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

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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

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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

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• 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

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Approach

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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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

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Approach | Data analyses (1/3)

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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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

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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

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• Societal perspective

• Academic perspective

• Real Estate Market

Relevance

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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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

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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

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Rental price indices | Office market

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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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

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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

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% 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

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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

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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

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Face rental price comparison

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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Rental price indices | Average vs. Hedonic

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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Rental price index | Average vs. Hedonic

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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Rental price index comparison market reports

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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Study 3| Testing relations between variables

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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Vacancy rates in the Amsterdam office market

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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Vacancy & Rental price

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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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

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• 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

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Spatial segmentation analysis | Incentives

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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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

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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

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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

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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

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Transaction analysis

I – Problem introduction | II – Problem definition | III -Theoretical framework | IV - Empirical research | V – Conclusions | VI – Reflection

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• 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

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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

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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

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• 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

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• 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

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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

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