BaseNet · The Finance Group is an international team of 33 researchers that collectively run the...
Transcript of BaseNet · The Finance Group is an international team of 33 researchers that collectively run the...
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Gerjan Vos
ERES and the Development of Real Estate Research in Europe
VOGON21e Studiemiddag24 mei 2007
Structure
� Evolution of ERES� Conference research contributions� Some discussion of the future
ERES goals
� Promoting a permanent network between real estate academics and professionals across Europe
� Advancing the field of real estate research
� Most important activity: The ERES Annual Conference
ERES achievements
� World’s largest successful real estate research conference � Significant improvement in paper quality� Excellent local organisers and Sponsorship � Numerous manuscript prizes and journal linkages� The Spring and Autumn industry research seminars� The ERES Education Seminar� Significant organic growth in the European core� A solvent organisation
Conference participants mainly researchers; academics and practitioners
2006 ERES 13th Annual Conference in Weimar (GER) Conference participants (based on conference fee’s) Category amount % Student 66 19% Companion 29 8% Vogon/Gif 75 21% Participant 182 52% Summary 352 100%
ERES Presidents and ConferencesERES Presidents 1994-2003 ERES conferences
Bert Kruijt 1994-95 Amsterdam 1994 Alastair Adair 1995-96 Stockholm 1995 Hakan Bergram 1996-97 Belfast 1996 Karl-Werner Schulte 1997-98 Berlin 1997 Pe Kohnstamm 1998-99 Maastricht 1998 Olli Olkkonen 1999-00 Athens 1999 Sotiris Tsocalos 2000-01 Bordeaux 2000 Bob Thompson 2001-02 Alicante 2001 Paloma Tultavill 2002-03 Glasgow 2002 Ken Gibb 2003-04 Helsinki 2003 Paola Lunghini 2004-05 Milan 2004 Matthias Thomas 2006-07 Dublin 2005 Weimar 2006 London 2007 Krakow 2008 Stockholm 2009
Research contributions
Finance and Investment
UK
USThe Netherlands
Germany
Australia
SIN
Spain
Finland
Sweden
Other
UK
Germany
The NetherlandsUSAustralia
France
Poland
Spain
Finland
Italy
SIN
Other
UK
Spain
US
France
The NetherlandsAustraliaHong Kong
SIN
Russia
Sweden
Switzerland
Poland
Taiwan
Turkey
Canada
Finland
Germany
Malaysia
Other
Market Analysis
Housing Policy & Economics
UK
The NetherlandsBelarus
Germany
NZ
Spain
Sweden
US
Italy
Poland
Australia
France
Slovenia
Estonia
Russia Other
UK
Spain
GermanyUS
The Netherlands
Hong Kong
Australia
France
Greece
Italy
SIN
Israel
Russia
Sweden
Switzerland
Other
CRE/Use and Occupation
UK
FinlandGermany
Australia
Poland
Spain
US
Buenos Aires
Hong Kong NZ
SIN
Sweden
The Netherlands
Planning, Development and Regeneration
Valuation
Some discussion of the futureStrategic Priorities
� A European Real Estate Research Journal � Better engagement with the membership – communication� Maximising media exposure for the things we do � Improving the visibility of ERES in Southern and Eastern
Europe� A fit for purpose - network of researchers to undertake
Pan-European research proposals � Engagement with EU: Research and Education agendas� Future products: A Bi-annual Policy Seminar? National
Seminars branded by ERES?
Future: moving in the right direction
work still to be done (short term)
� Linkage with other pan-European and national bodies with common areas of interest
� European Real Estate Research Journal� Corporate Governance - transparency� Electronic Membership System� Electronic Communications – Website and newsletter
Summarising:Most Significant Contributions
Successful annual conferenceInternational/European university linksCollaborative research/knowledge transferDevelopment of research areasAcademic-practitioner integration Foster RE in traditional universities
QUESTIONS ?
The 2007 European Real Estate Society Annual Conference
London, June 27-30
www.eres2007.org
SEE YOU ALLAT
Programma
1500 Inleiding
Gerjan Vos
1525 Local Office Returns; A Tale of Five Cities
Dirk Brounen
1550 Quantitative Measures of CRE and its link with organizational performanceRianne Appel-Meulenbroek
1630 Risk and Return of the client’s choice program for housing associations
Bert Kramer
1655 Shareholder Identity and Performance of REITsNils Kok
Welkom in Rotterdam !
RSM Finance RSM Finance
The Finance Group is an international team of 33 researchers that collectively run the School’s largest Master program. The Group has strong links with international partner Universities and participates in several networks with other top research institutions. The focal research areas of the group are (please click topics to find out more):
Asset Management Corporate Finance
Pension Finance Real Estate Finance
Socially Responsible International Markets Investing & Financial Regulation
RSM Finance
Highlights:• News• Events• In the media
Faculty and Staff:• Core Faculty• PhD-students• Staff
Research:• Asset Management• Corporate Finance• Pension Finance• Real Estate Finance• Social Responsible Investing• International Markets
Education:• Bachelor program• Master program• Executive teaching
Contact:• Contacting us• Visiting us
RSM Finance /RSM Finance / Real Estate Finance Real Estate Finance
The RSM Real Estate team currently consists of four researchers: Dirk Brounen (Asssociate Professor of Finance and Real Estate), Maarten Jennen (PhD-student international office markets), Peter Neuteboom (Senior researcher housing markets) and Melissa Porras Prado (PhD-student pension fund investments). Please click below to find more information regarding:
• Our Teaching
• Our Research
• Real Estate Seminars
• Industry Support
• RSM Real Estate Newsletter
Dirk Brounen
Maarten Jennen
PeterNeuteboom
MelissaPorras
RSM Finance
Highlights:• News• Events• In the media
Faculty and Staff:• Core Faculty• PhD-students• Staff
Research:• Asset Management• Corporate Finance• Pension Finance• Real Estate Finance• Social Responsible Investing• International Markets
Education:• Bachelor program• Master program• Executive teaching
Contact:• Contacting us• Visiting us
RSM Erasmus at ERES
Thursday, June 28th
1030 Real Estate Allocation in an ALM Framework, A5 by Melissa and Dirk1400 Demography and Housing Demand, B4 by Peter and Dirk1600 Local Office Rents: A Tale of Five Cities, C6 by Maarten and Dirk
Friday, June 29th
0900 Offices, Stocks, and Office Stocks, D2 by Maarten and Dirk1100 Calendar Effects in Property Shares, E2 by Dirk1330 Continental Factors Revisited, F2 by Dirk
RSM Erasmus at ERES
Thursday, June 28th
1030 Real Estate Allocation in an ALM Framework, by Melissa and Dirk1400 Demography and Housing Demand, by Peter and Dirk16160000 Local Office Rents: A Tale of Five Cities, Local Office Rents: A Tale of Five Cities, by Maarten and Dirkby Maarten and Dirk
Friday, June 29th
0900 Offices, Stocks, and Office Stocks, by Maarten and Dirk1100 Calendar Effects in International Property Shares, by Dirk1330 Continental Factors Revisited, by Dirk
Research questions
Can office rents be modeled internationally?Can office rents be modeled internationally?
Are local rents better modeled with local economics?Are local rents better modeled with local economics?
Literature review– US office market studies
• Rosen (1984) San Francisco office market• Wheaton (1987) national office market cycles• Why study local office markets? (Hanink, 1996)
– European office market studies• Data availability constraints lead to demand side reduced form models• Tradition continued in later work
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Main issues– Data
– Data
– Data
Our Data– Office market data
• Jones Lang LaSalle– Prime office rents– Office stock– Total office market take-up– Vacancy rate
• Period 1990-2006• Amsterdam, Brussels, Frankfurt, London and Madrid
Our Data– Economic data
• Eurostat, Experian and Agora Data • Wide array of available data
– Change service sector employment– Change GDP– Change value added service sector industry
• Period 1990-2006• National level• NUTS III level � Nomenclature of Territorial Units for Statistics
Greater Amsterdam, Bruxelles Capitale, Frankfurt Kreisfreie Stadt, Comunidad de Madrid, Inner London
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Prime rent dynamics
Vacancy rate dynamics
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Vacancy rate dynamics
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Can we understand the changes in office rents?
Results (1)
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Conclusion• Almost 60% of prime office rent dynamics can be explained with two
components based on economic and real estate data
• A model based on European customs works better to model rent dynamics than the U.S. based models
• Use of local economic data in modeling prime office rents does not provide additional insights of dynamic in a study of prime office markets for major cities
Why?• High correlation between local and national economic data for cities in
sample, partly because of weight• Prime office markets house a large number of (inter)national headquarters
and could therefore be less sensitive to the state of the local economy
Over the next four weeks…..
We will study second tier cities that exhibit less correlation withaggregate economy and house more local companies
Eindhoven University of Technology
Corporate Real Estate Management
Quantitative measures of CRE and its
link with organisational performance
-
Rianne Appel-Meulenbroek
Ben Feijts
Eindhoven University of Technology
Contents
� Introduction� CRE aspects in literature� New types of measures� Use for CREM in practice
Eindhoven University of Technology
Problem
Introduction
� CRE � performance user (the 5th resource)� CREM pro-active management� Prove added value
1. Which CRE aspects effect?2. How do they affect?3. How effect measured + managed?
Eindhoven University of Technology
CRE aspects in literature
� Ergonomics, environment psych., FM, logistics, engineering, sustainability, indoor climate
� CRE performance
� 52 aspects:� Structural (building, floor, workplace)� Installation (general, specific)� Location (proximity, accessibility, surroundings)
StaffVisitors
Equipment/processes
Eindhoven University of Technology
CRE aspects in literature (2)
� Why still unclear?� No uniform way of measurement� Interwoven character� Human well-being difficult
Structural:FormLayoutFlexibilityStandardisationEtc.
Installations:PresenceCapacityTechnicalconditionEtc.
Location:ProximityLogisticsNoiseOrientationEtc.
Eindhoven University of Technology
Structural aspects
� Performance?
� 7 CRE strategies1. Increasing the value of assets2. Promoting marketing and sales3. Increasing innovation4. Increasing employee satisfaction5. Increasing productivity6. Increasing flexibility7. Reducing costs
EffectivenessEfficiency
Flexibility
CreativityProductivity
Eindhoven University of Technology
Structural aspects (2)
�
� Specific group of aspects = non-measurablebut influences all 7 added value categories� configuration/layout
Aspect of added value Structural aspects MeasurabilityEmployee satisfaction Aesthetic characteristics (i.e. form, colour) .
Building dimensions/layoutFloor dimensions/layout (distances, workplace location)AccessibilityIndividual workplace dimensions/layoutControl of indoor climate YesControl of auditive privacy YesControl of visual privacy YesEmission of / reservoir for harmful substances YesPhysical characteristics of materials (i.e. reflection, isolation) YesErgonomics of workplace Yes
Eindhoven University of Technology
Structural aspects (3)
� 5 measures configuration/layout� Building dimensions/layout� Floor dimensions / layout� Individual workplace dimensions/layout� Accessibility� Position of facilities
Eindhoven University of Technology
New types of measures
� So far seems logical, but how to design this?� Different community � geography, urban
design� Spatial Network Analysis:
� Isovists� Visual graphs� Justified graphs
Eindhoven University of Technology
Isovists
� “the set of all points visible from a given vantage point in space and with respect to an environment”
� Space as how the user perceives it
Eindhoven University of Technology
Isovists (2)
� Workplacedimension/layout
� Floor dimension/layout
Connectivity
Complexity
Compactness
Average ∆x in isovist
Min ∆x in isovist
Max ∆x in isovist
Skewness of radial distance
Variance of radial distance
Isovist openness
Isovist occlusivity
Isovist area
Isovist perimeter
Eindhoven University of Technology
Visibility graphs
� To deal with an entire plan� Describes floor layout as a whole from the
viewpoint of accessibility
Eindhoven University of Technology
Visibility graphs (2)
� Building dimension/ layout
� Floor dimension/ layout
� Accessibility
� Position of facilities
Mean depth
Clustering coefficient
Eindhoven University of Technology
Justified graphs
� Topological distance
Convex map Justified graph (depths)
Eindhoven University of Technology
Justified graphs (2)
� Problem: no metric distance� Employees: route map (topological) � survey map
(metric)
� Advantage: genericnessbuildings(lawsuit arch. copyright)
Eindhoven University of Technology
Justified graphs (3)
� Building dimension/ layout
� Floor dimension/ layout
Convex map justified graph
Eindhoven University of Technology
Use for CREM in practice
� Measure + manage� Measures must be correlated with
performance� Spatial network software compatible AutoCAD� Standard statistical software (SPSS)� Some added value types are harder to measure� Difficulty in large sample of buildings
� Not for isovists� Benchmark just like financial RE indexes
Eindhoven University of Technology
Use for CREM in practice (2)
� Measure + manage� Several moments in design cycle
� 1st design phases �� suitability design, potential support added value� discussion architect and future users� compare with costs
� POE, recurrence �
� potential improvements� changed focus on added value (org. strategy)
Eindhoven University of Technology
Conclusions
� Measures appear to be interesting
� Many recommendations for further research:� Correlation 7 added value types� Importance configuration – other CRE aspects� Importance ‘structural’ – Location, installations� Direct versus indirect effect of CRE� Etc.
Eindhoven University of Technology
Questions
Risico en rendement van het Te Woon concept bij woningcorporaties
ORTEC bvRozenburglaan 99727 DL GroningenNederlandTelefoon 050 750 1700Fax 050 750 1740Internet www.ortec.nlE-mail [email protected]
Bert Kramer
Basisprincipes Te Woon
De klant bepaalt voor wat voor koop- of huurvorm hij of zij kiest. Aangeboden varianten verschillen per corporatie.Einddoel veel corporaties: (nagenoeg) gehele bezit in Te Woon
aanbieden. Invoering echter (zeer) gefaseerd.Veelgebruikte koop- en huurvormen:
� Huur: huren met jaarlijkse huurverhoging en maximale flexibiliteit; � Huurvast: waarbij de huur voor 5 of 10 jaar vaststaat; � Koopgarant: kopen met korting, een terugkoopgarantie en delen in de
waardeontwikkeling; � Koopcomfort: kopen tegen marktwaarde, waarbij de corporatie het
eerste recht van koop heeft.
Te Woon leidt in verwachting tot grotere verkoopvolumes.
Potentiële risicofactoren
Koopbereidheid bij invoeringOntwikkelingen op de woningmarkt gedurende de exploitatie
(terugkooprisico)Kosten bij beëindiging van een complex
Koopbereidheid bij invoering
Woonbron (Rotterdam, Spijkenisse, Delft, Dordrecht):� Nu 12.500 van de 50.000 woningen in Te Woon� Slechts ongeveer 7% kiest voor Koopgarant� Koopcomfort (0,5%) en Huurvast (0,5%) nauwelijks gekozen� Yeung (UvT / ORTEC, 2007): keuze Koopgarant – Huur afh. van: � Inkomen;� Huur;� Taxatiewaarde;� Aantal kamers.
Aramis (Roosendaal):� Pilot 52 woningen� 19% kiest voor Huurvast (10 woningen)� 15% kiest voor Koopgarant (8 woningen)
Koopbereidheid bij invoering
10,9%4,8%11%Huurvast
11%25%10,8%Koopgarant
1,4%1,2%1,4%Koopcomfort
Totaal Scherpenzeel (84 VHE)Ede (4209 VHE) Ervaring Woonstede
Conclusies:Ervaring varieert sterk per corporatieNauwelijks gekozen voor Koopcomfort.Keuze Huurvast varieert sterk per corporatie (afh. van voorlichting /
publicieit?).Vooral belangstelling voor grotere woningen (eengezinswoningen).Inkomen van huurder is belangrijke bepalende factor, maar is i.h.a.
onbekend.
Base Case deltaWonen
3%Huurvast
85%Huur
11%Koopgarant
1%Koopcomfort
TotaalBase case deltaWonen
Ook nieuwbouw projecten worden aangeboden in Te Woon.9.300 van de 14.300 woningen worden aangeboden, gespreid over 10 jaar.Geen rekening gehouden met kosten bij beëindiging complex met deel
Koopgarant of Koopcomfort.Mutatiegraad Koopgarant en Koopcomfort woningen 5% (obv eerdere studie
naar in 1998-2005 verkochte en teruggekochte MVE woningen).Mutatiegraad Koopgarant en Koopcomfort woningen onafhankelijk van
economisch klimaat (obv eerdere studie naar verhuisbeslissingen)
Gerealiseerde verkoopvolumes
134111221100Terugkoop Koopcomfort
319675661433034131140Terugkoop Koopgarant
76106799105956Koopcomfort
24267171481671453424Koopgarant Nieuwbouw
103472108991081151311141129679Koopgarant Bestaand bezit
Totaal2016201520142013201220112010200920082007
Gevoeligheidsanalyse
Mutatiegraad Koopgarant en Koopcomfort woningen 7% (gemiddelde mutatiegraad koopsector) -> meer terugkoop met daaraan verbonden terugkoop- en doorverkoopkosten.
Invoering Te Woon ineens: 9.300 woningen in 2008 Te Woonaangeboden.
Invoering ineens met dalende markt: als 2, waarbij de lokalehuizenmarkt instort a.g.v. overaanbod in 2008. Verkoopprijzendalen daardoor met 10% in 2008.
Terugkoop bij einde exploitatie. Aannames cf. Woonbron:� Vanaf 5 jaar voor einde exploitatie geen (door)verkoop meer.� Terugkoop tegen 79% van de marktprijs.� Extra levensduur 10 jaar.
Effect alternatieve varianten Te Woon
Verloop solvabiliteit
15
20
25
30
35
40
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
jaar
Sol
vabi
litei
t (%
bal
anst
otaa
l)
Base Case Te Woon
Alleen reguliere verkoop
Mutatiegraad koopgarant 7%
Invoering ineens
Invoering ineens met dalendemarkt
Terugkoop einde exploitatie
tijdnuverleden toekomst
Sc 1
Sc 2
Sc 3
Verloop solvabiliteit is onzeker
Riskdrivers (scenario’s):inflatie, rente, OG stijging, ...
Beleid: huurbeleidinvesteringsbeleid e.d.
Methode risicoanalyse
Trend / gemiddelde component : Visie corporatie, CPB, DNB, ...
Stochastische component : Op basis van op historische data
1. Trend / Beleidsmatig gem. 2. Stochastiek / Verbanden
3. Scenarios
1. scenario’s
2. doelstelling
3. horizon
4. risicomaatstaf
Hoe worden risico’s gemeten
Solvabiliteitsrisico’s Te Woon
Reguliere verkoop Te Woon
“Crash” scenario: grote verliezen op terug- en doorverkoop van MGE woningen (“dalende markt”) gecombineerd met hoge beheerskosten.
Resultaten gevoeligheidsanalyse
Terugkoop einde exploitatie Koopgarant 7% mutatie
Invoer ineens/dalende marktInvoering ineens
Samenvatting risicoanalyse
6%2%7%Kans solvabiliteit < 0%
-2.0%8,4%-1,7%95% zekere solvabiliteit
25,3%31,8%24,9%Verwachte solvabiliteit
Mutatiegraad 7%Te WoonReguliere verkoop
Score in 2016
5%5%11%Kans solvabiliteit < 0%
2,6%5,1%-7,0%95% zekere solvabiliteit
27,4%30,6%23,7%Verwachte solvabiliteit
Invoering ineens + dalende markt
Invoering ineens
Terugkoop einde expl.
Score in 2016
Conclusies
Invoering Te Woon leidt tot een verdubbeling van de verkoopvolumes ten opzichte van de meerjarenbegrotingsvariant.
Aannames rondom reactie klanten bepalen in hoge mate het resultaat. Deze aannames zijn bovendien niet een-op-een over te nemen van ervaringen van andere corporaties.
Het te voeren beleid bij einde exploitatie van een complex bepaalt in hoge mate het risicoprofiel van invoering van Te Woon.
Corporate Governance and PerformanceThe REIT Effect
Nils KokRob Bauer
Piet Eichholtz
Universiteit Maastricht
Corporate governance & vastgoedFBI-structuur reduceert free cash flow-probleem
• Vastgoedinvesteringen steeds meer indirect
• Agency probleem (Manne 1965)
• Oplossing: corporate governance
• Maar vastgoedfondsen (FBIs)…
…betalen 90% free cash flow uit…hebben beperkte investeringsmogelijkheden
• Hoe verandert dit de rol van corporate governance?
LiteratuurPositief effect corporate governance op performance
• Positief effect corporate governance op beurs rendementen en operationele prestaties (Gompers, Ishii en Metrick JFQA2003), maar…
…deze relatie is sterker in een zwakker institutionele omgeving(Durnev en Kim JF2005; Klapper en Love JCF2004
• REITs opereren in sterk gereguleerde setting
• Geen REIT-literatuur zoals Gompers et al., enkel studies naar relatietussen individuele governance mechanismen en prestaties
Bijdrage aan literatuurUnieke database, analyse op verschillende samples
• Governance literatuur betreffende REITs beperkt � van belang door toenemend aantal markten met REIT-structuur
• Unieke corporate governance database (Institutional Shareholder Services), bevat 61 objectieve ratings van alle governance mechanismen
• Onderzoek naar volledige sample (>5000 bedrijven), controle sample (bedrijven met hoge PPE/Assets ratio) en REIT sample (>220 Amerikaanse vastgoedfondsen)
• Verschillende prestatiemetingen: beurswaardering, operationeleprestaties en rendementen
Data & methodologie
• Tijdsperiode: 2003 – 2005
• Data:– Complete dataset: 11589 observaties (unbalanced)– REIT dataset: 509 observaties– Controle sample: 542 observaties– 26 industrieën
• Performance measures– Tobin’s Q– ROE, ROA, FFO/share, NPM en sales growth– Alpha (Carhart 4-factor model)
• Median-least square regressies (correctie outliers)– Controle variabelen– Industrie-correcties
Beschrijvende statistiekenRetail & office REITs scoren goed, diversified REITs matig
Top-5 CGQ67.661.554.153.652.7
Bottom-546.442.441.038.035.6
2003 2004 2005Governance index CGQ CGQ CGQ
54.6 64.5 61.529.3 26.6 27.0
Subindex means3.1 3.5 3.43.4 3.5 3.42.7 3.4 3.53.5 3.8 3.3
216 210 228
Panel A: Average CGQ Scores
Panel B. Real Estate
UtilitiesReal EstatePharmaceuticals & BiotechnologyMaterialsFood & Staples Retailing
EnergyTelecommunication ServicesFood Beverage & TobaccoMediaHousehold & Personal Products
MeanStandard deviation
Number of firms
Board Compensation Takeover Defenses Audit
Results full sampleSignificant relationship between governance & performance
Gov Index 0.001(8.37)
Audit Index 0.005(2.59)
Compensation Index 0.005(3.13)
Takeover Index 0.003(1.12)
Board Index 0.013(6.83)
Year Fixed EffectsIndustry ControlledMedian AdjustednPseudo-R2
Gov Index 0.027 0.006 0.003 0.000 -0.004(9.76) (4.84) (6.71) (11.23) (-1.00)
Year Fixed EffectsIndustry ControlledMedian AdjustednPseudo-R2
0.65%115890.71%0.64%0.65%
11589 11589 11589 11589
115891.79%
115891.18%
115894.87%
115890.06%
Panel A : Industry-Adjusted Q
11589
YYY
1.01%
YYY
YYY
YYY
YYY
Panel B: Industry-Adjusted Operating Performance
YYY
YY
YYY
YYY
Salesgrowth
YYY
0.57%
ROE ROA FFO/Share NPM
Y
Results REIT sampleOnly structure compensation schemes influences firm value
Gov Index 0.000(0.59)
Audit Index -0.010(-0.89)
Compensation Index 0.025(2.02) ***
Takeover Index 0.005(0.31)
Board Index -0.004(-0.32)
Year Fixed EffectsMedian AdjustednPseudo-R2
Gov Index -0.019 -0.002 0.003 0.000 -0.007(-1.24) (-0.48) (1.25) (-0.44) (-0.28)
Year Fixed EffectsMedian AdjustednPseudo-R2
Panel B: Operating Performance - REITs
Panel A: Tobin's Q - REITs
5.31%
YY
Y
0.37%0.22%11.69%509
0.59%509
1.94%509 509 509
509 509 509 5095.38% 5.40% 5.78% 5.32%
YY
YY
YY
YY
YY
YY
YYN
509
ROE ROA FFO/Share NPM Salesgrowth
YY
Robustness checkResults high PPE/assets sample similar to full sample
• We document relationship between governance & performance forfull sample, whereas no results are found for the REIT sample, but…
…results might be due to relatively high share of fixed assets in REITs
• Control sample: matched sample of companies with high corporatereal estate ratio (CRER)
Gov Index 0.003 0.038 0.013 0.013 0.000 0.008(2.93) *** (3.06) *** (2.25) ** (4.23) *** (4.03) *** (0.38)
Year Fixed EffectsIndustry ControlledMedian AdjustednPseudo-R2 0.24%
542 5420.84%
5424.10%
5423.73%
5426.78%
5426.45%
Y
YYYY
YYYY
YYY
YYY
YY
Y
Tobin's Q and Operating Performance: Control Sample
SalesgrowthROE ROA FFO/Share NPMTobin's Q
Equity performanceGood governance vs bad governance portfolios
• Ex-post recognition of governance
• Good Governance Portfolio vs. Bad Governance Portfolio
• 30% of market cap ranked highest and lowest
• Value-weighted approach
• Carhart 4-factor model:
ittititiftmtiiftit MOMHMLSMBRRRR εββββα ++++−+=− 3210 )(
Equity performanceGood governance does not outperform bad governance
Panel A. 30% value weighted portfolio - Full periodRm-Rft Adj. R2
Good governance -0.479 0.842 *** 0.90(-0.25) (21.39)
Bad governance 3.206 * 0.893 *** 0.93(1.89) (25.69)
Difference portfolio -3.685 -0.051 0.15(-1.43) (-0.96)
Panel B. 30% value weighted portfolio - Period 2000 - 2003Good governance 1.809 0.854 *** 0.88
(0.67) (11.68)Bad governance 7.767 *** 0.820 *** 0.91
(3.47) (13.59)Difference portfolio -5.958 * 0.034 0.08
(-1.67) (0.36)
Panel C. 30% value weighted portfolio - Period 2003-2006Good governance -3.563 0.850 *** 0.90
(-1.14) (16.46)Bad governance -2.979 0.943 *** 0.95
(-1.18) (22.73)Difference portfolio -0.584 -0.093 0.15
(-0.14) (-1.32)
ConclusiesIs hier sprake van een REIT effect?
Goede governance leidt niet hogere rendementen (investeerders zijn niet verrast)…
…dit kan verklaart worden door het ontbreken van een relatie tussen governance en fundamentele prestaties
Onze resultaten contrasteren de complete sample, de controle sample en bevindingen in de finance literatuur…
…en zouden kunnen duiden op een ‘REIT effect’
Maar:• Recente sample periode• Endogeniteits probleem• Relatief kleine sample
Vragen/opmerkingen?