Perkiomen Valley School District Enrollment

Transcription

Perkiomen Valley School District
Enrollment Projections
Perkiomen Valley School District
Prepared By
The Montgomery County Planning Commission
May 2013
Perkiomen Valley School District Board
Lori Snyder, President
Lynn Bigelow,Vice President
Gerry Barnefiher
Randy Bennett
Andrea Galambos
John King
Diane Landes
Ann Mantey
Paul Smith
Superintendent
Clifford Rogers, Ed.D.
Table of Contents
Introduction
................................................................................................................................................................... 1
School District Characteristics
Population ........................................................................................................................................................ 6
Birth Patterns .................................................................................................................................................. 8
School District Enrollment.........................................................................................................................10
Alternative School Enrollment ..................................................................................................................12
Housing Activity
Impacts of Housing on Enrollment ...........................................................................................................16
Housing Units Built ......................................................................................................................................18
Housing Units Proposed.............................................................................................................................20
Age Restricted Housing ..............................................................................................................................22
Housing Sales ................................................................................................................................................24
Cohort Progression Model ........................................................................................................................28
Projected Enrollment Summaries .............................................................................................................32
Indicators of Projection Change ...............................................................................................................34
Table of Contents (continued)
School Profiles
Introduction .................................................................................................................................................. 38
Evergreen Elementary School ................................................................................................................... 39
Schwenksville Elementary School ............................................................................................................ 40
Skippack Elementary School...................................................................................................................... 41
South Elementary School ........................................................................................................................... 42
East and West Middle Schools ................................................................................................................. 43
Conclusion
.................................................................................................................................................................... 46
Introduction
School districts can only plan for their future if they
have some idea of what that future will entail. The
number of students that will need to be served by
district facilities is the key variable that must be
understood in order to make prudent decisions.
Montgomery County and much of the region is in a
cautious period following a historic housing price
bubble and the subsequent bursting of that bubble.
Then came the Great Recession and a recovery
period that does not seem to be ending. These events
have slowed down growth in the county and in the
Perkiomen Valley School District. It was not very
long ago that many school districts were wondering
how to handle the influx of an increasing number of
students, and some were even building new schools.
Now many of those same districts are faced with a
declining school age population and deciding on the
most effective ways to utilize their facilities.
This report gives an overview of the population and
housing characteristics within the Perkiomen Valley
School District (PVSD) in order to establish the
conditions that have formed the most recent
enrollment trends. Future enrollments will depend
largely upon the following factors:

Recent and future births

Housing construction

Moves in and out of the school district

Private, charter, home, and cyber school growth

Popularity of age restricted housing construction
in the district
The following study employs the use of a Cohort
Progression Model to account for the above factors
and form projections for each grade level over the
next ten years. No model is perfect when it comes to
predicting the future, but given the right data, an
accurate projection for at least the next five years is
expected.
Projections should not be considered a final product
with the completion of the model. Additional data
and analysis, including housing and population
forecasts, characteristics of households by housing
types, geographic mobility by age cohorts, and
housing sales activity, are also presented in this study
so as to provide a useful context with the projections.
This context also provides the basis for using the
projections beyond just the next school year. The
study provides the important data points that should
be reviewed every year to determine if unanticipated
activity is occurring and how that might influence the
projections and actual enrollments down the line.
1
PERKIOMEN VALLEY SCHOOL DISTRICT
FIGURE 1: Elementary School Boundaries
29
A
GR
Lower
Frederick
L
VE
KE
PI
N
AI
M
BRIDGE RD
SKIPPACK PIKE
73
BIG RD
73
ST
å
Schwenksville
Skippack
KE
PI
Skippack Elementary
L
Schwenksville Elementary
113
VE
Evergreen Elementary
TOWNSHIP LINE RD
A
GR
Municipal Boundary
å
Perkiomen
å
29
South Elementary
113
¯
0
3,000
6,000
Base map prepared November 2012 by MCPC
2
12,000 Feet
å
THIRD AVE
Trappe
MAIN ST
Collegeville
ENROLLMENT PROJECTIONS
FIGURE 2: Middle School Boundaries
29
A
GR
Lower
Frederick
L
VE
KE
PI
BRIDGE RD
73
ST
å
SKIPPACK PIKE
73
N
AI
M
BIG RD
Schwenksville
Skippack
VE
L
KE
PI
East Middle School
TOWNSHIP LINE RD
A
GR
Municipal Boundary
113
Perkiomen
å
29
West Middle School
113
¯
0
3,000
6,000
12,000 Feet
THIRD AVE
Trappe
MAIN ST
Collegeville
3
4
School District
Characteristics
Part
Population
Birth Patterns
School District Enrollment
Alternative School Enrollment
Population
The Perkiomen Valley School District has seen
substantial growth over the past few decades fueled
by the construction of Route 422 and major
employers taking advantage of new highway access
points.
Overall, the Perkiomen Valley School District region
is forecasted to have 39,351 residents by the year
2020, an increase of 4.4 percent from 2010. This is
still a faster rate of growth than the county overall,
but relatively low compared to growth rates over the
last two decades. The housing market was booming
in the first half of the 2000s decade prompting new
construction and growth in many municipalities, but
the housing market and the economy overall
collapsed during the Great Recession toward the end
of the decade. The economic slowdown is still
holding growth back several years into the current
2010 decade.
On a municipal level, boroughs and townships within
the district have undergone significant change over
the last 30-40 years, but only Skippack and
Perkiomen Townships saw more than ten percent
growth over the last decade. Looking forward to
2020, moderate growth is expected to continue in
Skippack Township, but the remaining
municipalities are not expected to add more than 200
people. The boroughs are relatively built out and
current zoning and market realities limit how much
residential development is expected in Lower
Frederick and Perkiomen townships despite the
undeveloped land available. Additionally, household
sizes are expected to continue declining in most
places. This means that any new residential
construction would partially account for population
loss in existing homes before adding to the overall
population.
FIGURE 3: Population of PVSD, 1990-2020
45,000
40,000
35,000
Trappe
30,000
Skippack
25,000
Schwenksville
20,000
Perkiomen
15,000
Lower Fred erick
10,000
Collegeville
5,000
0
1990
2000
2010
Source: U.S. Census Bureau, except 2020 Projections (DVRPC and MCPC)
6
2020 (projected)
FIGURE 4: Population of PVSD Municipalities, 1990-2020
1990 Collegeville Lower Frederick Perkiomen Schwenksville Skippack Total 4,227 3,396 3,200 1,326 8,790 Trappe District Total
Montgomery County 2000* 1980‐1990 1980‐1990 Change Percent 821 24.1% 1,017 42.7% ‐65 ‐2.0% 285 27.4% 3,006 52.0% Total 4,988 4,795 7,093 1,333 9,920 2010 1990‐2000 1990‐2000 Change Percent 761 18.0% 1,399 41.2% 3,893 121.7% 7 0.5% 1,130 12.9% Total 5,089 4,840 9,139 1,385 13,715 2020 (Forecasted) 2000‐2010 2000‐2010 Change Percent 101 2.0% 45 0.9% 2,046 28.8% 52 3.9% 3,795 38.3% Total 5,141 5,037 9,320 1,411 14,871 2010‐2020 2010‐2020 Change Percent 52 1.0% 197 4.1% 181 2.0% 26 1.9% 1,156 8.4% 2,115 315 17.5% 3,210 1,095 51.8% 3,509 299 9.3% 3,571 62 1.8% 23,054
678,111 5,379
34,740 30.4%
5.4% 31,339
748,987 8,285
70,876 35.9%
10.5% 37,677
799,874 6,338
50,887 20.2%
6.8% 39,351
823,564 1,674
23,690 4.4%
3.0% * 2000 figures have been adjusted and corrected from original errors in the Census for Collegeville, Schwenksville, and Skippack.
Source: U.S. Census Bureau, except 2020 Forecasts (DVRPC and MCPC)
School Age Children
Age data from the last three decennial censuses shows a slightly different story.
Districtwide, there were fewer children ages 0-4 in 2010 than there were in
2000—though more than there were in 1990. Skippack Township was the only
municipality to post a meaningful gain in young children over the last decade.
School age children (5-17 years old) in the district grew at a much faster rate
(35%) than the entire district population from 2000 to 2010. Skippack and
Perkiomen Townships were the primary drivers of the growth, which can be
attributed to new single-family detached housing construction during the decade,
especially in the first five years. Trappe also grew in terms of school-age
children, while Collegeville, Lower Frederick, and Schwenksville declined.
The slowdown in housing construction and decline of birth patterns during the
recent economic downturn may lead to a small dip in the child population that is
getting ready to enter the Perkiomen Valley School District.
FIGURE 5: Population of Children, 1990-2010
Ages 0‐4 Collegeville Lower Frederick Perkiomen Schwenksville Skippack 1990 2000 1980‐1990 1990‐2000 Total Change Total Change 234 54 272 38 361 206 419 58 257 ‐11 816 559 136 55 78 ‐58 361 84 616 255 2010 2000‐2010 Total Change 226 ‐46 291 ‐128 766 ‐50 81 3 772 156 Trappe District Total
156 1505
252 2388
46 434
282 2483
126 978
‐30 ‐95
Ages 5‐17 Collegeville Lower Frederick Perkiomen Schwenksville Skippack 1990 1980‐1990 Total Change 625 43 559 71 543 ‐302 189 ‐15 768 ‐109 2000 2010 1990‐2000 2000‐2010 Total Total Change Change 762 137 693 ‐69 993 434 913 ‐80 1,435 892 2,197 762 222 33 204 ‐18 1,126 358 2,105 979 Trappe District Total
294 2978
512 5050
‐68 ‐380
218 2072
693 6805
181 1755
Source: U.S. Census Bureau
7
Birth Patterns
Population
The number of births in an area is a critical component to projecting future enrollments in a school district. While some families will migrate over time,
births provide a beginning indicator of the potential
for future kindergarten classes. This relationship will
be detailed in the cohort progression model (p. 35),
but it is important to note that birth data can give a
preview of what will happen with entering students
over the first five years of the projection period.
Birth Patterns
The trend for live births since 2000 in the district
shows a period of higher birth numbers during the
first half of the 2000 decade followed by a period of
gradual decline to decade-low totals the last couple of
years. The steady decline in births occurred despite a
twenty percent gain in overall population from 2000
to 2010, showing a disconnect between overall population change and potential school age population.
Attempting to pinpoint the causes of change in birth
totals over time is difficult, but one clue comes from
looking at the population of child-bearing age women. According to the Pennsylvania Department of
Health, birth rates for mothers in Montgomery County are at their highest between the ages of 25-34. The
population of women in that age group from the
PVSD dropped from 2,343 in 2000 to 1,919 in 2010.
Has the downturn in the economy with the Great Recession in 2008 driven the decline in births? Logically, it would make sense for some to defer or delay
decisions to have children based on economic uncertainty in one’s life. However, the numbers already
started to decline a couple years earlier in 2006.
While the economy may have an indirect impact as it
influences other factors such as housing construction
and sales activity, it alone should not be blamed for
the decline in births.
FIGURE 6: Number of Live Births in PVSD by School Calendar Year (Sept.-Aug.)
700
600
500
400
300
200
100
0
* Births during the 2012 months in the 2011-2012 school year were estimated due to state data being unreleased at the time of this report.
Source: Pennsylvania Department of Health
8
FIGURE 7: Number of Live Births per Municipality in PVSD by School Calendar Year (Sept.-Aug.)
School Year 2000‐01 2001‐02 2002‐03 2003‐04 2004‐05 Collegeville 73 76 95 85 104 Lower Frederick Perkiomen 60 156 87 178 71 186 68 160 62 163 Schwenksville 21 33 44 33 30 Skippack 110 125 147 137 120 Trappe 65 53 64 49 46 District Total 485 552 607 532 525 2005‐06 82 59 168 27 139 68 543 2006‐07 84 62 151 29 134 59 519 2007‐08 76 60 151 20 133 45 485 2008‐09 57 65 144 23 138 51 478 2009‐10 63 56 109 21 139 59 447 2010‐11 2011‐12* 44 55 45 77 130 113 22 6 113 113 59 55 413 420 * Births during the 2012 months in the 2011-2012 school year were estimated due to state data being unreleased at the time of this report.
FIGURE 8: Birth Rates (Births Per 1,000 Population) in PVSD by Calendar Year (Jan.-Dec.)
Calendar Year 2002 2003 2004 2005 2006 Collegeville 14.3 17.7 16.0 19.7 15.7 Lower Perkiomen Frederick 17.9 23.5 14.6 23.9 14.0 20.0 12.8 19.9 12.2 20.1 Schwenksville 24.2 32.1 24.1 21.9 19.7 Skippack 12.0 13.4 12.1 10.2 11.4 Trappe 16.0 19.1 14.5 13.6 20.0 District Total 16.8 18.0 15.5 15.1 15.4 2007 16.2 12.8 17.7 21.1 10.7 17.2 14.4 2008 14.9 12.4 17.2 14.6 10.3 13.0 13.3 2009 11.1 13.4 16.0 16.7 10.3 14.6 12.9 2010 2011 12.4 8.6 11.6 9.3 11.9 14.2 15.2 15.9 10.1 8.2 16.8 16.8 11.9 10.9 Figure 7 provides live birth totals per municipality
in the district as they align with the school
calendar year from September to August. This
alignment is important since the birth figures will
form part of a ratio that reflects how many
children actually become students in the PVSD
five years after they are born. Skippack and
Perkiomen Townships provide the most births in
any given year. Skippack also has the highest
population, but it includes approximately 4,000
prison inmates and several age-restricted
developments—unlikely sources for newborns.
Birth rates are a different statistic than live births.
An increase in actual births could be explained by
concurrent growth in the population base and vice
versa, but birth rates average out the number of
live births per 1,000 persons in an area. The
statistics in Figure 8 confirm that the pattern of
higher birth activity ten years ago is a fact
unrelated to changes in the overall population.
Trappe, Schwenksville, and Perkiomen have the
highest birth rates, although Skippack is again
weighted down by its prison population and
Collegeville is brought lower by the number of
Ursinus College students.
Pennsylvania’s overall birth rate for 2010 was 11.2
and the nation’s rate was 13.0. While the district
is currently at about the same level as the state,
this was not the case for most of the decade as
state rates never eclipsed 12.1 since 2000.
Sources: Pennsylvania Department of Health, U.S. Census Bureau
9
Population
Birth Patterns
Growth in the overall population does not always
correlate to growth within the school age population
and public school enrollment. In the 1990s and
2000s, growth in school aged children occurred at a
higher rate than the overall population. The
District’s overall enrollment figures from the last ten
years also reflect this growth with an increase of 864
students from 2003 to 2012.
However, enrollments since 2010 are beginning to
decline despite moderate growth in population at the
start of this decade that is expected to continue
through 2020 and beyond. Fluctuations in the size of
different age cohorts, birth rate trends, housing
activity, and migration are more responsible for the
change in enrollments than basic population growth.
driven by a dropoff in elementary school enrollment.
Over the last three school years, grades K-5 have
declined each year, losing over 230 students.
Enrollment in elementary schools for 2012 was back
to the same level it was ten years ago in 2003.
Middle school enrollments have been relatively
stable the last three school years, but gained over 300
students over the last ten years. High school
enrollments have been consistently increasing
throughout the last ten years, gaining over 500
students in that time frame. However, the current
and continuing declines in the elementary school
enrollments will ultimately begin to affect the higher
grade levels as fewer students are progressing from
one grade to the next.
A breakdown of the enrollment data by grade level
reveals that recent enrollment declines are being
FIGURE 9: School District Enrollment by Grade Levels, 2003-2012
3000
2500
2000
1500
K‐5
6‐8
1000
500
0
Source: Perkiomen Valley School District (enrollment as of October 1 each year)
10
9‐12
FIGURE 10: District Enrollment by Division, 2003-2012
Year Total Number Change Percent Change K‐12 from Previous Year from Previous Year 2003‐04 4,958 2004‐05 5,189 231 4.66% 2005‐06 5,260 71 1.37% 2006‐07 5,492 232 4.41% 2007‐08 5,606 114 2.08% Grade K‐5 2,557 2,660 2,685 2,710 2,704 Grade 6‐8 1,104 1,172 1,182 1,310 1,367 Grade 9‐12 1,297 1,357 1,393 1,472 1,535 2008‐09 5,747 141 2.52% 2,693 1,439 1,615 1,405 1,690 2009‐10 5,892 145 2.52% 2,797 2010‐11 5,911 19 0.32% 2,721 1,455 1,735 2011‐12 5,831 ‐80 ‐1.35% 2012‐13 5,822 ‐9 ‐0.15% 2,649 2,565 1,376 1,419 1,806 1,838 Source: Perkiomen Valley School District (enrollment as of October 1 each year)
FIGURE 11: District Enrollment by Grade, 2003-2012
Year 2003‐04 2004‐05 2005‐06 2006‐07 2007‐08 K 396 396 413 412 392 1 479 450 464 457 461 2 422 493 439 467 448 3 450 443 484 443 468 4 407 462 433 495 437 5 403 416 452 436 498 6 356 415 411 472 447 7 387 374 413 426 483 8 361 383 358 412 437 9 380 367 378 367 434 10 328 378 353 390 378 11 307 322 359 353 379 12 282 290 303 362 344 2008‐09 419 428 478 462 468 438 496 459 484 436 435 375 369 2009‐10 451 468 449 489 465 475 449 504 452 493 420 416 361 2010‐11 366 474 461 453 493 474 494 454 507 439 489 410 397 2011‐12 2012‐13 376 357 426 424 469 427 454 453 440 448 484 456 451 488 479 455 446 476 496 457 433 496 474 424 403 461 Source: Perkiomen Valley School District (enrollment as of October 1 each year)
11
Population
Birth Patterns
Potential alternative schooling choices include
private schools, charter schools, cyber schools, and
homeschooling. Enrollment in these schools are
enumerated from several data sources and do not
always have a consistent historical record. Further
confusing matters is that charter and most cyber
schools are also considered public schools.
Private Schools
The U.S. Census Bureau and its American
Community Survey provides some comprehensive
data on public versus private school enrollment,
which is probably the most straightforward
assessment of trends. However, these figures are still
estimates with a margin of error and they rely upon
the accuracy of individuals filling out questionnaires.
Figure 12 shows the available data that can be
compared from the Census and ACS.
The Census data indicates that private school
enrollment has dropped within the district since
2000, but that it may be on the increase over the last
couple of years. One potential explanation for the
drop in private school students since 2000 could be
FIGURE 12: Private School Enrollment According to U.S. Census Bureau
Private School Students 916 838 1154 Year 2011* 2009* 2000 Dataset ACS, 3 Year Es mates, 2009‐2011 ACS, 3 Year Es mates, 2007‐2009 Census 2000, Summary File 3 * 3 Year Estimates from the ACS are an average of 3 years worth of sampling data
FIGURE 13: Top Ten Alternative School Destinations
Private Schools Students Liv‐
ing in PVSD* Holy Cross Regional School 222 Pope John Paul II High School 118 St. Mary School 109 Calvary Bap st School 40 Renaissance Academy (public char‐
ter school) 31 Wyndcro School 24 Gwynedd Mercy Elementary School 22 Valley Forge Bap st Academy 19 Penn View Chris an School 18 Germantown Academy 14 * Only includes students that use PVSD Bus Transportation
Source: Perkiomen Valley School District
12
the economic recession starting in 2008, but this
cannot be completely verified given the estimated
data available. A recent Census Bureau report
studying a national decline in private school
enrollment dismisses the impact that the economy
has had and instead points to alternative schooling
choices, such as charter schools and homeschooling
as drains on private school enrollment.
The Perkiomen Valley School District also keeps
data on residents that attend private school, but it
only captures those students that use district bus
transportation. Data for the 2012 school year show
that the district transports 713 students living within
the district to private schools that may or may not be
located within the district. See Figure 13 for a list of
the most popular private school destinations. There
is no other data to suggest how many private school
students exist that do not use district buses, but we
can estimate that there may be as many as 200 other
private school students based on the ACS data.
Charter / Cyber Schools
FIGURE 14: Private Schools Enrolling Students That Reside Within the Perkiomen Valley School District
Charter schools are still considered public in
that they usually have free tuition and are
funded with public dollars. However, they
are independently operated and students are
not considered in the district enrollment
figure. According to the Perkiomen Valley
School District, there were 31 students living
in the district that attended physically
standing charter schools. Most of them were
at the Renaissance Academy in Phoenixville.
Another 44 students were enrolled in cyber
schools, which are a form of home-based
virtual charter schools. They can also be
considered public alternatives. Both types of
schools are relatively new options in the area,
first appearing in the area about ten years ago.
Historical data on these enrollments as they
concern PVSD children were not available.
Schools located in Lower
Gwynedd and Whitemarsh:
Gwynedd Mercy ES
Gwynedd Mercy HS
Germantown Academy
Homeschooling
The last alternative, which is not considered
public schooling, is homeschooling where the
parent is responsible for educating the child.
The Pennsylvania Department of Education
reports that there were 48 students being
homeschooled within the PVSD during the
2011-2012 school year. This number has
remained fairly steady over the last ten years
going as low as 35 and as high as 55.
* Only schools with ten or more students from PVSD are depicted.
13
14
Housing Activity
Part
Housing Activity
Impacts of Housing on Enrollment
School Age Children by Housing Type
Housing Units Built
Housing Units Proposed
Age Restricted Housing
Housing Sales
The average number of school age children in a
residential unit depends on the type of residential
unit. MCPC reviews the latest census data and
compares it to county property records as part of its
report titled, “Characteristics of the Population in
New and Existing Housing Units”. The latest report,
based on the 2010 Census, contains the average
number of school age children in single family
detached, attached, and multifamily housing types.
The data is also analyzed in terms of new and
existing units. The results of the study (Figure 15)
show that a newly constructed single family detached
home is over 20 times more likely to contain a school
age child than multifamily units. The difference is
less stark when considering all existing units, but
there are clearly more children found in detached
units than in multifamily units, with single family
attached units falling in between the other two.
The methodology for the report was replicated to just
focus on municipalities within the PVSD. While
there weren’t enough new units to develop
representative figures, it was still revealed that the
disparity between school age children across housing
types were similar to countywide levels. It also
shows that multifamily homes in the district may be
slightly more likely to have children than the county,
but detached homes are still responsible for a greater
number of children per unit.
FIGURE 15: Average Number of School Aged Children per Housing Unit
Montgomery County
Single Family Detached Single Family A ached Mul family 0.54 0.89 0.40 0.19 0.16 0.04 Single Family Detached Single Family A ached Mul family 0.74 NA 0.35 NA 0.25 NA School Age Children per Exis ng Unit School Age Children per New Unit Perkiomen Valley School District
School Age Children per Exis ng Unit School Age Children per New Unit Source: Montgomery County Planning Commission
16
Migration of Households
increases for one reason or another.
The connection between new housing units and new
population is fairly clear, although it also depends on
the type of units. The impact of household
movement in and out of any housing unit is a less
certain connection. This impact is incorporated into
the cohort progression model in terms of the recent
past and how it relates to enrollments. However, it
would also be useful to look at sales data of homes
and come to an understanding of what might happen
with school age children where sales activity
The American Community Survey offers data on
geographic mobility of households and the age
composition of those households. Figure 16 shows a
breakdown of households that have remained within
the same house as the year prior and households that
have moved within the last year. This latter group
would constitute the characteristics of people who
are purchasing homes or moving into rental units.
The results show that the percentage of school age
children is higher in homes that are occupied by the
same household as the year before. Therefore,
recently sold homes will contain fewer school age
children than homes that have not been sold. The
same is true for children younger than school age. A
sudden increase in home sales should not be
construed as having an immediate positive impact on
school enrollment.
Eventually, a boost in housing sales may still provide
a positive impact on increasing enrollments. Persons
age 25-34 are the most likely to conceive children.
This age group is more likely to occupy households
that have just moved into a new home, therefore
increasing the likelihood that new children will be
born into the district.
FIGURE 16: Percentage of Children in PVSD Area Households Related to Geographic Mobility
Persons Age 1‐4 Persons Age 5‐17 Persons Age 25‐34 Total Persons Number Percent Number Percent Number Percent Persons in households that have moved within the last year 5,315 127 2.4% 483 9.1% 1,243 23.4% Persons in households that have remained in the same house 31,166 1,747 5.6% 6,315 20.3% 3,783 12.1% Source: American Community Survey, 2007-2011Estimates
Owner / Renter Occupied
Housing in the Perkiomen Valley School District is
predominately owner occupied—85 percent of all
units. However, apartment rentals have been picking
up lately at the county level as the market is making
it easier for developers to fill rental units than it is to
sell units. The possibility also exists for an existing
property to undergo a change in tenure, either as an
apartment rental being turned into a condominium or
the owners of occupied units to begin renting them.
Data from the American Community Survey
suggests that school age children are more likely to
be found in owner occupied housing than they are in
renter occupied housing.
FIGURE 17: Presence of Children in Owner Occupied and Renter Occupied Housing Within the PVSD Area
Percent of Housing Percent of Housing with with Children Under 18 Children Under 6 Owner Occupied Housing Renter Occupied Housing 43% 31% 18% 15% Source: American Community Survey, 2007-2011Estimates
17
Housing Activity
Housing Units Built
Housing Sales
Housing Units Built
Residential construction activity within the district is
reflective of countywide activity over the last ten
years. After a high level of construction during the
housing boom of the first half of last decade, activity
fell to historically low totals during the recession and
recovery period leading up to the present time. Since
2009, there have not been more than fifty units
constructed annually in the district.
The majority of homes built since 2007 have been in
Skippack Township—319 units out of 411 total.
Biltmore and the first phase of Meadow Glen were
the two largest developments in Skippack. Biltmore
is a mixed housing type development that suffered
construction delays due to financial issues with the
original developer, THP, but 198 units of the planned
226 units have now been constructed. Meadow Glen
is an age restricted development with up to 200 more
units planned in future phases.
Single family detached housing is still the most
popular type of housing being produced in the
Perkiomen Valley District, although there has been
an increase in multifamily housing production over
the last five years. New detached homes are much
more likely to bring additional school age children
into the district as compared to townhomes and
especially multifamily apartments or condos (see
page 16).
FIGURE 18: Housing Units Built in PVSD by Housing Type, 2002-2011
450
400
350
300
250
Multifamily
200
Single Family Attached
150
Single Family Detached
100
50
0
2002 2003 2004 2 005 2006 2007 2008 2009 2010 2011
Source: Montgomery County Planning Commission
18
FIGURE 19: Housing Units Built in PVSD, 2007-2011
Units Constructed, 2007‐2011 Municipality SFD MF Total Collegeville 18 2 16 36 Lower Frederick 10 7 0 17 Perkiomen 28 0 0 29 1 0 0 1 202 5 45 4 72 0 319 9 Schwenksville Skippack Trappe 29
SFA A
GR
Lower
Frederick
L
VE
KE
PI
N
AI
M
BRIDGE RD
SKIPPACK PIKE
73
BIG RD
73
ST
Schwenksville
Skippack
6,000
29
Trappe
12,000 Feet
THIRD AVE
3,000
Perkiomen
113
¯
0
KE
PI
Multifamily
L
VE
TOWNSHIP LINE RD
A
GR
113
MAIN ST
Collegeville
19
Housing Activity
Housing Units Built
Housing Sales
While housing construction in the district has
declined in recent years, the number of new
proposals was almost nonexistent after 2008, with
the exception of 99 age restricted units in Skippack
as part of the Maple Glen development. That is not
to say that there is no future development on the
horizon. Some plans were put in limbo by 2008 or
earlier due to the general collapse of the housing
market nationwide. Many developers were suddenly
challenged by getting the necessary financing to start
or complete projects. Likewise, homebuyers also
were faced with tighter restrictions on mortgage
lending. Most activity was simply frozen.
The market is beginning to regain some footing over
the last year, so older projects or sites that were once
being pursued for development could again be
targeted by homebuilders as the market improves.
The map in Figure 21 shows proposal activity that
occurred over the last five years, along with the
known status of those projects. The Meadow Glen
proposals are phases of a larger development plan
that had been approved at an earlier time. There
were 67 units built since 2007, but the 202 units
indicated on the map have not yet been built.
MCPC also talked to managers from each
municipality to gather information on any other
projects that had not been formally submitted yet.
Only two small developments were mentioned (both
with 12 lots)-one in Lower Frederick and one in
Skippack. The Lower Frederick manager also
indicated that there was renewed interest in two sites
that had been previously submitted for 48 and 39
units—Melbourne Hill and the Ragusa Tract as
shown on the map.
Ultimately, there is no evidence of a major
resurgence in housing construction within the
district. However, the market is still recovering and
sites that were once desirable locations could see
renewed interest as the market improves.
FIGURE 20: Housing Units Proposed in PVSD, 2002-2012
350
300
250
200
150
100
50
0
20
Multifamily
FIGURE 21: Proposed Housing Units, 2007-2012, with Details Provided for Proposals with More Than 10 Units
2008 Meadow Glen Ph. 3
103 Detached Units (Age Restricted)
Approved But Not Built
2008 Ragusa Tract
39 Detached Units
Not Approved
29
Lower
Frederick
A
GR
2008 Melbourne Hill
48 Detached Units
Not Approved
2012 Meadow Glen Ph. 2
99 Detached Units (Age Restricted)
Approved But Not Built
2007 - Biltmore
226 Units Proposed and Approved
198 Units Built Since 2007
L
VE
KE
PI
BRIDGE RD
SKIPPACK PIKE
N
AI
M
73
BIG RD
73
ST
Schwenksville
Skippack
113
VE
L
KE
PI
PVSD Elementary Service Area
2007 Emmanuel Demutis
32 Multifamily Units
Built in 2012
TOWNSHIP LINE RD
A
GR
2007 The Highlands
50 Attached Units (Age Restricted)
Not Approved
Perkiomen
29
Skippack Elementary
South Elementary
2008 433-439 W. Main St.
18 Attached Units
Not Approved
¯
0
3,000
6,000
12,000 Feet
2007 Stearly Tract
31 Detached Units
Not Approved
113
Trappe
THIRD AVE
MAIN ST
2012 Monument Project at Glenwood
14 Attached Units
Not Approved
Collegeville
2007 Claymont at Collegeville
20 Detached Units
Built in 2008
21
Housing Activity
Age restricted housing refers to housing
developments that place minimum limits on the age
of residents but still offers independent living. The
age limit is usually set at 55 years old and above.
This housing does not include assisted living units or
nursing care beds although some age restricted
developments are actually continuing care
environments where all three types of living are
present—independent, assisted, and nursing–
allowing residents to transfer into more dependent
care as needed. Age restricted developments can
feature any type of housing, single family or
multifamily, but the housing is designed to facilitate
an older population and meet their needs.
Housing Units Built
Housing Sales
percent of all units proposed in the county have been
age restricted.
Age restricted housing became popular in
Montgomery County beginning in the mid to late
1990s and continues to be a prominent type of
residential development today. Since 1996, about 22
In the Perkiomen Valley School District, there are
approximately 600 age restricted units built with 200
more likely to be built in the near future. Over half
of these units were built between 2000 and 2006 with
one development being started since then, the
proposed 301 unit Meadow Glen at Skippack
development. Only 67 of these units had been built
through 2011, but approval has been granted for 202
additional units.
Figures 22 and 23 detail the activity and locations of
age restricted housing in the district. This type of
housing is important to recognize as it can account
for residential and population growth without directly
providing additional school age children. If future
construction activity is more heavily weighted
toward age restricted housing in place of traditional
housing, it could further reduce expected school
enrollments.
FIGURE 22: Existing Age Restricted Developments in PVSD
Municipality Development Name Total Units SFD SFA MF Year Built Skippack Meadow Glen 67* 67 2007—
Present Skippack Meadows at Skippack 125 125 2004‐2006 Carriage Ridge 38 38 2004 Skippack The Colony at Skippack 82 82 2001 Skippack Arbours at Skippack 87 87 2001 Colonnade of Schwenksvville 94 94 1987 Highland Manor 84 84 1969 Trappe Schwenksville Perkiomen * Meadow Glen was originally proposed for 301 units. 202 units were approved in 2011 but have not been built at this time.
22
FIGURE 23: Existing Age Restricted Developments in PVSD
Meadow Glen
67 Detached Units
(202 Additional Proposed Units)
29
A
GR
Lower
Frederick
L
VE
The Colony at Skippack
82 Detached Units
KE
PI
Colonnade of Schwenksville
N
AI
M
BRIDGE RD
SKIPPACK PIKE
73
BIG RD
73
ST
Schwenksville
Skippack
KE
PI
L
VE
PVSD Elementary Service Area
TOWNSHIP LINE RD
A
GR
Highland Manor
113
Perkiomen
29
Skippack Elementary
Carriage Ridge
38 Attached Units
¯
0
3,000
6,000
12,000 Feet
113
Trappe
THIRD AVE
South Elementary
MAIN ST
Arbours at Skippack
87 Detached Units
Collegeville
Meadows at Skippack
125 Detached Units
23
Housing Activity
Housing Sales
Market-rate housing sales activity has declined since
2005 within the Perkiomen Valley School District,
just as it has countywide and in much of the nation.
This was due to the unprecedented housing bubble
through the first half of the ’00 decade where median
sales prices increased as much as 15 percent on an
annual basis. The subsequent collapse during the
latter half of the decade saw home values flatten out
and often depreciate as financial markets tightened
up for potential buyers. By 2010, the county was
experiencing a historically low level in terms of the
number of units sold. Sales activity in the PVSD was
less than half of what it had been five years earlier.
Housing Units Built
Housing Sales
The impact of this decline in sales is that it slows
down migration activity in a region that features 85
percent of its housing stock as owner-occupied
housing. While it was demonstrated on page 23 that
housing transfers do not necessarily bring more
school age children with them, they do provide for a
churning of households that should result in a greater
number of child-bearing age women. The reduction
in home sales over the last five or six years probably
did not immediately affect school enrollments, but it
may be adding to the more recent enrollment declines
at the elementary school level.
FIGURE 24: Housing Units Sold in PVSD, 2005-2011
1000
900
800
700
600
New
500
Existing
400
Total
300
200
100
0
2005
2006
2007
2008
24
2009
2010
20 11
FIGURE 25: Existing Housing Units Sold in PVSD, 2007-2011 (New Units Not Included)
29
A
GR
Lower
Frederick
L
VE
KE
PI
N
AI
M
BRIDGE RD
SKIPPACK PIKE
73
BIG RD
73
ST
Schwenksville
Skippack
L
KE
PI
VE
TOWNSHIP LINE RD
A
GR
Housing Types
113
Perkiomen
29
Mobile Home / Other
113
¯
0
3,000
6,000
12,000 Feet
THIRD AVE
Trappe
MAIN ST
Collegeville
25
26
District Enrollment
Projections
Part
District Enrollment Projections
Cohort Progression Model
The method used in this study to calculate
projections for each grade level is known as the
Cohort Progression Model, which is also referred to
as Cohort Survival in some applications. This is a
fairly common approach and one used by the state
and other districts in formulating projections.
However, it should always be used with caution and
presented in context with the other variables offered
in this report. In some districts there will be cause
for adjustments to the model based on rapidly
changing factors in population growth or migration.
Projected Enrollment Summaries
Indicators of Projection Change
The nature of the model allows it to integrate trend
activity across a number of variables. Birth rates
have the most obvious impacts in the model but the
changes that take place account for trends in
population migration, housing construction, sales,
and alternative schooling choices, such as private,
charter, or homeschooling opportunities.
The model is fairly straightforward in its method. It
tracks each class in a given year and measures the
change in that class from one year to the next. Then
it applies an average of changes over a specified time
period to determine the percentage of a given grade
likely to “progress” to the next grade in future years.
A five year average was used for the Perkiomen
Valley School District since it would account for
enrollment patterns from the 2007 through 2012
school years. This period incorporates the low level
of population and housing activity that is still
affecting growth in the district, but it also goes back
far enough where the first two years were still more
active in terms of housing growth than recent years.
While we expect conditions to improve at a gradual
rate in the coming years, a return to the housing
boom period of the first half of the decade is not
likely for some time, if ever.
Figure 26 displays all of the progression rates for
each grade transition from the last five school years.
Then the average is calculated to arrive at a basic
trend that will be applied for each projected year.
28
Any progression rate that is greater than 1.0 indicates
that a class increased in size from one year to the
next as it also moved up a grade level. Progression
rates that are lower than 1.0 indicate that a class
decreased in size. For example, the first grade class
of the 2008 school year expanded its size when it
entered the second grade in 2009 at a rate of 1.05.
Using actual enrollment figures, the class went from
428 to 449 students during that period. The
following year in 2010, it entered the third grade with
only a slight increase at a rate of 1.01. In 2011, it
entered the fourth grade and actually decreased in
size at a rate of 0.97, losing 13 students by the
enrollment figures.
Looking at the whole range of progressions, most
grade levels show growth at the elementary and
middle school levels, but classes typically decline
during the high school years. The decline during the
high school years is usually a result of students who
drop out but may also be influenced by greater
mobility afforded to older teenagers. The largest
period of class growth takes place between
kindergarten and the first grade when classes
increased at a rate of 1.11 on average. It is not
known how many of these new students were already
in the district but received private kindergarten
education, or were members of households that just
moved into the district at that time.
FIGURE 26: Grade Progression Rates Over the Last Five Years
School Year Birth*‐K K‐1 1‐2 2‐3 3‐4 4‐5 5‐6 6‐7 7‐8 8‐9 9‐10 10‐11 11‐12 2008‐09 0.690 1.092 1.037 1.031 1.000 1.002 0.996 1.027 1.002 0.998 1.002 0.992 0.974 2009‐10 0.848 1.117 1.049 1.023 1.006 1.015 1.025 1.016 0.985 1.019 0.963 0.956 0.963 2010‐11 0.697 1.051 0.985 1.009 1.008 1.019 1.040 1.011 1.006 0.971 0.992 0.976 0.954 2011‐12 0.692 1.164 0.989 0.985 0.971 0.982 0.951 0.970 0.982 0.978 0.986 0.969 0.983 2012‐13 0.688 1.128 1.002 0.966 0.987 1.036 1.008 1.009 0.994 1.025 1.000 0.979 0.973 0.723 1.110 1.013 1.003 0.995 1.011 1.004 1.007 0.994 0.998 0.989 0.975 0.969 5 Year Avg. * The birth-to-kindergarten ratio uses birth data six years prior to the indicated school year, thus drawing the relationship between children born and the year they would actually enter kindergarten.
Birth-to-Kindergarten Ratio
The projection of future enrollments in the model
requires that we apply the trends in progression rates
to future classes as they go from one grade to the
next. However, the kindergarten class for each year
does not have an enrollment figure for its prior year
since those children would be in preschool or home
care outside of the district system. Therefore, we
must use live birth data in the district to identify
ratios of births to kindergarten. The birth data comes
from a given past year and is then applied to the
kindergarten class that would follow six years later in
order to capture the same children at each end of the
ratio. For instance, a birth-to-kindergarten ratio for
the 2012 school year uses birth data from the 2006
school year as the numerator and divides it by the
kindergarten enrollment in 2012 to form the rate
(0.688) shown in figure A.
The ratios of births to kindergarten are much lower
than the yearly grade progression rates as would be
expected. Much can happen in the six years between
a child’s birth and entry into kindergarten causing a
child to move away or others to move into the district
after having been born elsewhere. The averaging out
of the ratios gives us the best approximation of the
net result of all birth and migration activity in the
district, but clearly there is room for error.
One beneficial aspect of a birth-to-kindergarten ratio
is that it allows the model to integrate real data into
the first five years of the projection period. In other
words, projections of kindergarten classes for the
first five years, through the 2017 school year, can
account for real changes in birth patterns that have
occurred from 2007 to 2012. The downside is that an
estimated birth figure must be used for any projection
beyond the 2017 school year.
Projection Periods
Due to the distinction between using real birth data
and the need to estimate beyond five years,
enrollment projections are divided into two periods.
The primary period covers the first five school years
from 2013 to 2017, and the secondary period covers
the next five school years from 2018 to 2022. There
is a higher degree of accuracy expected during the
primary period than in the secondary period.
Obviously, recent trends are more likely to continue
in the short term before outside factors can influence
a change in patterns, but the use of the birth data
gives a more dependable start to projecting the size
of kindergarten classes in the future.
29
Estimated Births
The projection of kindergarten classes after 2017
requires the use of estimated birth figures for the next
five years. A simple approach used to estimate these
births is to use an average of the most recent birth
figures and extend it through the end of the
projection period. In the Perkiomen Valley School
District, the average number of births over the last
three years was 427. This is the figure used to
formulate the ten year district projection in Option 1.
The most recent births were the lowest of the decade,
so it is possible for them to begin cycling back up to
a degree. A second birth estimate was created using
a wider window of recent data. Option 2 uses the
average number of births over the last five years,
which was 449, to provide kindergarten estimates for
the 2018 through 2022 school years.
A third situation was created based on a theoretical
return of birth activity to levels that were present in
the first half of the last decade before the economic
.Also notice how the first five years (primary period)
are identical in each option regardless of the birth
estimate used since those years are still based on
historical birth data. It is the second five years
(secondary period) where changes begin to differ
amongst the three options.
and housing slowdowns and when birth rates were
higher. Option 3 projections use an average of birth
numbers from the years 2000 through 2007, which
comes out to 538.
Projected Enrollments
Figures 27, 28, and 29 offer the grade by grade
projections over the next ten years for each option.
Each grade level in a given year is determined by
applying the average grade progression rate from
Figure 26 to one grade earlier the year before. For
example, the 5th grade class of the 2013 school year
is projected to be 453 students. In 2014, that class
will be in the 6th grade. Multiplying the average 5th
to 6th grade ratio of 1.004 times 453 results in a
projected 6th grade class of 455 students. The same
class moves into the 7th grade in 2015 and grows to
458 students when applying the ratio for that
transition. Calculations like these are made at every
grade level to fill out the projection charts.
FIGURE 27: Projected Enrollments, OPTION 1
Births 6 School Year Years Ago* K 1 2 3 4 5 6 7 8 9 10 11 12 TOTAL 2013‐14 485 351 396 429 428 451 453 458 491 452 475 452 483 411 5,731 2014‐15 478 346 389 401 431 426 455 455 461 488 451 470 440 469 5,682 2015‐16 447 323 384 394 402 428 431 457 458 458 487 446 458 427 5,554 2016‐17 413 299 359 389 395 400 433 432 460 455 457 482 435 444 5,440 2017‐18 420 304 332 363 390 393 405 435 435 457 454 452 470 422 5,311 2018‐19 427 309 337 336 364 388 398 406 437 432 457 449 441 455 5,208 2019‐20 427 309 343 341 337 362 392 399 409 435 432 451 438 427 5,074 2020‐21 427 309 343 347 342 335 366 393 402 406 434 427 440 424 4,969 2021‐22 2022‐23 427 427 309 309 343 343 347 347 348 348 341 346 338 344 368 340 396 370 399 394 406 399 429 401 416 418 426 403 4,866 4,762 * The birth figure for each row does not pertain to births during that year, but rather the births that occurred six years prior to the projected year. The average birth-to-kindergarten ratio is then applied to get
the projected kindergarten class. For example, the birth figure of “420” for the 2017-18 projection is the actual number of births that were recorded during the 2011-2012 school year. Multiplying 420 times the
birth-to-kindergarten ratio of 0.723 results in the projected 304 kindergarten students for 2017.
30
31
The total enrollment projections for the district and at
each school level is presented on these two pages.
The three options based on births over the next five
years are also differentiated. However, there is no
distinction at the middle school and high school
levels since children born over the next five years
will not be old enough to influence those projections
within the ten year timeframe.
housing market, but it still shows that even with a
return to high birth numbers, the district will still see
a decline, especially during the first five years
(primary period).
Focusing on option 1, the projections for the
elementary schools show that the highest level of
annual enrollment declines are expected three to five
years out with enrollments eventually stabilizing and
potentially gaining at the end of the ten year range. If
birth rates go up or other factors bring about more
school age children, then the secondary period could
eventually bring about more growth as shown in
options 2 and 3. Of course any annual decline
forecasted at the elementary level is to be distributed
across four separate school buildings (see Part 4).
Option 1 is recommended to be considered the
default or baseline standard for enrollment
projections. It features the most conservative range
since the birth figures are closest to resembling what
has been happening the last three years. However,
option 2 is still a possibility and should be used for
contrast. If births pick up a little bit from the recent
trend, 22 per year to be exact, then the decline would
be slightly less overall. Both declines projected for
options 1 and 2 are still relatively close. Option 3 is
unlikely without a tremendous rebound in the
The projections for the middle schools and high
school indicate a lower level of decline during the
first five years. These schools are expected to drop at
a greater magnitude during the second five years
since the current pipeline of students is enough to
relatively sustain enrollments for now.
FIGURE 30: Total District Enrollment Projections
Op on 1 Year Annual Change Total Students Op on 3 Annual Change Total Annual Students Change 2012‐13 (Current) 5,822 5,822 5,822 2013‐14 5,731 ‐91 5,731 ‐91 5,731 ‐91 2014‐15 5,682 ‐49 5,682 ‐49 5,682 ‐49 2015‐16 5,554 ‐128 5,554 ‐128 5,554 ‐128 2016‐17 5,440 ‐114 5,440 ‐114 5,440 ‐114 2017‐18 5,311 ‐129 5,311 ‐129 5,311 ‐129 2018‐19 5,208 ‐103 5,224 ‐87 5,289 ‐22 2019‐20 5,074 ‐134 5,108 ‐116 5,244 ‐45 2020‐21 4,969 ‐105 5,020 ‐88 5,228 ‐16 2021‐22 4,866 ‐103 4,935 ‐85 5,216 ‐12 2022‐23 4,762 ‐104 4,849 ‐86 5,202 ‐14 ‐1,060 ‐973 ‐620 Total Change 2012‐2022 32
Total Students Op on 2 ENROLLMENT PROJECTIONS
FIGURE 31: Elementary School Enrollment Projections
Year Op on 1 Total Annual Students Change Op on 2 Total Annual Students Change Op on 3 Total Annual Students Change 2012‐13 (Current) 2,565 2,565 2,565 2013‐14 2,508 ‐57 2,508 ‐57 2,508 ‐57 2014‐15 2,448 ‐60 2,448 ‐60 2,448 ‐60 2015‐16 2,362 ‐86 2,362 ‐86 2,362 ‐86 2016‐17 2,275 ‐87 2,275 ‐87 2,275 ‐87 2017‐18 2,186 ‐89 2,186 ‐89 2,186 ‐89 2018‐19 2,131 ‐55 2,147 ‐39 2,211 25 2019‐20 2,084 ‐47 2,117 ‐30 2,253 42 2020‐21 2,042 ‐42 2,094 ‐23 2,302 49 2021‐22 2,026 ‐16 2,095 1 2,376 74 2022‐23 2,037 11 2,124 29 2,477 101 ‐528 ‐441 ‐88 Total Change 2012‐2022 FIGURE 32: Middle School Enrollment Projections
Year FIGURE 33: High School Enrollment Projections
Total Annual Students Change Year Total Students Annual Change 2012‐13 (Current) 1,838 ‐18 2013‐14 1,821 ‐17 1,404 3 2014‐15 1,830 9 2015‐16 1,373 ‐31 2015‐16 1,818 ‐12 2016‐17 1,348 ‐25 2016‐17 1,818 0 2017‐18 1,327 ‐21 2017‐18 1,797 ‐21 2018‐19 1,276 ‐51 2018‐19 1,801 4 2019‐20 1,243 ‐33 2019‐20 1,748 ‐53 2020‐21 1,202 ‐41 2020‐21 1,725 ‐23 2021‐22 1,163 ‐39 2021‐22 1,677 ‐48 2022‐23 1,104 ‐59 2022‐23 1,621 ‐56 ‐315
‐217 2012‐13 (Current) 1,419 2013‐14 1,401 2014‐15 Total Change 2012‐2022 Total Change 2012‐2022 33
MCPC analyzed the regional population forecasts for
the municipalities in the PVSD and identified the
expected number of new housing units that would be
needed to support the amount of population growth
forecasted for the district by 2020. Figure 34 shows
the existing housing units in 2010 and the number of
units (517) that would allow the district to grow at
the forecasted rate of 4.4 percent through 2020.
Figure 35 breaks down the housing forecast by
municipality. This analysis also accounts for
changes in household size and housing types.
No further adjustments to the projections on the
preceding pages are necessary at this time. The
background data and analysis throughout this report
forms a basis and understanding of how the numbers
should be interpreted. However, markets and trends
can always change in unexpected manners. This
section provides a further understanding of the
assumptions inherent with the progression model and
potential warning signs that would prompt a future
reconsideration of the projected enrollment figures.
These indicators are not likely to prompt an
immediate change in future enrollments, but over
time they could still influence the outlook.
The forecast of 517 units for the decade would
average out to roughly 52 units per year. Through
2012, the district is averaging slightly more at 55
units per year. At that rate the area might grow
slightly more than the original 2020 projection but it
is still early.
Housing Construction
New housing and births are the two most significant
factors that could suggest a revision in the expected
enrollments, but housing will have the more
immediate effect. Housing construction has been
very low over the last few years, so further declines
in enrollment due to housing would be unlikely.
However, a rapid turnaround in the housing market
that would bring higher numbers of units, especially
the single family detached type, could reduce the
expected declines.
The cohort progression model used in this report is
primarily based on the trends of the last five years.
Housing construction from 2008 to 2012 in the
district averaged out to 64 homes a year when age
restricted units are excluded. If housing construction
in the future is significantly more than 64 homes a
year, perhaps 100 units a year, then the cohort
progression model may slightly underestimate the
FIGURE 34: Housing Types, Existing and Forecasted
Exis ng as of 2010* Forecasted 2010‐2020 (MCPC) Units Built, 2010‐2012 (MCPC Preliminary) Single Family Detached Single Family A ached Mul family Mobile Home / Other 7,843 3,181 1,369 98 12,491 289 118 110 0 517 91 7 68 1 166 Total Units * Total Units as of 2010 are cited from Census 2010. Housing Type distribution comes from estimates in the 2007-2011 American Community
Survey, but are adjusted to match the total number of units as determined in Census 2010.
34
FIGURE 35: Forecasted Housing Units
Between 2010 and 2020, by Municipality
Municipality Collegeville Lower Frederick Perkiomen Schwenksville Skippack Trappe Forecasted Units 7 80 69 0 330 31 number of students. Conversely, if housing
construction goes down a lot, perhaps to 10 units a
year, then the cohort progression model may slightly
overestimate the number of students. The current
pace of 55 units per year and the projection of 52
units per year are close enough to the cohort
progression baseline of 64 units per year that no
adjustment is needed at this time for the enrollment
projections.
Birth Patterns
Birth numbers are directly integrated into the cohort
progression model and form the basis for the three
potential options presented on the preceding pages.
The number of births can significantly affect future
projections, but any changes today will not be felt for
at least six years in terms of the projections. Option
1 was based on an expected 427 annual births in the
district.
Annual birth data should be tracked to anticipate if
one option may become more likely during the
secondary period. Live birth data is available from
the Pennsylvania Department of Health, but the
numbers must be correlated to the school year rather
than the calendar year.
Private schools, charter schools, cyber schools, and
homeschooling could also impact the district’s public
school enrollment if students opt for these
alternatives at a greater or lesser rate than in the past.
The American Community Survey provides rather
delayed data on private schools averaged out over
multiple years, so the district’s record of private
school students using district buses is going to
provide the most useful information on any change in
enrollment trends. Nationally, private school
enrollment has declined in recent years. The
economy could be having an effect, but at least one
study from the Census Bureau claims that
mainstream public schools are not the primary
competition to private schools, but rather new charter
schools and homeschooling formats are causing
lower enrollments.
Charter schools, cyber schools, and homeschooling
make up a relatively small portion of students within
the PVSD, but many of these opportunities were not
around ten to fifteen years ago. Approximately 123
students were using these combined alternatives in
2012. The PVSD tracks annual enrollment in charter
and cyber schools as they are still considered public
schooling, but the Pennsylvania Department of
Education provides the annual number of
homeschooled students.
Housing Sales Activity
The amount of housing sales is expected to increase
at some point in the next few years as it has been
remarkably low due to the housing bubble bursting
and the Great Recession. When it does increase, the
effect on school age children in the district is still
expected to be a delayed reaction. New households
moving into an area are less likely to have school age
children, but they are more likely to have members of
child-bearing age. Therefore, an increase in school
age children probably will not be felt in the near term
but might in the longer term if housing sales
dramatically increase.
35
36
School Profiles
Part
School Profiles
Introduction
Introduction
Application of the Cohort Progression Model to
individual school buildings can be done, but it loses
some accuracy when enrollments are at a smaller
scale, especially when under one thousand. It
becomes even more difficult when school boundary
areas do not correspond with municipal boundaries,
making it impossible to use actual birth data related
to the precise area. Both situations are existing
conditions in the PVSD, so the following school
profiles do not present detailed projection numbers
for the future.
Evergreen Elementary School
Schwenksville Elementary School
Skippack Elementary School
South Elementary School
East Middle School
However, there is still useful data that can inform
more general forecasts for the future. Municipal
birth data can be considered more figuratively to get
a sense of what areas within the district are more
likely to change based on natural progression. The
county’s geographic data on housing construction
and sales can also be customized to each school
boundary. Plus, the overall projections for each
school level provide the context for how much
growth or decline might occur in each school.
The following profiles offer an assessment of what is
happening in each area and how it might affect future
enrollments. Of course, the high school has been left
out since there is only one, and the projections were
presented in Part Three.
West Middle School
38
Birth Patterns
Births for Perkiomen Township as a whole have been
declining with 2009 and 2011 being the lowest totals
since at least 2000. Birth totals on average have been
21 percent lower the last six years compared to the
previous six years.
Evergreen Elementary School serves the largest
portion of residents within Perkiomen Township.
Enrollment at the school has declined 5.7 percent
since 2009, but still remains slightly higher than it
was in 2007.
Forecast
Enrollments at Evergreen are expected to continue
declining over the next five years. A drop of
between 20 and 30 students is likely for the 2013
school year with a total loss of over 100 students by
2018. The largest annual loss is more likely to be in
about three years due to the recent low activity in
births and housing, in addition to the progression of a
bump in attendance from 2008-2009 that will be
leaving for middle school in 2014 and 2015.
Housing
Residential construction within Evergreen’s
boundary area has been almost nonexistent the last
three years. All of the 21 units built since 2007 have
been single family detached homes. Housing sales in
the boundary area have also tapered off over the last
five years, at a rate (-42.7%) slightly higher than the
overall county rate (-38.7%). There are currently no
active residential proposals of more than a couple of
units within the boundary.
FIGURE 38: Evergreen Elementary School Enrollment by Grade, 2006-2012
Annual Change FIGURE 36: Evergreen Elementary School Enrollment
730
720
710
700
690
680
670
660
650
2008
2009
2010
2011
FIGURE 37: Births in Perkiomen Township
by School Calendar Year (Sept.-Aug.)
School Year 2000‐01 2001‐02 2002‐03 2003‐04 2004‐05 Births 156 178 186 160 163 Year 2006‐07 2007‐08 K 108 96 1 121 118 2 120 115 3 112 113 4 130 106 5 107 125 Total 698 673 2008‐09 119 118 121 119 114 110 701 28 2005‐06 168 2009‐10 121 135 117 114 116 117 720 19 2006‐07 151 2010‐11 98 126 133 117 115 113 702 ‐18 2007‐08 151 2011‐12 2012‐13 112 92 103 104 130 105 128 132 112 128 115 118 700 679 ‐2 ‐21 2008‐09 144 2009‐10 109 2010‐11 130 2011‐12 113 2000‐2005 Avg.
2006‐2011 Avg.
169
133
FIGURE 39: Housing Activity Within Evergreen ES Boundary Area
New Units Built Exis ng Units Sold 2007 6 103 2008 13 95 Source: Montgomery County Planning Commission
2009 1 92 2010 1 67 2011 0 59 Total 21 416 ‐25 2012
Note: The majority of Perkiomen residents are in the
Evergreen boundary, but not all. Birth figures cover
the entire township so should only be used as a guide
to general birth patterns in the school’s area.
39
development that already brought 67 age restricted
units since 2007.
Schwenksville Elementary School serves all of the
residents in Lower Frederick and Schwenksville. It
also encompasses a portion of Perkiomen and
Skippack Townships. The school’s boundary was
extended further into Skippack prior to the 2008
school year. Enrollment at the school has declined
15.4 percent since 2008.
Birth Patterns
Combined births for Lower Frederick Township and
Schwenksville Borough have been declining with
2010 being the lowest total since at least 2000. Birth
totals on average have been 18 percent lower the last
six years compared to the previous six years.
FIGURE 40: Schwenksville Elementary School Enrollment
Forecast
Enrollments at Schwenksville are expected to only
moderately decline over the next five years. A drop
of about 10 students is likely for the 2013 school year
with a total loss of around 60 students by 2018. The
largest annual losses are more likely to be in about
three years due to the recent low activity in births and
housing. While there is nothing imminent in
residential construction that is not age restricted, the
interest from developers in the past could be renewed
if the market improves
Housing
Residential construction within Schwenksville’s
boundary area has been declining since 2008, and 67
of the 99 units built in the last five years have been
age restricted homes. Housing sales in the boundary
area have also declined over the last five years at a
rate (-34.3%) slightly lower than the overall county
rate (-38.7%). The area received several proposals
for developments back in 2007 and 2008 but none
ultimately got approved, except for later phases of
the Meadow Glen development, which is the same
FIGURE 42: Schwenksville Elementary School Enrollment by Grade, 2006-2012
Year 2006‐07 2007‐08 K 2008‐09* 1 2 86 93 85 82 84 83 3 100 85 96 92 103 102 4 5 82 103 97 88 Total 534 534 106 123 622 Annual Change 0 650
600
550
500
450
2008
2009
2010
2011
FIGURE 41: Births in Lower Frederick and
Schwenksville Combined by School Calendar
Year (Sept.-Aug.)
School Year 2000‐01 2001‐02 2002‐03 2003‐04 2004‐05 Births 81 120 115 101 92 88 2005‐06 86 91 2009‐10 90 98 89 104 99 101 581 ‐41 2006‐07 2010‐11 81 98 93 85 104 101 562 ‐19 2007‐08 80 2011‐12 2012‐13 68 80 90 80 93 98 90 89 87 89 114 90 542 526 ‐20 ‐16 2008‐09 88 2009‐10 77 2010‐11 67 2011‐12 83 2000‐2005 Avg.
2006‐2011 Avg.
99
81
* The boundary for Schwenksville ES was expanded in 2008 to add students that were formerly in the Skippack ES boundary.
FIGURE 43: Housing Activity Within Schwenksville ES Boundary Area
40
2009 13 104 2010 12 80 2011 5 69 Total 99 432 2012
Note: Schwenksville ES also draws some residents
from parts of Skippack and Perkiomen Townships
so these birth figures should only be used as a
guide to general birth patterns in the school’s area.
but still dropped over the last five years at a rate (24.4%) that was not as bad as the overall county rate
(-38.7%). There are no other pending developments
besides Biltmore, but the area is viewed as a viable
area for future residential development as the market
improves.
Skippack Elementary School serves the largest
portion of residents within Skippack Township. The
school’s boundary area was reduced prior to the 2008
school year. Since 2008, enrollment at the school has
gone up by 4.4 percent, mostly based on a large
kindergarten class in 2009. The school posted small
declines the last three years.
Birth Patterns
Births in Skippack Township have declined the last
two years, but remained fairly consistent throughout
the decade. Birth totals on average were only two
percent lower the last six years compared to the
previous six years.
Housing
Residential construction within Skippack’s boundary
area has been the most active within the PVSD, but it
was still down in recent years. The largest new
development is Biltmore, which began construction
in 2007 but has suffered delays due to the economy
and is still being completed. County records show
approximately 198 units sold and occupied, but the
development was ultimately planned for 226 units
that may still be completed. Housing sales in the
boundary area have been fairly consistent since 2008,
Forecast
Enrollments at Skippack ES are expected to remain
fairly stable for the next two or three years based on
the strong birth numbers through 2009 and some
continued development opportunities. The school
may still see a net drop of about 40 students through
the next five years.
FIGURE 46: Skippack Elementary School Enrollment by Grade, 2006-2012
Annual Change FIGURE 44: Skippack Elementary School Enrollment
820
800
780
760
740
720
700
2008
2009
2010
2011
FIGURE 45: Births in Skippack Township by
School Calendar Year (Sept.-Aug.)
School Year 2000‐01 2001‐02 2002‐03 2003‐04 2004‐05 Births 110 125 147 137 120 Year 2006‐07 2007‐08 K 112 128 1 143 147 2 143 140 3 133 151 4 154 133 5 137 160 Total 822 859 2005‐06 139 2008‐09* 108 133 134 127 128 114 744 ‐115 2006‐07 134 2009‐10 141 133 136 138 129 127 804 60 2007‐08 133 2010‐11 110 153 130 135 143 127 798 ‐6 2008‐09 138 2011‐12 2012‐13 104 102 127 129 149 123 134 142 139 134 138 147 791 777 ‐7 ‐14 2009‐10 139 2010‐11 113 2011‐12 113 2000‐2005 Avg.
2006‐2011 Avg.
130
128
37 * The boundary for Skippack ES was redistricted in 2008, putting some former Skippack area homes into the Schwenksville ES area.
FIGURE 47: Housing Activity Within Skippack ES Boundary Area
2009 18 104 2010 19 109 2011 50 96 Total 254 545 2012
Note: The majority of Skippack residents are in the
Skippack ES boundary, but not all. Birth figures cover
the entire township so should only be used as a guide to
general birth patterns in the school’s area.
41
multifamily units built in 2012. Another proposal
has been submitted for 14 townhouse units in
Collegeville but has yet to be approved.
South Elementary School serves all of the residents
in Collegeville and Trappe Boroughs, and a portion
of residents at the southern tip of Perkiomen
Township. Enrollment at the school has declined
14.1 percent since 2009.
FIGURE 48: South Elementary School Enrollment
700
Birth Patterns
Combined births for Collegeville and Trappe
Boroughs have been 18 percent lower the last six
years compared to the previous six years.
Housing
Residential construction within South’s boundary
area has been consistent but very low since 2007 with
only 46 total units built. Another 33 units were built
in Trappe in 2012, but they were all multifamily units
and are not expected to have as much of an impact on
school age children. Housing sales in the boundary
area have also declined over the last five years at a
rate (-33.6%) lower than the overall county rate (38.7%). The area received several proposals for
developments back in 2007 and 2008 but none
ultimately got approved, except for the 33
650
Forecast
Enrollments at South ES are expected to continue
declining over the next five years. A drop of
between 15 and 25 students is likely for the 2013
school year with a total loss of over 100 students by
2018. The largest annual losses are more likely to be
at four and five years out (2016 and 2017 school
years) due to the recent low activity in births and
housing along with the progression of currently high
enrollments in the first and second grades.
FIGURE 50: South Elementary School Enrollment by Grade, 2006-2012
Year 2006‐07 2007‐08 K 111 84 1 115 122 2 121 115 2008‐09 108 92 2009‐10 97 2010‐11 2011‐12 2012‐13 3 97 118 4 132 99 120 119 104 103 96 101 92 83 107 111 5 2008 4 118 Source: Montgomery County Planning Commission
42
500
2008
2009
2010
2011
School Year 2000‐01 2001‐02 2002‐03 2003‐04 2004‐05 Births 138 129 159 134 150 122 96 657 ‐9 2005‐06 150 128 120 127 679 22 2006‐07 143 103 107 126 126 659 ‐20 2007‐08 121 97 101 101 90 101 97 115 101 613 583 ‐46 ‐30 2008‐09 108 2009‐10 122 2010‐11 103 2011‐12 110 2000‐2005 Avg.
2006‐2011 Avg.
143
118
2009 13 102 2010 11 84 2011 8 101 Total 46 557 ‐5 2012
FIGURE 49: Births in Collegeville and
Trappe Boroughs Combined by School
Calendar Year (Sept.-Aug.)
95 128 FIGURE 51: Housing Activity Within South ES Boundary Area
2007 10 152 550
Total 671 666 Source: Perkiomen Valley School District (enrollment as of October 1 each year)
New Units Built Exis ng Units Sold Annual Change 600
Note: South ES also draws some residents from part of
Perkiomen Townships so these birth figures should only
be used as a guide to general birth patterns in the
school’s area.
East and West Middle Schools
Enrollment projections specific to the two individual
middle schools are difficult to ascertain due to the
fact that the boundaries for the middle schools
intersect elementary school and municipal
boundaries. However, the overall enrollment
projections for the middle school grade levels make it
easier to get an idea of what is happening with each
school since there are only two of them.
East Middle School draws all of the students from
South ES and a portion of the students from
Evergreen ES and Skippack ES. Enrollment at East
MS has bounced up and down over the last five years
but has remained at the same general level.
West Middle School draws all of the students from
Schwenksville ES and the remaining portions of
students from Evergreen ES and Skippack ES.
Enrollment at West has been a bit more stable than at
East but is still slightly down the last two years
compared to four years ago.
since it draws from South ES and a good portion of
Evergreen ES, both of which are losing students at a
greater rate. West MS may not start losing students
until closer to the five year mark since Schwenksville
ES is not losing as many students in the near term
and West also draws from the portion of Skippack
Township where there has been more new
construction.
The overall projections for Middle School students
(Figure C) show small declines over the next five
years growing larger during the last five years. East
MS is more likely to bear the brunt of these declines
FIGURE 52: East Middle School Enrollment by Grade, 2006-2012
Year 2006‐07 2007‐08 6 266 230 7 239 278 8 237 247 Total 742 755 Annual Change 13 2008‐09 294 242 283 819 64 2009‐10 240 283 236 759 ‐60 FIGURE 54: Combined Middle
School Enrollment Projections
Students Annual Change 1,419 2013‐14 1,401 ‐18 2014‐15 1,404 3 2015‐16 1,373 ‐31 Annual Change 35 2016‐17 1,348 ‐25 2017‐18 1,327 ‐21 2018‐19 1,276 ‐51 2010‐11 280 240 289 809 50 2011‐12 2012‐13 264 272 272 268 237 270 773 810 ‐36 37 Source: Perkiomen Valley School District (enrollment as of October 1 each year)
Year 2012‐13 (Current) East Middle School
FIGURE 53: West Middle School Enrollment by Grade, 2006-2012
Year 2006‐07 2007‐08 6 207 217 7 189 204 8 182 192 Total 578 613 2019‐20 1,243 ‐33 2008‐09 203 219 203 625 12 2020‐21 1,202 ‐41 2009‐10 213 217 213 643 18 2021‐22 1,163 ‐39 2010‐11 208 212 211 631 ‐12 2022‐23 1,104 ‐59 2011‐12 2012‐13 186 216 205 187 208 206 599 609 ‐32 10 Total Change from 2012 ‐315
West Middle School
43
44
Conclusion
Part
Conclusion
The Perkiomen Valley School District is in a position
familiar to many districts in the region. After years
and even decades of accommodating growth in the
student body, its elementary schools have started to
see modest declines in enrollment that could continue
to add up over the coming years and prompt new
considerations towards the effective use of facilities.
The general population continues to grow, although
slower than in past decades, but the population of
young children is not keeping pace. Declines in birth
rates over the last ten years and a historically low
period of housing activity have primarily caused the
drop in resident children entering the school system.
The Great Recession may not be responsible for the
drop in births but it was tied in with the bursting of
the housing market bubble and the lengthy recovery
period has continued to restrict housing growth.
Middle school and high school enrollments are still
increasing in the district, but the same forces
bringing young school age children down will
eventually have an effect on those schools as well.
Today’s smaller grade school classes are tomorrow’s
smaller secondary school classes.
The cohort progression model in this study uses
accurate birth data and accounts for recent trends in
enrollment over the last five years. Overall, the
district can expect enrollment to shrink in each of the
next ten years without significant reversals in
housing or population trends. The largest declines
are not expected until the 3-5 year range.
The 6-10 year range is less certain to predict since
births must be estimated at that point. A return to
higher birth rates could offset some of the projected
declines during the 2018-2022 period but there is no
real evidence that this will happen.
Births are important but not the only factor that can
affect enrollment. Not only is housing construction
low, but housing sales of existing units is also less
than half of what it once was. An increase in sales
46
would not immediately provide more children in the
area, but over time it could encourage new and
younger families to move into the district.
Not all school age children attend PVSD schools.
Private school enrollment appears to be down from a
decade ago. Charter schools, cyber schools, and
homeschooling are the choices of relatively few
students, but they are also newer options that were
not around or very popular ten to fifteen years ago.
Enrollment declines at the elementary school level
will not affect all schools the same. More stable
birth activity and the potential for more residential
development could keep Skippack and
Schwenksville elementary schools from losing as
many students as Evergreen and South elementary
schools.
Current signs for the future suggest that the model
should not need to be adjusted. However, conditions
can always change, so there are several indicators
that the district should continually check in order to
recognize if any trends are evolving from what the
model predicted. Housing construction is the most
obvious and could have a more immediate effect if
the market continues to recover and encourages more
development activity. An increase in births would
not effect enrollments for some time until those
newborns became old enough to start school.
Finally, this study is limited to a ten year range and
encourages a greater confidence in the first five years
of that range. However, when it comes to facilities,
an even longer view should be considered. County
forecasts of the population indicate that overall
growth is expected to increase at a faster pace during
the 2020-2030 decade. This is partially due to a
bump in child-bearing age women at the end of the
current decade, which would not only increase the
general population but ultimately the school age
population.

Perkiomen Valley School District Enrollment

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