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Graduation PresentationDelft, University of Technology1st Mentor: Philip Koppels2nd Mentor: Hilde RemøyCommissoner: Remon RooijLab coordinator: Theo van der VoordtStudent number: 1382136Date: 21-05-2014
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
1 /50
I. Problem introduction
II. Problem definition, Approach & Methods
III. Theoretical framework
IV. Empirical research
V. Conclusions
VI. Reflection on outcomes
Content
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
Rental adjustment equation (Hendershott, 1994)Schematically illustrated by Koppels & Keeris (2006)
Face rental price
Incentive
Effective rental price
2. In-transparency/Asymmetric information availability
1. Segmentation / Sub-market behaviour
2A
2B
Problem introduction
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
4 / 50
Explanation ?
• 1. Self-sustaining system
Other consequences of limited/in-transparency
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
5 / 50
• 3. Research implications
• 2. Barrier third parties & Competitive functioning market
I. Problem introduction
II. Problem
definition
III.Theoretical framework and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on outcomes 6 / 50
• 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?
Main research questions
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
Supply dataSupply dataTransaction data
Property database
Vacancy data
Supply data
Approach | Datamining process
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
9 / 50
GIS Data
BAG Database
Office Stock database
Own Research Data
Approach
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
10 / 50
Approach | Data analyses (1/3)
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
11 / 50
Study 1 Study 2Average developmentIncentives & effective rents+ market comparison
Face rental price
Incentive
Effective rental price
Testing relations between variables - by development
|Method | Analyzing development
|Method | (Lagged) Correlation
VacancyVacancy
IncentivesIncentives
Rental pricesRental prices
Eco. indicators
Eco. indicators
Approach | Data analyses (2/3)
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
12 / 50
Study 3 Study 4
RentalPrice Indices
Spatial Segmentation Analysis
|Method | Average vs. Hedonic
|Methods | Post-Hoc-Procedure & Correlation analyses
City-Distric
ts
City-Distric
ts
Sub-office markets
Sub-office markets
Business DistrictsBusiness Districts
Approach | Data analyses (3/3)
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
13 / 50
SPSS Statistics (v. 20) SPSS Statistics (v. 20)
Study 5
Transparency analysisDifference Face & Effective rents
|Method | Individual transaction analysis
Face rental price
Supply
Face rental price
Supply
Nominal effective
rental priceTransaction
Nominal effective
rental priceTransaction
% Diff.% Diff.
Approach
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
14 / 50
• Societal perspective
• Academic perspective
• Real Estate Market
Relevance
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
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
17 / 50
Vacancy
• Property Cycle: Rental prices, Vacancy, supply/demand vary around a long-term trend
• Vacancy indicator of specific cycle position
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)
Office markets | Segmented / sub-market behavior
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
18 / 50
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-lagIncentives used as short-time price adjustments
3. Corr. Vacancy and Real rents Stronger when structural components of vacancy are left out of the equation
Office markets |Vacancy from theory
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
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
22 / 50
Contract Year
Count Transactions LFA < 500 m2
Transactions LFA > 500 m2
Transactions with a known LFA
2002 378 247 53 300 2003 315 213 45 258 2004 342 231 43 274 2005 269 194 39 233 2006 325 239 53 292 2007 341 227 67 294 2008 288 189 50 239 2009 228 167 34 201 2010 187 142 30 172 2011 157 113 32 145 2012 127 109 18 127 Total # 2957 2071 464 2535
Transactions per year
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
Year Rental income NPV0 € 250.000 € 250.0001 € 255.000 € 481.8182 € 260.100 € 696.7773 € 265.302 € 896.1024 € 270.608 € 1.080.931
Nominal Contract Rent excluding incentives
Year Rental income NPV0 € 0 € 01 € 0 € 02 € 260.100 € 214.9593 € 265.302 € 414.2844 € 270.608 € 599.113
Nominal Contract Rentincluding incentives
Year Rental income NPV0 € 138.564 € 138.5641 € 141.335 € 267.0512 € 144.162 € 386.1933 € 147.045 € 496.6704 € 149.986 € 599.113
Nominal Effective Rent
Calculating effective rents | DCF method
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
24 / 50
% Incentives
NPVcheck
%
Incen
tives-
%
Incen
tive
s
NP
V C
heck
Incentives in the Amsterdam office market
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
25 / 50
ICT-CRISIS
ECONOMICRECOVERY
ECO NOMIC RECESSION
Contract vs. Effective rental price development
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
26 / 50
ECONOMICRECOVERY
ICT-CRISIS
ECONOMIC RECESSION
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
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
28 / 50
Pearson Correlations
Average difference: 15-23%
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
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
35 / 50
Pearson (Lagged) Correlations
Real Face Real Contract Real Effective
Vacancy & Incentives
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
36 / 50
0,523
0,678* 0,714*
Pearson (Lagged) Correlations
Percentage incentives
Study 4: Spatial Segmentation analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
37 / 50
• Sample 1| Sub-office markets Sample 2| Business Districts
Spatial segmentation analysis | Samples
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
38 / 50
Spatial segmentation analysis | Incentives
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
39 / 50
Sample 1| Sub-office markets Sample 2| Business Districts
Spatial Segmentation Analysis | Incentive conclusions
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
40 / 50
Post-Hoc test & Development analysis Correlation outcomes
Spatial segmentation analysis | Effective rental price
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
41 / 50
Sample 1| Sub-office markets Sample 2| Business Districts
Spatial Segmentation Analysis | Rental price conclusions
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
42 / 50
Post-Hoc test & Development analysis Correlation outcomes
Study 5: “Transparency” analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
43 / 50
Transaction analysis
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
44 / 50
• Connected 238 of 454 transactions
• Deleted: transactions > 106 final accurate transactions
• Average difference 20%
I. Problem introduction
II. Problem
definition
III.Theoretical framework and conclusions
IV. Empirical research
V. Conclusions
VI. Reflection on outcomes 45 / 50
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
Conclusions
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
46 / 50
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
Conclusions
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
• Overall: Database limitations– Only Accepted – 1/5th transactions: 450 ; LFA > 500 m2
• Study 1: % Incentives and effective rental price– Higher incentives?– Market comparison; few transactions
• Study 2: Hedonic price index– 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
Reflection on outcomes
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
49 / 50
• 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
• Study 4: Spatial segmentation• 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
Questions & Answers?
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
50 / 50
• Data analysis & Reliability check– Transaction data Municipal Tax Office
• Rental questionaire; incentives, rental prices – to tenant instead of landlord
• Only “accepted” transactions used in this research• Goal: test its market conformity
• 5 step Screening method– Step 1: Controlling/Checking input – Step 2: Consistency analysis– Step 3: Screening of the rental value– Step 4: Reliability check– Step 5: Assigning a particular status/condition to the transaction
Main rejecting reasons:• Improbable sale or rental price
- forced auction sales, (anti-) squatters, income requirement, sale-leaseback, rental price extension, temporary lease obligation with end-date, lower rent due rental defects of property, short rental contract, large investments in object
• (Possible) Family transaction
• Multiple disciplines in rent
• Objects which are out of use
• (Only a parking lot is rented)
Approach | Data Validity
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
51 / 63
Data reliability checkData reliability check
Recommendations for further research
I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection
52 / 63