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From YouTube: Community Facilities Study Meeting #5 Part 4 of 6
Description
Arlington VA Community Facilities Study Committee question-and-answer period about Validating Forecast Methodologies with consultant Bob Scardamalia, RLS Demographics and Richard Grip, Statistical Forecasting, LLC. Recorded April 8 2015 at Wakefield High School.
http://commissions.arlingtonva.us/community-facilities-study/
B
Request
for
a
PS
staff,
it's
not
exactly
a
question.
I'm
tired
of
hearing
the
school
estimates
aren't
any
good,
you
know,
etc,
etc.
Can
we
just
and
I'll
happily
go
into
my
archives
in
my
office
and
dig
out
all
the
papers,
the
mag
and
Todd,
and
others
of
us
have
been
looking
at
for
the
past
decade,
but
we
have
the
numbers
to
come
up
with
how
we're
doing
on
the
53
year.
B
When
what
this
study
group
is
trying
to
do
is
to
look
out
ten
years
look
out
15
years
and
we
need
to
it's
irrelevant
whether
we're
right
on
the
one
year
as
far
as
far
as
this
committee
is
concerned,
and
I
would
just
love
to
really
know
how
we've
been
how
we've
been
doing
on
that
projection
and
because
I
feel
like
we
keep
having
all
this
rumor
and
innuendo
conversation
about.
Our
projections
are
no
good
and
I
really
have
no
sense
of
whether
they're
good
or
not,
and
is
that
possible
to
do
that
or
somewhere.
A
C
Yes,
thank
you
I'm
Gabrielle
Arruda
with
the
committee.
Maybe
this
question
is
now
moot
because
of
what
you
just
said
right
now
in
terms
of
it
wasn't,
it
was
a
methodology
question,
but
it
was
also
a
review
of
sort
of
the
results.
So
one
of
the
questions
I
had
was:
how
did
the
methodology
that
you
use
and
also
then,
when
you
looked
at,
take
into
consideration
or
factor
some
of
the
mobility
that
has
to
very
reflective
of
this
community?
So,
for
example,
military
we
have
the
Pentagon.
We
have
also
the
Defense
University
around
here.
C
So
there's
a
lot
of
folks
that
come
in
and
out
also
State
Department
folks,
so
how
what
type
of
factors
or
what
you
have
in
place
to
account
for
that
and
then
the
other
piece
also
is
certain
phenomena.
One
thing
I
worry
about
is
when
you
rely
on
retrospective
data.
So
looking
back,
how
do
you
account
for
blip?
So
when
we
had
the
recession,
when
we
looked
at
the
numbers,
we
had
a
vast
number
of
kids
that
came
into
the
system,
because
parents
could
not
afford
their
private
schools
and
they
stayed
in
the
system.
C
So
when
you
just
look
at
data,
if
you
missed
that
point
right
or
if
you
don't
look
far
enough
to
capture
that
data,
how
do
we
know
what
is
happening
in
the
future?
If
we're
I
know
it,
nobody
has
a
crystal
ball,
but
how
do
we?
How
do
we
know
that
or
what
are
the
other
databases
or
sources
out
there,
that
we
could
possibly
look
to
to
help
be
more
accurate
with
the
five
and
ten-year
projection
on.
E
D
To
be
clear
about
that,
in
my
personal
esteemed
opinion,
I'm
going
to
go
back
to
the
first
question
in
terms
of
military,
how
do
you
account
for
that?
It's
a
great
question:
migration,
all
different
kinds
of
people
moving
in
and
moving
out,
here's
the
thing
the
progression
ratios
are
supposed
to
be
this
catch-all
basin
for
all
this
type
of
migration
going
in
and
out,
there's
a
net
either
it's
plus
or
minus.
The
question
is:
does
is
it
specifically
looking
at
military
migration
or
migration
do
to
people
moving
in
for
new
housing?
The
answer
is:
no.
D
You
can't
break
it
down
that
way,
but
it
a
grits
and
it
does
look
at
the
net
effect.
So,
for
instance,
if
you
have
a
hundred
first
graders
and
the
next
year,
you
have
a
hundred
and
twenty
second
graders
due
to
net
migration
due
to
military
bases
due
to
new
homes.
You've
got
a
twenty
percent
bump
up
because
of
that
now
we
don't
know
why,
but
it's
there
and
we
see
it
in
the
data.
So
there's
no
really
way
of
teasing
out
of
where
it's
coming
from.
D
The
key
thing
is:
if
that
migration
is
only
happening
a
one
time
event.
That's
when
we
have
problems.
That's
that
anomaly.
That
you're,
referring
to
when
I
looked
at
I
looked
at
mr.
white
gave
me
some
of
your
data
to
look
at
for
one
of
the
attendants
areas
and
I
looked
at
the
survival
ratios.
The
progression
of
ratios
from
the
last
14
years
that
looked
at
boom
times
looked
at
bus
times
and
I
really
didn't
see
much
of
a
difference
in
terms
of
rather
than
just
relative
noise,
which
we
normally
see
in
these
progression
ratios.
D
In
some
my
clients,
that's
partly
because
you
have
a
very
big
large
Gray's
where
the
noise
can
be
dampened.
But
if
you
have
a
smaller
grade
cohorts
what
I
sometimes
do
is
I
throw
out
any
any
ratios
that
are
above
plus
minus
one
standard
deviation
from
the
mean,
because
you
know
that
is
just
too
extreme,
but
I
did
not
see
anything
like
that.
Just
looking
back
and
as
far
as
data
sources
that
are
out
there
I'm
going
to
be
honest
with
you,
I
think
the
data
sources
that
they're
using
are
perfectly
fine.
F
And
if
I
can
John,
if
I
can
add
just
to
that
part
of
part,
I
think
there's
two
pieces
here
you
I
absolutely
agree
with
with
rich.
If
we
knew
that
the
recession
was
going
to
happen,
we'd
have
done
lots
of
things
different.
We
simply
don't
know
those
things
having
methods
and
in
both
the
county
and
the
school
district
have
methods
and
it
gets
to
riches
comment
about
alternatives.
F
What
would
happen
if
unemployment
took
a
dive
three
years
from
now
being
able
to
run
the
different
methods
and
run
different
scenarios?
Certainly
doesn't
tell
you
what's
going
to
happen,
but
it
gives
you
an
idea
of
what
the
range
of
possibility
is
going
to
happen.
The
other
thing
the
Census
Bureau
produces
from
the
American
Community
Survey,
microdata,
public
use,
microdata
and
what
it
gives
you
is
detailed
characteristics
about
my
response
to
the
survey.
F
My
household
information,
my
demographic
information,
that's
a
data
source
that
could
be
mined
because
you
can
look
at
migration
and
you
can
get
a
one-year
profile
of
who's
moving
in
who's
moving
out.
So
if
you
all
had
all
the
resources
that
you
would
love
to
have
would
be
a
data
source
that
you
could
analyze
and
add
value.
F
A
G
Crystal
crystal
city,
I
think,
is
great.
I
get
this
external
support
in
coming
up
with
ideas
for
how
our
forecasts,
which
I
think
they
both
emphasized
or
realistically
in
terms
of
precision,
really
possible
to
improve
primarily
in
the
short
term,
and
of
course,
we
know
that,
even
for
the
whole
sort
of
lead
time
decision
making
citing
construction
for
a
school,
we
are
not
talking
about
getting
two
or
five
years
for
warning
realistically
and
more
over.
Here
we
are
talking
about
not
just
school
capacity.
We
are
talking
about
demographics.
G
What
it
will
are
of
population
situation
be
20-30
years
down.
The
road
it
seems
to
be
are
not
picking
up
on
something
that
Richard
added
sort
of
in
passing,
at
the
end
that,
beyond
what
we
can
do
to
improve,
perhaps
in
a
relatively
of
marginal
way,
our
methodology
in
forecasting
that,
to
a
large
extent,
everything
that
is
longer
term
depends
much
more
on
fundamental
assumptions.
G
If
we
are
talking
about
the
aging
population,
will
they
want
to
stay,
and
will
we
be
able
to
provide
a
situation
where
they
can
aid
in
place?
So
it
seems
that
the
correctness
of
ambitionz
about
population
in
20,
40
or
something
like
that
and
the
composition
of
it
depends
much
more
on
sort
of
almost
wild
guesses
fundamental
assumptions
about
some
of
these
really
major
issues,
rather
than
fine-tuning
your
methodology.
So
I
would
like
to
get
some
comments
on
that.
You.
F
Have
to
be
absolutely
crystal
clear:
a
projection
whether
it's
a
school,
enrollment,
housing,
demographics,
whatever
is
a
set
of
assumptions
about
what's
going
to
occur
in
the
future
and
those
numbers.
If
those
assumptions
are
borne
out-
and
my
projections
are
right
on
the
money
who
would
have
imagined
that
40
years
ago,
I
could
have
hit
that
number
right
on
the
nose.
Well
I'd
like
to
say
it
happens
more
frequently
than
it
does,
but
chances
are
it's
not
because
we
simply
don't
know
you
have
to
understand.
Projections
are
nothing
more
than
that.
H
For
this,
my
question
I've
got
a
lot
of
questions,
but
I'll
ask
one
now,
which
is
something
you
also
highlighted
in
your
report,
around
the
data
gap
from
zero
to
five
and
in
getting
clarity
on
that
would
also
help
to
feed
information
up.
That
would
make
your
kindergarten,
your
projections
better,
all
the
way
through
so
I'm
wondering
one.
H
Are
there
recommendations
for
how
we
could
do
that
and,
for
example,
New
York
with
their
pre-k
initiative,
I
presume
there
was
some
sort
of
modeling
that
they
try
to
get
a
handle
on
what
their
numbers
were
before
they
put
a
dollar
number
behind
it.
So
what
are
some
ways
that
we
could
think
about
it?
And
that
leads
me
into
another
question,
which
is
that
there
are
about
a
hundred
and
ten
thousand
households
in
Arlington
about
thirty.
H
Seven
percent
of
those
are
single-family
homes,
and
that
has
been
the
primary
driver
of
the
school
enrollment
growth
so
give
or
take
40
thousand
single-family
homes.
Are
there
other
districts
that
just
do
phone
surveys?
You
know
random
sample
phone
surveys
of
you
know
10,000
households
in
there
and
and
actually
have
a
a
sort
of
a
real-time
picture
of
what's
going
on
in
the
district
sort
of
catching.
What
gabrielle
was
saying
some
some
of
these
blips
on
these
in
and
out
migrations?
So
are
there
other
other
tools
that
you're
seeing
other
districts
doing?
D
All
of
our
good
questions
regards
to
the
birth
decay
and
the
pre-k,
at
least
in
New
York.
That's
actually
still
an
ongoing
process
where
we're
trying
to
figure
out
how
many
you're
going
to
actually
wind
up
coming
into
the
system-
and
you
know,
unfortunately
it
is
a-
is
a
problem.
You
know
you've
got
five
year
gap
between
kids
being
born
and
then
coming
into
the
school
system
five
years
later.
So
what
are
your
options?
Can
you
do
a
phone
survey?
Could
you
do
a
mailing
survey,
all
these
different
options
at
your
disposal?
D
Now
it's
somewhere
it's
somewhere
in
the
low
70s,
72,
73
percent,
and
because
that's
the
ability,
you've
had
really
good
kindergarten
projections
in
the
last
couple
years.
So
I
think
that,
right
now
at
least
right
now,
I
would
say
that's
your
best
bet,
but
to
go
and
do
a
survey.
I
really,
in
my
honest
opinion,
is
I.
Think
you
would
just
be
you'd,
be
throwing
a
lot
of
time
and
money
into
the
wind
but
Bob.
You
may
have
some
comments
on
it:
okay,
Sal.
I
Yeah
I
was
just
curious
in
all
your
work
around
the
country.
If
you
see
any
good
studies
on
the
Millennials,
they
just
seem
to
be
a
mystery
to
everyone
in
Arlington.
You
are
these
mysterious
or
tougher
aid
of
the
Millennials.
What
are
they
going
to
do?
They're
gonna
stay
and
go.
Is
there
any
trend
that
we
see
where
the
Millennials
are
are
staying
in
certain
areas?
I
can
tell
them
kind
of
an
old
gen
Xer.
When
I
look
at
the
numbers
from
arlington,
we
moved
in
here
in
two
thousand.
I
We
bought
up
a
lot
of
housing
base.
We
had
kids,
we've
stayed
because
we
got
in
in
the
bubble
and
rode
that
up
to
great
appreciations
in
general
and
the
Gen
Xers
may
not
have
that
opportunity
here.
But
are
you
seeing
anywhere
else
around
the
country
where
certain
factors
and
certain
behaviors
of
the
Millennials
are
starting
to
play
out
in
some
way,
because
that
just
seems
to
be
a
big
question
here
like
we
can't
can't
get
our
hands
around
these
Millennials
and
I.
F
You're,
asking
a
guy
who's,
63
years
old,
to
try
and
get
a
handle
on
the
Millennials.
I
have
three
of
them:
three
sons
who
were
raised
in
New
York,
upstate,
New
York
rural
area.
One
of
them
is
here
in
the
Reston
area.
Tour
in
Los,
Angeles
I
did
a
paper
number
years
ago
with
a
colleague
at
Cornell
who
has
three
sons.
It
was
on
brain
drain
because
brain
drain
in
New,
York
State,
is
as
a
huge
issue
at
the
time
he
had
a
son
in
Boston,
the
Sun
in
Philadelphia
and
a
son
in
San
Francisco.
F
So
if
there's,
if
there's
something
that's
going
on,
whenever
I
talk
to
my
class
and
I
asked
them,
you
know
this
is
in
Albany
how
many
of
your
going
to
stay
in
Albany
after
you
graduate
none
of
them,
New
York,
City.
Many
of
them
are
coming
from
the
city.
That's
where
they're
going
back
so
this
this
movement
back
to
urban
areas-
and
you
know
lington-
is
just
prime
for
that
population
to
come
with
a
not
necessarily
come
back,
but
to
import
from
other
areas
because
of
federal
jobs.
F
Just
general
mystique
of
Washington
and
what's
going
on
here,
all
of
the
large
metropolitan
areas
are
experiencing
that
New
York
same
thing,
Boston
same
thing.
So
can
we
get
a
handle
on
it?
You
know
I'm,
not
sure
you
can
get
much
of
a
handle
again.
I
come
back
to
that
micro
data
from
the
Census
Bureau,
because
you
can
look
at
that
age
range.
What
are
their
characteristics?
What
are
their
education?
What
are
their
occupations?
F
You
know
in
roughly
that
mid-teens
to
30
s
population
where
are
they
moving
to
and
from
and
I
think
mining
that
data
helps
helps
get
a
handle
on
it.
There's
so
much
anecdotal
stuff
about
the
Millennials
in
the
media
that
it's
hard
to
answer
that
question.
So
I
come
back
to
what
can
you
do
with
the
data
and
that
would
be
the
data
source
to
you
to
utilize.
A
A
D
Millennials
are
still
living
in
their
parents.
Basement
I
mean
that
that's
you
know
part
of
the
problem.
I,
don't
think
that's
the
case
here
in
Arlington,
but
you
know
it
doesn't
seem
to
be,
but
a
lot
of
the
districts
that
I
work
with
are
in
New
Jersey
and
their
suburban,
and
they
have
incredibly
high
media
single-family
homes,
incredibly
high
taxes,
twenty-five
thirty
thousand
dollars
on
a
single-family
home.
D
It
just
prices
these
people
out
and
they're
completely,
not
even
interested
in
moving
into
these
communities,
and
they
have
in
Creole
e
sharp
declining
enrollment
because
of
it,
and
they
keep
asked
me
one
of
these
people
going
to
start
moving
into
our
community.
We
expect
them
to
come
in
I,
don't
think
they're
coming
and
they
don't
seem
to
get
that
I
think
they're
more
interested
in
in
living
in
an
urban
core.
Again
this
is
anecdotal
and
renting,
perhaps
with
the
housing
bus
they
don't
want
to
have
a
home
where
they're
underwater
with
their
mortgage.
F
On
their
coming
to
that
urban
core,
along
with
other
Millennials
I,
mean
all
three
of
my
kids
did
a
stint
in
New
York
City
and
they
were
rooming
with
three
or
four
or
five
other
kids,
because
that's
the
only
way
they
could
afford
it
so
that
that
affordability
issue
is,
is
big-time,
they're,
they're,
delaying
marriage,
they're
delaying
childbirth.
If
you
look
at
fertility
rates,
we're
talking
about
peak
fertility
rates
in
the
early
30s
rather
than
my
generation,
the
early
20s,
so
those
things
are
happening.
F
A
F
J
So
I
really
really
hope
that
we
can
use
that
type
of
data
to
refine
our
forecasts
for
our
single-family
homes,
because
you
know
looking
at
Lionel's
numbers
from
the
last
presentation,
the
the
additional
students
we
got
in
over
the
last
eight
years
from
the
single
family
homes
was
greater
than
every
other
housing
type
added
together.
So
we
really
do
want
to
get
a
good
handle
on
what
our
single-family
homes
will
produce
as
students
in
our
school
system.
J
My
follow-up
question
is:
we
have
also
a
fear
that
the
generation
factors
in
our
multi-family
homes
will
change
and
we
have
a
larger
and
grow
housing
stock
of
multifamily.
Do
you
guys
have
ideas
about
getting
a
better
insight
into
the
potential
or
the
futures
that
we
could
see
with
multi-family
housing
in
student
generation.
F
You
know
in
terms
of
that
last
part
of
your
question.
I
would
again
look
to
that
census,
microdata,
because
I
can
look
at
household
type
and
the
demographics
associated
with
it.
You
don't
find
in
general
census
information,
those
kind
of
cross,
tabulations
and
so
generating
that
unique
type
of
characteristic.
I
think
would
we
a
data,
p
piece
of
the
data
that
you
could
start
to
look
at
and
analyze
housing
type
and
monitoring
that
on
an
annual
basis,
where
it's
going
to
go
that
still,
it's
still
a
tough
one.
D
Yeah,
the
first
partier
was
more
of
a
comment,
I
think
and
and
I'll
just
actually
I'm
glad.
You
brought
that
up,
because
one
thing
I
forgot
to
mention
it's
actually
in
the
report
when
I
work
with
New
York
City
to
find
out
student
generation
factors,
we
use
the
pumps
data
set,
which
is
what
Bob
has
been
talking
about
last
couple
minutes
and
our
universe
is
recently
constructed
homes
from
the
last
decade.
Now
you
could
probably
do
something
like
that,
even
here
to
get
a
better
handle
on
yields,
rather
than
looking
at
the
whole
entire
stock.
D
You
know
you
have
to
have
a
lot
of
homes,
of
course,
built
in
that
Prop
10
years,
but
the
problem
we
run
into
is
the
sample
size.
The
ACS
is,
you
know,
even
if
we
use
a
five
percent
sample,
we
get
these
standard
errors
that
are
just
over
the
top,
and
our
coefficients
of
variation
are
just
so
ridiculous
that
it
means
that
our
yields
are
really
just
not
worth
the
paper
that
they're
printed
on
so
and
that's
for
the
largest
city
in
america
that
we're
dealing
with
New
York
City.
D
So
we
have
to
start
collapsing
categories
to
the
point
where
we
cannot
compute
yields
by
age
and
we'd
like
to
do
that,
because
we
want
to
know
how
many
elementary
kids,
how
many
middle
school
kids,
how
many
high
school
kids
come
out
of
a
housing
unit.
But
we
can't
do
that.
So
we
have
to
collapse
it
and
get
the
yield
for
the
whole
entire
borough.
We
don't
do
it
by
the
city
and
we
can't
even
do
it
by
housing
type,
because
the
sampling
error,
so
we
have
to
look
at
palms.
D
Maybe
is
something
you
can
look
at,
but
that's
another
option,
because
that
graph
that
I
showed
you
it's
analogous
I
mean
the
palms
data
is
looking
at
recently
built
homes
so
that
whole
thing
I'm
trying
to
say.
If
we
just
look
at
the
first
10
years,
it's
kind
of
analogous
to
having
homes
that
are
just
built
in
the
last
10
years,
because
those
are
the
people
that
are
moving
into
the
homes
and
buying
the
homes.
That's
why
I
said
to
take
the
average
of
the
first
ten
years
with
that
length
of
ownership
model,
Tonya.
K
So
I
just
wanted
to
I
guess
confirm
with
you
guys
some
things,
the
reason
that
I
think
or
my
understanding
is
the
reason
you
guys
are
here
is
because,
during
the
demographics
of
Arlington,
County
and
ApS,
there
were
some
discrepancies
or
some
missing
for
me.
Well,
not
miss
information,
but
just
different
presentations
of
information.
Okay,
and
so
it
sounds
like
both
the
county
and
the
school
system
are
doing
a
deep,
a
really
good
job
in
projections.
K
Well,
our
job
as
a
committee
is
to
figure
out
what
kind
of
fire
stations
are
going
to
need
in
the
future,
where
they're
going
to
go
schools,
bus
parking
transportation.
All
these
things
that
are
part
of
a
community.
You
know
a
growing
community
in
our
community.
As
you
said,
it's
dynamic,
unique
because
of
the
train,
you
know
well,
everyone
knows
why,
because
we
discussing
it
for
the
last
five
meetings
or
whatever.
K
So
when
we
go
and
start
analyzing
this
should
we
be
using
when
we're
projecting
schools
and
bus
transportation,
the
school
data
and
consider
that
more,
you
know
considered
as
a
hot
you'd
like
a
in
other
words,
sometimes
there's
a
discrepancy
us
to
a
projection.
Okay.
So
if
the
county
is
saying
that
multi-family
housing
is
going
to
produce
two
kids
per
unit
and
the
school
system
is
saying,
1.5
kids
per
unit
well,
when
you're
looking
at
big
number
is
that
point.
Five
makes
a
big
difference
right,
which
one
should
be
kind
of
focused
on.
K
Should
we
for
the
fire
station
should
we
use
the
county
data
and
for
the
school
system
should
use
the
school
data
because
clearly
they're
both
good
methodologies
for
their
respective
purposes,
but
for
the
purpose
of
our
committee?
What
do
we
do
because
is
that
I
don't
know
weenie
I
think
you
know
that
make
sense.
Well,.
D
Look
the
student
generation
factors
their.
This
is
where
you
got
to
collaborate
between
the
two
groups
and
there
shouldn't
be
a
discrepancy
between
the
two
I
mean.
In
fact,
the
pipeline
date
is
coming
from
the
county
government.
So
I
find
that
kind
of
hard
to
fathom
why
they
would
be
off,
but
that
they
should
they
should
be
right.
You
know
they
should
be
using
the
same
data.
In
fact,
when
I
work
in
New
York
City,
where
am
I
getting
my
data
from
I'm
getting
my
data
from
New
York
City
Department
of
Planning.
D
F
I'd
only
add
to
that
that,
depending
upon
why
those
differences
are
existing,
you
should
be
able
to
resolve
them,
even
if,
even
if
that
resolute,
there's
no
single
perfect
piece
of
data.
So
even
if
you
resolve
some
of
the
major
differences-
and
you
still
have
some
difference
between
the
two
that
gives
you
your
range
of
what
ifs
you
know.
So
what
if
the
county
number
is
more
accurate?
What
if
the
school
district
number
is
more
accurate?
It
gives
you
that
range,
and
it
gets
back
to
that.
A
L
Hi
mike
thomas
arlington
forest,
thank
you
for
a
very
interesting,
informative
presentation.
I
think
your
app
easier
to
make
projections
in
a
static
environment
than
a
dynamic
environment.
This
is
a
very
dynamic
environment.
We
have
a
housing
stock
right
now,
if
I
think
110,000
units.
The
county's
projections
are
that
we're
going
to
add
40,000
units
to
that
over
the
next
25
years.
That's
dynamic
change,
there's
not
room
for
single-family
houses,
they're
going
to
be
multifamily.
Well.
L
If
we
look
at
the
current
data,
we'd
suggest
that
they're
not
gonna,
be
many
students
generated
from
that,
and
we
think
that
most
of
the
new
students
coming
into
the
schools
are
from
single-family
houses.
Yet
out
of
those
1,200
new
students
that
came
into
the
schools
last
year,
ten
percent
came
from
a
single
multifamily
house
or
multifamily
development,
so
they're
not
all
the
same.
L
So
these
are
the
sorts
of
things
that
we
need
to
be
considering
as
we
do
this,
the
40,000
new
housing
units
that
we're
going
to
build
in
Arlington
are
there
going
to
be
studios.
One
bedrooms
two
bedrooms,
three
bedrooms:
it
makes
a
difference
if
there
are
two
and
three
bedrooms
and
the
Millennials
move
into
those.
That's
a
lot
different
than
there's
a
bunch
of
studios
and
one
bedrooms.
D
Want
to
add
real,
quick
I
promise
five
seconds
just
in
regarding
the
yields.
You're,
absolutely
correct.
We
try
to
do
is
get
specific
yields
by
bedroom
counts
and
that's
tough,
sometimes
because
a
lot
of
times
we
just
don't
have
the
data
on
that
I'm,
not
sure
if
the
palms
would
even
go
down
to
that
level
in
terms
of
number
of
bedrooms,
but
the
other
thing
was,
it
does
I
thought
so.
The
other
thing
is
that
every
multifamily
development
is
not
the
same
in
terms
of
amenities.
D
M
M
So
that's
just
a
question:
why
why
the
execution
isn't
being
considered
for
those
demographic
figures
and
then
the
suggestion
is
I
share.
The
concern
everyone
has
is
that
everything
here
revolves
around.
What
did
the
Millennials
do?
I
agree
that
surveys
can
be
problematic,
because
if
you
send
a
millennial
household,
a
survey
asking
them
about.
Are
you
you
know
their
kids
they're
going
to
answer
if
they
have
kids
or
plan
to
have
them
they'll,
throw
it
out
if
it's
not
in
the
cards
right
now,
so
maybe
a
poll
would
be
more
appropriate.
M
M
You
know,
if
you
ask
Millennials
of
that
sort.
Where
do
you
see
yourself
in
five
years?
Like
those
interview,
type
questions,
do
you
see
yourself
forming
a
household?
You
see
yourself
living
and
living
where
you
are
now
or
somewhere
else.
They
might
actually
answer
you
I,
don't
know
it
just
seems
like
asking
them.
What
they're
going
to
do
might
yield
some
results
and
I
don't
mean
asking
all
of
them,
but
a
poll.
F
So
I'm
not
sure
what
the
best
way
of
structuring
such
a
poll
would
be
I.
Think,
there's
probably
a
lot
of
national
anecdotal
type
approaches
to
that.
I
always
caution
my
students
to
look
at
the
source
of
the
data,
though,
and
if
you're
talking
about
all
Millennials
behavior
based
on
a
poll
of
a
thousand,
you
probably
have
some
some
issues
there
on
the
first
part
of
your
comment
about
you
know
what
might
that
enrollment
be
in
in
five
years?
That's
where
I
come
back
to
the
demographic
method.
F
If
I
can
look
at
what
the
female
population
is
going
to,
what
the
Millennials
of
a
certain
age
are
going
to
be
in
five
years
apply
a
fertility
rate
to
them.
I
can
generate
a
number
of
births,
and
that
starts
to
give
me
that
connection
between
the
demographic
change
in
terms
of
aging
of
the
Millennials,
who
you
know
primarily,
are
in
their
chonies
now
not
having
children
and
in
5-10
years
they're
going
to
be
in
their
30s
and
that's
when
they're
having
children.
F
That's
where
I
may
be
able
to
see
that
yeah
you
are
going
to
look
at
another
thousand
increase
five
or
ten
years
down
the
road.
So
again
it's
it's
another
piece
of
the
puzzle.
Is
it
going
to
tell
you
exactly?
Probably
not,
but
it's
another
piece
that
can
be.
They
can
add
value
to
the
methods
that
are
already
being
used.
N
Stealin
with
the
nining
ham
PTA,
the
2008
CIP
for
2009
through
14,
has
five-year
projections
in
it.
They
were
low
for
total
enrollment
by
eighteen
percent
five
years
out
and
they
were
low
for
elementary
by
twenty-seven
percent
five
years
out.
So
that's
the
degree
of
error
built
in
and
it's
one
thing
if
their
methodology
might
make
sense,
but
the
cohort
progression
rate
that
was
described
here
when
they
went
over
that
between
fifth
and
sixth
grade
was
a
loss
of
one
point.
Three
percent
at
that
transition
point
in
the
actual
forecast,
that's
out
there.
N
The
cohort
progression
rate
is
different
and
every
year
and
gets
as
high
as
a
loss
of
eleven
percent
in
the
last
year
of
the
model.
So
we
disappear
600
middle
school
students
in
the
out
years
of
our
model,
which
then
becomes
an
even
larger
number
in
high
school
later
on
so
I,
don't
know
if
we
have
alien
abduction
of
students
going
on,
but
we
do
not
have
the
methodology
that's
predicted
being
executed
and
the
numbers
that
we're
basing
our
future
plans
on
so
you're
here
to
help
us
figure
out.
N
We
need
to
be
looking
at
overall
employment
growth
in
the
area
and
to
improve
your
model
about
the
age
would
be
great,
but
what
we
also
need
to
look
at,
because
we
have
so
much
build
out
of
housing
stock
in
the
1950s.
You
also
need
to
be
looking
at
at
the
time
the
age
at
which
owners
cell,
because
if
you
have
a
whole
lot
of
neighbors
approaching
retirement
age
or
approaching
end
of
life
age
well,
those
houses
are
going
to
turn.
N
And
so
you
need
to
be
looking
at
the
age
at
which
people
sell
in
the
average
age
and
family
size
of
homebuyers
in
an
area.
Because,
basically,
what
happens?
Is
retirees
who
have
been
in
their
homes
for
20
or
30
years,
sell
to
developers
who
double
the
size
of
the
house?
And
then
families
buy
it?
And
then
the
other
thing
we
need
to
look
at
is
the
ratio.
What
happens
as
areas?
N
And
there
are
other
cities
have
done
this
before
us-
increase
the
cost
of
housing
faster
than
income
Rises,
because
the
family
that
bought
a
starter
home
five
years
ago
can't
even
buy
that
lot
now.
So
they
wait
until
they
have
two
kids,
three
kids
who
are
about
to
enter
school,
and
then
they
move
into
that
neighborhood
and
buy
that
bigger
house,
because
they
have
five
years
of
home
equity
and
five
more
years
of
stock
market
gains.
N
And
five
more
years
of
savings
to
apply
to
buying
into
those
areas,
so
there
are
some
things
we
need
to
be
doing.
We
I
hope
we
can
ban
the
phrase
the
Millennials.
We
are
a
tiny
percentage
of
the
DC
area.
We
are
a
niche
market,
it's
about.
Are
we
attractive
to
small
niches
of
all
the
generations
that
are
having
kids,
which
includes
some
pretty
old
parents
in
Arlington?
And
so
it's
not
just
the
Millennials
who
are
having
kids
this
year,
who
are
going
to
be
driving
our
high
school
enrollments
18
years
from
now?
N
E
E
Well,
not
she
had
me
now
in
my
generation
women,
a
lot
of
women
who
were
college,
educated,
delayed
children
and
into
their
40s,
but
you
know
I,
don't
know
how
you
figure
that
how,
when
I,
when
I,
listen
to
television
reporters
talk
about
demographics
in
the
United
States,
they
say
well,
the
Hispanic
community
has
a
far
greater
fertility
rate.
They
have
more
children
per
family,
they
have
children
earlier.
We
have
a
large
Hispanic
population
and
I'm
not
saying
this
to
be
in
any
way.
Racist,
but
I.
E
Don't
think
that
you
can
I,
don't
know
how
you're
going
to
figure
fertility
rates.
I
mean.
Do
you
are
you
going
to?
You
know
figure
out
what
the
percentages
of
Hispanics,
who
are
likely
to
have
larger
families
earlier
in
life
or
the
percentage
of
women
who
are
college
educated,
who
are
more
likely
to
delay
and
have
fewer
kids
I.
Don't
know
how
you
figure
that,
but
you
know
just
just
saying:
oh
well,
you
know
by
the
time
a
woman
reaches
30
she's
going
to
have
kids.
F
I
convey
a
cavalier
attitude
towards
it.
There's
data
the
State
Health
Department
and
the
national
center
for
health
statistics
will
provide
us
with
birth
data
by
age
of
woman.
So
we
can
look
at
census
populations
by
age
and
we
can
look
at
the
number
of
births
by
women
of
that
age
at
a
county
level,
and
from
that
you
calculate
a
fertility
rate.
F
What
proportion
of
women
aged
30
to
34
are
having
children
and
when
you
look
at
that
graphic
in
the
nineteen
in
the
baby
boom
years
that
graft,
starting
at
about
15
to
19,
had
a
sharp
peak
by
20
to
25
and
then
it
gradually
tapered
off.
When
we
look
at
that
graph
today,
it's
low
in
the
20s
and
then
by
the
late,
20s
and
30s
early
30s,
you
hit
that
peak
and
then
yes,
it
tapers
off
again
a
little
bit
higher
with
women
in
the
40s.
F
But
still
that
peak
is
in
those
ages
of
30
to
34.
Are
there
variations
by
race?
Yes,
black
fertility,
Latin
fertility,
Asian
fertility,
the
data
exists,
the
quality
is,
is
a
question
mark,
but
you
can
still
look
at
those
patterns
and,
yes,
national
trends
for
higher
fertility
of
Hispanics
correct.
Is
that
also
the
case
in
early
Arlington?
We
can
look
at
the
data,
so
come
back
to
saying.
You've
got
to
look
at
the
data
to
really
understand
how
Arlington
behaves
similar
to
other
areas
or
differently
to
other
areas,
but
the
data
exists
to
do
that.