In-transparency of the
Amsterdam office market:
The underlying incentive and
effective rental price
development
A quantitative research into the market dynamics
and spatial segmentation of the Amsterdam office
market over the period 2002-2012
Graduation Presentation
Delft, University of Technology
1st Mentor: Philip Koppels
2nd Mentor: Hilde Remøy
Commissoner: Remon Rooij
Lab coordinator: Theo van der Voordt
Student number: 1382136
Date: 21-05-2014
1 /50
Content
I.
II.
III.
IV.
V.
VI.
Problem introduction
Problem definition, Approach & Methods
Theoretical framework
Empirical research
Conclusions
Reflection on outcomes
Content | I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
2 / 50
I. Problem
introduction
II. Problem definition
III. Theoretical framework
and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on
outcomes
3 / 50
Problem introduction
Explanation ?
2B
2A
Face
rental
price
Incentive
Effective
rental
price
Rental adjustment
equation
(Hendershott,
1994)
1. In-transparency/Asymmetric
Segmentation
/ Sub-market
behaviour
2.
information
availability
Schematically illustrated by Koppels & Keeris (2006)
I – Problem introduction | II – Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
4 / 50
Other consequences of limited/in-transparency
•
1. Self-sustaining system
•
•
3. Research implications
2. Barrier third parties &
Competitive functioning
market
I – Problem introduction | II – Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
5 / 50
I.
Problem introduction
II. Problem definition
III. Theoretical framework
and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on
outcomes
6 / 50
Main research questions
•
1. To what extend does a price index based on face rents, provide an
accurate reflection of the market dynamics in the Amsterdam Office
market over the period 2002 – 2012?
•
2. Do spatial market segments differentiate in market dynamics in the
Amsterdam office market over the period 2002-2012?
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
7 / 50
Approach
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
8 / 50
Approach | Datamining process
Transaction data
Supply data
Supply data
Office Stock database
Own Research Data
Property database
I – Problem introduction | II
– Problem definition | III
BAG Database
Supply data
GIS Data
Vacancy data
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
9 / 50
Approach
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
10 / 50
Approach | Data analyses (1/3)
Study 1
Study 2
Average development
Incentives & effective rents
+ market comparison
Testing relations
between variables by development
Vacancy
Face
rental
price
Incentives
Incentive
Effective
rental
price
Rental prices
Eco. indicators
|Method |
Analyzing development
I – Problem introduction | II
– Problem definition | III
|Method |
(Lagged) Correlation
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
11 / 50
Approach | Data analyses (2/3)
Study 3
Study 4
Rental
Price
Indices
Spatial Segmentation Analysis
|Method |
Average vs. Hedonic
I – Problem introduction | II
– Problem definition | III
CityDistricts
Sub-office
markets
Business
Districts
|Methods | Post-Hoc-Procedure
& Correlation analyses
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
12 / 50
Approach | Data analyses (3/3)
SPSS Statistics (v. 20)
Study 5
Transparency analysis
Difference Face &
Effective rents
Face rental price
Supply
Nominal effective
rental price
Transaction
% Diff.
|Method |
Individual transaction analysis
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
13 / 50
Approach
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
14 / 50
Relevance
•
Societal perspective
•
Academic perspective
•
Real Estate Market
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
15 / 50
I.
Problem introduction
II. Problem definition
III. Theoretical
framework and
conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on
outcomes
16 / 50
Office markets | Cyclical
Vacancy
• Property Cycle: Rental prices, Vacancy, supply/demand vary around a long-term trend
• Vacancy indicator of specific cycle position
I – Problem introduction | II – Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
17 / 50
Office markets | Segmented / sub-market behavior
1.
Segmented structure ignored; inter-related office
markets in London (Stevenson, 2007)
1.
Sub-urban level most appropriate level for analyzing
office market dynamics (Jones, 1995)
2.
Sub-markets different behavior in the short term, but
follow a similar trend in the long run (Mueller, 1995)
3.
Clustering of offices  higher rents - Amsterdam
office market (Brounen en Jennen, 2009)
I – Problem introduction | II – Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
18 / 50
Office markets |Vacancy from theory
Koppels & Keeris (2006):
1.
Vacancy and rents  2 year time-lag
Landlords reluctant to adjust their rental rates when there are fluctuations in the vacancy
rate
2.
Incentives and Vacancy  No time-lag
Incentives used as short-time price adjustments
3.
Corr. Vacancy and Real rents
Stronger when structural components of vacancy are left out of the equation
I – Problem introduction | II – Problem definition |
III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
19 / 50
Rental price indices | Office market
I – Problem introduction | II – Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
20 / 50
I.
Problem introduction
II. Problem definition
III. Theoretical framework
and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on
outcomes
21 / 50
Data overview
Transactions per year
Contract
Year
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Total #
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
Count
378
315
342
269
325
341
288
228
187
157
127
2957
Transactions
LFA < 500 m2
247
213
231
194
239
227
189
167
142
113
109
2071
Transactions
LFA > 500 m2
53
45
43
39
53
67
50
34
30
32
18
464
- Empirical research | V – Conclusions | VI – Reflection
Transactions with a
known LFA
300
258
274
233
292
294
239
201
172
145
127
2535
22 / 50
Study 1 | Average Incentive and
Rental price development &
market comparison
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
23/ 50
Calculating effective rents | DCF method
Year
0
1
2
3
4
Rental income
€ 250.000
€ 255.000
€ 260.100
€ 265.302
€ 270.608
NPV
€ 250.000
€ 481.818
€ 696.777
€ 896.102
€ 1.080.931
Year
0
1
2
3
4
Nominal Contract Rent
including incentives
Rental income NPV
€0
€0
€0
€0
€ 260.100
€ 214.959
€ 265.302
€ 414.284
€ 270.608
€ 599.113
% Incentives
% Incentives
- % Incentives
Nominal Contract Rent
excluding incentives
NPV
check
Nominal Effective Rent
Rental income
€ 138.564
€ 141.335
€ 144.162
€ 147.045
€ 149.986
NPV
€ 138.564
€ 267.051
€ 386.193
€ 496.670
€ 599.113
NPV Check
Year
0
1
2
3
4
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
24 / 50
Incentives in the Amsterdam office market
ECO NOMIC
RECESSION
ECONOMIC
RECOVERY
ICT-CRISIS
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
25 / 50
Contract vs. Effective rental price development
ICT-CRISIS ECONOMIC
RECOVERY
ECONOMIC
RECESSION
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
26 / 50
Price development explained by Market
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
27 / 50
Face rental price comparison
Pearson Correlations
Average difference: 15-23%
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
28 / 50
Study 2 | Rental price indices
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
29 / 50
Rental price indices | Average vs. Hedonic
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
30 / 50
Rental price index | Average vs. Hedonic
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
31 / 50
Rental price index comparison market reports
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
32 / 50
Study 3| Testing relations
between variables
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
33/ 63
Vacancy rates in the Amsterdam office market
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
34 / 50
Vacancy & Rental price
Pearson (Lagged) Correlations
Real Face
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
Real Contract
- Empirical research | V – Conclusions | VI – Reflection
Real Effective
35 / 50
Vacancy & Incentives
Pearson (Lagged) Correlations
0,678*
0,714*
0,523
Percentage incentives
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
36 / 50
Study 4: Spatial
Segmentation analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
37 / 50
Spatial segmentation analysis | Samples
•
Sample 1| Sub-office markets
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
Sample 2| Business Districts
- Empirical research | V – Conclusions | VI – Reflection
38 / 50
Spatial segmentation analysis | Incentives
Sample 1| Sub-office markets
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
Sample 2| Business Districts
- Empirical research | V – Conclusions | VI – Reflection
39 / 50
Spatial Segmentation Analysis | Incentive conclusions
Post-Hoc test & Development analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
Correlation outcomes
- Empirical research | V – Conclusions | VI – Reflection
40 / 50
Spatial segmentation analysis | Effective rental price
Sample 1| Sub-office markets
Sample 2| Business Districts
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
41 / 50
Spatial Segmentation Analysis | Rental price conclusions
Post-Hoc test & Development analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
Correlation outcomes
- Empirical research | V – Conclusions | VI – Reflection
42 / 50
Study 5: “Transparency” analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
43 / 50
Transaction analysis
•
Connected 238 of 454
transactions
•
Deleted: transactions > 106
final accurate transactions
•
Average difference 20%
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV
- Empirical research | V – Conclusions | VI – Reflection
44 / 50
I.
Problem introduction
II. Problem definition
III. Theoretical framework
and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on
outcomes
45 / 50
Conclusions
1. “To what extend does a price index based on face rents, provides an accurate reflection of the market dynamics in the
Amsterdam Office market over the period 2002 – 2012?
Face rental prices – effective rental price (development): diff: 16-23 % (Study 1); diff: 20% (Study 5)
Underlying development; similar correlation | Prime rent development not representative for total market (Study 1)
• Effective rents vs. face rental indices  more cyclical and volatile (Study 2)
• Sig. correlation face rents & vacancy and real eff. rents & vacancy  similar rental adjustment / market dynamics (Study 3)
•
•
 Overall conclusion: index based on (real) effective rental price more accurate reflection of market dynamics
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V
– Conclusions | VI – Reflection
46 / 50
Conclusions
2. “Do spatial market segments differentiate in market dynamics in the Amsterdam office market over the
period 2002-2012?”
-
Incentives :
-
-
Significant different in height
No market segmentation in development; similar correlation in incentive development
Surrounding business districts correlated; Centre / Sloterdijk
Effective rental price:
-
Significant differences in height sub-office and business districts (nominal)
Yes, partial market segmentation in development (Stevenson, 2007)
West, North and South-East correlated
Surrounding business districts in City-district South-East correlated
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V
– Conclusions | VI – Reflection
47 / 50
I.
Problem introduction
II. Problem definition
III. Theoretical framework
and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on
outcomes
48 /50
Reflection on outcomes
•
Overall: Database limitations
–
–
•
–
Higher incentives?
Market comparison; few transactions
•
Study 2: Hedonic price index
–
–
•
Only Accepted
1/5th transactions: 450 ; LFA > 500 m2
Study 1: % Incentives and effective rental price
–
•
•
Low R Square (max. 0,33) in research
Cyclicality and market realistic reflection might
change in more accurate model
Study 3: Vacancy & Rents
•
•
Other vacancy rates; different outcomes
No difference from natural vacancy used
Study 4: Spatial segmentation
•
•
•
Rental adjustment equation: stronger correlation
with real effective rents; possible explanations:
• Small amount of transactions LFA > 500 m2
• Vacancy existing offices instead of entire market
• Current scale level not most appropriate
No diff. above and below 500 m2
Post-Hoc only diff. between some variables
Study 5: Face and effective rental price
-
Only 106 transactions; unsure whether transactions
are well-connected
Only indication of total difference
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions |
VI – Reflection
49 / 50
Questions
& Answers?
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions |
VI – Reflection
50 / 50
Approach | Data Validity
Data reliability check
• Data
analysis
& Reliability check
Main
rejecting
reasons:
–
•
Transaction data Municipal Tax Office
Improbable sale or rental price
• Rental questionaire; incentives, rental prices – to tenant instead of landlord
- forced auction sales, (anti-) squatters, income requirement, sale-leaseback, rental price
•extension,
Only “accepted
” transactions
used
in thislower
research
temporary lease
obligation with
end-date,
rent due rental defects of property,
•short
Goal:
test
its market
conformityin object
rental
contract,
large investments
Family transaction
• 5• (Possible)
step Screening
method
– Step 1: Controlling/Checking input
• Multiple disciplines in rent
– Step 2: Consistency analysis
Step 3:which
Screening
of the
rental value
•– Objects
are out
of use
– Step 4: Reliability check
•– (Only
lot aisparticular
rented) status/condition to the transaction
Step a5:parking
Assigning
I – Problem introduction | II
– Problem definition | III
-Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
51 / 63
Recommendations for further research
Furter research:
• The relation between the (real) effective • Correlation between variables in different
rental price and vacancy in the
moments of the cycle
Amsterdam sub-office markets
Adding non-accepted transactions to the
• Similar research for other market
research, in order to have a larger
segments – retail - incentives and effective database, especially for transactions LFA
rental price development
> 500 m2
•
•
Determinants in an (real) effective rental • Analyzing each transaction individually in
price index compared to a (real) contract order to calculate the ‘true’ incentive
rental price index
percentage in the Amsterdam office
market
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions |
VI – Reflection
52 / 63