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WORKING PAPER
The Environmental Dimensions of Emigrationfrom Rural Mexico
Lori M. HunterSheena MurrayFernando Riosmena
March 2011
Population Program POP2011-03_____________________________________________________________________________
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TheEnvironmentalDimensionsofEmigrationfromRuralMexico
LoriM.HunterDepartmentofSociology
CUPopulationCenter,InstituteofBehavioralScience,UniversityofColoradoatBoulder
SheenaMurrayDepartmentofEconomics
CUPopulationCenter,InstituteofBehavioralScience,UniversityofColoradoatBoulder
FernandoRiosmenaDepartmentofGeography
CUPopulationCenter,InstituteofBehavioralScience,UniversityofColoradoatBoulder
Donotcite.Ifinterestedinadditionalinformationonthestatusofthisresearch,
Preliminarymanuscriptpreparedforpresentationatthe2011meetingofthePopulation AssociationofAmerica,WashingtonDC.
Acknowledgements: PreliminarysupportforthisprojectprovidedbytheCenterfor
EnvironmentandPopulation(CEP)throughtheirSummerFellowshipProgram. Theworkhas
alsobenefitedfromtheNICHDfundedUniversityofColoradoPopulationCenter(grantR21
HD51146)forresearch,administrative,andcomputingsupport.Thecontentissolelythe
responsibilityoftheauthorsanddoesnotnecessarilyrepresenttheofficialviewsofCEP,NIH,
orNICHD.
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TheEnvironmentalDimensionsofEmigrationfromRuralMexicoLoriM.Hunter,SheenaMurrayandFernandoRiosmena
UniversityofColoradoatBoulder
Abstract: Inmanydevelopingcountries,naturalresourcedependencyisadaytodayrealityformanyruralhouseholds.Assuch,changesinweatherandclimatepatternsholdtremendous
potentialtoimpactlivelihoods.Whenlivelihoodoptionsareconstrainedduetoshiftsin
environmentalconditions,migrationbecomesasignificant,adaptivelivelihoodstrategy
reducinghouseholdvulnerability.Inthisproject,weofferapreliminaryanswertothequestion:
IsemigrationfromruralMexicototheU.S.associatedwithrecentpatternsofprecipitation,net
ofothersocioeconomicfactorsshapingmigrationpatterns?UsingdatafromtheMexican
MigrationProject(MMP),wemodelU.S.emigrationfromruralMexicancommunitiesasrelated
tocommunity,householdandenvironmentalfactors.Wefindthathouseholdssubjectedto
droughtconditionsarefarmorelikelytosendamigrantascomparedtothosesubjectedtowet
conditions.Theresultshaveimportantimplicationsforpolicyandprogrammaticresponseto
currentmigrationpressuresemphasizingdiversificationofruralMexicanlivelihoodsintheface
ofcontemporaryclimatechange.
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TheEnvironmentalDimensionsofEmigrationfromRuralMexicoLoriM.Hunter,SheenaMurrayandFernandoRiosmena
UniversityofColoradoatBoulder
Public,policyandacademicrealmshavebeenpayingincreasingattentiontothepotential
forenvironmentalchangetoalterpatternsofhumanmigration.Evenso,littlepeerreviewed
scholarshipexistsontheconnection.Thisprojectcontributesempiricallywithfocuson
internationalmigrationfromruralMexico,bothasettingandsocialprocessofconsiderable
policyrelevance.
AfocusonthepotentialforenvironmentalpushfactorstoshapeMexicanmigrationis
especiallytimelynotonlybecauseofcontemporaryclimatechangebutalsobecauseof
heightenedattentiontotrendsinU.S.immigration.TheUnitedStateshad39millionforeign
bornresidentsin2009thehighestproportionofforeignborninanynation(Martinand
Midgley2010).Mexicocontinuestobealeadingsourceofbothauthorizedandunauthorized
immigrationtotheUnitedStates(Hoefer,RytinaandCampbell2007);About30percentofU.S.
legalimmigrants,andhalfoftheunauthorizedforeigners,arefromMexico(MartinandMidgley
2006).
Althoughsubstantialresearchhasexaminedthesocial,economic,andpolicydriversof
MexicanmigrationtotheU.S.(e.g.Cohen2004;Durandetal.1996;Kanaiaupuni2000;
HernandezLeon2008;LindstromandLauster2001;Masseyetal.1987;Massey,Goldring,and
Durand1994;MasseyandEspinosa1997;Masseyetal.2002;MasseyandRiosmena2010;
Riosmena2009;Rosas2008),farlessisknownabouttheenvironmentalpushfactorsrelated
toMexicoU.S.emigration(Nevins2007);Toourknowledge,theonlysuchpublishedwork
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revealsintriguingstatelevelassociationsassociationsbetweenMexicanoutmigrationand
declinesincropyields(Fengetal.2010).Webelievetheprojectpresentedhere,atthe
householdlevel,istheonlyefforttodatemodelinginternationaloutmigrationfromrural
Mexicoasrelatedtoenvironmentalfactorsatgeographicscalesmoreprecisethanthestate.
Background
Thisprojecttakesplaceatthenexusoftwoliteratures:naturalresourcesandrurallivelihoods,
combinedwithmigrationasanadaptivelivelihoodstrategy,particularlyamongvulnerable
households. Theseliteraturesarebrieflyreviewedbelow,withspecificreferencetothe
Mexicansettingasavailablewithinexistingwork.
Rurallivelihoods,withfocusonnaturalresources:WeusetheconceptualframeworkofRuralLivelihoods(IFAD2010)whichhasbeenusedinawidevarietyofanalyticalendeavors
includingexplorationofhealthbehaviors(Rugalema2000),foodsecurity(Bank2005)and
householddiversificationstrategies(Yaro2006).Theframeworkclassifiesvariouscapital
assetsthatshapelivelihoodoptions,includinghumancapital(e.g.,labor),financialcapital
(e.g.,savings),physicalcapital(e.g.,automobiles),socialcapital(e.g.,networks),andnatural
capital(e.g.,wildfoods).Therelativeavailabilityofvariousassetsisshapedbyindividualand
householdactionsaswellasbroadersocioeconomicpoliticalstructuresandprocesses
(Bebbington1999).Inturn,availabilityshapeslivelihoodstrategieswhichmayincludehuman
capitaluse(e.g.,labormigration,seeCollinsonetal.2006a,2006bornaturalcapitaluse(e.g.,
makingresourcebasedcraftsformarket(Pereira,ShackletonandShackleton2006)).Ingeneral,
thelivelihoodsapproachhasprovenavaluabletoolinhighlightingthediversityanddynamism
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ofthechoicesandactivitiesinwhichruralhouseholdsengagetomeethouseholdneeds
(Wintersetal.2002).
Focusingonnaturalcapital,inruralregionsoftheworldslessdevelopednations,proximate
naturalresources(e.g.,land,water,wildfoods)areoftenessentialinmeetingbasicliving
requirements(e.g.Nunan2010).Assuch,environmentalchangehasimmediateanddirect
impactsonthehealthandwellbeingofmillionsofhouseholds(KoziellandSaunders2001).
InruralMexicospecifically,naturalcapitalintheformoflandandwaterareespecially
centraltolivelihoods.Withafocusonfourcarefullyselectedcasestudycommunities,Wiggins
etal.(2002)detailthediversityofruralMexicanslivelihoods.Intheirstudy,households
typicallyhadfivesourcesofincomeandthegreatmajorityofhouseholdshadaccesstoplotsof
land. Fully78%farmed,predominantlymaizeandbeans.Yet,althoughfarmingwasthemost
frequentsourceofincome,itcontributedinmostcasesonlyarelativelysmallfractionof
householdincomes(onaverage,14percent).Burnstein(2007)alsonotesthatcorn,in
particular,continuestobe amainstayofMexicanrurallivelihoods,anditsproductionsustains
some15millionofMexicos103millionresidents.Overall,althoughfarmingisnotthemain
activityforsmallholdersinruralMexico,itisacentralcomponentofthediversificationof
livelihoods(deJanvryandSadoulet2001;Wigginsetal.2002).Inthisway,livelihoodsare
vulnerabletoclimaticvariabilitythatmayimpactagriculturalproductivity(Eakin2005).
KeytoexaminationofnaturalcapitalwithinMexicoisunderstandingofejidos rural
communitieswhichcollectivelypossessrightstolandandwhoseresidentmembers
(ejidatarios)areentitledtoworkaplotoftheirown(Wigginsetal.2002).Ejidoswerecreated
throughlandtransfersstartinginthe1930s.Thoughmarketliberalizationreformsduringthe
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1990sallowedejidatariostoattainprivatetitlesofandthushavethecapacitytoselltheirlands,
veryfewhavesold(Barnes2009). Ofparticularrelevancetothepresentproject,itisestimated
thattheejidosectorcontainsapproximately60%oftheruralpopulation(deJanvryand
Sadoulet2001).Recentworksuggeststhatcontemporaryeffortstoprovideejidohouseholds
withacertificateoflandownershipareassociatedwithanincreaseinemigrationtotheU.S.,
therebyinferringthatmoresecureaccesstothisformofnaturalcapitalprovidesafoundation
fromwhichtoengageintherelativelyexpensivelivelihooddiversificationstrategyof
internationalmigration(Valsecchi2010). Assuch,ourmodelingstrategyincludesland
ownershipvariablesbothathouseholdandcommunitylevels.
Winters,DavisandCorral(2002)alsooutlinelivelihoodframeworksinruralMexico,
characterizingthediversityoflivelihoodactivitiesalthoughthecentralityofagricultureand
naturalcapitalremains.InWintersetal.s(2002)examinationofanationallyrepresentative
sampleofMexicanejidohouseholds,fully93.7%participatedincropproductionand
agriculturalactivitiesasawhole(crops,livestockandagriculturalemployment)madeupover
half(55%)oftotalruralhouseholdincome.Ofcourse,therearedistinctlivelihoodstrategies
dependingonwhetherruralMexicanhouseholdshaveaccesstoirrigatedorrainfedland.
Yetotherforcesbeyondthehouseholdclearlyalsoshapelivelihoodstrategies. Wintersand
colleagues(2002:141)aptlynotethatlivelihooddecisionmakingisconditionedonthecontext
inwhichthehouseholdoperatesinfluencedthroughnaturalforces,markets,stateactivity
andsocietalinstitutions.Inthisway,environmentalchangeactsinconcertwithpoliticaland
economicforcestoshapelivelihoodstrategiesand,forMexicossmallholderfarmers,recent
workhasdocumentedthenegativeimplicationsofthenationsglobaleconomicintegration
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(Eakin2005).Afterdecadesofpublicinvestmentandsupportiveagriculturalpoliciesspurring
agriculturalgrowth,neoliberalizationoftheagriculturalsectorandfoodpolicyduringthe
Salinasadministration,19881994,broughtdramaticchangestoruralMexico.Today,Mexican
povertyhasfurtherconcentratedinthecountryside,particularlyintheSouth(e.g.Hanson
2003;Nevins2007;Polaski2004;Zepedaetal.2009).Informedbyunderstandingofrecent
politicaleconomicconditionsinMexico,tocontrolforbroader,changingmacroconditionsnot
capturedbyourcommunitySESmeasures,weincludebothstateandyearfixedeffectsinthe
modelspresentedbelow.
Rurallivelihoodvulnerabilityandadaptation,withfocusonmigration: ApplicationoftheRuralLivelihoodsframeworktoMexicanlivelihoodsandclimateisfurtherinformedbysocial
scienceresearchonvulnerabilityandadaptation.Vulnerabilityisdefinedasthedegreeto
whichasystem,subsystem,orasystemcomponentislikelytoexperienceharmdueto
exposuretoahazardeitherasaperturbationorstress/stressor(Turneretal.2003).As
explainedbyLeichenkoandOBrien(2002:2),withinthecontextofclimatestudies,
conceptualizationofvulnerabilityhasmostlyfocusedonmarginality,susceptibility,adaptability,
fragility,andrisk.Usingthesefactors,vulnerabilitymappinghelpsidentifyregionsparticularly
vulnerabletoclimateshifts(FussellandKlein2006;Hahn,RiedererandFoster2009;Ionescuet
al.2009;Polsky,NeffandYarnaletal.2007).Highlevelsofresourcedependencecontributeto
climatevulnerability(ThomasandTwyman2006)andregionsinwhichresidentsdependon
rainfedagriculture(suchasmostofourstudysites)areespeciallyvulnerable(ReidandVogel
2006).
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Livelihooddiversificationistheprocessbywhichhouseholdsreducevulnerabilityasthey
seektoensurewellbeing(Ellis2000).Suchadaptationmayoccurinresponsetoclimate
vulnerability,withadaptationdefinedasadjustmentstoasysteminresponsetoactualor
expectedclimatestimuli,theireffects,ortheirimpacts(LeichenkoandOBrien2006).In
consideringvulnerabilityandadaptivepotential,Adger,PaavolaandHuq(2006:2)comment
theworldschangingclimateandourresponsestoitthreatentoexacerbatepreciselythose
trendsandpressuresthatcausepresentinsecuritiesandthatarelikelytoleadtoincreased
insecurityinthefuture.Theold,young,poor,andthosedependentonclimatesensitive
resources,includingalloftheworldsfarmersandfishers,areatgreatestrisk.
Migrationisaparticularadaptationstrategyusedbyhouseholdsinthefaceof
environmentalstrain(Bilsborrow1992;McLemanandHunter2010;McLemanandSmit2005;
NjockandWestlund2010;Nunan2010).Muchoftheexistingempiricalresearchonmigration,
livelihoodsandshiftsinnaturalcapitalfocusesonlandavailabilityand/orlandusedecisions,
andissituatedinAsia,andCentral/SouthAmerica(e.g.,Ayuwat1993;Snegstrom2009).Results
suggestwhenfacedwithalackoflivelihoodoptions,oftenduetocumulativeprocessesof
environmentaldegradation(Zweifler,GoldandThomas1994),householdsmaystrategically
diversifywithsomehouseholdmembersmigratingtoseekopportunityelsewhere(Bilsborrow
2002;Snegstrom2009;McLemanandHunter2010).Inthisway,changesinproximatenatural
capitalshapehouseholddecisionsaboutuseofhumancapital.
Fouradditionalstudiesdeservemention.Arecentone,undertakeninNepal,provides
evidencethatenvironmentalfactorsplayaroleinmigration,particularlyshortdistancemoves.
(Massey,AxinnandGhimire2010).Another,undertakeninEthiopia,evaluateshistorical
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experiencegainedfromdroughtinducedmigration,findingthatfamilieswithmoresurvival
strategiestendedtoresistdistressmigrationlonger(MezeHausken2000:382).InBurkinaFaso,
Henryandcolleagues(Henry,SchoumakerandBeauchemin2004)demonstratethatresidents
ofdrierregionsaremorelikelytoengageinbothtemporaryandpermanentmigrationsto
otherruralareas,ascomparedtoresidentsofhighprecipitationregions.Findley(1994)
exploredthemigratoryimplicationsofMalidroughtandfoundthattheseveredroughtof1983
1985wasassociatedwithadramaticincreaseinmigrationofwomenandchildren,andalsoan
increaseinshorttermcyclicalmigration.
Withtheaboveworkasafoundation,aspateofnewresearchhasrecentlyemergedonthe
migrationenvironmentassociation.Overwhelmingly,therecentadditionsprovideevidenceof
lackof,andvariabilityin,naturalcapitalactingasapushfactorinoutmigration,inconcert
withotherinfluences. Asanexample,bringingthelivelihoodsframeworktoruralmigration
environmentissuesinChina,Qin(2010)findsthatruraloutmigrationisastrategythatlowers
dependenceonnaturalcapital,specificallyagricultureandotherproximatenaturalresources
usedforsubsistence. Lowernaturalcapitalintheformofsmallerfishcatchesintensifies
livelihoodvulnerabilityinEastAfrica,resultinginthemigrationoffisherfolk(Njockand
Westlund2010;Nunan2010).
BringingourattentiontoMexico,Eakin(2005)arguesthatunderstandingfarmersrangeof
livelihoodchoices,andlimitstotheiradaptivecapacity,isimportantinunderstandingrural
vulnerabilitiestoclimatechange.Indeed,environmentaltrendsclearlyshapehouseholdcoping
capacitysinceagriculturalyieldsareimpactedbyclimatefactors(Luersetal.2003).Related,
researchhasshownthatofffarmemploymentandmigrationappeartostabilizehousehold
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livelihoodsthroughdiversificationandreducedenvironmentalreliance(DeJanvryandSadoulet
2001;Wigginsetal.2002).Suchlivelihooddiversificationisalsoimportanttoinsureagainst
incomerisksarisingfromcroppricefluctuations(Masseyetal.1993;StarkandBloom1985).
MigrationaslivelihooddiversificationinMexico,particularlyinlightofenvironmental
change,isalsosuggestedbyrecentlypublishedworkbySaldaaZorrillaandSandberg(2009)as
wellasbyFengetal(2010).Usingdatafromthe2,443municipalitiesofMexico,Saldaa
ZorrillaandSandbergseconometricanalysesrevealhigheremigrationratesfromMexican
municipalitiesmorefrequentlyaffectedbynaturaldisastersandwithrelativelyhigher
impoverishmentlevels.Operatingatthestatelevel,Fengetal.(2010)alsoidentifyan
environmentalpushwithintriguingstatelevelassociationsbetweendeclinesincropyields
andU.S.boundmigration.
Overall,existingscienceinseveralarenas naturalresources,livelihoods,vulnerabilityand
migrationasadaptation formsanimportantfoundationforbringingexaminationof
migrationenvironmentassociationstoruralMexico.Suchisespeciallythecasegiventhe
importantsocial,economicandpoliticalaspectsofMexicanmigrationtotheU.S.,asreviewed
next.
Mexicomigrationpatternsandprocesses: MexicanmigrationtotheU.S.hasalonghistory.Sustained,massivemovementoflabormigrantsdatesbacktorecruitmenteffortsby
U.S.employersintheearly20
th
Century(Gamio1930;Foerster1925;Cardoso1980).Migration
streamsplummetedduringtheGreatDepression(BalderramaandRodriguez2006;Hoffman
1924)butemergedagainduetoabinationallaboraccordwithMexico,theBraceroProgram,
initiatedin1942(Calavita1992).WhiletheBraceroProgramwasdiscontinuedin1964aspart
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ofbroadercivilrightsandimmigrationreform,immigrationfromMexicocontinued,both
legallyandundocumented,inasomewhatcircularfashion(Masseyetal.2002).Considerable
increasesinmigrationstreamsoccurredinthe1990sandformostofthefirstdecadeofthe21st
Century(MartinandMidgley2010;PasselandCohn2009)asemigrationfromMexicoincreased
(Beanetal.2001;HillandWong2005)andreturnmigrationratesplummeted(Masseyetal.
2002;Riosmena2004).
Historically,muchoftheMexicoU.S.migrationflowshascomefromruralareasinCentral
WesternMexico(Durandetal.2001;DurandandMassey2003).However,sincethe1980s,
emigrationtotheU.S.fromlesstraditionalsendingregionsinruralSouthCentraland
SoutheasternMexicohasincreasedconsiderably(especiallyinthelast15years,seeDurandand
Massey2003)helpingfueltherecentsurgeoutofruralareasand,inparticular,ofless
traditionalsendingcommunitiesinSouthernMexico(RiosmenaandMasseyforthcoming;
RiosmenaandZenteno2010).
RuralMexicanshave,ofcourse,alsomigratedtocitieswithinMexico(Garza2003;Lozano
Ascencioetal.1999)andsomechangesintheseprocessesarealsoofimportancetothe
presentproject.Ruralurbanflows,oncemainlydestinedforMexicoCity,Guadalajara,and
Monterrey,havebeenincreasinglydirectedtowardbordercitiessincethe1980s(Lozano
Ascencioetal.1999).Migrationtonortherncitiesisfueled,inlargepart,byemployment
opportunitiesinexportprocessing(maquiladora)
firms.Still,internalmigrantsarealsomore
likelytoultimatelyemigratetotheU.S.ascomparedtolongerterm(nonmigrant)northern
residents(Fussell2004;LozanoAscencioetal.1999).Thispatternsuggestsatleastpartofthe
internalmigrantflowfromruralareasmayeventuallyyieldU.Sboundmigration.
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Asbrieflynotedabove,explanationsforthetransformationinthegeographyofrural
Mexicanmigrationareassociatedwiththedeepeconomicrestructuringof,andshocksto,the
Mexicanpoliticaleconomy(FernandezKellyandMassey2007;Lustig1990;Masseyetal.2002;
Nevins2007).Theseshockshavedisproportionatelyaffectedlivelihoodsinruralareasandin
theSouthinparticular.Forinstance,considertheresultsofastudyoftheMexicaneconomy
sincetheenactmentofNAFTA.Zepedaetal.(2009)pointoutthatthemanufacturingsectorhas
gainedintermsofexports,productivityincreases,and,toalesserextent,jobgrowth.Still,
primarysectoremploymenthassufferedthemostlosses(forsimilarviews,seeHanson2003;
Polaski2004).Ofcourse,especiallyimportantfortheresearchoutlinedhere,manyrural
regionsofMexicoremaindependentonagricultureforsubsistenceand/orasacomponentofa
broaderlivelihoodstrategy(DeJanvryandSadoulet2001).
Asnoted,recentlypublishedresearchbySaldaaZorillaandSandberg(2009)andFenget
al.(2010)suggestintriguingmunicipal andstatelevelassociationsbetweenoutmigrationfrom
ruralMexicoandenvironmentalpushfactors(namelynaturaldisastersanddecliningcrop
yields,respectively).Yet,municipal andstatelevelanalysesdonotallowforadequatecontrol
ofthemyriadhouseholdlevelfactorsshapingmigrationdecisionmaking(e.g.Hondagneu
Sotelo1994;Lindstrom1996;Massey,Goldring,andDurand1994;MasseyandEspinosa1997;
StarkandBloom1985).Therefore,whatremainsmissingfromtheresearchonMexican
migrationisamorepreciseexaminationofthepotentialforenvironmentalfactorstobe
includedinthesuiteofmigrationdrivers. Theworkpresentedhereoperatesatfinerscales,
mostnotablythehouseholdandcommunitylevelsgiventherelevanceoftheformerasa
decisionunit(Masseyetal.1993)andofthelatterintermsofsocioeconomicandnetwork
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processesassociatedwithmigrationdecisions(MasseyandEspinosa1997;Massey,Goldring
andDurand1994).MakinguseoftheRuralLivelihoodsframework,weincludenatural
capitalamongthemoretypicalpredictorsofmigrationhuman,financial,physical,andsocial
capitals.GiventhepublicandpolicyattentiontobothclimatechangeandMexicanmigration,
bringingtheenvironmentexplicitlyintohouseholdlevelanalysesofmigrationinthissettingis
faroverdue. Here,weinvestigatethequestion: IsemigrationfromruralMexicoassociated
withrecentpatternsofprecipitation,netofothersocioeconomicandpoliticalfactorsshaping
emigrationpatterns?
DataWeusedatafromtheMexicanMigrationProject(MMP),abinationalresearchinitiativebased
atPrincetonUniversity(USA)andtheUniversityofGuadalajara(MX). Everyyearsince1987,
theMMPselectsbetween4and6Mexicancommunitiesandinterviewsarandomsampleof
approximately200households.TheMMPquestionnairecollectsbasicsociodemographicand
retrospectivemigrationquestionsaboutallmembersofthehouseholdatthetimeofthe
survey.Dataarealsocollectedonallchildrenofthehouseholdheadregardlessoftheirplaceof
residence.Amongthesequestions,respondentsreportthedatesandduration(ifapplicable)of
thefirstandlastU.S.tripforallmembersofthehousehold.Ourdependentvariablereflects
emigrationtotheU.S.byanadulthouseholdmember(age15+)withintheyearpriortothe
survey.Forthepurposesofthepresentproject,ouranalyticalfocusisoninternational
migration,althoughweintendtoexpandupontheworkpresentedherewithadditional
migrationstreams.Onemigration,aswouldbeanticipatedfromcontemporarytrends,
outmigrationfromthesampledruralhouseholdsisacommonphenomenonwith
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approximately21%sendingamigranttotheUSduringthethreeyearspriortotheyearof
observation.
Atthehouseholdlevel,weincludemeasuresreflectingaccesstothevarietyofcapitals
outlinedintheRuralLivelihoodsframeworkandcentraltohouseholdstrategies.Theseinclude
humancapital(e.g.,householdsizeandcomposition,educationallevels),financialcapital(e.g.,
businessownership),physicalcapital(e.g.landandlivestockownership,possessionsi),and
socialcapital(e.g.,headspriortriptotheUS). Astosamplecharacteristicsfortheselivelihood
variables,humancapitalmeasuredatthehouseholdlevelshowsthathouseholdheadshave
approximately5yearsofeducationand86%areemployedatthetimeofthesurvey. Overall,
40%ofhouseholdmembersareconsideredtobeinthelaborforce.Onaverage,26%of
householdsengageinfarming,22%ownabusinessandapproximately6%havebothafarmas
wellasbusiness. Ofthosewhoownland,approximately16%havetheirprimaryholdingin
eithercommunalorejidoland.Asnotedprior,householdswhoseprimarylandholdingisejido
territoryaremoreconstrainedinlivelihoodoptionsduetoincompletepropertyrightswhich
lessenstheirfinancialandcapitalassetsaswellasdecreasesthehouseholdsabilitytoaccess
formalcreditmarketsrelativetohouseholdswithprivateproperty.
Centraltothisprojectisinclusionofvariablesreflectingtheavailabilityofnaturalcapitalas
shapedbyrecentrainfalllevelsandvariability. Specifically,ourpredictorvariablesofcentral
interestrepresentrainfallpatternswithinthe3yearwindowpriortohouseholdobservation.
Wefollowedtheleadofmuchclimatescienceincalculatingastatesaverageannualrainfall
asoverahistoric30yearperiod,inourcase19601990.Ayearinwhichrainfallisonestandard
deviationbelowthestateshistoricaverageisclassifiedasadroughtyear.Inversely,arainy
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yearisoneinwhichcurrentrainfallisonestandarddeviationabovethestateshistorical
average. Importantly,wefindsubstantialvariationinprecipitationregimeswithapproximately
23%ofoursamplesubjectedtoadroughtintheirsurveyyear. Inaddition13%ofoursample
hadadroughttheyearpriortothesurveywhile3.6%hadadroughtinbothyears.
Approximately28%ofoursampleexperiencedarainyyearintheirsurveyyear,while23%had
arainyyeartheyearpriortothesurveyand7%hadarainyyearinbothyears.
Thehouseholdandindividualleveldataweresupplementedwithinformationcollectedby
theMMPatthecommunityandmunicipallevels.Thesedataincludeinformationreflecting
householdsaccesstolivelihooddiversificationoptions,suchasmanufacturingfacilities,in
additiontoinformationonlargerscalesocialcapital,suchascommunitylevelmigration
prevalence(indicatingstrengthofbroadermigrantnetworks). Indeed,thisformofsocial
capitaliswelldevelopedinmostcommunities,particularlyformen;Malemigrationprevalence
tendstobebetween2550%whilefemalemigrationprevalenceofmostcommunitiesis
between025%(seealsoMassey,Goldring,andDurand1994;FussellandMassey2004).
(Table1,DescriptiveStatistics,abouthere)
Giventhefocusonrurallivelihoods,oursampleisrestrictedtononurbancommunities.
Ouranalysesmakeuseofdatafrom24,132households,withatotalof117,040persons,in66
nonurbancommunitieslocatedin12statessurveyedfromtheyearof1987to2005.Giventhat
weincludestatelevelrainfalldata,onlystatesinwhichmorethanonecommunityhasbeen
surveyedareincludedinoursample(seeAppendixA).Thisrestrictionwasnecessaryinorderto
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ensurerepresentationandvariationinstatelevelvariablesovertimeandenablesustoutilize
statefixedeffectsinourregressionspecification.
MethodsWefirstsimplygraphaggregatedmigrationandprecipitationtrendsacrosstime,bystate,to
descriptivelyexaminetheirassociation.Importantly,wepresentmigrationtrendsonlyafterthe
highlevelsofmigrationmotivatedbythe1986ImmigrationandReformControlAct(IRCA),
whichprovidedamnestytoapproximately2.3millionseasonalandundocumentedMexican
workersintheUS.Forthesebivariateassociations,communitieswereclassifiedaccordingto
themajoritypercentageofthestatesclimatedistributionprovidedbythe2003studyby,
INEGI,NationalInstituteofStatistics,Geography,andInformatics. Overallcategoriesinclude:
warmdry,warmhumid,milddry,mildhumidandcold(INEGIAnuariosEstadisticosdelos
Estados,2004).Withinthesecategories,rainfalltrendswerecalculatedasrecentdeviation
fromthelongertermhistoricmean.Migrationprevalencerepresentsthenumberofadults
reported,retrospectivelyasleavingineachyear.
Wethendevelopeventhistorymultivariatemodelsand,giventhatmigrationisrootedin
householddecisionprocesses(e.g. HondagneuSotelo1994;StarkandBloom1985),wemodel
emigrationdecisionsatthisscale.Specifically,wemodelthelikelihoodthatatleastone
householdmemberemigratestotheU.S.inthethreeyearspriortothesurveyasafunctionof
communitylevel,householdlevelandenvironmentalfactors.Weoptedforathreeyearrecall
windowforthreereasons:1)tominimizepotentialmemorybiases(Auriat1991;Belli1998;
SmithandThomas2003);2)toincreasetherepresentativenessoftheanalysesbyavoiding
goingtoofarbackintime,whentheexperienceofpeopleemigratingoutofthecommunityis
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lost;and3)tomaximizethenumberofcovariatesavailableformodelingpurposes. Clearly,
timingrepresentsakeychallengeinworkingwiththeMMPdata.TheMMPisarepeatedcross
sectionalsurveythatincludesretrospectivequestions.Wemadeuseofinformationfromthe
retrospectivequestionstogenerateapseudopanelacrosstimeforeachhousehold.Evenso,
manyofthecommunityandhouseholdcharacteristicsaremeasuredonlyatthetimeofthe
survey. Thesestaticmeasurements,therefore,limitourabilitytoutilizeretrospective
informationtoofarbackintimeduetotheobvioustemporalmismatch. Tobalancedataneeds
withdataavailability,weusea3yearmigrationwindow,includingmigrationeventsonlyifthey
occurredwithinthe3yearspriortosurveyobservation.Wefurtherworkedtominimize
measurementerrorbyconvertingcommunitylevelmeasurestocategoricaldummyvariables.
Asouroutcomeofinterestisatimedependentevent,whichhasaprobabilityof
occurrencederivedfromacensoreddistribution,weemploydiscretetimeeventsurvival
analysistechniques.FollowingAllison(1982;seealsoSingerandWillett2003),wedothisby
fittingalogisticregressionmodelingthelikelihoodofU.S.migrationwhileconsideringthe
exposuretotheriskofemigrationofeachunitofanalysis. Todoso,weestimatethemodelon
asetofpseudoobservations,inthiscasehouseholdyearsofexposurebeforehousehold
membersemigration. TocontrolforthechangingeconomicconditionsinMexicoweemploy
bothstateandyearfixedeffectsandtoaddressthefactthathouseholddecisionsmaybe
correlatedatacommunitylevel,weclusterourstandarderrorsaccordingly.
ResultsFirst,Figures13presenttrendlinesforsampledMexicancommunitiesgroupedby
environmentalregion. Asnotedabove,theregionsaremilddry, mildhumid,andwarmhumid,
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asclassifiedwithintheMMPandbasedonthe2003studybyINEGI,NationalInstituteof
StatisticsandGeography,whichprovidesclimatezonecategorizationforeachstateinMexico.
Thefiguresclearlyhintatanassociationbetweenrainfallpatternsandemigration.Forexample,
inmilddryregions(Figure1),therelativelywetyearof1994wasassociatedwithrelativelylow
levelsofoutmigrationfromstudycommunitieswhilemigrationincreasedfollowingthe1999
rainfalldeficit. Inwarmhumidregions(Figure2),weseeconsistentlyhighlevelsof
precipitationaccompaniedbyasteadydeclineinemigration. Finally,inmildhumidregions
(Figure3),bothemigrationandrainfallhaverecentlybeenexperiencingupwardtrends,but
lookingcarefully,weseeafairlyconsistentnegativecorrelationwithlowprecipitationyears
characterizedbyrelativelyhighemigration(see1988,1994),andviceversa(see1990,1991,
and1995).
(Figures13abouthere)
Thefindingsfromourlogitmodelshedadditionallightandare,forthemostpart,consistent
withmanyofthestudiesmentionedinthebackgroundsection.Humancapitalvariables
suggesthouseholdswithmoreeducatedheadsarelesslikelytosendaninternationalmigrant,
perhapsrelatedtoenhancedlocalopportunitiestodiversifylivelihoods.Household
compositionisalsoassociatedwithemigration,withconsistentlypositivecoefficients
suggestinglargerhouseholdsaremorelikelytosendmigrantsasmightbeanticipated. Suchis
notthecase,however,inhouseholdswithrelativelymoredaughters,whicharelesslikelyto
sendaninternationalmigranttotheUS. Onfinancialcapital,employmentofheadandbusiness
ownershipdampenemigrationprobabilities,againlikelyduetoexistingdiversification
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strategies. Assetsandlandownershiptendstoincreasehouseholdemigrationprobabilitywhile
socialcapitalgainedthroughpriormigrationdoesindeedenhancethelikelihoodofemigration.
Keytoouranalysesisinclusionofnaturalcapitalmeasuresandthemodelsyieldintriguing
findings.Netoftheincorporatedhuman,physical,financialandsocialcapitalvariables,
environmentalfactorsretainstatisticallysignificantpredictiveabilitywithregardtoemigration.
Considerdrought.Netoftheotherincludedhouseholdandcommunitylevelcharacteristics,
householdsexperiencingadroughtintheyearunderconsiderationhave29%higheroddsof
sendinganinternationalmigranttotheU.S.thanahouseholdnotexperiencingadrought.1
While,ifthehouseholdexperiencedarainfalldeficittheyearprior,oddsare39%greaterof
internationalmigration.Yet,theassociationisevenmoresubstantialwhenconsideringa
longertermrainfalldeficit. Householdsexperiencinga2yeardroughtareoverthreetimesas
likelyasotherhouseholdstosendaninternationalmigranttotheU.S.
Asmightbeanticipatedbasedonthedroughtresults,higherthanaveragerainfallisthen
associatedwithlesseremigrationprobabilities. Householdswithrainfallabundanceintheyear
underexamination,relativetohistoricaverages,have30%loweroddsofsendingan
internationalmigrant and 40%loweroddsifhigherlevelsofrainfallcharacterizedtheyear
prior. Ontheotherhand,theestimateoftheassociationbetweenemigrationprobabilitiesandhigherthanaveragerainfalloverbothyearsdidnotreachstatisticalsignificance.
Ofcourse,itislogicaltoassumerainfallismostlikelytoimpacthouseholdswithresource
dependentlivelihoodstrategies. Assuch,wealsoestimateemigrationasafunctionofrainfall
interactedwithindicatorsforhouseholdswhoengageinfarming,workinagricultureorown
1Thepercentageincreaseinoddsisobservedusingabaseofanoddsratioof1.
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livestock. Here,somewhatcounterintuitiveresultsemerge. Twoyearrainfalldeficitsactually
decreasetheoddsoffarminghouseholdssendinganinternationalmigrantby35%ascompared
tononfarmhouseholdsata10%significancelevel.Similarly,theoddsofinternational
migrationdeclineforhouseholdswherethehouseholdheadisworkinginagriculture,with40%
loweroddsofsendinganinternationalmigrantcomparedtotheeffectofatwoyeardrought
onhouseholdswithanonagriculturalhead.Itislikelythatthesepatternshintatincome
constraints. Internationalmigrationisacostlyendeavorandperhapsunavailableto
agriculturaldependenthouseholdintimesofparticularlivelihoodstress.
Discussion&ConclusionHumanmigrationisacomplexsocialprocesscontingentonorigin anddestinationbased
factorsofwhichclimatevariabilitymaybeanimportantone. Assuggestedbypriorworkin
contextsasvariedasMali,EthiopiaandBurkinaFaso,theresearchpresentedherefindsan
associationbetweenrainfallpatternsandemigrationfromruralMexicototheU.S.,withdry
yearsgenerallyactingasamigrantpushandwetyearsinhibitingemigration.
InruralMexico,asinruralregionsacrosstheworldslessdevelopednations,environmental
changehasdirectimpactsonhealthandwellbeingofresidentssincenaturalresourcesare
oftencentraltoincomegenerationactivitiesand/oressentialinmeetingbasicliving
requirements(KoziellandSaunders2001).Giventhisresourcedependence,changesinweather
andclimatepatternsholdtremendouspotentialtoimpactlivelihoodsand,inthefaceofa
declineinlivelihoodoptions,migrationbecomesasignificantadaptivelivelihoodstrategy(e.g.
Adger2006;McLemanandSmit2006).
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CurrentclimatemodelsforLatinAmericaprojectmeanwarmingfrom1to6C,andanet
increaseinthenumberofpeopleexperiencingwaterstresswithintheregion(IPCC2007).
SpecifictoMexicosmostvaluableagriculturalexport,coffee,Gayetal.(2006)projectclimate
changemayyielda34%reductioninproductioninVeracruz,potentiallymakingcoffeeno
longeraneconomicallyviablelivelihoodstrategy(seealsoNevins2007;Zepedaetal.2009).
ClearlyenvironmentalchangeholdsimportantpotentialtoimpactruralMexicanslivelihood
strategies,andtherebyinfluencemigrationpatterns.Indeed,ourresultsfindaprominent
associationbetweenemigrationfromruralMexicoandrecentpatternsofprecipitation,netof
othersocioeconomicandpoliticalfactorsshapingmigrationpatterns.
Thepreliminaryworkoutlinedherepresentsmanydirectionsforfutureresearchthrough
expansionofbothsocialandenvironmentaldimensions.Onthesocialdimensions,weaimto
disaggregatemigrationstreamsbothbydestination(toexamineinternalandinternational
migration),whilealsoexploringdifferentmigrationoutcomesforMexicanmenandwomen.
Ontheenvironmentaldimension,weaimtointegrateadditionalaspectsofenvironmental
changeincludingtemperaturefluctuationsandshiftsinvegetationcoverage.Ofcourse,we
couldalsoexplorethepullofdesirablenaturalattributes;WithintheU.S.,astatelevel
associationexistsbetweenclimateandmigrationwithdesirableweatherattributes(warmer
temperatures,lesshumidity)associatedwithpositivenetmigration(Postonetal.2009).In
Ghana,regionswithgreateraccesstonaturalcapitalexperiencehigherlevelsofinmigration
(VanderGesest,VrielingandDietz2010).
Thepublic,policyandacademicrealmshaverecentlypaidincreasingattentiontothe
potentialforenvironmentalchangetoalterpatternsofhumanmigration.Social,political,
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economicandenvironmentalpressuresconvergeinruralMexicoregionswherethepresent
studysuggestsreductionofproximatenaturalcapitalmayenhancethelikelihoodof
householdstappingintomigrationslivelihoodpotential. Certainlysuchevidencesuggeststhat
theenvironmentaldimensionsoflivelihoodstrategies,includingemigration,deserveadditional,
focusedresearchattention.
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.5
.6
.7
.8
.9
1
1990 1995 2000 2005year of observation
Migrants Rainfall
States in Mild Dry Region: Aguascalientes, Chihuahua, GuanajuatoSan Luis Potosi and Zacatecas
Proportional Migrant and Rainfall Trends in Mild Dry Regions
.2
.4
.6
.8
1
1990 1995 2000 2005year of observation
Migrants Rainfall
States in Warm Humid Region: Colima, Guerrero, Jalisco, Michoacan,Oaxaca and Veracruz
Proportional Migrant and Rainfall Trends in Warm Humid Regions
Figure1
Figure2
Figure3
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Table1: MeansandStandardDeviationsof CommunityandHouseholdCovariatesVariable %/Mean Std.Dev
CommunityLevelCharacteristics
FemaleLaborForceParticipationbetween0 10% 26.70% 0.442
FemaleLaborForceparticipationbetween10 20% 60.70% 0.488FemaleLaborForceparticipationbetween20 30% 12.60% 0.332
ProportionofFemalesinManufacturingover50% 8.00% 0.271
MaleAgriculturalworkParticipationover50% 48.70% 0.500
FemaleMigrationPrevalence in1990between0 25% 86.50% 0.342
FemaleMigrationPrevalence in1990between25 50% 13.50% 0.342
MaleMigrationPrevalence in1990between25 50% 62.80% 0.483
MaleMigrationPrevalence in1990between50 75% 22.70% 0.419
MaleMigrationPrevalence in1990between75 100% 1.00% 0.099
Household
CharcteristicsDependentVariable: Householdsendsamigrant 20.60% 0.404
HumanCapitalHouseholdsize 4.85 2.369
PercentageofHHinLaborForce 39.70% 0.234
Householdheademployed 85.50% 0.352
Householdheadeducation 5.00 4.355
FinancialCapital
Householdhasbusiness 22.10% 0.415
SocialCapital
HouseholdheadnumberoftripstoUS 1.53 3.847
PhyscialCapital
Primarypropertyiseithercommunityorejidoland 15.70% 0.364
NaturalCapital
CurrentYearisaDroughtYear 23.30% 0.423
CurrentYearisRainyYear 27.90% 0.449
LastYearwasaDroughtYear 13.10% 0.338
LastYearwasaRainyYear 22.60% 0.418
TwoDroughtYearshaveOccurredinRow 3.60% 0.186
TwoRainyYearshaveOccurredinaRow 6.80% 0.251
RelianceonNaturalCapital
Householdengagedinfarming 26.30% 0.440
Householdhasbothfarmandbusiness 6.20% 0.241
Householdownslivestock 28.00% 0.450
Householdheadworksinagriculture 34.50% 0.476
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29
SE SE SE
ommunityLevelCharacteristics
ProportionofFemalesinManufacturing isover50% 0.666*** (0.204) 0.671*** (0.204) 0.673*** (0.204)
MaleAgriculturalWorkParticipationisover50% 0. 454** ( 0.177) 0. 449** (0. 175) 0. 445** (0. 175)
MaleMigrationPrevalence in1990wasbetween25 50% 0.571*** (0.159) 0.565*** (0.159) 0.558*** (0.160)
ouseholdCharacteristics
HumanCapital
HeadofHouseEducation 0.0616*** (0.0107) 0.0599*** (0.0107) 0.0603*** (0.0107)
AgeofHeadofHousehold 0.0133*** (0.00393) 0.0134*** ( 0.0039) 0.0135*** (0.00393)
Spouse'sEducation 0.0498*** (0.0118) 0.0495*** (0.0118) 0.0491*** (0.0119)
Lifecycle YoungChildren 1.327*** (0.194) 1.333*** (0.194) 1.332*** (0.194)
Lifecycle YoungandTeenageChi ldre n 1.702*** ( 0.200) 1.710*** (0.202) 1.710*** ( 0.202)
Lifecycle TeenageChildrenOnly 0.694** (0.310) 0.706** (0.311) 0.709** (0.311)
Lifecycle AdultChildren 1.474*** (0.222) 1.482*** (0.224) 1.485*** (0.224)
PercentageofDaughterstoHouseholdMembers 0.637*** (0.158) 0.639*** (0.159) 0.640*** (0.159)
FinancialCapital
TheHouseholdhasaBusiness 0.320*** (0.0834) 0.304*** (0.0792) 0.304*** (0.0793)PercentageoftheHouseholdthatisintheLaborForce 0.574*** (0.128) 0.574*** (0.128) 0.577*** (0.128)
HouseholdHeadisemployed 0.225* (0.116) 0.264** (0.117) 0.262** (0.117)
PhysicalCapital
PrimaryPropertyiseitherCommunityorEjidoLand 0.365*** (0.126) 0.361*** (0.126) 0.366*** (0.127)
PercentageofAmenitiesownedbyHousehold (outof11) 1.338*** (0.252) 1.353*** (0.251) 1.358*** (0.252)
NumberoflivestockownedbyHH 0.115*** (0.0310) 0.117** (0.0459) 0.115** (0.0461)
SocialCapital
HouseholdHead NumberofTripstotheUS 0.205*** (0.0167) 0.205*** (0.0169) 0.205*** (0.0169)
NaturalCapital
CurrentYearisaDroughtYear 0.254** (0.128) 0.253** (0.128) 0.254** (0.128)
CurrentYearisaRainyYear 0.361*** (0.139) 0.363*** (0.139) 0.363*** (0.139)LastYearwasaDroughtYear 0.329** (0.148) 0.330** (0.148) 0.332** (0.148)
LastYearwasaRainyYear 0.500*** (0.133) 0.502*** (0.132) 0.502*** (0.132)
AdroughthasOccurredTwoYearsinaRow 1. 228*** (0.464) 1. 224*** ( 0. 463) 1. 385*** ( 0. 472)
ARainyyearhasOccurredTwoYearsinaRow 0.329 (0.235) 0.335 (0.235) 0.336 (0.234)
RelianceonNaturalCapital
HouseholdisEngagedinFarming 0.0986 0.0913 0.116 (0.0924) 0.113 (0.0930)
HouseholdOwnsLivestock 0.0228 (0.114) 0.0283 (0.115)
HouseholdheadworksinAgriculture 0.0876 (0.111) 0.106 (0.112)
Interaction Farm&TwoYearDrought 0.444** (0.204)
InteractionOwnsLivestock&TwoyearDrought 0.237 (0.545)
InteractionHHHeadWorksinAg&TwoYearDrought 0.501** (0.250)
Intercept 3.956*** (0.826) 3.939*** (0.815) 3.938*** (0.813)
StateFixedEffects
YearFixedEffects
Community FemaleLaborForceParticipationControls
CommunityFemaleMigrationPrevalencein1990QuartileCo
CommunityMaleMigrationPrevalence in1990QuartileContr
Spouse'sEducationandNumberofUStripsControls
Observations
*Allresultsgiveninlogodds
Yes Yes
Table2: Discrete TimelogitPredictingtheLikelihoodofaHouseholdSendingaMigrant1 2
Yes Yes
Yes Yes
Yes Yes Yes
24,132 24,132 24,132
3
Yes
Yes
Yes
Yes
Robuststandarderrorsinparentheses ***p
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AppendixA1)
iTheMMPincludesmeasuresof11amenities/possessionswithinstudyhouseholds:runningwater,
electricity,sewage,astove,arefrigerator,awashingmachine,asewingmachine,aradio,atelevision, a
stereoandatelephone.
S tates , C ommunitites an d H H obs ervations in S am pleS tate C om m unitite s H H Ob servations P erce ntofS ample
A g uasc a lientes 2 6 5 0 2.69
C olim a 3 1 ,0 2 7 4.26
C hihuahua 3 1 ,2 6 6 5.25G ua najua to 1 2 4 ,1 8 1 1 7.33
G ue rrero 3 9 7 7 4.05
J alis c o 1 1 3 ,6 1 3 1 4.97
Mic hoac an 6 2 ,3 6 9 9.82
O axac a 4 1 ,7 0 4 7.06
P uebla 2 5 4 9 2.27
S a n Luis P otos i 9 3 ,1 7 6 1 3.16
V era c ruz 6 2 ,0 2 3 8.38
Z ac a tec a s 5 2 ,5 9 7 1 0.76
T otal 6 6 2 4 ,1 3 2 1 00