurveysfrom58countries

TheanalysisreliesondatafromlabourforcesurveysandotherhouseholdsurveysintheILOHarmonizedMicrodatacollection,'whichcoversover160countries.Sincethefocusofthisstudyisonthelabourmarketoutcomesofpeoplelivinginruralareas,theanalysisdrawsonsurveysthatincludeinformationonboththeemploymentstatusandearningsofhouseholdmembers,inadditiontothegeographicallocationofthehousehold(urbanvs.ruralareas).Whenitcomestojobcharacteristicsandearnings,thereportedestimatesrefertothemainjobsofindividuals.

Toeliminatevariationinearningsduetodifferencesinworkingtime,theanalysisfocusesongrosshourlywages.Adescriptiveoverviewofworkingtimeinruralandurbanareasisnever-thelessprovidedseparately(seebox2furtherdown).

Eveniftheycollectedinformationonthesedimensions,surveysfromcountrieswithaverysmallsurfacearea-islandssuchasComoros,MaldivesandSamoa-werenotincludedinthesamplestudied.Insuchcountries,theboundariesbetweenurbanandruralareasmaybethin,leadingtoablurringofrural-urbandifferencesandmakingcomparisonslessmeaningful.Nigeriawasnotincludedinthesampleeitherbecausetheavailablesurveydidnotprovidekeyinformationrequiredfortheanalysis,suchastheoccupationsofworkers.

Thefinalworkingdatabasecomprises58countries,coveringallregionsanddifferentlevelsofdevelopment.Intermsofregions,thesampleincludes18countriesfromAfrica,3fromtheArabStates,14fromAsiaandthePacific,7fromEuropeandCentralAsia,and16fromtheAmericas.Intermsofcountryincomegroups,thereare8high-incomecountries,13upper-middle-incomecountries,28lower-middle-incomecountriesand9low-incomecountries.5Theselectedcoun-tries,andtheircorrespondingsurveys,arelistedintheappendix(tableA1).

Whenaveragesareestimatedforthewholesample,orbycountryincomegroup,eachcountrysweightedequally.Thismakesitpossibletohighlighttheroleofcountry-specificinstitutionsandpolicies.Weightingeachcountrybyitsnumberofworkingindividualswouldhavecausedtheresultstobedrivenmainlybythemorepopulouscountries.

Toavoidreflectingshort-termdisruptionlinkedtotheCOVID-19pandemic,thesurveysselectedwerefrom2019orthelatestavailableyearbefore2019.Duringthepandemic,manynationalstatisticalofficesadaptedtheirdatacollectionprocessestothesocialdistancingmeasuresim-plementedintheircountries.Thisislikelytoimpactoncross-countryanalysisfortheyears2020and2021,especiallyoncomparisonsbetweensurveysconductedduringtheCOVID-19crisisandothers.Moreover,particularlyin2020,internalmigrationflowswereobservedinthecon-textofthepandemic,oftenresultinginmigrationlossesinurbanareasandgainsinruralareas.However,thesetrendsappeartohavebeentemporary(González-Leonardoetal.2022;Roweetal.2023).Withtheincreasingavailabilityofpost-pandemicdata,itshouldbecomepossibletoassessmoreaccuratelytheimpactthattheCOVID-19crisishashadontherural-urbandivide.

Formoreinformation,see

/about/data-collection-and-production/

.

Togroupcountriesaccordingtotheirlevelofincomepercapita,theWorldBankdlassificationcorrespondingtotheyearofcollectionofthesurveydatawasused.

11?ILOWorkingPaper107

Nationaldefinitionsofurbanandruralareas

Thedistinctionbetweenurbanandruralareasusedinthispaperreliesonthenationaldefini-tionsofgeographicalareasadoptedbycountries.Differencescanbeobservedacrosscountriesinhowtheydefineruralareas,notablywithregardtothecriteriausedtoidentifytheintegrationofanareaintoanurbanunit.Forexample,until2020,theFrenchnationalstatisticaloffice-theNationalInstituteofStatisticsandEconomicStudies(INSEE)-definedruralareasasallcom-munesnotbelongingtoanurbanunit,itselfdefinedasagroupingofmorethan2,000inhab-itantsinanareawithacertaincontinuityofbuildings,afeaturethatischaracteristicof"towns"(D'Alessandro,LevyandRegnier2021).?incontrast,theclassificationdevelopedbytheBrazilianInstituteofGeographyandStatistics(IBGE)r