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MAKINGTHEHOUSEAHOME:THESTIMULATIVEEFFECTOF
HOMEPURCHASESONCONSUMPTIONANDINVESTMENT1
EfraimBenmelechKelloggSchoolofManagement,NorthwesternUniversityandNBER
AdamGuren
BostonUniversity
BrianT.MelzerTuckSchoolofBusiness,DartmouthCollege
April9,2019
Abstract
We introduce and quantify a new channel through which the housing market affectshousehold spending: the homepurchase channel. Using an event-study designwith datafromtheConsumerExpenditureSurvey,weshowthathouseholdsspendonaverage$3,700moreinthemonthsbeforeandthefirstyearfollowingahomepurchase.Thisspendingisconcentrated in the home-related durables and home improvements sectors, which arecomplementary to thepurchaseof thehouse.Expendituresonnondurablesanddurablesunrelatedtothehomeremainunchangedordecreasemodestly.WeestimatethatthehomepurchasechannelplayedasubstantialroleintheGreatRecession,accountingforone-thirdof the decline in home-related durables spending and a fifth of the decline in homemaintenanceand investmentspending from2005to2010, togethertotaling$14.3billionannually.
1WethankGadiBarlevy,SusantoBasu,MartyEichenbaum,SimonGilchrist,BarneyHartman-Glaser,Michael
Reher,JeremyStein,AmirSufi,andseminarandconferenceparticipantsattheFederalReserveBankof
Chicago,GreenLineMacroMeeting,HebrewUniversity,StanfordUniversity,TelAvivUniversity,Universityof
CaliforniaBerkeleyHaasSchoolofBusiness,UniversityofChicago’sConferenceonHousingand
Macroeconomics,UniversityofCopenhagen’sWorkshoponNewConsumptionData,UniversityofNotre
Dame’sRoundtableonHousingandMortgageMarkets,andtheUniversityofSouthernCaliforniaLuskCenter
forRealEstateSymposium.SashaIndarteandPaolinaMedinaprovidedgreatresearchassistance.Benmelech
isgratefulforfinancialsupportfromtheGuthrieCenterforRealEstateResearchattheKelloggSchoolof
Management.Allerrorsareourown.
1
I.INTRODUCTION
Whydohouseholdconsumptionandthehousingmarketmove in tandemthrough
periodsofbothprosperityanddecline?Thisquestionhasbeencentraltomacroeconomic
analysis and monetary policy-making in the United States since 2000, as the aggregate
economyexperiencedadramaticexpansionandcontraction thatmirrored theboomand
bust in the housingmarket. Previous studies of this pattern have focused on the role of
housingwealth inspurringhouseholdconsumption through itseffectsonoverallwealth,
creditconstraints,andemployment.
Inthispaperweproposeandprovideevidenceforafurtherlinkbetweenthehousing
marketandhouseholdconsumptionthatdoesnotoperatedirectlythroughhouseprices.We
argue thathomepurchases,whichexperiencedaboomandbust similar to thatofhome
pricessince2000,stimulatedurableconsumptionbyraisingdemandforgoodsandservices
complementary to thehome.Thisrelationship follows fromtwomainassumptions.First,
owingtosearchfrictions,householdscannotfindhomesthatmatchtheirspecifictastesand
stock of durable goods. Buyers therefore tailor their newly purchased home to their
preferencesbyalteringthephysicalstructureandbybuyingnewfurnishingsandappliances.
Second,thesealterationsandpurchasesareatleastinpartirreversible.Homerenovations
andadditions,forexample,cannotbemovedfromoneresidencetothenext.Manyfixtures,
appliances,andfurnishingsarealsopurchasedtocomplementaparticularphysicalspace
andsoarepurchasedanewafteramove.Giventheseassumptions,aggregateconsumption
willexpandandcontractwiththenumberoftransactionsduringhousingcycles.Thishome
purchase channel is particularly potent in housing downturns,when sales tend tomove
morestronglywith–andreactproportionatelymorethan–homeprices.
2
Ourprimaryanalysisusesmicrodataonhouseholdspendingandbuildingpermitsto
estimatetherelationshipbetweenhomepurchasesandhome-relatedspending.Weanalyze
monthlyexpendituresreportedbyhomeownersintheConsumerExpenditureSurvey(CE)
between2001and2013.Wealsoanalyzequarterlyhomeimprovementactivityusingthe
buildingpermithistoryofapproximatelyninemillionhomesthatsoldbetween2001and
2013.
Agreatdealofhouseholdspendingistiedtothehome.Homeownerssurveyedinthe
CEspendanaverageof$1,300peryearonhomedurablesand$2,500peryearonhome
improvement and maintenance. This home-related spending constitutes nearly 40% of
homeowners’totaldurableandimprovementspendingof$10,200peryear.
Weuseanevent-studymethodologytoestimateboththetimingandmagnitudeof
spending responsesafter thepurchaseof ahome.Withaggregatedata,homevaluesand
homepurchasesmove in tandem,which complicates the separate identification of home
value and home purchase effects. 2 Individual-level data, however, enable an analysis of
homebuyers’expenditurespreciselyaroundthedateoftheirhomepurchase.Thisfeature
allowsustoisolatespendingbynewhomebuyersfromspendingbyexistingownerswho
haveexperiencedachangeinhousingwealth.Thevariationinthetimingofhomepurchases
further allows for time fixed effects that absorb general business-cycle fluctuations in
spending. Lastly, our preferred specificationmakes use of the panel nature of the CE by
controllingforhouseholdfixedeffects.Thesefixedeffectsnarrowtheidentifyingvariation
2.Thecorrelationofhomesalesandhousepricesinlevelsisbetween0.75and0.85andinlogchangesis
between0.4and0.5.SeeAppendixBfordetails.
3
towithin-householddifferences in timeafterhomepurchaseandabsorbhousehold-level
spendingdifferencesthatrelate,forexample,tovariationinwealth,income,andstageoflife.
We estimate that homebuyers spend $5,740 (measured in 2009 dollars)more on
homedurablesandimprovementsfromthreemonthsbeforethepurchasethroughoneyear
after the purchase of a primary residence. This increase includes $2,340 of additional
spendingonhome-relateddurables,whichamountstoatriplingofspendingcomparedto
longer-tenured owners’ $1,130 annual spending on home-related durables. Recent
homebuyersalsospendsubstantiallymoreonhomeimprovementandmaintenance.These
investments in thehomemore thandouble in the firstyearafterpurchase, increasingby
$3,400relativetolonger-tenuredowners’averageannualinvestmentof$2,350.Bothhome
durables and investment spending spike particularly in the first quarter following home
purchaseandremainmodestlyhigher forsix toninemonthsafterhomepurchasebefore
levelingoffattheirlong-termaveragebytheendofthefirstyearofownership.Households
thatpurchaseadditionalproperties—vacationhomesorinvestmentproperties—alsoboost
spending,butbyasmalleramountthanowner-occupants.
Our analysis of building permits likewise shows a substantial increase in home
improvements:theestimatedcostofpermittedjobsmorethandoublesinthefirstyearof
homeownership,increasingby$2,500.Thebuildingpermitdataallowfurtherexamination
ofany intertemporal substitutionofhome improvements.We find thathomesellersalso
increasespendingonimprovementsbyanaverageof$730intheyearbeforethesale.We
conclude that first-year owners’ improvement spending is incremental, since it does not
merelyreplacesellers’deferredinvestments.
4
In contrast to the patterns we observe for home-related spending, we find that
spending on nondurables and durables unrelated to the home remain flat or decline
modestlyaroundhomepurchases.Onnet, the increases inhomedurables, improvement,
and maintenance spending are not offset by spending declines in other consumption
categories.Theabsenceofspendingincreasesunrelatedtothehomealsoreinforcesacausal
interpretationofthemainresults.
The event-study methodology is not immune to omitted variables critiques. For
instance,ashockthatcausesthehouseholdtobuyanewhome–suchasawindfallincrease
inwealth,ajobpromotionthatraisesincomeexpectations,orachangeinfamilystatus,such
asthebirthofachild–mayalsoincreasedurablespendingevenintheabsenceofahome
purchase. One would expect, however, that such omitted variables would cause
systematicallyhigherspending,evenamongcategoriesthatareunrelatedtothehome.Yet
purchasesofvehicles,jewelry,books,andhealthequipmentareverysimilarbetweenfirst-
year and long-tenured owners after accounting for household fixed effects. Indeed, only
audiovisual goods, which we view as home related but which the Bureau of Economic
Analysis’sNationalIncomeandProductAccounts(NIPA)classifyasrecreational,showan
increaseafterhomepurchase.Thisobservanceofspendingincreasessotightlyassociated
with the home suggests that household fixed effects are successful in absorbing omitted
variablesinourmainanalysis.
Therelationshipbetweenhomepurchasesandspendinghasprovenimportantinthe
aggregate,particularlyduringtheGreatRecession.FigureIshowsthetimeseriesforhome
sales (in blue and on the left axis) and for combined home durables, improvement, and
maintenancespending(inredandontherightaxis)throughtheGreatRecession.Homesales
5
plungedbynearly50%between2005and2010,from8.36millionunitsperyearto4.50
millionunitsperyear.Spendingonhomedurablesandhomeimprovementandmaintenance
alsodeclineddrastically,fallinginrealtermsby12%and28%,respectively,overthesame
period.TheseweresomeofthelargestdeclinesinspendingacrossallcategoriesintheGreat
Recession.
Drawing on our event-study estimates for spending after home purchase and the
declineinhomesalesfrom2005to2010,wecalculatethatthecollapseofhomepurchases
ledtoa$14.3billionannualdeclineinspendingandinvestmentduringtheGreatRecession.
This partial equilibrium aggregation excludes any spending by suppliers of real estate
services,suchasrealtorsandbuildingcontractors,whoearnincomefromhomepurchases
andimprovements.Nevertheless,thischannelexplainsmorethanone-thirdofthedeclinein
spendingonhomedurablesand15%to20%ofthedeclineinhomeimprovementsspending
followingthelate-2000shousingcrisis.
We provide a further point of comparison to the literature on home prices and
consumption (e.g.,Mian, Rao, and Sufi, 2013) by analyzing the aggregate sales of home-
relateddurablesbymetropolitanareaintheEconomicCensus.Usingvariationinhousing
cycles across metropolitan areas, we jointly estimate the elasticities of home-related
spending tohomepricesand tohomepurchases.Home-relatedspendingmovesstrongly
with home purchases during both the housing boom (2002 to 2007) and bust (2007 to
2012).Theelasticityofspendingtopurchasesis0.26duringtheboomand0.12duringthe
bust.Bycomparison,theelasticityofspendingtohomepricesis0.29intheboomand0.23
inthebust.Whiletheseresultsdonothaveasconvincingidentificationasourevent-study
results, they help to compare the home purchase channel to the housing wealth effect
6
channelandillustratethatthehomepurchasechannelisameaningfuldriverofspendingin
thehousingsector.
Our work relates to a broad literature on the relationship between the housing
marketandconsumption.Severalpapershavequantifiedthisrelationshipandgenerallyfind
thathouseholdsconsumebetweenfourandelevencentsofeachdollarchangeinhousing
wealth.This literature includesworkwithregionalvariationbyCase,Quigley,andShiller
(2005,2012),MianandSufi(2011,2014a,2014b),Mian,Rao,andSufi(2013),andGurenet
al. (2018); workwith household-level data by Hurst and Stafford (2004), Campbell and
Cocco (2007),Attansioetal. (2009),andAttanasio,Leicester, andWakefield (2011);and
workwithaggregatedatabyCarroll,Otsuka,andSlacalek(2011).Intermsofunderstanding
themechanism,Cooper(2013)andDeFusco(2018)usenovelempiricalapproachestoshow
that the collateral channel is important. On the theoretical side, Chen, Michaux, and
Roussanov (forthcoming), Gorea andMidrigan (2018), Berger et al. (2018), and Kaplan,
Mitman, and Violante (2019) use calibrated models to inspect the mechanism, mainly
focusingonthecollateralchannel.MostdirectlyrelatedtothispaperisworkbyBestand
Kleven(2018),whoestimate thestimuluseffectsofchanges inhousing transactiontaxes
usingidentificationfromtaxnotchesintheUnitedKingdom.Inanextension,theyuseannual
U.K.microdatatoestimatethatahousingpurchasetriggersauxiliaryspendingequalto5%
ofthehouse’spriceinthefirstyearand1%thefollowingyear.Theiranalysisusesannual
repeatedcrosssectionsandcannotcapturethefinenessinconsumptionandheterogeneity
thatisafocusofourpaper.
Ourpaperalsorelatestotheliteratureontheconsumptionofdurables.Mostofthe
theoreticalliteraturefocuseson(S,s)adjustmentmodelswithfixedcosts(e.g.,Eberly1994).
7
Our findings highlight that many durable goods purchases are complementary to other
goodsorlifechanges,suchaspurchasinganewhouse.
Therestofthepaperisorganizedasfollows.SectionIIdescribesthedata,summary
statistics,andempiricalmethodology.SectionIIIpresentstheempiricalresultsofhousehold
spendingpatternsaroundhomepurchaseforhomedurablesandhomeimprovementsand
maintenance. In Section IV we discuss our empirical identification strategy and present
placebo and robustness tests. Section V explores heterogeneity in the home purchase
channel.SectionsVIandVIIprovideestimatesoftheaggregateeffectofthehomepurchase
channelandacomparisontotheeffectofhomeprices.SectionVIIIconcludes.
II.DATAANDMETHODOLOGY
We use survey data on household spending from the Consumer Expenditure
InterviewSurvey(CE),administrativedataonbuildingpermitsfromthedataanalyticsfirm
BuildFax,anddataonretailsalesfromtheEconomicCensus.
II.A.ConsumerExpenditureSurvey
OurprimarydatasourceistheCE,whichprovidesmonthlypaneldataonhousehold
spendingforarandomsampleofnearlythirtythousandhouseholdsperyear.Thedataare
ideal for our study because they combine measures of household expenditures with
information on home purchase timing, home characteristics, and household mortgage
borrowing. Survey participants remain in the sample for one year and report their
expendituresretrospectivelythroughfourquarterlyinterviews.
8
WeusetheCE’sdetaileddataonthetiming,value,andcategoryofexpendituresto
construct monthly data on purchases of durable goods and spending on home-related
maintenanceandimprovementprojects.Thesurveyincludesanextensivesetofquestions
aboutspendingondurables,withseparatesectionsdevotedtohomefurnishings,appliances
andhouseholdequipment,vehicles,andhomemaintenanceandimprovementprojects.For
durable goodspurchasedover theprevious threemonths, households report the typeof
product(e.g.,diningtableorrefrigerator),thepricepaid,andthemonthofpurchase.For
newandusedvehicles,householdsreportthemonthofpurchase,thenetpricepaid,andthe
value of any trade-in. Finally, for homemaintenance and improvement projects, survey
participantsreportthetypeofproject(e.g.,addinginsulationorreplacingsiding)andtheir
monthlyspendingonsuppliesandcontractorlabor.Theseprojectsincludehomeadditions
and remodelingprojectsaswell as repairsandmaintenance throughout the interiorand
exteriorofthehome.Wedeflateallexpendituresto2009dollarsusingtheConsumerPrice
Index (CPI) for each spending category for durables and using NIPA deflators for home
maintenanceandimprovement.
Inadditiontotrackinghouseholdspending,thesurveygathersinformationonhome
ownershipthatallowsustomeasurethetimeelapsedsincehomepurchase.Foreachhome,
includingthehousehold’smainresidenceaswellasanyvacationandinvestmentproperties,
thesurveycollectsthemonthandyearthepropertywasacquiredandtheestimatedcurrent
value.Forowner-occupiedproperties, the surveyalsocollects theageandbasicphysical
characteristics(e.g.,numberofbedroomsandbathrooms)ofthehome.Wethereforefocus
ourmainanalysison thepurchaseofprimary residences, forwhichwe canobserveand
control for theageand characteristicsof thehome.For eachhouseholdwe calculate the
9
numberofmonthssinceacquiringtheirprimaryresidence.Infurtheranalysisweestimate
the aggregate effects of all home purchases by considering purchases of non-primary
residencesandinvestmentpropertiesaswell.Inthatcasewemeasuretime-sincepurchase
astheminimumnumberofmonthssinceacquisitionacrossthehousehold’sproperties.
AnimportantfeatureoftheCEsurveydesignisthat itdoesnotfollowhouseholds
thatmoveafterenteringthesample;thesehouseholdsexitthesampleuponmoving.Asa
result,we observe atmost threemonths of expenditures before amove,with pre-move
spendingreportedretrospectivelybythefewhouseholdsthatentertheCEsamplejustafter
movingintotheirnewresidence.Ourmainanalysisthusprimarilyexploitsthevariationin
time-since-purchase for survey participants while they remain at a given residence. In
additionaltests,weusethepre-movingexpenditurestoexamineintertemporalsubstitution
in themonthspreceding themove, although confidence intervalswiden in thesemonths
becauseofsmallsamplesizes.
II.B.BuildingPermitData
Our second data source is a database of residential building permits compiled by
BuildFax. City or county agencies typically require homeowners or their contractors to
obtainbuildingpermitsbeforemakingsignificanthomeadditionsandalterations.BuildFax
collects these records from permitting agencies and organizes them into property-level
historiesofpermittingactivity.BuildFaxreportsthenumberofpermits,brokendownbythe
typeofwork:electrical,mechanical,plumbing,orstructural.Insomejurisdictions,BuildFax
observesanestimateofthebuilding,electrical,mechanical,plumbing,andtotaljobcost.The
10
dataspan1994to2013,withBuildFax’scoverageofpermittingjurisdictionsgrowingover
thistimeperiodfromroughly25%to50%ofU.S.homes.
Werestrictoursampletohomeswithasalestransaction.Usingpropertydeeddata
fromDataQuick,weobtainthepropertyaddressesofallsingle-familyhomeswithasales
transactionbetween2001and2013.BuildFaxthenmatchestheseaddressestothepermit
recordsinitsdatabaseandreturnsapaneldatasetwiththequarterlypermittingactivityfor
eachpropertyinajurisdictionwithdatacoverage.ThematchedBuildFax–DataQuickdataset
includesninemillionpropertiesforwhichthereisatleastonehomepurchasetransaction
duringoursampleperiod.
ThepermitdataprovidetwoadvantagesovertheCEdataforthestudyofresidential
improvements. First, the permit data afford more statistical power because of the
substantiallylargersampleofhometransactions.Second,thepermitdatacoverawidertime
window around home purchases.Whereas the CE data are available only threemonths
beforeahomepurchase,thepermitdataenablethestudyofimprovementsintheyearsand
monthsleadinguptoahomesale.Totheextentthatsellersarealsobuyersofanewproperty,
thiswider timewindowallowsus toevaluate theextentof intertemporal substitution in
improvements.
II.B.EconomicCensusData
OurthirddatasourceistheU.S.CensusBureau’sEconomicCensus,whichmeasures
theannualsalesandemploymentofallbusinesseseveryfiveyears.Themostrecentthree
surveysprovidedatafor2002,2007,and2012,whichcorrespondroughlytothebeginning,
peak,andtroughofthehousingcycle.Weexamineaggregatesalesbymetropolitanareafor
11
retailersofhome-relatedgoods,includingfurniture,electronicsandappliances,andbuilding
supplies.
II.C.SampleDescriptionandSummaryStatistics
Table I presents summary statistics for the CE and BuildFax samples. The table
reports household characteristics (Panel A), property characteristics (Panel B), and
householdspending(PanelC)fortheCEdata,anditreportspermittingactivity(PanelD)for
theBuildFaxdata.
TheCEsample includesallhomeownerssurveyedbetweenApril2001andMarch
2013.Thesampleincludes665,802monthlyobservationsfor70,529homeownerswithnon-
missinginformationonthedateofhomepurchase.
As the sample statistics in Panel A show, average household annual income and
financialassetholdings,measuredin2009dollars,are$73,516and$57,444,respectively.In
termsofeducation,11%ofhouseholdheadsinthesamplelackahighschooldiploma,26%
have only a high school diploma, 29%have some college education, 21%have a college
degree,and13%haveagraduatedegree.Ofthesampledhouseholdheads,73%arewhite,
14%areHispanic,8%areblack,and3%areAsian.Moving tomaritalstatus,65%of the
householdheadsaremarried,13%aredivorced,11%arewidowed,and10%havenever
beenmarried.Themeanfamilysizeis2.6.Theaverageagefortheheadofhouseholdis53
years,and24%ofhouseholdshaveaheadofhouseholdorspousewhoisretired.
PanelBreportssummarystatisticsonpropertycharacteristics.Thetypicalproperty
inoursamplewaspurchasedaroundthirteenyearsbeforethesurveydate.Morethan60%
ofthehouseholdshaveamortgage,andabout7%ofthehouseholdshaverefinancedtheir
12
mortgageinthetwelvemonthsbeforethesurvey.Theaveragehomeis37yearsoldandhas
3bedroomsand2bathrooms.
PanelCpresents informationonhouseholdspending thatweuse toconstructour
dependentvariables in theregressionanalysis.TheCEexpendituredataaredetailedand
comprehensive.Weclassifyspendingas(1)homeimprovementandmaintenance,(2)home
durables,(3)non-homedurables,and(4)food.Theimprovementsandmaintenancevariable
includesallspendingformaterials,tools,andlaborbutexcludesthecostofhomeappliances,
whichweallocatetospendingonhomedurables.Thevastmajorityofspendingonnon-home
durables,morethan75%,goestowardvehicles.
As Panel C demonstrates, the average spending on home improvement and
maintenanceis$209permonth,amountingto$2,508peryear,whiletheaveragespending
onhomedurablesis$108permonth,or$1,296peryear.Theotherspendingcategoriesof
non-homedurablesandfoodaverage$532and$612permonth,respectively.Households
makehome improvementexpenditures inabout17%of themonths inoursample.They
purchasehomedurablesmorefrequently,in28%ofthehousehold-monthobservationsin
theCEsample.
Thepermittingsampleincludesallhomeswithasalestransactionbetween2001and
2013. Our sample includes 9,081,284 properties with at least one purchase transaction
duringour sampleperiod,with44.1quartersofBuildFaxdata coverageperpropertyon
average,withatotalof400,060,883property-quarterobservations.AsPanelDillustrates,
theaveragepropertyhas1.85permitsduringoursampleperiod,withameancountof0.31
permits forelectricalwork,0.21permits formechanicalwork,0.22permits forplumbing
work,and1.11permitsforstructuralwork.Themeantotaljobcostforallproperty-quarter
13
observations in thedata is $634perquarter.However, conditional onproperty-quarters
with positive permit-related expenditure, the mean total job cost is $42,990. This high
averagejobcostrelativetotheCEreflectsthefactthatbuildingpermitsarenecessaryfor
largehome improvementsbutnot forsmaller improvements.Becauseof this,wesee the
analysisoftheBuildFaxdataassupportiveofthemorerepresentativefiguresintheCE.
III.ESTIMATINGHOME-RELATEDSPENDINGPATTERNSFOLLOWINGHOMEPURCHASE
AshighlightedintheIntroduction,homepurchasesarehighlycorrelatedwithhome
values.Time-seriesregressionsusingaggregatedatafailtoidentifyhomepurchaseeffects
separately from home value effects because of this collinearity. Cross-sectional analyses
using instruments thatprojectontobothpriceandsalesvolume,suchas theSaiz (2010)
instrument, also cannot separate the home purchase channel from housing wealth or
collateraleffects.
Inthispaperweapplyamethodologythatisinessencesimilartoaneventstudy.We
use spending microdata at the household level, which provides additional variation to
identifyhomepurchaseeffects:cross-sectionalvariationinspendingcategoriesaswellas
time-seriesvariationmeasuredastimesincehomepurchase.
III.A.AverageConsumptionandPermittingActivitybyTimeSincePurchase
Table II provides a first pass at exploiting this variation by showing households’
averagemonthlyspendingrelativetothedatetheypurchasedtheirprimaryresidence.The
rawdifferencesinspendingaroundhomepurchaseeventsarenotnecessarilycausedbythe
homepurchase,buttheyprovideausefulpointofdepartureforthesubsequentanalysis.
14
Panel A of Table II reports averagemonthly spending by category in the quarter
beforeahomepurchaseandeachofthefirstfourquarterafterthepurchase.Thefinalrow
ofthetableshowsaveragemonthlyspendingforhouseholdsthatpurchasedfiveormore
quartersago.Allspendingfiguresareinrealterms(2009dollars)andadjustedforinflation
usingtheConsumerPriceIndexforAllUrbanConsumers(CPI-U)pricedeflator.
AsPanelAofTableIIshows,theaveragemonthlyhomeimprovementspendingin
thefirstquarterafterthehomepurchaseis$598comparedtothemeanof$196permonth
afterthefirstyearofownership.Thatis,householdsspendthreetimesmoreineachofthe
first three months after the home purchase. Moreover, home improvement spending
remainselevated inthesecondquarterafter thepurchase—spending is$382permonth,
whichisnearlytwiceaslargeastheaveragespendingbeyondthefirstyearofownership.
Spendingonhomeimprovementalsoremainshighinthethirdandfourthquartersafterthe
homepurchase,at$325and$280permonth,respectively.
Likewise,householdspendingonhomedurablesincreasesdramaticallyinthefirst
quarterafterthepurchaseofaproperty.AsTableIIshows,theaveragemonthlyspending
onhomedurables in the first threemonths after thehomepurchase is $750permonth,
comparedtoamean$94permonthafteroneyearofownership,representinganalmost
eightfoldincreaseinspendingonhomedurables.Thelevelofspendingonhomedurables
remainshigherthanthemeanthroughoutthefirstyearafterthehomepurchase.Wealso
findanincreaseinspendingonnon-homedurablesintheyearafterthehomepurchase,but
thisincreaseissmallerthanthoseforhomeimprovementorhomedurables.Forexample,
spending on non-home durables is $787 per month in the first quarter after the home
purchase, representing an increase of 51% over the $521 per month spent among
15
households beyond the first year of ownership. Finally, we do not find any significant
changes in household spending on food following a home purchase, suggesting that the
purchaseitselfisunlikelytoleadtoadramaticchangeinthehousehold’slifestyle.
In Panel B of Table IIwe summarize the building permit activity following home
purchases.Thefractionofpropertieswithat leastonepermit is7.7%inthefirstquarter
followingapurchase.The incidenceofpermits then falls steadilyduring the firstyearof
ownershipandreaches2.6%amonghomesthataremorethanoneyearbeyondthepurchase
date.Theestimatedtotal jobcostdisplaysasimilarpattern,decliningfromanaverageof
$1,292inthefirstquarterfollowingthepurchaseto$506perquarterbeyondthefirstyear
ofownership.
Theserawdifferencesinspendingofcoursemayreflectselectionintowhopurchases
rather than spending caused by the home purchase itself. For example, if wealthier
households both spend more on food and move more often, we would observe similar
spendingpatternseveniffoodspendingwereunaffectedbyahomepurchase.Ourempirical
strategyaimstoaddressthisissueandprovideacausalestimateofthespendingresponses
tohomepurchase.
III.B.AnEmpiricalModelofSpendingPatterns
Thesummarystatisticspresentedabovesuggestthathouseholdsspenddramatically
moreonhomeimprovementandhomedurablesduringthefirstyearofownership.Wenow
turntoamultivariateanalysisofhouseholdspendingandpermittingactivityfollowinghome
purchases.
16
Weuseanevent-studymethodology,estimatingthe followingregressionmodel in
theCEsample:
1 𝑆𝑝𝑒𝑛𝑑𝑖𝑛𝑔*+ = 𝛼 + 𝛽01 𝑀𝑜𝑛𝑡ℎ𝑠𝑠𝑖𝑛𝑐𝑒𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒 = 𝑚<<0=>? + 𝛿+ + 𝜸′𝑿*+ + 𝜀*+ ,
where the dependent variable is spending by household i in month t. As measures of
spending, we consider alternately the level of spending (dollars per month), the log of
spending (natural logarithm of 1 + dollar spending), and the incidence of spending (an
indicator for spending>0).Aside fromdifferent scaling, the levels specification tends to
focusonfittinglargeexpenditures,whereasthelogspecificationputsmoreweightonsmall
purchases.
Thecoefficientsofinterestarefixedeffectsforeachmonthrelativetothetimeofthe
homepurchase(𝛽0,𝑚 ∈ −3, 11 ).Thesefixedeffectsmeasurethehousehold’sincremental
spendingineachofthethreemonthsbeforethehousepurchaseaswellasthefirsttwelve
monthsofhomeownershiprelativetoanexcludedcategoryofthirteenormoremonthsafter
purchase. Time-since purchase pertains to the household’s purchase of its primary
residence,forwhichwecanobserveandcontrolfortheageandphysicalcharacteristicsof
thehome.We include theseproperty characteristics in thevectorX,whichalso includes
controlsforhouseholdincomeandwealth,aswellasdemographics:householdsize,theage
of the head of household, and indicators for the head of household’s marital status,
retirementstatus,race,andeducation.Themodelalsoincludesmonth-by-yearfixedeffects
(𝛿+)tocontrolforcommonvariationinspendingovertime,suchasfluctuationsthroughthe
businesscycle.
Mostimportant,ourpreferredspecificationmakesuseofthepanelnatureoftheCE
by controlling for household fixed effects in addition to the control variables discussed
17
above.Thesefixedeffectsnarrowtheidentifyingvariationtowithin-householddifferences
intimeafterpurchaseandabsorbhousehold-levelspendingdifferencesthataredrivenby
suchfactorsaswealth,income,orstageoflife.
Weestimatethemodelwithordinaryleastsquares,andinrobustnesstestsweshow
similar findings forProbitandTobitmodelsdesigned fordiscreteandcensoredoutcome
variables. We calculate Huber-White standard errors with observations clustered by
household.Mostoftheanalysisispresentedusingfiguresthatplotthepatterninhousehold
spendingfollowinghomepurchaseormortgagerefinancing.Thefiguresareplottedbased
on the coefficients of the fixed effects for each month relative to the date of the home
purchase (𝛽0,𝑚 ∈ −3, 11 ). These fixed effects measure the household’s incremental
spendingineachofthethreemonthsbeforethepurchaseaswellasthefirsttwelvemonths
ofhomeownershiprelativetoanexcludedcategoryofthirteenormoremonthsfollowing
thepurchaseafterwecontrolforpropertyandhouseholdcharacteristics.
Weestimateasimilarmodelinthepermittinganalysis:
2 𝑃𝑒𝑟𝑚𝑖𝑡𝑠J+ = 𝛼 + 𝛽K1 𝑄𝑢𝑎𝑟𝑡𝑒𝑟𝑠𝑆𝑖𝑛𝑐𝑒𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒 = 𝑞NK=>N + 𝜹𝒕 + 𝜽𝒑 + 𝜀J+ .
Theunitofobservationinthisanalysisisthepropertypinaquartert.Animportantfeature
ofthepermittingdataisthatwecanobservepermittingintheyearsbeforeatransaction,so
weareabletoexpandthetime-relative-to-purchasedummiestoincludeeachoftheeight
quarters before and after the home purchase. Even though the quarters before the sale
concern a different homeowner, which means that we cannot measure intertemporal
substitutionforasinglehouseholdwiththepermitdata,wecanneverthelesstestwhether
onaveragesellersdefermaintenanceorupgradetheirhousebeforeselling.Becausemost
sellers repurchase, this helps us assess intertemporal substitution for permitted home
18
improvements.Bycontrast,becausetheCEdoesnottrackmovers,wecanobserveonlyup
tothreemonthsbeforeapurchase.
Wemeasurepermittingactivityalternatelyastheincidenceofapermit(perquarter),
thenumberofpermits(perquarter),thetotalestimatedjobcost(perquarter),andthelog
oftheestimatedjobcost(natural logarithmof1+ jobcost).Ascontrolvariables insome
specifications,weincludequarter-by-yearfixedeffects(𝛿+)andpropertyfixedeffects(𝜃J).
Weestimatethemodelwithordinaryleastsquaresandclusterobservationsbyproperty.
III.C.HomeDurableSpendingFollowingHomePurchase
TableIIIpresentsresultsfromestimatingRegression(1)usingameasureofhome
durablesspendingasadependentvariable.Asthetableillustrates,thereisanincreasein
spendingduringthetwelvemonthsfollowingahomepurchase.Whenwedonotcontrolfor
householdorpropertycharacteristics,logspendingincreasesby1.87logpointsinthefirst
month,2.02logpointsinthesecondmonth,and1.09logpointsinthethirdmonth.Theselog
differencesequatetoproportionalincreasesof549%,654%,and197%,respectively.This
patternofincreasedconsumptionthatpeaksinthesecondmonthremainssimilarwhenwe
controlforpropertyandhouseholdcharacteristicsandyearfixedeffectsinColumn(2)as
wellaswhenwecontrolforhouseholdfixedeffectsinColumn(3).
Controlling forhouseholdcharacteristicsand thenhousehold fixedeffectsreduces
the estimated spending responses modestly for the first few months following a home
purchaseandmoresubstantiallyformonths6to12followingthepurchase.Theelevated
spendinglateinthefirstyearofownership—reflectedincoefficientsof0.2to0.3formonths
9 to 11 of the first specification—falls modestly after controlling for household
19
characteristicsandthenbymorethanhalfaftercontrollingforhouseholdfixedeffects.Some
oftheelevatedspendinginthefirstyearofownershipevidentintherawdata,therefore,is
causedbygenerallyhigherspendingbyhouseholdsthattendtobuyhomesmorefrequently
ratherthanbyahomepurchaseperse.Thevariationacrossspecificationsisshownvisually
inAppendixA.Nevertheless,thereisasubstantialhomedurablesspendingresponseinthe
first nine months after purchase even for the most stringent specification that includes
householdfixedeffects.
Intermsofdollarspending,homedurablesspendingincreasesby$851inthefirst
monthand$744 in thesecondmonthafterahomepurchase. In the thirdand the fourth
monthsafterthepurchase,spendingincreasesby$303and$184,respectively.Finally, in
Column(5)ofTableIIIweusetheincidenceofspendingasourdependentvariableandfind
thatthepropensitytospendonhomedurablesincreasesby20%inthefirstmonth,24%in
thesecondmonth,and12%inthethirdmonthafterahomepurchase.Theincidenceofhome
durablesspendingis5%–8%higherinmonths4,5,and6and3%–4%higherininmonths
7,8,and9.
Table III alsopresentshousehold spending for the threemonthsbefore thehome
purchase.Asthetabledemonstrates,householdsreducetheirspendingonhomedurables
inthethreemonthsbeforemakingahomepurchase.Forexample,thepropensitytospend
is 18%, 19%, and 13% lower in months −3, −2, and −1 relative to the home purchase,
respectively. The spending patterns in these three months are consistent with some
intertemporalsubstitutionofconsumption inwhichbothbuyersandsellers inapending
transaction may delay durable goods purchases and home improvements until the
transactioniscompleted.However,theanalysisofdollarspendingshowsnodifferencein
20
spendingbeforeahomepurchaseandtheanalysisoflogspendingindicatesthatspending
afterthepurchasedwarfsthedeclinebeforethepurchase.Intheanalysisoflogspending,
forexample,thecoefficientsimplyacumulativespendingdifferenceof+6.97logpointsin
thetwelvemonthsafterapurchase,whichisthreetimesaslargeasthecumulative−2.13log
pointdeclineinthethreemonthsbeforethepurchase.
ThepatternofspendingonhomedurablesisillustratedinFiguresII.A,II.B,andII.C.
Eachfigureisplottedbasedonthecoefficientsofthefixedeffectsforeachmonthrelativeto
thedateofthehomepurchase,usingasdependentvariablesthelogarithmofhomedurables
spending(Figure II.A), thedollaramountofhomedurablesspending(Figure II.B),or the
incidenceofhomedurablesspending(FigureII.C).
III.D.HomeImprovementandMaintenanceFollowingHomePurchase
We also analyze household spending patterns on home improvement and
maintenanceandreporttheresultsinTableIVandFiguresIII.A,III.B,andIII.C.AsTableIV
demonstrates, we find a significant increase in home improvement and maintenance
spendingfollowingahomepurchase.Theincidenceofhomeimprovementspendingis11%
inthemonthofthehomepurchase,whileitisnotstatisticallydifferentfromzerointhethree
months before the purchase. The likelihood that a household will conduct home
improvementandmaintenanceincreasesto15%inthefirstmonthafterthepurchaseandis
10% and 7% in the second and third months, respectively, after the purchase. The
magnitudesofthesespendingarealsosignificant,amountingtoanaverageof$485,$479,
and$301ineachofthethreemonthsafterthehomepurchase.
21
Togaugethetotaleffectofahomepurchaseonspending,weanalyzethecombined
spendingonalldurablegoods(homeandnon-home)aswellasonhomeimprovementand
maintenance.TheresultsarepresentedinTableVandinFiguresIV.A,IV.B,andIV.C.AsTable
V, Column (4) shows, the combined spending on durables and home improvement and
maintenanceis$1,462inthemonthofthehomepurchase.Spendingremainshighinthenext
threemonths,withatotalof$1,323inthefirstmonthafterthepurchaseand$659and$452
inthesecondandthirdmonthsafterthepurchase,respectively.
III.E.PermittingActivityAroundHomePurchases
Results from estimating Regression (2) for our analysis of building permits are
presentedinTableVI.ThedependentvariableinColumns(1)to(3)isthenaturallogarithm
of1+totaljobcost,whileinColumns(4)and(5),thedependentvariableistheactualjob
cost indollars.Column(1)showsan increaseof0.241 logpoints inpermit total jobcost
duringthequarterinwhichahomeispurchased,oranincreaseof27.3%inpermitcost.The
estimatedjobcostisalso0.181and0.094logpointshigherinthefirstandsecondquarters
afterthepurchase,representingproportionalincreasesof19.8%and9.9%,respectively.The
patternofincreasedjobcostduringthequarterofthehomepurchaseandthefollowingtwo
quarters also remains similarwhenwe control for year fixed effects in Column (2) and
propertyandyearfixedeffectsinColumn(3).
Intermsofactualjobcost,theaverageincreasesby$763duringthequarterofthe
homepurchaseandby$835inthefirstquarterafterthepurchase.Inthesecondandthe
third quarters after the purchase, the average job cost increases by $561 and $365,
respectively,anditincreasesbyanadditional$223inthefourthquarterafterthepurchase,
22
asshowninColumn(4).Interestingly,permitjobcostsalsoincreasebeforethepurchase,
suggesting that home sellers invest in their homes before selling. This reveals that
householdsthatarebothbuyersandsellersdonotintertemporallysubstitutebydeferring
maintenanceontheiroldhomebeforepurchasinganewhomeandinvesting in it. Italso
suggeststhatifanythingourestimateofhomeimprovementandmaintenanceintheCEis
anunderestimatebecause itdoesnot fullyaccount forupgradesmadebeforea sale that
occurmorethanthreemonthsbeforethepurchase.
Finally,inColumn(5)ofTableVIweusetheincidenceofhavinganypermitasour
dependentvariableandfindthatthelikelihoodofhavingapermitincreasesby5.5%during
thequarterofthehomepurchase,followedbya3.5%increaseinthefirstquarterafterthe
purchaseand1.9%and1.3%increasesrespectivelyinthesecondandthirdquartersafter
thepurchase.
ThepermitdataoverallcorroboratetheresultsfromtheCE.Althoughwedonotwish
to takea strong standonaggregatedollarvalues, given thatnot allhome improvements
require a permit, the general time pattern is highly consistent withwhat we see in the
consumer survey, and a two-year look-back produces no evidence consistent with
intertemporalsubstitution.
IV.CAUSALITYANDROBUSTNESS
Theresultssofarsuggestthathouseholdsincreasetheirspendingonhomedurables,
improvement,andmaintenancewhentheypurchaseahouse.Theevidenceshedslighton
thelinkbetweenthehousingmarketandprivateconsumptionthroughatransactionchannel
ratherthanapricechannel.However,itisimportanttoexploremoredeeplywhetherthese
23
effectsarecausalorwhetherunobservedheterogeneityatthehouseholdlevelisdrivingthe
results. Our regressions control for household income and wealth and various
demographics:householdsizeandheadofhouseholdage,maritalstatus,retirementstatus,
race,andeducation.Ourresultsarerobusttotheinclusionofhouseholdfixedeffects,which
absorbfixeddifferencesinexpendituresduringtheyearthatthehouseholdappearsinthe
data.
Byincludinghouseholdfixedeffects,weexploittheexacttimingofspendingrather
thanrelyingonacoarsecomparisonbetweenhouseholdsthatrecentlypurchasedahome
andthosethatdidnot.Toclarifythispoint,itishelpfultoconsidertheexampleofelderly
homeowners, who tend to stay in the same home and to keep their current household
appliances.Amodelwithoutcontrolsorhouseholdfixedeffectswouldfindhigherspending
ondurablesineachmonthduringthefirstyearofownership,sincetheelderlyspendata
low rate and are disproportionately represented in the excluded category: owners who
purchasedmorethanoneyearago.Omittingagefromthemodelcausesanupwardbiasin
thespendingcoefficientsacrosstheboardineachofthefirsttwelvemonthsafterpurchase.
Controllingforageor,moreflexibly,absorbingunobservedheterogeneitywithahousehold
fixedeffectresolvesthisproblem.
It is still possible, however, that unobserved shocks that coincidewith (andmay
potentially drive) home purchase lead to increased spending precisely in the first few
monthsafterthepurchase.Thesepotentialomittedvariablesmayinclude:(1)unobserved
financial or housingwealth that permits higher spending; (2) an increase in permanent
incomethatmayresultinanincreasedpropensitytoconsume;and(3)anincreaseinfamily
sizethatrequiresgreaterspendingondurablesandmayalsocausethehouseholdtomove.
24
Wenextconsideraseriesofplaceboteststoalleviateconcernsthatourresultsare
drivenbyomittedfactorsunrelatedtothehomepurchase.Totestwhetheromittedvariables
aredrivingourresults,weinvestigatewhetherhouseholdspendingincategoriesunrelated
to home purchase display the same patterns as spending on home durables and home
improvementandmaintenance.UsinginformationprovidedintheCE,westudyspendingon
non-homedurables,food,andentertainment.
FiguresV.A,V.B,andV.Cshowspendingpatternsfornon-homedurables(Figure5.A),
food (Figure V.B), and entertainment (Figure V.C) corresponding to fixed effects in
Regression(1).3Asthefiguresdemonstrate,thereislittlechangeinconsumptionpatterns
in any of these categories. We find a very modest response of spending on non-home
durablesandnoresponseof spendingon foodorentertainment in themonths following
home purchase. If any wealth, income, or household size shocks coincided with home
purchasesandcausedshort-runincreasesinspending,onewouldexpectthemalsotoboost
non-housingspending.Instead,wefindmuchalargerresponseofhome-relatedspending.
Weshouldalsonoteherethatnon-homedurablesandfoodspendingarenotinsensitiveto
income andwealth – coefficients on those controls show the expected relationship. The
failuretofindanon-housingandnon-durablespendingresponsethusdoesnotresultfrom
anygeneralinelasticityofthesespendingcategoriestoincomeandwealth.
3.Thefiguresareconstructedfromregressionsthatusethelogarithmoftheexpenditureasadependent
variable.FiguresthatusetheactualdollarcostlooksimilarandcanbefoundinAppendixA.
25
V.HETEROGENEITYINTHEHOMEPURCHASECHANNEL
Therichnessofourdataallowsus toexploreheterogeneity in thehomepurchase
channeltoprovidemoretextureonhowitoperates.TableVIIassessesseveraldimensions
ofheterogeneityinthehomepurchasechannelbyreportingthecumulativechangeindollar
spending from three months before a home purchase through twelve months after the
purchase.
Wefirstsplitthesampleintoaboomperiodwithhighsalesfrom2001to2006anda
bustperiodwithlowsalesfrom2007to2012.Wefindthatmarginalpurchasesintheboom
periodinducemorehomedurablespendingbutlesshomeimprovementspendingthando
purchases in thebustperiod.Thenext foursplitsarebycharacteristicsof thepurchased
home.Wefindthattherearelargerresponsesforlargerhomesintermsofsize(numberof
bedrooms)andhomevalue.Intermsofhomeage,theincreaseindurablesandimprovement
expendituresislargestforhomesunderthreeyearsold,suggestingthatthereisstillsome
customization of newer homes. The purchase of homes serving as a primary residence
inducesmorehomedurablespendingandsubstantiallymoreimprovementspendingthan
doesthepurchaseofavacationorinvestmentproperty.Thefinaltwosamplesplitsareby
homeowner characteristics.We find that older and higher-income homeowners increase
their spending on durables and improvements by a larger amount following a home
purchase.
V.A.SummaryofCumulativeEffectofHomePurchaseonSpending
Figure VI summarizes our overall results by showing the cumulative impulse
responseofspendingtoahomepurchasebycategory.Asdiscussedabove,theincreasesin
26
spendingonhomedurablesandhomeimprovementandmaintenancefollowingpurchase
dwarf the declines in these series and on non-homedurables spending before purchase.
Cumulatively, the increase in spending from threemonths before purchase until twelve
monthsafterisabout$3,400forhomeimprovementand$2,340forhomedurables,withan
$850declineinnon-homedurablesspending.Theaggregateeffectisthusnearly$5,000for
the purchase of primary residences. These effects are somewhat smaller for secondary
residences, so theaggregate cumulativeeffectunconditionalonwhether the residence is
primaryorsecondaryis$3,700.
VI.THEAGGREGATEEFFECTOFTHEHOMEPURCHASECHANNELFROM2000TO2011
In this section, we assess how much the home purchase channel contributed to
changesinconsumptioninthehousingboomfrom2000to2005andtheensuingbustfrom
2005to2011.Todoso,wecomparethechangeinconsumptionthatonewouldpredictby
multiplying the change inhome salesbyourpreferred estimates of the effect of a home
purchase on consumption in each category to the actual change in consumption in that
categoryintheCE.4,5Thisprovidesasimple,partialequilibriumaccounting,similartothe
5.WedonotcomparetoNIPAtablesbecauseNIPAusesdifferentdefinitionsthatmakeitdifficulttocompare
levelschanges.Thisproblemisparticularlyacuteforhomemaintenance,repair,andimprovement,because
theseCEcategoriesaresplitacrossresidentialinvestment,“otherservices”inpersonalconsumption,and
“imputedrent”inpersonalconsumption.
6.Onemayworrythatoureffectsoverstatetheaggregateconsumptionchangebecausehouseholdssellhome
durablesaroundasale,andsosomeofthedurablesconsumptioniscanceledoutintheaggregatebysalesof
durables.However,wefindnoevidenceofincreasedhouseholdincomefromsalesofgoodsaroundahome
saleintheCE.Wethusconcludethatourestimatesdonotoverstatetheaggregatechangeinconsumptionfor
thisreason.
27
literature on housingwealth effects, that assesses howmuch of the observed change in
consumptioncanbeaccountedforbythehomepurchasechannel.
To create the national time series for consumption and home improvement and
maintenance, we aggregate the CE using the provided sample weights. We deflate
subcategoriesofdurableconsumptionbytheirsubcategoryCPIdeflatorandsubcategories
of improvement and maintenance by their NIPA deflator. For home sales, we use non-
seasonallyadjusteddataonexistinghomesalesfortheentireUnitedStatesfromtheNational
AssociationofRealtorstogetherwithmonthly,non-seasonallyadjusteddataonsalesofnew
homes fromtheCensusBureau.Thesedataprovideamoreaccurate timeseriesofhome
salesthanhomesalesaggregatedusingtheCEweights,althoughreassuringlythetwoseries
arequiteconsistent.Thisisthecasebecausethesecategorieshadlowerinflationthanthe
aggregateCPIintheboombuthigherinflationthantheaggregateinthebust.Consequently,
deflatingbycategorypriceindicesleadstoalargerrun-upinconsumptionintheboomand
asmallerdeclineinconsumptioninthebust.Wemultiplythemonthlytimeseriesbyour
preferredestimatesof averagedollar spending in the threemonthsbeforepurchase, the
monthofpurchase,andeachofthefollowingtwelvemonthsandthenaggregatetheimplied
timeseriestotheannuallevel.Wenexttakedifferencesbetween2000–2002and2005for
theboomaswellas2005to2008–2011forthebust.Wethendividethischangebytheactual
changeintheaggregateconsumptiontimeseriesforthesamecategorycreatedusingtheCE
microdataandweights,whichgivesusthepercentageoftheaggregatechangeexplainedby
thehomepurchasechannel.Weuse2005asourbaseyearbecausehomesalespeakedin
2005.
28
OurresultsareshowninTableVIII,withtheboomabovethehorizontallineandthe
bustbelowthehorizontalline.Ourresultsaregenerallystrongerforthebustthantheboom
fortworeasons.First,homesalesfellmoreinthebustthantheyroseintheboom.Second,
homedurablesconsumption–andtoalesserextenttheothercategories–grewbymorein
theboomthanitshrankinthebust,sothedenominatorisbiggerintheboomthanthebust.
Column (1) of Table VIII shows that in the boom the home purchase channel
accountedforabout8.5%to9.0%ofthegrowthinspendingonhomedurables,whileinthe
bustthehomepurchasechannelcontributed23%to39%percentofthedeclineinspending
onhomedurables.6Thehomepurchasechannelhasasmallnegativeeffectonnon-home
durables spending, mostly because households cut back slightly on non-home durables
spending in the months preceding a move. Column (4) shows the effect on home
improvementsspending,whichwas7.4%to9.3%intheboomand13%to19%percentin
thebust.Maintenanceisamuchmoreerratictimeseries,particularlyintheboom,butwe
can see a 10% to40%effect in thebust, as shown inColumn (5). Column (6) combines
improvements and maintenance spending, finding slightly higher numbers when
maintenanceisaddedthanforimprovementsalone.
Thecategoriesofspendingaffectedbythehomepurchasechannelareonlypartof
overalldurablesandhomemaintenancespending.Toshowtheeffectofthehomepurchase
channelontheselargercategories,TableVIIIshowstheaggregateeffectofthesedeclineson
total durables in Column (3) and on total durables plus home improvements and
7.Thedifferencesbetween2005–2008,2009,2010,and2011canlargelybeascribedtothetimepathofthe
denominator.Thisisbecausehomesalesfallfrom2005to2008andthenstayatroughlythesamelowlevel,
whilehomedurablesconsumptioncontinuestodeclineslightlyuntil2009,afterwhichitbeginstorebound.
Similarpatternscanbeseenfortheothervariables.
29
maintenanceinColumn(7).Intheboom,theaggregateeffectontotaldurablesspendingwas
1.5%to2.0%,risingto3.7%to4.8%whenspendingonmaintenanceandimprovementsis
added.Inthebust,theeffectontotaldurablesspendingwas2.7%to3.6%,risingto6.6%to
9.1%whenspendingonmaintenanceandimprovementsisadded.Notethatthesefigures
are likely underestimates for the impact of home transactions on maintenance and
improvements spending, because the CE design precludes us from accounting for
improvementsmadebysellersinordertomarketandselltheirhouse.
Toprovideasenseofthemagnitudeofthiseffect,theaveragehomepurchasetriggers
a net spending of $3,700 on durables, home improvement, andmaintenance from three
monthsbeforepurchasetooneyearafterpurchase,7andfrom2005to2010salesfellby3.86
millionunits.Thisimpliesanannualdeclineinspendingofapproximately$14.3billion,or
approximately0.1%ofGDP.Asayardstickforcomparison,Mian,Rao,andSufi(2013)find
thathomeequityfellby$5.6trillionfrom2006to2009andfindamarginalpropensityto
consume (MPC) metric out of housing wealth of 5.4%, implying a total decline in
consumptionof$302.4billion,with$128.8billionaccountedforbyautos,$89.6billionby
non-durables,and$61.6billionbynon-autodurables.Ourannualeffectof$14.3billionover
three years is thus equivalent to roughly three-quarters ofMian,Rao, and Sufi’s average
annualestimateddeclineinnon-autodurablesassociatedwiththedeclineinhousingprices
from 2006 to 2009 in the Great Recession, or roughly 15% of their overall decline in
consumption.
8.Thisfigurediffersfromtheanalysispresentedabovebecauseitcombinesbothprimaryresidencesand
secondhomes,whereasthemainanalysisaboveisforprimaryresidencesonly.
30
VII.COMPARINGTHEEFFECTSOFHOMEPURCHASESANDHOMEVALUESONCONSUMPTIONUSINGCITY-
LEVELSPENDING
To benchmark the home purchase channel relative to the more-widely-studied
housingwealtheffectchannel,wecarryoutananalysisofaggregate,city-levelspendingand
home purchases and compare the response of spending to house prices and house
purchases.WeusedataonretailsalesfromtheEconomicCensus,whichcollectstheannual
salesofallbusinesseseveryfiveyears.Themostrecentthreesurveysprovidedatafor2002,
2007,and2012.Thesedatescorrespondroughlytothebeginning,peak,andtroughofthe
housingcycle.Wefocusonsales inhome-relatedgoods,whichincludesalesbyfurniture,
electronicsandappliances,andbuildingsuppliesstores.
Wemeasure theelasticityof spending tohomepurchasesandhomevaluesat the
CBSAleveloverthesefive-yearhorizons.Toparsetheseparateeffectsofhomepurchases
and home values,we estimatemultivariate regressions that rely on variation in housing
cyclesacrossCBSAstoseparatelyidentifytheeffectsofhomepurchasesandhomevalues.
OurmethodologyissimilartothatofMian,RaoandSufi(2013),whichmeasuresthe
elasticityofspendingtohousingwealthatthecountyleveloverathree-yearhorizon(2006
to2009).Weestimateelasticitiesoverfive-yearhorizonsusingthefollowingmodel:
3 ∆(𝐿𝑜𝑔𝑆𝑝𝑒𝑛𝑑𝑖𝑛𝑔)W+ = 𝛼 + 𝛽∆𝐿𝑜𝑔(𝐻𝑜𝑚𝑒𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒𝑠)W+>< +
𝛾∆𝐿𝑜𝑔(𝐻𝑜𝑚𝑒𝑃𝑟𝑖𝑐𝑒𝐼𝑛𝑑𝑒𝑥)W+>< + 𝜹𝒕 + 𝜀W+ ,
wherethedependentvariableisthefive-yearchangeinlogannualretailsalesinCBSAcas
ofyeart.WeusedatafromCoreLogictomeasuretheannualvolumeofhomepurchasesand
theyear-endCoreLogichomepriceindexforprices.Wecomputethesemeasuresfortheyear
t-1,inordertoexaminespendingthatoccurssubsequenttothechangesinhomepurchases
31
andhomeprices.Similartothedependentvariable,wetakefive-yearchangesinloghome
purchases and the log home price index. The coefficients𝛽 and𝛾 thereforemeasure the
elasticitiesofspendingtohomepurchasesandhomeprices,respectively,andareseparately
identifiedbydifferencesinthetimeseriespatternsofpurchasesandprices.Weincludeyear
fixedeffects(𝛿+)toabsorbchangesinspendingcommontoallmetropolitanareasovereach
five-year period. We estimate the model using ordinary least squares with population
weights and clustering by metropolitan area for the calculation of standard errors. Our
estimationsampleincludesanobservationfor246CBSAswiththerequisitespendingand
housingdatain2007and267CBSAswiththerequisitedatain2012.
Themodel estimates, reported inTable IX, showsignificantpositiveelasticitiesof
home-related spending to both home purchases and home prices. In the housing boom,
between2002and2007,theelasticitiesofspendingtohomepurchasesandhomepricesare
0.26(p<0.01)and0.29(p<0.01),respectively.Inthesubsequenthousingbust,between
2007 and 2012, the elasticities of spending to home purchases and home prices decline
somewhatto0.12(p<0.01)and0.23(p<0.01),respectively.Whiletheseresultsarenotas
well-identifiedasourevent-studyresults,theyprovidecomplementaryevidencethathelps
to benchmark the strength of the home purchase channel relative to the more-studied
housingwealtheffectandunderscoreourmainconclusionthatthehomepurchasechannel
isimportantandcomplementarytohousingwealtheffects.
VIII.CONCLUSION
This paper describes and quantifies a new channel for the causal relationship
betweenhousingmarketsandspending:thehomepurchasechannel.Inthemonthsbefore
andintheyearfollowingahomepurchase,householdsspend$3,700,primarilyonhome-
32
related durable goods and homemaintenance and repair. To address concerns that this
relationship is driven by unobserved heterogeneity, we use an event-study design that
includeshousehold-levelfixedeffects,sothatallidentificationcomesfromavariationwithin
households before and after a homepurchase. To address concerns that the spending is
causedbyaneventthattriggersahomepurchaseratherthanthehomepurchaseitself,we
show that there is no related effect for food or entertainment spending, and a modest
offsettingeffectfornon-homedurablegoodsspending(includedinthe$3,700figureabove).
ThischannelplayedaquantitativelysizableroleinintheGreatRecessionandamore
modestroleinthepriorhousingboom.Itaccountedforathirdofthedeclineinhomedurable
goodsspendingduringtheGreatRecessionandafifthofthedeclineinhomeimprovement
and maintenance spending. A back-of-the-envelope calculation implies that the home
purchasechannelaccountedfora$14.3billion–or0.1%ofGDP–declineinspendingper
yearintheGreatRecession.
Thehomepurchasechannelcomplementstheresponseofconsumptiontochangesin
housingwealthdrivenbyhousepricesthathasbeenthefocusofrecentliterature(e.g.,Mian,
Rao,andSufi2013).AppendixAshowsthatchangesinhousingpricesandsalesvolumeare
highly correlated, both in levels and in log changes. The home purchase channel is
quantitatively smaller than the housingwealth channel because it only affects non-auto
durablesspending,butforthesecategoriesitissubstantial:themagnitudeofoureffectis
equivalenttothree-quartersofthecausaleffectofthe2006–2009changeinhousingwealth
onnon-autodurablesconsumptionestimatedbyMian,Rao,andSufi(2013).
Beyondunderstandingthemechanismsconnectingthehousingmarketandspending
intheGreatRecession,ourestimatesareofrelevancetopolicymakers.Totheextentthat
33
monetarypolicyispassedthroughintomortgageinterestrates,monetarypolicycanhavea
substantial impact on housing transaction volume. Our estimates are a crucial input for
monetarypolicymakerswhowishtounderstandtheeffectofthesesalesondurablesand
homeimprovementspending.Inaddition,ourfiguresareacrucialinputintothecost-benefit
analysisforfiscalpolicymakersinterestedinpursuingpoliciesdesignedtostimulatehome
sales, such as the new homebuyer tax credit in the Great Recession (Berger et al.,
forthcoming).
34
References
Attanasio,Orazio,AndrewLeicester,andMatthewWakefield,“DoHousePricesDrive
ConsumptionGrowth?TheCoincidentCyclesofHousePricesandConsumptionin
theUK,”JournaloftheEuropeanEconomicsAssociation,9(2011),399–435.
Attanasio,Orazio,LauraBlow,RobertHamilton,andAndrewLeicester,“BoomsandBusts:
Consumption,HousePricesandExpectations,”Economica,76(2009),20–50.
Berger,David,VeronicaGuerrieri,GuidoLorenzoni,andJoeVavra,“HousePricesand
ConsumerSpending,”ReviewofEconomicStudies855(2018),1502-1542.
Berger,David,NicholasTurner,andEricZwick,“StimulatingHousingMarkets,”Journalof
Finance(forthcoming).
Best,Michael,andHenrikKleven,“HousingMarketResponsestoTransactionTaxes:
EvidencefromNotchesandStimulusintheUK,”ReviewofEconomicStudies85
(2018),157-193.
Campbell,JohnY.,andJoaoF.Cocco,“HowDoHousePricesAffectConsumption?,”Journal
ofMonetaryEconomics,54(2007),591–621.
Carroll,ChristopherD.,MisuzuOtsuka,andJiriSlacalek,“HowLargeAreHousingand
FinancialWealthEffects?ANewApproach,”JournalofMoney,Credit,andBanking,1
(2011),55–79.
Case,KarlE.,JohnM.Quigley,andRobertJ.Shiller,“ComparingWealthEffects:TheStock
MarketVersustheHousingMarket,”AdvancesinMacroeconomics,5(2005),1–30.
———,“WealthEffectsRevisited:1975–2012,”CriticalFinanceReview,2(2013),101–128.
Chen,Hui,MichaelMichaux,andNikolaiRoussanov,“HousesasATMs?Mortgage
RefinancingandMacroeconomicUncertainty,”JournalofFinance(forthcoming).
35
Cooper,Daniel,“HousePriceFluctuations:TheRoleofHousingWealthasBorrowing
Collateral,”ReviewofEconomicsandStatistics,95(2013),1183–1197.
DeFusco,Anthony,“HomeownerBorrowingandHousingCollateral:NewEvidencefrom
ExpiringPriceControls,”JournalofFinance73(2018),523-573.
Eberly,JaniceC.,“AdjustmentofConsumers’DurableStocks:EvidencefromAutomobile
Purchases,”JournalofPoliticalEconomy,102(1994),403–436.
Gorea,Denis,andVirgiliuMidrigan,“LiquidityConstraintsintheU.S.HousingMarket,”
WorkingPaper,2018.
Guren,AdamM.,AlisdairMcKay,EmiNakamura,andJonSteinsson,“HousingWealth
Effects:TheLongView,”WorkingPaper,2018.
Hurst,Erik,andFrankStafford,“HomeIsWheretheEquityIs:MortgageRefinancingand
HouseholdConsumption,”JournalofMoney,Credit,andBanking,36(2004),985–
1014.
Kaplan,Greg,KurtMitman,andGianlucaViolante,“ConsumptionandHousePricesinthe
GreatRecession,”WorkingPaper,2019.
Mian,Atif,andAmirSufi,“HousePrices,HomeEquity-BasedBorrowing,andtheU.S.
HouseholdLeverageCrisis,”AmericanEconomicReview,101(2011),2132–2156.
———,“WhatExplainsthe2007–2009DropinEmployment?,”Econometrica,82(2014),
2197–2223.
———,“HousePriceGainsandU.S.HouseholdSpendingfrom2002to2006,”Working
Paper,2014.
Mian,Atif,KamaleshRao,andAmirSufi,“HouseholdBalanceSheets,Consumption,andthe
EconomicSlump,”QuarterlyJournalofEconomics,128(2013),1687–1726.
36
Saiz,Albert,“TheGeographicDeterminantsofHousingSupply,”QuarterlyJournalof
Economics,125(2010),1253–1296.
37
TableI.SummaryStatistics
PANELA:HouseholdCharacteristics Mean Std.Dev
PANELB:PropertyCharacteristics Mean Std.Dev
Income/Wealth Monthssincepurchase 160 156
Annualincome 73,516 66,335 Purchasedinprevious
12months?(%) 6.37 24.42Financialassets 57,444 291,913 Mortgagor?(%) 63.96 48.01Assetsinformation
missing? 0.11 0.32 Monthssince
refinancing# 59 70
Education Refinancedinprevious
12months?(%) 6.82 25.21Nohighschooldiploma 0.11 0.32 Ageofhome(years) 37 29Highschooldiploma
only 0.26 0.44 Ageofhomemissing? 0.09 0.29Somecollege 0.29 0.46 Rooms 6.63 2.03Collegedegree 0.21 0.41 Bedrooms 3.11 0.89Graduatedegree 0.13 0.33 Bathrooms 1.80 0.74
Race/Ethnicity Centralair? 0.68 0.47White 0.73 0.44 Swimmingpool? 0.11 0.31Black 0.08 0.27 Porch? 0.82 0.38Hispanic 0.14 0.35 Off-streetparking? 0.83 0.37Asian 0.03 0.18
Other 0.01 0.12 PANELC:HouseholdSpending
MaritalStatus Married 0.65 0.48 Spendingpermonth($)
Widowed 0.11 0.31 Homeimprovement
andmaintenance 209 1,960Divorced 0.13 0.33 Homedurables 108 698Separated 0.02 0.12 Non-homedurables 532 3,623Nevermarried 0.10 0.30 Food 612 500
Other Likelihoodofpurchase(permonth)
Ageofhouseholdhead 52.86 15.82 Anyhome
improvement? 0.17 0.38Familysize 2.63 1.45 Anyhomedurables? 0.28 0.45
Retired?(%) 23.69 42.52 Anynon-home
durables? 0.52 0.50
Anydurablesor
improvement? 0.38 0.49 Notes:Sampleincludes665,802monthlyobservationson70,529homeownerswithnon-missinginformationondateofhomepurchaseinCEsamplebetween2001and2013.
38
TableI.SummaryStatistics(Continued)
PANEL D: Building Permits Estimated Total Job Cost ($)
Unconditional, per quarter 634 13,149 Conditional on permit 42,990 99,502
Number of permits, by type (per property) Electrical 0.313 1.989 Mechanical 0.208 1.420 Plumbing 0.224 1.525 Structural 1.106 5.936 All 1.850 8.999
Notes:Buildingpermitsdataincludes400,060,883quarterlyobservationson9,081,284propertiesbetween2001and2013.
39
Table II. Household Spending Following Home Purchase or Mortgage Refinancing
Panel A: Spending After Home Purchase
Average Monthly Spending ($)
Quarters Since Purchase Home Improvement Home
Durables Non-home Durables Food
1 598 750 787 596 2 382 251 717 607 3 325 175 627 608 4 280 151 657 606
5+ 196 94 521 613
Panel B: Building Permits After Home Purchase
Building Permit Activity
Quarters Since Purchase Any Permit? Number of Permits Estimated Job
Cost ($)
1 0.077 0.122 1,292 2 0.057 0.094 1,344 3 0.040 0.063 1,032 4 0.034 0.052 813
5+ 0.026 0.039 506
Notes: Real spending per month measured in January 2009 dollars (CPI-U as price deflator).
40
TableIII.SpendingonHomeDurablesSurroundingaHomePurchase
DependentVariable:HomeDurables
MonthssincepurchaseLog
SpendingLog
SpendingLog
Spending Spending($) Spending>0?
-3 -0.45*** -0.48*** -0.86*** -53 -0.18*** (0.15) (0.15) (0.22) (226) (0.04)-2 -0.66*** -0.61*** -0.79*** 4 -0.19*** (0.06) (0.06) (0.10) (78) (0.02)-1 -0.38*** -0.36*** -0.48*** 121 -0.13*** (0.05) (0.05) (0.09) (78) (0.02)0 1.87*** 1.90*** 1.84*** 851*** 0.20*** (0.07) (0.07) (0.09) (63) (0.02)1 2.02*** 2.02*** 1.93*** 744*** 0.24*** (0.06) (0.06) (0.08) (54) (0.01)2 1.09*** 1.07*** 0.95*** 303*** 0.12*** (0.06) (0.06) (0.07) (39) (0.01)3 0.77*** 0.73*** 0.58*** 184*** 0.08*** (0.05) (0.05) (0.07) (41) (0.01)4 0.54*** 0.49*** 0.36*** 51** 0.05*** (0.05) (0.05) (0.06) (23) (0.01)5 0.52*** 0.47*** 0.35*** 35 0.06*** (0.05) (0.05) (0.06) (22) (0.01)6 0.40*** 0.36*** 0.23*** 44 0.03*** (0.05) (0.05) (0.06) (27) (0.01)7 0.40*** 0.36*** 0.24*** 13 0.04*** (0.04) (0.04) (0.05) (18) (0.01)8 0.38*** 0.34*** 0.21*** 18 0.03*** (0.04) (0.04) (0.05) (22) (0.01)9 0.22*** 0.18*** 0.07 8 0.01 (0.04) (0.04) (0.05) (19) (0.01)10 0.26*** 0.23*** 0.10** -4 0.02* (0.04) (0.04) (0.05) (19) (0.01)11 0.26*** 0.23*** 0.11** 19 0.02** (0.04) (0.04) (0.05) (23) (0.01)N 665,802 665,802 665,802 665,802 665,802R2 0.01 0.06 0.29 0.22 0.30
Controlvariables: Propcharacteristics? N Y Y Y YHHcharacteristics? N Y Y Y Y
HHfixedeffects? N N Y Y YYearfixedeffects? N Y Y Y Y
41
TableIV.
SpendingonImprovementandMaintenanceSurroundingaHomePurchase DependentVariable:HomeImprovementandMaintenance
MonthssincepurchaseLog
SpendingLog
SpendingLog
Spending Spending($) Spending>0?
-3 0.03 0.07 -0.02 1182 -0.02 (0.22) (0.22) (0.25) (1063) (0.03)-2 -0.09 -0.03 -0.08 40 -0.01 (0.07) (0.07) (0.10) (148) (0.02)-1 0 0.05 -0.01 149 0.00 (0.05) (0.05) (0.08) (98) (0.01)0 0.75*** 0.81*** 0.77*** 485*** 0.11*** (0.06) (0.06) (0.08) (95) (0.01)1 1.06*** 1.10*** 1.01*** 479*** 0.15*** (0.06) (0.06) (0.08) (80) (0.01)2 0.72*** 0.75*** 0.63*** 301*** 0.10*** (0.05) (0.05) (0.07) (74) (0.01)3 0.57*** 0.60*** 0.41*** 197** 0.07*** (0.05) (0.05) (0.07) (82) (0.01)4 0.40*** 0.42*** 0.25*** 123* 0.04*** (0.05) (0.05) (0.06) (67) (0.01)5 0.32*** 0.34*** 0.18*** 97 0.03*** (0.04) (0.04) (0.06) (65) (0.01)6 0.23*** 0.25*** 0.08 163 0.01 (0.04) (0.04) (0.06) (136) (0.01)7 0.24*** 0.26*** 0.11** 43 0.02** (0.04) (0.04) (0.05) (52) (0.01)8 0.16*** 0.19*** 0.03 19 0.01 (0.04) (0.04) (0.05) (39) (0.01)9 0.19*** 0.21*** 0.07 67* 0.01 (0.04) (0.04) (0.05) (38) (0.01)10 0.18*** 0.20*** 0.05 -13 0.01 (0.04) (0.04) (0.05) (29) (0.01)11 0.17*** 0.19*** 0.04 70 0.00 (0.04) (0.04) (0.05) (48) (0.01)N 665,802 665,802 665,802 665,802 665,802R2 0.00 0.03 0.27 0.23 0.29
Controlvariables: Propcharacteristics? N Y Y Y YHHcharacteristics? N Y Y Y YHHfixedeffects? N N Y Y YYearfixedeffects? N Y Y Y Y
42
TableV.
TotalSpendingonDurables,Improvement&MaintenanceSurroundingaPurchase DependentVariable:AllDurables,HomeImprovement&HomeMaintenance
MonthssincepurchaseLog
SpendingLog
SpendingLog
Spending Spending($) Spending>0?
-3 -0.05 -0.24 -0.69** 818 -0.08** (0.27) (0.26) (0.31) (1105) (0.04)-2 -0.82*** -0.85*** -1.00*** -350 -0.14*** (0.10) (0.10) (0.13) (269) (0.02)-1 -0.48*** -0.55*** -0.64*** 19.48 -0.10*** (0.07) (0.07) (0.11) (201) (0.02)0 1.49*** 1.42*** 1.38*** 1,462*** 0.10*** (0.07) (0.06) (0.10) (188) (0.01)1 1.70*** 1.58*** 1.48*** 1,323*** 0.11*** (0.06) (0.06) (0.09) (161) (0.01)2 1.11*** 0.96*** 0.82*** 659*** 0.07*** (0.06) (0.06) (0.08) (143) (0.01)3 0.91*** 0.72*** 0.52*** 452*** 0.05*** (0.06) (0.06) (0.08) (154) (0.01)4 0.66*** 0.46*** 0.28*** 164 0.04*** (0.06) (0.05) (0.07) (150) (0.01)5 0.59*** 0.40*** 0.22*** 52 0.03*** (0.05) (0.05) (0.07) (117) (0.01)6 0.44*** 0.26*** 0.09 61 0.01 (0.05) (0.05) (0.07) (166) (0.01)7 0.43*** 0.25*** 0.11* 118 0.02 (0.05) (0.05) (0.06) (119) (0.01)8 0.41*** 0.23*** 0.08 -50 0.01 (0.05) (0.05) (0.06) (93) (0.01)9 0.37*** 0.19*** 0.07 66 0.01 (0.05) (0.05) (0.06) (99) (0.01)10 0.35*** 0.17*** 0.03 -112 0.01 (0.05) (0.05) (0.06) (93) (0.01)11 0.35*** 0.18*** 0.04 73 0.01 (0.05) (0.05) (0.05) (105) (0.01)N 665,802 665,802 665,802 665,802 665,802R2 0.01 0.13 0.42 0.18 0.46
Controlvariables: Propcharacteristics? N Y Y Y YHHcharacteristics? N Y Y Y YHHfixedeffects? N N Y Y YYearfixedeffects? N Y Y Y Y
43
TableVI.BuildingPermittingActivitySurroundingaHomePurchase
Quarterssincepurchase DependentVariable:BuildingPermits
-8(Omitted)Log
JobCostLog
JobCostLog
JobCost JobCost($) Anypermit?
-7 -0.006 -0.004 -0.005 -7 -0.001 (0.000) (0.000) (0.000) (5.283) (0.000)-6 -0.010 -0.006 -0.007 2 -0.001 (0.000) (0.000) (0.000) (5.456) (0.000)-5 -0.007 -0.004 -0.005 48 -0.001 (0.000) (0.000) (0.000) (5.625) (0.000)-4 0.002 0.003 0.002 146 0.000 (0.000) (0.000) (0.000) (5.841) (0.000)-3 0.011 0.015 0.014 268 0.002 (0.000) (0.000) (0.000) (6.057) (0.000)-2 0.022 0.027 0.026 288 0.006 (0.000) (0.000) (0.000) (6.029) (0.000)-1 0.030 0.035 0.034 29 0.012 (0.000) (0.000) (0.000) (5.513) (0.000)0 0.241 0.245 0.244 763 0.055 (0.001) (0.001) (0.001) (7.057) (0.000)1 0.181 0.188 0.187 835 0.035 (0.001) (0.001) (0.001) (7.255) (0.000)2 0.094 0.104 0.103 561 0.019 (0.000) (0.001) (0.001) (6.828) (0.000)3 0.063 0.073 0.072 365 0.013 (0.000) (0.000) (0.001) (6.458) (0.000)4 0.043 0.054 0.053 223 0.009 (0.000) (0.000) (0.001) (6.137) (0.000)5 0.023 0.038 0.037 135 0.006 (0.000) (0.000) (0.000) (5.895) (0.000)6 0.010 0.029 0.028 95 0.005 (0.000) (0.000) (0.000) (5.814) (0.000)7 0.007 0.026 0.026 78 0.004 (0.000) (0.000) (0.001) (5.770) (0.000)8 0.003 0.023 0.023 63 0.003 (0.000) (0.000) (0.001) (5.708) (0.000)N 194,786,763 194,786,763 194,786,763 194,786,763 197,457,069R2 0.00 0.00 0.05 0.03 0.06
Yearfixedeffects? N Y Y Y YPropertyfixedeffects? N N Y Y Y
44
TableVII.HeterogeneityintheSpendingResponsetoHomePurchaseCumulativeDollarSpendingAroundHomePurchaseinMontht
(Sumofmarginalspendingresponses,t-3andt+12)
TimePeriodorSampleRestriction HomeDurables
HomeImprovement
andMaintenanceTimePeriod Housingboom(2001-2006) 2,544 3,069Housingbust(2007-2013) 1,923 4,699
HomeSize TwoorfewerBedrooms 1,596 2,447ThreeBedrooms 2,499 2,075FourormoreBedrooms 2,566 5,902
HomeValue BelowMedian(≤$175,000) 1,583 408AboveMedian(>$175,000) 3,114 6,125
HomeAge Lessthanthreeyearsold 6,139 7,198Threetotenyearsold 2,853 2,658Tenormoreyearsold 1,317 3,127
Residencyatpurchasedproperty? Yes;primaryresidence 2,340 3,400No;vacationorinvestmentproperty 1,486 801
HomeownerAge Thirty-fiveoryounger 1,462 1,901Thirty-sixorolder 2,964 4,517
HouseholdIncome BelowMedian(≤$57,000) 1,799 1,806AboveMedian(>$57,000) 2,740 4,645
45
TableVIII.AggregateEffectofHomePurchaseChannelinGreatRecession
Home Home HomeTotal
Durables,
HomeNon-Home Total Improve- Mainten- Improvements Improvements
Durables Durables Durables ments anceand
Maintenanceand
Maintenancet2000–2005 8.9% -0.6% 1.4% 8.7% 9.9% 8.8% 3.7%2001–2005 8.5% -0.6% 1.6% 7.4% 61.9% 8.4% 3.8%2002–2005 8.8% -0.8% 1.9% 9.3% -139.9% 10.9% 4.8%2005–2008 35.0% -1.3% 3.6% 19.9% 32.3% 21.0% 9.1%2005–2009 23.1% -1.4% 3.4% 13.3% 37.4% 14.5% 7.9%2005–2010 33.5% -1.0% 2.7% 13.3% 16.7% 13.7% 6.6%2005–2011 39.3% -1.3% 3.3% 15.7% 9.7% 14.5% 7.8%
Note: Each cell reflects the fraction of the total change in a consumption category for a given time periodexplainedbythehomepurchasechannel,computedbymultiplyingthechangeinhomesalesforthetimeperiodby our preferred estimate of the dollar amount of consumption associatedwith a homepurchase. For thepreferred estimate and the consumption time seriesused in thedenominator, theCEdata is deflatedby acategory-leveldeflatorfromtheCPI(fordurables),NIPA(forhomeimprovements,andthissamedeflatorisalsousedformaintenance,whichdoesnothaveitsowndeflator),oracombinationofCPIandNIPA(forthelast column). This is done at themonthly level and aggregated to the annual level. Each column reflects aconsumptioncategory,whileeachrowreflectsthetimeperiodoverwhichchangesarecomputed.ThedataonthetotalchangeinaconsumptioncategoryforagiventimeperiodareaggregatescomputedusingCEweights.ThesalesseriesiscreatedbycombiningNationalAssociationofRealtors(NAR)dataonexistinghomesaleswithCensusdataonsalesofnewsingle-familyhomes,bothtakenfromFRED(notethattheNARdataisnolongeronFREDbutcanbeobtainedfromtheNAR).
46
TableIX.HeterogeneityintheSpendingResponsetoHomePurchase
Dependentvariable:
∆Log(Home-relatedretailspending)
TimePeriod: 2002-2007 2007-2012
∆Log(HomePurchases) 0.26*** 0.12*** (0.06) (0.02)
∆Log(HomePriceIndex) 0.29*** 0.23*** (0.03) (0.04)
Yearfixedeffects? Y Y N 246 267R2 0.44 0.28
Note:Wereportestimatesoftheelasticitiesofretailspendingtohomepurchasesandhomeprices.Thedataonannualspending,whichareatthemetropolitanarealevel,comefromthe2002,2007and2012EconomicCensus.Thedataonhomepurchasesandhomeprices,whicharealsoatthemetropolitanarealevel,comefromCoreLogic.Wemeasurerealspendingandrealhomepricesin2012dollars,usingtheCPI-Uasthepricedeflator.Weestimatethemodelwithordinaryleastsquares,weightedbypopulation,andclusterobservationsbymetropolitanareawhencalculatingstandarderrors,whicharereportedinparentheses.
47
FigureI.HomeSalesandHome-RelatedSpendingintheGreatRecession
Note:Bothseriesarenormalizedbytheirmaximumvalue.Homesales,inblueontheleftaxis,arethesumoftheNationalAssociationofRealtors’existinghomesalesseriesandtheCensus’sseriesofnewhomesales.A12-monthmovingaveragecenteredattheindicateddateisshowntosmoothoutseasonality.Homedurables,improvement,andmaintenance,inredontherightaxis,isthesumofthesecategoriesfromtheConsumerExpenditureSurveyaggregatedupbythesurveyweightsandnormalizedto2009dollarsusingthecategorypriceindex.
.7.8
.91
Hom
e D
ur, I
mpr
, and
Mai
nt, P
eak
= 1
.4.6
.81
Sale
s, P
eak
= 1
2000 2005 2010 2015Date
Home Sales Home Dur, Impr, and Maint
48
FigureII.HomeDurablesImpulseResponsetoHomePurchase
49
50
FigureIII.HomeImprovementandMaintenanceImpulseResponsetoHomePurchase
51
52
FigureIV.TotalDurable,Improvement,andMaintenanceSpendingImpulseResponse
53
54
FigureV.Non-HomeDurables,Food,andEntertainmentResponsestoPurchase
55
56
FigureVI.SummaryofCumulativeEffectofHomePurchasebyCategory
57
AppendixA:TheRelationshipBetweenHousePricesandSalesVolume
Theliteraturehasfocusedlargelyonhowchangesinhousingwealthdrivenbyprice
movementsaffectsconsumption.Thehomepurchasechannelwedescribeiscomplementary
tothischannelbecausechangeinhousepricesarehighlycorrelatedwithchangesinsales
volume.
Figure A.1 shows the relationship between severalmeasures of home prices and
homesalesfrom1968to2013.Thepriceseries,whichincludetheNationalAssociationof
Realtors(NAR)mediansalesprice(1968–2013),theCoreLogicnationalhousepriceindex
(1976–2013),andtheFederalHousingFinanceAuthorityalltransactionspriceindex(1975–
2013), are all aggregated to quarterly, seasonally adjusted (by the data producer), and
adjustedforinflationusingtheCPIandnormalizedtoonein1990.Thesalesseriesisthe
NARsingle-familyhomesalesseries(1968–2013).Weuseonlysingle-familysalesrather
thanallsalesbecausesingle-familysalesareavailableforamuchlongerpanelthanallsales.
Tominimizeseasonalityinthisseries,whichisnotseasonallyadjustedbythedataprovider,
weshowaone-yearaveragearoundtheplotteddate.PanelAofFigureA.1showstheseries
inlevels,whilepanelBshowstheseriesinannuallogchanges.
Thepriceseriesarehighlycorrelatedwith thesalesvolumeseries,althoughsales
volumeissomewhatmorevolatile.Indeed,thecorrelationofthepriceserieswiththesales
seriesrangesbetween0.75and0.86,dependingontheindex.Beyondthiscorrelation,the
figurerevealsthatinboththeearly1980sandthelate1980s,whennationwidehouseprices
fellmodestly, and in theGreatRecession, salesvolume fellmuchmore thanprices. Sales
volumeappearstoleadpricechanges,butonlybyafewquarters.Inlogchanges,thereisstill
a fairly strong correlation between sales and prices, although sales volume is far more
58
volatile.Nonetheless,inannuallogchanges,thecorrelationsbetweenthesalesseriesand
pricesare0.47fortheNARmedianpriceseries.0.39fortheCoreLogicPriceIndex,and0.43
fortheFHFApriceindex.
FigureA.1.RelationshipBetweenPriceandSalesVolume
A.PriceVersusSalesVolumeinLevels
.51
1.5
2Sa
les
Volu
me
/ Pric
e, 1
990
= 1
1970 1980 1990 2000 2010Quarter
NAR SF Sales, 1yr Ave NAR Real SF Median PriceCL Real Price Index FHFA All Trans Real Price Index
59
B.PriceVersusSalesVolumeinLogChanges
−.4
−.2
0.2
.4Lo
g Ch
ange
in S
ales
Vol
ume
/ Pric
e
1970 1980 1990 2000 2010Quarter
NAR SF Sales, 1yr Ave NAR Real SF Median PriceCL Real Price Index FHFA All Trans Real Price Index