extreme weather events and property values
TRANSCRIPT
Extreme weather events and property values
A ULI Europe Policy & Practice Committee Report
Assessing new investment frameworks for the decades ahead
Author:Professor Sven Bienert
Visiting Fellow, ULI Europe
The mission of the Urban Land Institute is to provide leadership in the responsible use of land and in creating and sustaining thriving
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About the Author
SvenBienertisprofessorofsustainablerealestateatthe
UniversityofRegensburgandULIEurope’sVisitingFellow
onsustainability.Since2013,healsohasbeenmanaging
directoroftheIRE|BSInternationalRealEstateBusiness
SchoolattheUniversityofRegensburg,Europe´slargest
centre for real estate education.
Prof.Bienertgraduatedwithdegreesinrealestateeconomicsandbusiness
administrationandwrotehisPhDthesisonthe“ImpactofBaselIIonRealEstate
ProjectFinancing”.Hehasbeenconductingresearchinthefieldofsustainability
since2005,initiatingvariousprojectssuchasImmoValue,theIBI-RealEstate
BenchmarkingInstitute,andImmoRisk.
SinceApril2010Prof.BienerthasbeenheadoftheIRE|BSCompetenceCenterof
SustainableRealEstateattheUniversityofRegensburg,wherehisrecentresearch
hasfocusedon“greenpricing”andtheimpactofextremeweathereventson
propertyvalues,amongothertopics.Hisresearchhasreceivedseveralnational
andinternationalprizes,andhispapershavebeenpublishedinnumerousleading
internationalrealestatejournals.Prof.Bienertisalsotheauthorandeditorofseveral
realestatebooks.
Prof.Bienertcombinesacademicknowledgewithpracticalprivatesectorexperience,
having held management positions in a number of leading real estate consulting
companies.In2010hebecamefounderandmanagingdirectorofProbusRealEstate
GmbHinVienna,whichmanagesa€2.1billioncommercialrealestateportfolio
acrossCentralandEasternEuropeandSoutheasternEurope.
Credits
AuthorProfessor Sven Bienert
UniversityofRegensburg
VisitingFellow,ULIEurope
ProjectStaffJoe Montgomery
ChiefExecutiveOfficer
ULIEurope
Gesine Kippenberg
ProjectManager
James A. Mulligan
SeniorEditor
Andrew Lawrence
EditorialSupport
Createinn Design
Graphic Design
About ULI
2
©2014bytheUrbanLandInstitute.
PrintedintheUnitedKingdom.Allrightsreserved.Nopartofthisreportmaybereproducedinanyformorby
anymeans,electronicormechanical,includingphotocopyingandrecording,orbyanyinformationstorageand
retrievalsystem,withoutwrittenpermissionofthepublisher.
ISBN:978-0-87420-338-7
Recommendedbibliographiclisting:
Bienert,Sven.ExtremeWeatherEventsandPropertyValues:AssessingNewInvestmentFrameworksforthe
DecadesAhead.London:UrbanLandInstitute,2014.
About ULI 2
About the author 2
Credits 2
Introduction 4
Executive summary 4
Why climate matters 6
Extreme weather events and their effects on property values 8
Calculation methodology for expected losses from extreme weather events 13
Outlook on the future development of extreme weather events 18
Case study: Increased insurance premiums/annual expected loss 22
Conclusion 24
Appendix: Overview of the present state of research 25
Literature and footnotes 26
Contents
3
Extreme Weather Events and Property Values
Executive summary The escalating threat of extreme weather events• Realestatevaluesarebeingincreasinglythreatenedbyextremeweather
events,suchasstorms,hail,flooding,droughts,tropicalcyclones,
and landslides.
• Theseeventshavefargreaterrelevanceforrealestateinvestorsthanthe
morefrequentlydiscussedeffectsofcreepingclimatechange,suchas
rising mean temperatures.
• Thenumberofextremeweathereventshasdoubledgloballysincethe
1980stoanaverageofover800eventsperyearduringthepastdecade.
• Theoccurrenceofsucheventsisthereforeescalatingandislikelyto
continuetodosountiltheendofthiscentury(andbeyond),asclimate
change becomes more severe.
Their effects on real estate markets and values• Newfinancialuncertaintiescausedbyextremeweatherareaffectingthe
highestandbestuseofrealestatethroughouttheworld.Asrealestate
valuesaccountforabout3.5timestheGDPindevelopedcountries,even
relativelysmallchangesinvalueswillhaveanenormousfinancialimpact
on economies.
• Monetarylossesrelatedtorealestateandinfrastructureandresulting
fromsevereweathereventshavetripledgloballyduringthepastdecade,
withdirectlossesrecordedbyreinsurancecompaniesamountingto
US$150billion(€109.5billion)peryear.Inseverelyaffectedregions,
losseshavereachedupto8percentofGDP.
• Estimatesbasedonthelatestclimatedata,aswellaslossratios
calculatedbythenewly-developedtoolintroducedinthisreport,indicate
thatexpectedmonetarylossesforbuildingsarelikelytodoubleinsome
placesinthenearfuture,affectingbuildinginsurancepremiumsand
totaloccupancycostsasaresult.
Introduction
Today, the real estate industry is increasingly
having to address the causes of climate change, of
which it is a main contributor, through an evolving
range of requirements that include regulatory
controls on CO2 emissions, environmental and
sustainability strategies; and the ‘greening’ of
property investment portfolios and developments.
However, to a large degree, a major consequence
of climate change - extreme weather events - has
yet to be seriously addressed by the industry.
Many real estate investors and associated players
are simply not aware that these events - the
escalation in their occurrence and magnitude of
which is all too evident - pose a rising, compelling
and more immediate threat to property value, and
are therefore overlooking the related risks within
their investment decision-making.
In this report, the threat of extreme weather events
and their impact on real estate and property
value is analysed, and a new tool is introduced to
show how expected losses can be calculated. In
also giving an outlook on the future development
of events, this paper highlights why weather
risks should be considered as a key emerging
driver to future investment strategies. It looks to
stimulate debate by presenting new valuation-
related methodologies and by making clear
recommendations for market participants that
range from the future-proofing of portfolios to the
re-thinking of asset allocation.
Extreme weather events and their effects on property valuesAssessing new investment frameworks for the decades ahead
4
• Moresignificantly,itmightbecomeimpossibletoinsureagainstsevere
fundamentalchangesresultingfromextremeweather-andfrom
intensive events in particular.
• Totallossesfromextremeweathereventsarebeingseriously
underestimatedastrackeddataonlyaccountsfordirectlossesandnot
consequentiallosses(e.g.,areductionintourism)orindirectlosses(e.g.,
reducedturnoverandrent).Thedepreciationofnaturalcapitalisalso
being ignored.
• Agreaterfrequencyofextremeweathereventswillleadtomorepeople
leavingaffectedregions,therebyaffectingpropertyvaluesat
bothendsofthemigratorypath.
An inadequately prepared real estate market• Thefinancialuncertaintiescausedbyextremeweatherarebeing
considerablyunderestimatedbyrealestateinvestors.Untilrecently,
theirportfolioallocationshaverarelytakenintoaccountthescienceof
climate change.
• Thisisprobablyduetotheabsenceofcomprehensiveriskmodels/
tools;alackofready-to-processdatathatcanbeusedinrealestate
forecastingmodels;and,tosomeextent,continueduncertaintyonthe
forecastsforgreenhousegasemissions,andthereforeclimatechange.
• Realestatemarketparticipantsarealsotendingtounderestimaterisks
fromweathereventsthathaveaveryhighpotentialforacutemonetary
lossesbuthaveaverylowprobabilityofoccurring.
Calculating expected losses from extreme weather events • Therisksfromeventsareeithernotbeingintegratedintorealestate
investmentsorvaluations,orareonlybeingaddressedindirectlyby
adjustinginputparameterssuchasrents,yields,orcostsonamore
qualitativebasis.
• Fromarealestateindustryperspective,theriskfromnaturalhazards
shouldbeunderstoodasonlybeingone-sided:downsidewithno
potential upside.
• Thecalculationofannualexpectedlossesasameasureofriskfor
propertyvaluesisderivedfromthehazardoftherespectiveextreme
weatherevent,anempirically-validateddamagefunction(vulnerability),
and a value.
• Throughtheuseofdatafromclimatemodelsandinsurancecompanies
(concerninghistoricaldamages),aswellasfromcost-basedvaluations,
far-reachingconclusionscanbemaderegardingthefuturedevelopment
ofpropertyvaluesinaspecificsituation.
Recommendations for real estate investors• Regardsustainabilityinitiativesasmorethanjustacostdriver,andmake
more intensive efforts to ensure that assets and the respective allocation
oftheseassetsare“future-proofed”.Fulfillingtoday’sregulatory
requirementsisjustthestartingpointonamuchlongerandbroader
routetoasuccessfulsustainabilitystrategy.
• Ensureahigherawarenessofrisksrelatedtoclimatechangesothat,
corporation-wide,theyaretreatedasastrategicissue.
• Evaluatetheannualexpectedlossforpropertiesorportfolioscausedby
futureclimatechangeandextremeweatherevents.
• Bealerttothebroaderindirectandconsequentialeffectsofsevere
weather on real estate.
• Rethinkassetallocationintermsofregions,assetsubclasses,and
micro-locations.Inaddition,re-evaluatecoreandotherassetsin
locationsthatmaycurrentlybetreatedasa“safehaven”
for investments.
• Increasetheadaptationofexistingbuildingstockiftheoutcomeofan
assetanalysisis“hold”.Somepropertiescanbemademoreresilient
throughrelativelyminorretrofits(suchasimprovementstofacades,
roofs,siteinfrastructure,windowsanddoors,connectionsbetween
buildingparts,etc.).
• Developproperrisk-managementtoolsthatfocusonclimatechange,
andintegratethemintoexistingcontrollingfunctionsandprocesses.
• Improveawarenessofpotentialnewregulationofgreenhousegas
emissions as part of stricter climate policies.
• Considermitigatingpotentialsevereweatherimpactsthroughuseof
weatherderivativesorportfoliodiversification.
• Thinkonaregionalorevenproperty-specificlevelbecausenatural
disasters are best treated with regional climate data and models.
• Actnowtoreduceriskfromclimateextremeswithmeasuresthatmight
rangefromincrementalstepstotransformationalchanges.Extreme
weathereventsarealreadyimpactingfinancialreturnsintherealestate
industryandinthefuturewillcontinuetodosoonafargreaterscale.
5
Extreme Weather Events and Property Values
Today, man-made climate change is widely
accepted to be the cause of rising global
temperatures, the melting of the Arctic ice cover,
changing weather patterns and related impacts to
the natural environment and ecosystems.
Despite global political efforts, levels of harmful
emissions are increasing without effective restraint
and, if this remains the case, the acceleration in
climate change is likely to continue unabated.
The looming economic consequences of climate
change will have a significant and growing impact
on the real estate industry, which makes it ever
more important for market participants across
most real estate disciplines to be proactive in
mitigating and adapting to its effects.
In2011and2012thehighest-everaveragetemperatureswererecordedin
Europeandtheworldfortwoconsecutiveyears.1
Proof of considerable global warming: record high temperatures are being reported.
Theconsequencesofclimatechange,andthechangesintheglobal
averagetemperatureassociatedwithit,arefar-reaching.TheArcticice
coverhasdecreasedfromover8millionsquarekilometresin1980tounder
5millionsquarekilometresin2012–2013.2Andthewaterreleasedbythe
meltingiceisoneofthemainreasonswhysealevelshaverisenby20
centimetressince1880.3
Leadingscientistsagreethatmostclimatechangehasbeencausedby
man(anthropogenicclimatechange).4Despiteworldwideefforts,global
greenhousegasemissions(measuredincarbondioxideequivalents)
rose3percentin2012toabout32gigatonsperyear,thehighestlevel
ever measured.5
Arctic Sea Ice Minimum Comparison 1984 - 2012
Source:NASAEarthObservatory
In2013,theconcentrationofgreenhousegasesintheatmosphere
exceededwhatisconsideredthecriticallevelof400partspermillion
(ppm),comparedwith280ppmduringthepre-industrialera.6Againstthis
background,andevenwiththegreatesteffortsbeingmade,itisalmost
impossibleforcontinuingpoliticalattemptstolimitglobalwarmingto2°C
to succeed.7
Atmospheric Concentration of CO2 (EEA) 1750-2010
Source:EEAEurope
Why climate matters
1 MüRe,2013,p.40ff/IPCC,2013,p.4.2 Petersonetal.,2013,p.20/IPCC,2013,p.5.3 Rahmstorf,2007,p.1ff/IPCC,2013,p.6.4 MüRe,2008,p.6/Latif,2009,p.153/Petersonetal.,2013,p.IV/IPCC,2013,p.8f,p.12f./Bouwer,2011,p.39f.
5 MüRe,2013,p.40.6 NationalOceanicandAtmosphericAdministration(NOAA),10.Mai2013/IPCC,2013,p.7.7 Note:“DohaClimateGateway”negotiationswithmandatoryregulationsfrom2020onstillrefertothe2degreeCelsius goalattheDohaclimateconferenceinDecember2012.
6
Climatechangeisalreadycausingmassivechangesinecosystemsandwill
havefurtherseriousconsequencesasglobaltemperaturescontinuetorise.
Thiswillimpactmanyareasofsocietyandtheeconomy,includinghealth,
foodproduction,andurbandevelopment.Measuresmustthereforebe
takentosimultaneouslylimitthedriversofclimatechangewhileadapting
to its effects in all areas of life.
Thispaperconcentratesonarealestate-basedeconomicapproachto
globalwarmingandpursuesthefollowingquestions:
• Whatarethefinancialimplicationsforrealestateassetsofanincreasing
numberofextremeweatherevents?
• Howmightthefrequencyofextremeweathereventschange?
• Whyshouldtherealestateindustryintensivelyaddressclimate
changenow?
Climate change massively reduces real estate related income potential in the form of ground rent.
Realestateisboundbylocation,andrealestatevaluesarealwaysbased
on the highest and best possible use of a location. The protection of
real estate against the hazards of natural disaster and the loss of use is
thereforeclearlyvital-whetheritissafeguardingtheincome-generation
ofagriculturalandforestland(andthequalityoflife),theinvestmentand
occupancycredentialsofcommercialandresidentialbuildingsorthe
durabilityofinfrastructurefacilities.
Aninitial,purelyqualitativeanalysisthatfocusesonthevariousdrivers
forrealestatemarketvalue-assuggestedbythevaluationtechnique
“comparisonapproach”-showsthatmanyfeaturesofasiterelevantfor
valuationaredirectlylinkedtoenvironmentalconditions,andaretherefore
alsoexposedtotherisksofclimatechange.Thesefeaturesinclude:
• Macro-andmicro-locations-climaticconditions,especiallyillumination,
wind,emissions(noise,smoke,dust),andrainfall;and
• Soilconditions-surfaceformation,naturalcover,bearingcapacity,
groundwaterconditions,mudslideareas,andexposuretorisks(flooding,
avalanches,storms,hurricanes,etc.).
Andsomemorerecentimpactsofclimatechangeonenvironmental
conditionsareonlygraduallyemerging.Forexample,NorthernRussia’s
regions are seeing an increasing impact from the thawing of the
permafrost,withthecoolertemperaturespreventingtheairfromabsorbing
thewatervapourgenerated;asaresult,theamountofmoistureinthesoil
isconstantlyincreasing,formingsmalllakes.Thisishavingasubstantial
impactonregionalecosystems,aswellasbuildingsandinfrastructure,
which in some places no longer stand on solid ground.
Thelossofthepotentialuseoftherealestateautomaticallyleadstolost
value,whichhasnegativeconsequencesforaneconomyasawhole.In
developedeconomies,thevalueofpropertyamountstoanaverageof3.5
timesacountry’sGDP.8Thus,evensmallchangesinvaluecanleadtolarge
monetarydamages.Moreover,inrealestatevaluation,presentvalueis
regularlyconsideredinassessingfuturepotentialbenefits.Therefore,even
relativelymoderatereductionsinvaluecanleadtobiglossesinannual
expectedreturns.
Due to the wider economic significance of property values, even relatively small drops in value will constitute massive economic losses.
Thisandotherimpactsofclimatechangearelikelytocontinueto
predominateandresultinmassiveadjustmentsintherealestate
industryuntilanewbalanceisstruck.Ontheotherhand,afewinthe
realestateindustrycouldactuallybenefitfromclimatechange.For
instance,agriculturewillbefeasibleinregionspreviouslyconsideredtoo
cold,allowing,forexample,vineyardstomovefarthernorth;likewise,
warmertemperaturesatmorenorthernlatitudeswillraisepropertyprices
as climate refugees migrate and encourage more tourists to visit high
mountain areas.
The profitability of real estate will be increasingly influenced by climate protection regulations.
However,itwouldbemisleadingtoportraytherealestateindustryonlyin
termsofitsvulnerabilitytoclimatechangebecause,throughdevelopment,
itisoneoftheprimarycontributorstotheproblem;withbuildings
accountingfor30to40percentofallenergyuse,theindustryisoneof
themainsourcesofCO2 emissions.9Asaresult,amultitudeofpolitical
initiativestoreduceemissionsarecurrentlyaimedattheconstructionand
realestatesectors-andtheintroductionofinitiativeswillcontinue.10 The
industrywillalsobeaffectedbymeasuresrequiredtoadapttoclimate
changeandrelatedlegalframeworks.Thoseimpactsarenotaddressedin
this report.
Critically,duetoitsvulnerability,11therealestateindustrymusturgently
studythedriversanddynamicsofclimatechangesoitcanadapt
proactivelytothechangesorcontributetotheirmitigation.Itisachallenge
thataffectsandmustbeaddressedbyanumberofsubdisciplineswithin
theindustry,includingrealestatevaluation,riskmanagement,investment,
andprojectdevelopment/construction.
8 Brandes,2013,p.9:EstimatedValueofInsuredCoastalPropertiesamountintheUnitedStatestoUS$27.000billionin2012.9 WBCSD,2009,p.6.10 Bosteelsetal.,2013,p.6.11 Guyattetal.,2011,p.15:Realestateisverysensitivetoclimateimpacts./Leurigetal.,2013,pp.5,7
7
Extreme Weather Events and Property Values
Extreme weather events caused by climate change
- including storms, hail, flooding, heatwaves, and
forest fires - often lead to severe damage and must
be differentiated from long-term change, such as
rising mean temperatures.
The annual average number of extreme weather
events has more than doubled globally since 1980.
The total global damage caused by extreme
weather - mainly to property and infrastructure -
is rising dramatically and now exceeds US$150
billion (€109.5 billion) per year. Furthermore, these
losses, which are those registered by reinsurance
companies, by no means constitute all losses
related to real estate.
For example: first estimates of forests lost to more
frequent fires in Russia and the United States
top €600 billion in present values; and there is a
corresponding impact on the income-generating
potential of relevant property. Similar calculations
could be made for other extreme weather events,
regions, and property types.
The real estate industry has tended to be reactive
and is only now taking its first steps towards
preparing for foreseeable climate changes. To date,
awareness has not been strong, partly because few
quantitative studies on real estate in the context of
extreme weather events have been undertaken.
Theimpactofclimatechangeonpropertyanditsvalueiscomplex.In
thispaper’sintroductionweaddressedtheimpactsoflong-termclimate
change,suchasrisingmeantemperatures,howeverthisdoesnotinclude
themoreimmediateeffectsofextremeweatherevents,whichcanleadto
significantlossesinaveryshortperiod.12Climatechangeisalsoaltering
thefrequency,intensity,spatialimpact,duration,andtimingofevents;
andinsomeinstancestheshiftsareunprecedented.Inparticular,extreme
weatherevents-naturaldisastersthatincludestorms,hail,flooding,
heatwaves,droughtsandforestfires–arehavingasignificanteffecton
thosesectorsthatarecloselylinkedtoclimate,suchasinfrastructure,
water,agriculture,forestry,andtourism,aswellasrealestateingeneral
(seefigure1).13
Thisstudytakesanin-depthlookatextremeweathereventsandtheir
impactonpropertyvalues.Forthemarkettheseevents–whichonly
representadownsiderisk-canresultinrealestateinvestments14:
• Beingsubjecttopricerisesduetoincreasedinsurancepremiums
oralteredconstructionmethods-knownasadaptationcosts-or
deterioratingreturnsoncapital;or
• Losingvalueduetolimitedusability(wherethehighestandbestuse
maynolongerbefeasible);or
• Beingsubjecttoexpensivedamagesduetouninsuredrisks,andhence
deteriorating returns.
Therefore,therealestateindustryisinevitablyexposedtothepotentialloss
ofpropertyreturnsinlocationsthatarevulnerabletoextremeweather.15
Hurricane Katrina property damage
Source:FreeImages,PalmerCook
Extreme weather events and their effects on property values
12 WorldBank,2013,p.94:Reducedpropertyvalues.13 Guyattetal.,2011,p.61/Cruzetal.,2007,p.492:Effectsontourismmightbemassive./Lamond,2009.14 ULI,2013,p.14ff:Recommendation16:Accuratelypriceclimateriskintopropertyvalueandinsurance.15 Guyattetal.,2011,p.58.
8
Figure 1. Effects of climate change on property values
Source:IREBSUniversityofRegensburg
According to reinsurance statistics, total losses from extreme weather events already exceed €109.5 billion per year.
Theeconomicimplicationsofextremeweatherbecomeevidentifone
considersthatgloballossescausedbyweather-relatednaturaldisasters
in2011and2012exceededUS$150billion(€109.5billion)inbothyears,
rankingthemamongthefivemostcostlyyearssince1980.16However,
fromabroaderperspective,thesetotallosses(whicharefrequentlycited
inreinsurancestatistics)are,infact,farbelowtheactualfinancial
losses suffered.
Toelaborate,financiallossescanbebrokendownintofourcategories:
• Directlossesinclude17alltypesoftangibleassets(privatedwellings,and
agricultural,commercialandindustrialbuildingsandfacilities);
infrastructure(e.g.,transportfacilitiessuchasroads,bridges,andports;
energyandwatersupplylines;andtelecommunicationsequipment);and
publicfacilities(e.g.,hospitalsandschools).
• Indirectlossesmayincludehighertransportcosts,lossofjobs,and
lossofincome(bothrentandrevenuelostduetobusiness
interruption).
• Consequentiallosses-or“secondarycosts”-arisethrough
repercussions such as declining tourist numbers or lower direct
investments,whichreduceeconomicactivity,andthuslowerGDP.
• Lossesrelatedtonaturalcapitalincludedamagetoecosystemsand
thedepreciationofnaturalresources(adverseecologicalimpacts).
Climate AspectCommercial and
Residential Real EstateForestry Agriculture Infrastructure
Rise in temperature
Reduced ground rent (lower potential revenue, in the case of regional population changes; also, increased need for cooling, and thus higher operating costs)
Reduced ground rent (in the case of increase in forest fires, pest infestation, extinction of species)
Reduced ground rent (in the case of increasing drought, pest infestation)
Increased wear on installations; unstable ground
Water scarcity Decline in attractiveness of a region/decline in ground rent; higher costs for water supply and treatment
Reduced revenues from forestry/increased danger of forest fires
Reduced harvests; increased costs for irrigation
Decline in bearing capacity of soil
Rising sea level Reduced settlement area in coastal regions
Reduced agricultural land area/loss of potential revenues
Danger to port facilities
Increase in extreme weather events
1. Direct loss (e.g., hail damage to buildings)
2. Indirect loss (e.g., through gaps in production or rent after hurricanes)
3. Consequential loss (e.g., declining number of tourists in flood areas, rising insurance premiums)
1. Direct loss
2. Consequential loss
3. Depreciation of natural capital (permanent damage to ecosystems, extinction of species)
1. Direct loss
2. Consequential loss
3. Depreciation of natural capital
1. Direct loss
2. Indirect loss (infrastructure damages due to extremes in temperature, precipitation/ flooding/overload of urban drainage systems/storm surges, which can lead to damage to roads, rail, airports, and ports; electricity transmission infrastructure is also vulnerable)
Increased regulation
Higher construction costs and running costs; higher costs, particularly in the case of carbon taxation
Higher construction costs and running costs
Increased adaptation costs due to climate change
Higher adaptation costs to protect properties and to make buildings energy - and resource efficient
Higher adaptation costs Higher adaptation costs Higher adaptation costs
16 MüRe,2013,p.53.17 Kronetal.,2012,p.542:Directlossesareimmediatelyvisibleandcountable(lossofhomes,householdproperty,schools, vehicles,machinery,livestock,etc.).
9
Extreme Weather Events and Property Values
However,itisonlydirectlossesthatareeffectivelytrackedinloss
estimates–alltheothercategories,whichalsoincludeadaptationcosts
incurredforprotectingbuildingsfromextremeweatherevents,andthe
monetisationofpersonalinjuryandthedamagetohistoricstructures
and cultural heritage18,arenotincludedoradequatelyincorporatedinto
estimates.19Yetalltheseaspectsareofmajorimportanceforrealestate
marketsastheycanbedirectlylinkedtoincomeandvalues.
Truedamagecostsarethereforemuchhigherthanestimates,which
highlightstheneedfortherealestateindustrytowidenitsperspective
beyondjustdirectlosses.
Official statistics dramatically underestimate real estate-related damage.
InthecaseofforestfiresintheUnitedStates,forexample,thedamage
tothenaturalcapital-i.e.,treesandotherplants-isnotincorporatedin
damagedatacollectedbyreinsurancecompanies.However,intermsofthe
long-termincome-generatingpotentialfromforestryandtheattractiveness
oftheaffectedarea,thisdamageisfarmorerelevantthanthelossofany
buildingstofire.
Examiningthisparticularexampleinmoredetail,rainfallintheUnited
Statesin2012wasmuchlowerthantheannualaveragesfor1961to1990,
andtheyearwasalsomarkedbyalarge-scaleheatwaveandaperiod
ofseveredrought.Thisresultedinasmuchasa40percentreductionin
average agricultural production20andaconsequentdeclineinthegross
incomegeneratedbytheaffectedplotsthroughthereductionofground
rent.Inwoodedareas,thedroughtwasaccompaniedbyforestfiresthat
destroyed3.7millionhectares,thethirdhighestfiguresincerecordsbegan.
Heat wave map via NASA June 17/24, 2012
Source:NASA
Ananalysisoflong-termU.S.averagesinthepre-andpost-climatechange
situationrevealsinterestingdetails.Acomparisonof1970-1986and1987-
2003showsthatduringthelatterperiod,whichwasseverelyaffectedby
climatechange,fourtimesasmanyforestfiresoccurredandsixtimes
asmuchforestlandfellvictimtoflames,andtheforestfireseasonlasted
onaverage50percentlonger.Itcanbeestimatedthatover330million
cubicmetresofwoodwasdestroyedin2012,intheprocesslowering
bothresourceproductivityandlandvalues.Thisisirrespectiveofdamage
toforestecosystems,thedestructionofbuildingsandinfrastructure,
agriculturallosses,orthelong-termdeclineintheattractivenessofthe
affected regions.
Forest fires near Chalkidiki, Greece 2006
Source:Shutterstock/VerveridisVasilis
Atanaveragepriceof€85percubicmetre,thiscorrespondstomorethan
€28billionburnedandthereforewastedresources,andthisisdataforjust
oneyear,onecountry,andthetreeinventoryofforests.
Comparedwiththehistoricalaverageforthepre-climatechangeperiod,
this represents an increased loss of about €23billionperannumdueto
thesharpriseinforestlandlosttofire.Translatedintermsofanincome
stream,anddiscountedataninterestrateof5.0percent,thiswould
represent a loss of forestland of over €460billioninpresentvalues21 due
toforestfiresintheUnitedStates.
Heatcombinedwitharidityisalsoanincreasingprobleminotherpartsof
theworld.Russia’ssouthernandwesternregionslikewiseexperienced
extremeforestfiresin2012,toppingrecordhighsthathadbeensetas
recentlyas2010,atrendwhichoverthepast10yearshasseentheareain
Russiaaffectedbyforestfiresgrowfrom750,000tomorethan1.75million
hectares per annum.22 If the same valuation method is applied as for the
UnitedStates,Russianforestfireshaveincurredalossinpresentvalueof
more than €150billion.
21 Note:Theassumptionofaperpetuityservesonlytoillustratetheextentofthesituationanddoesnotclaimtobe scientificallyconclusiveastothefacts.22 MüRe,2010,p.33,p.37.
18 IPCC,2013,p.270.19 Kronetal.,2012,p.535f,p.542f.20 MüRe,2013,p.42
10
More frequent fires have destroyed over €600 billion in present values from forests in the United States and Russia alone - and have reduced land values accordingly.
Inadifferent“extreme”,Thailandexperienceditsworstfloodingin50
yearsin2011,causingestimatedeconomiclossesof€40billion.Most
ofthelossescamefrompropertydamageandthelossofgroundrent,
withcommercialandindustrialareas,roads,otherinfrastructureand
agriculturebeingparticularlyhardhit.Twomillionpeoplewereforcedfrom
theirhomes,1millionhousesweredestroyedorseverelydamaged,10
millionfarmanimalswereevacuatedorkilled,and1.6millionhectaresof
agriculturalland-10percentofthecountry’stotal-waslargelydestroyed.
About25percentofthetotalharvestfortheyear-inparticularrice-waslost.
Thailand floods 2011
Source:WikimediaCommons
Theseexamplesindicatethehugevolumesoflong-termincome-generating
realestatepotentialbeingdestroyedbyextremeweatherevents.Yetno
structuredrecordofthisdamageexists,norisitincorporatedininsurance
statistics.Whatismore,theaffectedregionswillbehitbyhumanmigration
flows23 which will further reduce residential and commercial real estate values.
The number of extreme weather events is increasing considerably. A total of over 800 events occur on a 10-year average, compared with only 400 in the 1980s.
Countlessotherexamplesexistoftheincreasingfrequencyofextreme
weatherevents-floodsaftertorrentialrainsinChina,thehighest
floodwatersinNewYorkCityin100years,cyclonesanddroughtin
Australia,andfloodinginlargeareasofGermany,Austria,andtheir
neighbours-allevidenceofongoingclimatechangeleadingtoaverifiably
significantincreaseinextremeweather.24Globally,840weather-related
naturaldisastersoccurredin201225,andstudiesbyMunichREhaveshown
thatthenumberofdisastershasmorethandoubledgloballybetween1980
and2012(seefigure2).26
23 Cruzetal.,2007,p.488.24 IPCC,2012,p.7:Inregardtothechangeswhichhaveoccurredsofar,theIPCChasdeterminedthat“atleastmedium confidencehasbeenstatedforanoveralldecreaseinthenumberofcolddaysandnightsandanoverallincreaseinthe numberofwarmdaysandnightsattheglobalscale,lengthornumberofwarmspellsorheatwaveshasincreased, PolewardshiftinthemainNorthernandSouthernHemisphereextratropicalstormtracks,therehasbeenanincreasein extremecoastalhighwaterrelatedtoincreasesinmeansealevel.”25 GDV,2011,p.1/MüRe,2013,p.52/Mechleretal.,2010,p.611ff.26 MüRe,2013,p.3ff.
Geophysical events
(Earthquake,tsunami,volcaniceruption)
Meterological events
(Storm)
Hydrological events
(Flood,massmovement)
Climatological events
(Extremetemperature,drought,forestfire)
Figure 2 : Development of the number of natural disasters throughout the world from 1980 to 2012
Source:MünchenerRückversicherungs-Gesellschaft,GeoRisksResearch,NatCatSERVICE-AsatJanuary2013
11
Extreme Weather Events and Property Values
Flooding in Greater Bangkok 2011
Source:WikimediaCommons
Asimilartrendisevidentinrespecttothetotaldamagesresultingfrom
theseevents,whichhasmorethantripledfrom1980to2012,from
US$50billiontooverUS$150billionperyear(€36.5billionto€109.5
billion).27Furthermore,a2012reportbytheIntergovernmentalPanelon
ClimateChange(IPCC)concludedthatinareasmostaffectedbyextreme
weather,averagecostsamountedtoupto8percentofGDP.28From
amacroeconomicviewpointregardingrealestate,thequestionofthe
proportion of losses insured29islargelysecondarybecausepropertyprices
will increase regardless of rising premiums or even as a result of the claim
itself.Whatdoesrequireexplanation,however,iswhylossesinproperty
value are higher in percentage than the increase in severe weather events.
Increased settlement of high-risk areas, combined with socio-economic growth, partly accounts for the higher real estate losses.
Therearetwomainreasons.Firstly,thelossescausedbyclimatechange
arebeingexacerbatedbyman-madechangesintheaffectedareas,with
increasedlossesarisingfromdensersettlement,increasedurbanisation
ofhigh-riskareas30(e.g.,theFloridacoast),higherconstructioncostsand
quality,and,insomecases,theincreaseduseofmaterialssusceptible
todamage,suchasfacadesusingthermalprotectionmaterialsinareas
prevalent to hailstorms.31Secondly,thelossesarenotadjustedinrelation
toglobalsocio-economicgrowth;initialstudiesadjustingforthisshow
“only”alinearincreaseintotallossesof€1.7billionperyearoverthepast
30years.32
Flood damage
Source:FreeImages,NurettinKaya
There is a lack of quantitative research regarding extreme weather events and the real estate industry.
Theamountofliteratureonsocio-economicdevelopmentinconnection
withextremeweathereventsisgrowingrapidly.33However,relatively
fewquantitativeresearchresultsexist34 that cover the interface between
naturalhazardsandrealestate,duemainlytothefactthatonlyinthepast
fewyearshavethenumberofeventsandvolumeofdamageincreased
significantly.TheIPCCfindsthat“[o]nlyafewmodelshaveaimedat
representingextremesinarisk-basedframeworkinordertoassess
the potential impacts of events and their probabilities using a stochastic
approach,whichisdesirablegiventhefactthatextremeeventsarenon-
normallydistributedandthetailsofthedistributionmatter.”35Otherauthors
have also stressed the challenges related to this factor.36
Thefollowingsectiongoesintogreaterdetailinthiscontextbydescribing
aninnovativecontributiontoresearchimplementedaspartoftheImmoRisk
project.37Specifically,itpresentsanapproachtocalculateannual
expectedlosses(AELs)duetoextremeweatherevents.Thisapproach,
basedonfuture-orientedclimatemodels,canbeusedtodeterminean
approximateincreaseinexpectedlosses.Thisallowsconclusionstobe
derivedregardingthefutureperformanceofaproperty(orportfolio)and,
ifnecessary,adjustmentoftheallocationofassetsintermsofselectionof
regions,propertyuses,etc.
27 MüRe,2013,p.52.28 IPCC,2012,p.270/Guyattetal.,2011,p.14:CostofphysicalclimatechangeimpactcouldreachUS$180billionperyear by2030(€131.4billionpa)29 Mills,2005,p.1040f/Mills,2012,p.1424f/Mechleretal.,2010,p.611ff.30 Howelletal.,2013,p.46:Greaterconcentrationofpropertiesinriskzones.31 Naumannetal.,2009,p.228/MüRe,2008,p.4.32 MüRe,2013,p.58.
33 IPCC,2012,p.265.34 Note:SeetheAppendixforanextendedoverviewofthecurrentstateofresearch.35 IPCC,2012,p.266.36 Wilby,2007,p.42/Guyattetal.,2011,p.1ff:Traditionalassetallocationdoesnotaccountforclimatechange.Thereisa smallamountofresearchwhichfocusesontheinvestmentimplicationsofclimatechange./Brandes,2013,p.12ff:The riseofmodelingandfutureriskscenarios.37 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
12
Calculation methodology for expected losses from extreme weather events
Fortherealestateindustry,questionshavearisenbasedontherisksof
climatechangeingeneralandextremeweathereventsspecifically.These
include:
• Dynamicsregardingpropertyvalues:Whatimpactsonthevaluesof
existinginvestmentscanbeexpectedinthefuture?
• Investmentanddivestmentdecisions:Whichregionswillbepositivelyor
negativelyaffectedbycontinuingclimatechange?Whatconclusionscan
bedrawnforfutureinvestmentdecisions?
• Propertytypes/sectors:Arecertaintypesofpropertyusemoreaffected
byextremeweatherthanothers?
• Portfoliomanagement:Howcaninvestmentsbeallocatedtoachieve
adiversifiedpropertyportfolio,therebyprotectingagainstpossible
increasedclimate-relatedrisks?Whatisthebestallocationof
investmenttorealestatewithinabroadermulti-assetportfoliowhen
climaterisksaretakenintoaccount?
• Externalities:Whatcantherealestateindustrycontributetowards
internalisingnegativeexternalities,38andtowhatextentcanirreversible
damagesbeavoided?
Fromaninvestor’sviewpoint,thepotentialimpactofextremeweatheron
propertyvaluesisprobablythemostfundamentalconcern,soitwillbe
addressedherefirst.(Thefuturedevelopmentofextremeweatherevents
willbediscussedinthefollowingchapter,whichwillhelptobuildagreater
understandingoflikelychanges.39)
Toassessthepossibleimpactonpropertyvalues,thisstudyintroduces
arisk-basedresearchapproach,usingabottom-upmethodologythat
quantifiestheriskintheformofexpectedlossesthroughobservationofa
singleproperty.
The risks from extreme weather events are either
not being integrated into real estate investments or
valuations, or are only being addressed indirectly by
adjusting input parameters such as rents, yields, or
costs on a more qualitative basis. Likewise, despite
its relevance, climate data is also being excluded.
From a real estate industry perspective, the risk
from natural hazards should be understood as being
only one-sided: downside with no potential upside.
In general, the risk is measured by the likelihood of
the occurrence of a specific monetary loss within a
certain time frame.
The calculation of annual expected losses (AELs)
through extreme weather events as a measure
of risk for property values is derived from (1) the
hazard of the respective extreme weather event,
(2) an empirically validated damage function
(vulnerability), and (3) a value. The modeling
is extremely complex, and the requirements
concerning the quality and quantity of data are very
high.
Through the use of data from climate models
and insurance companies (concerning historical
damages), as well as from cost-based valuations,
far-reaching conclusions can be made regarding the
future development of property values in a specific
situation.
The core task in the risk analysis of climate
impacts is to derive probability distributions for the
occurrence of specific extreme weather events, and
to determine the damage functions concerning the
extent to which the respective property is affected.
38 Note:Anexternaleffectis,forexample,airpollutioncausedbyenergyconsumptionthataffectsathirdparty(e.g.,the societyingeneral)thatwasnotresponsibleforthatemission.Theexternalityis“uncompensated”forthepolluterbecause thecostwillbebornebyothersunlesstheexternalityis“internalised”throughregulation(e.g.,taxes).
39 ULI,2013,p.17:Marketvaluedriveslanduse.
13
Extreme Weather Events and Property Values
Performance with regard to potential capital losses is only the first issue when natural hazards are considered in real estate decision making.
Todetermineadeclineinvaluethatmayonlyoccurinthefuture,it
isessentialtoexploretheinteractionamongparameters,structural
characteristics,andotherfactorsthataffectthepropertyinquestionin
the form of causal chains.40Riskswithalowprobabilityofoccurrenceand
highlosspotentialtendtobeunderestimatedinmostanalyses41and,in
practice,investmentdecisionsareusuallymadeonthebasisofhistorical
dataandcorrespondingtimeseries(e.g.,rents,vacancies,etc.).42 This
observationhasgreatrelevanceforassessingextremeweatherevents
expectedinthefuture,andfortheimplicationsofthoseevents,because
thereisstrongevidencethattherelevanceoflow-probabilityrisksisstill
underestimated-notleastbyprofessionalmarketparticipants,suchas
propertyinsurersandinvestors(Lansch,2006).
Investment decisions today are often made solely on the basis of historical data series.
Naturalhazardsarepartoftheperformanceriskwhichtakeseffectonthe
supplyside43,andinmostmarketstheseriskscanbecoveredbynatural
hazard insurance. The resulting annual insurance premiums are included
intheoperatingcostsoftheproperty,andcangenerallybechargedtothe
tenantasnon-allocableoperatingcosts.Despitethefactthattheycanbe
apportioned,thesecostsneverthelessdohaveanimpactonvalueinthe
mediumtolongtermfromtheowner’sperspective,becauserisingutilitybills,
asawiderexample,mayincreasethetotaloccupancycostsintheviewofthe
tenantandultimatelylimitaproperty’spotentialtogenerateahighernetrent.
Againstthisbackdrop,fromtheperspectiveoftherealestateindustry,
extremeweathereventsconstitutethedownsideriskofamonetary
loss occurring in the future.44ThisExpectedLoss(EL)isderivedfroma
combinationoftheprobabilityofacertainextremeweathereventoccurring
(tobeunderstoodinthesenseofenvironmentalscienceasthereciprocal
ofacertainreturnperiod),andtheamountofdamageitwouldcauseifit
didoccur.Thisfundamentalrelationshipisillustratedinfigure3.
Thus,thecoretasksinvolvedintheriskassessment 45 of climate change
impactsintherealestateindustryare(1)derivingprobabilitydistributions
fortheoccurrenceofcertainextremeweatherevents(hazard),and,
similarly,(2)determiningreliabledamagefunctions(vulnerability 46)
regardingtheimpactonaspecificproperty.Thesetwoareasrepresent
thekeyelementsoftheriskmodel.47Inregardtotheimpact,themodel
generallyworkswithrelativeshares,inpercentage(2a,relativelosses)ofa
totalvalue(2b,absolutelosses).Therefore,(3)itisalsoimportanttoderive
cost-basedpropertyvalues(exposure).Thesearedeterminedaccording
totheinsurablevalue,48 in compliance with the procedures in regard to
insuranceofproperty,usingthereplacement-costapproach.49
The hazard, vulnerability, and cost-based value elements determine the expected loss.
Hence,forapropertyg,atalocationr,atapointintimet,theriskcan
bedescribedbythefollowingfunctionalrelationshipamonghazard,
vulnerability,and(cost-based)value:
Risk (r,g,t) = Hazard (r,t) * Vulnerability (g,t) * Cost Value (g)
40 IPCC,2013,p.10:climatefeedbacks.41 Osbaldistonetal.,2002,p.46/Ozdemir,2012,p.1ff.42 Wilby,2007,p.42:“Aboveall,thereisanurgentneedtotranslateawarenessofclimatechangeimpactsintotangible adaptationmeasuresatalllevelsofgovernance.”/Guyattetal.,2011,p.1:Standardapproachesrelyheavilyonhistorical dataanddonottacklefundamentalshifts.43 Lechelt,2001,p.28.44 Büchele,2006,p.485/Kaplan,Garrick,1997,p.93.
45 UNDHA,1992,p.64:“Riskareexpectedlosses(of...propertydamaged...)duetoaparticularhazardforagivenarea andreferenceperiod.Basedonmathematicalcalculations,riskistheproductofhazardandvulnerability.”45 ULI,2013,p.17:Marketvaluedriveslanduse.46 Thywissen,2006,p.36/UNDHA,1992,p.84:“Degreeofloss(from0%to100%)resultingfromapotentiallydamaging phenomenon.”47 Heneka,2006,p.722/Büchele,2006,p.493.48 InsurablevalueaccordingtoInternationalValuationStandards(IVS):Thevalueofapropertyprovidedbydefinitions containedinaninsurancecontractorpolicy.49 EuropeanValuationStandards(EVS),2012..
ClimateChange
+--
Risk Assessmentfor the exposure
Annual expected loss
Location Specific
Hazard - function
Property Specific
Vulnerability
Cost value
Extreme WeatherEvents
• Climatology• Meteorology• Hydrology• Insurance Data• Real Estate Data
Figure 3: Real estate risk assessment approach for extreme weather events
Source:IRE|BS,UniversityofRegensburgwithreferencetoBienert/Hirsch/Braun,2013,p.1ff:ImmoRiskToolforBMVBS.
14
HazardfunctionsoriginatefromtheresultsofGlobalClimateModels
(GCMs),whichgenerallyhavenodirectrelationtotherealestateindustry.
Climatemodelsareabletoforecastfuturechangesintheprobabilityof
occurrence,theintensity,andthetypicaldurationofextremeweather
events-forexample,ofaparticularwindspeedbeingreachedorvolume
of hail falling.50Inordertogetalocation-specifichazardfunction,GCMs
mustbedownscaledtoaregionallevel(aRegionalClimateModelor
RCM),sometimestakingintoaccounttheveryspecificcharacteristics
of the surroundings.51Thealreadyapparentincreaseintheprobabilityof
occurrenceofextremeweathereventscanbederivedvisuallywiththehelp
offigure4,whichshowsrealclimatedataandpredictions.
Figure 4: Sample wind hazard function for a location in Northwest Germany, present vs. future
Source:IRE|BS,UniversityofRegensburgwithreferencetoBienert/Hirsch/Braun,
2013,p.1ff:ImmoRiskToolforBMVBS/seealsoHofherretal.,2010,p.105ff.
Inthecontextofvulnerabilityanalyses,functionalrelationshipsbetween
theintensityoftheextremeweathereventandtheresultingmonetary
lossesmustbeobtainedforeveryevent.Thelossfunctionthendescribes
therelationshipthatisdetermined,basedontheanalysisofalargenumber
of historical losses. Loss functions thus represent the connection between
theintensityofaneventandtheresultinglossinthevalueobserved
(vulnerabilityfunction).52Forexample,experienceindicatesthatacertain
windspeedcanmeanthat30percentofaparticulartypeofbuildingcould
bedestroyed.Thisisgenerallydeterminedbyempirically-basedevidence
fromhistoricalinsurancedataorbyanexpert’sopinion.53Oncerelative
lossesareestablished,monetarylossesonlyariseincombinationwiththe
valueofaspecificproperty.
Figure 5: Loss function which correlates intensity with storm damage.
Source:IRE|BS,UniversityofRegensburgwithreferencetoHeneka,2006,p.724
/seealsoUnanwaetal.,2000,p.146.
Thedeterminationoftheexpectedlossresultingfromtheinteraction
betweenindividualelementsisillustratedbyfigure6.
Figure 6: Integrative calculation of the risk of natural hazards in the case of uncertainty on all levels of observation.
Source:Bienert/Hirsch/Braun,2013,p.1ff:ImmoRiskToolforBMVBSwith
referencetowww.cedim.deandHenekaetal.
Closerinspectionrevealsthatan(expected)totallossmustalwaysbe
relatedtoonespecifictimeinterval(e.g.,oneyear)andincludeallpossible
riskscenariosofaparticularextremeweatherphenomenon(e.g.,wind)
-thatis,itmustbeweightedaccordingtoitsindividualprobabilityof
occurrence.
50 IPCC,2013,p.10,14f/Khanetal.,2009:Stormriskfunctions/Leckebuschetal.,2007,p.165ff/Mohretal.,2011/ Waldvogeletal.,1978,p.1680ff.51 Fleischbeinetal.,2006,p.79f/Linkeetal.,2010,p.1ff/Orlowskyetal.,2008,p.209/Rehmetal.,2009,p.290f: Modelforwindeffectsofburningstructures/Rockeletal.,2007,p.267f/Sauer,2010/Thiekenatal.,2006,p.485ff: Approachesforlarge-scaleriskassessments.
52 Cortietal.,2009,p.1739f/Cortietal.,2011,p.3335f/Granger,2003,p.183/Pinelloetal.,2004,p.1685f/Sparkset al.,1994,p.145ff.53 Golzetal.,2011,p.1f:Approachestoderivevulnerabilityfunctions./Hohl,2001,p.73f:Damagefunctionforhail./ICE, 2001:Source-Pathway-Receptor-Consequence-Concept/Jainetal.,2009/Jainetal.,2010/Kafali,2011/Klawaetal., 2003,p.725f/Matson,1980,p.1107/Naumannetal.,2009a,p.249f/Naumannetal.,2009b:Flooddamagefunctions. /Naumannetal.,2011/Penning-Rowselletal.,2005/Schanze,2009,p.3ff.
Dam
age
[S]
1
0G G crit tot
Intensity of extreme weather [G]
g(v)
Monetary Loss in Euro
Intensity of hazard (for ex. wind speed in m/s)
Probability in %
Risk-function Cost Value
Vulnerability-function Hazard-function
Damage Ratio in %
1971-2000 2071-2100
Annual exceedance probability (in %) 10-1 10-2
20 10 -10
25
30
35
40
45
Win
d sp
eed
(in m
/S)
15
Extreme Weather Events and Property Values
Inthiscontext,itwouldbeexpedienttocalculateanannualexpectedloss
(AEL)-i.e.,todefineoneyearasarelevanttimeinterval.Asthehazard
cantakeonnotonlysingle,discretecharacteristics-forexample,“in
4%ofthecasesthewindspeedreaches8metres/second”-butalso
constitutepartofacontinualdistribution,thehazardfunctionmustbe
integrated:54
ƒ =probabilitydensityfunctionofthehazard(hazardfunction)
S = loss function
W =valueofbuildingproperty
x =intensity/formofhazard(e.g.,windforceorwaterdepth)
xmin =lowerintegrationlimit,abovewhichdamageistobeexpected
p =probabilityofreoccurrence
AEL(j) =annualexpectedloss(inaspecificextremeweatherevent,j)55
To obtain a complete picture of the AELofaparticularproperty,allpartial
resultsofthedifferentextremeweatherevents(e.g.,wind,hail,flood,etc.)
are added up:
with AEL=annualexpectedloss(sum),andAEL(j)=annualexpectedloss
(inaspecificextremeweatherevent,j).
Fromarealestatevaluationperspective,theannualexpectedlosscould
nowbesubjecttopresentvalueconsiderationsbyimplementingarisk-
adequatecaprate(i):
with PV=presentvalue(oftherisk),andAEL=annualexpectedloss
(here,identicalforallyears)withi= cap rate.
Toaccountforthemostrealisticcaseinwhich(atleast)thehazard
changes,itisusefultodifferentiatebetweendifferentAELassumptions,
anddifferenttimeframes.Incontrasttoperpetuity,itwouldthenmake
sensetodothecalculationwithonereversionaryannuityfordifferent
annualexpectedlosses:
with PV=presentvalue(ofallexpectedlosses)representingtherisk,and
AEL=annualexpectedloss(int)withd= discount rate.
Thisvaluecouldalsobeusedaspartofapropertyvaluation,andinrisk
managementandportfoliomanagement.Asclimateriskshavebeen
implicitlytakenintoaccountintheinputparametersofvaluationstodate,
caremustbetakentoavoidredundancies;torefertothetotalpresent
valueasadeductionwouldthereforeprobablynotbeconstructive.On
theotherhand,itwouldmakesensetotakethepresentvalueofafuture
increaseintheannualexpectedlossescomparedtotheinitialvalue-such
astheaverageofthepreviousperiods,forexample.
with PV=presentvalue(ofallexpectedlossesthatexceedthehistorical
benchmark)representingtherisk,andAEL=annualexpectedloss(int)with d= discount rate.
The meaningful aggregation of hazard, vulnerability, and cost data elements in an annual expected loss as a present value involves a great deal of computing time and requires an extensive database.
Itshouldbenotedthat“cost”-andthereforealsoAEL-donot
automaticallyequal“value”andthisiswhypropertyvalueisoften
calculated using hedonic pricing models. These models attempt to
separatethegivenpropertypricesintotheirvaluedriversbyusing
multipleregressionmodels.Untilnow,however,researchershavemainly
focusedontheinfluenceofinfrastructure,populationdensity,and
othersocio-economicaspectswithintheframeworkofhedonicpricing
models,althoughsomeenvironmentalfactorssuchascrime,typesof
neighbourhood,earthquakerisk,airpollution,andclimatehavealsobeen
analysed.HarrisonandRubinfeld(1978)andlaterSmith(1995),aswell
asCostaandKahn(2003)andothers,haveinvestigatedhowthehedonic
priceofanon-marketgoodlike"climate"canbeestimated.(Thisfield
ofresearchthatfocusesonrealestatecanbecalled"cross-cityhedonic
qualityoflifeliterature".56)
Evenso,therearereasonswhytheuseofhedonicpricingmodelsto
estimate the cost and impact of climate change has so far remained
untouchedasaresearchfield.Theyaremainlybecause(1)hedonicpricing
modelsanalysehistoricaldata,andclimatechangeisadynamicprocess
withmanyofitsresultsonlyvisibleinthefuture,(2)climatechangeisa
complextopicwitharangeofinteractingvariables,and(3)uncertaintyis
inherentwhentalkingaboutclimatechange.
54 Kaplan,Garrick,1997,p.109:Therefore,informationaboutthehazardisaccompaniedbyastatementinregardtothe relevantstatisticalcertaintyinordertoshowthecertainty(e.g.,95percent)withwhichadefineddegreeofdamagewill notbeexceeded.55 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.56 Craggetal.,1997,p.261f/Craggetal.,1999,p.519f/Kahn,2004.
AEL(j) = ſ ƒ(x)S(x)Wdx = ſ S(p)Wdpxmin 0
1
AEL = Ʃ AEL(j)n
j=1
PV (Risk)= AEL
i
PV (Risk) = Ʃn
t=1
AELt
(1+d)t
PV (Increased Risk) = Ʃn
t=1
(AELt - AEL0)(1+d)t
16
However,hedonicpricingmodelscanhelpagreatdeal.Astheycan
disclosethevalueof“manyseverestorms”inonecityand“nostorms”
inanother,therearepossibilitiesforestablishinga“price”foranaspect
ofclimate.Combiningthemodelsforclimatechangewithaprojection
offutureeventsenablesacalculationoftheimpactofincreasingrisks
ofextremeweathereventsonthehousingmarketinthegivenlocation.
Nevertheless,theproblemsofinteraction,uncertainty,timepreference,
and changing consumer preferences still need to be addressed.
Inthiscontext,thecalculationmodelpresentedabovecanonlybe
understoodasafirststeptowardsthedeeperexplorationofnatural
hazards.Asyetitdoesnotallowforseveralnaturalhazardsoccurring
simultaneouslyandperhapsbeingsubjecttocorrelations57-forexample,
droughtincombinationwithveryhightemperaturesandlowhumidity
typicallyincreasestheriskofwildfire.Italsodoesnottakeintoaccount
thatlossfunctionscanalsobesubjecttodynamicsovertimeandcan
thereforechange;extremeweathereventstodaypossiblyincreasethe
vulnerabilityofagivenpropertytofutureextremeeventsduetoalower
resilience.Ontheotherhand,investmentstoincreasetheresilience
typicallyoccurafterafirstdisasterhastakenplace.Asaresult,extreme
weathereventswillaffectthecapabilityofthepropertytoadaptinvarious
ways.Furthermore,aswellastheverycomplexmodelingofthefunctional
relationships,thelimitedavailabilityofdatarepresentsafurtherrestriction
onderivingexpectedlosses,andthisgenerallyexposesclimatemodelsto
various uncertainties.58
Figure 7: Elements for the derivation of expected losses
Source:IRE|BS,UniversityofRegensburg,2013.
The analysis is restricted by data availability and complex functional modeling of the facts.
Itisthereforenoeasytasktoperformariskanalysisofextremeweather
eventsinrelationtopropertyvalues.Theaforementionedtopicsmust
bedealtwithinastructuredmanner,andthefundamentalrelationships
inrespecttoriskmanagementmustbeconsidered.Someofthekey
questionsthatariseare:
•Whatistheexactshapeofthedistributionofthespecifichazardfunction
foragivenkindofextremeweathertoday?Whichkindofdistributionfits
besttomodelthehazard,andwhichriskfunctionsandextremevalue
statisticsmightapply?
•Howwilltheriskchangeinthefutureinregardtotheintensityand
frequencyofextremeweatherevents?Howcandensityfunctionsbe
derivedtodaythatarerelevantforthefuture(e.g.,2020-2030)in
thisregard?
•Howisdamagecausedtoindividualpropertiesrelatedtotheintensity
ofanextremeweatherevent?Howcancorrespondingdamagefunctions
bederived?
•Whatinfluencedotechnicalprogressandadaptationtoexpectedlosses
haveonfuturevulnerability?
Inthenextsectionofthisreport,theelementsofvulnerabilityfunctionand
hazard function59areintroduced.Figure7givesanoverviewoftheorigins
of the data.
57 Buznaetal.,2006,p.132f.58 Cruzetal.,2007,p.495f/Lindenschmidtetal.,2005,p.99f/Merzetal.,2004,p.153f/Merzetal,2009,p.437f/Sachs, 2007,p.6ff.59 Note:AmoredetailedscientificexplanationofthetwoelementscanbefoundintheImmoRiskprojectreports.
Hazard Vulnerability Value
Database Historical events, modelled data for the distribution
Data based on historical losses (empirical loss events) or data derived by experts for a specific building type (engineering aproaches)
Typical replacement costs for specific building type, comparative data
Forecast Global and Regional Climate Models are the basis from which extreme value statistics are derived.
Only a few approaches exist to date. Changes of vulnerability are dependent on technical progress, adaptation measures, etc.
Cost inflation of given data for today’s replacement costs are possible.
17
Extreme Weather Events and Property Values
Outlook on the future development of extreme weather events
Intermsofstrategicrealestateinvestmentdecisions,aswellas
observationofthecurrentsituation,itisimportanttoanalysethe
developmentofallfactorsthatpotentiallyaffectfuturereturnsandvalues
aswellastheunderlyingdrivingforces.Inthisrespect,extremeweather
eventswillbecomeincreasinglyrelevantand,inlightofcurrentresearch,it
isassumedthatthetotalnumberandintensityofdifferentextremeweather
events will continue to grow.60
Figure 8: Impact of projected climate change
Source:IPCC,2012/Bouwer,2010.
CalculationsmadebytheImmoRiskprojectconcerningfuturetimeframes
havereachedthesameconclusion,whileallforecastsregardingthe
change in different hazard functions indicate a growing threat over time.61
Figure9illustratesthisresultbasedontheexampleofachangeindensity
function.
Leading scientists are highly likely to assume in
their scenarios that the overall risks from extreme
weather events will continue to increase, ultimately
leading to even higher losses. The corresponding
risk functions are generally composed of the
future hazard functions and the vulnerability of the
affected properties.
In these scenarios, increasing losses will be driven
in particular by the rising number of extreme
events (hazard). There is no clear conclusion,
however, regarding the development of the
vulnerability of buildings and infrastructure. On
one hand, resilience may improve due to major
investments in adaptation measures; on the other,
there are many reasons to believe the vulnerability
of the property stock in general will rise further,
such as the continued zoning for new construction
in heavily affected areas.
In developing strategies to address the threat of
extreme weather events for individual properties,
a strong, regional differentiation is essential when
considering the risks.
Furthermore, when it comes to real estate, it is
increasingly important to pay attention to relevant
psychological impacts. Even if people often do not
give up their property until they have been hit by
natural disasters repeatedly, these situations will
occur more frequently in the future, and migration
will intensify accordingly.
In regard to the vegetation in affected areas, trees
and other plants with a long growth phase, in
particular, will die out first, and this may happen
more rapidly.
Number of studies
Hazard type
Median estimated increase in loss in 2040 from 2000
9 Tropical storms 30%
6 Other storms 15%
6 Flooding 65%
60 Donatetal.,2011,p.1351ff/Donatetal.,2010,p.27ff/Naumann,2010,p.53/WorldBank,2013,p.XVff/Guyattetal., 2011,p.58:Physicalimpactswillincreasefrom2050on./Howelletal.,2013,p.4ff/IPCC,2013,p.4/Kunzetal.,2009, p.2294/Pintoetal.,2007,p.165f.61 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
18
Figure 9: Change in the density function of extreme weather events
Source:IPCC,2013,p.7
Note: The top graph shows the effects of a simple shift of the entire distribution
toward a warmer climate. The bottom graph shows the effects of an increase in
temperature variability with no shift in the mean.
Generalisedstatementsarenotconstructive,however,because
“confidenceinprojectingchangesinthedirectionandmagnitudeofclimate
extremesdependsonmanyfactors,includingthetypeofextreme,the
regionandseason,theamountandqualityofobservationaldata,thelevel
ofunderstandingoftheunderlyingprocesses,andthereliabilityoftheir
simulationinmodels.”62
Global trends are obvious; regional differentiation is necessary, however.
If substantial conclusions are to be drawn for individual properties or
portfolios,furtherregionaldifferentiationmustbeappliedtothefollowing
statements that refer to general developments:63
•Indevelopedcountries“...exposuretoclimate-andweather-related
hazardshasincreased,whereasvulnerabilityhasdecreasedasa
resultofimplementationofpolicy,regulations,andriskpreventionand
management(EEA,2008;UNISDR,2009).”64Thistrendwillprobably
continue,whereasvulnerabilitymightyetincreaseforlessdeveloped
countries.65
•“Modelsprojectsubstantialwarmingintemperatureextremesbytheend
ofthe21stcentury.Itisvirtuallycertainthatincreasesinthefrequency
andmagnitudeofwarmdailytemperatureextremesanddecreasesincold
extremeswilloccurinthe21stcenturyattheglobalscale.”
“AcrosslargepartsofEurope,the1961-1990100-yeardroughtdeficit
volumeisprojectedtohaveareturnperiodoflessthan10yearsbythe
2070s.”66
InMediterraneancountriesinparticular,droughtswillleadtoincreased
economiclosses(particularlywhenrelatedtothedangerofmore
intensiveforestfiresintermsoflength,frequency,andseverity)while
heatextremesinAsiawillalsoproliferateinthenearfuture.Across
theworld,globalwarmingwillalsoputaddedpressureonagricultural
yields.67Inthiscontextexpertsalsopointtothemountingconcerns
aboutincreasingheatintensityandotherclimate-relatedthreatsinmajor
Europeancities.68
Warmingwillleadtoanincreaseinthelackofwaterintheaffected
regions69andcausetheArcticicemassandglacierstoretreatfurther.70
•“Itislikelythatthefrequencyofheavyprecipitationortheproportion
oftotalrainfallfromheavyfallswillincreaseinthe21stcenturyover
manyareasoftheglobe....[F]uturefloodlossesinmanylocationswill
increase.”71
“Heavyrainfallsassociatedwithtropicalcyclonesarelikelytoincrease
withcontinuedwarming.”72
“Itisverylikelythatmeansealevelriseswillcontributetoupwardtrends
inextremecoastalhighwaterlevelsinthefuture.”73
ForEurope,thesealevelcanbeexpectedtorisebyanother0.46metre
by2080,leadingtofurtherseveredamagetopropertyandinfrastructure
incoastalregions.Totalmonetarydamageduetoflooding,salinity
intrusion,landerosion,andmigrationcouldrisefromacurrent€1.9
billion to €25.3billionin2080annually.74ForAsia,expertswarnthatthe
sea-levelrisecouldbeasmuchas1metreby2100ifthetemperature
risesby4°C.75
“Thereishighconfidencethatchangesinheatwaves,glacialretreat,
and/orpermafrostdegradationwillaffecthighmountainphenomena
suchasslopeinstabilities,movementsofmass,andglaciallakeoutburst
floods.Thereisalsohighconfidencethatchangesinheavyprecipitation
willaffectlandslidesinsomeregions.”76
62 IPCC,2012,p.9/Guyattetal.,2011,p.62.63 IPCC,2012,p.12ff/IPCC,2013,p.15ff.64 IPCC,2012,p.255/Schmidtetal.,2010,p.13ff.65 Satterthwaiteetal.,2007,p.15ff.
66 IPCC,2012,p.242/Lehneretal.,2006,p.1ff.67 WorldBank,2013,p.XVII.68 Wilby,2003,p.251ff.69 WorldBank,2013,p.XVII.70 IPCC,2013,p.17.71 IPCC,2013,p.13.72 IPCC,2013,p.19.73 IPCC,2013,p.120.74 Brownetal.,2011,p.31.75 WorldBank,2013,p.XVII/Leurigetal.,2013,p.4.76 IPCC,2013,p.114.
ShiftedMean
IncreasedVariability
Prob
abili
tyo
fOcc
urre
nce
Prob
abili
tyo
fOcc
urre
nce
19
Extreme Weather Events and Property Values
Lowland in coastal countries - below 5m elevation.
Source:EuropeanEnvironmentAgency
Theoverallpicturefromthismostrecentresearchisclear:extreme
weathereventswillriseinnumber,nomatterwhatkindofnaturalhazard
isdiscussed.Inparticular,theincidenceofforestfires,heatwaves,and
droughtswillcontinuetoincreaseinmanyregions,whilefloods,hail,and
severestormswilloccurwithgreaterfrequency.Likewisemudslides,
avalanches,andotherexamplesofsevereerosionwillbecomeevenmore
common,especiallyinmountainousareas,whileflashfloodswillgrowin
regularityandthemigrationofpeoplefromseverelyaffectedareaswill
escalate.
Expertsassumethat,aboveall,Russia77andtheUnitedStates78 will be
affectedtoanincreasingextent.Ofspecificnoteareheatwaves,their
accompanyingdroughtsandforestfires,andtheresultinglossesfor
forestryandagriculture,asdiscussedearlier.FortheWesternUnited
States,forexample,Spracklenetal.(2009)assumethattheaveragearea
burnedinforestfireseachyearwillmorethandoublewithinthenext40
years.Ifrainfalldecreases,thedrynessofthesoilwillincrease,especially
inthoseareasthatrelyonmountainmeltwater.
The rise in wildfires reports in the last 30 years
Source:ClimateCentral
It is widely accepted that a significant increase in frequency and intensity of extreme events - and therefore in damage - is highly likely.
Itisalsoexpectedthatdisastersassociatedwithclimateextremeswillhave
anincreasinginfluenceonpopulationmobilityandrelocation.Evenso,it
shouldbenotedthatpeoplemightnotimmediatelygiveuptheirhomesas
aresultofadisaster,butmaychoosetodosoiftheeventhappensagain.
Forexample,inpartsofAustriaanincreaseinrealestatesaleswasonly
noticedwhenthesameregionwasfloodedforasecondtime-acoupleof
yearsafterthefirstoccurrence.
Assevereweathereventsoccurwithgreaterfrequencyormagnitude,or
both,somelocalitiesmaybeconsideredincreasinglymarginalasplaces
tolive.Intensityandrecurrenceofnaturaldisasterswillthereforehavea
greatinfluenceonlocationdecisionsmadebypeople,yetonlywhencertain
tolerancelevelshavebeenreached.Theresultingmigrationwillnotonly
impacttheplacesbeingleftbehind,butclearlyalsotheareasthatpeople
moveto.Itislikelythattheareasmostaffectedbythelossofpopulation
willbecoastalsettlements,smallislands,mega-deltas,andmountain
settlements.79
77 MüRe,2013,p.40.78 Brandes,2013,p.4:basedonthe“DraftNationalClimateAssessmentReport”,U.S.GlobalChangeResearchProgram, January2013.
79 IPCC,2012,p.234f.
20
Studieshavealsodemonstratedthatperiodsofseveredroughtcanalso
leadtotherapidlocalextinctionofcertainplantsinaffectedareas-a
developmentthatissettointensify.80Inparticular,thisaffectstrees
with a long growth phase that cannot adapt fast enough to the changing
environment,asshownbythecaseoftheColoradopinyon(Pinusedulis)in
the2000-2003U.S.drought.81
Frequently recurring extreme weather will intensify human migratory flows. In the plant world, trees with a long growth phase will die out first.
InGreenland,thepresenceofheatislandswithincreasinglyrising
temperatures could cause the ice cover to continue to recede on a large
scale.However,itisquestionablewhethertheiceintheArcticwillcontinue
toretreatatitsveryhighaveragerateof11.3percentperdecadein
summer(basedontheoveralldifferenceinicecoverin2012compared
with1980).IntheSouthernHemisphereitcanbeassumedthattheannual
seaiceextent(Antarcticwithoutinlandice)willcontinuetoincrease-
althoughattheslowerrateof2.8percentperdecadeinthesouthern
summer,asrecordedtodate(basedonthechangefrom1980to2012).
The rising temperatures will also cause stronger winds around the Poles.
TheIntergovernmentalPanelonClimateChange(IPCC)assertsthat
various alternative emission scenarios and the climate models based on
themrepresent“asubstantialmulti-centuryclimatechangecommitment
createdbypast,presentandfutureemissionsofCO2.”82Becausemost
oftheimpactsrelatedtoclimatechangewillpersistovermanycenturies,
evenifemissionsarestoppedtoday,itisclearthatmanyconsequencesof
climatechangearenotforeseeable,despitestate-of-the-artforecasting
techniques.Forexample,thepossibilitythattheAtlanticMeridional
OverturningCirculation(AMOC)-thelarge-scaleoceancirculationcreated
bysurfaceheatandfreshwaterfluxes-mightcollapseafterthe21st
century,cannotbeignored.83
The limits of climate models are reached when thresholds and tipping
pointsrelatedtosocialand/ornaturalsystemsareexceeded.84For
example,Fischlinetal.(2007)analysed19studiesandconcludedthatup
to30percentofplantaswellasanimalspeciesmightbeatanincreased
riskoffastextinctioniftemperatureriseexceeds2°Cto3°C-whichisa
realistic scenario.85Suchfundamentalchangestotheenvironmentwillhave
significantbut,asyet,unpredictableeffectsontheeconomy.
The continuous deterioration of the ecosystem and ongoing climate change could lead to critical tipping points being reached more frequently.
Thus,acleartrendtowardsmoresevereandmorefrequentextreme
weatherevents-withcorrespondingeffectsonrealestateandthe
broadereconomy-mustbeanticipated.Incontrast,nouniformtrends
canbederivedconcerningvulnerabilityofrealestatetoextremeweather.
Itisgenerallytobeexpectedthattheexposureofrealestateportfolios
toextremeweathereventswillseearelativedecreaseworldwidedue
toadaptationmeasurestocombatsuchevents-thoughtheadaptation
neededwillprobablybesimultaneouslyconnectedtosubstantial
investments.
Theexposureofrealestatetoclimatechange-relatedriskisclosely
connectedtosocio-economicdevelopments,suchasthecontinuedrisein
populationandeconomicgrowth,improvedsocialwelfare,andthelocation
ofnewsettlementareas.Inthisregard,itwillbenecessaryinthefuture
tobemuchmoresensitivewhendesignatingexistingnaturalareasas
building zones.86Positiveactionsinthisdirectioncanalreadybeobserved
indevelopingcountries,wherebuildingregulationsandland-useplanning
areincreasinglytakingintoaccounttheneedtoreducethevulnerabilityof
buildings to the effects of climate change.87Intelligentwarningsystemsare
alsoincreasinglybeinginstalledthatcanhelpprotectpeopleandprevent
propertydamage.
It is impossible to derive clear information regarding the development of vulnerability.
Meanwhile,threatstorealestatefromsevereweatherremainintheform
ofunbridledgrowth,uncontrolledconstructionofsettlementsinpoor
countries,anduseofmodernconstructionmaterialsandelements,such
as certain facades or fragile solar panels on roofs that could be damaged
byhailorotherstormdamage.Moreover,recentstudiesfocusingonport
citieswithmorethan1millioninhabitants,forexample,haveestimated
thatrealestateassetsinthesecitiesthatmightbeexposedtoaonce-a-
centuryextremeeventcouldgrowtenfoldtoaroundUS$35trillionby2070
(€25.5trillion).88
80 WorldBank,2013,p.XVII.:Drought-induceddie-offofplantsandtrees.81 IPCC,2012,p.244./Granieretal.,2007,p.124f.82 IPCC,2013,p.19.83 IPCC,2013,p.17.84 Dawsonetal.,2009,p.9685 Dawsonetal.,2009,p.244.
86 Cruzetal.,2007,p.491f:Weaklanduseplanningandenforcementareincreasingvulnerabilitytoextremeweatheraswell as climate change in general.87 Feyenetal.,2009,p217f.88 Nichollsetal.,2008,p.8ff/WorldBank,2013,p.XXI,p.33ff,p.82ff:Regardingcoastalcitiesingeneral.
21
Extreme Weather Events and Property Values
Case Study: Increased insurance premiums / annual expected loss
Inthiscasestudy,ahypotheticalpropertyisprocessedwiththedata
ofdamagefunctionsaswellas(future)hazardfunctionstoderivean
annualexpectedloss(AEL)ofthepropertyfordifferenttimeperiods.The
characteristicsofthehypotheticalpropertyareshowninfigure10.89
Figure 10: Property details
Source:IRE|BS,UniversityofRegensburg.
Theriskofwindstormhazardsistypicallyexpressedasthefrequency
oftheoccurrenceofstormeventswhichexceedacertainwindspeed
([exceedance]probability).Atthisproperty’slocation,weassumethereisa
stormeventevery10years(returnperiod),withsqualls(windgusts)ofup
to31.6metrespersecond(114km/h)tobeexpected.Thecorresponding
functiondescribingthisrelationship-thatis,thereturnperiodofwindstorm
intensities(windspeeds)-canbestatedasfollows:90
Here,x is the wind speed and Tistherecurrenceinterval.Inthisexample,
α (3.31)andβ(24.12)aretheextremevaluestatisticalparametersofthe
Gumbel-distribution91reflectingthecurrentsituation(basedasaproxyon
the latest available data set regarding hazards that occurred within the time
period1971-2000).
Takingintoaccountthespecificbuildingandlocationcharacteristics,the
followingempiricallyderivedstorm-damagefunctioncanbeapplied.Thisis
a power function of
with Sastherelativedamagetothepropertycausedbyagivenwind
speed,x. The parameters a and b are derived from empirical damage
functions(basedonrealinsurancedataofhistoricallossesthatoccurredin
connectionwithcertainstormeventsinthepast).Inthiscase,
a =3.3*10-19 and b =10.0//92
Thefunctionsalsoaccountforthefactthatthedamagesforverylowwind
speeds(uptoabout30metrespersecond)areclosetozero.However,
withhigherwindspeeds,theyincreasestrongly.Otherfactors-suchas
howlongthewindstormlasts,gustiness,93 or trees that might surround the
building-arenotexplicitlymodelledhere.
Accordingtothisdamagefunction,thestormforareturnperiodof100
years,withwindspeedsofabout39.3metrespersecond,would,for
example,leadtodamagesofabout0.377percentofthetotalbuilding’s
costvalue;thepercentagerelatedtotheoverallvaluereflectsmainly
therepairworkneededforthepartiallydestroyedroofcover,damaged
windows,andotherrelativelyfragilebuildingpartsthatwillbeexposedto
stormevents.Itshouldbenotedthatbecauseofthehigh-quality,robust
constructionofpropertiesinGermany,severe,structuraldamagesare
usuallytheexceptioninstorms.
Todeducetheannualexpectedloss(AEL*)inallpossiblestormevents,
this formula involving all recurrence intervals or probabilities must be
integrated as follows94:
Hazard Type Windstorm
Property type Single-family house (detached)
Construction Solid construction/stone
Year of construction 2010
Gross external area 250 sq metres
Levels above ground 1
Height of building 3.25 metres
Type of roof Flat
Roofing Soft roofing
Standard of fittings Very high
Special exposure to hazards None
Year of assessment 2013
x(T)= β - α * ( ln (-ln(1- )))1T
S (x) = a * ( 1 + x )b
89 Note: Case study was calculated by Jens Hirsch and Sven Bienert. The case study is for illustration only.90 SeeAugter/Roos,2010,p.21f.91 Markoseetal.,2011,p.35ff:GeneralizedExtremeValue(GEV)distribution./Rootzenetal.,1997,p.70f/Singhetal., 1995,p.165ff.
92 Thisdamagefunctionisforthepurposesofillustrationonly,withreferencetorealdatafromtheinsuranceindustry.93 Wieringa,1973,p.424:Differentiationofgustfactors.94 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
= 0.637
= 0.637
AEL* = 0.637* ſ S(x(p))dp1
0
=0.637 * 0.293‰ = 0.187‰
* ſ a*(1+β-α*(ln (-ln(1-p))))b dp1
0
1
0* ſ a*(1 + x(p))b dp
22
Duetoproperty-specificelements,95 this result is adapted in regards to
typeofuse,age,construction,androofing,basedonempiricalvaluesfrom
theinsuranceindustry;theresultingcorrectionfactorhereis0.637,andis
integratedaccordinglyintheformulaabove.
Here,theannualexpectedlossis0.187‰ofthevalueofthebuilding.The
AEL(ineuros)isthereforecalculatedbymultiplyingtheobtainedAEL*
bythepropertyvalue(basedoncostdataforthebuildingonly).
SincebenchmarkdataisavailableinGermany(NHK,normalised
replacementcost,2010,whichrepresentstheaveragebuildingcostsper
squaremetre),96itispossibletoderivereplacementcostspersquare
metreforagivenbuilding;thebenchmarksalreadyincludeconstruction
costs,value-addedtax,and17percentforrelatedcosts(e.g.,design,
planningapproval,projectmanagement,etc.).Aftertakingintoaccountthe
building-costindexforinflation,andadjustingthefiguresaccordingtolocal
andregionalpricinglevels,theadjustednormalreplacementcostsroundto
€1,950persquaremetregrossexternalarea.Thereplacementcostofthe
property(withoutland),therefore,encompasses
Theannualexpectedlossthusamountsto:
Thisvaluelargelycorrespondstotoday’sinsurancepremiums,butshould
beclassifiedas“veryhigh”.
Wenowchangetheinputparametersbasedontheinformationderived
fromRegionalClimateModels(RCMs)regardingthehazarddata,anduse
theextremestatisticsparameterα (now3.56)andβ(now25.82)asinput
for the Gumbel distribution applied in this case for the time period
2021-2050.
The new AEL* is 0.637 * 0.578‰ = 0.368‰; the new AEL = 0.368‰ * €487,500 = €179.49
Inthiscase,theinsurancepremiumwillthereforealmostdoubleinthe
medium term based on latest climate data.
Whena3percentinterestrateisapplied,asimplifiedconsiderationofa
pure capitalisation of the annual difference results in97
with PV=presentvalue(ofallexpectedlossesthatexceedthehistorical
benchmark)representingtherisk,andAEL=annualexpectedloss(int)with i= cap rate.
Therefore,althoughtheincreasedriskseemsrelativelymoderateand,
whenrounded,amountstoonlylessthan1percentofthetotalbuilding
value,onemusttakeacoupleoffactorsintoaccount.First,severalother
hazardtypesrelatedtoextremeweathereventsmustalsobeconsidered
-hail,flooding,etc.-andthesehazardfunctionsmightevencorrelate.
Furthermore,besidesdirectlossesduetoextremeweather,therealso
areeffectsduetothegradualclimatechangethatneedtobereflected,
asshouldindirecteffectsandconsequentiallossesrelatedtoextreme
weather.Ifallthese(increasing)risksaretakenintoaccount,theoverall
impactontoday’svaluemightbesignificantenoughtocatchthe
owner’sattention.
NHK = 1,950 * 250.0m2 = €487,500€m2
AEL = AEL* * NHK = 0.187‰ * €487,500 = €91.16
PV (Increased Risk) = (AELt - AEL0)
i
PV (Increased Risk) = (179.49 - 91.16)
0,03
PV (Increased Risk) = €2,944.33
95 Databasedonexperience:GesamtverbandderDeutschenVersicherungswirtschaft(GDV),Germaninsurancecompanies association.96 SeeBundesministeriumfürVerkehr,BauundStadtentwicklung,SW-RL,2012,p.12ff.
97 Note:Thelaterincreasebasedonthereferenceperiodswasnotincludedinthisillustrationoftheeffect.
23
Extreme Weather Events and Property Values
Conclusions
Thisreportverymuchconfirmsthatclimatechangeisarealityandthat
itsnear-termconsequences-intheformofextremeweatherevents-are
growinginscale,intensityandfrequency.Fortherealestateindustry,
whichisalreadyadaptingtotacklethecausesofclimatechange(ofwhich
itisamaincontributor)inareassuchasemissionsandenvironmental
controls,addressingtheseweather-relatednaturalhazardsand
correspondingthreatsshouldnotjustbeviewedasthe‘nextchallenge’
on the agenda. It should be part of a wider mindset that considers how
climatechangeandallitseffectswillinfluencerealestatelocation,building
specificationandcost,operatingcostsand,ultimately,value.
Ashighlighted,extremeweathereventsarenowhaving,insomecases,
a devastating effect on particular regions of the world with spectacular
economiclosses–andtheimpactsarenotjustbeingrepeatedmore
frequentlybutarewideningtotouchnewgeographies.Withfinancial
returnsalreadybeingaffected,adeeperunderstandingofthescience
ofclimatechangeanditsimpactonpropertyvalueisthereforerapidly
required;asistheadoptionofnewcriteriawithintheinvestment-decision
makingprocess.
Therealestateindustry,critically,shouldnotattempttomitigatethe
increaseinextremeweathereventsandtheresultingincreaseinrisk
bymerelyrelyingonpotentiallyrising(andnon-allocable)insurance
premiums.Thedirectandindirecteffectsonspecificregionsandasset
classesmaybesoenormous,thatinvestmentlocationscurrentlyseenas
“safehavens”mustbereconsidered.Theresultwillbere-evaluations,
buildingadaptationcosts,andfundamentallydifferentallocationsof
investmentfunds.Moreover,thedramaticregionaldifferencesinthe
expectedimpactfromclimatechangerequiresananalysisoftherealestate
inventoryineachregion,andthenindividualrecommendationsmadeonit.
Aspartofthechangeinmindset,itisalsoessentialthatclimatechange
anditsrisksarethoroughlyunderstoodand,whererelevant,actedonat
everystageofthepropertylifecycle.Forexample,planningeffortsthat
integrateclimatechangeriskswillbeincreasinglyimportantforinvestors.
Atthesametime,fromanurbanplanningperspective,theextenttowhich
the public sector adopts building adaptation measures and implements
broaderspatialplanningconceptstoaddressriskswillbecomemore
importantinaworldofincreasinglycompetitiveinternationalcitymarkets.
Ininvestmentmarkets,managingclimateriskwill,amongotherthings,
mostlikelyleadtoanincreasedallocationofinvestmenttorealestate
assetsthatarealreadyfuture-proofed.Investorsmustthereforetake
significantstepstowardsimprovingtheresilienceoftheirportfolioswhile
integratingriskassessmentsrelatedtoclimatechangeintheirportfolio
management.Simultaneously,advisersandassociatedindustryplayers
willneedtobeatthesamepoint,ifnotfurtheruptheclimatechange
intelligence curve.
Atpresent,researchintothefutureofpropertyvaluesinthefaceof
increasingweather-relatednaturalhazards,andtheimplicationsfor
riskandportfoliomanagement,isstillinitsinfancy.Thisreportis
therefore a contribution towards heightening awareness and opening up
discussiontoalargeraudienceintherealestateindustry.Pivotaltothe
debateishowweather-relatedlossescanbeaccuratelycalculatedand
therisksassessed;thenewlosscalculationmethodologyfeaturedin
thispaperseekstoprovidetheindustrywithatoolthatwillenablereal
estateinvestorstomakefar-reachingconclusionsinregardtothefuture
developmentofpropertyvaluesinaspecificsituation.
Extremeweathereventswillcontinuetomultiplyandintensify,and
althoughimprovedforecastingwillbecomestronger,therewillalwaysbe
anelementofunpredictabilityintheirnatureandlocation.Inreality,as
thesethreatscontinuetoescalatenoonewillbetrulyinvulnerable.Acting
nowtofuture-proofassets,improveresilienceandreducerisksisvitalfor
therealestateindustryacrosstheworld.
24
Appendix: Overview of the present state of research
Existingstudiesrelatedtoclimatechange,andthatfocusonextreme
events,mainlydealwithempiricalvaluesinspecificregionsorcities.
Amongthese,forexample,aretheUNDROsurveyforManila(1977);the
KATANOSreportforSwitzerland(1995);theAustralianAGSOCitiesproject
withitsemphasisongeohazards(1999);andstudiesregardingTurrialba,
CostaRica(2002),andToronto(2003).Inadditiontotheirregionalfocus,
mostofthestudiesconcentrateonsingle-hazardresearch-thatisan
isolated consideration of a single natural hazard. 98Inparticular,several
studies from different regions have focused on the economic losses
withrespecttoflooddamage(e.g.,L.M.Bouwer’s2010studyofthe
Netherlands).Simultaneousconsiderationofseveralextreme-weather
hazards-forexample,inthemanneroftheAustralianresearchofBlong
(2003)-has,uptonow,beenanexception.Inviewofthepractical
relevanceofclimatechange,thisissurprising.99
Inregardtohazardresearch,thefewstudiesthathaveaddressed
economiclossesfromhaildamagehaveyieldedmixedresults.McMaster
(1999)andNiallandWalsh(2005)foundnosignificanteffectonhailstorm
lossesforAustralia,whileBotzenetal.(2010)predictedasignificant
increase(upto200percentby2050)fordamagesintheagricultural
sectorintheNetherlands-theapproachesusedbythetwostudiesvaried
considerably.TheRosenzweigetal.(2002)studyreportedonapossible
doublingoflossestocropsduetoexcesssoilmoisturecausedbymore
intense rainfall.100
Invulnerabilityresearch,DodmanandSatterthwaite(2008)havefocused
onthevulnerabilityofresidentialproperty,andSatterthwaitehasalso
analysedtheeffectsofclimatechangeonareaswherethepoorlivein
veryelementaryhousing.IncommonwithDouglas(2008),hefoundsuch
housingtobehighlyvulnerable.Furthermore,Wilby(2003,2007)has
intensivelyexaminedtheimpactofclimatechangeonhighlydeveloped
cities such as London.
Climatechangeandpopulationdensityhasbeenespeciallyaddressedby
Cutteretal.(2008),whileEndlicheretal.(2008)havealsofocusedon
largecities,althoughthereportconcentratedonprospectiveheatwaves
thatwillposespecificchallengesforsuchareas.Morespecifically,
McGranahanetal.(2007)haveexploredtherelationshipbetween
windstormsanddenselypopulatedareasincoastalregionsandfoundan
increasing threat.
RiskManagementSolutions(2000,2012)hasconcentratedoncertain
constructionmaterialsandtheirvulnerabilityincaseofwindstorms,and
Witharanaetal.(2010)haveusedsoftwaretoquantifybuilding-content
vulnerability.
98 Grünthaletal.,2006,p.21.99 DiMauroetal.,2006,p.1.100 IPCC,2012,p.272.
25
Extreme Weather Events and Property Values
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Resilience.WorldBank,Washington,DC.
WorldBusinessCouncilofSustainableDevelopment(WBCSD)(2009):
EnergyEfficiencyinBuildings-TransformingtheMarket.WBCSD,Geneva.
32
Footnotes
1 MüRe,2013,p.40ff/IPCC,2013,p.4.
2 Petersonetal.,2013,p.20/IPCC,2013,p.5.
3 Rahmstorf,2007,p.1ff/IPCC,2013,p.6.
4 MüRe,2008,p.6/Latif,2009,p.153/Petersonetal.,2013,p.IV/IPCC,2013,p.8f,p.12f./Bouwer,2011,p.39f.
5 MüRe,2013,p.40.
6 NationalOceanicandAtmosphericAdministration(NOAA),10.Mai2013/IPCC,2013,p.7.
7 Note:“DohaClimateGateway”negotiationswithmandatoryregulationsfrom2020onstillrefertothe2degreeCelsiusgoalattheDohaclimateconferenceinDecember2012.
8 Brandes,2013,p.9:EstimatedValueofInsuredCoastalPropertiesamountintheUnitedStatestoUS$27.000billionin2012.
9 WBCSD,2009,p.6.
10 Bosteelsetal.,2013,p.6.
11 Guyattetal.,2011,p.15:Realestateisverysensitivetoclimateimpacts./Leurigetal.,2013,pp.5,7
12 WorldBank,2013,p.94:Reducedpropertyvalues.
13 Guyattetal.,2011,p.61/Cruzetal.,2007,p.492:Effectsontourismmightbemassive./Lamond,2009.
14 ULI,2013,p.14ff:Recommendation16:Accuratelypriceclimateriskintopropertyvalueandinsurance.
15 Guyattetal.,2011,p.58.
16 MüRe,2013,p.53.
17 Kronetal.,2012,p.542:Directlossesareimmediatelyvisibleandcountable(lossofhomes,householdproperty,schools,vehicles,machinery,livestock,etc.).
18 IPCC,2013,p.270.
19 Kronetal.,2012,p.535f,p.542f.
20 MüRe,2013,p.42
21 Note:Theassumptionofaperpetuityservesonlytoillustratetheextentofthesituationanddoesnotclaimtobescientificallyconclusiveastothefacts.
22 MüRe,2010,p.33,p.37.
23 Cruzetal.,2007,p.488.
24 IPCC,2012,p.7:Inregardtothechangeswhichhaveoccurredsofar,theIPCChasdeterminedthat“atleastmediumconfidencehasbeenstatedforanoveralldecreaseinthenumberofcolddaysandnightsandanoverallincreaseinthenumberofwarmdaysandnightsattheglobalscale,lengthornumberofwarmspellsorheatwaveshasincreased,PolewardshiftinthemainNorthernandSouthernHemisphereextratropicalstormtracks,therehasbeenanincreaseinextremecoastalhighwaterrelatedtoincreasesinmeansealevel.”
25 GDV,2011,p.1/MüRe,2013,p.52/Mechleretal.,2010,p.611ff.
26 MüRe,2013,p.3ff.
27 MüRe,2013,p.52.
28 IPCC,2012,p.270/Guyattetal.,2011,p.14:CostofphysicalclimatechangeimpactcouldreachUS$180billionperyearby2030(€131.4billionpa)
29 Mills,2005,p.1040f/Mills,2012,p.1424f/Mechleretal.,2010,p.611ff.
30 Howelletal.,2013,p.46:Greaterconcentrationofpropertiesinriskzones.
31 Naumannetal.,2009,p.228/MüRe,2008,p.4.
32 MüRe,2013,p.58.
33 IPCC,2012,p.265.
34 Note:SeetheAppendixforanextendedoverviewofthecurrentstateofresearch.
35 IPCC,2012,p.266.
36 Wilby,2007,p.42/Guyattetal.,2011,p.1ff:Traditionalassetallocationdoesnot account for climate change. There is a small amount of research which focusesontheinvestmentimplicationsofclimatechange./Brandes,2013,p.12ff:Theriseofmodelingandfutureriskscenarios.
37 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
38 Note:Anexternaleffectis,forexample,airpollutioncausedbyenergyconsumptionthataffectsathirdparty(e.g.,thesocietyingeneral)thatwasnotresponsibleforthatemission.Theexternalityis“uncompensated”forthepolluterbecausethecostwillbebornebyothersunlesstheexternalityis“internalised”throughregulation(e.g.,taxes).
39 ULI,2013,p.17:Marketvaluedriveslanduse.
40 IPCC,2013,p.10:climatefeedbacks.
41 Osbaldistonetal.,2002,p.46/Ozdemir,2012,p.1ff.
42 Wilby,2007,p.42:“Aboveall,thereisanurgentneedtotranslateawarenessof climate change impacts into tangible adaptation measures at all levels of governance.”/Guyattetal.,2011,p.1:Standardapproachesrelyheavilyonhistoricaldataanddonottacklefundamentalshifts.
43 Lechelt,2001,p.28.
44 Büchele,2006,p.485/Kaplan,Garrick,1997,p.93.
44 UNDHA,1992,p.64:“Riskareexpectedlosses(of...propertydamaged...)duetoaparticularhazardforagivenareaandreferenceperiod.Basedonmathematicalcalculations,riskistheproductofhazardandvulnerability.”
45 ULI,2013,p.17:Marketvaluedriveslanduse.
46 Thywissen,2006,p.36/UNDHA,1992,p.84:“Degreeofloss(from0%to100%)resultingfromapotentiallydamagingphenomenon.”
47 Heneka,2006,p.722/Büchele,2006,p.493.
48 InsurablevalueaccordingtoInternationalValuationStandards(IVS):Thevalueofapropertyprovidedbydefinitionscontainedinaninsurancecontractorpolicy.
49 EuropeanValuationStandards(EVS),2012.
50 IPCC,2013,p.10,14f/Khanetal.,2009:Stormriskfunctions/Leckebuschetal.,2007,p.165ff/Mohretal.,2011//Waldvogeletal.,1978,p.1680ff.
51 Fleischbeinetal.,2006,p.79f/Linkeetal.,2010,p.1ff/Orlowskyetal.,2008,p.209/Rehmetal.,2009,p.290f:Modelforwindeffectsofburningstructures/Rockeletal.,2007,p.267f/Sauer,2010/Thiekenatal.,2006,p.485ff:Approachesforlarge-scaleriskassessments.
52 Cortietal.,2009,p.1739f/Cortietal.,2011,p.3335f/Granger,2003,p.183/Pinelloetal.,2004,p.1685f/Sparksetal.,1994,p.145ff.
53 Golzetal.,2011,p.1f:Approachestoderivevulnerabilityfunctions./Hohl,2001,p.73f:Damagefunctionforhail./ICE,2001:Source-Pathway-Receptor-Consequence-Concept/Jainetal.,2009/Jainetal.,2010/Kafali,2011/Klawaetal.,2003,p.725f/Matson,1980,p.1107/Naumannetal.,2009a,p.249f/Naumannetal.,2009b:Flooddamagefunctions./Naumannetal.,2011/Penning-Rowselletal.,2005/Schanze,2009,p.3ff.
33
Extreme Weather Events and Property Values
54 Kaplan,Garrick,1997,p.109:Therefore,informationaboutthehazardisaccompaniedbyastatementinregardtotherelevantstatisticalcertaintyinordertoshowthecertainty(e.g.,95percent)withwhichadefineddegreeofdamagewillnotbeexceeded.
55 Bienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
56 Craggetal.,1997,p.261f/Craggetal.,1999,p.519f/Kahn,2004.
57 Buznaetal.,2006,p.132f.
58 Cruzetal.,2007,p.495f/Lindenschmidtetal.,2005,p.99f/Merzetal.,2004,p.153f/Merzetal,2009,p.437f/Sachs,2007,p.6ff.
59 Note:AmoredetailedscientificexplanationofthetwoelementscanbefoundintheImmoRiskprojectreports.
60 Donatetal.,2011,p.1351ff/Donatetal.,2010,p.27ff/Naumann,2010,p.53/WorldBank,2013,p.XVff/Guyattetal.,2011,p.58:Physicalimpactswillincreasefrom2050on./Howelletal.,2013,p.4ff/IPCC,2013,p.4/Kunzetal.,2009,p.2294/Pintoetal.,2007,p.165f.
61 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
62 IPCC,2012,p.9/Guyattetal.,2011,p.62.
63 IPCC,2012,p.12ff/IPCC,2013,p.15ff.
64 IPCC,2012,p.255/Schmidtetal.,2010,p.13ff.
65 Satterthwaiteetal.,2007,p.15ff.
66 IPCC,2012,p.242/Lehneretal.,2006,p.1ff.
67 WorldBank,2013,p.XVII.
68 Wilby,2003,p.251ff.
69 WorldBank,2013,p.XVII.
70 IPCC,2013,p.17.
71 IPCC,2013,p.13.
72 IPCC,2013,p.19.
73 IPCC,2013,p.120.
74 Brownetal.,2011,p.31.
75 WorldBank,2013,p.XVII/Leurigetal.,2013,p.4.
76 IPCC,2013,p.114.
77 MüRe,2013,p.40.
78 Brandes,2013,p.4:basedonthe“DraftNationalClimateAssessmentReport”,U.S.GlobalChangeResearchProgram,January2013.
79 IPCC,2012,p.234f.
80 WorldBank,2013,p.XVII.:Drought-induceddie-offofplantsandtrees.
81 IPCC,2012,p.244./Granieretal.,2007,p.124f.
82 IPCC,2013,p.19.
83 IPCC,2013,p.17.
84 Dawsonetal.,2009,p.96
85 Dawsonetal.,2009,p.244.
86 Cruzetal.,2007,p.491f:Weaklanduseplanningandenforcementareincreasingvulnerabilitytoextremeweatheraswellasclimatechangeingeneral.
87 Feyenetal.,2009,p217f.
88 Nichollsetal.,2008,p.8ff//WorldBank,2013,p.XXI,p.33ff,p.82ff:Regardingcoastalcitiesingeneral.
89 Note:CasestudywascalculatedbyJensHirschandSvenBienert.Thecasestudyisforillustrationonly.
90 SeeAugter/Roos,2010,p.21f.
91 Markoseetal.,2011,p.35ff:GeneralizedExtremeValue(GEV)distribution./Rootzenetal.,1997,p.70f/Singhetal.,1995,p.165ff.
92 Thisdamagefunctionisforthepurposesofillustrationonly,withreferencetorealdatafromtheinsuranceindustry.
93 Wieringa,1973,p.424:Differentiationofgustfactors.
94 SeeBienertetal.,2013,p.1ff:ImmoRiskToolforBMVBS.
95 Databasedonexperience:GesamtverbandderDeutschenVersicherungswirtschaft(GDV),Germaninsurancecompaniesassociation.
96 SeeBundesministeriumfürVerkehr,BauundStadtentwicklung,SW-RL,2012,p.12ff.
97 Note:Thelaterincreasebasedonthereferenceperiodswasnotincludedinthis illustration of the effect.
98 Grünthaletal.,2006,p.21.
99 DiMauroetal.,2006,p.1.
100 IPCC,2012,p.272.
34
Heading
35
Extreme Weather Events and Property Values
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