THE DETERMINANTS OF OFFICE LOCATION
IN THE NEW YORK METROPOLITAN REGION
by
James Murphy
B.A. Yale University
1980
Submitted
in Partial
of
to the Department of Urban Studies and Planning
of the Requirements for the Degree
Fulfillment
Master of City Planning
at the
Massachusetts Institute of Technology
June 1983
James Murphy 1983
grants to M.I.T. permission to reproduce
document in whole
thesis
copies of this
The author hereby
and to distribute
or in part.
Signature of Author
D
r-tment of Ur a
tudies and Planning
NJ
9 May 1983
Certified by
Professor Karen Polenske
Thesis Supervisor
Accepted by
I
iz
Hotc
MASSACHUSETTS iNSTITUTE
OF TECHNOLOGY
JUL 211983
LBRARIES
Professor Donald Schon
Chair, MCP Committee
The Determinants of Office Location
in the New York Metropolitan Region
by James Murphy
Submitted to the Department of Urban Studies and Planning
on 9 May 1983 in partial
fulfillment of the requirements
for Degree of Master of City Planning.
Abstract
In New York City, as in the nation, blue-collar
employment is losing ground to white-collar, factories to
offices.
Since office jobs are concentrated in Manhattan,
there is a growing disparity of employment opportunity
between Manhattan and the outer boroughs of New York City.
Moreover, this spatial disparity is compounded by an
immense skill disparity:
office
jobs are ill-suited
to New
York's huge blue-collar
labor force.
The continuing loss
of manufacturing jobs, nonetheless, has caused many to look
to office development as the only potential source of new
jobs in
the outer
boroughs.
These outer boroughs are
thought to be in competition with the suburbs primarily for
back office functions that are priced out of the Manhattan
office
market.
We designed an empirical analysis of the determinants
of office location in the suburbs of New York City. Such a
of the
us judge the ability
study, we thought, could help
We sought to
office
development.
outer boroughs to attract
explain the variations in office rents across towns by cost
Do rents vary across
factors, and by amenity factors.
towns because the costs of office development vary, or
because the amenities of the towns vary?
We hypothesized
that
since
the supply of office
space is fixed
in the short
run, demand for various amenities would bid up rents in
some towns more than others.
The results
of our analysis
were consistent with our hypothesis:
amenity factors
predicted rents much better than did cost factors.
We
suggest that long-term rent differentials across towns can
best be explained if one assumes a monopolistically
competitive
office
market.
We interpret
our findings
in
the context
of other
important theoretical
and empirical
research on office location.
2
What consequence do these findings have for New York
development in the outer
to stimulate office
City's efforts
The amenity orientation of office location poses
boroughs?
dilemmas for the city in that those locations most
attractive to developers are also those locations least in
only by
we argue that
Finally,
need of development.
reducing the fiscal and political balkanization of the
development
office
New York be able to divert
region will
from Manhattan to the depressed business districts of the
outer boroughs.
Thesis Supervisor:
Professor
Title:
Karen Polenske
3
Acknowledgments
I
and
am indebted
This
Economics.
during
I
committee:
and
Karen
when
at
times
William
C.
Wheaton,
that
was
there
who provided
underpinnings
theoretical
Polenske,
confidence
her
thesis,
for
for
RPA
research
my
members
the
thank
Professor
encouragement
President
1982.
to
wish
also
of
study grew out
the summer of
Vice
Armstrong,
Regina
to
particular
in
(RPA)
Plan Association
to the Regional
my
of
for
my advisor,
Professor
doubt;
and Mr.
of the study;
on
help
essential
her
complete my
I would
some
thesis
the
Edward H.
Kaplan, for his indispensible help in designing the statistical
analysis.
Ed
Kaplan
merits
special
acknowledgment
because of his brilliance, patience, and generosity.
to my parents,
I am very grateful
Murphy,
for
their
support
constant
Finally, but by no means
typist,
Ms.
Jacqueline
LeBlanc,
processor proved indispensible.
4
least,
whose
Mr.
and
I am
skill
and
Mrs.
Donald
encouragement.
indebted
with the
to my
word
Scheme of Contents
Page
6
Its Consequences........ ........
I.
The Transition and
II.
Back-Office Development:
Fact or Mirage?..........10
III.The Outer Boroughs Versus the Suburbs..............13
IV.
An Analysis of the Determinants
of Office Location........................ .........
A.
B.
C.
D.
V.
The Cost Model...
The Amenity Model
...............
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.16
.18
.23
.26
Office Location. ........ 31
Specifics of the Cost Model........... .
Amenities and Monopolistic Competition .
Amenities and Office Location Theory.. .
Offices and Household Location Theory. .
Public Policy and Office
A.
B.
C.
.
.
00 0 .
.
Diagnostics....
...... 0
The Amenity Orientation of
A.
B.
C.
D.
VI.
Introduction.....
The Variables and Some
16
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.32
.33
.35
.37
Location...................39
A Role for Government?................
The Dilemmas of Office Development....
What Is To Be Done?...................
.
.
.
. . . . .39
. . . . .41
. . . . .45
Tables.................................................48
Table 1:
Data Matrix for Selected Variables.......48
Table 2a:
1982 Electricity Cost Differentials
Table
in the
Reg ion ............................
1981 Income Tax Differentials
in the Region............................51
2b:
51
Table 3:
1980 Office Building Operating
Table
Expenditures.............................52
Correlation Matrix for Selected
4:
Variables................................53
Table 5:
Derivation of Dependent Variable
and Its Variance.........................54
Notes..................................................55
Bibliography...........................................58
5
I.
The Transition and Its Consequences
The office building has come to replace the
factory as the symyol of contemporary urban
economic development.
New York
1950-1980,
City's economic
the
manufacturing
city
lost
problems
540,000,
Of the
jobs.
1977, 227,000 were
remain
or
558,000
severe.
one-half,
of
net job loss
in manufacturing.
From
its
from
1970-
By contrast,
there
was a net gain of 111,000 jobs from 1977-1980, despite a
loss
of
40,000
This
fledgling
recovery,
during the early
in
business
jobs.
after
during
this
period. 2
loss
of jobs
a catastrophic
1970s, was due almost entirely
and professional
Since
jobs
manufacturing
1977,
services
the growth
--
of
to growth
that
office
is,
office
employment
has
exceeded the decline in manufacturing employment.
important
More
the profound
growing
to
of
office
this
disparity
net
employment
gain
is
of the New York economy from
transformation
manufacturing
consequence
than the simple
employment.
long-term
of
One
structural
employment
important
change
opportunity
is
a
between
Manhattan and the four outer boroughs of Staten Island, the
Bronx,
Brooklyn,
the service,
in
was
and
Queens.
Because
dominates
finance, insurance, and real estate industries
New York City,
limited
the partial
job recovery from 1977-1980
to Manhattan.
1.0 percent
in the rest of the city.
Brooklyn
period
and
6
in
sector
during
of
this
Private
6.5 percent
boroughs
Manhattan
the
employment rose
Manhattan,
Worse,
Bronx,
but
less
than
in the poorest
private
sector
employment
are
Since manufacturing jobs
jobs, the long-term substitution
are office
than
of office
for
economic
the
worsen
to
tend
will
employment
manufacturing
city
the
throughout
distributed
evenly
much more
3
declined.
actually
disparity between Manhattan and the outer boroughs.
are by no means unique
These trends
the
rather,
to an increase
in
in
II,
is
due
grew from
economy
workers,
to
Employment in
to 57.1
30.4 million
and
finance,
trade,
of
and government.
sector
tertiary
a
Since World War
service
industries
of
manifestation
the American
in
and
tertiary
the
dramatic
white-collar
transportation,
services,
the
a
of the growth
all
virtually
but
transformation.
economic
national
growth
is
city
to New York City;
million
jobs over the period 1950-1975, or from 54 percent to 69
percent
The
of
the nation's
national
employment has
transition
The centripedal
location
contrast
from
--
favorably
With
cities to suburbs,
manufacturing
to
service
the
from the point
of
of view of
that characterize
forces
flight
office
characterize
that
forces
with the centrifugal
manufacturing.
4
consequences for the economy of
significant
cities.
cities --
workforce.
manufacturing
and from the Northeast to the
from
Southwest,
many geographers and city officials believe that office
development
promises
center cities.
offices
is
patterns.
base
for
declining
The concentration and employment density of
thought
This
a new economic
to
be
ideally
suited
to urban
land-use
is not to say that there has been little
7
in
pronounced
5
cities.
Australian
Office migration to
markets, downtowns
between
own:
percent of
in major
and
by 1975.6
major downtowns
net addition
acquired
a constant share of
they have retained overall
to
reason
some
thus
tertiary sector will
that
expect
22
space,
of office
There
23 percent of total national detached office space.7
is
the
percent of
cities seem to have held their
1975,
the nationwide
that
meaning
1960
in
dramatic growth of suburban office
even with the
Still,
is
313 firms,
or
to 63 percent,
and declined
suburbs
500 Corporation
at 71
1963
in
peaked
areas
metropolitan
or
firms headquartered
The number of these
headquarters.
is more
in British
the
of Fortune
the case
in
dramatic
especially
than
States,
United
the
like
offices,
has been extensive and
in general,
suburbanization
total
suburbanization of
of offices;
dispersal
the
of
growth
the
strengthen the economic base of major
cities.
It
be
would
misleading,
however,
simply
if
aggregate employment measures and conclude that,
employment
well.
As
growing due
is
we
saw
in
during 1977-1980, the net
important
in
disparities:
Brooklyn
work:
equivalent
the
New
of
York's
declined,
manufacturing
a
gain
city,
of
one
New York
8
is
all
"recovery"
was
able
example,
to
at
is by no means
job.
office
for
asymmetry is
A fundamental
loss of one manufacturing job
to
overall
increase in employment masked
employment
and the Bronx.
survey
development,
to office
case
the
to
As
a
provide
major
many
to
jobs
middle-income
either highly-paid
(and are typically
workers.
male
8
this structural
the
enter
labor
window
on
New York's
1970,
the
The consequences of
employment.
service
of
the
exceeded
the unemployment
1970,
while after
below
consistently
was
rate
unemployment
before
that
economy may be the fact
this
of
consequences
employment
consistently
has
to the
are not suited
hope
without
force
average,
the national
is
mismatch can only worsen as low-income men
to a service
transition
proportions
immense
of the low-income workforce.
skills
rate
of
mismatch
A
because the jobs created
developing
One
for the enormous number of blue-collar
employment
potential
does not offer
sector
the service
of income,
distribution
to produce a more unequal
Besides tending
by women).
or
jobs for experienced professionals,
poorly-paid jobs for clerical personnel
held
Now,
New York are
in
the jobs available
economy,
as a service
people.
working-class
unskilled
average.
national
The
8.6 percent 1980 jobless rate for New York was one-fifth
higher
in
rate
1980 in
was
percent.
17.7
9
statisticians have dubbed New York "the
capital
study
conducted
Development
estimated
on
that
employment
Some
youth
unemployment
Another window on the employment
of the nation."
to
consequences of the transition
a
while the
New York City was 28.3 percent,
average
national
teenage unemployment
the
than the national average;
by
the
City
patterns
commuting
perhaps 75
9
a service economy
Office
to
percent of
New
the
of
York.
is
from
Economic
It
was
135,000 office
women.
middle-aged
suited to
not be
1 0
Although
the
employment
for
reducing
new
housewives.'
suburban
may
jobs
service
1
Such
to be) do not bode well
is what they prove
that
these
chiefly
blue-collar New York City residents, they
to
are well-suited
by commuters,
held
1977 are
since
created
jobs
either for
New Yorkers,
working-class
prospects of
(if
trends
or
disparities in income.
regional
Reality or Mirage?
II. Back-Office Development:
New York City officials view the transformation of the
national economy and
given.
These officials, along with many economists and
most
from the growth of
recent development
1 2
sector?
the service
A
in the Manhattan office market poses
The
issues for the economy of New York City.
vexing policy
1980-1982 were the boom phase of the characteristic
years
boom-bust
square
from
1980-1985.
Five million
proportion
of
uneconomic
for
These
office
support
costs,
support
it
services
services,
ft
becomes
to
as a
increasingly
pay
headquarter
or back-office
include computer services and data processing,
10
through
and higher
to increase
continue
in
Consequently,
per sq.
to $40
As rents
operating
strong
remained
were very low.
rents rose dramatically
in Midtown Manhattan.
prices.
Demand
vacancy rates
so that
office
1 3
construction.
of office
cycle
feet per year were scheduled for construction
Manhattan
1982,
How can New York City
as:
the issue
define
geographers,
benefit
its dramatic New York manifestation as
functions,
training
programs, accounting and billing, and
insurance companies have found that
banks and
Several
can
split headquarter
and
then
areas.
relocate
Should
city
of
New
in
York
officials
a trend,
the suburbs,
City.
New
to
lower-rent
it is of concern to
office
space in
beyond the tax jurisdiction
York
City
in the outer boroughs.
base
is
the
development
one
functions
economic
development
hope to capture most of the relocated back-office
space
tax
back-office
since most of the low-rent
the region is
they
functions from back-office functions
this become
officials
check processing.
hope
in
city's
first
the outer
for
Preventing the erosion of the
concern,
boroughs
job growth
in
the
is
but
also
back-office
desired
stagnant
as the
outer
borough
economies.
There
are
some
functions might
argued
in
business
of
at
Europe
importance
actual
back-office
Robert M.
of
offices
clients,
has
and
to the
led
some
face-to-face
pattern
of
the greatest
office
11
presence
Since
contact
of offices
give
men whose
1 4
face-to-face
dispersal
the
among
as to
to hold that
accountants,
and
"so
decisions."
commonplace
allow
why
1926 that office activities concentrate
contact
arriving
reasons
relocate out of Manhattan.
districts
ease
plausible
then,
it
in urban
possible
is desired
has
concentrate
in
other
professionals.
the
researchers
contact.
1 5
to
lawyers,
The
United States
qualify
Research
communcations
a
order to
executives,
in
in
become
among
suburbs
Haig
to
the
uncover
confirms the
its
London
to
higher
content
firms that
in general,
is,
in
the center
more
center-city
firms have
city.16
The type
of job
than the type of firm
important
a
than do
functions
and routine
of clerical
remain
such
that
indicated
suburbs
a
telecommuni-
that relocated from Central
A study of firms
location.
require
not
do
therefore
and
cations,
entirely on
rely almost
office, functions
or back-
Routine,
in a firm.
decision-making positions
the top
but only for
contact,
face-to-face
of
importance
in
predicting dispersal.
space
plausible
these
Despite
relocate out of
to
Manhattan,
often remove
incentives to
may.require
that
require
a
and do
conditions
reflect
rents
the
firms will consider
of the office market,
a
not
lower-
short-run
for
incentives
Given
efficiency.
do
that
not provide consistent
long-run
achieving
efficiency
relocate to
location
But market
rent peripheral one.
Long-term
rents
in
fluctuations
functions
office
central
expect back-office
to
relocate.
routine
high-rent
reasons
boom-bust
cycle
relocating back-
office functions when vacancies are low and rents high, but
when rents
fall,
the
functions disappears.
small
fraction
associated
support
of total
with
functions
incentive
Since real
expenses,
unless there
is
relocate back-office
estate
not
are only a
likely
to
a very substantial
fluctuations
rent
costs
and since there are costs
are
firms
moving,
to
send
rent
conflicting
saving.
Short-term
signals
to firms and may hinder the achievement-of
12
move
long-
in conservation and alternative
investment
substantial
prices
to
signals
can be extended
when one considers
the office market
government is
for
role
the case of energy, a sensible
government.
of
role
the
alternative
and
conservation
The analogy to
sources to a standstill.
In
in
in oil
1982 decline
The
firms.
investmen t
brought
fluctuate and send
energy prices
sources of energy, but
conflicting
requires
efficiency
Long-term
energy.
of
case
the
in
is especially evident
This phenomenon
term efficiency.
to
tax energy, to maintain a high price and send consistent
reduce
to
districts
relocation of
location. 1
central
encouraging
by
would
This
routine office functions.
the
ration
most need a
that
to those functions
downtown sites
scarce
congestion
business
in central
space
tax office
government should
that
argue
similarly
could
One
firms.
to
signals
7
III.The Outer Boroughs Versus the Suburbs
New York City is
need
an unenviable
reduce
within
boroughs
competition
space.
There
New
to
question
can
space
office
of
disparity of
The
city.
the
dispersed
the
York
the
City.
outer
is
Some degree
both
inevitable
and desirable due to
to the costs of congestion
to
postion.
out of Manhattan
of offices
of dispersal
due
in
be
employment
is
to
what
captured
The
boroughs
suburbs
for
opportunity
extent
this
the
outer
offer
stiff
in
low-rent
is a huge prime office space market
13
the
office
in place
in many suburban
been
virtually
outer
locations,
for
example, while
no major office
developments
misleading
boroughs as if
no
typical
contrast
site
site.
outer
industrial
locational advantages, it
the
suburbs
with
the
The
boroughs,
business
offer
is
a
a typical
bewildering
from downtown Stamford,
from Newark
parks,
suburbs
to
Scarsdale.
which
such as
districts,
vast
Spring Creek
such
or downtown Brooklyn.
whether a firm prefers
The same
include
as
to rural
is true of
expanses
in
in Brooklyn,
or
St.
George,
The issue
outer
There is
anymore than there
of locations,
New Jersey,
Island,
to
suburban
diversity
dense
the four
these were homogeneous entities.
outer-borough
the
in
have
boroughs since World War II.
When considering comparative
is
there
Staten
then becomes not
the suburbs or the outer
boroughs,
but instead the specific locational characteristics desired
that may be
found in the suburbs,
in the outer boroughs, or
both.
Several
Development
city
officials,
Corporation,
compete with
especially
have
argued
sites.
To begin with,
the
notion
that
misleading
site.
proposition
campus-style,
two
that
the
in
Public
order
to
the suburbs, the outer boroughs must offer
suburban-style
office
at
But
that
even
the
we
typical
low-rise
major highways,
if
there
is
some
typical
suburban
at
site
the
implications of
14
a view embodies
provisionally
office park
the
such
suburban
accept
is
a
the
large,
intersection of
such
a popular
suburban site are by no means cl ear.
site that makes it attractive?
What
is
it about
Do firms want the view, or
the highway?
Are the buildings low-rise because the
is
because
cheap, or
firms
move
security?
office
to
the
The
low-rise
are more
countrysidE
simple
for
f act
this
of
the
land
convenient?
the
beauty,
popularity
Do
or
for
these
of
1 us why they are popular.
parks does not tel
The debate about the r elative comparative advantages of
the
suburbs
and
exclusively
on
hypothesize
that
feature
offer
the
couter
speculati on
and
firms f avor
a higher income
anecdotes
about
boroughs
anecdotal
r esidential
these
plausible.
theories
The
empirically,
is
whether
and what such tests
to
of
the outer
suburbs for
locations
offices;
(2)
and
subsidies and
other
office
are,
doubt,
they can be
tested
us about the
development
location.
(3)
in general,
to
compete with
to judge which specific
to
judge
incentives
No argument
15
in
(1) to judge the ability
what
are
tax
the
types of
within a given borough are most likely
development;
that firm
An empirical analysis may
in three ways:
boroughs,
to
no
inform the debate about office
the outer boroughs
Others
was robbed.
might tell
determinants of office location.
be able
or
the president
anecdotes
they
firm moved
lives there;
and
question
this
Some
because
environment.
r elocation:
moved out of Manhattan b ecause
almost
evidence.
suburban sites
Stamford because the cha irman
Many of
relies
to attract
abatements,
likely to
influence
is made that an empirical
analysis
issues
can
offer
facing
the
solutions
New York.
distribution
consequences
development
of
may
be
to
and
vexing
income,
important
of a site.
but it
the
policy
location of offices affects
more
may tell
developers,
The
employment
potential
determinants
site
any
the
A study of
us whether
can tell
than
and
a site
is
these
simple
locational
attractive
to
us nothing about whether the
should be developed.
IV. An Analysis of the Determinants of Office Location
A.
Introduction
Most office buildings are built on speculation by
real
estate
developers
employment
is
often
and demand
and
in
As one observer
lead time
verge
8
Profits
tax
partnership
development
supply
space.
on
laws
in
in
in
real
the
This
speculation
of future
demand,
the
estate
United
estate
New York is
wrote:
real
demand,
space
can
States
extremely cyclical
be
in
very
encourage
development.
in
1 9
Office
character.
"Inadequate information and long
for construction distort
and
the growth in
by the chronic oversupplies of office
cities. 1
handsome,.
equity
for office
based on a very sketchy analysis
as evidenced
many
who must anticipate
which
is
uneven
2 0
irrational."
the relationship
The
and often
office
between
appears
market,
to
thus,
appears to approximate the famous hog-market disequilibrium
of
economic theory.
performance,
If the office market
then we would expect
16
is a boom-bust
vacancy rates
to
fall
very low during the boom and rise
--
which
is,
vacancy
14.6
rate
in
fact,
fell
to
happens.
0.5 percent
In
in
Manhattan,
1967-68,
but
the
rose to
1972.21
in
percent
what
very high during the bust
One reason for this
cyclical
pattern
is
the long
lag between the conception of a project and its completion.
The two
to three-year lead time for a project means that
the supply
of office
changes in demand.
completed,
use
if
it
space cannot
Moreover,
immediately respond
once an office
is
cannot be quickly converted to an alternative
demand
falls.
What
do
immediately
changes
in demand are the vacancy rate and
demand,
assuming a fixed supply in
vacancy rates
rents,
building
to
to fall
then,
and rents
will
tend
to
respond
the
the short
term,
to be bid up.
be
rent.
determined
to
High
causes
Short-term
by
demand
characteristics, since supply is fixed.
We began our analysis by selecting the 47
towns
that account for most of the suburban New York office space
market
and
available.
for
which
Since
office
with the suburbs, and
market
not comparable,
suburban
office market.
and
total
the
buildings.
suburban New York.
comprehensive
is
since
We
no
census
Our sample,
inventory
17
thought
were
to be
the Manhattan office
our study to the
obtained
square
building
are
we restricted
number of
There
by
the outer boroughs
competing
is
rents
rents per
feet
of
for
office
though,
available,
square
each
foot
of
278
buildings
in
was from the most
an
inventory
that
included
approximately
calculated
the
total
Since
a weighted mean
rents
our
included
by
with
assumption
rents
that
districts
stock.
footage
prime
One
we
of
(see Table
office
40,000
the buildings,
below 10
these
each town by dividing
excess
per
this
5).
space,
sq.
we
ft.
We
so we excluded
dollars
rents below
office
assumption,
for
new,
in
on the age of
From
square
in
buildings
lacked data
buildings
is
buildings.
rent
the total
interest
only
inferior
1800
sq.
ft
on the
correspond
to
expect,
such
would
on
old,
an
to find such low rents only in very old office
such as
in
Bridgeport,
Connecticut,
or Newark,
the case. 2 2
New Jersey - which was in fact
We sought to explain the variations in rent across
towns
by
a
variety
differentials
assuming
that
short term,
demand
factors
and
to
the
supply of office
amenity
we expect that
relating
differentials.
space
rents will
bid up
amenities.
places to work and
by
the
If supply
willingness
is
indeed
town.
variations
B.
The
in
Since
we
are
fixed
in
the
Towns
to the
that
are
to
fixed
pay
for
in the
locational
short term,
little effect on
rents.
Variables
and Some
The cost variables
(1)
cost
live should have office
then we would expect cost factors to have
the
is
to
vary according
for amenities in a particular
more desirable
rents
of
Diagnostics
included the following:
Two measures of the height
18
of buildings
in
a
given town:
The mean number of stories, and the proportion
of buildings
in a given town with more than eight stories.
The taller
a building,
the more costly
significantly
more
is
to construct
above 8 stories
per square foot, and building
be
it
costly
than
is
thought to
building
under
8
stories.23
(2)
Electricity
monthly electric
bill
costs,
hours (see Table 2).
included
in
the sample were
(3)
away
costs
decrease
dol lars
In
(4)
Effective
per
hundred
location
central
business
district
increase,
commercial
assessed
i ndicate
in
locational
as
district,
rents
property
tax rates,
val uation.
There
in
is
no
that
the
in
with
correlation
inter-jurisdictional
were passed on to the tenants,
taxes
difference s
and
theory,
so that
positive
A significantly
Alternatively,
tax
the
the rents.
classical
the absence of any correlation
the
utilities),
agr eement about the incidence of the commercial
could
differences
the
from
to that
tax.
rents
in
rents
accordingly.
theoretical
property
all
(include
reflected
150,000
The distance to Manhattan in miles as a proxy
moves
transport
the average
Since virtually
gross
should be
for transportation costs.
one
by
for firms using approximately
kilowatt
cost of electricity
given
with rents
were
taxes
borne
while
might mean that
by
the
landlord.
2 4
a positive correlation between the property
rents
may
advantages
mean
that
could raise
19
towns
their
with
significant
commercial
property
taxes
to
capture
some
of
the
tax
the debate on property
of
those
locational
to
not adequate to contribute
Our study is
advantages.25
value
notes
and only
incidence,
the
issues.
no measure.
Labor costs,
(5)
but
substantial,
labor
in
differences
are
there
The cost
region.
between
New York City and
its
differs
Table
(see
but
3),
included the following:
tax rates, in
property
Effective residential
We hypothesize
valuation.
per hundred assessed
dollars
New York
the
among suburbs.
The amenity variables
(1)
suburbs
in
probably
labor
of
significant
not
probably
among suburbs
costs
metropolitan
probably not
are no doubt
buildings
office
and operating
constructing
of
costs
The labor
that executives choose office locations in places where
they
or
live
either
would
to.
like
We
thus
a
expect
negative correlation with rents, since high residential
property taxes are a disamenity.
Commuter
(2)
variable
categorical
Manhattan
is
assumed
(3)
New
York,
to
access
rail
of either
yes or no.
Manhattan,
Rail access to
to be an amenity.
Location by state,
Connecticut,
variable
Jersey.
Although
New
and
unlike corporate
states.
Since
income taxes.
income taxes,
state
income
20
for
a categorical
factors may vary by state, we hypothesize that
important is personal
a
Personal
the most
income taxes,
vary widely across our
taxes differ
many
by kind of
three
income
taxed,
and not simply in degree,
a categorical
variable
the best way to attempt to capture this effect.
who
make
locational
decisions
concerned with the state
rate
would
be a
with
and
the
right
of
residential
class,
amenity
is
including
the proportion
percentage
change
"white flight");
who
have
income;
in
to
and their
from
school;
A highly desirable
residents
income,
are
and
(5)
educational
several
proxies
the
25 years old
per
capita
the proportion of the
the
number
of clerical
workforce;
and
the
of the workforce.
hypothesized
predominately
So
(to measure
median
proportion
is
work near
occupation.
over
proportion of the
location
and
1970-1980
the
income;
number of managers and their
"living
who are black;
residents under the poverty level;
the
by
residents
population
the median family
workers,
live
and
measured
high
very
2).
or
the proportion of adults
completed
be
We expect that managers
race,
of
to
stratification,
officials prefer
similar
assumed
(see Table
kind of people."
a
Executives
income tax, and a low tax
major amenity
top coroporate
people
personal
Socio-economic
(4)
are
is
white,
to be one where
well-educated,
high
in managerial occupations.
School quality, as measured by county average
expenditures
per
assumed to regard high quality
capita.
schools
Executives
are
as an amenity.
Our
measure of school quality, though, is very poor.
The
information
correlation
about
both
the
21
matrix
provided
bivariate
important
relation
between
independent
relationships
4).
dependent
among
The
the
correlations
independent
the
and
variables
amenity
independent
between
variables
with
variables.
Although this
the
multiple regressions,
predictors for
rent
pattern
than
rents
from poor data
the correlations
Since our
variables
measures of the same factor,
a high
of .941;
.715
capita
level.
income,
with
the
include
we would
phenomenon.
we
must
cost
in
the
not
The
this result
Perhaps
the
independent
several
different
expect these to have
family income
have
and
a correlation
residents who are black has a
proportion
To avoid redundancy,
colinearity,
that
among
for example,
the proportion of
correlation
the
factors.
degree of correlation. Median
median per
were
highly
than are cost factors.
on cost
variables.
more
it suggests that amenity factors are
derives
important are
our
pattern:
could disappear
however,
more
Table
and
interesting
possibility cannot be excluded,
solely
rent
consistently
average
about
(see
average
one
were
and
variables
the
displayed
correlated
better
variables,
or in
use
two
below
the
statistical
poverty
parlance,
measures
of
the
same
On the basis of these preliminary diagnostics,
we chose the most promising
The
mean rent
sample of buildings
for
variables
(see Table
1).
each town was derived
located
in
that
town,
from a
and weighted by
the number of square feet.
Since the number of square feet
differed
we
in
each
town,
have
varying
confidence in the estimated average rents.
22
degrees
of
Larger samples,
ceteris paribus, mean better
predictions, so we need to
give
more weight to towns with a larger
feet
of office
number of square
space in our sample of buildings.
definition of mean rent,
Given our
and assuming that rents per sq. ft
by building have constant variance, then weighted
squares
is
the appropriate
model-building
least
technique
(see
Table 5).
C.
The Cost Model
Our first
of cost
taller
factors.
run,
and
the costs of
rents) would certainly
incidence
complex
was to predict
of
on the basis
we
supply is,
would
expect
electricity
be
commercial
If
issue.
then
rents
We assumed that the costs of constructing
buildings
are gross
The
task
reflected
in
the
fact,
tax
to
correlation
between rents and commercial
assumption,
positive
correlation
we
be
would
part,
shifted
forward
gradient of classical
negative
correlation
to the
and
tenants.
by
the
predict
between
taxes are,
run,
more
property taxes.
inelastic
short
a
the short
borne
supply is
the
is
in
property taxes could indicate that
in
the rents.
taxes
fixed
From
significantly
in
property
landlord.
this
(since these
rents
no
A
'and
not completely
at
Finally,
least
the
in
rent
location theory leads us to expect a
between
rents and the
distance to
Manhattan.
Our
first
model
predicts
rents
as an
additive
function of the average stories of buildings, the costs of
electricity and the commercial
23
property tax rate.
The estimated coefficients are:
(1)
= 16.384 + .459 (average stories)
(4.580)
(2.360)
rent
+ .249(electricity costs) - 1.641(commercial tax)
(.782)
(-3.395)
(The figures in parentheses
coefficients are T-ratios)
significantly
coefficient
different
principal
with
this
are made about
correlation
explain.
electricity
for the commercial
what assumptions
negative
for
from zero at
difficulty
coefficient
We will
is
difficult,
argue
later
measured
is
the
costs
the .05
model
is
incidence,
if
is
level.
the
property tax.
not
The
negative
No
matter
a significantly
not
impossible,
to
that this negative relation
can be understood only when we assume that
being
the
r 2 = .259
dgf = 43
The
under
residential
Another shortcoming of this model
what
property
is
is
tax
really
rate.
that it only explains
about 26 percent of the variations in rents.
Our
predictive
second
model
attempts
to
relations remain constant
distance by adding it to our
see
if we
if
these
control
for
first model.
The estimated coefficients are:
(2)
rent
=
16.739 +
(4.517)
+
.461(average
(2.346)
.269(electricity costs) -
(.828)
1.697(commercial tax)
(-3.359)
- .017 (distance)
(-.429)
dgf = 42
stories)
r2 =
24
.263
Neither distance nor electricity cost coefficients
are
significant
at
commercial
the .05
property tax
commercial
tax.
Since
costs and distance
them
level.
The coefficient
remains difficult
for the
to interpret
as a
the coefficients for electricity
are essentially
zero,
we decided to drop
from the model.
Our
third
model,
then,
additive
function of the average
property
tax.
predicts
stories
rents
as
an
and the commercial
The estimated coefficients are:
(3) rent
19.007 +
(15.410)
=
-
.429(average stories)
(2.261)
1.405(commercial tax)
(-3.738)
dgf
r 2 = .249
.
44
=
Comparing
models
shows
essentially
Still,
statistically
are
that
all
models.
statistic with those of
these
two
in
significant.
measuring something else.
problems,
commercial
no way
In
Our
for
implies
are
that
particular,
they
we
are
tax coefficient
is
Because of these substantial
we thought it
tax variable,
that we could
account
power of the previous
assume that the commercial
interpretive
previous
even though both of our coefficients
significant,this
to
variables
of the explanatory
substantively
forced
the r 2
and fit
useful
a model
to omit this
with variables
interpret.
fourth model
predicts
function of electricity costs,
25
rents
as an additive
the average stories and the
distance
to Manhattan.
The estimated coefficients are:
(4) rent = 20.889 -
.423(electricity costs)
(5.358)
+
(-1.510)
.141(average stories) + .018(distance)
(.738)
(.403)
r2 =
dgf = 43
.060
Here none of the coefficients
the
.05
less
level,
and the
than 1 percent.
explained
variations
in
rents
is
It appears that the explanatory power
of the previous models and the
significance of
stories coefficient depended on
tax.
is significant at
Yet the commercial
the average
the commercial
property
property tax coefficient is not
interpretable and may be measuring the residential property
Our cost factors
tax.
power.
our
appear to have
This result does not prove, but
assumption
possibility
that
short-term
remains
that
or that we are measuring
D.
these
is
supply
results
consistent with
is
fixed.
The
are due to poor data
the wrong cost factors.
The Amenity Model
Our second task
of amenity factors.
the
almost no explanatory
variations
was to predict
rents
With supply fixed
in
rents should
on the basis
in the short
stem from
shifts
run,
in
the
demand curve due to a willingness to pay for a desirable
location.
could
What
So we would expect that
command
higher
rents
than
constitutes a desirable
26
more desirable
less
desirable
location?
locations
locations.
We
assume
that
executives,
like
everyone,
rather than long ones.
in
offices
And
prestigious
and
also
they live
want
profile,
a
desirable
but
their
like
to
work
locate their
like
offices
to
in
to
to live.
locate
short,
in
other
From these assumptions we would
town
also have
trips
or would
fashionable places where,
large firms have located.
expect
short
So they would
a town where
executives
prefer
to
have
high
fashionable
office
a
a
socio-economic
district.
We
assume that it requires a certain critical mass of managers
to make a town fashionable,
number of managers.
be
thought
would
reduce
the
though
the high-income
such
profile
a clerical
workforce
of the town.
Finally,
lower residential
property
to higher.
first
model
of the residential
of managers,
income per
predicts
property
the number of clerical
rents
as
tax rate,
workers,
capita.
The estimated coefficients are:
(1)
for
large clerical workforce might also
are assumed to prefer
Our
function
A
desirable,
executives
taxes
so we used the variable
rent = 13.802 - 1.333(residential tax)
(12.484)
(-4.219)
+ 2.440(managers) (8.073)
+
dgf = 42
.263(clerical)
(-2.673)
.258(median income)
(2.798)
r 2 = .844
27
an
additive
the number
and the median
All
different
of
our
coefficients
from zero at
the .05
level,
are
significantly
and the model expains
84 percent of the variations in rents.
Since this
clerical
workers
workforce,
measuring
Our
model
instead
there
the
is
a
of
their
chance
effects of the
(.971)
size
workers
and
both
(see Table
colinearity, we decided
if
our
that
we
are
the
in
managers
4).
groups
and
the
just
town on rents.
(.755)
Because
of
fact
high correlations
to control
occupational
proportions
size of
correlation matrix shows
population
see
uses the number of managerial
and
of this
between
clerical
danger of
for population size and
retain
any
independent
explanatory power.
Our second model, then, simply adds the population
size to the
first model.
The estimated coefficients are:
(2) rent =
13.802 (12.331)
1.333(residential tax)
(-4.164)
.258(median income) + .000(population)
(2.757
(-.008)
+
+ 2.439(managers) - .261(clerical)
(7.772)
2
(-1.027)
dgf = 41
r
= .844
It
the
is
previous
population
simultaneously
at
the .05
to exert
level.
remarkable just how similar this model
one
and
--
except
the
become
that
number
the
of
insignificantly
coefficients
clerical
explanatory
28
for
workers
different
The number of clerical
no independent
is to
from
zero
workers appears
power
apart
from
the
size
of the population.
appears
to retain
controlling
The number of managers,
a significant
for
predictive
population
size.
however,
power even after
It
is
not,
then,
simply
the size of a town that makes it desirable for offices, but
the size of
the managerial population.
not prove,
desire
but
is
consistent
with,
Such a result does
the theory that
firms
fashionable locations.
Our
third model
predicts rents
property
as
tax
population,
(3) rent =
summarizes
an additive
rate,
the
these
function
median
of
income
findings,
the
per
and
residential
capita,
the
and the number of managers.
13.695 - 1.406(residential
(12.280)
(-4.503)
+
.289(median income)
(3.272)
+
-
tax)
.018(population)
(-2.431)
2.267(managers)
(8.537)
r 2 = .840
dgf = 42
These
willingness
equal,
1.41
to
firms
dollars
residential
dollar
pay for
are willing
for
one
reduction
1000
increase
The
in
interpreted
29
as
a
Other things
rent
dollar
tax rate,
population,
be
amenities.
to pay in
every
property
can
certain
increase in the median
1000
poses an
coefficients
per square foot:
reduction
cents
income,
in
the
for every
1000
2 cents
for every
and 2.27 dollars
for
every
in managers.
negative
relationship
interpretive question.
29
of
population
Why should
an
to
rents
increase
in
population
reduce
correlation
rents?
of rent
(.120).
But
this
positive
the
number
managers.
higher
rents
managers.
is
positive
But
between
larger
control
significant
large
Brunswick,
matrix
and rents
at the .05
the larger
level.
black
Elizabeth,
in
our
sample,
perspective
of
income,
that
population
Although
significantly
(see Table
by
2).
for
decided to
these
is
corporate
state,
include
We
30
negative
New York
immediately think
such
as Newark,
The
New
correlation
has
Given that
all
a
-. 409
of
population
these
--
negatively
income
taxes
tax
the
is
not
to rents.
taxes do
that while
income
it
related
income
is
from
disamenities,
a categorical
state.
mean
cities with a large
not
vary
vary widely
costs do
for executives do.
personal
the
and at .440 correlation
personal
This suggests
by state, amenities
test
--
managers
be
indicates more
population
intuition:
with
does
turns
Bridgeport.
with the proportion of blacks.
correlated
and
metropolitan
residents.
and
correlation with median
surprising
rents
to
This makes sense when
cities
cities in our
confirms
positively
seems
population
to be older, declining industrial
the
positive
for the number of managers,
between population
proportion of poor,
of
a
bivariate
slightly
correlation
relation
So
once we
we consider that
tend
is
the
insofar as a larger population
the relation
and
begin with,
and population
measuring
of
To
not vary
In an attempt to
differentials,
variable
for
we
location by
Our
categorical
fourth
variables
model
simply
to the third
added
the
state
model.
The estimated coefficients are:
(4) rent = 13.740 - 1.024(residential tax)
(9.141) (-2.339)
+
+
.296(median income) - .016(population)
(3.572)
(-2.088)
1.822(managers) + 1.830(Connecticut)
(6.006)
-
(3.055)
.722(New Jersey) -
(-1.616
r 2 = .873
dgf = 40
Although categorical
a category has
state
variables do not tell us why
predictive power,
categories
the
1.108(New York)
(-5.472)
are quite
importance
of
the coefficients of
consistent
personal
these
with our theory
income
taxes
on
of
location
amenity.
Connecticut
rents, and
is the only state of the three that does not tax
earned
tax
income;
and has
Jersey's
New York
effects,
levies
is
related
thus,
strong
effect
between
is
models
significant
are
positive
effect
the most progressive
on
rents;
the other
Moreover, a general
hierarchically
5.0925 which
a
the most negative
coefficient
income tax.
has
two,
3 and 4, yields
at
statistically
the .05
income
and
as is
F-test between
significant
New
its
the two
an F-ratio
level.
on
of
The state
as well
as
substantively significant.
V.
The Amenity Orientation of Office Location
Amenity
factors
appear
31
to
predict
rents
much
more
are a number of good reasons for
move to more
we will
considerations,
with the most specific
the
should be
explanations of why amenity factors
general
Beginning
to be so.
this
there
that
argue
We will
factors.
than do cost
powerfully
predictors.
best
A.
Specifics of the Cost Model
property
problems.
No matter how we view the question of
and
commercial
tax
between
This
rates.
negative
residential property tax coefficient,
is
anything,
if
measuring,
the
property tax
tax
rate
for
coefficients
both
the .05
at
insignificant
our
to
fourth
is
variable
tax.
the commercial
amenity model.
tax
property
level.
leads us to
property
residential
As a final test of colinearity, we added
property
fact,
interpretation of the
straightforward
with the
the commercial
The
explain.
combined
believe that what
incidence,
correlation
.865
property
residential
to
difficult
a
shows
matrix
correlation
is
relation
negative
the
interpretive
tax rate posed significant
commercial
this
to
attached
coefficient
negative
The
rates
The
became
This convinced us that
colinearity was the problem.
The
insignificance
of
consistent with other
recent
research
gradient.
on
the
theory,
rents
business
district
to compensate
rent
diminish
as
our distance coefficient
theoretical
In
for the increased travel
32
empirical
classical
distance
The decline
grows.
and
from
in
rents
is
location
the
central
is
thought
costs to the center
city.
A weakness
of this
(1)
heroic assumptions:
transport
surface
direction;
(2)
area
district;
(3)
must
and
be
a flat
travel
production
take
uniform
throughout
ever
developments in
in
the
areas
model.
to become
the
any
in
central
a
business
and maintenance
region.
Although
no
assumptions,
intra-metropolitan distribution
plausibility of
Suburbanization has caused metropolitan
increasingly
attraction exerted
in
distribution
of economic activity especially weaken the
the gravity
rather
undifferentiated
approximated these
the
its
equally costly
and
place
been
the costs of construction
metropolitan area has
recent
has always
There is
making
all
metropolitan
model
multinuclear,
by the core city.
weakening the
Empirical
studies of
urban land-value gradients over time show that the gravity
model
is
losing predictive power.
As a result
of the dispersion of business activity
and the growth of other centers, distance from the
central
business district
once commanding
metropolitan variation
The
is
gradually
losing its
power
to explain
in site
value. 2 6
dispersal
of
economic
intra-
activity
throughout
metropolitan New York lessens the need and thus the cost of
travel
to New York City.
rent gradient,
our
distance
B.
All of which tends to flatten
which may help explain the
insignificance
of
coefficient.
Amenities and Monopolistic Competition
We have assumed that
fixed,
the
while demand shifts
a location.
Implicit
is
in
the short
according
supply is
to the desirability
the view that
33
run,
the supply,
of
office
is a homogeneous product distinct from the amenities
space,
of its location.
not
space
to
as
Yet it is plausible to think of office
but
homogeneous,
its
of
the amenities
as
according
differentiated
location.
Many commodities are
Just as
differentiated by reputation, quality, or fashion.
so
from Macy's,
suit
the same commodity as a
from Brooks Brothers is not
a suit
an
as
commodity
Supply
City.
Jersey
cannot
not the same
is
Greenwich
measured
be
simply
in
in
since the product supplied has diverse
quantities,
physical
in
office
competition
monopolistic
in
an office
qualities.
the short
In
fixed
under
model.
But
run,
competition,
monopolistic
this
has
rent differentials across
for
office space
fixed
the
in
should
observe
long-run
time
Jersey
competition,
there
is
seller
in
our
consequences
If we
assume that
towns.
should
supply
rent
in
to
control
fixity.
over
between,
rents
lower
is
that
to short-term
addition
a long-term
level.
demand,
Yet, we
for
example,
Why does supply not increase
reason
The
In the
to meet
increase
differentials
Greenwich
City?
up rents.
to an equilibrium
fall
Greenwich and Jersey City.
over
in
long-term
demand can bid
short-run,
rents
and
is
is a homogeneous product, then with supply
however,
run,
long
it
as
the office-space market is characterized by
if
monopolistic competition,
the
supply of office stock is
the
the
to
level
of
monopolistic
for
fixity
in
supply,
Product differentiation gives
a
34
scarce
resource
--
the
prestige
for
as people
Insofar
of the product.
then
location,
the prestigious
rent.
long time command a higher
are scarce
profits
resources,
that
their
If
suits are unique,
Brothers
Greenwich
are
a
different
change,
for a
and reputation
then
can convince people
increasing the supply of
not necessarily lower the price of a
suit.
scarce
command higher rents
can
seller
Prestige
Brooks Brothers
other-make suits will
Brooks
the
owners can earn long-term
and their
from them.
to pay more
are willing
Prestigious
resources,
office
and
locations
their
owners
in
can
in the long term because they provide
product.
Eventually,
new prestigious
it
is
true,
locations emerge.
fashions
Market power
to
raise prices diminishes.
Our
model
determination and
of
a
examines
only
cannot prove
or
short-term
disprove
monopolistically competitive
since
amenities are
the
basis
our amenity- oriented model
of
rent
the hypothesis
office market.
product
Yet,
differentiation,
is at least consistent with the
theory of monopolistic competition.
C.
Amenities and Office Location Theory
Cost models of firm
geographers
(1956),
such as Weber
primarily
to
Manufacturing
firms
location
respect
factors
with
location were developed by
(1909),
Losch
explain
are
to
thought
to
the plant and
35
and Isard
location.
industrial
to
markets
of production on the other.
materials
(1954),
processed
choose
on
the
an
one
optimal
hand
and
Because shipping raw
commodities
from the
plant
is
expensive,
sensitive
make
as
difficult
sense
to
functions
"office
location
be
fairly
since
costs
of
sensitive
not
it
is
office
argues
Malamud
that
to costs
2 7
of any location
locational
tradition and
offices,
to be less
activities."
economic
to
models do
locational
perceived
is
intangible,
case of
the
Since the costs
and
thought
decision-making.
such as
than are most
in the
measure
is
these cost-oriented
Yet
to costs.
much
location
decisions
are often
are typically
small
made by
fashion.
can weigh
There is no process of accounting that
the enhancement in quality of executive decisionmaking in a given locatio 8 against the costs of
operating at that location.
In addition, the greater mobility of offices in
with manufacturing
comparison
of choosing a poor
are smaller
Surveys
decisions
location.
are
of
another window on
than
location
that
who
make
costs
locational
the determinants of office
of alternative
about
hard
financial
the
costs
to the trendiness
proximity
to
with
"executives
2 9
data".
of
the
crowd.
executive
36
ideas
The
alternative
or "swarming,"
that they are minimizing the
by staying
sites,
on vague and personal
decisions
on
uncertainty
feel
the
Since little quantitative evidence is available
must base location
contribute
that
means
locat-ion.
executives
on the costs and benefits
rather
plants
very
sites
may
as executives
risks of choosing a poor
3 0
Many surveys
residences
is
often
reveal
a
key
influence on location in
International
surveys
also
influence decisions to
di sameni t ies
Sydney,
London,
reveal
and New York.
that
push
move to the suburbs.
include
congestion,
expansion, and high rents.
In
3 1
factors
These urban
lack
of
room
for
a survey of major English-
speaking na tions, only American executives mentioned a poor
overall
u rban
environment
This probably
decisions.
urban life in
American,
as
a
reflects
factor
the
British,
in
relocation
relative
quality
and Australian
Th ere have been no good studies
of
3 2
cities.
of the influence
of prestige on location decisions, even though real estate
pla ce
agents
Surveys
with
of
to
great
executives
respect
swarm
a
to
a
financial
deal
of
find
prestige
3 4
relocation.
fashionable
emphasis
The
institutions.
may
Banks may
be
favor
3 3
prestige.
menti )ned
tendency
location
on
frequently
for offices to
reinforced
conventional,
prestigious sites when considering loans to developers.
D.
preference
industrial
widespread
rather
office-location
than
recognition
cost
decisions,
calculation
the
like
Malamud
equilibrium
models
communication
costs
industrial
evidence
of
the
are
endeavor
for
analogous
personal
characterizes
of
influential.
create
of
Some
neoclassical
location
to
model.
importance
37
to
office
location
that
equilibrium-cost models
location theory remain highly
researchers
the
3 5
Offices and Household Location Theo ry
Despite
in
by
in
which
transportation costs
Yet
the
subjective
pervasive
factors,
in
office-location
the
possibility
of
within
the context
of
Given the centrality of personal
preference
in
and
prejudice,
ignorance of alternatives
throws
decisions
office-location model
developing
an
industrial
location theory. 3 6
office
Traditional
income
industrial
office
location.
theory
assumed
that
moved
the
to
the benefit of extra
commuting.37
extra
than
a
understanding
location
household
households
preferred
context
theoretical
for
theory
location
should offer
location theory
household
location,
satisfactory
more
on
doubt
considerable
they
because
suburbs
the costs of
land more than
by
research
recent
But
upper
Wheaton
indicates that extra land is actually valued less than the
He concluded that the demand
costs of commuting.
does
explain migration to
not
suggested that people are
taxes and amenities,
suburbs;
the
3 8
quality.
when
tested
local
(i.e.,
received)
services
housing
found
location
and
evidence
correlated
with
the
local
is
by assuming
taxes
land and bidding up their
that
tax
property
net
values
the
prices.
are
3 9
quite similar
Oates
model
to our model
38
fiscal
and
demand
Oates
positively
expenditure and negatively
rate.
fiscal
paid
raising
households,
lower
Oates then
that
between
difference
attract
with local
the
location.
residential
hypothesis
Tiebout's
residuals
for
choosing
he
Tiebout was
the first to argue that households examine
advantages
land
instead,
the suburbs by
drawn to
such as school
for
correlated
of
of office
household
location.
Where
he
property
residential
found
the same negative
correlated with property value, we found
correlation
rents.
with
correlated
significant
findings with
our
The
location.
causal
models and our office
executives.
offices
to locate
to
VI.
Not
link
What
of office
amenity model
location model
location
household
between
is
of these
the consistency
is
office
taxes
4 0
location.
household
for our purposes
and
theories
and
property
found residential
Reschovsky also
negatively
taxes
property
residential
between
negatively
taxes
is the preferences of
surprisingly, corporate officials prefer
like
places where they reside or would
in
reside.
Public Policy and Office
A.
Location
A Role for Government?
Before
we
implications of our
turn
to
some
of
the
public
findings, we should examine the
why should government
intervene
can
be
externalities.
There is
office
issue:
why not
location,
We believe that government
let the market function freely?
intervention
in
policy
justified
reason
the
on
basis
that
to believe
of
although
the costs to firms may not differ much across locations,
the costs to society differ considerably.
legitimate
private
costs
locations.
example.
role
in reducing
and
the
Campus-style
Built
the
social
suburban
divergence between the
for
costs
office
along major highways,
39
Government has a
many
sites
these
are
office
office
a good
parks
of sewers,
governments assume the costs
local
these
and highway expansion to accomodate
are major
highway capacity is enormous -By
the
since
costs
firm,
private
The
the
to estimate
costs
transportation
Manhattan,
regional
time to work is
which throws
cost
travel
much
of
of
sites
At
rely
the
for
is
however,
1
use:
disparity
on auto
use,
while
the
40
travel
in
reduction
--
in energy
energy
relies
use
The
the
transportation
double
virtually
is
at
achieved
"The
Manhattan
in
sites.
executives
Differences
the
subcenters,
campus
move to the suburbs.
explain
regional
The
at campus sites
locations." 4
survey
time (including
most pronounced
energy
greater
a
locations
suburban
constant.
time to work,
Manhattan
transport
with
relative magnitude of
travel
on why offices
light
energy use per employee
that
the
to a campus site,
but total
remains
time to work is
reduced
choose
conducted
office
and
subcenters,
reduced,
etc.)
trips,
travel
A
place.
associated
the
among
For firms moving from Manhattan
lunch
to
incentive
Plan Association
Regional
employees
office
as
are not borne by the firm.
campus site
of
in
already
costs
the
since
subcenter
regional
no
such
fewer external
creates
is
has
increased
subcenter,
regional
infrastructure
however,
Offices
sites.
and is borne by the public.
and Bridgeport,
Stamford,
Newark,
in a
location
contrast,
utilities,
cost of
and the
traffic generators,
and
state
Typically,
locations.
very popular
have become
in the mode of
use:
on
campus
transit.
per employee
is
halfway between
the
Manhattan
Such dramatic contrasts
social
costs
incurred
encourage
economic
B.
in
energy
low
the campus
energy use suggest
by different
office
conservation,
justification
and
some of the
locations.
government
for regulating
high.
office
To
has
a
sound
location.
The Dilemmas of Office Development
We
can
findings tell
office
now
turn
us about
development
in
Our model
to
the
do
our
to stimulate
the outer boroughs?
in
the determination of
what
New York City's efforts
indicated
the assumed fixity
question:
that
supply,
rents.
in
costs
the short
run,
had little
About
the
due to
bearing
long-run
on
importance
of costs, our model tells us nothing directly. Nonetheless,
many geographers
office
location
is
be
fashion and
is
monopolistically
casts
and
development
taxes
in
outer
developers
determining
on
other
the
in
incentives
boroughs
of
New
there
are
implications
enormous
for
differences
41
the
long
the office
costs
long-run
of
for
would
rents.
run,
tax
York
have
a
of
abatements,
Commercial
for
market
All
stimulating
Westchester County,
far prefer Westchester.
grave
if
then
efficacy
The amenity orientation
general,
And
even
in
to costs and seems to
in the outer boroughs.
are higher
the
amenity oriented.
in
even
not very sensitive
doubt
subsidies,
that
competitive,
secondary role
this
have concluded
office
property
example,
City,
yet
than
office
4 2
of office
location
the outer
boroughs.
among
within
and
has,
in
While
boroughs,
overall,
the
outer
boroughs have
socioeconomic profile ---
executives
Residential
than
in
County.43
It
Fairfield
done about this.
desirable
say,
of corporate
Fairfield
County.
in the outer boroughs are
York
State,
though
lower
higher
than
is not clear, however, what can be
With the preponderance of apartments
New York City,
benefit
does,
property taxes
New
less
from the perspective
than
suburban
a much
lowering
landlords,
residential
property
but not necessarily
taxes
in
would
tenants.
Quite simply, the poverty, blight and crime of
many parts
and
of the outer
--
Brooklyn
boroughs --
are
a
state
the resources required
New York City;
afford both
promise
if
and
to create
the federal
the
our cities.
formidible
Moreover,
development.
local
to
office
governments
government,
and
the Bronx
obstacle
a decent
military budget
The outer
especially
environment
meanwhile,
the
lack
in
cannot
reconstruction of
boroughs would appear to have more
costs were
the
key
determinant
of
office
location, for New York City is in a much better position to
reduce development
attractive
costs
than to make the outer
places to live
Our
development
findings
in
boroughs
and work.
pose a
number of
dilemmas
for
office
the outer boroughs.
First,
if
executives
will
tend
to
prefer
the
amenities of the suburbs,
then back-office development may
offer
for
routine
the
most
functions
promise
involve
42
few
the
outer
executives.
boroughs,
since
Unfortunately,
back-office functions
technologies,
growth.
and
are the most
thus
offer
rapidly replaced by new
little
potential
employment
So the very office functions the boroughs are most
likely
to obtain,
likely to
local
are the office
functions
that
are
least
enhance employment opportunity and stimulate
borough
explicitly
economies. 4
Swedish
government
back-office
jobs to depressed regions precisely because
it was thought
these
in
The
the 1960s not to relocate
that
decided
4
jobs would be replaced by automation.
Instead,
the Swedes chose to relocate headquarter functions to those
5
regions. 4
Second, if amenities are in fact crucial, then some
boroughs have more promise than other
locations
in
locations.
income
and
Bronx.
a
given
Staten
a lower
borough
Island and
more
promise
Queens
unemployment
Because of
boroughs,
rate
this amenity
have a
and some
than
higher
than Brooklyn
comparative
other
median
and the
advantage,
Queens and Staten Island may hold more potential for office
location
and
likely
variety
the
than Brooklyn or the Bronx.
Bronx
transit
of potential
Similarly,
to
locations
the
rest
for office
of
the
city;
designated as an office park,
in the
very poor
a
itself
transit access.
from
the
least
within boroughs there are
development.
the Fordham Road business district
links
it is Brooklyn
that most need new jobs, and appear
to get them.
the Bronx,
Yet
physical
If
and
43
In
has excellent
Baychester
Commons,
northern Bronx has
firm desires
social
a
disamenities
to
isolate
of
a
borough downtown,
city
is,
in
the firm may prefer
fact,
Of
development.
marketing
course,
an office park.
these
precisely
office
because
The
parks
the office
for
parks
are isolated from the disamenities of borough downtowns and
lack
transit
facilities,
lower-income
borough
they
are
all but
residents.
A key characteristic
lower-income
New Yorkers
jobs created
in office parks would
suburban
inaccessible to
of
is that they do not own cars, and
almost
certainly go
to
commuters.
All
of
determinants,
this
such
suggests
as
that
executive
market
locational
preferences,
not
will
necessarily reduce employment disparities between Manhattan
and
the
outer
Yorkers.
boroughs,
Office
preferable to
first,
the
jobs
in
and
city of
second,
for
borough
location in office parks
infrastructure
The
provide
development
because downtown jobs
income people;
by
or
poor
downtowns
for two
development
must be provided
fact that the city has good
to low-
the external
in
costs
office parks
--
--
borne
where
could be substantial.
reasons to
regulate office
location, however, by no means implies that it will.
so
many alternative
locations
other jurisdictions,
regulate
office
suburbs.
If
it
available
to
With
developers
in
the city fears that any attempt to
location
will
is to
reduce
employment
and income within
be able
exercise
to
is
reasons:
are more accessible
because
New
land-use
44
only
lose
the growing
offices
the
disparities of
New York City,
controls to
to
the city
must
divert office
development
from Manhattan
Yet the exercise
boroughs.
is the dilemma -C.
What Is
in
boroughs.
for
genuine
attracted,
the
of those controls
of public
vexing
attract offices
policy
As
to the outer
any,
development.
in
the outer
for
will
How
be
we
saw,
efforts
boroughs hold
office
simply
little
promise
The
is
office
is
not likely
residents
jobs
jobs; and
least
economic
in need
development
to provide
of those
jobs
boroughs?
of New York City to use land-use
to divert
to
to developers are
satisfactory
New
development
low-growth back-office
boroughs that
the unemployed
ability
and here
the suburbs.
by office
development.
sites most attractive
of
--
must be to extricate
dilemmas posed
economic
if
of the outer
To Be Done?
York from the
outer
parts
might only chase offices to
The task
the
to distressed
controls
Yet the
and taxes
growth from Manhattan to the distressed
downtowns of the outer boroughs is undermined by the myriad
political boundaries.
spans over portions of
The New York metropolitan
three states and
a dozen suburban counties.
income
taxes;
Firms that
every
town
Each state
levies
economy
includes more than
levies different
different
property
need access to Manhattan can locate
outside
taxes.
of
New York City, or even outside of New York State, and incur
lower taxes and cheaper land. 4
and
congested
permanent
office
Manhattan
gridlock),
employment
6
becomes
no matter
becomes
45
(83
So no matter how overbuilt
(east
Midtown
how unevenly
percent
of
total
is
in
near-
distributed
New York
City
office
regulate
space
office
is
in
4 7
Manhattan
location without
),
the
fearing
city
cannot
the erosion
of its
tax base.
What
fewer fiscal
office
reason
is
there to believe, however, that
jurisdictions would enable the
growth to
the outer
boroughs?
experiments
are not possible
meteorology
or
of
astronomy,
London approximates
in
Although controlled
the social
for that
City to divert
sciences
matter),
crowding
such a control.
Council,
however,
London:
the
has
As
new
congestion.
jurisdiction
office
Controls were
construction
1964 and 1977 an estimated
in
least
in
Regional
enable
part,
to
the
Council
is
revenue
sharing
fiscal
tax
base.
disparities
that
development
in
does not
London.
Between
to the
jobs
suburbs,
of
owing,
4 8
controls.
a
would
location
wtihout fear of
Greater
New
York
government,
can
help
City
through
reduce
encourage the suburbanization
Only a reduction
of metropolitan
possible
then,
tax jurisdiction
the federal
and grants-in-aid,
households and offices.
balkanization
While
not imminent,
metropolitan
introduced in 1964 to
imposition
New York to regulate office
its
London
170,000 to 250,000 office
government and a unified
eroding
Greater
all
central
were dispersed from the center city
at
The
over
in New York,
London with its
suburbanization of offices,
erode the tax base.
limit
and
in
New York will
the distressed
46
in
the experience
office space expanded enormously in central
concommitent
(nor
the
of
the political
make
business
office
districts
of
the outer
boroughs.
47
TABLE 1:
Data Matrix for Selected Variables
#
Town Name
1.
2.
3.
Bridgeport
Danbury
Darien
4.
5.
6.
7.
Westport
Greenwich
Stamford
New Haven
8.
9.
1981 Mean Rent
(per
sq.ft)
1980 Pop.
(in thousands)
1980
Median Income
(in thousands)
$16.168
18.045
20.500
142.546
60.470
18.892
$ 6.081
7.957
18.153
22.415
26.612
27.331
15.963
25.290
59.578
102.453
126.109
16.925
16.602
10.719
5.822
Englewood Cliffs 17.462
19.078
Fort Lee
5.698
32.449
14.535
13.295
10. Hackensack
11. Montvale
17.689
15.863
36.039
7.318
9.462
10.814
12.
13.
14.
15.
15.385
16.000
12.500
14.871
26.474
19.068
11.407
5.330
9.692
9.199
10.792
11.681
16. Newark
17. West Orange
14.511
15.202
329.248
39.510
4.525
10.837
18. Jersey City
19. Secaucus
14.146
15.000
223.532
13.719
5.812
9.495
20. Lawrenceville
21. Princeton
22. New Brunswick
10.000
14.810
12.591
2.109
12.035
41.442
12.479
9.502
5.782
23. Piscataway
24. Woodbridge
25. Freehold
14.090
16.987
10.000
45.555
13.762
10.020
7.143
10.483
6.957
26. Red Bank
11.222
12.031
8.344
27.
28.
29.
30.
31.
32.
33.
34.
35.
14.357
15.792
14.596
13.000
16.595
14.752
14.730
14.000
12.064
9.359
16.614
5.305
7.465
11.983
9.710
106.201
7.118
55.593
9.528
9.254
10.492
4.900
10.693
9.000
6.712
11.571
5.625
36. Garden City
37. Great Neck
15.241
14.288
22.927
9.168
13.602
13.209
38.
39.
40.
41.
42.
43.
44.
45.
46.
Lake Success
Hempstead
Hauppauge
Melville
Elmsford
Rye
New Rochelle
Scarsdale
White Plains
18.459
10.500
11.839
13.897
10.631
19.500
22.000
14.961
17.153
2.396
40.404
20.960
8.139
3.361
15.083
70.794
17.650
46.999
22.495
7.236
8.149
9.843
9.603
14.756
10.343
22.956
10.876
47.
Tarrytown
15.890
10.648
10.778
Paramus
Rutherford
West Caldwell
Roseland
Florham Park
Morristown
Parsippany
Toms River
Bridgewater
Franklin Twp.
Elizabeth
Springfield
Union
48
TABLE 1(cont.)
#
Town Name
Mean
Stories
1.
Bridgeport
Danbury
11.000
3.833
Darien
Westport
Greenwi.ch
Stamford
New Haven
3.000
3.000
3.100
5.852
10.333
2.
3.
4.
5.
6.
7.
8.
9.
Englewood Cliffs 2.667
Fort Lee
Hackensack
Montvale
Paramus
6.636
6.000
1.750
3.571
Rutherford
12.000
15.
16.
17.
West Caldwell
Roseland
Newark
West Orange
2.000
3.714
16.788
3.500
18.
Jersey City
12.500
19.
20.
21.
22.
23.
Secaucus
Lawrenceville
Princeton
New Brunswick
4.667
2.000
2.688
6.500
Piscataway
Woodbridge
Freehold
2.600
5.111
5.000
Red Bank
Florham Park
Morristown
3.500
2.400
5.286
Parsippany
Toms River
Bridgewater
Franklin Twp.
Elizabeth
Springfield
Union
Garden City
3.000
3.000
3.500
3.500
6.000
3.000
2.667
4.333
Great Neck
Lake Success
Hempstead
3.545
3.000
7.000
Hauppauge
Melville
Elmsford
3.333
3.538
4.000
10.
11.
12.
13.
14.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
Rye
New Rochelle
2.000
17.000
Scarsdale
4.333
White Plains
Tarrytown
6.882
6.000
49
Commercial
Prop. Tax
Resi-
dential
Prop. Tax
$2.86
1.15
1.36
$2.06
2.29
1.39
.95
1.60
3.81
1.05
1.69
2.64
1.69
1.62
2.24
2.52
0.85
1.71
3.95
1.47
1.82
2.85
1.71
2.13
3.18
2.86
4.40
6.46
3.50
6.88
3.88
3.12
2.17
4.67
2.96
3.23
1.58
1.11
586
2501
1465
421
1560
915
707
237
4647
1.81
2.09
2.72
2.73
1.46
2.48
1.85
1.91
1.79
2.18
3.00
1.83
1.80
3.34
3.63
3.28
3.70
3.83
3.32
3.77
3.04
3.50
4.44
2.54
3.51
3.60
2.74
4.00
3.43
1.53
6.65
5.50
5.04
6.36
4.16
4.30
5.78
5.20
8.30
6.80
4.60
5.50
3104
3.56
3.07
4.25
1.70
1.86
1.73
2.59
1.99
3.71
2.25
3216
1564
1994
2551
4621
5513
3.12
2.28
2.90
2.50
# of
Mgrs.
2117
4948
372
69
405
840
1310
708
337
473
446
624
246
279
505
255
2548
616
1187
2049
717
290
1322
480
320
172
1263
4294
2026
3165
501
Table l(cont.)
*Sources:
Mean Rent - Black's Guide 1982
Stories
- Black's Guide 1982
Comm. Tax - Center for Local Tax Research
Res. Tax - Center for Local Tax Research
Income - U.S. Bureau of the Census 1983
Population - U.S. Bureau of the Census 1983
Managers - U.S. Bureau of the Census 1972
50
Table
2a:
1982 Utility Cost Differentials
in the Region*
KWHR
STATE
UTILITY
1,500
10,000
150,000
N.Y.
Con Edison
LILCO
$ 299
170
$1,402
1,091
$19,540
14,527
N.J.
Jersey Central
Power & Light
PSE&G
171
864
12,274
183
930
12,254
United Illuminating
Conn. Light & Power
208
193
192
1,111
14,962
11,256
11,227
CONN.
Hartford Electric Light
*Source:
Edison Electric
TABLE 2b:
(1)
Corporate
1981
978
976
Institute
Income Tax Differentials
Income:
State
Flat
Rate
New York
10%
No
9%
No
10%
No
New Jersey
Connecticut
(2)
Personal
Federally
Deductible?
Income:
New York:
2% up to $1,000 and
New Jersey:
Connecticut:
*Source:
in the Reqion*
The Tax
14%
2% up to $20,000 and
above $23,000
2.5%
7% on capital gains.
above $20,000
Foundation,
51
Inc.
above 20,000
1-9% on dividends
TABLE 3:
1.
1980 Office
Building Operating Expenditures*
The components of office operating expenditures:
Energy
Cleaning
Real Estate
General Building Costs
Administrative Costs
Other
2.
Downtown New York and other major downtown sites
1980,
in
Total
New York
Tulsa
San Francisco
Houston
Washington, D.C.
Atlanta
Differentials
suburbs for
sq. ft):
in
selected
operating
regions
Region
Middle Atlantic
Northern Midwest
Southern
Southwest
Expense
985.6
760.3
543.2
533.9
506.0
491.6
423.1
Chicago
*Source:
(for
cents per sq.ft):
City
3.
22%
15%
22%
10%
6%
25%
City
833.4
502
443
481
expenses in
cities
(for
1980, in cents
Suburbs
605.3
516
406
487
Building Owners and Managers Association
52
vs.
per
TABLE 4:
Correlation Matrix For Selected Variables*
Mean Rent
Distance
Mean-Rent
Distance
1.000
Stories
-0.038
1.000
0.123
-0.141
1.000
Comm. Tax
-0.223
-0.297
0.506
1.000
Electricity
-0.036
-0.071
0.221
0.666
1.000
Res. Tax
-0.338
-0.170
0.399
0.865
0.609
1.000
Income
0.450
-0.189
-0.365
0.023
0.212
-0.055
1.000
Population
0.120
-0.051
0.740
0.279 -0.066
0.280
-0.409
1.000
Managers
0.598
-0.068
0.624
0.176
0.053
0.117
-0.035
0.755
Clerical
0.114
-0.127
0.732
0.296
-0.069
Stories
*Sources:
Comm. Tax
Electricity
Res. Tax
Income
Population
0.303 -0.413
Managers
Clerical
1.000
0.971 0.769
Mean Rent - Black's Guide 1982
Distance - Regional Plan Association, Map of Region
Stories - Black's Guide 1932
Comn. Tax - Center for Local Tax Research
Electricity - Edison Electric Institute
Res. Tax - Center for Local Tax Research
Income - U.S. Bureau of the Census 1983
Population - U.S. Bureau of the Census 1983
Managers - U.S. Bureau of the Census 1972
Clerical - U.S. Bureau of the Census 1972
53
1.000
TABLE 5:
Derivation of Dependent Variable and
Its Variance
Derivation of weighted mean rent:
Let ri
= rent/sq.ft in building j, town i.
Assume rij has a constant variance:
(
)2
Now, mean rent in town i, is given by:
ri=
ni
E rij Si
j=l
=
total rent in
i
total sq.ft. in i
ni
=sij
j=l
where si- is the sq.ft for building
ni = num er of buildings in town i.
j in town i
Derivation of variance of mean rents:
nThen, variance
(ri)
12
E
si*
j=1
n1
=
var(rij)
2
n=
( G2)
,=12
Therefore, weighted least
squares is the appropriate
technique.
Assuming rents have a constant variance across
towns, observed mean rents will be heteroskedastic, as
demonstrated in the derivation above.
54
Notes
1.
An Urban and
P.W. Daniels, Office Location:
1975), p. 1.
Bell,
Study (London:
2.
on the New
Samuel M. Ehrenhalt, "Some Perspectives
York City Economy in a Time of Change," in New York
City's
Changing Economic Base ed. Benjamin J. Klebaner
(New York:
Pica Press, 1981), p. 13.
3.
Ibid.,
4.
Regina B.
Armstrong,
"National
Trends in
Office
Construction, Employment and Headquarter Location in
Patterns of Office
U.S. Metropolitan Areas" in Spatial
John
Growth and Location, ed. P.W. Daniels (New York:
Wiley and Sons, 1979), p. 64.
5.
Office
Ian Alexander,
York:
Longman, Inc.,
6.
Armstrong, "National Trends in Office Construction,
Headquarter Location in
Employment and
Metropolitan Areas," p. 86.
Regional
p. 18.
Location and Public
1979), p. 40.
Policy
(New
U.S.
88.
7.
Ibid.,
p.
8.
"New York City and the
Jr.,
Thomas M. Stanback,
Changing
Services Transformation" in New York City's
Economic Base
ed. Benjamin J.
Klebaner (New York:
Pica Press, 1981), p. 53.
9.
Ehrenhalt,
Economy in
10.
Elizabeth Dickson, "Changing Commuting Patterns to New
York City," New York City Office of Economic Development,
1982.
11.
Gail
G.
City,
1960-1975,"
on the New York City
"Some Perspectives
a Time of Change," p. 15.
Schwartz,,
"The Office Pattern in New York
Spatial Patterns of Office Growth
(New York:
P .W. Daniels
John Wiley
in
and Location, ed.
and Sons, 1979), p.
229.
12.
See,
for example, Regina B. Armstrong, The Office
Industry:
Patterns of Growth and Location (Cambridge,
MA:
The MIT Press, 1972), p. 2.
13.
Schwartz, "The Office
1975," pp. 224-227.
14.
Cited
p.
in
Alexander,
Pattern
Office
8.
55
in
New
Location
York
and
City,
1960-
Public Policy,
15.
P.W.
Daniels,
on Office
Location
"Perspectives
Research," in Spatial Patterns of Office Growth and
Location ed. P.W. Daniels
(New York:
John Wiley and
Sons, 1979), p. 23; and Alexander, Office Location
Public Policy,
p.
25.
16.
Alexander, Office Location and Public
17.
Such a tax was imposed
in
Paris,
Policy,
p.
54.
see Alexander, pp.
76-78.
18.
Ibid.,
p.
19.
Schwartz,
"The
1975," p.
226.
20.
Ibid.,
p.
215.
21.
Ibid.,
p.
221.
22.
See "Black's
Guide 82:
Space Market," published
Bank, New Jersey, 1982.
23.
According to William C. Wheaton, this
developers.
thumb among office
24.
William
25.
James Heilbrun, Urban Economics and Public
York:
St. Martin's
Press, 198 1),
p. 461.
26.
Ibid.,
27.
Cited in Daniels,
Research," p. 4.
28.
Ibid.,
29.
Alexander, Office Location and Public Policy,
30.
Ibid.,
p.
52.
31.
Ibid.,
p.
52.
32.
Ibid.,
p. 48.
33.
Daniels,
p. 14.
34.
Alexander, Office Location and Public
50.
Office
Pattern
in
New York City,
1960-
Suburban Manhattan Office
by James F. Black, Jr.,
Red
is
a
rule
of
C.
Wheaton,' "The
Incidence
of
InterJurisdictional Differences in Commercial Property
Taxes" (December 1981), p. 3.
Policy (New
p. 148.
"Perspectives on
Office Location
p. 4.
"Perspectives
56
on
Office
Location
p 18.
Research,"
Policy,
p.
50.
35.
Daniels,
p.
"Perspectives
on
Office
Location
Research,"
15.
p.
4.
36.
Ibid.,
37.
"Impacts of the New Federalism on
Michael Wasylenko,
Location of Households and
the Intra-Metropolitan
A Review of the Evidence on Intra-Metropolitan
Firms:
TRED
at
presentation
Location" (paper prepared for
Conferences, 1982), p. 23.
38.
An AnalyW.C. Wheaton, "Income and Urban Residence:
Location," American Ecosis
of Consumer Demand for
pp. 620-631.
nomic Review 67(1977),
39.
Taxes and Local
of Property
W.E. Oates, "The Effects
An Empirical
Values:
Spending on Property
Public
Tiebout
and
the
Tax
Capitalization
of
Study
Economy 77 (1969),
Hypothesis," Journal of Political
pp. 957-970.
40.
A. Reschovsky, "Residential Choice and the Local PubAn Alternative Test of the Tiebout Hypolic Sector:
thesis,"
Journa L of Urban Economics 6 (1979), pp. 501-
520.
41.
"Travel
CCumella,
Robert
and
Pushkarev
Boris
Office Building Settings,"
Requirements of Alternative
Plan Association,
Technical Report No. 2, Regional
1983.
42.
Center for Local Tax Research, "Effective Real
Property Tax Rates in the Metropolitan Area of New
York," 1981, pp. 9-12.
43.
Ibid.,
44.
Daniels,
p.
pp.
9-12.
"Perspectives
on
Office
Location
Research,"
16.
Office
45.
Alexander,
46.
Schwartz,
"The
1975," p.
216.
p.
218.
47.
Ibid.,
48.
Alexander,
Location
Office
Office
Pattern
Location
57
and Public
in
Policy,
New York
and Public
p.
City,
Policy,
p.
78.
1960-
65.
Bibliography
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Office Location
York:
Longman Inc., 1979.
and
Policy,
Public
New
Alonso, William.
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The
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MIT Press, 1975.
Armstrong, Regina B.
"National Trends
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Office Construction, Employmen t and Headquarter Location in
U.S.
Metropol itan
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Patterns of Office Growth
New York:
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Armstrong, Regina B.
The Office Industry:
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Growth and Location, Cambridge,
MA: The MIT Press, 1972.
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82:
Published by James
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Bell,
An Urban
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