Who Lives in New Jersey Housing? UPDATED NEW JERSEY DEMOGRAPHIC MULTIPLIERS The Profile of Occupants of Residential Development in New Jersey Alexandru Voicu and David Listokin CENTER FOR URBAN POLICY RESEARCH EDWARD J. BLOUSTEIN SCHOOL OF PLANNING AND PUBLIC POLICY RuTgeRs, The sTATe uniVeRsiTy Of new JeRsey NEW BRUNSWICK, NEW JERSEY november 2018
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Who Lives in New Jersey Housing?
UPDATED NEW JERSEY DEMOGRAPHIC MULTIPLIERS
The Profile of Occupants ofResidential Development
in New Jersey
Alexandru Voicu and David Listokin CENTER fOR URbAN POLICY RESEARCH
EDWARD J. bLOUSTEIN SCHOOL Of PLANNING AND PUbLIC POLICYRuTgeRs, The sTATe uniVeRsiTy Of new JeRsey
The information in this report may be used with full attribution to
Rutgers, The State University of New Jersey, and the authors.
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
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Definitions/Comments ii
Preface v
PART ONE: An Introduction to Demographic Multipliers: Description and Illustrative Applications
Demographic Multipliers: Description and Derivation 1
Summary of New Jersey Demographic Multiplier Findings 13
Data Statistics and Statistical Analysis 16
How to Use This Report and Illustrations 20
Data and Model Challenges; Ongoing and Future Research 22
PART TWO: New Jersey Demographic Multiplier Data
STATEWIDE—NEW JERSEYRESIDENTIAL MULTIPLIERS
A. Newer Housing Units, Built 2000–2016, from 2012–2016 American Community Survey
• TotalPersonsandPersonsbyAge 34
• School-AgeChildren 37
• PublicSchoolChildren 40
• TotalPersons(statistics) 43
• School-AgeChildren(statistics) 46
• PublicSchoolChildren(statistics) 49 B. All Housing Units, Newer and Older, from 2012–2016 American Community Survey
• TotalPersonsandPersonsbyAge 53
• School-AgeChildren 57
• PublicSchoolChildren 61
• TotalPersons(statistics) 65
• School-AgeChildren(statistics) 69
• PublicSchoolChildren(statistics) 73
CONTENTS
Who Lives in neW Jersey housing?ii
DEFINITIONS/COMMENTS
ACS
Bedrooms (BR)
(Housing Size)
Demographic Multipliers
Housing Age
Housing Categories
(Structure Type)
Housing Rent (Contract Rent)
Housing Rent (Gross Rent)
Household Size
Housing Tenure
(Ownership or Rental)
Housing Unit
American Community Survey. The ACS is a yearly survey of population and housing in theUnitedStatesthatisadministeredbytheUnitedStatesCensusBureau.
Thenumberofroomsthatwouldbelistedasbedroomsifthehouseorapartmentwerelistedonthe market for sale or rent even if these rooms are currently used for other purposes. A housing unitconsistingofonlyoneroomisclassifiedashavingnobedroom(studio).
Inthisstudy,encompassesresidentialdemographicmultipliers—thenumberandprofileof occupants in housing.
• All (or All Age)housing.Inthisstudy,referstoallhousingunitsbuiltinNewJerseyofanyyear.Itincludesbothnewerandolderhousingunits.
• Single-familydetached.A1-unitstructuredetachedfromanyotherhouse,thatis,withopenspace on all four sides. Such structures are considered detached even if they have an adjoining shedorgarage.Aone-familyhousethatcontainsabusinessisconsidereddetachedaslongasthebuildinghasopenspaceonallfoursides.
• Single-familyattached. A1-unitstructurethathasoneormorewallsextendingfromgroundtoroofseparatingitfromadjoiningstructures.Inrowhouses(sometimescalledtownhouses),doublehouses,orhousesattachedtononresidentialstructures,eachhouseisaseparate,attached structure if the dividing or common wall goes from ground to roof.
Contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings,utilities,fees,meals,orservicesthatmaybeincluded.
Gross rent is the contractrentplustheestimatedaveragemonthlycostofutilities(electric,gas,waterandsewer)andfuels (oil,coal,kerosene,wood,andthelike) if thesearepaidbytherenter(orpaidfortherenterbysomeoneelse).Inthisstudy,themonthlygrossrents(convertedtohousing-unitvalue;seeHousingValue)areindicatedinthePartIIdemographictables.
Thetotalnumberofpersonsinahousingunit.
A housingunitisoccupiedifitiseitherowner-occupiedorrenter-occupied.Ahousingunitisowner-occupiediftheownerorco-ownerlivesintheunit,evenifitismortgagedornotfullypaidfor.Alloccupiedhousingunitsthatarenotowner-occupied,whethertheyarerentedoroccupiedwithoutpaymentofrent,areclassifiedasrenter-occupied.
A housingunitmaybeahouse,anapartment,agroupofrooms,orasingleroomthatisoccupied(or,ifvacant,intendedforoccupancy)asseparatelivingquarters.
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DEFINITIONS/COMMENTS
Housing Value (Rent)
Median Housing Value
Public School Children (PSC)
Residential Multipliers
School-Age Children (SAC)
Terciles (Housing Value)
Forowner-occupiedunits,housingvalueisthecensusrespondent’sestimateofhowmuchtheproperty(includingthelotandadditionalbuildingsfornon-condominiummulti-unitbuildings)wouldsellforifitwereforsale.Inthisstudy,thevalueofarentedunitisestimatedtobe110times the monthly grossrent. The housing value and rents are adjusted to 2016 values using theACSadjustmentfactorforhousingdollar.ForNewerHousinginNewJersey(unitsbuilt2000–2016),housingvalueiscategorizedintotripartiteclassification:housing priced below the median, housing priced above the median, and All Value housing.Sinceinthe5-yearACSsurveymedianvalueschangefromyeartoyear,theclassificationisdonerelativetotheyear-specificmedianvalues.Theabovehousingpricetermsarejustastheyarestated. HousingpricedbelowthemedianshouldnotbeconfusedwithaffordableorMount Laurel housing,asitissometimesreferredtoinNewJersey.Housingpricedabovethemedianisnot synonymouswithwhatissometimesreferredtoasmarket-ratehousing(tocontrastthemarket-rate from theaffordableor“Mount Laurel”categories).Forallhousingunits inNew Jersey(newerandolderbuiltunits),housingvalueiscategorizedintoaquadripartiteclassification:All Value housing,andthenhousingunitsarrayedbyterciles(thirds)ofvalue:firsttercile(lowerone-third),second tercile(middleone-third),andthird tercile(upperone-third).Thefirsttercileis notsynonymouswitheitheraffordablehousingorMount Laurel housing.
These multipliers show the population associated with different housingcategoriesas well as housingdifferentiatedbyhousingvalue,housingsize(bedrooms),andhousingtenure.
The authors wish to thank the representatives from the public and private sectors in New
Jersey and beyond who provided important comments on the current investigation. Among
others, we thank Sidney Wong of Community Data Analytics; Richard Voith and Daniel
Miles of Econsult Solutions, Inc.; and Richard Grip of Statistical Forecasting LLC. We also
thank Morris Davis and David Frame of the Rutgers Center for Real Estate, our colleagues
at the Rutgers Business School. This study was greatly improved by the research of all the
above-named consummate professionals.
We appreciate the multifaceted and valuable assistance of Jamie Berger to the current
study. An earlier 2006 version of this research was edited and produced by Arlene Pashman,
an editor at the Bloustein School for decades.
Finally, we acknowledge our colleague, Robert W. Burchell of Rutgers University, with
whom we have collaborated on demographic research for the past four decades.
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PREFACE
Inthe1970sand1980s,researchersatRutgersUniversity(atanacademicunitthatultimatelybecameacomponentoftheRutgersEdwardJ.BlousteinSchoolofPlanningandPublicPolicy)publishedaseriesofnationalstudies(hereinafter,the“Rutgers–Blousteinstudies”)1 that contained information onresidentialdemographicmultipliers—thenumberandprofileofpeople(including school-age and public school children) found in differentcategories of housing units. The Rutgers–Bloustein studies provided demographic information for the nation, and for each of the census regions (e.g.,NortheastUnitedStates)andcensussubregions(e.g.,MiddleAtlanticStates,whichincludesNewJersey).
The Rutgers–Bloustein studies were widely applied throughout the United States aswell as inNew Jersey. In 2006, aNew Jersey-specificmultiplier study2was conducted by Rutgers–Bloustein that examinedhousing built in theGarden State between1990 and2000. Inevitably,however,theRutgers–Blousteinstudiesbecamedatedovertimeanddonotreflectthedemographicrealityofageneraldeclineovertimeintheaveragehousehold sizeand theaveragenumberofpupilsperhousingunit.Forinstance,thenumberofpublicschoolchildrenintheaverageNewerBuiltNewJersey4-bedroomsingle-familydetached(SFD)homedroppedfrom1.21in1980(unitsbuilt1970to1980)to0.85in2016(unitsbuilt2000to2016),adeclineofabout30percent.Inotherwords,theintroductionof1004-bedroomSFDsinNewJerseyasof2016wouldgenerateonlyabout85publicschoolchildrenascomparedto121pupilsafewdecadesearlier.
Inshort,thepracticeofusingtheolderpublisheddemographicstudiesproducesanerroneousoverstatementofthepopulationgeneratedbynewdevelopment in New Jersey.
To improve the state of our knowledge, this Rutgers–Bloustein study producesdemographicinformationonhouseholdsizeandpupilgeneration(bothschool-ageandpublicschoolspecific)thatisbothcurrent(usesthelatest released American Community Survey [ACS] data from the U.S. Census Bureau)andNewJersey–specific(containsdemographicdatauniquetothisstatealone).Ourstudytapsthe2012–2016AmericanCommunitySurveyfor New Jersey—the latest ACS release as of the writing of this report and aprimaryarms-lengthsourceusedbydemographers,urbanplanners,andother researchers.
Thedocument’s data are invaluable for accurate demographicpro-jections and development impact assessment. Yet, as with any data, there are limitations, and we later discuss shortcomings of the information in the current investigation.Morebroadly, sensitivity is requiredwheneverprojecting the population of new development from any given demographic multipliers,foritisinherentlydifficultto“crystalball”theexactdemographic
The practice of using the older published demographic studies
produces an erroneous overstatementof the population generated
by new development in New Jersey
1.RobertW.BurchellandDavidListokin,The Fiscal Impact Handbook (NewBrunswick,NJ:CenterforUrbanPolicyResearch, 1978); RobertW. Burchell, David Listokin,andWilliamDolphin,The New Practitioner’s Guide to Fiscal Impact Analysis (NewBrunswick,NJ: Center forUrban Policy Research, 1985); RobertW. Burchell andDavid Listokin,Fiscal Impact Analysis (Washington,DC:NationalAssociationofHomeBuilders,1991);andRobertW. Burchell, David Listokin, andWilliam R.Dolphin,Development Impact Assessment Handbook and Model (Washington,DC:UrbanLandInstitute,1994).
2.DavidListokinandIoanVoicu,Who Lives in New Jersey Housing? New Jersey Demographic Multipliers (NewBrunswick,NJ:RutgersUniversity,CenterforUrbanPolicyResearch,2006).
Who Lives in neW Jersey housing?vi
future and impact. Further, it is important that the study’s data not bemisused to exclude certain categories of housing, such as homeswithmore bedrooms, or rental housing, or affordable housing, or for thatmatterhousing ingeneral,becauseof theapprehension that residentialdevelopmentwillgenerate“toomany”newresidentsandpublicschoolchildren.Thatexclusionaryperspectivedoesnotacknowledgecurrentdata(thedemographicmultipliershavegenerallydeclinedinsizeovertime),subvertsgoodplanning(smartgrowthcallsforarangeofhousingandamixoflanduses),andviolatestheMount Laurel principle of all communities inNewJerseyhavingtheobligationofmeetingthespectrumofthestate’shousing needs.
The current demographic multiplier study from Rutgers–Bloustein joins otherparallelgoodresearchonthesubject.Examplesincludestate-by-statehouseholdsizeandschool-agechildrenmultipliers in theUnitedStatesfromtheCommunityDataAnalytics(CDA)teamatEconsultSolutions,Inc.,locatedinPhiladelphia(https://econsultsolutions.com/cda-demographic-multipliers); state-by-state school children demographicmultipliersdevelopedbytheNationalAssociationofHomeBuilders(NAHB,CarmelFord,http://eyeonhousing.org/2017/02/the-average-number-of-school-age-children-per-home/); and school-age childrenmultipliers inNew Jerseyrental units developed at theRutgersUniversityBusiness School (RBS)CenterforRealEstate(MorrisA.Davis,DavidFrame,RonaldS.Ladell,andDebraTantleff,“School-AgeChildreninRentalUnitsinNewJersey:ResultsfromaSurveyofDevelopersandPropertyManagers,”July2018,https://www.rutgersrealestate.com/publications/white-papers/school-age-children-study/#page=1).TheCDAandNAHBstudiesutilizeACSdataandcontaindemographic multipliers for a variety of housing in New Jersey as well as all otherstates.TheRutgersRBSinvestigationfocusesonschool-agechildrendataforNewJerseyrentalhousingunitsfromaspecializedanddetailedsurveyofdevelopersandpropertymanagersinthisstate.Weencouragethe readers of this current Rutgers–Bloustein demographic investigation to considerandreviewtheabove-citedotherdemographicstudies.
Foreasyuse,thispublicationfromRutgers–Blousteinisorganizedintotwoparts.Thefirstdescribestheresidentialdemographicmultipliersandpresentsillustrativeexamples.ThesecondpartcontainsthefullarrayoftheNewJerseymultipliersforhouseholdsize,school-agechildren,andpublicschoolchildren.WeshortlypresentanoverviewguidetoallofthePartTwotablescontainingthemultiplierdataassembledinthismonograph,andweurgereaderstoreadthePartOnetextbeforeusingPartTwoinformation.Foreasyreference,wealsoprovideasummaryofthedefinitionoftermsrelated to the multipliers on pages ii and iii of this study.
It is important that the study’s data not be misused to exclude housing
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The ACS is the “premier source for detailed population and housing information about our nation”
— U.S. Census Bureau
Part One
AN INTRODUCTION TO DEMOGRAPHIC MULTIPLIERS
—
DESCRIPTION AND ILLUSTRATIVE APPLICATIONS
DEMOGRAPHIC MULTIPLIERS:DESCRIPTION AND DERIVATION
Howmanypeople and school children are generatedby housing inNewJersey?Governmentandcitizensingeneralunderstandablyare
interestedinthesepopulationfiguresbecausetheyaffectthedemandforpublicservicesandexpenditures(e.g.,foreducationandtransportation),themarket demand for nonresidential space, and other important considerations.
AstheprofileofpopulationinhousinginNewJersey(andelsewhere)isamoving targetover time—amirrorof thedynamicfluxofAmerica’shouseholds—it is important to obtain current demographic information.The stark demographic changes in New Jersey housing over the past few decadesarefoundinTableI-1.Itisevidentthattheresidentialdemographicmultipliers have declined over time, with that decline somewhat moderating in recent years, or even sometimes reversing direction. In short, current demographic information is essential.
Toprovideempiricalupdated informationconcerning “who lives inNew Jersey housing,” the current Rutgers–Bloustein study contains data onresidentialdemographicmultipliersthatshowthenumberandprofileof the populations associated with different categories of housing in the GardenState.Demographicprofilesarepresentedforthevastmajorityoftheoccupied housing in this state, including detached and attached, single and multifamily,andownedandrental(thespecificmultiplehousingcategoriesaredetailedshortly);onlyafewrelativelyminorsubsetsofhousinginNewJerseyarenotexamined.3
Thedemographicmultipliers are derivedbyRutgers–Bloustein fromtheAmericanCommunitySurvey (ACS),which isdefinedby theUnitedStatesCensusBureauthatadministerstheACSas“anongoingsurveythatprovides informationon a yearly basis about our nation and its people ....[P]ublicofficials,plannersandentrepreneursusethisinformationtoassess the past and plan the future.”4TheCensusBureauobservesthattheACSisthe“premiersourcefordetailedpopulationandhousinginformation
3. This study does not present New Jersey demographic multipliersfortheoccupantsofmobilehomes;householdsresiding in unusual and outlier housing combinations,suchasone-bedroom,single-familydetachedhomes,andsix-bedroomtownhouses;andfortheoccupantsofgroupquarters,suchasshelters.
4.United States Census Bureau, “About theAmericanCommunity Survey.” https://www.census.gov/programs-surveys/ACS/about.html
Who Lives in neW Jersey housing?2
aboutournation.”5WetapthelatestreleaseoftheACSasofthewritingin this study.
ThespecificACSinformationthatisanalyzedisthe2012–20165-yearACSPublicUseMicrodataSample(PUMS)becauseonlyPUMSallowsthedetailedcross-tabulationofdemographicinformation.The5-yearPUMSfilesaremultiyearcombinationsofthe1-yearPUMSfileswithappropriateadjustments to theweights and inflation-adjustment factors. Bywayofbackground, theAmericanCommunity Survey containsbothpublishedsummarydataandPublicUseMicrodata.Inthesummarydata,thebasicunitisanidentifiedgeographicarea,andinformationonpeopleandhousingispresentedbygeographicarea(e.g.,Newark[NewJersey],ortheentirestate).Thepublisheddataarereadilyusable,buttheiruseislimitedtotheinformationaspresented;itisnotpossibletospecifycross-tabulationsofhousingbydemographicvariables(e.g.,toexaminetheassociationbetweenhousing and population characteristics). For instance,while averagehouseholdsizeforagivencommunityorthestateasawholeisavailablefromthepublishedsummarydata,theestimatesdonotindicatehouseholdsizefortwo-bedroomtownhousesversusthree-bedroomtownhouses,thetypeofdetailedinformationsoughtbymostanalysts.
By contrast, the PublicUseMicrodata Sampledoes permit cross-tabulationofonevariablebyanyotherdesiredvariables.ThebasicunitinthePUMSisahousingunitanditsoccupants.Thesedisaggregateddatacanbe summarized and,most importantly, allowdetailed studyof therelationshipsbetweenhousingandpopulationcharacteristicssuchasthosedescribedshortly.WiththePublicUseMicrodataSample,theanalystcanundertakecross-tabulationofsizeofhousehold(includingthenumberofschool-ageandpublicschoolhouseholdmembers)bythetype,size,value,andtenureofthehousingunit—thedatapresentedinPartTwoofthisstudy.
ThePublicUseMicrodataSampleisavailablefordifferentlevelsofgeographicdetail,suchasthenation,state,andcounties/countygroups.(TheUnitedStatesCensusBureauisenjoinedfromreleasingPublicUseMicrodata samples for geographic areas containing fewer than 100,000 persons.)ThePUMSisavailableina1Percentor5Percentsample.Thecurrentstudyusesthelarger5PercentPUMSsampleforNewJersey.
Rutgers–Blousteinderivesdemographicmultipliersforbothrecentlybuilt(2000to2016)NewJerseyhousing(inotherwords,“NewerHousing”or“NewerBuilt”)aswellasallNewJerseyhousing(newer,andolder—or“AllAge”).Bothofthesehousingagecohortsareinformative:theNewer,orrecentlybuilt,datapresentsasnapshotofthemoreimmediate-resulthousehold and school children characteristics from newer development, whiletheAllHousing–unitdatapresentsthelonger-termhouseholdandschoolchildrenprofile.Naturally,thesamplesizeoftheAllHousinggroupis larger than that of just the Newer Housing category. The total weighted sample for the all housing cohort in New Jersey that is studied here is
Only PUMS allows the detailed cross-tabulation of demographic information
about3.1millionhousingunits(about155,000actualunitssampledinthe5PercentPUMS)—almosttentimesthesamplesizeofthenewerhousingcohortinNewJerseythatisexamined(about330,000weightedhousingunits,reflectingabout17,000actualunitssampledinthe5PercentPUMS).Thetenfold-largersamplesizeof theAllHousingcohort, inpart,affordsthe demographic multipliers derived for this group enhanced statistical robustnessrelativetotheNewerBuiltdemographic,asexplainedlaterinthisstudy. Yet, many analysts prefer, and communities are often most interested in, the more immediate result household and school children demographic profileprovidedbytheNewerBuiltmultipliersasopposedtotheAllHousingcategory.Bottomline:bothhousing-agesetsofmultipliers—forNewerBuiltand All Housing—deserve consideration, with their inherent advantages and disadvantages.
ForboththeNewerBuiltandAllHousing,Rutgers–Blousteincalculatesthe New Jersey residential multipliers for:
TAbLE I-1Illustrative New Jersey Statewide Residential Demographic Multipliers
Notes: a. Datafor1980isforhousingbuilt1970through1980;datafor1990isforhousingbuilt1980through1990;datafor2000isforhousingbuilt 1990through2000;anddatafor2016isforhousingbuilt2000–2016. b. Ownedandrentedunitsofaveragevalue.Multifamily=housingunitsinstructurescontaining5ormorehousingunits.
Source:For1980,1990,and2000,U.S. Census of Population and Housing,PublicUseMicrodataSampleforNewJerseyforindicatedyears.For2016, 2012–2016AmericanCommunitySurvey,PublicUseMicrodataSampleforNewJersey.
1. Household Size (HS): Total persons per housing unit.
2. Age distribution of the household members organized intothefollowingeightagecategories:0–4,5–17,18–34,35–44,45–54,55–64,65–74,75+.
3. Total school-age children (SAC),ornumberofpersonsinthehouseholdofschoolage,definedasthose5to17yearsold.(TheSACisthesameasthenumberofhouseholdmembersintheage5–17category.)
4. Total public school children (PSC), or the SAC who attend publicschools.
5. TheSAC and PSCbyschoollevelandgradegrouporganizedasfollows:elementary(kindergarten-grade5),juniorhighschool(grades6–8),andhighschool(grades9–12).
These multipliers and some associated statistics, such as sample size,dispersionofthedata,andtheconfidenceintervalsoftheindicateddemographicinformation(statisticalcharacteristicsdescribedlaterinmore
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1. Single-Family DetacheD (Own/Rent)d
2 Bedrooms <$284 >$284 <$162 $162–258 >$258
3 Bedrooms <$304 >$304 <$228 $228–350 >$350
4to5Bedrooms <$506 >$506 <$325 $325–520 >$520
2. Single-Family attacheD (Own/Rent)d
2 Bedrooms <$238 >$238 <$149 $149–238 >$238
3 Bedrooms <$283 >$283 <$168 $168–284 >$284
3. SmalleR (2-4 UnitS) mUltiFamily (Own/Rent)d
0–1 Bedroom <$114 >$114 <$103 $103–134 >$134
2 Bedrooms <$145 >$145 <$127 $127–171 >$171
3 Bedrooms <$178 >$178 <$154 $154–207 >$207
4. miD-SiZe (5–49 UnitS) mUltiFamily (Own)e
0–1 Bedroom <$210 >$210 <$125 $125–208 >$208
2 Bedrooms <$289 >$289 <$170 $170–260 >$260
3 Bedrooms <$303 >$303 <$191 $191–354 >$354
5. miD-SiZe (5–49 UnitS) mUltiFamily (Rent)f
0–1 Bedroom <$119 >$119 <$99 $99–127 >$127
2 Bedrooms <$185 >$185 <$122 $122–164 >$164
3 Bedrooms <$178 >$178 <$119 $119–167 >$167
6. laRgeR (50 UnitS) mUltiFamily (Own)e
0–1 Bedroom <$314 >$314 <$152 $152–271 >$271
2 Bedrooms <$500 >$500 <$253 $253–418 >$418
3 Bedrooms <$836 >$836 <$354 $354–608 >$608
7. laRgeR (50 UnitS) mUltiFamily (Rent)f
0–1 Bedroom <$178 >$178 <$59 $59–126 >$126
2 Bedrooms <$281 >$281 <$133 $133–224 >$224
3 Bedrooms <$316 >$316 <$130 $130–252 >$252
8. all hOUSing UnitS (Own)e
0–1 Bedroom <$261 >$261 <$136 $136–251 >$251
2 Bedrooms <$304 >$304 <$180 $180–289 >$289
3 Bedrooms <$329 >$329 <$233 $233–354 >$354
4–5Bedrooms <$507 >$507 <$334 $334–523 >$523
9. all hOUSing UnitS (Rent)f
0–1 Bedroom <$129 >$129 <$95 $95–128 >$128
2 Bedrooms <$178 >$178 <$124 $124–163 >$163
3 Bedrooms <$180 >$180 <$145 $145–191 >$191
Housing Structure/Type/Bedrooms Statewide NEWER Housing Unitsa Statewide ALL Housing Units
b
Tenure (Own/Rent) Value (2016 in $000s)c Value (2016 in $000s)
c AllHousingValuesand AllHousingValues
Below/AboveMedianValue andbyTercile bELOW AbOVE FIRST SECOND THIRD MEDIAN MEDIAN TERCILE TERCILE TERCILE
TAbLE I-3Organization of the New Jersey Residential Demographic Multipliers
a. HousingunitsbuiltinNewJersey2000–2016(NewerBuiltunits)asmonitoredbythe2012–2016AmericanCommunitySurvey. b.AllHousingunitsinNewJersey(NewerBuiltandolder)asmonitoredbythe2012–2016AmericanCommunitySurvey. c.Symbol<means“lessthan”;Symbol>means“greaterthan.” d. Includesbothownedandrentedhousingunits. e. Includes only owned housing units. f. Includes only rented housing units.
Source: TablesII-AandII-B.
Who Lives in neW Jersey housing?6
HousingType Housing Household School-Age PublicSchool Size Size Children Children (Bedrooms) (HS) (SAC) (PSC)
TAbLE I-9Illustrative New Jersey Statewide Residential
Demographic Household Size and School Multipliers(2016—ALL UNITS)a
(FIRST TERCILE Housing Values)b
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detail),arepresentedinaseriesoftwelvetablesinPartTwoofthisstudy,organizedasdetailedinTableI-2.Therearesixtables(II-A-1throughII-A-6)forthe“Newer”NewJerseyhousing(unitsbuilt2000–2016)andaparallelsixtables(II-B-1throughII-B-6)forthe“AllNewJerseyHousing,”bothnewerandolder.Alltwelvetablespresentvaryingdemographicandstatisticaldata(TableI-2),organizedbythehousingtype,size(numberofbedrooms),tenure(ownorrent),andvaluecharacteristicsshowninTableI-3.AsTableI-3indicates,therearemultiple(nine)housing-typeandtenurecombinations,arangeofhousingsizesfrom0(studio)–1bedroomtothemuch larger4-5bedrooms, andanarrayofhousingvalues. ForNewerHousingbuilt2000–2016,therearethreehousingvaluegroupsasof2016inNew Jersey: “all values,” “below-medianvalue,”and“above-medianvalue.”6 For All Housing—Newer Built and older—there are four value groupsasof2016:AllValues;andunitspricedatthefirsttercileofvalue(lowerone-third);secondtercileofvalue(middleone-third);andthirdtercileofvalue(upperone-third).7
HousingType Housing SCHOOL-AGECHILDREN Size ALL ELEMENTARy MIDDLE HIGH SCHOOL (bedrooms) (K–12) (K–5) (6–8) 9–12)
Illustrative New Jersey Statewide Residential Demographic School (Grade Level) Multipliers
(2016—NEWER UNITS built 2000–2016)a (All Housing Values)
6.Theabove-medianandbelow-medianpricedistinctionsare as indicated and should not be confusedwith thedistinctions betweenmarket-priced housing and below-market(orMount Laurel)-pricedhomes.
7.Aswith the above-median and below-median pricedistinctions, the tercile price cohorts are as indicated and should not be confusedwith the distinctions betweenmarket-pricedhousingandbelow-market(orMount Laurel)-priced homes.
findingsaresynopsizedhereinTablesI-4throughI-9.TableI-4showsthehouseholdsize(HS),school-agechildren(SAC),andpublicschoolchildren(PSC)forcommonconfigurationsofhousing(e.g.,3-bedroomSFDasopposedto2-bedroomSFD)ofNewerHousinginNewJersey(built2000–2016)ofAllHousingvalues.Inparallel,TableI-5doesthesamebutpresentstheHS,SAC,andPSCdemographicsofAll[NewJersey]Housing—NewerBuiltandolder—of All Housing values. Since housing value impacts the multipliers, TablesI-6throughI-9summarizethedemographicsbyhigher-valuepricecohorts(TablesI-6andI-7)versuslower-valuepricepoints(TablesI-8andI-9)for,respectively,theNewerHousinginNewJersey(TablesI-6andI-8)andforAllexistinghousingintheGardenState(TablesI-7andI-9).
Toillustrate,wefocusontheNewerBuilt(built2000–2016)housingdemographics.ForAllValuesuchhousingunits(TableI-4),foreveryonehundred3-bedroomnewersingle-familydetachedhomes(bothownedandrented),about276personswouldbegenerated,including45school-agechildren,ofwhom39wouldlikelyattendpublicschool.Onehundred(100)2-bedroomnewer townhouses (bothownedand rented)wouldgenerateapproximately 231 persons, including about 27 school-age children,23 in public school.Onehundred (100) 2-bedroomnewermultifamilycondominiums in buildings of at least 50 housing unitswould containabout201persons,ofwhom8wouldbeofschoolage,4attendingpublicschool.Onehundred(100)2-bedroomnewerrentalhousinginbuildingsofminimum50-housing-unitsizewouldhouseabout224persons,ofwhom15wouldbeofschoolage,13attendingpublicschool.
What is thepopulationgeneration if theNewerBuilt housing (built2000–2016)wereofhigher,above-medianvalue?Thenthedemographicswould be as follows (Table I-6): For every 100 3-bedroomnewer suchhighervaluedsingle-familydetachedhomes,about261personswouldbegenerated,including36school-agechildren,ofwhom31wouldlikelyattendpublicschool.Onehundred(100)2-bedroomnewertownhousesofabove-medianvaluewouldgenerateapproximately236persons,includingabout25school-agechildren,19inpublicschool.Onehundred(100)2-bedroomnewermultifamilycondominiumsinbuildingsofminimum50housing-unitsizewouldcontainabout236persons,ofwhom14wouldbeofschoolage,7attendingpublicschool.Onehundred(100)2-bedroomrentalhousinghomesinbuildingsofatleast50housingunitswouldcontainabout236persons,ofwhom10wouldbeofschoolage,7attendingpublicschools.
FromtheaboveandthemoredetaileddatacontainedinPartTwo,anumberofdemographic impactpatternsareevidentwith respect to thenumberofpeopleandschoolchildrenassociatedwithNewJerseyhousing.Ingeneral,detachedhousingcurrentlyproducesthehighestnumberofresidentsandpupilscomparedwithattachedhomes.Detachedhomeswithmore(4–5)bedroomshavetherelativelylargesthouseholdsizeandpupilgeneration.Additionally,commontypesandconfigurationsofattachedhousing,suchas2-to3-bedroomtownhousesand1-to2-bedroommultifamilyunits,havea relatively low demographic impact. It is sometimes erroneously assumed that eachhousingunit inNew Jerseycontainsaboutonepublic schoolchild.ThelatestACSdataindicatedthatisthecaseonlyforlarge(four-or-more-bedroom)single-familydetachedhomes.Housingtenurealsohasanimpact.
Itisfurtherimportanttorealizethatthepractical importofanygivennumberofpeopleandschoolchildrengeneratedbynewdevelopmentdependsonthespecificsandcontextofthehostlocalcommunityreceivingthisgrowth.Whiledevelopmentgenerating200to300persons,includingroughly25to50school-agechildren—theapproximatedemographicimpactsfromthe100-housingunitdevelopmentscenariosofdifferenttypesthatwereillustratedabove—wouldlikely have only minor incremental impact in a larger community and larger schooldistrict, theeffectwouldbemuchmoreconsequential ina smallermunicipalityandschoolsetting.Similarly,development-generatedpopulationwillbemoreconsequentialinacommunityexperiencinggrowththatislikelytocontinuetogaininsizeintothefutureversusamunicipalityandschooldistrictlosingpopulation,andwherethatdownwardtrendisexpectedtocontinueintothecomingyears.Wereturntothesevaryingcontextualsituationsthataffectthepracticalconsequenceofthepopulationgrowthintroducedbydevelopmentlaterinthisstudy.Fornowwefocusontheimportantbasicinformationprovidedbythedemographicmultipliers.
Further demographic information is providedby the current study.Besidesthetotalnumberofschool-ageandpublicschoolchildren,thereisunderstandableinterestintheirgradeorschoollevel,suchaselementary,juniorhigh or middle school, and high school. The current investigation provides the breakoutof the totalschool-age (SAC)andpublicschoolchildren (PSC)bythreeschoolcategories—elementary,middle,andhigh.TableI-10showsthis tripartite school distribution for SAC inNewerBuilt housing (built2000–2016)ofallhousingvalues.BesidesdifferencesinthetotalSACforthevarioushousingtypes,sizesandtenures,evidentfromTableI-10aswellarevariationsintheschool-leveldistributionofthemultipliers.Forinstance,
Much more attention needs to be paid to senior demographics
While school childrenunderstandably garner a lot of attentionwithrespecttodemographicmultipliers,nottobeignoredareotheragegroups.Thecurrentstudyshowsthehouseholdmembersbyeightagegroups.TableI-11summarizestheresultsfortwopolaroppositesoftheseagecohorts:pre-school(personsaged0–4)andsenior(personsatleast65years)fortheNewerHousing (built 2000–2016)ofAllHousingvalues.These age-cohort datawith respect to the demographic multipliers are of interest to demographers, planners, social workers, and others.
Take,forexample,theseniorpopulation(personsatleast65years)thatisexpectedtoexperienceconsiderablegrowthintothefutureas“BabyBoomers”age.Withthatseniorgrowthareincreasingsocial,health,andotherconcernsandneededaccommodations.NewJersey’sseniorpopulationisanticipatedtoincreaseby62percentfrom2010to2030,comparedwitha9.7percentoverall state population growth in this period and a very modest 3 percent growthfrom2010to2030forNewJersey’schildren.9Whileheretoforethemost interest concerning demographic multipliers has typically focused on SACandPSC,inlightofthepopulationtrendsjustcited,muchmoreattentionneedstobepaidtoseniordemographics.Theseniorandotheragecohortdatainthisdocumentcanhelpexpandtheagelensofthedemographicmultiplierstobeconsulted.
9. New Jersey Department of Labor andWorkforceDevelopment,“PopulationandLaborForceProjectionsforNew Jersey: 2010 to 2030.”
TAbLE I-16
New Jersey Population over Time (2010–2029): Total and Selected Age Groups
NEWJERSEYPOPULATION
OVERTIME,BYYEAR
(JULy 1 OF EACH yEAR) NEWJERSEYPOPULATION(IN000s)aBYAGEGROUP All Ages 0–4 5–9 10–14 15–19 5–19 65+
2.Standarderror (SE)10—ameasureofanestimate’svariability.Thegreatertheestimatedstandarderrorinrelationtothesizeoftheestimate(HS,SAC,orPSC),thelessreliabletheestimate.Approximately68percent of the time, the sample estimatewillbewithinoneSEofthetruepopulationvalue;about95percentofthetime,thesampleestimatewillbewithin2SEsofthepopulationvalue;andabout99percentofthetime,thesampleestimatewillbewithin3SEsofthepopulationvalue.
Related are the different statistics for the two age cohorts of housing for which multipliers are presented here. Since there are inherently more All [ages]Housingunits(NewerBuiltandolder)thanjustNewerBuilt(built2000-2016)housing,thesamplesizeavailablefromthePUMSisnoticeablylarger for the All [ages] Housing New Jersey demographic multipliers than fortheNewerBuiltunitsalone.(ComparethesamplesizesinTablesII-A-4throughII-A-6toTablesII-B-4throughII-B-6inPartTwo).Asnotedearlier,the total weighted sample for the All [ages] Housing cohort that is studied hereisabout3.1millionhousingunits(about155,000actualunitssampledinthe5PercentPUMS)ascomparedwithabout330,000weightedhousingunits(reflectingabout17,000actualunitssampledinthe5PercentPUMS)for theNewerBuilthousingcohort.Asa furtherexample, the5Percentweightedsampleformultifamilyrentalunitsofallbedroomconfigurations(0-3bedrooms)inbuildingsof5-49housing-unitsizeis36,883fortheNewerBuiltrentalhomesascomparedwith357,678fortheAll[ages]Housingrentalcohort.Forthemultifamilyrentalunitsofallbedroomconfigurations(0-3bedrooms)inlargerbuildings(50ormorehousingunits),the5Percentweightedsampleis34,997fortheNewerBuiltrentalhomesversus166,979forthesimilarlyspecifiedAll[ages]Housingrentalgroup.Inparallel,therearedifferencesbetweentheSEs,CIs,andEMPsbetweenthetwoagecohortsofNewJerseyhousingstudiedhere,withtheAll[ages]Housinggroup(bothNewerBuiltandolderhousingunits)typicallyhavinganadvantageinthisregard(e.g.,relativelylowerSEsandlowerEMPs).
This difference reflects an inherent conundrum in trying to specifyaccuratedemographicmultipliers,whetherHS,PSC,orSAC.Accuracyisenhancedbydevelopingmultipliersforveryspecifichousingsituations, such asmultifamilyhousingofacertaintype,size,tenure,andvalue,asopposedto multifamily housing in general. Or, we might want to target only Newer Builthousingunits,asthatgivesasnapshotofthemoreimmediate-resulthousehold and school children characteristics from newer development. Yet, the finer the grid of housing situation by type, size, tenure, and soon,thesmallertheinherentsamplesizeofeachindividualsituation.Thatdiminishing sample poses statistical challenges: Are there enough cases from whichtodevelopastatisticallyreliableestimate?Inthecurrentinvestigation,wehaveattemptedtobalancethegoalsofdevelopingafine-meshgridofvarying specific situations as opposed to overly generalizedmultipliers,whilesimultaneouslymaintainingacceptablestatisticalreliabilityforeachof the cells of demographic information that is presented.
What variables are associatedwith differences in the demographicprofile?Statisticalanalysisbythisstudy’sauthorsoftheresidentialmultiplierdata finds the following. In general, larger units (in terms of bedrooms)havestatisticallysignificantmorehouseholdmembersandschoolchildren(bothSACandPSC),andhousingtypesthattypicallyarelarger(intermsofbedrooms),suchassingle-familydetachedhomes,arestatisticallymorepopulation-intensive than theircounterparts typicallyconstructedwithasmallernumberofbedrooms,suchasmultifamilyunits.
AREA Total Population 5–19 Age Population Percentage Change in
Population, 2014–2029a
2014 2029a 2014 2029a Total, All Ages 5–19 (%) (%)
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
19
Whilehousingsizeand,relatedly,housingtypearetheprimarychar-acteristicsassociatedwiththestatisticallysignificantvariationinthenumberofpeopleandschoolchildrengeneratedbyagivenhousingunit,thereareother influences.There is a statistically significant relationshipbetweenhousing price and population intensity (HS, SAC, and PSC),with thepopulationyieldgenerallysomewhathigherinless-expensiveunitsofagivensizeandtypeandsomewhatlowerintheirmore-expensivecounterparts.Housing tenure, whether a unit is owned or rented, also is statistically associatedwiththedemographicprofile.Ingeneral,rentalhousingofallhousingtypesisrelativelymorepopulation-intensive(HS,SAC,andPSC)than the owned housing counterparts.
Thedetailedstatisticalanalysisrelatedtotheabovefindingsisavailablefromtheauthors.Inbrief,acommonlyappliedstatisticalapplication,OLS(ordinaryleastsquares)regression,wasappliedtoexaminewhatvariablesareassociatedwithstatisticallysignificantdifferencesinthedemographicprofile(HS,SAC,andPSC),controllingfortheothervariables(e.g.,examiningtheassociationofhousingtype;controllingforhousingsizeandtenure).That study revealed thathousing type,housing size, housing value, andhousingtenureareallassociatedwithstatisticallysignificantvariationindemographicprofile (HS,SAC,andPSC). In termsofexplanatorypowerofvariationindemographicprofile,thenumberofbedroomsisthemostpowerful,followedbybuildingtype,buildingvalue,andthenbyhousingtenure—butthereisnotmuchdifferenceinexplanatorypoweramongthelatterthreevariables.12
Itisimportanttodifferentiate,however,betweenastatisticallysignificantvariation and a difference of practical import. The former refers to a difference that statisticallywould not likely be due to chance; the latter is framedcontextuallyandmayvarybydifferingusers,applications,andcomponentsof the demographic data.
Forinstance,whilea2-bedroomunitmaygeneratestatisticallyhigherSACthananequivalent1-bedroomhomeofthesametype,orahousingunitofbelow-medianvaluemayyieldstatisticallyhigherHSthanthesamehomeofabove-medianvalue,thismaynothavemuchpracticalimportifthemagnitudeoftheproposednumberoflarger(bybedroom)housingunitsofbelow-medianvalueismodestinscale,and/orthishousingisproposedinalarger-populationcommunitywherethepopulationisprojectedtobestableorexperiencedecline.Additionally,wereiteratetheconceptualframeworkenunciatedinthisstudy’spreface:Demographicmultipliersshouldnotbeusedtoexcludehousingandsmartgrowth.Aproperlyfunctioninghousingmarket,andonerealizingtheMount Laurel vision of housing inclusion, are bestservedbycommunitiesencouragingdiversehousingwithrespecttohousingtypes,size,value,andtenure.
12.Tocomparetherelativeexplanatorypowerofdifferentvariables,theauthorsusedavariantofthestepwiseregres-sion. Specifically, each variable (or set of variables)wasexcludedfromtheregression,oneatatime,andcheckedbyhow much the adjusted R2declinedasaresult.ThevariablewhoseexclusionresultsinthelargestdropintheadjustedR2hasthebiggestexplanatoryvariable.
It is important to differentiate between a statistically significant variation and a
difference of practical import
Who Lives in neW Jersey housing?20
HOW TO USE THIS REPORT AND ILLUSTRATIONS
Thecurrentstudyprovidesinformationonthenumberandprofileofpersons of different categories of housing units in New Jersey. The analyst
should follow the following steps in using the detailed data provided in PartTwooftheinvestigation.
1. What demographic information is being sought with respect to time perspective?FordemographicsonNewerBuilthousing(unitsbuilt2000–2016),gototheII-Aseriesoftables;fordemographicsonAllHousinginNewJersey,bothnewerandolder,gototheII-Bseriesoftables.Asearliernoted, each of these housing age cohorts with respect to the demographic multipliershasadvantagesanddisadvantages;ultimately,bothagecohortsareinformative,andbothshouldbeconsulted.
2. Whatspecifictypeofdemographicmultiplierissought? This will vary,andTableI-2isagoodoverallguide.Forexample,fortotalpersonsandpersonsbyage,accessTablesII-A-1(NewerBuilthousing)andII-B-1(AllHousing); forschool-agechildrenbygradelevel,seeTablesII-A-2andII-B-2;andfordemographicstatistics,consultTables4through6inboththeII-AandII-Bseries.
3. For what type of housing is the demographic information being sought? Carefully consider themultiple specific characteristics of thehousingbeingexaminedbyhousingtype,housingsize,housingtenure,andhousingvalueaccordingtothematrixshowninTableI-3toslottheappropriatedemographicmultipliers to consult. From the1970s,whenRutgers–Blousteinresearchersfirststartedtoprovideplannersandotherswith residential demographicmultipliers, thesemultipliers have beendifferentiatedbyvariationsinhousingunittype,size(numberofbedrooms),tenure (ownor rent), value (e.g., above- or below-median), and othercharacteristics, so it is very important in considering the demographic multiplierstobespecificinexactlywhattypeofhousingisbeingconsidered.
Forexample,ifthevalueofthehousingbeingexaminedisunknown,thenusetheAllHousingValuedata;however,ifthehousingvalueisknown,then it isoptimal to slot to theappropriatebelow-median/above-mediancategories for the Newer Built housing or to the appropriate housing values bytercilefortheAllHousinggroup,asguidedbyTableI-3.Toillustrate,thestatewidemedian-pricedNewerBuilt(built2000–2016),3-bedroomNewJersey townhouse as of 2016, as derived from the 2012–2016 ACS, was valued at$283,000.Three-bedroomNewerBuilttownhousespricedbelow$283,000wouldbeinthe“below-median”category,whilethosepricedabove$283,000wouldbeinthe“above-median”category.Toreiterate,thesepricebreakpointshavenorelationshipto“affordable”orMount Laurel versusmarket-pricedhousing.ForNewerBuilt4-to5-bedroomNewJerseysingle-familydetachedhomes,themedianstatewidevalueasof2016is$506,000,understandablyhigher than themedian$283,000 for the3-bedroomNewerBuiltNewJerseytownhouse,becausethedetachedhomehasmorebedrooms;itlikelycomprisesahighersquarefootageand“consumes”moreland(becauseitisdetached)thanthe3-bedroomtownhouse.
Carefully consider the multiple specific characteristics of the housing being
examined by housing type, housing size, housing tenure, and housing value
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
21
To further illustrate, the statewidemedian-pricedNewerBuilt (built2000–2016)2-bedroomNewJerseyrentalmultifamilyunitinbuildingsofmid-range(5-49unit)sizeasof2016wasvaluedat$185,000.(Themonthlygross rentwas$1,681,and theunit value is estimatedat110 times the$1,681,or$185,000.)Suchunitsvaluedbelow$185,000($1,681monthlygrossrent)wouldbeinthe“below-median”category,whilethosepricedabove $185,000 ($1,861monthly gross rent)would be in the “above-median” value category.
As noted earlier, housing values for the All Housing units category in NewJersey(bothNewerBuiltandolderunits)areorganizedbyterciles.Toillustratethat,all(newerandolder)single-familydetached4-to5-bedroomhomesinNewJerseyasof2016hadafirst-tercilehousingvalueoflessthan$325,000,a second tercilevalueof$325,000 to$520,000,anda thirdtercilehousingvalueofgreaterthan$520,000.(Thefirst-tercilevaluecohortisnotsynonymouswitheither“affordablehousing”orMount Laurel-priced housing.)
Beingasspecificaspossibleinthevalueofthehousingbeingexamined,aswellasthishousing’sothercharacteristicsofhousingtype,size,andtenure,guidestheanalystintowhatmatchingdemographicmultipliersshouldbeconsulted.TablesI-2andI-3serveasausefulroadmap.Tofurtherwalkthereader through the use of the demographic multipliers, a simple illustrative examplefollows.
The first-tercile value cohort is not synonymous with either
“affordable housing” or Mount Laurel–priced housing
Who Lives in neW Jersey housing?22
Whatabout theagedistributionofall thepersonsgeneratedbythetownhouses versus thedetachedhomes? FromTable II-A-1 inPartTwo,theage-cohortinformationshowninTable1-12canbeassembled.Fromtheabovedata, theanalystcouldestimatethatof the231personsfromtheonehundred2-bedroomtownhouses,about22(231x0.094)wouldbefouryearsofageorunder,whileofthe378populationfromtheonehundreddetached4-to5-bedroomhomes,26persons(378x0.070)wouldfall into the youngest age cohort. The townhouses would proportionately containrelativelymorepersonsofseniorage—65yearsorolder—thantheirdetached counterparts. Of the 231 persons from one hundred townhomes, 15.4percent,13or36persons,wouldbeexpectedtobeatleast65yearsoldas contrasted with 6.6 percent,14or25persons(ofthetotal378persons),forthesingle-familydetachedhomes.
If theanalystwanted toquantify the90percentconfidence intervalfor thepublic school children from the example2-bedroom townhouseand the single-familydetached4-5bedroomhome, then fromTable II-A-6 the followingdatawouldbeascertained.Ninety (90)percentof thetime,theonehundred2-bedroomtownhouseswouldgeneratefrom17to28publicschoolchildren,whileninetimesoutof ten, theonehundred 4-to5-bedroomsingle-familydetachedhomeswouldgeneratefrom80to89publicschoolchildren.FromTableII-A-6theanalystwouldquantifythatthepublicschoolchildrenmultipliersforthesetwotypesofhousing(0.226forthetownhouseand0.848forthesingle-familydetached)arebasedonweightedsamplesof14,175and94,104respectively(recalltheyareweighted5percentsamples),havestandarderrorsof0.033and0.028respectively,andtheirerrormarginsasapercentageare,intandem,24and5.
DATA AND MODEL CHALLENGES; ONGOING AND FUTURE RESEARCH
As with all analyses, there are limitations as well as advantages to the current study.
The residential demographic profile is amoving target, andwhilethecurrentinvestigationusesthelatestavailable(2012–2016)AmericanCommunitySurvey(ACS)information,thatitself,inevitably,isbecomingdated.WhilethecensusandACSarethebestarms-lengthsourcesavailableto demographers, they have acknowledged shortcomings, such as likely underrepresentation of certain ethnic and racial populations.
13.Combines9.3percentand6.1percentforthe65–74and 75+ age cohorts, respectively, for the 2-bedroomtownhomes(seeTableII-A-1).
14. Combines 4.5 and 2.1 percent for 65–74 and 75+agecohorts,respectively,forthe4-bedroomsinglefamilydetachedhomes(seeTableII-A-1).
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
23
agesituations(newerunitsorall-age),whichhasthebenefitoftargetingthemultiplierstospecificcasesasopposedtooverlygrossgeneralization,facesthechallengeofsecuringsufficientsamplesizetoensurestatisticalrobustness.Relatedtothe“finegrid”challenge,whilewecanstatisticallypredictwith someconfidence the total numberof school ageorpublicschoolchildrenfromthedemographicmultipliers,thestatisticalabilitytopredicttheexactschool-group level(i.e.,elementary,middle,orhighschool)distributionofthesechildrenismorechallenging,andwecannotpredicttheschoolgenerationbyindividualgrade,saykindergartenversusthirdgrade.Thatcanbefrustratingtoschoolplannersbecausetheyspecificallyseektoknowtheimpactofproposedhousingdevelopmentbyspecificgradeandtoplan accordingly for physical space, teacher, and other educational needs.
Offurthernote,whilethecurrentinvestigationspecifiesmultipliersbyamultipledimensionalgridofhousingsituationsoftype,size,value,tenure,and age, it surely does not cover the full gamut of varying housing cases. Wedonotdifferentiatetheschoolchildrenmultipliersbythequalityofthelocal school district, while anecdotal evidence suggests that households withmorechildrenmaydisproportionatelyself-selectincommunitieswithhigh-qualityschoolsystems.Assuch,theschoolmultiplierswouldlikelybehigherinhigher-achievingschools.Wedonotdifferentiatemultipliersbywhether housing is in a transit-oriented community (TOD), andpastresearchbytheauthorsinNewJerseyindicatedalowerschoolchildrenyield from TOD units;15 the lower New Jersey TOD student generation maybelinkedtoTODhousingunitprice,bedroomcomposition,location,lifestyle,andotherfactors.OthershaveobservedthatTODhousingoftendisproportionately attracts households with relatively few children. One studycommentedthat“mostTODhasproducedhigher-endhousing,oftentargeted toempty-nestersand/oryoung,primarilychildlessprofessionalsas opposed to families.”16Anotherstudysimilarlyobserved that“RecentTODprojectshaveoftencateredmoretoyoungprofessionals,empty-nesteror other households without children….”17Wecannotseparatelyspecifymultipliersbyhigher-versuslower-achievingschooldistricts,orforTOD,becausetheACSdoesnothavedataonlocalschooldistrictqualityoronthe presence of a TOD.
Moreover,whilewecandifferentiatemultifamilyhousingbythesizeofthebuildingcontainingsuchhomes(2-to4-unit,5-49unit,and50ormoreunit),wecannotdifferentiatethemultifamilymultipliersbyheightofabuilding(intosaylow-rise,mid-rise,andhigh-rise)fromcensusandACSdatabecausethesesourcesdonothaveadescriptorfornumberofstoriesinastructure.Thatbuildingheightdescriptorwaslastcontainedinthe1980censusenumerationssowecannotcurrentlysegregatebuildingsbylow-,mid-,andhigh-risefromcensussources.Thisisanunfortunateshortcomingbecausepriorworkbytheauthorswhenbuildingheightdatawasavailable,as well as contemporary anecdotal information, strongly suggests that the demographic multipliers, and especially the school children yields, go down asbuildingheightincreases.Toascertainmultipliersbybuildingheight,acustomizedsurveywiththisheightdatawouldhavetobeconducted.
15.David Listokin and IoanVoicu,Who Lives in New Jersey Housing? New Jersey Demographic Multipliers(NewBrunswick,NJ:RutgersUniversity,CenterforUrbanPolicyResearch,2006).
17.TheCenterforTransit-OrientedDevelopment(CTOD)InPartnershipwiththeCenterforCities,“FamiliesandTransit-Oriented Development: Creating Complete Communities forAll.” http://citiesandschools.berkeley.edu/reports/tod205_familiesandTOD_2012.pdf.BoththeBierbaumetal.and CTOD citied studies strongly advocated for a menu of changestomakeTODsavailabletoamuchbroaderarrayofhouseholdstoincludefamilies,thelessaffluent,andotherscurrently not fully represented in TODs.
Contemporary anecdotal information strongly suggests that the
demographic multipliers, and especially the school children yields, go down
as building height increases
Who Lives in neW Jersey housing?24
An example of such a surveywas conducted by theDemographicSubcommitteeoftheLong-RangeEducationalFacilitiesPlanWorkGroup(AlexandriaWorkGroup)oftheAlexandria[Virginia]CityPublicSchools(ACPS).18TheAlexandriaWorkGroup cross-matched the address andhousing typeofeveryACPSstudent,examininga totalofabout75,000housingunits,toderivetheaveragenumberofstudentsperhousingunitofdifferentcategories.Athree-yearaverage(2010–2012schoolyears)ofstudentyieldswasexaminedinthisVirginiacommunityofabout160,000population.WereportbelowthestudentratiosdevelopedbytheAlexandriaWorkGroupforhousinginwhichheightofbuildingwasdifferentiated.
ACPS STUDENT RATIOS by HOUSING TyPE
Housing Total Total Student
Type Units Students Ratio
GARDENCONDOS 7,034 484 0.069
MID-RISECONDOS 5,396 489 0.091
HIGH-RISECONDOS 6,711 498 0.074
GARDENAPARTMENTS 10,857 3,253 0.300
MID-RISEAPARTMENTS 8,507 1,171 0.138
HIGH-RISEAPARTMENTS 10,811 913 0.084
Total: 49,316
Whilefortheapartments,presumablyrental,theACPSstudentratiosclearly decline as building height increases from the low-rise gardenapartments to themid-rise and high-rise apartments, for the owned(condominiumsor“condos”)multifamilyunits,thereisalessclearchangefromthegardencondosversusthemid-riseandhigh-risecondos.Furtherandimportantly,theremaybeacorrelationbetweentheheightofabuildingand theproportional shareof smaller (0- and1-bedroom) versus larger(2-and3-bedroom)individualhousingunits,withmid-riseandhigh-risebuildingshavingalargerproportionalshareofthesmallerindividualunits.Also,housingpricesperunitarelikelyhigherasbuildingheightincreasesbecauseofthetypeandcomplexityoftheconstructionandotherfactors(e.g.,needfordeeperfoundations,elevators,andmorespecializedlaborinahigh-rise).Inshort,thereisaconflationoffactorsthatmaycontributetotheACPSstudentmultiplierschangingasthevariableofbuildingheightisintroduced. As smart growth encourages higher density, with an increase of buildingmoremid-riseandhigh-risehousing,itbecomesyetmoreimportanttobetterunderstandhowbuildingheightmayinfluencethedemographicmultipliers.Asnoted,thebuildingheightvariableisunavailablefromtheACS,sospecialdedicatedsurveysthatincludebuildingheightwillneedtobeconducted.Justsuchaspecializedsurveyofschoolchildreninlow-
As smart growth encourages higher density, with an increase of
building more mid-rise and high-rise housing, it becomes important to better understand how building height may influence the demographic multipliers
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
25
rise,mid-rise,andhigh-risebuildingswasconductedinNewJerseybytheRutgersBusinessSchoolCenterforRealEstate,andweurgeourreadersto see theirwork (https://www.rutgersrealestate.com/publications/white-papers/school-age-children-study/#page=1).
WealsocannotspecifyfromtheACSthedemographiccharacteristicsof households in Mount Laurel affordablehousing,asubjectofconsiderableinterestinNewJersey.ItwouldbeadvantageousinNewJerseytosurveydirectly thehouseholdsizeandnumberofschoolchildreninoccupiedMount Laurelhousing.That surveycouldbeextended toother typesofaffordablehousinginNewJersey,suchasunitssubsidizedbylow-incomehousingtaxcredits(LIHTC).
Theoptimalwaytodothatwouldbetoconductasurveyoftheoccu-pantsofaffordablehousinginNewJersey.TheuniverseofsuchdevelopmentsisfoundbyNewJerseycounty,individualcommunity,individualhousingdevelopment,andtypeofsubsidy(e.g.,Mount Laurel orLIHTC)ataNewJerseyDepartmentofCommunityAffairs(DCA)databaseentitled“GuidetoAffordableHousinginNewJersey(RevisedApril01,2016)”(http://www.state.NJ.US/dca/divisions/codes/publicationalguide.html).The admittedlydifficultjobwouldthenbetosurveyastatisticallyvalidsampleofsuchaidedhousingtoderiveHS,SAC,andPSCforthesubsidizedhousingsector,mostprominently for Mount Laurel units. The previously cited Rutgers Business SchoolStudyofschoolchildreninNewJerseydidexamineactualschoolyields from Mount Laurelhousinginthisstate(https://www.rutgersrealestate.com/publications/white-papers/school-age-children-study/#page=1).
Whilethebestinformationonthedemographicsofsubsidedhousingis fromsurveyofsuchunits, it ispossible fromtheACStoexaminethedemographicsof low-andmoderate-income (LMI)households,definedhereashouseholdswithincomesthatdonotexceed80percentofareamedian income (AMI), adjusted forhousehold size. (It is80percentofAMI for four-personhouseholds. It is a sliding scale forhigher than80percentofAMIforlargerthanfour-personhouseholds,slidinglowerthan80percentforsmallerthanfour-personhouseholds.)TableI-13showstheHS,SAC,andPSCforLMIhouseholdsinNewJerseyasdefinedaboveinnewer (2000–2016)rentalhousingunits inbuildingsof5ormoresuchhomes.19Forinstance,itindicatesthatLMIhouseholdsinthe2-bedroomrentalunitsasdescribedabovecontained2.511persons,ofwhom0.439wereofschoolage,with0.408inpublicschool,whilethe3-bedroomrentalhomeoccupiedbyLMIhouseholdscontained3.591persons,with1.229SACand1.087PSC.Again,weemphasizethatthesearethedemographicsofLMIhouseholdsinnewerrentalhousing;whilethesehouseholdsmaybeeligiblefortargetedaffordablehousinginitiatives,suchasforMount Laurel orLIHTC,theLMI-eligiblehouseholdsmaynotbeamirroroftheultimateoccupantsofthesubsidizedhomes.Forthatweneedthededicatedsurveyofthesubsidizedhousingdescribedearlier.
To further our understanding of the occupants and demographics of subsidized housing,we report below on some investigations donenationally:
2.A 2017 study20 of the occupants of a sample of 38 LITHCde velopments in New Hampshire that was conducted for BCMPlanningLLCfortheNewHampshireHousingFinanceAuthority yielded the following information from a household surveyofgeneraloccupancy(non-age-restricted)LIHTCrentalunits:
Housing Household Average Pupils Unit Size Size Enrolled in School
1-bedroom 1.09 0.05
2-bedroom 2.19 0.51
3-bedroom 3.82 1.64
3.ThepreviouslydescribedAlexandria,VirginiaLong-RangeEdu-cationalFacilitiesPlanWorkGroupsurveyofstudentsbyhousingtype in this community found the following with respect to two categoriesofsubsidizedhousing;thesehousingunitswerenotdifferentiatedbyhousingsize(e.g.,numberofbedrooms):
Housing Type Total Units Students Student Ratio per Unit
From the admittedly sparse data presented above—from the LMIdemographics for New Jersey and from the Ohio, New Hampshire, and Virginiainvestigations—wecandrawsomeroughdemographicparametersforLMIhouseholdsandoccupantsofvarioustypesofaffordablehousing.A commonandunfortunatemisconception is that LMI households andoccupantsofsubsidizedhomeshaveexceedingly largehouseholdswithmanyschoolchildren.Theadmittedlysparsedataassembledheresaysthatperspectiveisanoversimplification.WhiletheLMIandsubsidizedoccupiedhomes may have relatively higher population densities with respect to
20.BCMPlanningLLC,“AffordableRentalHousingDevelop-ments:CharacteristicsofResidentsofNewHampshireLowIncomeHousingTaxCreditApartments.” Study conductedonbehalfoftheNewHampshireHousingFinanceAuthority,September2017.
A common and unfortunate misconception is that LMI households and occupants
of subsidized homes have exceedingly large households
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
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HS,SAC,andPSC thanhigher-incomeandmarket-pricedhousing—andeven that requiresmore statistical study—the specter of extremely highpopulationdensities in the affordablehousing sector is unsubstantiated,especiallywithrespecttothe1-bedroomand2-bedroomunits.Moreover,asindicatedrepeatedlyinthisstudy,socialequity,smartgrowth,andaproperlyfunctioninghousingmarketshouldencourageandwelcomeabroadvarietyof housing.
Ongoing statisticalwork by the authors regardingmultipliers alsobearsmentioning.The authors of the current investigation are currentlyengagedinextensiveadvancedstatisticalanalysistobetterunderstandthecomplexmultifacetedinfluencesofthedifferencesinthemultipliersandtheirchangesovertime.Thisworkisalsoexaminingdifferentgeographiesof the multipliers, such as demographics for New Jersey versus other states and within New Jersey, for statewide multipliers versus multipliers for more micro-scale locations, such as PublicUseMicrodataAreas, or PUMAs.(PUMAsareU.S.CensusBureau–definedgeographicunitsofatleast100,000peopleforthedisseminationofPUMSdata.)Alsobeingexaminedarethestatisticalinfluencesofprojecttype(e.g.,TOD),educationalquality,andschool proximity in the demographicmultipliers.Ongoing research bythisstudy’sauthorsalsoincludesanalysisofthedemographicmultipliersdifferentiatedbymultiplecategoriesofhouseholdincome21 as this income comparestotheareawidemedianincome(AMI)adjustedforhouseholdsize.Thehouseholdincomecategoriesstudiedare:extremelylow(<30%AMI),verylow(30%to50%AMI),low(50%to80%AMI),middleorworkforce(80%to140%AMI),andhigh(>140%AMI).Differenthouseholdincomesareassociatedwithvaryingdemographicmultipliers,andweexaminethatvariationcontrolling forothervariables, suchashousing type, size,andtenure. Our multifaceted statistical and other ongoing demographic research willbereleasedbyRutgers–Blousteininaseriesoftechnicalpapersinthefuture.
A final and important comment concerns themodel context of thecurrentstudyandhowthatmodel’sconceptualapproachcanbebroadenedin the future. This study provides residential demographic multipliers for New Jersey,whichasdescribedareusefulforascertainingthepopulationimpactof development. It is important to place the application of demographic multipliersinalargerconceptualmodelcontext.
Itisinstructivetoconceptualizeatri-focalmodellens(MACRO,MICRO,andMID-RANGE)intryingtodeterminetheimpactsofdevelopmentaddingpopulation, especially the effect on schools.
21. Both household income and housing value have, as expected,somecorrelation,withhigher-incomehouseholdstendingtoresideinhigher-valuedhomesandviceversa.Thus, in developing multipliers with a sensitivity to varying “affluence,” one would vary themultiplier by eitherhousehold income or housing value. There are arguments forbothapproaches.Specifyingmultipliersbyhouseholdaffluenceavoids the situationofhouseholds thatmaybehouse-richbutincomeless-advantaged(e.g.,someseniorhouseholds).Ontheotherhand,inexaminingaproposeddevelopment,informationmaybemorereadilyavailableonthevalueofthehousingproposed(sellingpriceorrent)asopposed to the income of the future residents.
To illustrate, let us consider a new housing unit proposed to sell for $200,000. The housing value in the instance is clear,buttheincomeofthepurchaserismurkierbecauseof differences in possible downpayments andmortgageterms, especially the former. Similarly, with a rental unit, the housingvalueisclearer(althoughthismayvarydependingonhousingoperatingexpenseratiosandcapitalizationrates)than the income of the occupants of the rental home. For example,sayahousingunitisexpectedtorentfor$2,000per month. The ACS indicates that in New Jersey in 2016 themedianmonthlygross rentwasaboutone-fifth (19.6percent) ofmedian household income. So on average(median),the$2,000grossmonthlyrentimpliesamonthlyhousehold incomeof about $10,000 ($2,000/.2), or anannualhousehold incomeofabout$120,000.But the .2rent-to-income ratio just described is amedian, and alandlordmayverywellacceptahigher30percentratio(orevenhigher35percent),inwhichcasethe$2,000apartmentcouldcontainahouseholdwithaboutan$80,000annualincome($2,000/.3=$6,667x12)—quitedifferentfromthe$120,000 renter household income earlier calculated. Yet, housingdevelopersandpropertyownersmaybeable toframe their target market with respect to the likely household incomesof theunits theysellor rent.So, therearebothadvantages and disadvantages in whether demographic multipliersarespecifiedbyeithertheoccupant’shouseholdincomeorthehousingunit’svalue.Weconsiderbothofthese approaches in our ongoing work.
Who Lives in neW Jersey housing?28
ThefirstframeworkisaMACROmodel,wheretheanalystconsidersthebroadchangesinpopulationandschoolchildrenovertimeandprojectedchangesinthesepopulationsintothefuture.TableI-14showsthatwhereasthe number of public school children inNew Jersey grew significantlybetween1990and2000,thatgrowthhassinceabatedinmorerecentyears,andisprojectedtodeclinesomeintothefuture(from2015to2027).
TableI-15setsthepublicschoolfuturetrends(2015–2017)inbroaderperspectivegeographicallyandbygradelevel.Whilethenumberofpublicschoolchildrenisprojectedtoincreaseatthenationallevelbetween2015and2027,thisvariestremendouslybyregionandstate—growingintheSouthandWestregionsoftheUnitedStatesanddecliningintheNortheastand Midwest portions of the country. New Jersey tracks the Northeast downwardprojectedtrendover2015–2027inschoolenrollment,andthetrendsinnearbystatesarenotedaswell(e.g.,severe2015–2027declineinConnecticut;lesssoinNewYork).Withrespecttopublicschoolenrollmentbygradelevel(pre-Kto8,versusgrades9–12):Broadlyspeaking,inallgeographicareas,thepre-Kto8enrollmentisprojectedtochangemoreinto the future (either increase or decrease depending on region/state)comparedwiththenumberofstudentsinuppergrades9-12.Forexample,inNewJersey,whereasthetotalpre-Ktograde12publicschoolenrollmentinthestateisprojectedtodecreaseby3.8percentover2015–2027,theenrollmentinpre-Kto8thgradesisprojectedtodeclinebyasomewhatlower3.4percentover2015–2027,whilethenumberofstudentsintheuppergrades9–12isprojectedtodeclinebyalarger4.7percentoverthesametimeperiod(TableI-15).
TablesI-16andI-17shifttomacropopulationchangesinNewJersey.Historically,New Jersey’soverallpopulationhasgrownover time (e.g.,from8,414,000in2000to8,792,000in2010,to9,006,000in2017),andisprojectedtogrowstatewideintothefuture(to9,531,000by2029).Thepopulationchange,however,variessignificantlybyagecohort.Themoreseniorpopulation(65yearsandolder)inNewJerseyisprojectedtoincreasesignificantly(e.g.,from1,314,000in2014to1,857,000by2029).Attheotherendof thespectrum, thepre-schoolpopulation (ages0–4) isalsoprojectedtogainsomeovertime(e.g.,from533,000in2014to573,000in2029).
Theschool-agepopulation,however,shownapproximatelyinTableI-16bytheage5–19cohort,isprojectedtodeclineovertimeinNewJersey(e.g.,from1,702,000in2014to1,686,000by2029).Withinthis5–19yearcohort(roughly“schoolage”),theyoungeragecohort(5–9years)isexpectedtogrowover2014 to2029,but this ismore thanoffsetbyaprojectednoticeabledeclineinpopulationinthe10–14and15–19agecohorts.ThisroughlycorrelatestotheprojectedchangeinpublicschoolenrollmentbygradelevelinNewJerseythatwasearlierobservedinTableI-14inthatthe projected decline in New Jersey school enrollment is anticipated to begreaterintheupper9–12gradesasopposedtothelowerpre-Kto8thgrades.
Updated New Jersey Demographic Multipliers
RutgeRs–Bloustein
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New Jersey’spopulationchange isnotuniform throughout the statebutvaries significantlybycounty.As is indicated inTable I-17,between2014 and2029, the state’s geographically inner-ring and somemiddle-ringcounties(e.g.,Bergen,Hudson,andMiddlesex)areprojectedtogrowsignificantlyinpopulation(bothallpersonsandtheschool-agepopulation-linked5–19agecohort)asopposedtomuchslowergrowthorevendeclineinouter-ringcounties.Forinstance,over2014–2029,thetotalpopulationisprojectedtodeclineinouter-ringHunterdonCountyby4.3percent,andthiscounty’sschool-agecohortofpersons5-19yearsisprojectedtodeclinebyayetgreater35.2percent.Incontrast,ininner-ringHudsonCounty,the2014–2029totalpopulationisprojectedtoincreaseby11.7percent,andthe5–19agecohortisanticipatedtogainbyayetgreater21.3percent.
TheaboveareallMACROpopulationforcesthatmayaffecthownewdevelopmentaddingpopulationandschoolchildreninpracticecontextuallyand differently affects the demand for added municipal and school services inNewJersey.ThesemacroforcesaresurelynotuniquetoNewJersey.Forexample, a2017 studyby theMassachusettsMetropolitanAreaPlanningCouncil(MAPC)observedthatMassachusettspublicschoolenrollmentpeakedin2002,hasdeclinedsincethen,andtheschool-agechildren(ages5-19)population inmetropolitanBostonwasprojected todeclineby8percentfrom2010–2040evenasthetotalpopulationwasprojectedtoincreaseby13 percent.22Giventhesemacropopulationforces,MAPCconcluded:“Atthedistrict level,weobservenomeaningful correlationbetweenhousingproductionratesandenrollmentgrowthoverasix-yearperiod....Itappearsthatbroaddemographictrends,parentalpreferences,andhousingavailabilitynow play a much larger role in enrollment growth and decline.”23WhileNew Jersey is surely not a mirror of Massachusetts or metropolitan Boston, theGardenStatedoessharesomeofthemacropopulationforcesthatMAPCobserved; accordingly,weneed tobetter thinkhowdevelopment addingpopulation affects actual school enrollment growth.
Beyondthemacroperspective,thesecondlensinourtri-focalmodelofhow development affects municipal and school services is a very different MICRO scale—what is happening in an individual community or individual school district.Amicro-scale approach characterized the previouslydescribedsurveyofschoolyieldsinAlexandria,Virginiabyhousingtype—astudyofabout75,000housingunitsinthecommunity.SomeNewJerseystudieshavesimilarlyfocusedatsuchadetailedlocallevel.Forexample,whentheWestWindsor-PlainboroSchoolDistrict(WWPSD)inNewJerseywanted to know how future development would affect enrollment in this highly rated two-community-servicing school system, it commissioneda2013studybyanotedschooldemographerwhoconsideredsuchdistrictandcommunity-specificmicrofactorsas:theactualschoolgeneration(numberofpupilsproduced)byeachindividualdevelopmentofdifferentcategories(single-familydetached,townhouses,andapartments)aswellasforbothmarket-rate and affordableMount Laurel housing in both communities(thesurveyencompassed8,936housingunitsinWestWindsorand9,500housingunitsinPlainsboro);howtheseschoolyieldsdifferedbylengthof
22.Tim Reardon and Sarah Philbrick, “TheWaningInfluenceonPublicSchoolEnrollmentinMassachusetts.”MAPCResearchBrief,October2017,MetropolitanAreaPlanningCouncil,p.1.
23.Ibid.,p.1.
We need to better think how development adding population affects
actual school enrollment growth
Who Lives in neW Jersey housing?30
housingoccupancy(e.g.,overtimetheschoolpupilgenerationinsingle-familydetachedhomesdeclinedashouseholdsagedinto“empty-nesters”);anticipated future development in each community bymagnitude andcategory(single-familydetached,townhouses,andapartments,andmarketrate/Mount Laurel);observeddetailedpasttrendsofenrollmentbyeachgradeintheWWPSD(yieldingindividualgradecohortsurvivalratios);andmuchmorecommunity-specificinformationcharacteristicofamicro-levelanalysis.24
The2013studyfoundthatnewerWest-Windsorsingle-familydetached(SFD)homesgenerated1.03to1.29studentsperunitandthatalltheSFDhomesinthiscommunity,newerandolder,hadanaverage0.73studentyield.(TheSFDyieldwentdownaslengthofSFDownershipincreaseddue to the “empty-nester” effect.) Similarly, newer SFDs in Plainsborogenerated1.05to1.31studentsperunitcomparedwithanoverallaverageof0.88perhomeforalloftheSFDsinthiscommunity,newerandolder.Combined newer and older condominiums and townhouses inWestWindsorgenerated0.50studentsperunit,almostidenticaltothe0.49yieldforthesetypehomesinPlainsboro.The2013studyalsocalculatedstudentsgeneratedinrentalapartmentsinbothWestWindsorandPlainsboro.
Anearlier2007study25intheWestWindsor–PlainsboroSchoolDistrict(WWPSD)surveyed10,120housingunitsinWestWindsorandPlainsboro(4,154 condominiums and townhouses, and5,966 apartments). Basedon that survey and other research, it offered amatrix of demographicmultipliersforrentalapartmentsandownedmultifamilyunits(combinedcondominiumsandtownhouses),bothmarket-rateandaffordable,intheWWPSD.Themultipliersvariedbyhousingtype,presenceorabsenceofaffordablehousing,andwhetherornotthehousingwas“child-friendly.”Thelatterconditionwascharacterizedbynumerousfactors,includingbothlocation(housingwithinwalkingdistancetoelementaryschoolandwhetherlocatedeastorwestofU.S.Route1,amajorarterialinthearea)andhousingdevelopmentamenities(playgrounds,swimmingpools,andtenniscourts).For example, the student generation permarket-priced condominium/townhouseunitwassuggestedat0.5inachild-friendlydevelopmentversus0.3forsuchhousingthatwasnotsochild-supportive.Forrentalapartmentswithaffordablehousing,thesuggestedyieldwas0.5(child-friendly)and0.3(notchild-friendly).Formarket-raterentalapartments,thesuggestedstudent yield was 0.2, and no differentiation was made for the presence or
Thedetailed local focus is the raisond’êtreof themicroapproach.Increasingly,“bigdata”studiesoftheactualstudentyieldofallormanyofthehousingunitsinagivencommunityarebeingconducted(e.g.,4,132housingunitsstudiedinBernardsTownship,NewJerseyand1,408housingunitsexaminedinHaddonfield,NewJersey).26Amicro-focusedanalysis,suchasthestudiescitedabove,withlocalsurveyofthousandsifnottensof thousands of the occupied housing units in a given community with respect to school children generation, enhances our knowledge of how newdevelopmentimpactsaspecificjurisdiction.Thespecificjurisdictiondynamic is important because even after controlling for housing type,size,value, tenure,andothercharacteristics,differentcommunitiesmayverywell experience different population outcomes fromdevelopment.Thesamepriceandsizehousingunit,whetherownedorrental,mayverylikelyhaveadifferenthouseholdsizeandschool-childrengenerationin,say, a “Manhattan-oriented” housing development in JerseyCity versusdevelopmentinthenewersuburbsofWestWindsorandPlainsboro.Insightsintosuchidiosyncraticdemographicdifferencesbycommunityandhousingmarketareaffordedbythemicro-focusedapproach.
Thefinallensinourtri-focalmodelwetermMID-RANGE.Itdoesnotlookasbroadlyorlong-termastheMACRO,nordoesithavethemicroscopicindividual community focus of the MICRO model. Instead, it consists of the observedcharacteristicsofhousinginaregionorstatewithrespecttothetotalnumberofpersonsinahousingunitandtheprofileofthatpopulation,suchasschool-ageandpublicschoolchildren.Thesearedemographicmultipliers,and characterizing thisMID-RANGEdevelopment-impact perspective isquantificationofthepopulationeffectsofdevelopmentbyarticulatingcurrentandaccuratedemographicmultipliers.ThisdemographicmultiplierMID-RANGEmodelcontexthasbeentheframeworkforthecurrentstudy.Whilethedemographicmultiplierframeworkisusefulandhasbeenlongusedintheplanningprofession,weshouldnotforgetthatitisjust“onelens”inthetri-focalmodelframework.Demographers,planners,andothers,includingthecurrentstudy’sauthors,needinthefuturetobetterholisticallyintegratethe“three-lens”approachinconsideringtheimpactsofdevelopment.
Demographers, planners, and others need to better holistically integrate the “three-lens” approach in considering
the impacts of development
26.RichardGrip, “Demographic Study for theBernardsTownshipSchoolDistrict,”December2017;andRichardGrip, “Demographic Study for theHaddonfield PublicSchools,”June2014.
†InafewisolatedcasesinTableII-A-5andTableII-A-6,standarderrorandotherstatisticaldataarenotpresented.Weusedthereplicateweightstoconstructthestandarderrors.Forthezero-countcells,theformulahasazerointhedenominatorofafraction,hence the missing values.
34
TABLE II-A-1. STATEWIDE NEW JERSEY
TOTAL PERSONS AND PERSONS BY AGE (Newer housing units built 2000-2016, from 2012-2016 ACS)