HomeMy WebLinkAboutAgenda - 04-21-1998 - 10bORANGE COUNTY
BOARD OF COMMISSIONERS
ACTION AGENDA ITEM ABSTRACT
Meeting Date: April 21, 1998
Action Agenda
Item
SUBJECT: APARTMENT ASSOCIATION OF NORTH CAROLINA -- IMPACT FEES FOR MULTI-
FAMILY DEVELOPMENT PROPERTIES
DEPARTMENT: COUNTY MANAGER PUBLIC HEARING: Yes —x—No
BUDGET AMENDMENT REQUIRED: Yes _x No
ATTACHMENT(S):
- 2/19/98 Letter to Commissioner Halkiotis
- 1/23/98 Letter to County Manager
- 5 -19 -97 Letter to Marvin Collins plus attachments
- May 1997 Report of Dr. Emil Malizia (UNC - Chapel
Hill - Dept. of City & Regional Planning)
INFORMATION CONTACT: County Manager
County Attorney
TELEPHONE NUMBERS:
Hillsborough - 732 -8181
Durham -688-7331
Mebane -227-2031
Chapel Hill -967-9251
PURPOSE: To receive a report from the Apartment Association of North Carolina that recommends
lower school impact fees for apartment units.
BACKGROUND: On June 7, 1993, Orange County adopted an ordinance establishing a system of impact
fees to be used to finance a portion of the cost of public school space needed because of
new residential growth. The ordinance became effective July 1, 1993 and impact fees
have been collected in the Orange County Schools District and Chapel Hill - Carrboro City
Schools District since that time. Fees collected in each school district are placed in a trust
fund for the purpose of funding new public school space in that district. The current
impact fee for the Orange County Schools District is $750.00 and $3,000.00 for the
Chapel Hill - Carrboro City Schools District.
The basis for the impact fee structure is documented in Technical Report - Calculation of
Proportionate Share Impact Fees for Financing Public School Capital Needs, commonly
referred to as the Technical Report. The Technical Report was first revised in May, 1995
to include new cost data for school construction. It was revised again in May, 1996 to
2
include updated cost information, the recommendations of the School Facility
Construction Standards Work Group, and the findings of a graduate student study of
student generation rates in new housing built between 1992 and 1994. The 1996 update
of the Technical Report concluded that the maximum amounts that can reasonably be
charged on impact fees are $3,404 for the Orange County Schools District and $11,593
for the Chapel Hill - Carrboro City Schools District.
The Apartment Association of North Carolina has requested lower impact fees for
apartment units based on a report prepared for them by Professor Emil Malizia of the
UNC Department of City and Regional Planning. The report concludes that apartments
generate fewer students per unit than traditional single - family dwellings. While
interesting, the report may not have applicability to Orange County since it is based on
statewide, rather than Orange county- specific data. Previous work on the subject
performed by Orange County showed no relationship between housing size and number
of students.
The original Technical Report as well as updates to it were prepared by retired Planning
Director, Marvin Collins. Plans for a new update are imminent and the UNC Department
of City and Regional Planning has been contacted regarding preparation of a 1998
Technical Report update.
The County Attorney's view is that an analysis of student generation rates by housing
type in Orange County, considering separately single family housing and multi - family
housing, can be undertaken to determine whether Orange county data supports a different
impact fee for the two housing types. Such an analysis was done for Chatham County
housing. The data resulted in a supportable school impact fee of $3,529 for new single
family housing unit and $1,164 for a new multi- family housing unit. The researcher
reached the following conclusion: "Multifamily fees are significantly lower than single
family and mobile home fees due to the relatively low number of students per
multifamily household in Chatham County." (Emphasis added.)
Orange County's impact fee presently includes all student generation data per household.
A reduction in the fee for multifamily housing will necessarily result in an increase in the
fee for single family housing. A lower justified impact fee for multifamily housing could
also tend to make the impact fee less regressive.
RECOMMENDATION: The Administration recommends that the Board receive the report from the
Apartment Association of North Carolina, but defer any response until such time
as the update to the Technical Report is completed.
3
Estates, Inc.
.1al Estate Development Corporation
February 19, 1998
Orange County Board of Commissioners
Steven Halkiotis, Vice Chair
1007 Panther Court
Hillsborough, N.C. 27278
Dear Vice Chair Halkiotis,
Estates, Inc. anticipates beginning construction of 240 apartments in Orange County this spring. When
we began the planning process in 1995, for our project, county impact fees were S750.00 per unit. This
fee was a blanket assessment that applied to single family dwellings and apartments. Since that time the
fee has quadrupled to $3,000.
Those of us that develop multi - family properties believe that an equal assessment of impact fees is unjust
and punitive. We want to pay our fair share of costs. We know that new development impacts the cost of
providing services hence impact fees. Proportionality, is a concept whereby the impact of costs to a
governing body (such as Orange County) can be quantified to allocate true impact and recognizes that
multi- family differs from single family. This is not an exact science but evidence indicates that the
impact of single family to multi- family is about 3 to 1. Dr. Emil Malizia of the Department of City and
Regional Planning, UNC at Chapel Hill, has done a great deal of work in this area Our contention that
multi- family is being assessed disproportionately appears to be supported by his analysis.
On February 10,1 met with Mr. Link along with several of my colleagues in multi- family development
and Mr. Ken Szymanski, Executive Director of the Apartment Association of North Carolina to make our
case that we felt impact fees in Orange County were disproportionately being applied It is my hope that
this issue will be discussed at the Commissioner's meeting, March 17th.
We are in a consensus that this issue need revisiting. As stated, we want to pay our fair share. We appeal
to your sense of fairness. Thank you for your consideration.
Sincerely,
W144,*�
Ned Pendarvis
1401 Main Street
P.O. Box 1 1739
olumbia, South Carolina 29211
803.765.93 18
FAX 803.765.9427
AANC
M
Apartment Association of North Carolina
Representing the Multi - Family Housing Industry in North Carolina
January 23, 1998
Mr. John Link
Orange County Manager
P.O. Box 8181
Hillsborough, NC 27278
Re: Orange County School Impact Fees
Dear Mr. Link
PS/ �J "09- V
Our Association continues to have a keen interest in having a conversation with yourself, Orange
County Attorney Jeff Gledhill, and the Orange County Board of County Commissioners on the
subject of the calculation of Orange County school impact fees. We contend that the imposition of
these fees on multi-family rental housing, which is a readily identifiable class of properties that by
its very nature houses fewer children than single - family housing and thus has demonstrably less of
an impact on educational facility costs, is inequitably high and very possibly illegal. Please see the
attached letter written to Mr. Gledhill on September 30, 1997.
The North Carolina Court of Appeals, in a 1989 case, adopted the "rational nexus" test requiring
exactions to be properly and fairly related to the need for new public facilities generated by a new
development. In our view, apartment developers have, since 1993, paid and are continuing to pay
school impact fees in your county which are substantially beyond that portion of the cost which is
reasonably attributable to the needs created by new apartment construction.
Our Association commissioned an independent University of North Carolina study on this subject
last year. We have shared all of the findings with Mr. Gledhill, and Mr. Collins and Mr. Bell of the
Planning Department. UNC's Dr. Emil Malizia wrote, "Charging impact fees on apartment units at
half the fee charged to single - family or less would be more consistent with the actual impacts on
public schools. Furthermore, the impact fee would be far less regressive as a result ". We note that
the consultant for neighboring Chatham County states that the maximum supportable impact fees
per housing unit are $3,529 for single - family and $1,164 for multi- family.
Units of government have a duty to achieve the highest possible level of equity in attempting to
recover actual costs, or in forecasting future cost recovery. I will phone you next week for your
reaction to this letter and for your advice on how to best proceed. Thank you.
Sincerely,
Kenneth N. Szymanski, AICP
Executive Director
cc Mr. Jeff Gledhill
711 Fast Morehead St. • Suite 201 • Charlotte, North Carolina 28202.7043349511 • FAX 704 - 333 -4221
5
AANC , -
Apartment Association of North Carolina
Representing the Multi- Family Housing Industry in North Carolina
May 19, 1997
Mr. Marvin Collins, AICP
Orange County Planning Director
306 F Revere Road
Hillsborough, NC 27278
Dear Mr. Collins:
Thank you for visiting with me recently on the subject of the history and evolution of Orange
County school impact fees. As you will recall, I left with you two copies of the recent report,
"The Impacts of Recent Residential Development on Public Schools in North Carolina Urban
Areas: Single - Family Housing Compared to Apartments ", prepared by Dr. Emil Malizia of the
University of North Carolina. Further, you inquired whether this data might be available solely
for the Raleigh - Durham- Chapel Hill area, with an eye toward implementing the results in setting
Orange County impact fees.
Dr. Malizia has responded to this request with the attached memo dated May 14, 1997. While
he does not wish to analyze any geographic subset from our dataset, he states that data from
the PUMS (Public Use Microdata Sample) can be used for specific urban areas. He suggests
comparing "Single Family Detached" in Raleigh - Durham to "Apt (units >50)" in Raleigh-
Durham. The data analysis (enclosed) indicates that, on average, 0.50 persons aged 5 through
17 reside in the "Single Family Detached "; while, on average, 0.02 persons aged 5 through 17
reside in the "Apt (units >50) ". This ratio is 25 to 1!
The Chatham County report (referenced by Dr. Malizia) states that the maximum supportable
impact fees per housing unit are $3,529 for single family and $1,164 for multifamily (a ratio of
slightly more than 3 to 1).
Mr. Collins, our Association has a strong conviction that units of government in fact have a duty
to achieve the highest possible level of equity in attempting to recover actual costs, or in
forecasting future cost recovery. While the allocation of these costs is an inexact science, and
there will always be questions about equity, clearly greater equity is achieved by establishing
differential fee amounts for single- family and multi- family residential types than by
maintaining a flat, uniform fee. Dr. Malizia's independent research suggests that these two
housing types generate, on average, substantially differential impacts on public schools.
Tailoring the fees beyond the averages, based on the specific bedroom mix of proposed housing
developments, can bring about even finer resolution of fairness, because of the observed
variation of generation rates by bedroom size (for both single- family and multi-family).
711 East Morehead St. • Suite 201 • Charlotte, North Carolina 28202.7043349511 • FAX 704333 -4221
6
Letter to Mr. Marvin Collins tifay 19, 1997 p.2.
You had alluded to an upcoming staff report/ recommendation to the Orange County Board of
County Commissioners on this subject. It is our sincere rope that Dr. Malizia's new research
can soon be translated into equitably structured impact fees in Orange County. We are very
concerned about the disproportionate effects that Orange County impact fees have on multi-
family housing costs. In other states, litigation has brought about the calculation and
assessment of differential rates by housing type. By their very definition, impact fees charged
must not exceed a proportionate share of the cost incurred or to be incurred in accommodating
the development paying the fee.
If our Association can assist your work in any way, please contact me. Thank you very much.
Sincerely,
Kenneth N. Szymanski, AICP
Executive Director
Attachment
cc: Apartment Association of North Carolina Board of Directors
Dr. Emil Malizia
DEPARTMENT OF CITY AND REGIONAL PLANNING
University of Notch Carolina at Chapel Hill
MEMORANDUM
TO: Ken Szymanski
FROM: Emil Malizia
DATE: May 14, 1997
SUBJECT: NC Urban Area Data on School Age Children by Housing Type
I. Orange County Survey Data
I have checked the dataset. Only 96 records (Z 1. 1% of the sample) were drawn in the
Research Triangle Area. Furthermore, only 13 surveys were Orange County households.
I will send a copy of the entire dataset with the Carolina Planning article as soon as the final
version is typed. You can use the data in any way you wish.
I do not want to analyze any geographic subset of the data since the survey was not designed
to provide accurate area - specific statistics.
II. PUMS Data
On the other hand, the PUMS data can be used for specific urban areas. They are generally
consistent with our survey results. The Carolina Planning article will contain an exhibit with
PUMS data that are comparable to our survey data. It gives statistics for apartments and
singiafantily households with 4 bedrooms or more.
I have enclosed the table we compiled with PUMS data that shows households that send their
children to public schools. You can compare "S.F. Detached" in Raleigh- Durham to "Apt
(uniu >50) in Raleigh - Durham. Single - family households clearly generate more persons and
many more public school - attending children.
I have also enclosed p.3 from the report Tiisebler did for Chatham County. The generation
rates for - Single Family" and "Multi- family" are PUMS data for Orange County amd
Chatham County. Marvin Collins can get the entire report, dated September 30, 1996, from
Keith Meggiason, Chatham County planning director (919 -542- 8204).
M
M. Conclusions
These PUMS data indicate that singlo-family households generate significantly greater
impacts on public schools, at all levels, compered to multi- family households. Charging
impact fees on apartment units at half the fee charged to single - family bouses Qr few would
be more consistent with the actual impacts on public schools. Furthermore, the impact fee
would be far less regressive as a result. For example, a fee of $3.000 on a house priced at
$240,040 is 1.25% of the price; the same fee on an apartment costing $60,000 is 5.00/9.
Dropping the impact fee to S1,500 still generates a burden on the apartment of 2.5%.
• Type
l
Val
(
S+ocal
0 -4
3 -l0K
1 14 -17
lt•
9
.0tal
Ashevtlle
2.39
0.16
0.18
0.09
0.23
1.65
Burlington
2.46
0.15
0.19
0.10
0.17
1.90
Charlotte
2.56
0.19
�• 0.21
0.10
0.14
1.92
Fayetteville
2.75
0.:7
0.:9
0.12
0.13
1.93
Crown abcro -ice -HP
2.47
0.17
0.20
0.09
0.13
1.99
Hickory - Morganton
2.56
0.17
0.20
0.10
0.15
1.94
Jacksonville
2.83
0.34
0.30
0.11
0.14
1.93
Raleigh- Ourhaf
2.42
0.17
0.19
0.09
0.11
1.86
)illmingtoa
2.42
0.15
0.19
0.10
0112
1.88
Mobile Howes
Asheville
2.59
0.31
0.2S
0.09
0.13
1.90
Burlington
2.53
0.24
0.20
0.10
0.14
1.95
Charlotte
2.59
0.26
0.24
0.10
0.14
1.95
Fayetterille
2.60
0.35
0.24
0.10
0.09
1.91
Greensboro-r6-Ha
2.52
0.24
0.23
0.10
0.13
1.61
Hickory- Morganton
2.56
0.26
0.26
0.10
0.12
1.92
Jacksonville
2.66
0.36
0.25
0.08
0.11
1.66
Raleigh- Ournam
2.68
0.24
0.24
0.09
0.11
1.80
Wilmington
2.40
0.21
0.26
0.07
0.33
1.73
C.F. (D /A)
Asheville
2.49
0.13
0.17
0.10
0.12
1.97
Burlington
2.55
0.13
0.20
0.11
0.13
1.97
Charlotte
2.71
0.18
0.22
0.11
0.16
2.04
Fayetteville
2.97
0.23
0.29
0.14
0.19
2.02
Gretnsboro-WS-HP
2.61
0.16
0.21
0.10
0.14
2.00
Hickory- Morganton
2.65
0.15
0.19
0.11
0.17
2.04
Jacksonville
2.99
0.3S
0.34
0.14
0.16
2.00
Raleigh - Durham
2.65
0.19
0.22
0.11
0.14
2.00
Wilmington
2.60
0.14
0.10
0.12
0.14
2.01
3.1'. Detached
Asheville
2.50
0.13
0.10
0.10
0.12
1.90
Burlington
2.53
0.14
0.20
0.11
0.13
1.99
Charlotte
2.73
0.19
0.22
0.11
0.16
2.05
Fayetteville
2.87
0.22
0.20
0.14
0.19
2.04
Greensboro- 143 -HP
2.64
0.16
0.21
0.11
O.IS
2.02
Hickory- Morganton
2.66
0.15
0.19
0.11
0.17
2.05
Jackaonville
2.96
0.20
0.34
OAS
0.18
2.01
Raleigh- Durham
2.70
0.18
0.21
0.12
0.15
2.03
Wilmington
2.62
0.14
0.18
0.12
0.14
2.03
S.F. Attached
Asheville
1.88
0.10
0.07
0.05
0.03
1.64
Burlington
2.24
0.06
0.21
0.07
0.04
1.06
Charlotte
2.20
0.12
OAS
0.07
0.12
1.74
Fayetteville
2.99
0.44
0.43
0.14
0.16
1.02
Greensboro -NS -HP
1.92
0.10
0.11
0.04
0.04
1.63
Hickory- Morganton
2.34
0.10
0.24
0.11
0.21
1.67
Jscks00+111&
3.11
0.73
0.34
0.06
0.03
1.96
Raleigh- Ducham
2.09
0.13
0.11
0.05
0.07
1.71
Wilmington
2.24
0.22
0.18
0.10
0.11
1.62
Apt. tall units)
AMovillo
1.82
0.16
0.12
0.06
0.07
1.41
Burlington
1.94
0.10
0.17
0.03
0.04
1.S2
Charlotte
2.02
0.10
0.15
0.06
O.OB
1.54
Fayetteville
2.36
0.34
0.29
0.06
0.06
1.62
Gr..nsbere -WS -61P
1.90
0.16
0.13
0.06
0.04
1.46
Hickory- Mocgsntoa
1.96
0.19
0.17
0.06
0.08
1.47
Jacksonville
2.18
0.30
0.17
0.05
0.03
1.63
Raleigh - Durham
1.91
0.13
0.12
0.05
0.06
1.56
Wtledngton
1.97'
0.17
0.13
0.05
0.04
1.50
Apt. WaitacS07
Ambeville
1.99
0.17
0.14
0.07
0.08
1.43
Sur11m9ton
1."
0.10
0.17
0.03
0.04
1.53
Charlotte
2.05
0.19
0.26
0.06
0.09
2.3s
reyettevllle
7.36
0.34
0.29
0.07
0.06
1.63.
Greensboro-w-H!
1.91
0.17
0.14
0.06
0.00
1.47
elokory- Moc9antoe
1.90
0.19
0.17
0.06
0.09
1.47
Jackawavlllt
2.17
0.29
0.17
O.OS
0.03
1.62
malelga -Derive
1.94
0.14
0.13
6.0s
0.06
1.61
Milalagton
1.99
0.14
0.14
0.05
0.07
1.59
Apt. funitG >50)
IAsl.evllte
1.24
O.OS
0.01.1
0.00
0.00
1.20
$'rliflgton
1 71
0.00
0.00
0.00
0.00
1.21
1 O
charlotte
1.34
0.04
0.02
0.00
0.01
1.27
Fayetteville
1.00
0.00
0.00
0.00
0.00
1.00
Greensboro -MS-Hp
1.15
0.02
0.02
0.00
0.01
1.14
Hickory- MOryanton
1.45
0.00
0.30
0.00
0.00
1.15
Jacksonville
3.11
1.11
0.00
0.00
0.00
2.00
Aalelah- Durham
1.23
0.01
0.00
0.01
0.01
1.21
MSlmingLOn
1.46
0.00
0.00
0.00
0.00
1.46
Othar
Aehev111e
1.42
0.11
0.00
0.00
0.00
1.31
aurlington
1.62
0.00
0.00
0.17
0.15
1.30 '
Charlotte
1.25
0.)0
0.14
0.12
0.10
1.79
rayettoville
3.72
0.69
0.36
0.12
0.24
1.81
Greensboro -W-HP
2.46
0.20
0.25
0.09
0.12
1.80
Hickory - Morganton
2.22
0.09
0.04
0.00
0.11
1.89
.Tackvo vllle
3.06
0.14
0.31
0.20
0.43
1.97
Halvigh- Duchar
2.21
0.16
0.08
0.06
0.11
1.79
V411rington
22.14
0.06
O.TO
0.10
0.12
1.75
4
0
Table 1 below summarizes the restilii,ig maxinruut supporutble• iutpacr fces by type cif' housing
unit. These fees total $3,529 for new single family housing units, $1,104 fi_,r new 12:u!!ilj:tZily
units, and $3,714 for new mobile hornc�, Multifaitiily fees are signifiicanily lower than singtc
fartuly and mobile home fees due to the relatively low nuiliber of students per multifamily
household in Chatham County. Impact fees for mobile hot ics ure higher than single fans ly
impact fees because of a greater property tax credit off -sct for single family homes. (Single
family homes are more expensive than mobile homes and therefore receive more credit in the
forni of future property tax payments used to pay off school debt service.) The impact fees
ultimately adopted by the elected officials could be less than the ttiaxirnum justifisable and /or they
could be phased.
Table 1: Public School impact Fees
Public School Students Per Household
Single Family (SF)
Multifamily (MF)
Mobile Home & Other (MN)
Level Of Service
Nigh
Building Sq_ Ft. Ptr Student
K • 9
Net Local Capital Cost Per Sq. H.
Grades
Portable Classrooms per 100 students
Cost Per Portable Classroom
Maximum Gross Impact Fee Per /lousing Unit Ref
ore Credits
0.28
Single Family
0.40
Multifamily
0.04
Mobile Home & Other
0.29
Less Property Tax Credits
0.37
Single Fancily
5902
Multifamily
$ 178
Mobile Home do Othtr
S195
Less Sales Tar Credits
0.00
Single Family
$932
Multifamily
5704
Mobile Home & Other
5944
Marimum Cross Ito act Fee per Homing Unit
ISingle Family $3,5n.
Muhifamtly $1.164
MOW)c Home A Other S3,7141
Elcmcntary/Mid4tc
Nigh
All
K • 9
9 -12
Grades
Standards:
0.28
0.11
0.40
0.11
0.04
0.15
0.29
0.09
0.37
113
163
$102.19
5107.19
0.39
0.00
$30.000
$30,000
$3,313
$1,945
$5,263
SI,270
$776
52,046
$3,339
$1,513
$4,9.53
11
Page 3 Tischler g ASSOCialeS, MC
• 12
The Impacts of Recent Residential Development on Public Schools in North
Carolina Urban Areas: Single - Family Housing Compared to Apartments
prepared by:
Dr. Emil E. Malizia
Department of City and Regional Planning
The University of North Carolina
at Chapel Hill
May, 1997
13
May 1, 1997
Prepared by: Emil E. Malizia
AANC Report:
The Impacts of Recent Residential Development on-Public
Schools in North Carolina Urban Areas: Single - Family Housing
Compared to Apartments
Background
In May 1996, the Principal Investigator (PI) completed a
survey of the academic literature and trade publications
pertaining to development impact fees for the Apartment
Association of North Carolina (AANC). The specific concern
was to identify empirical estimates of development impacts
by housing type -- apartments compared to single - family
residences. The review supported the idea that apartments
generally have lesser impacts compared to single - family
housing primarily because the former have fewer persons per
household and fewer children per household.
Survey Work
In September 1996, the PI agreed to conduct a random sample
survey of housing units in the five urban areas of North
Carolina — Asheville, Charlotte, Piedmont Triad (Greensboro
and Winston - Salem), Research Triangle (Raleigh, Durham, Cary
and Chapel Hill), and Wilmington. The survey was designed to
estimate the differences between the household
characteristics of apartment dwellers compared to the
occupants of single- family housing. The sample size was
supposed to be large enough to generalize the results to all
metropolitan areas of North Carolina.
The survey was specifically intended to determine the number
of children being sent to public schools by households
living in recently built apartments and single - family
dwellings. The questions pertained to household size;
number, age and grade level of children; public, private or
home schooling; tenure of the household in the dwelling,
county, urban area or state; and housing size, value and
age. Exhibit 1 is the survey questionnaire.
In October 1996, staff at the Center for Urban and Regional
Studies conducted a telephone survey of 630 households in
the five North Carolina urban area's in order to generate the
14
information needed to test for statistically significant
differences between occupant characteristics of recently
constructed apartments and single - family housing. The
minimum sample size was determined by reviewing previous
apartment surveys. The amount of variation in household
size and in number of children were used to estimate sample
size. The PI determined that a sample of 150. apartment
units and 150 houses would be sufficient to generate
statistically significant difference -of -means tests for
North Carolina urban areas.
The goal of having results that could be generalized to
North Carolina urban areas ideally required a listing of all
recent construction in all metropolitan counties. Of
course, this ideal sample frame does not exist. Instead,
expert sources were used to identify recent apartment
complexes and subdivision locations in the five North
Carolina metropolitan areas surveyed. AANC identified 19
apartment complexes constructed since 1990 in these areas.
Local planners, economic developers and real estate brokers
were contacted for information on recent residential
subdivisions and on additional apartment complexes. This
process essentially randomized the selection of street
locations in each metropolitan area.
The sample was drawn from street address and phone number
listings derived from Select Phone Deluxe — software that
includes a set of 6 CD -ROMS and essentially compiles the
telephone listings available for every area of the U.S. The
software was satisfactory for the task although it was not
entirely current nor error free. It was superior to the
available R.L. Polk & Company's City Directories, which were
outdated and not available for all areas. AANC also provided
telephone number listings from member tenant lists for the
apartment complexes.
A sample of households was randomly drawn from these
listings. An equal number of apartment units and houses was
drawn. The number from each urban area roughly corresponded
to that area's relative size. The range was from 69 in
Wilmington to 118 in Charlotte. Thus, the sample could be
described as a cluster random sample. However, the sample
size is far too small to generate any reliable statistics
for each area. Instead, the PI compiled information from
the 1990 Census to generate the demographic profiles for
each metropolitan area in North Carolina and has forwarded
this "PUMS" data to AANC.
From the sample of 630 households, responses were received
from 465 households. The response,rate of 74% was very high
15
primarily due to follow -up telephone calls made by the
interviewers and project managers. Of these, 455 surveys
were ultimately found to be usable in the analysis. Exhibit
2 is the disposition sheet used to track each survey.
The completed telephone interviews were checked, and the
information was carefully coded in order to stress quality
control. The PI also examined every survey for coding
errors and double checked questionable entries. Therefore,
the information on which the analysis is.based is highly
reliable.
The data were compiled in a SAS data set and analyzed on a
univariate and multivariate basis. The univariate analysis
uncovered some questionable values in the data set, and
again the original survey information was reviewed and
corrected as appropriate to eliminate these discrepancies.
Results
The variable names and summary statistics are in Exhibit 3.
The statistics were run on all variables for convenience
although they are not meaningful for some variables such as
the first four listed. The first 25 listed variables,
through Interviewer Number, come from the compiled surveys.
The next eight unlabeled fields convert the residential
tenure variables from year -month values to decimal values in
years. This conversion is accomplished by dividing "months
of residence" by 12 to create a decimal value and then
adding this amount to "years of residence." For example,
the values for YRSRES and MNTRES are 3.24 years and 2.07
months, respectively. The decimal value, TOTRES, is 3.41
years which equals 3.24 years plus another 2.07/12 years.
Approximate monthly rent was assigned to each apartment unit
on the basis of its urban -area location and number of
bedrooms. Assigning approximate rent level was preferable
to asking respondents about rent they paid because survey
questions about monetary values always drive down response
rates to that question and to others as well. For example,
218 owner- occupants indicated the year their residence was
built, but only 169 of them indicated its approximate value.
The last two variables listed were computed from the data
set. The number of adults is the difference between number
of persons in the unit and number of children aged 18 or
younger. The number of children in pre- school, private or
home school is the difference between number of children and
the number in public school in one of three grade levels.
16'
The most important task was to produce an exhibit similar to
the one provided by the Illinois School Consulting Service.
This information is the population per dwelling unit by age
group for all units, for single - family, for apartment units,
and for units of different size. The PI had to complete a
preliminary analysis to determine the number of owner -
occupied dwellings to include in the analysis. Ideally, he
wanted to include all units. However, the sample frame for
single - family housing was not sufficiently precise to
capture only recently built homes. In fact, 37 units
surveyed were built before 1985 and 19 before 1975.
The results on number of persons and children in the unit
were higher for all units than for more recently-built
housing, but the differences were very small. This result
does support the idea that, on average, household size tends
to increase slightly with years of tenure in the house.
Difference -of -means tests were run comparing housing with
two, three and four bedrooms. The analysis showed that no
statistically significant differences exist between all
single- family units, the subsample of houses built after
1985 and the subsample of houses build after 1975 for units
with the same number of bedrooms. Thus, the PI was able to
retain all units in the analysis on the basis of this
analysis.
The analysis pertains to 216 apartments and 239 single -
family units. In fact, eight single- family units are mobile
homes (2), condos ( 5 ) or townhouses (1) . The rest are
single - family detached units. The PI analyzed these eight
records individually and decided to leave them in the sample
because their demographic characteristics matched the
single - family detached and owner - occupied unit
characteristics quite well. Of course, these units tended
to be smaller and less valuable than detached single - family
housing.
All apartment units were rented while seven single - family
units were rented.
The PI compiled the table of average generation rates from
separate analyses of sample subsets. The results are shown
in Exhibits 4 and 5. The nine rows give housing type and
are listed below with the number of observations (n) for
that category: 1) all units (n = 455), 2) all single - family
units (n = 239), 3) single - family units with two bedrooms (n
= 15 which includes one one - bedroom house), 4) single- family
units with three bedrooms (n = 126 which" includes three
units not reporting number of bedrooms), 5) single- family
units with four (n = 78), five (n-,= 18) or six bedrooms (n =
k
2), 6) all apartment units (n = 216), 7) apartment units
with one bedroom (n = 50), 8) apartment units with two
bedrooms (n = 117) and 9) apartments with three bedrooms (n
= 49) .
The eight•coluinns distribute the total number of persons per
dwelling unit by age and school status. Pre - school children
per unit listed in the first column are not old enough to
attend public schools. In the next three columns, children
in public schools per unit are assigned by grade, either to
elementary school, junior high school or`high school.
School -age children attending private schools or receiving
schooling at home per unit are listed in the fifth column.
The sixth column lists the number of children 18 years old
or younger per dwelling unit. Adults per unit, which
includes 18 year -olds who are not attending high school,
usually because they have begun college, are in the seventh
column. The total number of persons per dwelling unit is
shown in the final column.
Except for rounding errors, the rates are additive. The
rates for public - school attendees by grade give the rate of
public school attendance. The sum of this rate and the pre-
school plus private /home school rates is the average number
of children in the units. This rate added to the rate for
number of adults gives the number of persons per unit.
Exhibit 4 presents the average rates for each cell, which
represent the best point estimates for the sample. Exhibit
5 contains the estimates of standard error, which can be
used to calculate confidence intervals for each average rate
and to test for the significance of differences between
single - family and apartment units.
The results in Exhibit 4 generally confirm our expectations
on the basis of previous surveys. Single- family houses
definitely have more persons per unit and more children per
unit than apartments. Moreover, these differences are
highly statistically significant (t statistic for persons
per unit = 7.37, for children per unit = 6.21). The rates
for single - family houses are higher than the apartment rates
for every category. Therefore, one can say that recent
apartment development in urban areas of North Carolina
generates less demand for public education and for other
demographically - driven public services than single - family
housing developed in these urban areas. One major result
from the survey is that all apartment units in the sample
generate 0.435 persons 18 years old or less compared to
0.975 children from single - family houses.
18
The results for units by number of bedrooms are interesting.
As expected, the rates for apartments with one bedroom, the
smallest dwelling units, are the lowest while the rates for
houses with four or more bedrooms are the highest. The
overall difference is about one adult and one child more
living in single - family houses with four or more bedrooms
compared to one - bedroom apartments.
On the other hand, the rates for two- and three - bedroom
apartments compared to two- and three - bedroom houses are
quite similar. Two - bedroom apartments appear to generate
more population and school -aged children than two - bedroom
houses. However, these differences. are not statistically
significant. For example, the t statistics comparing number
of persons per dwelling unit and number of children per
dwelling unit in two - bedroom apartments and in two - bedroom
houses are 1.00 and 0.30, respectively. Significant t
statistics have values of about 2.00 or more.
The average values for three - bedroom apartments are higher
than the values for three - bedroom houses and usually lower
than the values for houses with four or more bedrooms. The
statistical analysis indicates that the former differences
are significant while the latter differences are not. For
example, three - bedroom apartments generate greater impacts
than three bedroom houses for persons per unit and children
per unit. The t statistics are 3.35 and 2.13, respectively.
On the other hand the comparable t statistics for three -
bedroom apartments compared to houses with four bedrooms or
more are 0.83 for persons per unit and 1.35 for number of
children per unit. Also, three - bedroom apartments and
houses with four or more bedrooms have the same impact on
the public schools. (The average rates for grades K -12 are
0.755 for both.) Although the survey collected no
information on income, households in three - bedroom
apartments are probably less affluent than households in
three - bedroom or four - bedroom houses.
The results for apartments compared to single - family houses
are consistent with these detailed comparisons on the basis
of number of bedrooms because of the mix of dwelling units
found in most recent developments. Apartment complexes are
dominated by one - bedroom and two - bedroom units, which are
developed much more frequently than three - bedroom units. On
the other hand, new subdivisions rarely contain two - bedroom
dwellings. Residential development is dominated by houses
with three bedrooms or more. Thus, the weighted average
impact of apartment complexes is significantly less than the
impact of the same number of single - family dwelling units.
CONCLUSIONS
19
The survey achieved its intended purpose. Apartment units
that have been built in North Carolina urban areas since
1990 house significantly fewer persons per unit and fewer
children per unit than single - family houses. As long as
apartment developers and managers own complexes with
predominantly one- or two - bedroom units, they can argue,
with confidence, that their complexes are generating fewer
persons per unit and children per unit than the same number
of recently built, detached single - family houses with three
bedrooms or more.
Three - bedroom apartment units have demographic impacts that
are greater than the impacts of three - bedroom houses.
Households in three - bedroom apartments are living at higher
densities and are more likely to send children to public
schools.
This information should be useful to AANC as they discuss
the application of impact fees and other forms of
development exactions with local and state officials.
EXHIBITS
20 -
EXHIBIT 1 Apartment Association of North Carolina Survey
EXHIBIT 2 Disposition Sheet
EXHIBIT 3 Variables, Labels and Descriptive Statistics
EXHIBIT 4 Average Generation Rates by Housing Type
EXHIBIT 5 Standard Errors of Generation, Rates by Housing
Type
(10/3) Apartment Association of North Carolina Survey
ID. No. Urban Area County Apart= l/House =2
(01 -03) (04 -04) (05 -06) (07 -07)
Hello, my name is . I'm calling from the University of North Carolina at
Chapel Hill, Center for Urban and Regional Studies. This month we're calling people in
different North Carolina cities to obtain information that school planners can use to better predict
the number of students. The questions will take less than 5 minutes to complete, and they deal
with the size of your home and number of people in your family. We have only a phone number
and we will not record any names, so all answers are anonymous.
If I have your permission, let me begin by asking...
1. How many people are in your household including yourself?
(How many people live in your household 50% or more of the time ?) (10 -11)
2. Do you have any children aged 18 or younger in your household?
Yes..................................... ..............................1
No............................. ...... ..............................2
Refused................................. ..............................9
(12 -12)
If YES: For each child, could you tell me his or her age; whether he or she attends a
public school, a private school or is home schooled; and what school grade he or she is
in? Let's start with the youngest child -- what is his or her age? School grade? Type of
school (public, private, home)? ASK FOR EACH CHILD.
If NO, go to Question 3.
Code after the completion of the interview:
Number of children aged 18 or younger
(13 -13)
21
Age;
Grade
Public
Private
Ho' lme:
School, ,
;:School >
:School>:.'
Child #1
1
2
3
Child #2
1
2
3
Child 43
1
2
3
Child #4
1
2
3
If NO, go to Question 3.
Code after the completion of the interview:
Number of children aged 18 or younger
(13 -13)
21
22
Number of children in public elementary school (grades K -5)
r
(14 -14)
Number of children in public middle school (grades 6 -8)
(15 -15)
Number of children in public high school (grades 9 -12)
(16 -16)
3. Do you own or rent your home?
Own.................................... ......................:.......1
Rent.................................... ..............................2
Other.................................... ..............................3
Refused................................. ..............................9
(17 -17)
4.
How many bedrooms do you have in your home?
(18 -18)
5.
How many bathrooms do you have in your home?
(There can be half - baths, so can have the values 1.0, 1.5, 2.0, 2.5, etc) (19 -21)
6.
How long have you -lived in your home?
years months
(Don't know =88, refused =99)
(22 -23) (24 -25) tom.
7.
How long have you lived in county name?
years months
(Don't know =88, refused =99)
(26 -27) (28 -29)
8.
How long have in you lived in the urban area name area?
years months
(Don't know =88, refused =99)
(30 -31) (32 -33)
9.
How long have you lived in North Carolina?
years months
(Don't know =88, refused--99) 1
(34 -35) (36 -37)
(Homeowners only)
10. In what year was your home built?
(Don't know--8888, refused =9999) (38 -41)
11. Can you give the approximate square footage- of the heated area of your home?
(Don't know --8888, refused =9999) (42 -45)
(Note: Most single - family, 3 bedroom houses in North Carolina are from 2,000 - 2,500 sq. fQ -
12. What is the approximate value of your home?
(Don't know= 888888, refused= 999999) (46 -51)
Thank you for your help. Interviewer Number
(52 -53)
W
W
DISPOSITION SHEET
Urban Area:
County:
Apartment House (circle one)
Telephone No.
Date Called Day Called Time Called Disposition* Interviewer (name /no.)
1.
2.
3.
4.
5.
6.
7.
8.
* 1 = completed interview
2 = refused
3 = no answer
4 = answering machine -- note number of rings before switches to message
5 = nonworking number
6 = inconvenient time / call back / appointment:
Appointment
Day Date Time Name to ask for
23
numbed by numkids _ .06 Tuesday, January. 21, 1997 55
.•.r• Variable Label ' ''� N Mean Std Dev
-
----- ---------------------`------------------------------------------ -------- - - - - --
ID
URBANAR
COUNTY
APTHOUS
NUMHOUS
KIDS18
NUMKIDS
KIDSK5
KIDS68
KIDS912
OWNRENT
NUMBED
NUMBATH
YRSRES
MNTRES
YRSCOUN
MNTCOUN
YRSURBA
MNTURBA
YRSNC
MNTNC
YRBUILT
SOF00T
VALUE
INTVNUM
PERMNRES
TOTRES
PERCNRES
TOTCORES
PERURRES
TOTURRES
PERMNCRE
TOTNCRES
RENT
NONPUBPR
ADULTS
ID. No.
Urban Area
County
Apartment or House
Number in Household
Presence of Children 18 or Younger
Number of Childrem 18 or Younger
Number Public School grades K -5
Number in Public grades 6 -8
Number in Public grades 9 -12
Own or Rent Home
Number of Bedrooms in Household
Number of Bathrooms in Household
Years Lived in Home
Months Lived in Home
Years of Residence in County
Months of Residence in County
Years of Residence in Urban Area
Months of Residence in Urban Area
Years of Residence in North Carolina
Months of Residence in North Carolina
Year House was Built
Approximate Square Footage of Home
Approximate Value of Home
Interviewer Number
approximate monthly rent
no. children in private /home school /pres
number of adults in household
455
476.8483516
454
3.3920705
453
4.3509934
455
1.5252747
454
2.6585903
455
1.5912088
455
0.7186813
455
0.2373626
455
0.0879121
455
0.0879121
454
1.4911894
452
2.8141593
448
2.1584821
451
3.2394678
451
2.0687361
450
9.0688889
450
1.4311111
450
10.0555556
450
1.3311111
449
15.6481069
449
1.0534521
218
1987.78
198
2326.97
169
173437.28
448
3.8370536
451
0.1723947
451
3.4118625
450
0.1192593
450
9.1881481
450
0.1109259
450
10.1664815
449
0.0877877
449
15.7358946
216
729.3055556
455
0.3054945
454
1.9383260
285.2359968
2.0067279
7.5728310
0.4999104
1.3055168
0.5054000
0.9731995
0.5440200
0.3059020
0.3130197
0.5004739
0.7656561
0.7444767
4.7995688
3.0378608
11.8152882
2.6370516
12.6656165
2.5890228
16.5560736,
2.4214062
9.9377943
933.5140635
92221.11
1.5766082
0.2531551
4.7315896
0.2197543
11.7436413
0.2157519
12.5934044
0.2017838
16.4869097
126.0490092
0.6270978
0.7282886
N
.A
numbed by numkids''
_ .06 Tuesday,
January 21, 1997 56
• Wtriable
Cabel
Minimum
Maximum ,
---------------------------------------------------------------------='--------
ID
ID. No.
1.0000000
948.0000000
URBANAR
Urban Area
1.0000000
7.0000000
COUNTY
County
1.0000000
92.0000000
APTHOUS
Apartment or House
1.0000000
2.0000000
NUMHOUS
Number in Household
1.0000000
7.0000000
KIDS18
Presence of Children 18 or Younger
0
2.0000000
NUMKIDS
Number of Childrem 18 or Younger
0
3.0000000
KIDSK5
Number Public School grades K -5
0
3.0000000
KIDS68
Number in Public grades 6 -8
0
2.0000000
KIDS912
Number in Public grades 9 -12
0
2.0000000
OWNRENT
Own or Rent Home
1.0000000
2.0000000
NUMBED
Number of Bedrooms in Household
2.0000000
4.0000000
NUMBATH
Number of Bathrooms in Household
1.0000000
6.0000000
YRSRES
Years Lived in Home
0
45.0000000
MNTRES
Months Lived in Home
0
11.0000000
YRSCOUN
Years of Residence in County
0
66.0000000
MNTCOUN
Months of Residence in County
0
11.0000000
YRSURBA
Years of Residence in Urban Area
0
74.0000000
MNTURBA
Months of Residence in Urban Area
0
11.0000000
YRSNC
Years of Residence in North Carolina
0
74.0000000
MNTNC
Months of Residence in North Carolina
0
11.0000000
YRBUILT
Year House was Built
1916.00
1996.00
SQFOOT ,
Approximate Square Footage of Home
900.0000000
6000.00
VALUE
Approximate Value of Home
6000.00
700000.00
INTVNUM
Interviewer Number
2.0000000
9.0000000
PERMNRES
0
0.9166667
TOTRES
0.0833333
45.0000000
PERCNRES
0
0.9166667
TOTCORES
0.0833333
66.0000000
PERURRES
0
0.9166667
TOTURRES
0.0833333
74.0000000
PERMNCRE
0
0.9166667
TOTNCRES
0.1666667
74.0000000
RENT
approximate monthly rent
500.0000000
950.0000000
NONPUBPR
ho. children in private /home school /pres
0
3.0000000
ADULTS
number of adults in household
1.0000000
,v
7.0000000 "'
Exhibit 4
Population, Age - Cohorts and Schooling Status by Housing Type
Average Generation Rates per Unit
Type of Unit
Pre - School
(0-4 yrs.)
Elementary
Grades K -5
Jr. High
Grades 6 -8
High School
Grades 9 -12
Private or
Home School
Children
(18 yrs or less)
Adults
Persons per
dwelling unit
All Units
0.2102
0.2374
0.0879
0.0879
0.0953
0.7187
1.9383
2.6586
Single Family
0.3002
0.3264
0.0921
0.1130
0.1432
0.9749
2.0840
3.0630
Two BR or less
0.2000
0.0667
0.0000
0.0000
(2)
0.2667
1.4667
1.7333
Three BR
0.3333
0.2857
0.0556
0.0714
(2)
0.7460
2.0320
2.7840
Four BR or more
0.6224
0.4184
0.1531
0.1837
(2)
1.3776
2.2449
3.6224
Apartments
0.1106
0.1389
0.0833
0.0602
0.0422
0.4352
1.7778
2.2130
One BR
0.0000
0.0200
0.0000
0.0000
(2)
0.0200
1.3400
1.3600
Two BR
0.1282
0.1026
0.0598
0.0342
(2)
.0.3248
1.7350
2.0598
Three BR
0.3673
0.3469
0.2245
1 0.1837
1 (2)
1.1224
1 2.3265
3.4490
(1) Average generation rates for Elementary, Jr. High and High School pertain to public schools only.
(2) Included with Pre - school children
P
Exhibit 5
Population, Age- Cohorts and Schooling Status by Housing Type
Standard Errors for Average Generation Rates per Unit
Type of Unit
Pre - School
(0 -4 yrs.) (1)
Elementary
Grades K -5
Jr. High
Grades 6 -8
High School
Grades 9 -12
Children
(18 yrs or less)
Adults
Persons per
dwelling unit
All Units
0.029
0.026
0.014
0.015
0.046
0.034
0.061
Single Family
0.047
0.040
0.020
0.024
0.067
0.049
0.085
Two BR or less
0.145
0.067
0.000
0.000
0.182
0.165
0.316
Three BR
0.055
0.052
0.021
0.023
0.083
0.060
0.106
Four BR or more
0.083
0.071
0.039
0.049
0.106
0.083
0.123
Apartments
0.032
0.029
0.021
0.016
0.056
0.049
0.079
One BR
0.000
0.020
0.000
0.000
0.020
0.068
0.074
Two BIV
0.039
0.035
0.025
0.017
0.063
0.054
.0.083
Three BR
0.095
0.085
0.067
0.056
1 0.156
0.089
0.168
(1) Children in private or home schools included with pre - school children.
N
V