Chapter 6:
Real Estate Market Analysis
R.E. “Market Analysis”
is a collection of practical analytical tools and
procedures designed to help answer
decision questions, such as:
Decision Questions
– Where to locate a branch office?
– 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?
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.
Types 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

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
Focus on latter type (market supply & demand)…
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
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:
o Space leased but unoccupied is vacant.

Vacancy Rate is an indicator of equilibrium
(balance between supply & demand in the space
market)
Some vacancy is normal and
natural in a market, due to:
o
Search time & moving costs (hence LT leases):
§
§
o
 Don’t take “first deal”
 Search for “good deal” (takes time to find)
“Overbuilding”:
§
§
 Impossible to perfectly predict demand growth
 “Lumpy supply”
The “natural vacancy rate”:
o Rate around which vacancy tends to cycle
o Rate that indicates supply/demand balance
o Above which rents fall, below which rents
rise
o Tends to be higher in more volatile &
faster-growth markets
o Tends to be lower in more supplyrestricted markets
Rent:
§
§
§
§
Rent on new leases in the market
Another equilibrium variable
Most important space market variable
Tricky to accurately quantify (private
info,“apples vs oranges” problems)
§ Watch out for “asking rent” vs
“effective rent”
Example:
$10 rent but 1-yr abatement in 5-yr lease:
o What would you say is the “effective rent”?
Consider “real rent”
– rent adjusted for general inflation (as better
indicator of market trend)
Construction:
§
§
Supply side variable
Starts & completions
o Starts  “Pipeline”
o Completions  Additions to supply side of market
§
Consider net addition to supply:
o Construction Completions – Demolition &
Conversion Out
o Include re-habs & conversions in also
Absorption:
§
§
§
Change in occupied space
Demand side variable
“Gross absorption” = Total new lease signings
o 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
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.
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).
Example market analysis:
Exhibit 6- 1: Annual construction, absorption, and vacancy in the US
office market. 1994-98 are historical figures, 1999-2001 are
forecasts.
Source: LaSalle Advisors Investment Research, 1999 Investment Strategy Annual
Report. © LaSalle Investment Management, reproduced by permission.
What type of decisions would such an analysis be relevant
for?…
Defining the scope of the
market analysis…
§
Geographic/Property type market
segments (or sub-markets)
§
Time-frame of the study (historical,
forecast to when?)
Example of geographic submarkets: Atlanta office market
Exhibit 6- 2: Atlanta MSA Office Sub-markets, 1998.
(Source: Lend Lease Real Estate Investments, Real Estate Outlook: 1999,
based on data from Jamison Research and Lend Lease Investment
Research. © Lend Lease, reproduced by permission. )
Market analysis methodology:
§
Simple trend extrapolation vs Structural
analysis
Trend extrapolation:
§
Take advantage of inertia in space
market (past partly predicts the future)
§ Consider trends and cycles
§ Potential to use statistical techniques
(time-series analysis: autoregression,
ARIMA, VAR, vector error-correction)
§ Potential to bring in capital market
factors as predictors
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.
Formal analysis requires:
o Demand model (including elasticities)
o Supply model (including elasticities & lags)
o Equilibrium model (including landlord behavior)
§
Useful for gaining fundamental understanding
of the market, and making long-term forecasts
§
Used more in academic studies than business
decisions
More widely used in business
decision-making are basic short-term
(1-3 yr) structural market analyses…
Exhibit 6-3: Generic framework of a basic short-term structural market analysis for real
estate
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 of new supply
Forecast demand sources
Forecast of new demand
Forecast space shortfall or
surplus
Decision implicatons?
Major drivers of the demand
side of the space market…
Exhibit 6-4: Major demand drivers by property type
Property Type
Demand Drivers
Residential single family
(Owner occupied)
 Population
 Household formation (child
rearing ages)
 Interest rates
 Employment growth (business &
professional
 Population occupations)
Residential multifamily
(Apartment renters)
Retail
Office
Industrial
Hotel & convention
 Household formation (non-childrearing ages)
 Local housing affordability
 Employment growth (blue collar
occupations)
 Aggregate disposable income


Aggregate household wealth
Traffic volume (specific sites)
Employment in office occupations:
 Finance, Insurance, Real Estate
(FIRE)
 Business & professional services
 Legal services
 Manufacturing employment
 Transportation employment
 Airfreight volume
 Rail & truck volume
 Air passenger volume
 Tourism receipts or number
A simple formal structural
model of a space market…
Supply side:
C (t )   ( R(t  L)  K ),if R(t  L)  K ,
(1)
0,otherwise
S (t )  S (t  1)  C (t )
Demand Side:
Physics:
D(t )    R(t )  N (t )
OS (t )  D(t  1)
(2)
(3)
(4)
v(t )  ( S (t )  OS (t )) / S (t ) (5)
Vacancy rate:
Landlord behavior: R(t )  R(t  1)(1   ((v(t )  V ) / V )) (6)
Put these six equations
together . . .
Numerical example:

Supply sensitivity

Demand sensitivity

Technology
SF/employee

Demand intercept

Rent sensitivity

Construction lag
 = 0.3
 = 0.3
 = 200
 = 10 million SF
 = 0.3
L = 3 years
Exhibit 6-5 Simulated
Space Market Dynamics
100
0.800
90
0.700
80
0.500
50
0.400
40
0.300
30
0.200
20
Year
EMPL
VAC%
RENT
CONST
59
57
55
53
51
49
47
45
43
41
39
37
35
33
31
29
27
25
23
21
19
17
15
13
9
11
0.000
7
0
5
0.100
3
10
Constr. MSF
60
1
Vac, Rent, Empl.
0.600
70
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.
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 forwardlooking?
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?