20181192 Ver 1_C540_ICE_Growth_Memo_1117_20180122

Historic Growth Memorandum
For
Complete 540 — Triangle Expressway Southeast Extension
DRAFT
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Wake and Johnston Counties
STI P Nos. R-2721, R-2828, R-2829
Prepared for:
Prepared By:
Michael Baker Engineering
I N T E R N AT I 0 N A L
November 2017

Contents
ExecutiveSummary .......................................................................................................................................1
Introduction..................................................................................................................................................2
Methodology and Region Definition .............................................................................................................2
Population..................................................................................................................................................... 7
RegionalTrends .........................................................................................................................................7
FLUSATrends ............................................................................................................................................ 9
PopulationDensity ......................................................................................................................................13
RegionalTrends .......................................................................................................................................13
FLUSATrends ..........................................................................................................................................14
AverageHousehold Size ..............................................................................................................................17
RegionalTrends .......................................................................................................................................17
FLUSATrends .......................................................................................................................................... 20
Employment................................................................................................................................................ 23
RegionalTrends .......................................................................................................................................23
FLUSATrends .......................................................................................................................................... 24
EducationalAttainment ..............................................................................................................................26
RegionalTrends .......................................................................................................................................26
FLUSATrends .......................................................................................................................................... 26
MedianIncome ...........................................................................................................................................27
RegionalTrends .......................................................................................................................................27
FLUSATrends .......................................................................................................................................... 27
SchoolQuality .............................................................................................................................................30
RegionalTrends .......................................................................................................................................30
FLUSATrends .......................................................................................................................................... 34
AverageCommute ...................................................................................................................................... 36
RegionalTrends .......................................................................................................................................36
FLUSATrends .......................................................................................................................................... 39
Regional Economic Drivers and Related Trends ..........................................................................................42
ResearchTriangle Park ............................................................................................................................42
WakeCounty Trends ...............................................................................................................................43
Conclusion................................................................................................................................................... 44
WorksCited .................................................................................................................................................46

Executive Summary
The North Carolina Department of Transportation (NCDOT) and the Federal Highway Administration
(FHWA) propose to build a new, full-control of access highway from NC 55 Bypass in Apex to the
US 64/US 264 Bypass (I-495) in Knightdale, a distance of approximately 28 miles. This proposed highway,
known as Complete 540 —Triangle Expressway Southeast Extension, is proposed as a toll facility.
This memo was developed to examine historic demographic trends that may influence existing or future
regional population and employment growth trends. Most of these historic growth trends are not
directly related to transportation infrastructure, and examining them may indicate likely growth
patterns that would occur with or without a specific roadway project. Growth trends were examined for
the Raleigh-Durham-Chapel Hill, NC Combined Statistical Area (CSA) and the Complete 540 Future Land
Use Study Area (FLUSA) for recent reporting periods beginning in 1990.
This region, also known more informally as the Research Triangle Region, has unique economic drivers
that have created economic success and continue to foster growth. The three major universities in the
region, University of North Carolina at Chapel Hill, North Carolina State University, and Duke University,
formed the Research Triangle Park (RTP) in 1959 to link their talent and resources with public- and
private-sector research entities and companies focused on innovation. Over 250 businesses employing
over 50,000 people are currently located in RTP, the nation's largest research park. Areas of
specialization include biotechnology and information technology, and the region's research and
partnerships also support a world-class medical community. Further, in addition to all the employment
generated to serve a region of over 1 million population with education, social services, retail, and other
services, regional employment is also boosted by the presence of the State government in Raleigh.
CSA and FLUSA level data show a pattern of sustained population and employment growth and
increases in population density in addition to a concentration of recent growth within Wake County. The
other FLUSA counties (Harnett and Johnston) also show strong growth and are projected to increase in
population through 2035. Growth indicators at the CSA level, namely employment, average household
size, educational attainment, median income, and school quality indicate that growth will very likely
continue in the counties comprising the project FLUSA. Analysis of population, population density,
average household size, school quality, and commute in the FLUSA counties at the sub-county level
further indicates growth is likely within the FLUSA.
The FLUSA area has both positive and negative indicators for growth compared to the other zones in the
three-county study area. Within the FLUSA counties, growth indicators suggest that much of the future
population growth will occur within Wake County. Population densities are still relatively low outside of
the urban core of the City of Raleigh, leaving ample room for additional growth in the suburban and
rural portions of the county. In particular, population density is relatively low in the FLUSA, suggesting
that there may be land available for development. With higher median household income and a greater
perceived school quality than neighboring counties, many new residents and potential homebuyers
would be attracted to Wake County. School quality appears to be highest in central, western and
northern Wake. Northern Harnett County and eastern Johnston County appear to have some positive
growth factors, particularly the relatively low population densities and increases in employment and
median income. Johnston County appears to have a higher quality school district, and would therefore
be more likely to attract growth, relative to Harnett County.

Introduction
The North Carolina Department of Transportation (NCDOT) and the Federal Highway Administration
(FHWA) propose to build a new, full-control of access highway from NC 55 Bypass in Apex to the
US 64/US 264 Bypass (I-495) in Knightdale, a distance of approximately 28 miles. This proposed highway,
known as Complete 540—Triangle Expressway Southeast Extension, is proposed as a toll facility.
The project is located within the greater Raleigh area, known as the Research Triangle Region, which
includes Raleigh, Durham, Chapel Hill, and the surrounding counties. The Research Triangle refers to the
three premier universities in the region, University of North Carolina in Chapel Hill, North Carolina State
University in Raleigh, and Duke University in Durham. Raleigh is both the state capital and the seat of
Wake County. Durham is the county seat of Durham County and Chapel Hill is the largest city in Orange
County. More specifically, the project would be located in southern Wake County and western Johnston
County.
The Research Triangle region is known for its medical, technology, and education economic clusters.l It
contains the largest research business park in the U.S. (Research Triangle Park or RTP) and has spent
decades harnessing the synergy between the three premier universities in the region, public sector
research, and private sector research and development. RTP alone hosts over 250 businesses employing
over 50,0000 people, with over 3,000 patents awarded to RTP tenants since 19702. The region ranks 5tn
in educational attainment among 36 comparable regions, with about half of residents attaining a
Bachelor's Degree or higher, and nearly 1 in 5 residents holding a graduate degree.3
The purpose of this memo is to examine historic trends in population and employment growth, along
with other changes in demographic factors, which may affect existing or future regional population and
employment growth trends. Information about the region's economic drivers and notable trends related
to growth are also provided to add context to the regional and study area trend analysis. Most of these
historic growth trends are not directly related to transportation infrastructure, and examining them may
indicate likely growth patterns that would occur with or without a specific roadway project. This memo
examines population growth, population density, average household size, educational attainment,
median income, employment, school quality, and commute time to understand the historic growth
trends and to assess what these trends and factors suggest about growth trends in the future. These
factors were chosen based on readily available historic data from state and federal resources. In
addition, as described in subsequent sections of this memo, research indicates that these factors may
help explain past and future growth trends.
Methodology and Region Definition
The US Census includes Raleigh and the surrounding area in multiple geographies. This memo is
concerned with the following geographies:
Raleigh-Cary, NC Metropolitan Statistical Area (MSA), defined by the US Census Bureau as
Franklin, Johnston, and Wake counties; and
Raleigh-Durham-Chapel Hill, NC Combined Statistical Area (CSA), defined by the US Census
Bureau as Franklin, Johnston, Wake, Chatham, Durham, Granville, Harnett, Lee, Orange, Person,
and Vance counties.
1 Research Triangle Regional Partnership n.d.
z The Research Triangle Park, 2017.
3 Ibid
2

Prior to initiating studies of potential Indirect and Cumulative Effects (ICE), NCDOT and FHWA, in
consultation with resource agencies, defined a Future Land Use Study Area (FLUSA). The FLUSA is the
area surrounding the proposed Complete 540 project that may be affected as a result of the project in
combination with other public and private development projects (see Figure 1), and includes parts of
Harnett, Johnston, and Wake counties. The FLUSA was identified in the Qualitative ICE Report and will
continue to be the main study area in the analysis of the Quantitative ICE Report to be conducted for
the Final Environmental Impact Statement (EIS) for the proposed roadway.4
The MSA regional definition does not include Harnett County; using the MSA designation as the basis for
the regional analysis would ignore a part of the FLUSA. In addition, the Triangle Region is an inter-
connected and polycentric metropolitan region and limiting the regional analysis to the MSA would
exclude key counties, such as Durham and Orange counties, from the analysis. Therefore, this memo
uses the CSA definition of the region as the basis for evaluating historic growth patterns across the
larger Raleigh-Durham-Chapel Hill area.
In addition to analyzing growth and trends over time at a regional level, this memo examines growth
and trends at a sub-county level among the three counties comprising the FLUSA, where such
information is available. Sub-county zones (called Census regions in this memo) were established based
on block group boundaries created by the US Census Bureau (see Figure 2). Block group boundaries
often change with each decennial census. For this reason, only boundaries that remained constant
between the 1990, 2000, and 2010 Censuses were used to develop the Census regions. The zones
defined are aggregations of Census block groups, but the specific block groups vary for each census year.
This memo only analyzes trends at the Census region level for the three counties in the FLUSA region
(Harnett, Johnston, and Wake), rather than all counties in the CSA. Census regions include the first letter
of the county name and a number. Eight Census regions are within the FLUSA boundary. These are Zone
H1, Zone J1, Zone J5, Zone W1, Zone W3, Zone W4, Zone W6 and Zone W8. Table 1 provides the
percentage of each Census region within the FLUSA boundary.
4 H.W. Lochner, Inc. 2014
3

Table 1: Census Regions within the FLUSA Boundary
Zone H1
Zone H2
Zone H3
Zone H4
Zone J1
Zone J2
Zone J3
Zone J4
Zone J5
Zone W1
Zone W2
Zone W3
Zone W4
Zone W5
Zone W6
Zone W7
Zone WS
Harnett
Yes
No
No
No
Johnston
Yes
No
No
No
Yes
Wake
Yes
No
Yes
Yes
No
Yes
No
Yes
4
13
0
0
0
78
0
0
0
14
<1
0
83
45
0
82
0
1

Figure 1: FLUSA and MSA Location

Figure 2: FLUSA Census Regions
0
Cc�m�let� 540 Demagr�,phics
Cer�sus Regians
� FLUSA Boundary
� Census Region Boundaries
0 County Bounc�aries
Census Regions were created by combinirng 1990, 2000,
an�d 20'86 Census Block Groups. The regions were
created to follow Block Group Boundaries that did
not change over the 20 year period. Census Block
Group data wvas aggregated into those regions for
the purposes of this analysis.
10 20
Miles
I N T E R N A T I 0 N A 6

Population
Regional Trends
Both historic population data from the US Census and population forecasts produced by the North
Carolina Office of State Budget and Management (NCOSBM) State Demographics branch show a pattern
of high population growth in the CSA from 1990 to 2010 that is anticipated to continue into 2035. As
shown in Table 2, between 1990 and 2000, the CSA grew by 36 percent; followed by a growth of 31
percent between 2000 and 2010. Overall, the population of the CSA grew by 78 percent between 1990
and 2010. Wake County had the highest overall population in 1990, 2000, and 2010.
The counties that have historically experienced the greatest growth rates are Wake and Johnston
counties, at 113 percent and 108 percent growth, respectively, from 1990 to 2010. While every county
in the CSA experienced growth, Lee, Person, and Vance counties grew more slowly than the CSA as a
whole. Between 1990 and 2010, the population grew by 40 percent in Lee County, 31 percent in Person
County, and 17 percent in Vance County. Figure 3 illustrates the population growth rate trends within
the CSA.
Analyzing county growth as a percent of the CSA shows the distribution of population growth across the
CSA. This is reflected in the Table 2 column "County Share of CSA Population Growth (%) 1990-2010."
Historically, Wake County captured the greatest percentage of CSA population growth, accounting for 57
percent of growth between 1990 and 2010. Durham and Johnston counties both captured 10 percent of
CSA population growth.
Table 2: Population Changes for Raleigh-Durham-Chapel Hill, NC CSA Counties
1990- � Growth
1990 2000 2010 2010 1990-2010
Growth
FLUSA Counties
Harnett 67,822 91,025 114,678 46,856
Johnston 81,306 121,965 168,878 87,572
Wake 423,380 627,846 900,993 477,613
Remaining CSA Counties
Chatham 38,759 49,329 63,505 24,746
Durham 181,835 223,314 267,587 85,752
Franklin 36,414 47,260 60,619 24,205
Granville 38,345 48,498 59,916 21,571
Lee 41,374 49,040 57,866 16,492
Orange 93,851 118,227 133,801 39,950
Person 30,180 35,623 39,464 9,284
Vance 38,892 42,954 45,422 6,530
CSA Total 1,072,158 1,455,081 1,912,729 840,571
Source: US Decennial Census, Summary File 1, Table P1, 1990, 2000 and 2010.
Percentages are rounded and the sum may not equal 100%.
7
69
108
113
County Share of
CSA Population
Growth (%) 1990 -
2010
6
10
57
64 3
47 10
66 3
56 � 3
40 2
43 � 5
31 1
17 1
78 -

Figure 3: Regional Population Trends
1990 � 2000
Person Granvill
� Vance
Orange
Chatham
Lee
� �
Harnett �:,
Franklir�
2000 - 2010
0
Complete 5�0:
Regional L��mographics
P�p�latian Change
Interstates
�6 US RouteS
� FLUSA Boundary
� Cflunty Boundary
Percent Populakion Change
4% - 12%
13% - 20%
� z�% - 30°io
i 31 °/a - 40%
� 41 % - 51�' °/a
�
W�E
�i
s
0 20 40
I i I i I
Miles
I N T E R N A T I 0 N A L

Based on forecasts produced by the State Demographics branch, these population growth patterns are
anticipated to continue (see Table 3). Overall, the population of the CSA is forecast to grow by 46
percent between 2010 and 2035, a 2 percent annual growth rate. According to forecasts, Johnston
County will experience the highest percentage of population growth during that period, eclipsing Wake
County. However, this difference is largely a function of the smaller population base in Johnston County.
Wake County will experience the second highest percentage growth between 2010 and 2035.
Forecasts indicate that historic trends in the distribution of regional growth by county will continue
between 2010 and 2035. As shown in Table 3, Wake County is forecast to capture 57 percent of the
regional population growth from 2010 to 2035, while Durham County is forecast to capture 16 percent.
Johnston County is forecast to capture 11 percent of CSA growth, while Harnett County is expected to
capture 7 percent. Forecasts anticipate that Granville, Lee, and Person counties will capture less than 5
percent of the region's growth. Vance County is forecast to lose population between 2010 and 2035.
Table 3: Population Forecasts for Raleigh-Durham-Chapel Hill, NC CSA Counties
2010 2020 2035
2010- � County Share of
2035 Growth CSA Population
Growth 2010- Growth (%)
2035 1990 -2010
FLUSA Counties
Harnett 115,724 139,259 173,080 57,356 50
Johnston 169,612 201,850 263,815 94,203 56
Wake 906,910 1,105,706 1,406,726 499,816 55
Remaining CSA Counties
Chatham 63,786 75,494 92,418 28,632 45
Durham 271,303 325,799 408,936 137,633 51
Franklin 60,823 66,881 76,008 15,185 25
Granville 57,599 59,236 62,100 4,501 8
Lee 57,879 59,242 59,363 1,484 3
Orange 134,053 149,922 174,888 40,835 30
Person 39,428 39,588 40,071 643 2
Vance 45,314 44,847 44,775 -539 -1
Regional Total 1,922,431 2,267,824 2,802,180 879,749 46
Source: NCOSBM State Demographics, last updated October 8, 2015
Note: 1) Based on estimated populations in July of that year. 2) Regional Total % may not sum to 100% due to rounding.
7
11
57
3
16
2
1
0
5
0
0
Current population forecasts predict continued growth for the majority of CSA counties. Historic
population data shows a pattern of high growth, which forecasts indicate will continue at a more
modest rate from 2010 to 2035. Wake and Johnston counties are forecast to capture the highest
percentage of population growth in the CSA and Wake County is expected to continue to capture the
majority of the region's growth.
FLUSA Trends
When analyzing population data for the FLUSA counties, growth varies within each county. Table 4
further outlines population trends within the FLUSA. Harnett County experienced the least growth and
the lowest growth rate among the FLUSA counties, growing at 69 percent between 1990 and 2010.
During this time, the population distribution shifted within the county. In 1990, Zone H2, in the eastern
section of the county, had the highest population. By 2010, Zone H4, the southern portion bordering the
0

Fayetteville and Fort Bragg areas in Cumberland County, had the largest share of the county population,
growing by 157 percent since 1990. Population in Zone H1, which borders Wake County, grew by 91
percent in the same period. As seen in Figure 4, population increased in the northern and southern
sections of the county (Zones H1 and H4). Zone H2 and Zone H3 grew at a slower pace than the other
two zones and had lower populations in the 2010 Census.
Johnston County also experienced a shift in population distribution during this period. Historical Census
data indicates that the population shifted from a relatively even distribution across the county to a more
concentrated population along the Wake-Johnston border.
In 1990, Zone J1, Zone J3, and Zone J5 in the western, eastern, and southern areas of Johnston County,
respectively, had similar total populations. Between 1990 and 2010, the population of Zone J1 more
than doubled (growing by 41,805). By 2010, Zone J1 had the highest population in the county (62,053).
Zone J2, which also borders Wake County, also doubled in population. This zone experienced the fastest
growth, 215 percent. Zone J5, which includes part of the southern portion of the FLUSA experienced a
90 percent growth rate between 1990 and 2010.
Table 4: Ponulation Growth in FLUSA Counties
Harnett 67,822 91,025 114,678 46,856 69
Zone H1 16,164 24,064 30,931 14,767 -� 91
� Zone H2 23,018 23,881 24,358 1,340 6
Zone H3 12,585 16,416 18,098 5,513 44
Zone H4 16,055 26,664 41,291 25,236 157
Johnston 81,306 121,965 168,878 87,572 108
Zone J1 20,248 38,995 62,053 41,805 206
Zone J2 8,591 15,474 27,070 18,479 215
� Zone J3 20,122 24,354 26,199 6,077 30
Zone J4 11,404 12,968 13,845 2,441 21
Zone J5 20,941 30,174 39,711 18,770 90
Wake 423,380 627,846 900,993 477,613 113
Zone W1 86,516 94,597 103,454 16,938 � 20
Zone W2 44,531 100,307 177,512 132,981 298
Zone W3 70,353 92,540 109,933 39,580 � 56
Zone W4 46,854 74,895 124,867 78,013 � 166
Zone W5 94,928 117,138 126,772 31,844 � 34
Zone W6 32,497 66,915 114,625 82,128 252
Zone W7 30,271 59,008 116,664 86,393 I 285
Zone W8 17,430 22,446 27,166 9,736 56
Source: US Decennial Census, Summary File 1, Table P1, 1990, 2000 and 2010
Notes: 1) Population totals for Harnett County in 1990 and 2000 vary slightly from the Indirect and Cumulative Effects Report by H.W. Lochner,
Inc. The difference in population is 11 people and 4 people lower, respectively. There is no clear reason for this small difference as this memo
and the Lochner report used official US Census Bureau data collected from authoritative sources. 2) FLUSA Census regions are shown in bold.
In 1990, the population in Wake County was concentrated in and around the City of Raleigh, which is
mostly included in Zone W1, with portions in FLUSA area Zones W3 and W4. However, during the
following two decades Wake County experienced high population growth and much of that growth
occurred in surrounding zones. By 2010, population in Wake County was more evenly distributed across
10

the county. According to the 2010 Census, all but one zone (Zone W8) in Wake County had populations
over 100,000. During this period Zone W6 experienced an exceptionally high growth rate (252 percent).
Both Zones W6 and W8 are FLUSA zones. Zones W3 and W4 grew by 56 percent and 166 percent,
respectively.
To summarize, Census data show Wake County was and continues to be the dominant population center
in the region. The FLUSA counties, Harnett, Johnston, and Wake, had the highest percent growth in the
CSA from 1990 to 2010. Population projections indicate that FLUSA counties are likely to grow at a rate
higher than the CSA average through 2035. Zones within Harnett and Johnston Counties that are part of
the FLUSA experienced substantial growth between 1990 and 2010. While growth within Wake County
was more variable, Zones W3, W4, and W6, which include the majority of the FLUSA in Wake County,
had growth rates of 56 percent, 166 percent, and 252 percent, respectively.
The population growth trends during and after the recession that began in late 2008 are also relevant to
an understanding of growth trends in the FLUSA. Historical data taken from the ACS shows continual
population growth in Harnett, Johnston, and Wake Counties over the last decade. The year of slowest
growth occurred between 2009 and 2010 when the population grew by only 2.3 percent -- Harnett
County's by less than one percent. Between 2010 and 2015 the three counties experienced a combined
growth of 14 percent. The FLUSA experienced an even larger growth during the same period of
approximately 18 percent. The robust growth of the FLUSA counties and the FLUSA itself during and
after the recession suggests the area has highly resilient drivers of growth.
Table �����on Grow�h TrFi,ds in cl F� LUS' �o �e�� 7GJ`
� , , • % CAGR
County 2009 2010 2012 2015 Growth 2010- / Growth 2010-2015
2009- 2015
�
Harnett 108,885 109,031 115,559 124,320
Johnston 156,888 160,675 169,122 178,396
Wake 828,759 850,546 905,573 976,019
Total 1,094,532 1,120,252 1,190,254 1,278,735
FLUSA N/A 256,959 278,436 303,383
Source: US Census American Community Survey, Five Year, Table 50101
11
2010
0.1
2.4
2.6
2.3
N/A
2.7
2.1
2.8
2.7
3.4
14 �
11
15
14
18

Figure 4: Popu/ation Changes in the FLUSA Counties
�nnn nnnn
`� �mplete 540 �emo�;raphics
12
Populatian �hange
Interstates
�- US Rautes
� �County Boundaries
� FLUSA Boundary
Census Region Bour�daries
Census Regior�s
Perc+ent Popc�lation Change
2% - 15%
15.1 % - 25%
25.1 % � 35%
i 35.1 % - 45%
i 45.1 % - 56%
Census Block Group data was aggregated into
Census Regions for the purposes of this analysis.
Census Regions were created by combining 1990,
2�OD, and 2010 Census B1ock Groups. The regioms
were created to follow Block Group Boundaries that
did not change over the 20 year period.
N
W�E
e
0 1 f3 20
I i I � I
Miles
INTEdiNATIONA L

Population Density
Regional Trends
Population density is the number of people per square mile. Changes in population density over time
often show similar patterns as population growth, but can also be a helpful indicator of the availability
of land for future development. Where population density is particularly high, it suggests that there is
less land available for development; therefore, the area may see slower growth in the future.
Census data show a pattern of increasing population density in the CSA region (see Table 6). The average
population density in the CSA increased from 198 people per square mile in 1990 to 327 people per
square mile in 2010. This is a 65 percent increase in population density between 1990 and 2010. Overall,
population density increased continuously over the twenty years of data analyzed in each of the CSA
counties.
In 1990 and 2000, Durham County had the highest population density in the CSA. Wake County had the
second highest population density, followed distantly by Orange County. Eight of the eleven counties in
the CSA had population densities below the regional average. These counties are farther from the urban
centers of Raleigh, Durham, and Chapel Hill, and include Chatham, Franklin, Granville, Vance and Person
counties. Table 5 shows population density data for the CSA over time.
While population density continued to increase between 2000 and 2010, growth varied through the CSA
(see Figure 5). Wake County eclipsed Durham in the 2010 Census with a population density of 1,079
people per square mile, compared to Durham's population density of 936 people per square mile. Both
Wake and Durham counties consistently had population densities higher than the CSA average.
Table 6:
Density for Raleigh-Durham-Chapel Hill, NC CSA Counties
Population
2010 Density Change
(1990-2010)
FLUSA Counties
Harnett 114 153 � 193 79 � 69
Johnston 103 154 213 110 � 107
Wake 508 755 � 1,079 571 _ 112
Remaining CSA Counties
Chatham 57 72 � 93 36
Durham 626 769 936 310
Franklin 74 96 123 49
Granville 72 91 113 41
Lee 161 191 227 I 66
Orange 235 296 336 101
Person 77 91 101 24
Vance 153 169 ' 179 26 �
Regional 198 258 327 129
Average
Source: US Decennial Census, 1990, 2000 and 2010, Summary File 1, Table GHT-PH1
Percentages are rounded to the nearest whole percent.
13
63
SO
66
57
41
43
31
17
65

While Wake County had a population density of 1,079 people per square mile in 2010, this does not
necessarily mean that the area has reached build out or that additional growth cannot occur. An
illustrative comparison is the growth pattern of population density in the Charlotte-Gastonia-Rock Hill
CSA. Like the Raleigh-Durham-Chapel Hill CSA, the Charlotte-Gastonia-Rock Hill CSA has a strong urban
core in Charlotte and interdependent surrounding counties and municipalities. Charlotte is located in
Mecklenburg County, whose population density of 1,322 people per square mile in 2000 exceeded Wake
County's 2010 population density. However, Mecklenburg County has continued to grow, reaching 1,756
people per square mile in 2010. If Wake County follows a similar trend to Mecklenburg County, its
population density is likely to increase during the foreseeable future. While population densities in
surrounding counties suggest that they may have a greater amount of developable land, it does not
appear that population density in Wake County has reached a level that would limit growth.
FLUSA Trends
Population density in the FLUSA counties follows similar trends as population growth. Densely
populated areas in the FLUSA are predominantly concentrated in zones near urban areas. As with
population growth, higher population densities occurred in zones along the Wake County border in
Johnston County and in zones along both the Wake and Cumberland borders in Harnett County. Overall
trends in Wake County show population density is highest in and around the urban core of the City of
Raleigh and Town of Garner (Zones W1, W3, W4, and W5) (see Table 7).
Harnett County population density is highest in Zone H2. However, this zone only grew by six percent
between 1990 and 2010. The highest increase in population density occurred in Zone H4, which is
adjacent to Cumberland County. Zone H1, which is adjacent to Wake County, experienced the second
highest increase in population density between 1990 and 2010. Both Zone H1 and Zone H4 had lower
population densities than Zone H2. Current data suggests that these zones still have developable land
that could support future growth (Figure 6).
Population density in Johnston County is highest in Zone J1, which is adjacent to Wake County. The
zones with the highest population density increases between 1990 and 2010 are Zone J1 and Zone J2
(near the Town of Clayton). These areas appear to have ample space for continued development in the
future. Zone J3 has a similar population density to Zone J2; however, it experienced a much lower
increase in population density. Trends suggest that Zone J1 and Zone J2 will continue to be areas of high
population growth.
Within Wake County, the area with the highest population density is Zone W1, which is primarily the
center of the City of Raleigh. However, population density in Zone W1 increased slowly, indicating that
much of the land there is already developed. Zones that experienced the greatest increase in population
density are Zone W2, Zone W6, and Zone W7. While Zone W6 and Zone W7 had high population density
growth, the population densities in the 2010 US Census are low when compared to other zones. Lower
relative density suggests that there is still available land for development in those areas. This, coupled
with the increasing density and continuing trends in population growth in these zones, indicates that
these areas may continue to support development and increased population in the future.
14

Figure 5: Regional Population Density Trends
�99Q - 2000
Granville� �
\!a n r.F
2040 - 2010
15
Complete 540:
Regional Demographics
Popul�tior� Density Change
I nte rstates
/� US Routes
� FLU�A �oundary
� Cou�nty �aundary
Percen# Populatoon Density Change
6% - 1 �%
13% - 20%
� 21 % - 30%
� 31 °fo - 44%
i 41 % - 50°to
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I N T E R N A T I 0 N A L

Table 7: Population Density in the FLUSA Counties
Harnett 114 153 193
Zone H1 105 156 200
� Zone H2 284 295 301
Zone H3 71 94 103
Zone H4 84 140 216
Johnston 103 154 213
ZoneJ1 148 286 455
ZoneJ2 62 113 198
�ZoneJ3 149 180 194
ZoneJ4 74 84 90
ZoneJS 90 130 170
Wake 508 755 1, 079
Zone W1 2,881 3,150 3,445
Zone W2 335 755 1,335
Zone W3 760 1,000 1,187
Zone W4 403 644 1,074
Zone W5 1,746 2,155 2,332
Zone W6 185 380 652
Zone W7 186 363 717
Zone W8 189 243 295
Source: US Decennial Census, 1990, 2000 and 2010, Summary File l, Table P1.
Note: FLUSA Census regions are shown in bold.
79
95
17
32
132
110
307
136
45
16
80
571
564
1,000
427
671
586
467
531
106
69
90
6
45
157
107
207
219
30
22
89
112
20
299
56
166
34
252
285
56
Population densities within the FLUSA counties suggest certain Census regions of Harnett, Johnston, and
Wake counties have sufficient available land to support continued growth. In Harnett County, areas
adjacent to Cumberland and Wal<e counties (including FLUSA Zone H1) show a trend of increasing, but
still relatively low population density. Johnston County follows similar trends, with areas of increasing
population density in FLUSA Zones J1 and J2 adjacent to Wake County. Growth in Wake County shows
population density is increasing in areas north and south of the City of Raleigh (FLUSA Zones W3, W4,
and W6), which contain most of the FLUSA in Wake County. Population density in Zone W1, which
includes the urban core of Raleigh, grew at a slower rate.
16

Average Household Size
Regional Trends
Analyzing household size may aide in the understanding of the type of household living in a particular
area. Typically, if household size is greater than two residents, that household is more likely to include
dependent children. These households are also more likely to make more daily trips. Conversely,
households with two or fewer residents are considered less likely to have dependent children and, for
that reason, are expected to make fewer daily trips. National Census data from the 1990, 2000, and
2010 show a pattern of household size decreases, with more people living alone, waiting to have
children, and/or having fewer children.5
As shown in Table 8 and Figure 7, Harnett, Johnston, Orange, and Wake counties experienced an
increase in household size between 1990 and 2010. However, a majority of the counties in the CSA
experienced a decline in household size. These counties include Chatham, Durham, Franklin, Granville,
Person and Vance. The decline in household size for these counties varies from two to five percent. Lee
County experienced a slight increase in household size between 1990 and 2000; however, the
household size decreased between 2000 and 2010, and overall decreased slightly between 1990 and
2010.
Table 8:
Household Size
% Change 1990-
2010
FLUSA Counties
Harnett 2.60 2.61 2.68 3
Johnston I 2.55 2.58 2.70 6
Wake 2.46 2.51 2.55 4
Remaining CSA Counties
Chatham 2.51 2.47 2.43
Durham � 2.40 2.40 2.35
Franklin 2.61 2.58 2.56
Granville � 2.68 2.58 2.57
Lee 2.59 2.61 2.58
Orange I 2.34 2.36 2.41
Person 2.61 2.50 2.47
Vance 2.69 2.60 2.56
CSA Average 2.49 2.50 2.53
Source: US Decennial Census, 1990, 2000 and 2010, Summary File 1, Table H1
Note: Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010
-3
-2
-2
-4
-1
3
-5
-5
2
5 US Census Bureau. 2010 Census Briefs - Households and Families 2010. Issued April 2012.
17

Figure 6: FLUSA Population Density Trends
�nnn nnnn
� -�m�pl�te 54(�� D�magraphics
18
I�opulat�on Density Change
Interstates
�- US Routes
� County Boundaries
� FLUSA Boundary
Census Reguon Boundaries
Census Regions
Percec�t Population aensity Change
2% - 10%
� a.7 Qio - soQra
�� 3a. � °�o - �a��a
i �a. � �ro - �a�io
i 7Q.1 %o - 125%
Census Block Group data was aggregated into
Census Regions for the purposes of this analysis.
Census Regions were created by carnbining 'V990,
2000, and 2010 Census Slock Groups. The �egions
were created to fol�low Block Group Boundaries that
did not chenge over the 20 year period.
N
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e
o �0 20
i � i � i
Mi�es
1 N T E R N A T I m N A L

Figure 7.• Regional Changes in Average Household Size
1��0 - Z000
2000 - 2010
Person) I Granvi
Orang�
C�;
rham
�o
1� ��1
Chatham
fi4
so� Wake
�
Lee �
421 //
/.�. Ha�nCl�l fu"r.
19
Vance
,
� �
u
Franklin
Jahnston '\
L
� ��
,,���
f'
Complete 540:
Regional Demographics
Househa�d Size Cha�ge
Int�rstates
/�� �JS Routes
� FLUSA �oundary
� County �oundary
Percent Household �ize Change
+ -4.2°!o to -2.5%
-2.4°/a to -1 %
-Q.9% t0 1 %
a.1%to2.5%
i 2.6% to 4%
rv
W�E
�r
e
Q 20 40
I i I i I
Miles
INTEVtNpTIONAL

FLUSA Trends
As discussed previously in this document, an average household size greater than two can indicate that
there are dependent children in the household. In addition to being an indicator of a greater number of
trips per day, the presence of children within the household may increase the perceived importance of
school quality in home buying decisions relative to other counties in the CSA. All counties within the
FLUSA experienced an increase in household size, indicating the demand for high quality schools is likely
higher in these areas.
The average household size in Harnett County was the highest within the FLUSA in the 1990 and 2000
Censuses (see Table 9). However, Johnston County had a larger average household size than Harnett
County in the 2010 Census. Zones H2 and H3 had declining average household sizes while Zone H4 had a
consistently increasing household size (see Table 9 and Figure 8). Zone H1, which is included in the
FLUSA, had a slight increase in household size from 1990 to 2010.
The average household size in Johnston County grew between 1990 and 2010, increasing by 6 percent
during that time. The average household size is highest in Zone J1 and Zone J2, which are part of the
FLUSA and adjacent to Wake County.
The average household size in Wake County grew between 1990 and 2010, albeit more slowly than
either Johnston or Harnett County. As depicted in Figure 8, the household size in Wake County at the
Census region level varies greatly in each of the decennial censuses. In Zone W1, the urban core of the
City of Raleigh, the household size grew by the largest margin in the county between 1990 and 2010.
The highest average household sizes are in Zone W4, Zone W6, and Zone W7.
Table 9: Averaae Household Size in the FLUSA Counties
Harnett
Zone H1
Zone H2
Zone H3
Zone H4
Johnston
Zone J1
Zone 12
Zone J3
Zone J4
Zone J5
Wake
Zone W1
Zone W2
Zone W3
Zone W4
Zone W5
Zone W6
Zone W7
1990
2. 60
2.79
2.55
2.84
2.73
2.55
2.68
2.63
2.53
2.49
2.55
2.55
2.48
2.48
2.57
2.63
2.46
2.77
2.76
2000
2.61
2.73
2.50
2.81
2.77
2.58
2.72
2.70
2.54
2.47
2.58
2.59
2.60
2.51
2.59
2.68
2.42
2.77
2.79
2010
2. 68
2.80
2.47
2.74
2.93
2. 70
2.80
2.84
2.60
2.60
2.69
2.61
2.67
2.50
2.48
2.78
2.34
2.82
2.78
% Change 1990-2010
3
<1
-3
� -4
J� �
6
4
8
3
4
5
2
8
<1
-4
6
-S
2
<1
Zone W8 2.74 2.70 2.73 <-1
Source: US Decennial Census, 1990, 2000 and 2010, Summary File 1, Table H1
Notes: 1) Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010. 2) FLUSA Census regions are shown in bold.
2�

Overall, average household size for counties in the FLUSA has grown during the last 20 years. In Harnett
County, average household sizes are highest along the borders with Wake and Cumberland counties.
The average household size in Johnston County is higher along the Wake County border, with lower
household sizes in the central and eastern parts of the county. Lower household sizes in Wake County
occurred in the middle and western parts of the county. Higher household sizes occurred in the northern
and southern portions of the county. Wake County zones within the FLUSA showed various trends in
household size, with most (Zones W1, W4, and W6) increasing while others (Zones W3 and W8)
decreased.
21

Figure 8: FLUSA Changes in Average Household Size
�nnn nnnn
� �m�plete 54(� Demc�graphics
Household Size Ch�.nge
Interstates
i� US Rautes
� FLUSA Boundary
� County Boundaries
Census Region Boundaries
Censws Regi�ons
Percent Household Size Change
� -4% t0 -2.5%
-2.4% tt7 -1 %
-0. 9 °/a to 1 %
1.1'%t03%
i 3.1 % to �.7%
22
Census Bloek Group data was aggregated into
Census Regions for the purposes of 4his analysis.
Census Regions were created by combining 1990,
2000, anc� 2010 Census Block Groups. The regions
were create� to follow Block Group Boundaries ihat
did not change over the 20 year period.
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Miles
I N T E R N A T I 0 N A L

Employment
Regional Trends
Historical employment data collected by the North Carolina Department of Commerce shows that the
number of people employed in the CSA increased from 1990 to 2015 (see Table 10 and Figure 9).
Between 1990 and 2015, regional employment grew by 72 percent, or about 422,158 jobs. This growth
was most dramatic between 1990 and 2000, with 33 percent employment growth during this period.
Growth between 2000 and 2010 was more modest at 14 percent. However, this slower employment
growth may be attributed, in part, to the 2008 economic downturn. During the five-year period between
2010 and 2015, employment grew by 12 percent, a 2 percent annual average.
Table 10: Average Annual Employment
� 1990 2000
Harnett
Johnston
Wake
Chatham
Durham
Franklin
Granville
Lee
Orange
Person
Vance
30,179
42,787
248,082
21,445
99,302
17, 945
18, 746
20,162
52,026
15,653
18,701
1990-
2010 2015 2015
Growth
FLUSA Counties
40,831 43,253 46,788 16,609
62,432 73,576 83,732 40,945
358,674 440,623 514,344 266,262
Remaining CSA Counties
26,179 28,033 31,336 9,891
119,017 131,566 148,179 48,877
23,709 24,903 27,344 9,399
21,599 24,716 27,132 8,386
23,723 23,633 24,115 3,953
63,423 65,332 70,757 18,731
17,430 16, 383 16,911 1,153
18,933 16,332 16,548 -2,153
/ 1990-2015 County
Growth Employment
1990 - Growth as % of
2015 CSA Employment
Growth
55
96
107
46
49
52
45
20
36
8
-12
Regional 585,028 775,950 888,350 1,007,186 422,158 72
Total
Source: North Carolina Department of Commerce, Labor & Economic Analysis Division
Notes: 1) Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010, 2) County percentages have been subject to rounding
4
10
63
2
12
2
2
1
4
0
-1
Generally, areas with job growth tend to also experience population growth. Historic employment data
in the CSA follows similar patterns to both population and population density. Wake County captured 63
percent of regional employment growth from 1990 to 2015 and experienced 107 percent employment
growth during that time. As shown in Table 10, this is much higher than any other county in the region.
This growth was steady throughout the period analyzed. Between 1990 and 2000, employment in Wake
County grew by 45 percent. Growth continued at a more modest rate (23 percent) between 2000 and
2010. This growth continued, and employment grew by 15 percent between 2010 and 2015. Historic
employment data shows that Wake County continues to be a place of employment growth and these
trends suggest that this will continue in the future.
Other counties in the CSA experienced high employment growth during this period. In addition to Wake,
Franklin, Harnett, and Johnston counties also experienced employment growth of 50 percent or more
between 1990 and 2015.
23

Vance County is the only county in the CSA region to experience a decline in employment. Lee and
Person counties experienced comparatively low growth, 20 percent and 8 percent, respectively.
If past employment trends continue, many of the counties in the CSA will continue to experience
employment growth. Historic data shows a pattern of employment growth in the CSA region between
1990 and 2015. Historic trends concentrate employment growth in Wake County. Other counties with
sustained employment growth include Harnett, Johnston, and Franklin. These trends have continued
over 25 years and there is no evidence indicating these trends will change.
FLUSA Trends
The North Carolina Department of Commerce releases employment data at the county level, therefore
the employment data cannot be aggregated for the Census regions created for this memo. However, the
three FLUSA counties, Harnett, Johnston, and Wake, had the highest percent job growth within the CSA
between 1990 and 2015. This suggests continued population growth in the region.
24

Figure 9: Regional Average Annual Employment
1990
Ora�nge
Chath�am
Person Granvill
Vance
2000 � '
158
501
r
Orange ; � Franklin
�J� _
1 B 401
��rham
� �:
�' �� �
� �.
Chatham
Lee � �
izi
Harnett
� @,
Jah nston
Granvi�i
Var�ce
v�, � ��
Franklin
��rharx� ,-��J,r
�o
m' � '�;p
._
�
- �-
%� Q�' �?sa1
f" _ _''-�
,�---
Wake � ' �ohnstoc�
Lee � j
izi
Harnett
40
25
Complete 54�:
Regional Demographies
Total Emplo�Tmer�t �hange
Intersta�es
/�' US Routes
� FLUSA Boundary
0 Cour��y Boundary
Total Employment
15,653 - 25,aoa
25,001 - 50,OOQ
50,001 - 100,flOQ
� 100,001 - 250,(700
i ��o,oQ� - �� �,aoo
N
N'� E
0 20 40
I i I i I
Miles
INTERNpTIOMAL

Educational At�tainment
Regional Trends
Educational attainment is a notable feature in the region as a whole, and particularly in those counties
where major universities are located. The measure of educational attainment is the percentage of the
population aged 25 or over with a Bachelor's degree or higher. North Carolina's statewide average for
this statistic was 28 percent in 2014. Within the CSA, in Chatham, Durham and Wake counties, 56
percent, 46 percent, and 48 percent of their respective populations met this benchmark of educational
attainment in 2014. While the major universities in the CSA are the University of North Carolina at
Chapel Hill, Duke University, and North Carolina State University, other universities in the CSA include
North Carolina Central University, Shaw University, Meredith University, Saint Augustine's University,
William Peace University, Barton College, Campbell University, and North Carolina Wesleyan College.
FLUSA Trends
Within the FLUSA counties, Harnett and Johnston Counties fall below the statewide average, while Wake
County is well above the statewide and regional averages. All of the CSA counties have seen
improvement in Educational Attainment since 1990, again, with the highest results in the three counties
that host major universities. A more granular look at educational attainment for the FLUSA area shows
that it falls below the overall Wake County average, but well above the Harnett and Johnston County
averages, based on data from the 2014 American Communities Survey.
Table 11: Educational Attainment Trends
Harnett
�
Johnston
Wake �
FLUSA
10
11
35 I
Chatham Zp
Durham 33
Franklin 9
Granville 10
Lee 14
Orange 46
Person g
Vance � 9
FLUSA Counties
13 19
16 20
44 � 48
36
Remaining CSA Counties
28
I 40
� 13
13
17
52
10
11
� Change 1990-2014
+9
� +9
+13
� N/A
All CSA Counties 27 34 I 40 I + 13
North Carolina 17 � 22 � 2g � +11
Sources: US Decennial Census, 1990, 2000, Summary Table 3; US Census 2014 American Community Survey, Five Year, Table 51501
26

1f IR-�i'. .� �.���-
Regional Trends
Median income varies greatly throughout the region. However, most counties in the CSA experienced
high growth in median household income between 1990 and 2014, correlating with the population
growth during this time. During the 2010 Decennial Census, the Census Bureau shifted median income
data from the Decennial Census to the American Community Survey. Therefore, the period for median
income changed from 1990-2010 to 1990-2014.
As shown in Table 12, Wake, Orange, and Chatham counties had the highest median household incomes
in 2014, while Vance County had the lowest median household income of any CSA county (Table 12).
Over 24 years, the Harnett County median income grew by 104 percent. However, Wake County had the
highest median household income in the CSA during each reporting period.
Table 12: Median Income Growth
FLUSA Counties
Harnett $21,743 $35,105 $44,417 $22,674
Johnston $25,169 $40,872 $49,799 $24,630
Wake $36,222 $54,988 $66,579 $30,357
Remaining CSA Counties
104
98
84
Chatham $28,539 $42,851 $57,140 $2g�601 100
Durham $30,526 $43,337 $52,038 $21,512 70
Franklin $25,049 $38,968 $42,763 $17,714 71
Granville $26,488 $39,965 $49,655 $23,167 87
Lee $26,419 $38,900 $46,309 $19,890 75
Orange $29,968 $42,372 $57,261 $27,293 91
Person $25,625 $37,159 $43,381 $17,756 69
Vance $21,555 $31,301 $34,075 $12,520 58
Source: US Decennial Census, 1990, 2000, Summary File 3; Table P053; US Census 2014 American Community Survey, Five Year, Table 619013
Notes: Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010. 1) Measured in 1989 US dollars. 2) Measured in 1999 US Dollars. 3)
Measured in 2014 inflation-adjusted dollars
FLUSA Trencls
The US Census Bureau calculates median income by census tract. Since the sub-county regions are an
aggregation of census block groups (a smaller geography within the census tract geography) and income
is a median value, calculating an average is not possible. However, Harnett and Johnston counties,
within the FLUSA, are among the top three counties in the CSA in median income growth between 1990
and 2014). In the CSA, Wake County had the largest median household income increase from 1990 to
2014 at $30,357.
In addition to Median Income, it is useful to examine Median Earnings by Level of Education for further
insight into the income trends affecting the FLUSA. These data, shown in Table 13, demonstrate that
27

residents of all the FLUSA jurisdictions who have a Bachelor's degree have markedly higher incomes,
with an additional earnings premium for those with graduate or professional degrees. This phenomenon
is most pronounced in Wake County, where nearly 1 in 5 residents 25 or over have a graduate or
professional degree, and the difference in earnings is over $32,000 compared to those without a
Bachelor's degree, and over $15,000 compared to those with a Bachelor's degree.
Tal�le 13: Medran Ec�rnir�gs by Ed�ca'rrcii�rl Attcinn�enr, FI_[JSA Counties, 201�?�*
Harnett
Median Percent of
I Earnings County
Population
25+
Johnston
Median Percent of
Earnings County
Population
25+
Totalfor
Adult
Population $31,348 100 $32,965
25 Years+:
Less than
high school $15,971 16 $ 19,469
graduate
High school
graduate/ $27,670 31 $ 30,124
equivalency
Some college
or associate's $31,997 34 $ 34,154
degree
Bachelor's
degree $36,439 12 $46,450
Graduate or
professional $56,415 7 $51,073
degree
US Census 2014 American Community Survey, One-Year Average, Table 51501
Note: Table results may not add up to 100 percent due to rounding
28
Wake
Median Percent of
Earnings County
Population
25+
100 $40,821 100
13 $16,970 S
31 $27,175 17
36 $34,881 27
15 $51,365 31
5 $66,976 18

Figure 10: Regional Median Income
Per
199a
Orange
70 �
��
Chatham
sa
501
�
l�ee
J GranvilV
Vance -
ii
,sa �
�
r-.�--.
R�� �rar�klin
� 4ot
fhBRl
��� FD
�"'�,N' �+'
\� .�i 2fi4
- .J.�.
VWake
Ham�tt
�
Jahnston
29
Car��l��� 54�:
l��g�a�nal I� emograp�h�cs
H€�usehold I�.come �hamge
c�
Intersta�es
�� US ROUtBS
� F�USA Bnurodary
� Gounty Bounc�ar�r
I�edian Household I�comme
���,���.a� - �z�,00c�.Qo
�z�,oao.o� � ���,00�.oc�
� $3�,040.Q1 - $45,00(�,DO
- �45,OU4.01 � $55,DO�.a�d
� $�a,Q(?0.01 � $67,00�.0�1
�
w�e
s
Q �0 Q�
� 1 � 1 �
Miles
I�ITERNATI�WAL

School Quality
The quality of a school district is an important factor driving household location decisions and an
indicative factor of growth in a region. Jack Dougherty, an associate professor of Educational Studies at
Trinity College in Hartford, Connecticut, researched how public school quality helps to drive suburban
growth:
..."shopping for schools" clearly became an important family strategy for upward mobility, as
higher-salary positions increasingly depended on educational credentials, which in turn relied on
the status of one's public school system. During the course of the twentieth century, suburban
families became more conscious of this equation: buying a home in the "right" neighborhood in
order to send their children to a"good" public school, would increase their odds of being
accepted to a"top-ranked" college, and help them to land the "perfect" job.6
Other researchers have shown the strong correlation between school district quality and the value of
housing. This is revealed in the high demand for housing in good school districts. Theodore Crone, an
Economist with the Federal Reserve Bank of Philadelphia, noted, "Home buyers seem to evaluate the
quality of public education at the district level."' Finally, other researchers have noted that "[i]n towns
where it is easy to build more housing, better quality schools do not lead to higher property values.
Instead, they lead to more real estate development." Based on this assessment, areas that are
perceived to have higher quality schools would be expected to have increased development as a result.
Since most school districts in North Carolina conform to county boundaries, homebuyers with school-
aged children are therefore likely to consider school quality by county when choosing a residence to
rent or buy.$
Additional research indicates that higher test scores are a factor that affects housing prices and can
increase housing costs in an area or make the area more desirable for future development. In her
research, Sandra E. Black found that housing prices rise 2.5 percent for a 5 percent increase in test
scores.9 A study looking at the relationship between test scores and residential housing prices in North
Carolina determined that the housing market places higher values on property in school districts with
higher test scores at an average of 3 percent to 4 percent higher than a property with average test
scores. Test scores play a pivotal role in the perception of school quality and have a strong influence on
housing value.lo
Regional Trends
As with many of the factors discussed in this document, four-year graduation rates by school system
vary throughout the region, as shown in Table 14. Lee County Schools had the highest graduation rate in
the region, followed closely by Johnston, Orange, Chatham and Wake. School systems with the lowest
four-year graduation rate are Person and Vance counties.
6 Dougherty, Jack. "Shopping for Schools: How Public Education and Private Housing Shaped Suburban Connecticut." Journal of
Urban History 28, no. 2(March 2012): 205-224.
� Crone, Theodore M. "Capitalization of the Quality of Local Public Schools: What Do Home Buyers Value?" Working Paper No.
06-15, Federal Reserve Bank of Philadelphia. August 2006.
8 Black, Sandra E. "Do Better Schools Matter? Parental Valuation of Elementary Education." The Quarterly Journal of Economics,
Vol. 114, No. 2(May 1999): 577-599.
9 Martinez, Erika. "Do Housing Prices Account for School Accountability?" Duke University, November 2010.
10 NC Department of Public Instruction, Accountability Services Division. lune 4, 2008.
30

Table 14: Four-Vear Graduation Rate by School System
�e .e •
FLUSA Counties
Harnett County Schools 81.5
Johnston County Schools 88.8
Wake County Schools 86.1
Remaining CSA Counties
Chatham County Schools 87.3
Durham Public Schools 80.7
Franklin County Schools 82.6
Granville County Schools 83.8
Lee County Schools 89.1
Orange County Schools 88.0
Person County Schools 78.9
Vance County Schools 77.5
Regional Average 84.0
Sources: North Carolina State Board of Education, Accountability Services Division, 2014-2015
Note: Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010
In North Carolina, state end-of-grade (EOG) tests are administered to students in third through eighth
grade and measure proficiency in a variety of core subjects. Students must pass with a"proficient" or
better to move to the next grade level. The percent of students scoring proficient or above on EOG
exams is a cumulative score of English language arts (ELA), mathematics, and science. The State Board of
Education defines proficient as a score of three or above on the EOG exams.
Table 15: Percentage Average Statewide Test Scares Proficient or Above
.. � . . . ...
• • . .�-
Math and Reading Testing, Grades 3-8
FLUSA Counties
Harnett County Schools 45
Johnston County Schools 58
Wake County Schools 66
Remaining CSA Counties
Chatham County Schools 46
Durham Public Schools 43
Franklin County Schools 49
Granville County Schools 43
Lee County Schools 51
Orange County Schools 60
Person County Schools � 54
Vance County Schools 43
Regional Average 52
Sources: North Carolina State Board of Education, Accountability Services Division, 2014-2015
Note: Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010
31

Wake and Orange counties have comparatively higher test scores in the region for most subjects and
age groups. Wake County scores were between 14 percent higher than the regional average across
grade levels (see Table 15). Other school systems with comparatively high test scores are Johnston and
Person counties.
Another educational metric that is commonly referenced as an influence on location decisions is the
Scholastic Aptitude Test (SAT) composite score (combined scores of math, critical reading and writing).
However, the SAT score only represents college bound students, so it is not a comprehensive score
representative of all students in the district. As shown in Table 16 and Figure 11, among the 11 CSA
counties, Wake County schools had the highest average SAT score in 2015. The average SAT score for
schools in the region was 1,415 (a perfect score being 2400). SAT scores for the Wake County School
District were 11 percent higher than the regional average. Other counties in the CSA with average scores
higher than the CSA average were Orange and Johnston counties.
FLUSA Counties
Harnett County Schools 423 39 467 465
Johnston County Schools 892 41 500 497
Wake County Schools 6,400 67 540 525
Remaining CSA Counties
Chatham County Schools 337 65 481 474
Durham Public Schools 1,177 60 469 476
Franklin County Schools 212 40 476 477
Granville County Schools 245 46 485 474
Lee County Schools 223 37 482 474
Orange County Schools 307 62 522 519
Person County Schools 114 44 451 437
Vance County Schools 234 57 427 424
Regional Average - 51 482 477
Sources: North Carolina State Board of Education, Accountability Services Division, SAT Report 2015
Note: "%o Tested" refers to the percentage of students in the school district that took the SAT in 2015
442 1374 �
473 1470
504 1569
457
453
457
445
449
498
427
410
456
�
1412
1398
1410
1404
1405
1539
1315
1261
1415
School quality is an important factor for households in making location decisions, particularly for
households with children. Based on school quality indicators, such as four-year graduation rates, SAT
scores, and state EOG test scores, the counties that would be most desirable for homebuyers are Wake,
Orange, and Johnston. If these trends continue, these areas would be more likely to attract new
households and new development, thus more likely to experience higher population growth than the
other counties in the region.
32

Figure 11: Average Composite SAT Score by High School for CSA Region
��m�lete �4�: Regio�.al I��magra��.ics
S��T Sc��es
School Level SA7 Scores
� 1146 - 1230
• 1231 - 135�
� 1351 - 145�
� 1451 - 1 �50
* 15�1 - �719
Onterstates
�� �1S R�utes
� �LU�A Boundacy
� Ct�a�nty Bounda�r
33
M
w�e
�
a io za
I s o � i
�t� i��.
IN4@RN�ATIONAL

FLUSA Trends
As school systems in North Carolina are organized by county, the educational data is presented by
county. Data on school quality is presented at the county or school district level or the individual school
level, not at a Census geography level.
Harnett County Schools have the lowest four-year graduation rate, with almost 82 percent of students
graduating high school in four years (see Table 14). Overall, Johnston County has the highest four-year
high school graduation rate, at nearly 89 percent. Wake County Schools have the second highest
graduation rate, with 86 percent of students graduating high school in four years.
EOG scores for school systems with boundaries that overlap the FLUSA are presented in Table 15.
Harnett County ranks below the CSA average while Wake and Johnston are above the CSA average.
In Figure 12 average SAT test scores are depicted by high school location. The schools with the highest
average SAT scores are in western and central Wake County. Scores are lowest in southern and eastern
Wake County. Johnston County Schools had the second highest combined SAT score of the FLUSA
counties (see Table 16). Scores are highest in central and western Johnston County. Harnett County
Schools had the lowest average combined SAT score of the FLUSA. Average combined SAT scores in
Harnett County are almost 200 points lower than Wake County Schools and 100 points lower than
Johnston County schools. Scores at high schools in northern and southern Harnett County are the
highest in that school system.
There are clear distinctions in school quality of the FLUSA counties. Wake County Schools SAT scores and
state EOG test scores are the highest of the FLUSA counties. However, Johnston County Schools had the
highest high school graduation rate in the FLUSA, with Wake County Schools and Harnett County Schools
following behind. Within the FLUSA counties, the data suggests that Johnston and Wake counties have
the more desirable school systems for potential homebuyers, which suggests these counties would be
more likely for future development.
34

Figure 12: SAT Scores by High School in the FLUSA Counties
35
Comp�ete 5�0 �ducat�on
S1�.T' Scores
Interstat�s
�� US Rout�es
� County Boundarues
� F�USA Boundary
School Level SAT Scores
• 1317 - 1352
• 1353 - �425
• 1426 - 1496
� 1497 - 1589
. 1590 - 1719
Mf�
,v 4 E
5
0 1(1 2a
Miles
I M T E R N A T I 0 N A L

Average Commute
Regional Trends
Convenient access to jobs is another important factor in household location decisions within a region.
Areas with shorter commutes may be more attractive for potential homebuyers, as workers will spend
less time commuting. However, regional growth patterns in most metropolitan areas do not indicate
that commute times are a primary driver of location decisions. While it may seem counter-intuitive that
households would choose to live where commute times are longer, research suggests that within a
reasonable range of commute time, households will choose locations based more on other preferences,
such as school quality, neighborhood quality or other factors. In their summary of research on the
impacts of transportation on land use, the National Research Council noted the following:
"Research on commuting patterns within the current distribution pattern of jobs and
residences in the Los Angeles metropolitan area, however, indicates that commuting
trips are two-thirds greater than would be required if workers were located in
neighborhoods that minimized their commutes (Small and Song 1992). This indicates
that a key assumption of location theory does not hold in practice. The excess
commuting that occurs may be explained by preferences for neighborhoods with low
crime rates or amenities such as schools; the difficulty of minimizing commutes for both
workers in dual worker households; and other influences, such as racial discrimination
(Giuliano and Small 1993; Mills 1994),11'.
The Census Bureau tracks a variety of information about trips to and from work. The comparisons
among counties in the region are revealing. Due to changes in reporting for the 2010 Census, the Census
Bureau began releasing commute information in the American Community Survey. Therefore, reporting
years for commute times are 1990, 2000, and 2014.
Between 1990 and 2000, the average commute time for residents in CSA counties increased by 4.8
minutes, and remained relatively stable between 2000 and 2014 (see Table 17 and Figure 13).
Overall, between 1990 and 2014 commute times in the CSA increased by 19 percent. Commutes in every
CSA county increased from 1990 to 2014. However, commute times decreased between 2000 and 2014
in Harnett, Johnston, Wake, Franklin and Lee Counties. Overall, Franklin County reported the smallest
change in commute time between 1990 and 2014. Vance and Granville counties experienced the
greatest increases in commute times during this period.
In 2014, commute times in five counties are below the regional average of 28.2 minutes. These counties
are Durham, Lee, Orange, Vance, and Wake. Proximity to the Raleigh urban core and shorter commutes
than the regional average could potentially increase the desirability of Wake County for potential
homebuyers.
11 National Research Council 1995
36

Table 17: Averaqe Commute Times in Reqional Counties
Average % Average % Average %
� Travel Time Difference Travel Time Difference Travel Difference •
to Work from 1990 to Work from 2000 Time to from 2014 ••�
(Min) Regional (Min) Regional Work Regional � �
Average Average (Min) Average
FLUSA Counties
Harnett 25.3 7 30.8 10 30.2 7 � 25
Johnston 26.5 12 32.3 15 31.2 10 18
Wake 22.3 -6 26.4 -6 25.7 -9 15
Remaining CSA Counties
Chatham 24.4 3 28.9 3 29.3 4 � 20
Durham 20.5 -14 23.0 -18 23.6 -16 15
Franklin 29.4 24 34.8 24 32.1 14 � 9 �
Granville 23.9 1 28.6 2 30.5 8 � 28
Lee 22.2 -7 25.8 -8 25.7 -9 16
Orange 21.2 -10 23.7 -16 24.3 -14 14
Person 26.0 11 30.9 10 32.6 16 26
Vance 19.2 -19 24.1 -14 25.0 -11 30
Regional 23.3 - 28.1 - 28.2 - 19
Average
Source: US Decennial Census, 2000; US Census 2014 American Community Survey, Five-Year Average, Table 808303
Note: Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010. 2) Census data presented in terms of "mean" travel is referred to as "average"
in this table.
37

Figure 13: Regional Changes in Average Commute Time
38
�amplete 540:
Regional Demagraphics
Averag� Camrnute Change
I nte cstates
�— US Routes
� FLUSA Boundary
� Courtty Boundary
Average Commute
19.2-22NIin
22 - 24.9 Min
25 - 27.9 Min
� 28 - 30.9 Min
i 31 - 34.8 Min
�n
N Y f
0 20 40
I i l e I
hriiles
INTERNATIONAL

FLUSA Trends
Average commute time is an indicator of potential growth, as a short commute is often attractive to
potential homebuyers. Commutes at the sub-county level may show the specific areas of potential
growth within the FLUSA. Every Census region experienced an increase in average commute time
between 1990 and 2014 (see Table 18 and Figure 14).
Of the three FLUSA counties, Harnett County had the second longest average commute. Overall, the
average commute time in the county was 8 percent longer than the CSA commute in 2014. Within
Harnett County, Zone H1 had the longest commute time from 2000 through 2014. In 2014, the average
commute in Zone H1 was 16 percent longer than the regional average. Zone H2 had the shortest
average commute in 2014, with a commute time five percent shorter than the regional average.
Johnston County had the longest average commute of the FLUSA counties, with an average commute
that was 11 percent longer than the regional average in 2014. FLUSA Zones J1 and J5 had commutes that
were consistently longer than the average regional commute in 1990, 2000, and 2014.
Average commute times in Wake County were the shortest within Zone W1. This is the urban core of
Raleigh, therefore, commutes would be expected to be short when compared to other parts of the
region. Commute times are also consistently short in Zone W2, Zone W3, and Zone W5, which surround
the urban core. Census regions further from Zone W1 and the City of Raleigh urban core had commute
times that are longer than the regional averages in 1990, 2000, and 2010. These zones, Zone W6, Zone
W7, and Zone W8 had average commute times that were between 7 and 13 percent longer than the CSA
average commute time. Zone 4, which is also in the FLUSA, had commute times that were longer than
the CSA average in 1990 and 2000, but less than the CSA average in 2014.
39

Table 18: Averaqe Commute Time in FLUSA Counties
Average % Average %
Travel Difference Travel Difference
Time to from 1990 Time to from 2000
Work Regional Work Regional
(Min) Average (Min) Average
FLUSA Counties
Average %
Travel Difference
Time to from 2014
Work Regional
(Min) Average
Harnett 25.3 9 30.8 10 30.2 8 19
Zone H1 27.1 16 32.7 16 32.6 16 21
Zone H2 22.0 -6 27.0 -4 26.7 -5 22
Zone H3 25.6 10 30.5 9 31.6 13 23
Zone H4 28.2 21 32.5 16 29.9 6 6
Johnston 26.5 14 32.3 15 31.2 11 18
Zone J1 25.8 11 32.8 17 30.8 10 20
Zone J2 31.3 34 36.4 30 35.0 24 12
� Zone J3 24.9 7 29.2 4 28.8 3 16
Zone J4 24.8 6 28.5 <1 26.7 -5 8
Zone J5 27.6 19 33.0 17 32.0 14 16
� Wake 22.3 -4 26.4 -6 25.7 -8 15
Zone W1 19.3 -17 21.7 -23 21.8 -22 13
Zone W2 21.1 -9 24.4 -13 23.5 -16 11
r Zone W3 22.3 -4 25.6 -9 25.2 -10 13
I
Zone W4 23.8 2 29.1 4 26.7 -5 12
Zone W5 21.5 -8 24.5 -13 23.8 -15 10
Zone W6 26.0 12 31.2 11 30.4 8 17
Zone W7 26.6 14 30.5 9 28.8 3 8
Zone W8 26.3 13 34.0 21 30.1 7 14
CSA 23.3 28.1 28.2 19
Regional
Source: US Decennial Census, 2000; US Census 2014 American Community Survey, Five-Year Average, Table B08303
Notes: 1) Raleigh-Durham-Chapel Hill, NC CSA Counties, 1990-2010. 2) FLUSA Census regions are shown in bold.
Average commute times have risen between 1990 and 2014 in every Census region in the FLUSA. While
the average commute time for each zone rose, trends show longer commute times in Johnston and
Harnett counties and shorter commute times in Wake. This suggests that Wake County may be a more
desirable location for potential homebuyers.
40

Figure 14: Regional Changes in Average Commute Time
41
mpXete 540 Demograph�.cs
�-�verage Comr�ute Change
Inters�ates
�- US R�outes
� County Boundaries
� FLUSA Boundary
Census Region Bouo�daries
Census Region Bau�daries
Census Regior�s
Average Commute
19 - 22 Min.
23 - 25 Min.
�� �6 - �8 Min.
i 29 - 31 Min.
� 32 - 35 Min.
Census glock Group data was aggregated into
Census Regions for the purposes af this analysis.
Census Regions were created by combining 1990,
2000, and 2D10 Census �lo�k Groups. The regions
were created to follow Block Group Boundaries that
did not change over the 20 year period.
N
W�E
1�
s
Q �9 24
I i I i I
Miles
I N T F R N A T I 0 N A L

Regional Economic Drivers and Re�ated Trends
A few specific trends that describe the region's economic drivers and relate to additional growth
dynamics add further insight into the growth history and outlook of the Research Triangle Region.
Research Triangle Parl<
Universities are a source of innovation. The focus in the Research Triangle Region on partnership
between Universities, public sector research entities, and private sector innovators has led to, "... sharec
resources, groundbreaking research, and graduates working at the forefront of their fields."12 The idea
of harnessing the opportunities presented by the three founding universities of RTP — NC State
University, Duke University, and UNC-Chapel Hill — to attract private and public sector research jobs has
been a key driver of regional economic growth and success. Results include high educational attainment
of regional residents, higher earnings than state and national averages, and low unemployment (as
documented elsewhere in this memo).
In Research Triangle Park, biotechnology and information technology are major industries within RTP
tenants, along with business, financial and insurance services, and specialized firms in agricultural
biotechnology, as well as instruments and advanced materials. Over 250 businesses employing over
50,000 people are located in RTP, the nation's largest research park. These RTP businesses have
received over 3,000 patents for their research and development work since 1970, and have generated
245 company start-ups. 13
Looking at Research Triangle Park and Wake County together, the major employers include multiple
healthcare systems, the State of North Carolina, IBM Corporation and Universities (Table 19).
Table 19: Employers with 2,000 or more Employees in Wake County and Research Triangle Park
Duke University and Health System
State of North Carolina
Wake County Public School System
IBM Corporation
North Carolina State University
WakeMed Health & Hospitals
Rex Healthcare
SAS Institute, Inc.
GlaxoSmithKline
Lenovo
Fidelity Investments
North Carolina Department of Health & Human Services
Sensus
City of Raleigh
Conduent Inc.
Duke Energy
QuintileslMS
Spectraforce Technologies Inc.
1z The Research Triangle Park, 2017.
13 Ibid
42
36,004
24,083
18,554
10,000
9,069
8, 943
5,700
5,616
4,950
4,200
4,000
3,800
3,691
3,673
3,300
2,700
2,600
2,600

MetLife
Wake Technical Community College
Wells Fargo
RTI International
First Citizens Bank
Grifols
Pharmaceutical Product Development, Inc. (PPD)
Verizon Business
Source: Wake County Economic Development. 2017.
Wal<e County Trends
2,600
2,547
Z,300
2,276
2,026
2,000
2,000
2,000
As the major source of employment in combination with RTP, and as the jurisdiction comprising most of
the FLUSA, Wake County's growth trends provide indicators of both the impetus for growth and the
regional growth pressures affecting the FLUSA. For example, a review of Wake County's 2016 report on
Trends and Outlook14, based on US Census, other national, and county data, provides the following
highlights:
• From 2010 to 2015, Wake County was the second fastest-growing county over 1 million in
population in the US (14 percent), second to Travis County in the Austin, Texas region (15
percent), and ahead of Mecklenburg County, North Carolina (12 percent).
• After accounting for births and deaths, Wake County saw 43 net migrants daily, on average,
from 2010 to 2015. Of these migrants to the county, on average, 32 arrived from other U.S.
jurisdictions and 11 arrived from other countries.
• In 2014, the percentage of Wake County adult residents with a bachelor's degree or higher
ranked 5th nationally among 36 peer counties with similar population size and growth rate.
• Unemployment among Wake County residents has been consistently below state and national
averages (see Figure 15).
• In 2014, the top occupation in Wake County was educational services, health care and social
assistance, accounting for 20.9 percent of employed residents. The second-highest occupation
at 17.8 percent was professional, scientific, management and administrative.
• A heat map of 2015 residential and commercial building permits shows the major concentration
of development activity in a band from RTP to Fuquay Varina in western and southern Wake
County.
• Starting in 2012, there has been a surge in multifamily housing permits in Wake County. In 2016,
37 percent of Wake County households rented, and a substantially higher percentage of renters
than homeowners spend more than 30 percent of their income on housing.
14 Wake County, 2016.
43

Figure 15: Wake County, State of North Carolina and U.S. Unemployment Rates, 2007 to 2015
12.0
10.0
8.0
6.0
4.7
i�6
4.0
3.5
2.0
0.0
2007
10.9
8.3 '
2008 2009 2010 2011 2012 2013
Wake #—NC —�USA
Source: Bureau of Labor Statistics, Department of Labor
2014
5.8
5.3
4.7
2015
A final trend that has relevance to Complete 540 is the trend in daily Vehicle Miles Traveled (VMT) in
Wake County. The VMT data show large increases from 2000 to 2007 at the county, state, and national
levels (Table 20). However, between 2007 and 2014, North Carolina VMT increased by only 4 percent
and national VMT actually decreased slightly. During the same time period however, Wake County saw a
25 percent increase in VMT, and a 65 percent increase from 2000-2014.
Table 20: Vehide Miles Traveled Data for Wake County, North Carolina, and the U.S.
Wake County 6,203 8,219 10,259 33
NC 89,504 103,598 108,012 16
USA 2,767,363 3,049,027 3,040,220 10
Sources: USDOT FHWA Highway Statistics Table VM-2; NCDOT North Carolina Traffic Crash Facts
25
4
0
65
21
10
Conclusion
Growth patterns and trends at both the CSA and FLUSA level show a pattern of sustained population and
employment growth and increases in population density in addition to a concentration of recent growth
within Wake County. The other FLUSA counties (Harnett and Johnston) also show strong growth (based
on Census data) and are projected to increase in population through 2035. Growth indicators at the CSA
level, namely employment, average household size, educational attainment, median income, and school
44

quality indicate that growth will very likely continue in the counties comprising the project FLUSA.
Analysis of population, population density, average household size, school quality, and commute in the
FLUSA counties at the sub-county level further indicates growth is likely within the FLUSA.
Based on population trends, employment, median income, school quality and commute times, Wake
County will most likely continue to capture a high amount of growth in the future. Wake County leads in
these indicators, and population forecasts suggest that past population trends and regional growth
dynamics will continue into the future.
Within FLUSA counties, growth indicators suggest that much of the future population growth will occur
within Wake County. Population densities are still relatively low outside of the urban core of the City of
Raleigh, leaving ample room for additional growth in the suburban and rural portions of the county.
With higher median household income and a greater perceived school quality than neighboring
counties, many new residents and potential homebuyers would be attracted to Wake County. School
quality appears to be highest in central, western and northern Wake.
Northern Harnett County and eastern Johnston County appear to have some positive growth factors,
particularly the relatively low population densities and increases in employment and median income.
Johnston County appears to have a higher quality school district, and would therefore be more likely to
attract growth, relative to Harnett County.
Analysis of these growth patterns and trends indicates that the CSA region will continue to grow and
that a sizeable portion of that growth is likely to occur within Wake County. The FLUSA area has both
positive and negative indicators for growth compared to the other zones in the three-county study area.
In particular, population density is relatively low in the FLUSA, suggesting that there may be land
available for development. Indicators of school quality, however, is somewhat lower in the FLUSA than
in other parts of Wake County suggesting that other parts of Wake may have higher relative growth
pressures in the future. Additional housing trends in Wake County indicate that 37% of homeowners
rent, substantially more renters pay more than a third of their income for housing, and there has been a
surge in multifamily home construction since 2012. Together, these trends suggest there may be a
market for higher-density housing in more affordable areas of the region such as portions of the FLUSA.
Underscoring the evident growth trends in the region, and in Wake County in particular, are a set of
economic drivers that point to sustained growth. The unique regional partnership of universities and
public- and private- sector research entities has fostered innovation, business growth, and hundreds of
start-up companies. The RTP and the state government are key economic engines that steadily attract
new residents to Wake County and the Research Triangle region.
45

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47