F.)Kwame)Yeboah,)Robert)Myers)and)T.)S.))Jayne 1 )

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1 !!!!!!! UnpackingtheSourcesofIncomeGrowth insub8saharanafrica By F.KwameYeboah,RobertMyersandT.S.Jayne 1 March31, YeboahisanAssistantProfessor,MyersisaUniversityDistinguishedProfessor,andJayneisUniversity FoundationProfessorintheDepartmentofAgricultural,FoodandResourceEconomicsatMichiganState University.WegratefullyacknowledgefundingforthisstudyfromtheBillandMelindaGatesFoundation,and appreciatetheguidanceandcommentsonearlierdraftsfromkristenmacnaughtonandsaraboettiger. 1

2 Executivesummary Thispaperprovidesamicro8levelanalysisoftrendsandsourcesofincomegrowthoverthepastdecade amonghouseholdsinsub8saharanafrica(ssadisaggregatedbylocalityofresidence(ruralvsurban areas, households landholding size, proximity to urban markets, and the gender and age of the householdhead.theresultsarederivedfromnationally8representativehouseholdsurveysfromseven countries(ghana,ethiopia,nigeria,malawi,tanzania,uganda,andzambiabetween2003and2015. While cross8country variations warrant caution against overgeneralization, the analysis confirms a generalriseininflation8adjustedhouseholdincomesinssaoverthepastdecade.behindthispositive overarchingpicture,wehighlightfiveimportantdisaggregatedfindings.first,realhouseholdincome in most countries has grown more rapidly among female8headed households than male8headed households (Ghana, Ethiopia, Nigeria, and Uganda. On average, real incomes of female8headed households rose by 105% compared to 33% for male8headed households. However, baseline real incomesoffemale8headedhouseholdswereonly68%thoseofmaleheadedhouseholds.therefore, although female8headed households are catching up, their incomes still lag behind those of male8 headedhouseholdsinthemostrecentsurveysby27%onaverage. Thesecondkeyfindingisthathouseholdswithfavorablemarketaccessconditionshavehigherincomes andexperiencedabout2to5timesmoregrowthintheirincomesthanthosewithrelativelyunfavorable marketaccessconditions.infact,inghana,ethiopiaandmalawi,averageincomesforhouseholdswith morefavorablemarketaccesswereabouttwicethatofthosewithrelativelyunfavorablemarketaccess conditions.third,householdsheadedbyayouth(15824yearshavethelowestaverageincomeand experiencedthelowestgrowthinincomeoverthepastdecade.fromthemostrecentsurveys,incomes forhouseholdsheadedbyyouth(15824yearsis,ontheaverage,about36%and45%lowerthanthat ofhouseholdsheadedbyyoungadults(25834yearsandadults(35yearsormorerespectively.annual growthintheaverageincomeforyouth8headedhouseholdsisalsoabout8810percentagepointslower. Fourth, we find that real incomes have grown more rapidly among urban households than rural households in most countries (Ghana, Ethiopia, Malawi, Nigeria, Zambia with annual growth rates abouttwotimesmorethanthatofruralhouseholds.averageincomesofurbanhouseholds,forthe mostrecentsurveysarealsonearlyabouttwicethatofruralhouseholdsinmostcountries(ghana, Ethiopia,Malawi,Tanzania,ZambiaFifth,theresultssuggestlandlesshouseholds,ontheaverage, have the highest income in most countries (Ghana, Ethiopia, Malawi, Nigeria, Zambia and also experiencedthefastestannualincomegrowthofabout47%comparedto31%forhouseholdsowning lessthan2hectares,24%forthosebetween2and10hectaresand13%forthosewith10hectaresor more.whilehouseholdsowninglessthan2hectaresoflandexperiencedthefastestgrowthratesin incomeamonghouseholdsowningland,thegrowthisstartingfromarelativelylowbaseandtheir currentincomesareabout14%lowerthanthatofhouseholdswithlandholdingsbetween2and10 hectares. A decomposition analysis of household real income per labor time revealed three main groups of countries.thefirstgroupconsistsofcountrieswherethelargestproportionoftheobservedgrowthin realhouseholdincomeperlabortimeoverthepastdecadeislinkedtoincreasesinreturnstolabor fromthenon8farmsectors.ghanaandmalawifallintothisgroup.amongthisgroup,theshareof 2

3 incomegrowthattributedtofarming,whilegenerallyincreasing,islessthanthatfromthenon8farm sector.thesecondgroupofcountries,exemplifiedbytanzania,iswherethereallocationoflabortime fromfarmingintonon8farmactivitiesaccountsforthelargestshareofobservedgrowthinthereturns tolabor.farmingandnon8farmsectorsinthesecountriesalsocontributedtoincreasesinincome.the thirdgroupiscomposedofcountrieswheregrowthinthereturnstolaborfromfarmingisthelargest contributortochangesinhouseholdincomeperlabortime.thesecountries,whichincludenigeria generallyexperiencedsignificantdeclinesinthereturnstolaborinthenon8farmsector.innigeria s case, labor has been reallocated from non8farm activities back into farming, which decreased the growthinhouseholdincomeperlabortime.thisismostlikelyatemporarytrendinfluencedpartially bythecountry sslumpingoilsectorinrecentyears.thesecross8countryvariationsreflectthediverse waysinwhichafricaneconomiesaretransforming,andcallfortailoredcountry8specificstrategiesto achieveeconomicgrowthandpovertyreduction. Ageneralizedfindingacrossalmostallcountriesisthathouseholdsareincreasinglydevotingmoreof theirlabortimetonon8farmsourcesastheireconomiestransform.however,despiteitsdecliningshare in households labor time and incomes, farming remains extremely important for livelihoods and economicgrowthforseveralreasons:first,farmingstillaccountsforthelargestshare(over50%of households labortimeandasignificantsourceofincomeforthemajorityofhouseholdsinallcountries. The most recently available surveys indicate that 44% to 87% of the households in the countries examinedderiveatleastpartoftheirincomefromfarming.overone8thirdoftotalhouseholdincome is comingfromfarming.consideringthelargeshareofpeopledependentonfarming,investments aimedatincreasingthereturntolaborinfarmingwouldthusdirectlyaffectthegreatestnumberof peopleandpromotebroad8basedandinclusivegrowth. The second and more fundamental reason why the farming sector 8 farm productivity growth in particular8remainscrucialpertainstothesector srelevanceinthegenerationofnewjobsintherest oftheeconomy.wedemonstratethatthepaceofgrowthinemploymentandincomesinthenon8farm sectoroverthepastdecadeiscloselylinkedtoproductivitygrowthinfarming.inlinewithhistorical industrializationexperiences,ourtime8serieseconometricanalysisfoundthatcountriesthatachieved thehighestagriculturalproductivitygrowtharethosethatexperiencedthemostrapidexitoflabor fromfarmingintooff8farmsectors,andthehighestgrowthinlaborproductivityinnon8farmsector.as demonstratedintheliterature,farmproductivitygrowth,especiallyifbroadbased,resultsingreater employmentandincomemultipliereffectsthanoff8farmproductivitygrowth.therefore,strategiesthat effectivelyimproveproductivityandprofitabilityoffarmingremainscriticaltoexpandingemployment opportunitiesandimprovinglivelihoods. 3

4 Highlights!!!!!!!! Weobserveincreasesininflation8adjustedaveragehouseholdincomeinSSAoverthelast decadeatthenationallevelandamongmostsub8categoriesofhouseholds In most countries, average household income has grown more rapidly among female8headed householdsthanmale8headedhouseholdsbutstartingfromarelativelylowbase(ghana,ethiopia, Uganda,Zambia,Nigeria.Consequently,averageincomeoffemale8headedhouseholdsstilllag behindthatofmale8headedhouseholdsbyabout27%ontheaverage. Householdslocatedinrelativelyfavorablemarketaccessconditionshaveincomesabouttwice higheronaverageandexperiencedmorerapidgrowthintheirincomesthanthosewith relativelyunfavorableaccesstomarket. Householdsheadedbyayouth(15824yearshavethelowestincomelevelsofanyagecategory andexperiencedthelowestgrowthinincomeoverthepastdecade.incomeoftheyoungadults (25834yearsgrewatacomparableratewiththatofadults(35864years!! Realincomeshavegrownmorerapidlyamongurbanhouseholdsthanruralhouseholdsinmost countrieswithannualgrowthratesabouttwotimesmorethanthatofruralhouseholds.average incomeofurbanhouseholdsarenearlyabouttwicethatofruralhouseholdsinmostcountries!! Households are increasingly devoting more of their labor time to non8farm sources as their economiestransforms.however,farmingstillaccountsforthelargestshareofhouseholds labor timeinmostcountriesandhenceremainsanextremelyimportantsourceoflivelihood. Among the different classes of households, male8 and adult8headed households, households residinginareasthatarerelativelydistantfromurbanareasandthoseowninglargerparcelsof landappearstodevotealargershareoftheirworktimetofarmingactivities. Farm and non8farm activities differed in their relative contribution to the observed growth in household incomes across countries, pointing to important variations in countries economic transformationprocessinsub8saharanafrica.!! Thepaceofthegrowthinemploymentandincomesinthenon8farmsectoroverthepastdecade iscloselylinkedtoproductivitygrowthinfarming. Investmentsinon8farmproductivitygrowthwillbecriticalforbuildingbroad8basedandinclusive economicgrowthwithexpandedemploymentopportunities. 4

5 1.!Introduction After decades of stagnation, Africa s economies have been transforming quite rapidly since The continentwashometosixofthetenfastestgrowingeconomiesinworldinthe2000sandseveralafrican countriesrecordedgdpgrowthratesabove5%duringtheperiod(theeconomist2011.africaneconomies alsodemonstratedamuchstrongerresiliencecomparedtotheworldeconomyaftertheglobalfinancial crisis,recordinggdppercapitagrowthofabout3percentin2010whilethatoftheworlddeclinedby1.4 percent(worldbank2015.eveninthefaceofrecentchallengesintheexternalenvironment(e.g.declines incommoditypricesandriseofusinterestratesthatismarkedlyslowingthiseconomicprogress,africa s prospectsforcontinuedpositivegrowth,atleastinthemediumterm,remainsfavorable. ThetrendofeconomicgrowthrecoveryinSSAisobservedinboththeagricultureandthenon8agriculture sectors. Recent cross8country analysis suggest Africa is making steady progress towards agricultural transformationwithmostafricancountriesenjoyingsustainedagriculturalproductivitygrowthsince2005. Farming svalueaddedisestimatedtohaveincreasedby5.2percentbetween2000and2014comparedto lessthan3percentinthepreviousdecade(worldbank2015,fuglie2015.bothpublicandprivatesectors areincreasinglyinvestinginafrica sagriculturevaluechains.thisisevidencedintheriseofthenumberof medium8andlarge8scalefarms,whichareincreasinglyaccountingforasizeableandrisingportionoftotal farmland in many African countries (Jayne et. al. 2016, and the growth in agribusinesses that are dynamicallyrespondingtopopulationgrowth,urbanizationandchangingfooddietsassociatedwiththe incomegrowth(tschirleyetal.2015.thereisalsoevidenceofarapidbuthighlyvariableshiftsinthelabor forcefromfarmingtooff8farmsectorsoverthepastdecadeinmostafricancountriesaspartoftheon8 goingeconomictransformation(yeboahandjayne,2016;macmillanetal.,2014.significantgrowthisalso experienced in the non8farm economy where sectors such as construction, wholesale, transport and communicationenjoyedvalueaddedgrowthratesmorethantwicethoseofpreviousdecades(ulimwengu etal,2016. WhilerecentevidencepointstoanewdynamisminmuchofAfrica,thereislittleclarityonwhatexactlyis drivingit,theroleoftheagriculturesectorinparticular,howwidelysharedthisgrowthis,andwhatitall meansforagriculturaldevelopmentpoliciesandprogramsfocusedonimprovinglivelihoodsandpoverty reduction.evidencesuggestsafrica srecentimpressiveeconomicperformancehasbeenaccompaniedby ruralpovertyreductiononlyinsomecountries,butnotinothers. 2 Whileitisgenerallywellestablishedthat agriculturalproductivitygrowthdoescontributetothereductionofpovertyinareaswheremostofthe workforceisstillengagedinagriculture,thisrelationshipisconditionedbynumerousfactors,includingthe initial distribution of productive assets that determines the degree to which agricultural productivity growth is inclusive and that, in turn, governs the strength of subsequent income and employment multipliers(johnston&kilby,1975;lipton,2005;mellor,1976;vollrath,2007.therefore,thisobservation 2 Examplesofwhereagriculturalgrowthdoesnotappeartohavehadmucheffectonpovertyreductioninclude Zambia(Jayneetal.,2012;Malawi,BeninandMadagascar(AASR2016 5

6 ofavariablecross8countryrelationshipbetweengrowthandpovertyreductionraisesquestionsaboutthe nature and inclusivity of the growth the various countries are experiencing and their implications for povertyreductionprograms.! Moreover, most recent analyses on Africa s economic transformation process have been based on aggregatedataatthenationallevel(mcmillanandheady2014;mcmillanandrodrik2011;rodrik2014. Whileilluminating,thesestudiesofferlittleinsightsintohowtheobservedtransformationtranslatesinto realincomegrowthandwelfareimprovementsamongdifferentclassesofhouseholds.indeed,thereare fewstudiesprovidingempiricalestimatesoftherateofrealhouseholdincomegrowthindifferentafrican countries across different classes of households and across different historical periods. Even fewer studieshavedecomposedsuchhouseholdincomegrowthintoitsvarioussources.thelatterisimportant becausedecompositioncanidentifythemajorcontributingfactorstothegrowththatisoccurring,as wellassuggestimportantbottlenecksthatneedtobeaddressedifincomegrowthisgoingtoaccelerate. 2.Objectives Asacontributiontotheon8goingpolicyandresearchchallenges,thisstudyseekstoachievethefollowingobjectives: "! Documentrealhouseholdincomegrowthovertimeforvariouscountriesdisaggregatedacross differentclassesofhouseholds "! Examinethesectoralcontributiontohouseholdincomegrowthbydecomposingrealhousehold incomeperhouseholdlabortimeintogrowthcomponentslinkedtofarmingandnon8farmsources andreallocationeffects "! Identify the sources of farming income growth by further decomposing farming income into constituent components including terms of trade effect (changes in relative prices, a productivity effect (yield increases, an area expansion effect (change in cultivated area relative to total area controlledbythehouseholdandlaborproductivityeffect "! Exploretheevolvingroleofagricultureintheon8goingeconomictransformationprocess "! Considertheimplicationsofthesetrendsforagriculturalpolicyandpovertyreductionstrategiesin Africa 3.!Data Theprimaryanalysisreliesondatafromtwowavesofnationallyrepresentative,multi8yearhouseholdlevel surveysfrom seven countriesin SSA Ghana,Ethiopia,Malawi,Nigeria, Tanzania, Uganda andzambia. Table1presentsthedatasources,theyearscoveredandthetotalnumberofhouseholdssurveyedforeach 6

7 country.mostofthesedatasetsarepubliclyavailableattheworldbankpageaspartofthelivingstandard MeasurementSurveywithIntegratedSurveyofAgriculture(LSMS8ISA 3. Table1CountriesandDatasetsIncludedintheAnalysis Country Nameofsurvey Yearcollected ofhh Ghana GhanaLivingStandardSurvey5 2005/06 8,686 GhanaLivingStandardSurvey6 2012/13 16,772 Ethiopia EthiopianRuralSocioeconomicSurvey 2011/ EthiopianSocioeconomicSurveyII 2013/ Malawi IntegratedHouseholdSurveyII 2004/05 11,280 IntegratedHouseholdSurveyIII 2010/11 12,271 Nigeria NigeriaLivingStandardSurvey 2003/04 19,158 GeneralHouseholdSurvey8Panel 2012/13 4,706 Tanzania NationalPanelSurvey 2008/09 3,280 NationalPanelSurvey 2012/13 5,015 Uganda NationalHouseholdSurvey 2005/ NationalPanelSurvey 2011/ Zambia RuralIncomesandLivelihoodsSurvey RuralAgriculturalLivelihoodsSurvey Eachofthedatasourcescontainedamongotherthings,detailedinformationonemploymentandtimeuse for all household members, income from various economic activities, demographic characteristics of householdmembersandhouseholdassets(e.g.,landownedandexpenditures.weusedthisinformation toexplorechangesinhouseholdincomebetweenthetwomostrecentwavesofsurveysdisaggregated acrossdifferentkindsofhouseholdsbylocalityofresidence(ruralvsurbanarea,households landholding, households accesstomarket,genderandageofhouseholdhead.insomecountries,wesupplemented thedatawithinformationfromtheruralincomegeneratingactivities(rigadatabasedevelopedbythe FoodandAgriculture OrganizationoftheUnitedNations 4.TheRIGAdatabase provides informationon 3 pipk: ~thesitepk: ,00.html 4 7

8 householdincomefromvariouseconomicactivitiesbasedonthesamelsmssurveysweemployedinthis analysis.theincomeindicatorsarecomputedusingasystematicapproachacrosscountriesmakingthem comparableacrosscountries.thedatabasealsocontainsvariablesthatallowedustolinkhouseholdsto theoriginaldatasets. Somelimitationsofthedatahoweverneedtobeacknowledged.Insomecountries,certainkeyvariables werepresentinonewavebutabsentinanothermakingcomputationofhouseholdcategoriesimpossible. Forinstance,informationonthenearestdistancefromthecommunityinwhichhouseholdsresidetoa motorableroadwasonlyavailableinnigeriageneralhouseholdsurveyof2012/13andnotinthe2003/04 survey.hence,wewereunabletocomparechangesinrealincomeovertimeacrosshouseholdswith relatively different access to market in Nigeria. Similarly,! available data for some countries (Ethiopia, Zambiaaremissingkeyinformationonhowhouseholdmembersallocatedtheirtimebetweenfarming andnon8farmactivities.consequently,wewereunabletocomputefulltimeequivalentsanddecompose incomeperfteintoconstituentcomponents. 4.!AnalyticalMethod 4.1!Measurements We focus our analysis on the post 2000s period, during which much progress towards economic transformation in SSA has occurred. The first stage of the analysis involves the computation of real householdincomeovertime.householdincomewerecomputedastheaggregatesumofincomereceived from all the income8generating activities household members undertook in the year the survey was conducted.wedistinguishedbetweenincomefromfarmingandnon8farmsources.incomefromfarming sectorconsistsofwagesfromagriculturalactivities(includingfishing,huntingandrevenuesfromcropand livestockproduction.incomesfromallotheractivitiesincludingthosefromeconomicactivitieswithinthe upstreamanddownstreamstagesoftheagrifoodsystemweredesignatedasnon8farmincome.foreach country,computednominalhouseholdincomeinlocalcurrencywereconvertedintoconstant2010prices by deflating them using consumer price indices obtained from the World Bank s World Development Indicators database 5. This was subsequently converted into US dollar to facilitate comparison across countriesovertime. Timeuseinformationwasthenusedtocomputetheshareofeachhouseholds timedevotedtofarming andnon8farmactivitiesasanaggregateofthefull$time$equivalents$(fteofemploymentofhousehold members.thefteapproachcomputestheshareofindividual sworktimeovertheyeardevotedtoarange ofworkactivitiesandhenceprovidesanestimateoftherelativeimportanceofvariousactivitiesandsectors 5 Indicators&populartype=series&ispopular=y 8

9 inpeoples livelihoods.afulltimeequivalentof40hoursaweek,fourweekspermonthfora128month periodwascomputedasonefte. Mostdecompositionstudiesuseemploymentsharesbasedonthestated number of people engaged in the sector (McMillan and Rodrik 2011; Marouani and Mouelhi, However,suchemploymentsharesdonotaccountfortheintensityoftheemploymentandpotentially overestimate households engagement in particular sectors (Yeboah and Jayne, We therefore employ the FTE approach of accounting for households engagement in economic activities in our decompositionofincome. Inanattempttogaugetheextenttowhichobservedeconomictransformationintheregionhasbeen inclusive, we explored changes in income across different classes of households based on various householdcharacteristics.wefirstexploredtheextenttowhichobservedincomegrowthisexperienced amongruralandurbanhouseholds.povertyinssaisgenerallyconsideredendemictoruralareas.over70 of the continent s poor resides in rural areas and countries with relatively large proportion of rural populationtendtobeassociatedwithhigherincidenceofpoverty(beegleetal.2016.incomegrowth amongruralhouseholdscouldthussignifyprogresstowardspovertyreductioninacountry.classification ofhouseholdsbylocalityreliedontheirdesignationinthedatabytheirnationalstatisticalservices 6.Hence, householdslivinginareasdesignatedas urban inthedatawereclassifiedas urban andviceversa. Wealsoexploreddifferencesbetweenmale8headedandfemale8headedhouseholds.Anestimated60%of world spoorpopulationarewomen(mcferson,2010.theprevalenceoftraditionalrestrictionstowomen propertyrightsandgender8baseddiscriminationintheworkforceoftenputwomenatadisadvantageto securingneededresourcestoleapoutofpoverty.consequently,female8headedhouseholdsaregenerally associatedwithhigherincidencesofpovertyrelativetomale8headedhouseholds.arecentanalysisalso suggestsarisingshareoffemale8headedhouseholdsacrossthecontinentlargelydrivenbychangesin marriagebehavior,educationandhealth(milazzoanddewalle,2015.thisraisesconcernsabouthow wellthesehouseholdsaresharinginthegainsfromthesustainedeconomicgrowthwitnessedoverthe pastdecadeandhalf. Inaddition,changesinincomepatternsareexploredfordifferentgroupsofhouseholdsbasedontheir relative access to market. Improved market access facilitates farmers ability to sell their produce and generate additional income, which is subsequently spent on off8farm goods and services, generating importantincome and employmentmultiplier effects on the rest of the economy. Interms ofmarket access,wedistinguishedbetweenhouseholdswith low andthosewith high marketaccessbasedon theproximityoftheircommunitytonearestmotorableroads.householdslivingincommunitiesthatare atleastonekilometerawayfromamotorableroadwereclassifiedaslow8market8accesshousehold. Foragrariansocieties,landisoneofthemostimportantassettogeneratingincome.Evidencesuggests rapidchangesinthefarmlandownershippatternsinssa.whilefarmsunderfivehectaresstillaccountfor 6 Variousnationalstatisticalservicesemploydifferentcriteriaintheirclassificationofareasas urban.forinstance,inghana localitieswithapopulationof5000ormoreareclassifiedasurban.whereasinmalawi,urbanreferstoalltownships,town planningareasandalldistrictcenters. 9

10 90%ofallfarmsintheregion,anincreasingportionofagriculturallandiscontrolledbymedium8scaleand large8scale farms owned by African investor farmers (Jayne et al., Rising population density particularly in land constrained regions of SSA is also increasingly shrinking farm sizes per capita and reducing the amount of land available for agricultural purposes (Headey and Jayne, It is well recognizedthatinequalityinlanddistributionnegativelyaffectsfutureeconomicgrowth(deningerand Squire1998,andevenintheprocessofgrowth,poorhouseholdsappeartobenefitlessthannon8poor householdswhenincomeandassetsaredistributedunequally(gugertyandtimmer1999.hence,we examinetheextenttowhichthechanginglandownershippatternsismediatinghouseholds abilitytoshare inthegainsoftheeconomictransformationbeingexperiencedinregion.wedistinguishbetweenfour groups of households based on household landholdings namely 1. Landless households 2. Households owninglessthan2ha,3.householdsowningbetween2haand10ha,and4.householdsowning10haor moreofland. Lastly,ouranalysisisalsodisaggregatedbytheageofhouseholdheadinlightofreporteddifferentialaccess toresourcesforvariousagegroups(filmerandfox2014.usingthereportedageoftheheadofeach household,threeagecategorieswerecreatednamely1.youth(15824years2.youngadult(25834years 3.Adults(35ormoreyears. 4.2! DecompositionofRealHouseholdIncomeperFTE Tohelpusunderstandthecontributingfactorsandconstraintstoincomegrowth,wedecomposedthe observed changes in real household income into constituent components and attributed to each component or sector a share of the total observed growth. We adopt the Shapley decomposition methodology, a simple addative method that decomposes changes in total real income to particular componentsbyaccountingfortherelativesizeofthecomponentintheinitialyearaswellasthemagnitude ofthechangeinthatcomponentbetweentheinitialandmostrecentsurveyyear. Ashouseholdincomefromeachsectorisafunctionoftheworktimedevotedtothesector,realhousehold income is first normalized by a measure of households labor time allocated to each sector (full time equivalenttogiveusameasureofthereturntohouseholdlabor,realincomeperfte.usingtheshapley methodology,therealincomethathouseholdsreceiveforanhouroftheirlabortime(incomeperftecan be decomposed using several consecutive steps, as illustrated in Figure 1, with each subsequent step offeringadditionalinsightsintothesourcesofincomegrowthoverthelastdecade. The changes in household real income per FTE may occur in two mainways.first, it could arise from changes in the return to labor (income from the economic activities/sectors in which households are employed,perhapsasaresultoftotalfactorproductivitygrowthinthosesectors.itcouldalsoarisefrom structuralchange,whichentailshouseholdsreallocatingtheirlabortimefromlessremunerativesectorsto other sectors that offer relatively higher returns to labor and thereby increasing overall income. Consequently,inthefirststepofthedecomposition,growthinrealincomeperFTEisdecomposedinto 10

11 changes in income growth arising from farming and non8farm sectors and from the reallocation of householdlabortimebetweenthetwosectors.inthesecondstage,farmingincomeperfteisfurther decomposedintochangeslinkedtocropproductionandotheragriculturalactivitiessuchaslivestockand agriculturalwages.next,thechangesincropincomeperfteisdecomposedintocomponentsattributed to growth in income per cropland cultivated, the share of total cropland under cultivation and total croplandperfteinstep3.inthefourthstep,incomepercroplandisdecomposedintogrowthlinked changesinincomefromthevariouscropscultivatedonthelandandthereallocationoflandbetween crops.lastly,wedeterminethecontributionofchangesinpricesofcropsandyieldfromcropstothe growthinincomereceivedfromthevariouscrops. Thisreportfocusesonthefirststageofdecompositionexploringtherelativecontributionofthechanges inincomefromfarmingandnon8farmsectorandsectoralreallocationoflabortimebetweensectorsto incomegrowthperfte. Real HH(income(per(FTE Agricultural income(per(fte( NonBagricultural(income(per(FTE Reallocation(of(FTE(between( sectors Other(agricultural(income(( (livestock!and!agricultural!wage Crop(income(per(FTE (returns!to!agricultural!labor!from! crop!production Share(of(cropland(under(crop( production( (Cropland!intensity Total(cropland(per(FTE( (Area!expansion effect!! Income(per(cropland(( (land!productivity!effect income(from(various(crops(per( cropland(cultivated Reallocation(effect(of(cropland( between(crops Terms(of(trade( (Changes!in!relative!prices Yield(effect (output!per!area!planted Figure1StepwiseapproachtodecomposinghouseholdincomeperFTE 11

12 5.!ResultsandDiscussions 5.1!$Trends$in$real$income$growth$$ $ Table2presentsestimatesofaverageinflationadjustedincomeamongdifferentclassesofhouseholds overtime.notethatthereportedinflationadjustedincomeisnetofallobservablecostassociatedwith generatingtheincome.whilethedifferencesinsurveydesign,timeperiodsandsampleacrosssurveys warrantcautionagainststrictcomparisonofabsolutevaluesofincomeandovergeneralizationofincome patterns,afewobservationsareapparent.first,theresultsindicateageneralpositivegrowthinaverage inflationadjustedincomeamonghouseholdsinthecountriesstudied.withtheexceptionofuganda,all thesixremainingstudycountrieshaveexperiencedsignificantgrowthinhouseholdincomeoverthelast decade. This is consistent with the broad literature pointing to Africa s progress towards an economic recovery(ulimwenguetal.2016;mcmillan&harttgen,2014.therearehoweversubstantialvariations acrosscountriesintherateatwhichgrowthinrealincomeisoccurring.foroursevenstudycountries,the growthinaveragerealhouseholdincomehasbeenmostrapidinghana,whereaveragenethousehold income grew about 137% annually between 2006 and This is followed by Nigeria and Ethiopia, recordingannualgrowthratesabout45%and25%respectively.averageinflationadjustedhousehold incomegrowthwascomparativelylessrapidintanzania,zambia,andmalawibutgenerallyrobustwith annualgrowthratesofabout10%,11%and6%respectively. Second,thegrowthinaveragehouseholdincomeattheaggregatelevelsisreflectedamongbothruraland urbanhouseholds.however,incomegrowthappearstobemorerapidamongurbanhouseholdsrelative toruralhouseholdsparticularlyinghana,ethiopia 7 andmalawiwithaverageincomegrowthratesofabout 43%relativeto22%forruralhouseholds.Averagerealincomeofurbanhouseholdsalsoremainshigher andistypicallymorethantwicethatofruralhouseholdsinallthecountriesexamined. Third,theobservedgrowthinincomeisgenerallyexperiencedamongfemale8headedandmale8headed households.inmostcountries,averageincomehasgrownmorerapidlyamongfemale8headedhouseholds than male8headed households (Ghana, Ethiopia, Nigeria and Uganda. On the average, female8headed householdsexperiencedanannualgrowthofabout105%increaseintheirhouseholdincomecomparedto about 33% of male8headed households. In a recent cross8country analysis using Demographic Health Surveysfor24countriesinSSA,MilazzoandvandeWalle(2015alsoobserveddecliningincidencesof povertyamongbothmaleandfemale8headedhouseholdsbutindicatedafasterrateofdeclineamongthe later.inexaminingthecontributionofvariousdemographicgroupstothechangesinpovertyreduction, theauthorsfoundthecontributionoffemale8headedhouseholdstochangesinpovertyreductiontobe nearlyasmuchasthatofmale8headedhouseholdsalthoughfemale8headedhouseholdsconstituteda 7 ForEthiopia,therapidgrowthinincomeamongurbanhouseholdsmayhavebeeninfluencedbythedifferencein samplingusedforthetwosurveys.the2011/12focusedprimarilyonruralhouseholdsandsampledafew householdsfromsmalltownswhowereclassifiedasurban.the2013/14howeverincludeshouseholdsfrombigger citieswhoontheaveragehavehigherincomes. 12

13 ! Table!2!Changes!in!Mean!Real!Household!income!over!Time!across!Different!Classes!of!Households!! Ghana Ethiopia Malawi Nigeria1 Tanzania1 Uganda1 Zambia Annual1%1 Annual1%1 Annual1%1 Annual1%1 Annual1%1 Annual1%1 2005/ /13 change 2011/ /14 change 2004/ /11 change 2003/ /13 change 2008/ /13 change 2005/ /12 change Annual1%1 change AllHouseholds 11111,048 11, , , , , Locality Urban ,276 13, , , , , , , , Rural , , , , , Gender Male5head ,133 11, , , , , Female1head , , , , Landsize Landless 11111,192 12, , , , , , , Less1than121hectare , , , , , hectare 11111, , , , , , , , Over1101hectare 11111, , , , , , , , , , Marketaccessconditions High , , , , , Low , , , , Age Youth , , , , Young1adult , , , , , Adult 11111,110 11, , , , , ! Notes:!Average!household!income!are!in!constant!2010!prices!in!US!dollars! 13

14 smaller'share'of'the'population.'while'welcoming'this'progress,'it'is'worth'noting'that'income'growth' among'female6headed'households'is'often'starting'from'a'low'base'of'income'relative'to'that'of'male6 headed' households' (32%' lower,' on' average.' Consequently,' although' female6headed' households' are' catching' up,' the' average' income' of' female6headed' households' still' lags' behind' that' of' male6headed' households'in'the'most'recent'surveys'in'by'about'27%,'on'the'average.' ' Fourth,'the'various'household'landholding'groupings'have'also'experienced'some'growth'in'their'average' income.'in'tanzania,'growth'in'income'has'been'most'rapid'among'households'owning'more'than'10'ha'of' land.'however,'for'the'remaining'countries'with'available'data'(ghana,'ethiopia,'malawi,'nigeria,'zambia,' the'rate'of'growth'in'average'income'has'been'most'rapid'among'landless'households'with'growth'rates' of'about'47%'on'the'average.'this'compares'to'31%'for'households'owning'less'than'2'hectares,'24%'for' those' between' 2' and' 10' hectares' and' 13%' for' those' with' 10' hectares' or' more.' Interestingly,' average' household'income,'computed'from'the'most'recent'surveys,'is'also'highest'among'landless'households'in' these'countries.'although'this'is'not'the'case'for'uganda,'this'finding'may'suggest'that'landholding'size' may'not'be'a'good'indicator'of'a'household'wealth.'as'the'economies'of'these'countries'transforms,'more' opportunities'are'being'created'in'off6farm'sectors'like'finance'and'telecommunication,'which'are'relatively' less'dependent'on'land'to'generate'outputs.'these'off6farm'sectors'often'offer'high'paying'jobs'and'provide' avenues'for'skilled'individuals'from'landless'households'to'earn'a'good'income.''while'households'owning' less'than'2'ha'of'land'are'also'experiencing'rapid'growth'over'time,'their'growth'is'starting'from'an'initial' relatively'low'base'and'as'such'remains'the'lowest'income'group'in'most'countries'(ethiopia,'uganda,' Malawi,'Tanzania,'Zambia.''Indeed,'income'for'households'owning'less'than'2'hectares'of'land'is'on'the' average'about'14%'lower'than'that'of'those'with'landholdings'between'2'and'10'hectares.'''''' ' Fifth,'for'those'countries'for'which'we'have'comparable'survey'pairs, access'to'market'appears'to'play'a' key'role'in'the'rate'at'which'average'income'is'growing.'generally,'households'with'more'favorable'access' to'market'were'associated'with'higher'incomes'and'experienced'about'265'times'more'growth'in'their' income'than'those'with'relatively'unfavorable'market'access'conditions.'''in'fact,'in'ghana,'ethiopia'and' Malawi,'average'income'among'households'with'more'favorable'market'access'was'about'twice'that'of' those'with'relatively'poor'market'access'(table'2.'' ' Sixth,'all'households'regardless'of'the'age'of'the'household'head'appears'to'share'in'the'economic'recovery' as'evidenced'in'the'general'positive'growth'among'the'various'household'categories'based'on'age'of'the' household'head' (Table' 2.' However,'the'extent'to'which'the' growth'is'shared'differ'across'household' categories.'indeed,'the'largest'average'income'is'observed'among'households'headed'by'adults'(35'years' or'more'and'the'growth'rate'of'their'income'is'generally'comparable'with'that'of'the'households'whose' head'is'a'young'adult'(25634'years.'youth6headed'households'also'experienced'increases'in'income'of'' about' 23%' relative' to' 33%' and' 31%' for' households' headed' by' young' adults' (24635' years' or' adults.'' Households'headed'by'a'youth'(15624'years'are'associated'with'the'least'average'real'income'in'the'most' recent'year'and'the'lowest'growth'in'income'over'time.''this'is'not'surprising'considering'the'relatively' challenging'labor'market'conditions'and'the'difficulties'the'youth'faces'to'secure'a'job.'in'most'african' countries,' the' year' age' bracket' represents' a' period' during' which' formal' secondary' and' tertiary' education'or'informal'vocational'trainings'are'received.''hence,'individuals'in'this'age'category'who'are' 14

15 active'in'the'labor'force'are'typically'out6of6school'youth'who'often'lack'the'skills,'experience'and'trusted' networks'to'secure'gainful'employment.'their'employment'prospects'are'thus'restricted'to'low6earning' activities,'which'eventually'consign'them'to'the'bottom'of'the'income'ladder.'''''' ' An'examination'of'the'sectoral'shares'in'household'income'reveals'a'growing'importance'of'non6farm' income'to'households'as'the'economies'transforms.'in'most'of'countries,'we'observe'declines'in'the'share' of'total'household'income'from'the'farming'sector'with'a'corresponding'rise'in'non6farm'income'share' total' real' household' income.' In' fact,' income' shares' from' farming' declined' from' about' 61%' to' 48%' in' Malawi'over'the'six6year'period'while'Tanzania'experienced'about'a'ten6percentage'point'decline'over'a' four6year'period.'''nonetheless,'farming'still'accounts'for'a'significant'share'of'total'household'income.' Estimates'from'the'most'recently'available'data'suggest'at'least'a'third'of'real'household'income'at'the' national'level'is'derived'from'farming.''farming s'income'share'is'particularly'higher'among'households' living'in'rural'areas,'those'owning'land'regardless'of'landholding'size,'and'those'living'in'communities'with' limited'access'to'market.'for'these'classes'of'households,'over'50%'of'their'average'income'is'still'coming' from'farming.'''the'farming'sector'also'remains'a'significant'source'of'livelihood'for'most'households.''' About'44%'of'households'in'Ghana'to'as'much'as'87%'of'households'in'Malawi'are'dependent'on'farming' for'some'share'of'their'household'income'(table'a2.'''' ' 5.2!Household,labor,time,allocation,between,farming,and,non8farm,sectors, Structural'transformation,'involving'the'reallocation'of'economic'activity'away'from'less'productive'sectors' of'the'economy'to'more'productive'ones,'has'long'been'considered'a'fundamental'driver'of'economic' development' (Timmer' 2009;' Barrett,' Carter,' and' Timmer' 2010;' Duarte' and' Restuccia' 2010;' McMillan,' Rodrik,'and'Verduzco6Gallo'2014.'Both'in'theory'and'actual'experiences'of'currently'developed'countries,' movement'of'labor'from'low6productivity'semi6subsistence'farming'to'more'productive'manufacturing'and' service'sectors'has'generally'been'associated'with'overall'increases'in'productivity,'living'standards'and' poverty'reduction.'for'countries'in'the'early'stages'of'development,'household'members'typically'devote' a' disproportionate' share' of' their' abundant' labor' to' traditional' agriculture.' Productivity' growth' in' agriculture' accumulates' additional' purchasing' power' among' millions' of' rural' families' that' generates' powerful'multiplier'effects'on'the'rest'of'the'economy,'expanding'job'opportunities'in'off6farm'sectors'and' thereby'releasing'labor'to'non6farm'sectors.'consequently,'a'reduction'in'the'share'of'the'work'force'and' total'work'time'devoted'to'farming'has'generally'been'associated'with'success'of'the'farming'sector'in' setting'in'motion'the'initial'stages'of'economic'transformation'through'expenditure'multipliers.'hence,'in' effort'to'understand'the'patterns'of'income'growth'among'households'in'ssa,'we'examine'the'extent'to' which' households ' work' time' devoted' to' the' various' sectors' is' shifting' over' time' as' the' economy' transforms.'' ' Table'3'present' provides'information'on'the'proportion'of'household'adult s'working'time'devoted'to' farming.''we'compute' full'time'equivalents '(FTE'expressed'as'a'percentage'of'an'adult s'total'work'time' over'the'entire'year.''note'that'farming s'share'of'total'fte'is'significantly'lower'than'farming s'employment' share'based'on'the'number'of'people'engaged'in'farming.'recent'estimates'suggest'that'farming s'share' 15

16 Table&3&Changes&in&share&of&household&work&time&allocated&to&each&sector&over&time& & Proportionoftotalworktimeallocatedtofarmingsector(% Ghana Malawi Nigeria Tanzania Uganda AllHouseholds Locality Urban Rural Gender Male7head Female1head Landsize Landless Less1than121hectare hectare Over1101hectare Marketaccessconditions High Low Age Youth Young1adult Adult & 16

17 oftotalworktime(fteisoftenabout10percentagepointslowerthanfarming semploymentshares.this isbecausemostpeopledonotworkasfarmersyearroundinrainfedagriculturalsystems.infact,farming isestimatedtotakeupabout500c1000hoursperyearwhereasmostjobsintheoffcfarmsectorsentails morethan2000hoursperyear(mccullough2015.hence,inanygivenyear,theshareoffarmingjobs declines when weighted by the amount of time allocated to it during the year, which is what the FTE approachdoes. TheresultsfromTable3showsthathouseholdsinmostcountriesareincreasinglydevotingmoreoftheir worktimetononcfarmactivities.farming sshareoftotalworktimehassignificantlydeclinedbyabout9 percentagepointsinghanaandtanzaniaoverasevencandfourcyearperiodrespectively.similardeclines arealsoobservedformalawi whichwitnessedfarming sshareoflabortimedeclinefrom72%to68% between2005and2011whileugandaexperiencedaboutatwocpercentagepointdeclineoverasixcyear period.thesepatternsareconsistentwiththefindingsofseveralotherstudiesthatprovideevidenceof laborexitfromfarmingtononcfarmsectorsoftheeconomyinafrica(mcmillan&harttgen,2014;devries, Timmer,&deVries,2015;Yeboah&Jayne,2016. Inananalysisinvolving11SubCSaharanAfricancountries, devriesetal.(2014reporteddeclinesintheshareofemploymentinfarmingfrom61.6percentin1990 to49.8percentin2010.mostrecently,yeboahandjayne(2016alsoobserveddeclinesintheshareof farmingintotalemployment,althoughtheabsolutenumberofpeopleengagedinfarmingisstillincreasing in most SSA countries due to population growth. The authors attributed the declining farming s employmentsharetothemorerapidpercentagegrowthintheoffcfarmsectorsoftheeconomy,including the upstream and downstream segments of the agricfood system. Anotableexceptiontothistrendis Nigeriawherehouseholdsappearstobeincreasingtheshareoftheirworktimedevotedtofarming.Other studies using different dataset have also observed similar employment patterns in Nigeria, which potentiallyreflectthenegativeeffectofnaturalresourceboomoneconomictransformation(mcmillanand Harttgen Sackeyetal.(2012highlightstheincreasedpublicinvestmentinagricultureparticularly in Nigeria s rural areas in the 2000s as part of efforts to stem ruralcurban migration. The Federal GovernmentofNigeriathroughitsAgriculturalTransformationAgendasoughttocreate3.5millionjobsin agricultureforyouthandwomenthroughdirectinvestmentinfarmingandagribusiness(adesugbaand Mavrotas It is also possible that these renewed public investments in the agricultural sector followingdecadesofneglectunderanoilsectorcdriveneconomymighthavecontributedtotheobserved reallocationoflabortimetowardsfarminginnigeria. Although a growing share of the household s work time is being devoted to noncfarm activities, it is essentialtonotethatfarmingstillaccountsforthelargestshareofhouseholds labortimeinmostcountries andhenceanextremelyimportantsourceoflivelihood.asignificantlyhigherproportion(over50%ofall households worktimeintanzania,malawiandugandaisstilldevotedtofarmingactivities.asexpected, ruralhouseholdsparticularlydevoteadisproportionateshareoftheirlaborhourstofarming.amongthe 8 Asteadygrowthintheoilsectorin1960sandsubsequentoil$boominthe1970sinNigeriaservedtodrawlabor awayfromagricultureintoprimarilytheservice relatedsectorsoftheeconomy.however,withdeclinesinoilprices andassociateddebtcrisisinthe1980s,thenigerianeconomywasunabletosupporttheseoffcfarmeconomic activities,whosegrowthwaslargelydependentontheoilrevenues,resultinginlaborreallocationtowards agriculturesince1980s. 17

18 differentclassesofhouseholds,ruralhouseholds,malecandadultcheadedhouseholds,householdswith less favorable access to market and those owning relatively larger parcels of land appear to devote a disproportionateshareoftheirworktimetofarmingactivities.forinstance,about53%oftheworktime ofruralhouseholdsinugandaand80%inmalawiisaccountedforbyfarming(table3. 5.3!$Sectoral$contribution$to$real$household$income$over$time$$ Realhouseholdincomeperlabortimewasdecomposedintoconstituentcomponentstoenableusestablish thecontributionofthevarioussectorsandreallocationoflaboracrosssectorstotheobservedincome growthoverthepastdecade.theresultsforeachofthestudycountriesforwhichavailabledatapermitted decompositionanalysis, arepresentedintables4c8.foreachcountry,wepresentinformationonthe annualpercentagechangeintotalincomeperfulltimeemploymentandtherelativecontributionfromthe various sectors and reallocation of labor time between sectors to the observed income growth. We highlight a few salient observations here. First, households are generally experiencing growth in the averageearningstheyreceivefromtheactivitiestowhichtheydevotetheirlabortime.withtheexception ofuganda,householdsinalltheremainingcountriesexperiencedapositivegrowthinincomeperftewith annualpercentagegrowthrangingfromabout5%intanzaniatoashighas125%inghanaduringthe period. TherearehowevercrossCcountrydifferencesregardingtherelativesectoralcontributiontothisgrowthin thereturnstohouseholdlabortimesignifyingthediversewaysinwhichvariousafricaneconomiesare transforming. At the national level, three main groups of countries based on the component with the largestcontributioncanbediscerned.thefirstgroupconsistsofcountrieswherethelargestproportionof observedgrowthinhouseholdincomeislinkedtoincreasesinincomegrowthfromthenoncfarmsectors. GhanaandMalawifallintothisgroup.About92%ofthetotalgrowthinhouseholdincomeperFTEinGhana and56%inmalawiisattributedtochangesinthereturnstohouseholdlabortimeinthenoncfarmsector. Inotherwords,changesinincomethathouseholdsreceiveforeveryfullCtimeemploymentinthenonCfarm sectoralonewouldhaveresultedinanannualincreaseinhouseholdincomeperfteby115%and9%in GhanaandMalawirespectively,iftheincomefromfarming andtherelativesharesofhouseholdtime allocatedtovarioussectorsremainedconstantovertheperiod.thecontributionofthefarmingsectorto overallgrowthinhouseholdincomeperfteduringtheperiodisnearlynegligibleinghanabutquiterobust inmalawiwhereitaccountedforabout39%ofthegrowthintotalincomeperfte(table4and5.with thereturnstolaborinthefarmingsectorgrowingslowlyinghana,thereallocationofhouseholdlabor awayfromfarmingactivitiescontributedpositivelytoincomegrowthandaccountedforabout8%ofthe totalchangeinhouseholdincomeperlabortime(table4.similarly,laborexitfromfarmingaccountedfor about5%ofthetotalchangeinincomeperfteinmalawi(table5. Inthesecondgroupofcountries,thegreatestshareofthechangeintotalincomeperhouseholdlabortime islinkedtothesectoralreallocationoflabortime.anexampleistanzania,wherethereallocationoflabor timefromfarmingtononcfarmsectorcontributedabout47%ofthetotalgrowthinincomeperfte.the noncfarm sector in Tanzania therefore appears to have generated employment and good earning opportunitiestoabsorbtheexcesslaborfromfarming.indeed,returnstolaborinthenoncfarmincreased duringtheperiod,enabingthesectortoaccountforabout43%ofthetotalincomeperfte.thegrowthin 18

19 thereturnstolaborinfarmingwasalsoimportant,contributingabout10%ofhouseholdincomegrowth (Table7.AnotherexampleisUganda,whereoverallgrowthinincomeperFTEdeclinedovertheperiod largelyduetoworseningreturnstolabor,whichtranslatedintonegativecontributionstooverallchangein incomeperftefromthenoncfarm(c77%andfarming(c22%sectors(table8. Table4DecompositionofchangeinrealhouseholdincomeperFTEinGhana,2006C2013 Typeofhousehold Annual%change inmeanhh incomeperfte Shareoftotalchangelinkedto Withinsectoralgrowth Farming NonCfarm Reallocationeffect Allhouseholds Locality Urban Rural 97.2 C Gender MaleCheadedHH C FemaleCheadedHH Landholdingsize Landless C Lessthan2ha C1.4 2C10ha haormore Marketaccess High Low 50.9 C C3.9 Agegroupings YouthChead(15C Youngadult(25C C Adults(35ormore