The Office Market, and the Labor Market
Employment
Decentralization, “edge” cities.
MIT Center for Real Estate
Week 5: Employment
Decentralization, “edge” cities.
• Measuring Decentralization, space versus
jobs.
• Wages, the urban labor market and the
incentive for decentralization.
• Local agglomeration, clustering,
transportation infrastructure, planning and
other “limits to sprawl”.
MIT Center for Real Estate
National % of office space in CBD as opposed to
Suburbs (source: CBRE)
MIT Center for Real Estate
Washington D.C.: City and Suburban
Office Space (source: CBRE)
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1950
1953
1956
1959
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
District of Columbia Suburban Maryland Northern Virginia
MIT Center for Real Estate
Decentralization “flattens” the
cumulative W.D.C. spatial distribution of
office space. [Source: geo-coded building data, CBRE]
Pe r ce nt of Stock
120%
100%
80%
60%
40%
20%
0%
0
2
4
6
8
14
16
22
24
30
10
12
18
20
26
28
32
M ile s out fr om Ce nte r
1980 2002
MIT Center for Real Estate
The Distribution of Office Using Jobs Across The
NY CMSA [Source: Employment Zip file, 1999]
120%
100%
80%
60%
40%
20%
0%
102
108
0
6
12
18
24
30
36
42
48
54
66
72
78
84
90
96
60
Inf ormation, Real Es tate, Prof es s ional Serv ic es
Financ e
Management of Companies , A dminis trativ e Serv ic es
MIT Center for Real Estate
Figure 7: Los Angeles Spatial Distributions
Employment Population
1
Cummulative Employment and Population (%)
.75
.5
.25
0
0 10 20 30 40 50 60 70
Distance from Center of the CBD (miles)
MIT Center for Real Estate
Figure 6: New York Spatial Distributions
Employment Population
1
Cummulative Employment and Population (%)
.75
.5
.25
0
0 5 10 15 20 25 30 35 40 45 50 55
Distance from Center of the CBD (miles)
MIT Center for Real Estate b
Concentration = ∫ e(t) dt
0 b
Where: e(t): cumulative fraction of jobs (population) at distance t
b: distance at which 98% of population live.
Figure 8: Employment and Population Centralization
in a Sample of 120 Cities
Honolulu
Wichita DesMoin
Rochest
.8 Birming Erie
Oklahom
Jacksonv Syracu Jacksonv
Pensac Tulsa Sarasot
Lansing Tucson Fresno
Anchor Austin NewOrleSacram
SanAnton
Charlest
Employment Centralization
Montgom
Portland Toledo
AtlCity Chatta ColSpr Biloxi Columb
PeoriaMinneap FortWay Allent
Houston
SaltLake Wash
Huntingt Lincoln
CorpChr Columb
Shrevep Louisv Pittsbu
Waco Modesto
McAllen Flint Albany Spokane Waterb
Reno ElPasoIndianap Norfolk NewYork
.7 Charlot Kansas LexFay
RichmondFtMyers
Harrisb GrRapids
LosAng
SpringfReading Omaha
BatonRMadison
Cincinn
ProvidenStockton August
Greenv Mobile Boston
SantaB
Seattle Provo Savannah
Denver
Dayton
Lrock Roanoke StLouis
Buffalo Milwauk
Phoenix Worcest
SthBend
Evansv SanDieg
Baltim
Daytona LasVegas Rockf
Tampa
Lubbock
Atlanta
Dallas Canton Salem Memphis Detroit
Kalamaz Knoxv
Lancast
Raleigh WPalmB
Chicago
.6 Greensb
Orlando Scranton Philad
Columb
Clevel
SanFran
Miami
Youngst
Hartford
.5
.5 .6 .7
Population Centralization
MIT Center for Real Estate
Employment Dispersal and commuting
• If people can commute only inward (not true but a useful
assumption!). Then the number of people traveling inward
at any point is the difference between the cumulative
number of jobs located up to that point and the cumulative
number of workers living up to that point.
• Proof: if the number of inward travelers at distance (t) is
less than this difference then not all jobs up to t are being
filled. If the reverse, then there are more commuters than
jobs up to t and jobs beyond t are not being filled.
• Implication: jobs must be more centralized than residences
for positive traffic flow in the allowed direction.
• With complete job-residence dispersal: no commuting!
• With centralized employment traffic worst at the edge of
the business district
MIT Center for Real Estate
F ig u r e 4 : L a n d U s e a n d T r a v e l C o s t s ,
2 m illio n in h a b it a n t s , m ix e d u s e c it y , h ig h a g g lo m e r a t io n
1 .2 500
450
1
400
350
0 .8
% of Total
300
0 .6 250
200
0 .4
150
100
0 .2
50
0
0
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190
D i sta n c e ( 1 / 1 0 M i l e )
C u m u l a t i ve E m p l o y m e n t C u m u l a t i ve P o p u l a t i o n T r a ve l C o s t s / m i l e
F ig u re 6 : L a n d U s e a n d T ra v e l C o s ts ,
2 m illio n in h a b ita n ts , m ix e d u s e c ity , lo w a g g lo m e ra tio n
1 .2 350
1 300
250
0 .8
% of Total
200
0 .6
150
0 .4
100
0 .2 50
0 0
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190
D i sta n c e (1 / 1 0 M i l e )
C u m u la t ive E m p lo y m e n t c u m u la t ive P o p u la t io n Tra ve l C o s t s / m ile
MIT Center for Real Estate
Wage as well as Rent Gradients
• In a location equilibrium, no one wants to change location
of either home or work.
• For workers at a particular plant – what insures that they
are indifferent to different residential locations? Housing
Rent (Lecture 2).
• For residents at a particular home location what insures
that they are indifferent to switching jobs? Different
Wages. Jobs closer to the center must pay for the
incremental additional cost of commuting: hence a “Wage
Gradient”.
• But: cities do not have inward-only commuting!
MIT Center for Real Estate
Commuting times in the greater NY CMSA
[internal = Origin and destination in same area]
Destination Internal
Origin Downtown Midtown
CT 56.5 56.2 20
NJ 53.2 52.9 22.1
NY 40.6 39.8 40.9
Weighted Avg 42.1 41.3
MIT Center for Real Estate
Land Rent and Commuting in a city with both a CBD and
a suburban Sub Center
Sub Center
CBD
Land rent
rf
r(d)
r(d)
ra
commute
d1 d6 d1 d5 d2 d3 d4
MIT Center for Real Estate
Why firms leave the CBD for a Subcenter.
• Subcenter workers at d5 pay the same for land as
CBD workers living there, but have a shorter
commute. Hence their wage must be less by the
difference in commute: (d5 – d1 ) versus (d2 – d5 ).
• Note that land rents still make workers that are
employed at each center indifferent about living at
different locations around that center.
• Firms at the CBD now must not only pay higher
land rent (equal here to residential), but must also
pay higher wages for labor.
- Wages: 15% more [e.g. $13,500]
- Rent (per worker): 250 x $15-20 [e.g. $4250]
MIT Center for Real Estate
MIT study of wages and average commuting time by location
of employment [POWPUMA]
MIT Center for Real Estate
Why not a Fully Dispersed Polycentric City?
An MSA grows Horizontally with additional sub
centers and no increase in commuting at each sub
center [See Gordon, et al.]
Land Rent
rf
r(d)
ra
MIT Center for Real Estate
The Degree of Decentralization/Dispersal:
Many small –vs- Few large Centers
• Clusters (nodularity) versus “sprawl”.
• Economic Agglomeration
• Realities of Transportation networks.
• Heterogeneous workers, housing mix.
• Planning limits.
- Forced sprawl through height limits
- NIMBY
- limited commercial land zoning
MIT Center for Real Estate
Boston Office Market: Nodularity and the
distribution of subcenters
Office Area, Buildings, and Asking Rents, Boston-Area Towns, 1993, CBRE.
Town (Cluster Square Feet (thousands) Number of Buildings Rent
Boston
Back Bay 10,675 66 25.19
Financial District 26,754 141 26.73
South Station 3,053 21 23.50
Andover 1,438 10 16.25
Burlington 3,498 43 18.90
Cambridge 11,103 116 18.64
Framingham 3,196 39 14.06
Lexington 2,320 38 19.41
Natick 1,518 19 15.50
Newton 1,973 38 18.32
Quincy 4,797 44 15.90
Waltham 5,843 60 19.60
Wellesley 1,774 36 19.45
Westborough 1,664 15 12.50
Residual 26,793 548 15.21
MSA 106,399 1,234 20.74
adapted from DiPasquale and Wheaton (1996)
MIT Center for Real Estate
Urban “Agglomeration”
• Firms of the same type share information and ideas if they
are in proximity to each other. [non competes?]
• Firms of different types that do business with each other
find it more convenient if in proximity. [transportation
costs are trivial and the Internet?]
• Workers can switch jobs more easily (not have to move
residence) when there are many similar jobs in proximity.
• Firms find it easier to fill vacancies when there are many
workers in other (similar) companies nearby.
• Fun, Entertainment, nice lunch spots emerge when lots of
firms locate together [implication is that workers accept
lower wages!].
• Do Headquarters enjoy agglomeration? [Shilton].
MIT Center for Real Estate
Firm Production costs are lower in larger subcenters
(Agglomeration), but wages are higher
Information technology (----) erodes agglomeration?
Output Costs
Maximum center size
Total Costs
wages
Productio
n costs (ag
glomeratio
n)
Sub Center Size
