Transcript Chapter 1

Chapter 6:
Real Estate Market Analysis
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R.E. “Market Analysis”
is a collection of practical analytical tools and
procedures designed to help answer decision
questions, such as:
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Decision Questions

What size or type of building to develop on a specific site?
 What type of tenants to look for in marketing a particular
building?
 What the rent and expiration term should be on a given
lease?
 When to begin construction on a development project?
 How many units to build this year?
 Which cities and property types to invest in so as to
allocate capital where rents are more likely to grow?
 Where to locate new retail outlets and/or which stores
should be closed?
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Market Analysis usually requires
quantitative or qualitative understanding
(& prediction) of:
Demand Side
Supply Side
of the Space Usage Market relevant to some R.E.
decision.
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Two Major Types (levels) of Market Analysis:

Specific micro-level analysis
 Applies to single property, site, or user
 E.g., feasibility analysis or site analysis for a
development project
 “shoe leather…” (also mktg consultants like Claritas)

Broader, more general characterization of a
space market
 Applies to an entire R.E. space market segment or
submarket
 E.g., forecast of supply & demand (&/or rents and
vacancy rates) in Chicago office market, or Class A
office Mkt in downtown Chicago
 “research shops” (or subscriptions)
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General market-level analyses focus on
Five major market indicators:
1.
2.
3.
4.
Vacancy rate
Market Rent
Quantity of new construction starts
Quantity of new construction
completions
5. Absorption of new space
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Vacancy Rate:

Percentage of the stock of space that is currently not
occupied
 Vac.Rate = (Empty SF)/(Total SF) = 1 – Occup.Rate
 Watch out for sub-lease space:
 Space leased but unoccupied is vacant.

Vacancy Rate is an indicator of equilibrium (balance
between supply & demand in the space market)
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Some vacancy is normal and natural
in a market, due to:

Search time & moving costs (hence LT leases):
  Don’t take “first deal”
  Search for “good deal” (takes time to find)
 More uncertainty  LL sets higher reservation rent
(but tenant sets lower rent target, so deals tougher).
 Higher moving costs or search costs LL sets lower
reservation rent (& tenant accepts higher rent target,
so deals easier, longer term leases).

“Overbuilding”:
  Impossible to perfectly predict demand growth
  “Lumpy supply”
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The “natural vacancy rate”:





Rate around which vacancy tends to cycle
Rate that indicates supply/demand balance
Above which rents fall, below which rents rise
Tends to be higher in more volatile & faster-growth
markets
Tends to be lower in more supply-restricted markets
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What does it look like the natural vacancy rate is in the Boston office market?
Is it higher in the CBD or the suburbs?
Boston Office Sub-Markets Vacancy Rate: 1989-2009
30%
25%
20%
15%
10%
5%
Suburban
CBD
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2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
0%
Cambridge
10
Rent:





Rent on new leases in the market
Another equilibrium variable (along with vacancy
rate)
Most important space market variable
Tricky to accurately quantify (private info,“apples
vs oranges” problems)
Watch out for “asking rent” vs. “effective rent”
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Example:
$10 rent but 1-yr abatement in 5-yr lease:

What would you say is the “effective rent”?
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Example:
$10 rent but 1-yr abatement in 5-yr lease:

What would you say is the “effective rent”?
10*(4/5) = $8.
Or, more carefully, if tenant can borrow @ 8%:
=PMT(0.08,5,NPV(0.08,10,10,10,10)) = $8.30.
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Consider “real rent”

rent adjusted for general inflation (as better
indicator of market trend)
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Construction:

Supply side variable
 Starts & completions
 Starts  “Pipeline”
 Completions  Additions to supply side of market
Don’t forget projects in permitting & planning stage too

Consider net addition to supply:
 Construction Completions minus Demolition &
Conversion Out
 Include re-habs & conversions in also
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Absorption:

Change in occupied space
 Demand side variable
 “Gross absorption” = Total new lease signings
 Includes moves within the market
“Net absorption” = Net increase in occupied
space
 Net absorption more relevant for indicating market
demand:
 (Vacant SF)t = (Vacant SF)t-1
+ (Constr)t – (Net Absorption)t

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These market indicator variables:
Vacancy, Rent, Construction, Absorption
Can be used to help characterize & understand
the current market, and forecast how it may
change relevant to R.E. decisions.
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e.g., The Months Supply measure:
Vac  Constr
MS 
NetAbsorp/ 12
MS < Typical Construction Project Duration
 Tight Market
 Room for new development projects
MS > Typ.Constr.Duration
 May be some slack
(but consider natural vacancy rate).
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Perhaps enhance with a
Months Excess Supply measure?...

Vac%  NatVac%StockSF ConstrSF
MES 
NetAbsorpSF / 12
Compare this to typical construction time and what is
in pipeline…
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Absorption in Largest U.S. Multi-Tenant Office Markets
1998-2000 ANNUAL AVG
HOUSTON
CHICAGO
BOSTON
ATLANTA
DALLAS / FORT WORTH
SAN FRANCISCO
LOS ANGELES
NEW YORK
2001-2004F ANNUAL AVG
2.02
2.51
2.86
3.01
4.16
3.32
6.53
4.53
4.82
4.68
5.89
5.57
4.95
6.19
6.29
7.56
10.05
9.28
WASHINGTON DC
Source: Torto Wheaton Research. Millions of square feet. Forecast 2001-2004
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14%
24%
12%
22%
10%
20%
8%
18%
6%
16%
4%
14%
2%
12%
Gross Asking Rent ($/SF-YR)
80
Vacancy as Percent of Existing Stock
90
26%
70
60
50
40
30
20
2010Q3
2009Q3
2008Q3
2007Q3
2006Q3
2005Q3
2004Q3
2003Q3
2002Q3
Real Rent (constant 2011 dollars)
Vacancy (Right Axis) Avg 11.3%
2001Q3
2000Q3
1999Q3
1998Q3
1997Q3
1996Q3
1995Q3
1994Q3
1993Q3
1992Q3
1991Q3
1990Q3
1989Q3
1988Q3
1987Q3
2011Q1
2010Q1
2009Q1
2008Q1
2007Q1
2006Q1
Absorption (Left Axis) Avg 0.3%/yr
2005Q1
2004Q1
2003Q1
2002Q1
2001Q1
2000Q1
1999Q1
1998Q1
1997Q1
1996Q1
1995Q1
1994Q1
1993Q1
0
1992Q1
0%
1991Q1
-10%
1990Q1
10
2%
1989Q1
4%
-8%
1988Q1
-6%
1987Q1
6%
1986Q1
-4%
1985Q1
8%
1984Q1
10%
1983Q1
0%
-2%
Construction Completions (Left Axis) Avg 0.7%/yr
New York
1986Q3
Construction & Absorption As Percent of Existing Stock at
Annualized Rate
28%
1982Q1
28%
26%
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
Vacancy (Right Axis)
22%
10%
20%
8%
18%
6%
16%
4%
14%
2%
12%
0%
10%
-2%
8%
-4%
6%
12%
10%
30
8%
20
6%
4%
2%
0%
Vacancy (Right Axis)
Atlanta
28%
26%
24%
22%
70
Gross Asking Rent ($/SF-YR)
Vacancy as Percent of Existing Stock
2010Q3
2009Q3
0%
2008Q3
-10%
2007Q3
2%
2006Q3
-8%
2005Q3
4%
2004Q3
6%
-6%
2003Q3
8%
-4%
2002Q3
-2%
2001Q3
2000Q3
1999Q3
1998Q3
1997Q3
1996Q3
1995Q3
1994Q3
10%
20%
60
18%
16%
50
14%
40
12%
10%
30
8%
20
6%
4%
10
2%
2010Q3
2009Q3
2008Q3
2007Q3
Vacancy (Right Axis)
2006Q3
2005Q3
2004Q3
2003Q3
2002Q3
2001Q3
2000Q3
Real Rent (constant 2011 dollars)
1999Q3
1998Q3
1997Q3
1996Q3
1995Q3
1994Q3
1993Q3
1992Q3
1991Q3
1990Q3
1989Q3
1988Q3
1987Q3
0
1986Q3
1994Q1
1993Q1
1992Q1
1991Q1
1990Q1
1989Q1
1988Q1
1987Q1
1986Q1
1985Q1
1984Q1
1983Q1
1982Q1
2011Q1
0%
2010Q1
12%
2009Q1
2%
2008Q1
14%
2007Q1
4%
2006Q1
16%
2005Q1
6%
2004Q1
18%
2003Q1
8%
2002Q1
20%
2001Q1
10%
2000Q1
22%
1999Q1
12%
1998Q1
24%
1997Q1
80
14%
1996Q1
90
26%
1995Q1
28%
16%
Vacancy (Right Axis) Avg 17.5%
1993Q3
Real Rent (constant 2011 dollars)
Vacancy (Right Axis) Avg 13.4%
Atlanta
1992Q3
1991Q3
1990Q3
1989Q3
1988Q3
1987Q3
2011Q1
2010Q1
2009Q1
2008Q1
2007Q1
2006Q1
2005Q1
2004Q1
2003Q1
2002Q1
2001Q1
2000Q1
1999Q1
1998Q1
1997Q1
1996Q1
1995Q1
1994Q1
1993Q1
1992Q1
1991Q1
1990Q1
1989Q1
1988Q1
1987Q1
0
1986Q1
0%
1985Q1
2%
1984Q1
Construction & Absorption As Percent of Existing Stock at
Annualized Rate
16%
14%
-8%
Absorption (Left Axis) Avg 3.1%/yr
18%
40
-10%
Construction Completions (Left Axis) Avg 4.3%/yr
20%
50
4%
18%
22%
60
-6%
Absorption (Left Axis) Avg 1.6%/yr
24%
70
10
Construction Completions (Left Axis) Avg 2.5%/yr
26%
80
(same scale across 3 metros)
12%
28%
Vacancy & Rent
24%
Gross Asking Rent ($/SF-YR)
26%
14%
Vacancy as Percent of Existing Stock
16%
San Francisco
90
28%
1986Q3
Construction & Absorption As Percent of Existing Stock at
Annualized Rate
San Francisco
18%
1983Q1
(same scale across 3 metros)
(Note: 2001Q3 is -17% & -19% (ann rate) for construction & absorption due to 9/11 terrorist attack.)
1982Q1
Construction, Absorption, & Vacancy
New York
16%
18%
0%
21
Recall from Chapter 1: Space markets are “segmented”
– different rents can prevail @ same time in different
locations, or for different types of uses.
Apartment Market Asking Rents Net of Inflation: 1986-2011, Seven Metros
Gross Asking Rent ($/mo/unit, Constant 2010 $)
3,500
3,000
Atl
2,500
Bos
Chi
2,000
Dal
NY
1,500
SF
DC
1,000
500
2010Q3
2009Q3
2008Q3
2007Q3
2006Q3
2005Q3
2004Q3
2003Q3
2002Q3
2001Q3
2000Q3
1999Q3
1998Q3
1997Q3
1996Q3
1995Q3
1994Q3
1993Q3
1992Q3
1991Q3
1990Q3
1989Q3
1988Q3
1987Q3
1986Q3
0
Source: CoStar Group
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Recall from Chapter 1: Space markets are “segmented”
– different rents can prevail @ same time in different
locations, or for different types of uses.
Office Market Asking Rents Net of Inflation: 1986-2011, Seven Metros
Gross Asking Rent ($/mo/unit, Constant 2010 $)
90
80
70
Atl
60
Bos
Chi
50
Dal
NY
40
SF
30
DC
20
10
2010Q3
2009Q3
2008Q3
2007Q3
2006Q3
2005Q3
2004Q3
2003Q3
2002Q3
2001Q3
2000Q3
1999Q3
1998Q3
1997Q3
1996Q3
1995Q3
1994Q3
1993Q3
1992Q3
1991Q3
1990Q3
1989Q3
1988Q3
1987Q3
1986Q3
0
Source: CoStar Group
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Defining the scope of the
market analysis…

Geographic/Property type market segments
(or sub-markets)
 Time-frame of the study (historical, forecast
to when?)
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Exh.6-3: Example of geographic sub-markets:
Atlanta office market as defined by CoStar (2012)…
25
Exh.6-3: Example of geographic sub-markets:
Atlanta office market as defined by CoStar (2012)…
2012 Space Market Data Consolidated Into 10 Major Submarkets:
Class A Market Statistics
Mid-Year 2012
Market
# Blds
Vacancy
YT D
Under
Quoted
T otal RBA
Direct SF
T otal SF
Absorption
Deliveries
Const SF
Buckhead
46
15,136,275
2,546,080
2,732,620
18.1%
409,649
0
0
$26.14
Central Perimeter
79
20,717,900
3,433,301
3,672,549
17.7%
524,075
300,000
300,000
$21.83
Downtown Atlanta
30
16,428,027
2,960,675
3,269,055
19.9%
(212,230)
0
0
$19.44
Midtown Atlanta
40
16,275,244
2,722,405
2,923,162
18.0%
274,272
0
450,000
$26.17
North Fulton
113
16,678,599
2,539,667
2,758,154
16.5%
0
72,310
$19.69
Northeast Atlanta
69
8,386,917
1,434,935
1,459,613
17.4%
67,500
344,476
$19.92
Northlake
23
3,371,463
451,495
454,958
13.5%
(75,833)
0
290,000
$20.07
Northwest Atlanta
83
17,949,924
2,758,250
2,846,632
15.9%
(122,782)
0
0
$21.57
South Atlanta
22
1,645,906
377,640
411,771
25.0%
15,741
0
0
$20.16
1
71,500
0
0
0.0%
0
0
0
$0.00
W est Atlanta
T otals
506
116,661,755
19,224,448
20,528,514
Vac %
YT D Net
17.6%
(5,149)
116,233
923,976
367,500
1,456,786
Rates
$21.97
Source: CoStar Property®
Class B Market Statistics
Mid-Year 2012
Existing Inventory
Market
YT D Net
YT D
Under
Quoted
Absorption
Deliveries
Const SF
Rates
17.7%
8,050
0
0
$18.92
28.1%
84,617
16,000
0
$18.05
1,250,658
8.3%
(38,992)
0
0
$14.46
936,071
14.6%
84,056
0
0
$17.81
2,454,982
2,503,965
17.0%
134,143
2,400
0
$14.73
T otal RBA
Direct SF
T otal SF
86
4,797,941
820,644
847,587
Central Perimeter
256
9,560,549
2,604,334
2,684,364
Downtown Atlanta
147
15,059,769
1,249,348
Midtown Atlanta
134
6,419,880
885,651
North Fulton
833
14,722,654
Buckhead
Northeast Atlanta
# Blds
Vacancy
Vac %
1,374
20,436,802
4,288,304
4,372,377
21.4%
99,853
22,200
23,504
$14.49
Northlake
674
18,646,450
2,081,709
2,136,103
11.5%
11,488
13,822
0
$16.94
Northwest Atlanta
1,113
21,682,629
4,044,095
4,088,813
18.9%
49,508
0
16,650
$15.73
South Atlanta
756
14,138,178
1,719,928
1,779,284
12.6%
59,354
0
41,145
$16.62
11.8%
57,362
40,000
40,000
$15.28
16.3%
549,439
W est Atlanta
T otals
191
2,540,934
5,564
128,005,786
300,831
20,449,826
300,831
20,900,053
94,422
121,299
$15.96
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Existing Inventory
26
Exh.6-3: Example of geographic sub-markets:
Atlanta office market as defined by CoStar (2012)…
Class C Market Statistics
Market
# Blds
Vacancy
T otal RBA
Direct SF
T otal SF
Vac %
7.6%
YT D Net
YT D
Under
Quoted
Absorption
Deliveries
Const SF
Rates
(814)
0
0
$18.01
Buckhead
259
1,849,733
140,517
140,517
Central Perimeter
371
3,242,745
489,551
489,551
15.1%
33,846
0
0
$13.90
Downtown Atlanta
221
4,762,046
885,019
885,019
18.6%
40,760
0
0
$15.42
Midtown Atlanta
232
1,722,184
141,457
152,881
8.9%
(4,861)
0
0
$15.72
North Fulton
852
4,315,854
466,578
468,743
10.9%
98,111
0
0
$12.88
Northeast Atlanta
1,634
8,417,983
1,100,365
1,103,960
13.1%
(3,853)
0
0
$13.08
Northlake
1,603
9,065,346
698,939
701,635
7.7%
79,970
0
0
$13.44
Northwest Atlanta
1,748
9,303,317
983,138
987,399
10.6%
83,859
0
0
$13.69
South Atlanta
1,650
8,575,900
1,007,506
1,007,506
11.7%
39,149
0
0
$13.71
0
0
$11.89
W est Atlanta
475
3,201,587
928,581
928,581
29.0%
27,561
T otals
9,045
54,456,695
6,841,651
6,865,792
12.6%
393,728
0
0
$13.68
Source: CoStar Property®
Total Office Market Statistics
Existing Inventory
Market
# Blds
Mid-Year 2012
Vacancy
T otal RBA
Direct SF
T otal SF
Vac %
YT D Net
YT D
Under
Quoted
Absorption
Deliveries
Const SF
Rates
Buckhead
391
21,783,949
3,507,241
3,720,724
17.1%
416,885
0
0
$24.32
Central Perimeter
706
33,521,194
6,527,186
6,846,464
20.4%
642,538
316,000
300,000
$19.95
Downtown Atlanta
398
36,249,842
5,095,042
5,404,732
14.9%
(210,462)
0
0
$17.99
Midtown Atlanta
406
24,417,308
3,749,513
4,012,114
16.4%
353,467
0
450,000
$24.10
North Fulton
1,798
35,717,107
5,461,227
5,730,862
16.0%
227,105
2,400
72,310
$17.15
Northeast Atlanta
3,077
37,241,702
6,823,604
6,935,950
18.6%
212,233
89,700
367,980
$15.75
Northlake
2,300
31,083,259
3,232,143
3,292,696
10.6%
15,625
13,822
290,000
$16.49
Northwest Atlanta 2,944
48,935,870
7,785,483
7,922,844
16.2%
10,585
0
16,650
$17.75
South Atlanta
2,428
24,359,984
3,105,074
3,198,561
13.1%
114,244
0
41,145
$16.27
W est Atlanta
667
5,814,021
1,229,412
1,229,412
21.1%
84,923
40,000
40,000
$13.52
T otals
15,115
299,124,236
46,515,925
48,294,359
16.1%
1,867,143
461,922
1,578,085
$18.47
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Mid-Year 2012
Existing Inventory
27
Market analysis methodology:

Simple trend extrapolation vs Structural
analysis
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Trend extrapolation:

Take advantage of inertia in space market
(past partly predicts the future)
 Consider trends and cycles
 Potential to use statistical techniques (timeseries analysis: autoregression, ARIMA,
VAR, vector error-correction)
 Potential to bring in capital market factors
as predictors
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29
Structural Analysis:

Model the structure of the market
(underlying determinants of supply &
demand, e.g. population growth and
employment growth)
 Forecast the underlying determinants (e.g.,
economic base analysis like we talked about
in Ch.3), then use model to predict space
market.
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30
Formal analysis requires:
 Demand model (including elasticities)
 Supply model (including elasticities & lags)
 Equilibrium model (including landlord behavior)

Useful for gaining fundamental understanding of
the market, and making long-term forecasts
 Used more primarily in consultants reports and
academic studies
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31
Exh.6-4: Widely used decision-making tool:
Basic short-term (1-3 yr) structural market analysis:
SUPPLY SIDE
DEMAND SIDE
Inventory existing supply
Identify sources of space usage demand
Quantify relationship between
demand sources and quantity of
space usage
Inventory construction pipeline
Forecast demand sources
Forecast of new supply
Forecast of new demand
Forecast space shortfall or surplus
Decision implicatons?
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32
Property Type
Demand Drivers
Residential single family
(Owner occupied)
 Population
 Household formation (child
rearing ages)
 Interest rates
 Employment growth (business &
professional occupations)
Residential multifamily
(Apartment renters)
 Population
 Household formation (non-childrearing ages)
 Local housing affordability
 Employment growth (blue collar
occupations)
Retail



Office
Employment in office occupations:
 Finance, Insurance, Real Estate
(FIRE)
 Business & professional services
 Legal services
Industrial




Aggregate disposable income
Aggregate household wealth
Traffic volume (specific sites)
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Exh.6-5: Major drivers of the demand side of the space market:
Manufacturing employment
Transportation employment
Airfreight volume
Rail & truck volume
 Air passenger volume
 Tourism receipts or number
visitors
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Hotel & convention
33
A simple formal structural model of a space market:
Supply side . . .
Construction (developer behavior):
C (t )   ( R(t  L)  K ), if R(t  L)  K ,
(1)
0, otherwise
R(t) = Rent at time t ($/SF).
L = Construction lag (yrs).
K = Replacement cost rent level.
ε = Price elasticity of supply (responsivenesss)
Stock (aggreg.supply) response:
S (t )  S (t  1)  C (t )
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(2)
34
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A simple formal structural model of a space market:
Demand side . . .
Tenant demand:
D(t )   R(t )   N (t )
(3)
N = Underlying “need” (e.g., employment)
η = Price elasticity of demand
τ = Technology parameter (e.g.
SF/employee)
Occupied space:
(lag to implement demand reflects search & move time)
OS (t )  D(t  1)
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(4)
35
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A simple formal structural model of a space market:
Supply & demand sides (equilibrium) . . .
Rent adjustment
(landlord & potential tenant behavior):
R(t )  R(t  1)(1   ((v(t )  V ) / V ))
(6)
v(t) = Vacancy rate at time t.
V = “Natural” vacancy rate for the mkt.
Vacancy rate “physics” (definition):
v(t )  (S (t )  OS (t )) / S (t )
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(5)
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Put these six equations together . . .
Numerical example typical parameters:

Supply sensitivity  = 0.3

Demand sensitivity  = 0.3

Technology
 = 200 SF/employee

Demand intercept  = 10 million SF

Rent sensitivity
 = 0.3

Construction lag
L = 3 years
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Exh.6-6 Simulated Space Mkt Dynamics
100
0.7
90
0.6
60
0.4
50
0.3
40
30
0.2
20
0.1
10
0
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0.5
70
Constr. MSF
Vac, Rent, Empl.
80
0.0
1
4
7
10
13
16
19
22
25
28
31
34
37
40
Year
Employment(000s)
Rent($/SF/YR)
Vacancy(%)
Construction Completions(MSF/YR)
11-year cycle, even though no business cycle!
38
Rent & Vacancy Alone
Vac, Rent
20.0
15.0
Vac
quartercycle lead
ahead of
rent.
Vacancy peaks just
before rent troughs
10.0
5.0
0.0
Year
VAC%
RENT
Devlpt
cycle
exagerates
rent&vac
cycle.
New supply enters just as vacancy peaks
Employment & Construction Alone
0.700
120
Empl. 000s
0.800
0.600
100
0.500
80
0.400
60
0.300
40
0.200
20
0.100
0
0.000
Constr. MSF
140
RE mkt
cyclical
even when
underl
demand
not
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25.0
Year
EMPL
CONST
39
Market Dynamics

The real estate cycle may be different from and
partially independent of the underlying business
cycle in the local economy.
 The cycle will be much more exaggerated in the
construction and development industry than in
other aspects of the real estate market, such as
rents and vacancy.
 The vacancy cycle tends to slightly lead the rent
cycle (vacancy peaks before rent bottoms).
 New construction completions tend to peak when
vacancy peaks.
Specifics depend on the parameter values.
(& CAVEAT: This is a simple model, ignores forward-looking behavior.)
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40
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Market Dynamics

In the preceding model, were any of the market
participants forward-looking?
 What features of the above results do you think
are due to myopia or purely adaptive behavior on
the part of the market participants?
 In the real world, what factors or elements in the
real estate system will tend to be forward-looking?
 In the real world, will it be possible to perfectly
forecast the future? Will some market participants
likely be somewhat myopic or adaptive in their
behavior?
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Forward-looking decisions & negative feedback equilibrates the system…
SPACE MARKET
Exhibit 2-2
SUPPLY
(Landlords)
ADDS
NEW
Rising supply
 Falling cash
flow Falling
asset prices 
Less dvlpt…
LOCAL
&
NATIONAL
ECONOMY
DEMAND
(Tenants)
RENTS
&
OCCUPANCY
FORECAST
FUTURE
DEVELOPMENT
INDUSTRY
Consider
constr
pipeline,
underl
demand
evolution…
ASSET MARKET
IF
YES
IS
DEVELPT
PROFITABLE
?
CONSTR
COST
INCLU
LAND
SUPPLY
(Owners
Selling)
CASH
FLOW
PROPERTY
MARKET
VALUE
MKT
REQ’D
CAP
RATE
CAPI
TAL
MKTS
DEMAND
(Investors
Buying)
= Causal flows.
= Information gathering & use.
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42
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But positive feedback can cause spirals that result in cycles…
SPACE MARKET
Exhibit 2-2
SUPPLY
(Landlords)
ADDS
NEW
Rising prices
 Increased
demand 
More dvlpt…
LOCAL
&
NATIONAL
ECONOMY
DEMAND
(Tenants)
RENTS
&
OCCUPANCY
FORECAST
FUTURE
DEVELOPMENT
INDUSTRY
ASSET MARKET
IF
YES
IS
DEVELPT
PROFITABLE
?
CONSTR
COST
INCLU
LAND
SUPPLY
(Owners
Selling)
CASH
FLOW
PROPERTY
MARKET
VALUE
MKT
REQ’D
CAP
RATE
DEMAND
(Investors
Buying)
= Causal flows.
CAPI
TAL
MKTS
Rising prices 
Increased
demand 
Rising prices…
= Information gathering & use.
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Both the space market & the asset market can tend to be cyclical,
but the cycle is not necessarily the same…
Exhibit 2-5. Example Space Market Rents & Asset Market Prices (adjusted for
inflation): 1986-2011*
120
Indexed to 1986Q4 = 100
110
100
90
80
70
60
50
2010Q4
2009Q4
2008Q4
2007Q4
2006Q4
2005Q4
2004Q4
2003Q4
2002Q4
2001Q4
2000Q4
1999Q4
Rent
1998Q4
1997Q4
1996Q4
1995Q4
1994Q4
1993Q4
1992Q4
1991Q4
1990Q4
1989Q4
1988Q4
1987Q4
1986Q4
40
Price
*The lines depicted here are illustrative examples typical of the US commercial real estate markets, but not exact correlates of the same markets. The rent line
is based on asking rents for office space in seven major metro areas (source: CoStar); the asset price line isthe NCREIF-based TBI (source: MIT) transaction price
index for institutional investment property. Both the rent line and the asset price line are net of CPI inflation.
Source: CoStar Group, NCREIF, MIT
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44
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Both the space market & the asset market can tend to be cyclical,
but the cycle is not necessarily the same…
Exhibit 2-5. Example Space Market Rents & Asset Market Prices (adjusted for
Asset mkt
inflation): 1986-2011*
120
cycle
Indexed to 1986Q4 = 100
110
Space mkt
cycle
100
Both mkts
cycle
together
90
80
70
60
50
40
2010Q4
2009Q4
2008Q4
2007Q4
2006Q4
2005Q4
2004Q4
2003Q4
2002Q4
2001Q4
2000Q4
1999Q4
1998Q4
1997Q4
1996Q4
1995Q4
1994Q4
1993Q4
1992Q4
1991Q4
1990Q4
1989Q4
1988Q4
1987Q4
1986Q4
Rent
Price
*The lines depicted here are illustrative examples typical of the US commercial real estate markets, but not exact correlates of the same markets. The rent line
is based on asking rents for office space in seven major metro areas (source: CoStar); the asset price line isthe NCREIF-based TBI (source: MIT) transaction price
index for institutional investment property. Both the rent line and the asset price line are net of CPI inflation.
Source: CoStar Group, NCREIF, MIT
© 2014 OnCourse Learning. All Rights Reserved.
45
Geltner MIT/CRE