The Economics of Development: Integrating
Land Economics and Portfolio Analytics
European Real Estate Society
Stockholm, Sweden
June 2009
Terry V. Grissom Ph.D.*
James N. Berry Professor.*
Jasmine L.C. Lim Ph.D.*
*School of the Built Environment University of Ulster,
Jordanstown
The Economics of Development
• Development decisions/strategies are highly associated if not
dependent on development valuation analysis
• This valuation approach is directly linked to the constructs of
distributive theory requiring a consideration of value
differences and potential profits that arise from differing land
uses associated with alternative project proposals
• Distributive theory requires an analysis of the return or
compensation for each of the factors of production that define
economic production, growth and development
• This requires that consideration of the differences in returns to
the varying levels of distributive factors of labour, capital, land
and entrepreneurship and their associated risk exposures that
may arise under proposed alternative developments possible
on any given site.
• This approach combines the options approach to development
with the traditional production/manufacturing process
The Economics of Development
• This integrated approach to development: option and
production fits one scenario of capital theory defining capital
as:
– The “product of production” and as investment (economic measures of
time) See Ahmed (1990)
• This allows labour and capital (real and financial) as
development inputs and allows the distributive measures of
land and profit (residuals) as the dependent (determined)
measures along with the total returns measure of performance
as defined by risk and uncertainty variables in the context of
the Fama-French Three factor model (1992).
Applicability of the Three Factor Model
to Property Development
• Variables
– Leverage
– Capital cost as spread between construction loan cost less LIBOR
 L (YM  RF )M / E
– Capital size variable where size is the log of the equity cost of
development

ln( C )
SUi
E
– Proxy for development performance which the ratio of equity cost of
development is divided by the gross development value which is
equivalent to the Fama French book equity to market equity ratio#
 ln( DVE / CE )
# This is a proxy which could include entrepreneurial effort, enterprise, innovation,
coordination and strategic management
The Economics of Development
3 Factor Fama-French Model for Single Use Development
E ( RiU  RF ) | U     Mm ( RMmp  RF )   L (YM  RF )M / E   SUi ln( CE )   ln( DVE / CE )   iU
3 Factor Fama-French Model for Mixed Use Development
E(R  R ) | U     ( R
 R )   (Y  R ) M / E   ln(C )   ln( DV / C )
iU F
Mui Mupi F L M F
SUi E i
Ei Ei
  ln( DV / C )  
j
Ej Ej iUj
3 Factor Fama-French Model extended to multiple
Mixed Use Development
E(R  R ) | U     ( R  R )   (Y  R ) M / E   ln(C )   ln( DV / C )
iU F
Mui Mupi F L M F
SUi E i
Ei Ei
  ln(V / C )   ln( DV / C )  
j Ej Ej k
Ek Ek iUjk
The Economics of Development
• Equating development especially mixed use development to a portfolio of
uses subject to risk associated with alternative combination of use
strategies is an extension of the option approach adopted by real estate,
financial and urban economists. See Grenadier (1995,1996), Williams
(1991, 1993), Capozza and Henley (1989) and Geltner and Miller (2001).
• This focus on development as a strategic choice of alternatives also allows
the use of data development from the development valuation reports
employed by practitioners, lenders and others considering proposed
development. This data in turn is a function of the random market and
project specific data available in any given market.
• Use of the development valuation reports for given sites and proposed
projects offers an empirical approach that is similar to the simulation
derived from developing an array of alternative portfolios based on
different weightings of securities and general economic data.
• See data extraction form
Return and Risk Factors and Data Development Matrix
Information
Single Use
Mixed Use
Return Measures:
Rates/Yields
Rents
Values
Costs
Profit
Finance Information:
Mixed Ranges *
Options or Choices of financing
considered
Loan-to-value ratio
Interest rate
Loan term
Payment frequency
Property Use
Prior Use
Single Use (HBU?)
Mix Uses:
Primary
Secondary
Others
-1 .05 0 .05 1
Quality of Associations:
Primary to Area
Primary-secondary
Primary-others
Physical Size
Mix Use Break Down:
% of each use to total:
Physical Size:
Value:
Cost:
Neighbourhood
Land Uses in Area (#)
Quality
Single
Ranges
-1
Rank Range:
-0.5
0 0.5 +1
The Economics of Development
A sample application of the model considering project
yields, land value residuals, and profit as a percentage
of proposed project development valuation are
depicted in the tables that follow:
Statistics and Variable Coefficients
Yield (Total Return) per Project for
Proposed Use Mix
Base/
HBU
Use
Additional R2
Use
α
β Coeff t- Stat
Leverage
β Coeff t- Stat
Log Size (cost)
β Coeff t-Stat
Log BEME
β Coeff t-Stat
Office
Office
Retail
Residential
Hotel
56.6
38.5
56.6
97.8
-0.7900
0.0912
-0.7907
-0.1697
-1.288
1.520
-1.288
-6.505
-0.1133
-0.1331
-0.1133
0.0146
0.0078
-0.0015
0.0078
0.0132
-0.0165 -1.9920
-0.0006 -0.0941
-0.0165 -1.9922
0.0081 1.3507
Residential
Office
Retail
Residential
Hotel
21.7
47.8
16.7
37.3
-0.1614 -0.2608
0.0341
1.1290
0.0220
0.2639
0.0845
0.5520
0.1903
-0.1075
0.1020
0.9945
0.5560
-0.8583
2.9980
0.9070
0.0038 1.1732
0.0018 1.0168
0.0017 0.3547
-0.0037 - 0.3598
-0.0014 0.7726
0.0013
0.2489
-0.0064 -0.4164
-0.0376 -0.6902
Office
Resident
Mix
Office/
Retail
14.9
48.0
0.0542
0.0327
0.0647
-0.1009
0.1975
- 0.6503
-0.00016 - 0.2737
0.0018
0.8082
-0.0105 -0.7982
Off:
-0.000094 -0.1142
Ret:
0.00145 -0.2259
0.4990
0.8884
-0.4033
-0.8260
-0.4033
0.0650
2.1040
0.4432
2.1041
-7.6961
Statistics and Variable Coefficients for Residual
Land Value Difference by Project Proposed Use
Mix
Base/
HBU
Use
Additional
Use
R2
α
β Coeff t-Stat
Leverage
β Coeff t-Stat
Log Size (cost)
β Coefft t-Stat
Log BEME
β Coeff t-Stat
Office
Office
Retail
Resident
Hotel
84.7
94.9
84.7
99.7
-4.28E+09
-1.04E+10
-4.28E+09
6.77E+08
-1.760
-3.520
-1.760
1.240
-1.98E+10
-1.93E+09
-1.98E+10
1.32E+10
2.67E+09
6.05E+08
2.67E+09
-1.23E+09
1.8183
3.6112
1.8183
- 2.5430
-1.51E+09
-2.10E+09
-1.51E+09
-3.07E+09
-4.7210
-6.3740
-4.7210
-24.470
Resident
Office
Retail
Residential
Hotel
81.9
89.4
88.3
99.3
-8.37E+09
-5.78E+09
-5.43E+09
-1.69E+09
-4.212
-2.394
-2.601
-1.589
-1.51E+09 -0.1371
-5.43E+09 -0.5430
-4.51E+09 -0.5291
5.04E+09 0.6980
5.04E+08
3.50E+08
3.23E+09
6709807
4.7680
2.4566
2.6390
0.9681
-28084931
-5.67E+08
-6.91E+08
-2.56E+09
-0.4790
-1.2790
-1.9026
-7.1356
-1.7870
-2.4124
-1.7870
2.8378
Statistics and Variable Coefficients for Residual
Land Value Difference by Mixed Project and
Additional Land Uses
Base/
HBU
Use
Additional R2
Use
α
β Coeff t-Stat
Leverage
β Coeff t-Stat
Log Size (cost)
β Coeff t-Stat
Log BEME
β Coeff t-Stat
Mixed
Office
Retail
Residential
Hotel
-1.65E+10
-7.00E+09
-6.98E+09
-3.72E+10
-2.41E+09
-1.13E+08
-1.03E+10
-3.72E+10
9.05E+09 10.4809
3.96E+08 2.1827
3.91E+08 2.5920
1.21E+09 3.0840
-1.83E+09
-7.91E+08
- 8.39E+08
-7.11E+08
95.5
87.8
88.1
99.8
-9.847
-2.412
-2.567
-3.186
-0.4490
-1.0920
-1.2520
-2.5078
-5.2260
-1.9027
-2.5530
-0.6619
Statistics and Variable Coefficients Profit (Residual as
Percentage of Value) per Project for Proposed Use Mix
Base/
HBU
Use
Addition
al Use
R2
α
β Coeff t-Stat
Leverage
β Coeff t-Stat
Office
Office
Retail
Resident
Hotel
51.0
38.3
51.0
71.7
-0.2557
-0.3307
-0.2557
-0.5251
-1.2890
-0.7663
-1.2891
-0.1724
-0.4851
-0.4305
-0.4851
2.9422
-0.5375
-0.3689
-0.5375
1.1306
0.0269
0.0382
0.0269
0.0093
2.2480
1.2630
2.2480
0.4632
-0.0134
-0.0219
-0.0134
-0.0855
-0.5037
-0.4574
-0.5037
-1.2175
Resident
Office
Retail
Resident
Hotel
09.4
31.3
21.4
76.1
-0.4010 -0.1997
-0.9320 -0.3730
-0.1110 -0.4551
0.3365 1.0390
0.6069
0.2174
0.5890
4.0980
0.5470
0.2100
0.5912
1.8670
0.0076
0.0180
0.1761
-0.0165
0.7128
1.2250
1.2370
- 0.7857
-0.0022
0.0589
0.0447
-0.1812
-0.3732
1.2857
1.0408
-1.6617
MIX
Mix
48.1
0.0670
0.7082
0.9038
1.38E-10
2.3366
0.11438
1.6560
1.6049
Log Size (cost)
β Coeff t-Stat
Log BEME
β Coeff
t-Stat
Conclusions
• Yield analysis from the proposed model is consistent
with the findings of systematic investment portfolios
using the Fama-French model (See Bond, Karoyli,
Sanders 2004)
• This research is broader as applied to development in
three perspectives:
– in allowing the consideration of mixed uses not just the
difference in alternative development scenarios as offered by
option models
– in allowing for the consideration of combination of uses (a
mixed portfolio) as the use mix impact land values measures
and profit as a residual calculation
– in allowing for the incorporation of risk and uncertainty into
traditional valuation and land economic measures of
performance
Conclusions
• The performance of office and retail synergies within a
mixed use development increases all measures (yield,
profit and residual land value) compared to the
dominance of a single use.
• Residential within a mixed use development increases
the complexity of a risk and market model as a
consequence of mixed tenure housing/affordability
housing provision
• The inclusion of hotels in a mixed use development
contribute to a residual land value enhancement over a
single use development
Conclusions
• Mixed use development increases land residual value
relative to risk levels and may offer strategy to hedge
recessionary impact.
• The findings of the model emphasises the benefits of
entrepreneurial developer’s effort of innovation and
strategic management in value creation.