2017 introducing the m&g real estate european connectivity ... · the reviewed cities, boosting...
TRANSCRIPT
Part of the M&G Group
Introducing the M&G Real EstateEuropean Connectivity Rankings
June
201
7
For investment professionals only
2
Introduction 3
Mega trends 3
Connectivity 3
Urbanisation 4
How Big Data can help 4
Measuring urban connectivity 4
Connectivity scores and rankings 5
Top city performers 5
Top performers by enablers 6
Top performers by effects 6
Where is the value? 8
Analysis 8
Implications for real estate investors 10
Helsinki: Potential connectivity climber 10
Appendices
City connectivity rankings 11
Methodology 13
Connectivity metrics: enablers 14
Connectivity metrics: effects 15
City density classification 16
Connectivity scores vs yields 18
Contents
3
1. Introduction
Connectivity is the smart physical and digital
infrastructure that make our cities tick and helps their
economies to grow. It keeps the wheels of our transport
systems turning smoothly. And crucially, it brings
together residents, visitors, businesses and public and
private institutions.
The power of connectivity doesn’t stop there. At M&G
Real Estate, we believe that well-serviced connectivity
infrastructures help to underpin a city’s property
fundamentals too. We also believe that a better
understanding of connectivity can help investors to
identify relative value opportunities in real estate and to
future-proof their investments more effectively.
That’s why we developed the M&G Real Estate European
Connectivity Rankings to grade 64 European cities1
based on their capacity to improve physical and digital
urban connectivity in the face of the growing density
pressures that face Europe’s cities today.
The table below highlights a snapshot of our top-10
city performers based on their final connectivity scores.
In this paper, we outline the methodology behind our
rankings, with the complete rankings appearing on page
11 of the Appendix.
Mega trendsConnectivity
‘Good density’, according to the Urban Land Institute (ULI), is defined by four drivers: technology, capital, urban form
and design, and infrastructure and connectivity. And the results of good urban density include elements of mixed-use
design, connectivity, green spaces, cohesiveness and liveability (Figure 1.2).
Source: Density: drivers, dividends and debates, June 2015, Urban Land Institute.
Outcomes of Bad Density
Mixed Use Connected Planned Spacious
Incremental Designed Green Appropriate
Liveable Cohesive
Monotonous Isolated Unmanaged Unliveable
Segregated Inflexible Ugly Polluting
Crowded ConspicuousOutcomes of Good Density
Densification
Technology CapitalUrban Form and
DesignInfrastructure and
Connectivity
Enablers and Secondary Drivers
Fig 1.2: Densification: Drivers, dividends and debates
Fig 1.1 Top 10 city performers
Total Connectivity Rank City Density* Total Enabler Rank Total Effects Rank1 Paris High 1 56
2 Berlin Medium 2 31
3 Stuttgart Medium 3 28
4 Zurich Medium 5 14
5 Stockholm Medium 8 15
6 Amsterdam Medium 7 36
7 Munich Medium 6 39
8 London High 4 62
9 Bremen Low 11 5
10 Luxembourg Low 18 4
Source: M&G Real Estate, December 2016. *Please see Appendix 5 for the definition of city density.
1Our analysis utilises annual PMA prime rent and yield data for these 64 European cities.
4
Urbanisation
Over 70% of Europeans live in cities and the urban areas
around them, with that figure expected to reach 80% by
2050. And with around 85% of European GDP generated
in cities, this backbone of the region’s economy is only
set to grow in importance.
However, the physical infrastructures needed to support
growing cities are struggling to cope and housing demand
is outpacing supply. This kind of densification does not fit
the model envisaged by the ULI and is evident across
the EU where the overcrowding rate of households, as
measured by Eurostat, is higher in cities (c.18%) than in
towns and suburbs (c.14%) or rural areas (c.7%).
Demand for better connectivity is also being boosted
by an unprecedented wave of migration as more people
move into European cities to live and work. Business and
tourist travel is also on the rise as travel becomes more
affordable, new routes become available, the stock of
short-stay accommodation improves, and income levels
rise in Asia and elsewhere.
How Big Data can help
Big Data could help to plug the funding gap and break
the link between economic growth and congestion with
cheap data-based solutions. The range, volume and
frequency of data are growing rapidly as cities start
to install sensors into everything from streetlights to
parking bays. By next year already, some 80% of cars in
Western Europe will be able to receive and generate real-
time traffic data, according to INRIX. In addition, some
cities like Gothenburg in Sweden are pressing ahead with
autonomous car technology, aiming to introduce 100
driverless cars on their roads by end-2017.
Taken together, that suggests congestion looks set
to fall as more travellers are diverted at peak hours
from crowded routes to less-packed ones. Indeed, there
is already some evidence of that: despite London’s
relatively poor overall showing, research by INRIX shows
that traffic signal optimisation and smart motorways
are proving successful at reducing traffic congestion in
the UK capital and on its principal motorway, the M252.
Emissions of pollutants should also fall, because fewer
vehicles would be idling in traffic jams and there would
be fewer cars on the street.
Applying data analytics to create intelligent
transportation systems will play a key role in improving
urban connectivity, in line with predictions that Big Data
will boost European GDP by 1.9% by 20202.
Measuring urban connectivity
In this study, we measure how the physical and digital
infrastructures, both public and private, performed in 64
European cities. Our objective is to identify real estate
value in dense, sustainable and well-connected urban
centres from a connectivity perspective.
Our assumption is that relatively high scores support
strong real estate fundamentals. Cities with the most
visionary connectivity policies are more likely to continue
to attract talented people despite rising density pressures
like traffic congestion and carbon emissions.
We split the connectivity metrics we track into two
categories: ‘enablers’ and ‘effects’. Enablers can be
considered as urban connectivity ‘inputs’ (e.g. city
mobility strategy, Wi-fi speed, the coverage of Real
Time Passenger Information apps), while effects can
be considered urban connectivity ‘outputs’ (e.g. network
affordability, transport carbon emissions, safety). A more
detailed breakdown of evaluation indicators is outlined in
the Methodology section at the end of this paper.
% T
ota
l Po
pu
lati
on
60
50
40
70
30
20
10
0
19501960
19701990
19802010
2000
80
90
100
F2030
F2020
Urban Rural
F2050
F2040
Source: United Nations, 2015.
Fig 1.3: Europe urban and rural population (% total 1950-2050)
% o
f p
op
ula
tio
n
0
4
8
12
16
20
2
6
18
14
10
Cities Towns and suburbs Rural areas
*The overcrowding rate describes the proportion of people living in an overcrowded dwelling, as defined by the number of rooms available to the household, the household’s size, as well as its members’ ages and their family situation. Source: Eurostat.
Fig 1.4: EU27: Overcrowding rate by degree of urbanisation (2015)*
2 Source: Inrix.
5
2. Connectivity scores and rankings
Fig 1.1 on page 3 shows our top-10 city performers
based on their connectivity scores and the graphic
below maps the 64 reviewed cities across Europe: the
larger the bubble the higher the connectivity score.
Top city performers
Paris, Berlin and Stuttgart top the total connectivity
rankings. Paris performs particularly well in Real-Time
Passenger Information (RTPI) coverage and green
transport modes, with 83% of journeys to work made
using public transport, cycling or walking.
German, French and Swiss cities dominate the top 10
positions. The common denominator is the relatively
higher levels of investment per capita on transport
infrastructure and maintenance.
Conversely, peripheral European cities, such as Naples,
Arhus, Montpellier and Seville, appear at the bottom
of the rankings. To dig deeper into these results, we
plotted enabler scores against effect scores by density
category (Fig 2.2).
Fig 2.1: Total connectivity score map
Paris
Barcelona
London
Rome
Manchester
Leipzig
BrusselsBristol
Edinburgh
Madrid
Cologne
Stuttgart
Amsterdam
BerlinHamburg
Munich
Dublin
Leeds
Naples
AntwerpGuildfordThe Hague
Lisbon
Sevilla
Glasgow
Milan
Cambridge
Marseille
Düsseldorf
Århus
Oslo
Nice
Bordeaux
Oxford
Hanover
Frankfurt
Mannheim
WarsawDortmund
Luxembourg
Vienna
Bremen
Copenhagen
Stockholm
Lyon
Helsinki
Lille
Urtrecht
Gothenburg
Zurich
Malmo
Toulouse
Bologna
Aberdeen
Dresden
Espoo
Prague
BirminghamRotterdam
Nantes
Eindhoven
Valencia
Montpellier
Nürnberg
Source: M&G Real Estate, December 2016.
6
We found that high-density cities generally score relatively
better when it comes to enabler indicators, while low-
density cities have higher effect scores. Medium-density
cities tend to fall somewhere in between.
However, there are notable exceptions in each density
category. In our view, it is these cities that, from a
connectivity perspective, hold the most promise for real
estate investors beyond Europe’s more liquid gateway
markets because they could represent a source of
latent value.
Enablers: Top city performers
Paris has the highest enabler score, followed by Berlin
and Stuttgart. Conversely, Montpellier, Prague and
Nuremberg have the lowest scores.
Among the high-density cities, London and Barcelona
are particularly strong in the areas of RTPI app coverage,
green transport mode provision and mobility strategy.
Barcelona’s score is high because it was one of the first
European Demonstration Cities to adhere to CIVITAS
objectives when the initiative was first launched in 2002.
The Catalan city’s Municipal Council for the Environment
and Sustainability also launched its ‘Agenda 21’ agenda
that year, whose commitments were renewed in 2013
and include plans to ‘improve mobility and make
pedestrian life a welcoming setting’.
Among medium-density cities, Stuttgart, Zurich and
Amsterdam also achieve high enabler scores. With
an average broadband speed of 85Mbps, Stuttgart
provides the fastest downloading speed by far across
the reviewed cities, boosting its Wi-Fi speed score.
Amsterdam ranks second with a Wi-Fi speed score of
80Mbps, which supports the Dutch capital’s portfolio of
smart city projects, including a public city dashboard that
displays updated statistics on transport, environment,
community, culture and security every 10 seconds3.
Zurich’s enabler score is boosted by its RTPI app
coverage indicator. Typically, tourist destinations such
as Berlin, Lisbon and London score relatively well on this
measure. Digital connectivity is also recognised as critical
infrastructure in the Mayor of London’s 2050 Plan, which
aims to improve connectivity in underserved areas.
Effects: Top city performers
Espoo, Nantes and Luxembourg – all low-density cities
– occupy the top-three positions in the effects rankings.
Bremen
Bremen, a top-10 ranked low-density city, scores relatively
highly in terms of average commute time (25 minutes),
safety and security (0.11 road deaths per 10,000
population), as well as low carbon emissions (25% due
Fig 2.2: Enabler vs effects scores by density category
Source: M&G Real Estate, December 2016.
100
90
80
70
60
50
40
30
20
10
00 40302010 50 60 70 80 90 100
Effects score
En
ab
lers
sco
re
High Density Medium Density Low Density
Paris
Barcelona
London
Rome
ManchesterLeipzig
BrusselsBristol
Valencia
Edinburgh
Madrid
Cologne
Stuttgart
Amsterdam
Berlin
Hamburg
Munich
Dublin
LeedsNaples
Antwerp
Guildford
Montpellier
The Hague
Lisbon
SevillaGlasgow
Milan
Cambridge
Marseille
Düsseldorf
Århus
Oslo
Nice
Bordeaux
Oxford
Hanover
Frankfurt
Mannheim
Warsaw
Dortmund
LuxembourgVienna
Bremen
Copenhagen
Stockholm
Rotterdam
Lyon
Helsinki
Lille Urtrecht
Gothenburg
Zurich
MalmoToulouse
BolognaAberdeen
Dresden
EspooPrague
Eindhoven
Nantes
Fig 2.3: Average city connectivity score by density category
Density Category
Total Connectivity
Enablers Effects
High 59 67 25
Medium 52 52 52
Low 44 40 58
Source: M&G Real Estate, December 2016
3Source: http://citydashboard.waag.org/
7
to transport). Bremen’s efforts in the field of promoting
cleaner and more sustainable public transport were
recognised when the city received a CIVITAS award in
2014 for “Urban mobility and social inclusion – Planning
accessibility for more sustainable cities”. A number of
transport-related engagement tools introduced in the
city, including an online geo-referenced consultation
platform, also helped Bremen to win the accolade.
In common with all the German cities we reviewed,
Bremen performs consistently well on transport emissions.
This is driven by the Low Emissions Zones (LEZs) it
introduced in 2008 with the aim of improving air quality
by restricting polluting vehicles within defined areas.
Aberdeen
Among the UK’s low-density cities, Aberdeen achieves
the highest score in terms of effects, boosted by
affordability (the cost of a monthly travel card on
public transport equates to 1.5% of monthly GDP per
capita) carbon emission (13% due to transport) and
award indicators.
In 2014, the European Commission awarded the city a
European Mobility Week award. Aberdeen’s Sustainable
Urban Mobility Plan was recognised for addressing
social and economic objectives including a focus on
sustainable transport. The plan was developed in close
consultation with citizens and stakeholders, with almost
500 people completing online surveys or providing
feedback through social media.
Vienna
Among the top-10 ranked medium-density cities, Vienna
scores relatively high on affordability (1.4% of GDP per
capita spent on public transport) and safety and security
(0.10 road deaths per 10,000 population). We understand
Vienna is in the process of creating a living lab that will
test designs and systems to implement intelligent traffic
solutions, green buildings, water management and a
smart grid infrastructure across the city. In the long
term, this initiative will serve to boost its score both in
terms of enabler as well as effect indicators, and could
see it climb our rankings when next updated.
8
3. Where is the value?
The following section builds on the previous analysis
by linking total connectivity scores to market yields by
density category, as shown in Fig 3.1 below. The aim
here is to support the investment decision-making
process by identifying relative pricing opportunities from
a connectivity perspective.
Analysis
The relationship between scores and market yields shows
that the more connected the city, the lower the yield.
Many of the cities that achieve high connectivity scores
are also among the most liquid investment markets.
High-density cities like Paris, London and Barcelona, for
example, achieve top-quartile total connectivity scores.
They also offer keen property yields, well below 5%.
Paris and London are the most liquid European markets,
attracting average annual investment volumes in excess
of €6 billion per annum since 20014.
Some medium-density cities, namely Stockholm, Munich
and Berlin also offer investors high connectivity scores at
a relatively keen price.
For the same top-quartile connectivity score, select
medium- and low-density cities offer higher property
yields. These include Amsterdam, Lyon and Rotterdam,
as well as Bremen, Luxembourg and Malmö. While
these are relatively less liquid markets, the maturity and
performance of their connectivity infrastructures can
offer yield discounts above 200 basis points compared
with high-density cities.
Among high-density cities, Naples is a clear loser in the
connectivity rankings and this is reflected in the higher
yield. Relatively higher yields are also reflected in the
bottom quartile connectivity scores of medium- and
low-density cities such as Antwerp, Montpellier and The
Hague. Nuremberg, Birmingham and Cologne are also
low-quartile performers but offer keen yields below 5%.
Clearly, while the relationship between connectivity and
yields is broadly downward trending, the scores are wide
ranging, highlighting the fact that a number of other
urbanisation and real estate drivers also contribute to
market pricing. These could include liquidity, a tight
supply-demand balance, or alternative density enablers
such as innovation.
When seeking value beyond traditional gateway markets,
we believe that investors should target cities that achieve
a combination of high enabler and effect scores (ideally
above 50). We believe this optimal balance of density
drivers is more likely to efficiently service densification
pressures and support strong property fundamentals.
Of the reviewed cities, 18 fall into this category of
relatively high enabler and effect scores. They comprise
a range of high-, medium- and low-density cities and are
shown in Figure 3.2.
At 6.0%, Toulouse offers the highest yield. It is also easily
the most southerly city in the list, followed by Lyon. Five
of the cities are in the Nordic region, with another five in
Germany, including relatively high-yielding Bremen. The
UK has only one entry in the shape of Bristol.
Fig 3.1: Yield vs connectivity scores by density category
Source: PMA, M&G Real Estate, December 2016.
8.0
7.0
6.0
5.0
4.0
3.00 40302010 50 60 70 80 90 100
Weighted connectivity score
Pri
me
offi
ce y
ield
(e
nd
20
15
)
High Density Medium Density Low Density
Paris
Barcelona
London
Manchester
LeipzigBrussels
Bristol
Edinburgh
Madrid
Cologne
StuttgartAmsterdam
BerlinHamburg
Munich
Dublin
Leeds
Naples
Antwerp
Guildford
Montpellier
The Hague
Lisbon
Glasgow
MilanCambridge
Marseille
Düsseldorf Oslo
Bordeaux
Hanover
Frankfurt
Mannheim WarsawDortmund
Luxembourg
Vienna
Bremen
Copenhagen
Helsinki
Stockholm
RotterdamLyonLille
Urtrecht
Gothenburg
Zurich
Malmo
Toulouse
Bologna
Aberdeen
Dresden
Espoo
Prague
Nantes
NurembergBirmingham Rome
4 Source: CBRE, DTZ, Eurostat, M&G Real Estate.
9
Fig 3.2: All round connectivity winners
Enabler score: 51 to 100
Effect score: 51 to 100
City Market yield (%) City Market yield (%)
Toulouse 6.0 Helsinki 4.9
Warsaw 5.7 Copenhagen 4.5
Bremen 5.6 Stuttgart 4.5
Rotterdam 5.5 Gothenburg 4.5
Dresden 5.4 Vienna 4.4
Lyon 5.3 Berlin 4.3
Luxembourg 5.3 Frankfurt 4.2
Malmo 5.3 Stockholm 3.8
Bristol 5.0 Zurich 3.3
Key: High Density, Medium Density, Low Density
Fig 3.3: How the other cities fare further down the ranking
Enabler score: 0 to 50
Effect score: 51 to 100
Enabler score: 51 to 100
Effect score: 0 to 50
Enabler score: 0 to 50
Effect score: 0 to 50
City Market yield (%) City Market yield (%) City Market yield (%)
Bologna 6.8 Lisbon 5.9 Naples 8.0
Utrecht 6.5 Brussels 5.2 Antwerp 6.8
Nantes 6.4 Hannover 5.2 Montpellier 6.5
Espoo 6.4 Amsterdam 5.1 The Hague 6.3
Aberdeen 6.0 Rome 4.8 Leeds 5.8
Bordeaux 6.0 Milan 4.5 Dortmund 5.5
Marseille 5.8 Dublin 4.4 Edinburgh 5.3
Mannheim 5.4 Barcelona 4.3 Glasgow 5.3
Prague 5.4 Hamburg 4.2 Leipzig 5.2
Lille 5.3 Madrid 4.0 Guildford 5.0
Cambridge 4.8 Munich 3.8 Nuremberg 5.0
Düsseldorf 4.4 Paris 3.5 Manchester 4.8
Oslo 4.3 London 3.5 Birmingham 4.8
Cologne 4.5
Key: High Density, Medium Density, Low Density
Source: M&G Real Estate December 2016, PMA March 2016.
10
HELSINKI: Potential connectivity climber
Helsinki comes in at number 21 in our rankings but has the potential to climb higher in the years ahead due to
connectivity-friendly initiatives. By 2025 it hopes to make its centre car-free—not by banning cars but by building
a transport system that renders them redundant.
Finland’s sense of shared national endeavour is important here. To help roll out an ambitious new app that aims
to provide the end-user with a bespoke and seamless solution in real time to all its transport problems, the city
government is rewriting legislation to bring the laws covering different modes of transport into harmony. The app,
which has been developed by MaaS Global (short for Mobility as a Service), is called Whim and the residents of
Helsinki will soon be able to use it to travel across the city from early 2017.
Whim mixes and matches a variety of participating public and private transport services. For example, Whim could
suggest a bicycle from the city’s bike-share scheme (if one is near your front door), followed by a train and then a
taxi; an on-demand bus (“hail” it on the app and it will come and pick you up); or a one-way car-share to a tram and
a rented “e-bike” with a small electric motor. Once a route has been chosen it will make all the bookings needed,
as well as ensuring that hire vehicles are available and public-transport sections are running on time. Costs will be
displayed for every option, making clear the trade-offs between speed, comfort, and price.
Customers will be able to buy one-off journeys or ‘bundles’ modelled on mobile-phone contracts, allowing for a
certain amount of travel each month. For perhaps €95 a month it might offer free city-wide public transport, 100km
of local taxi use, 500km of car rental, and 1,500km on national public transport.
Whim is precisely the type of technology that is changing the way we interact with the urban landscape, with
implications for the real estate investment community. This technology could soon be replicated in England with
suggestions of Birmingham as the next possible test case.
Source: MIT Technology Review, The Economist, September 2016.
Implications for real estate investment
For real estate investors seeking value, factors such as
liquidity and supply-demand imbalances always need to
be evaluated. But a city’s connectivity performance is an
increasingly important factor too.
Access to cheap live transit data looks set to dramatically
improve the way residents travel across urban centres. At
a city level, low-cost intelligent transport solutions should
radically improve digital and physical infrastructures,
contributing to economic growth. As such, the scores of
more peripheral European markets have the potential to
improve substantially.
Technological advances can make smaller capital cities
like Copenhagen and Helsinki and regional cities like
Bremen and Malmö more attractive places to work and
live. The analysis developed here aims to identify those
emerging locations that, from a connectivity perspective,
are best-placed to deliver sustainable property
fundamentals and superior pricing opportunities.
The M&G Real Estate Connectivity Rankings will likely
see risers and fallers in the years ahead as cities adopt
smart technologies to withstand the evolving challenges
that come with city living and working, and – of course
– urban real estate investment. We highlight one such
potential climber below.
11
Appendix 1. City performance table
Country City DensityCategory
TotalRank
EnablerRank
EffectRank
TotalScore
Enabler Score
EffectScore
France Paris High 1 1 56 100 100 13
Germany Berlin Medium 2 2 31 98 98 52
Germany Stuttgart Medium 3 3 28 97 97 57
Switzerland Zurich Medium 4 5 14 95 94 79
Sweden Stockholm Medium 5 8 15 94 89 78
Netherlands Amsterdam Medium 6 7 36 92 90 44
Germany Munich Medium 7 6 39 90 92 40
UK London High 8 4 62 89 95 3
Germany Bremen Low 9 11 5 87 84 94
Luxembourg Luxembourg Low 10 18 4 86 73 95
Germany Hamburg Medium 11 10 37 84 86 43
France Lyon Medium 12 13 12 83 81 83
Austria Vienna Medium 13 15 8 81 78 89
Sweden Malmo Low 14 24 3 79 63 97
Spain Barcelona High 15 9 59 78 87 8
Ireland Dublin Low 16 12 42 76 83 35
Netherlands Rotterdam Medium 17 17 17 75 75 75
Germany Frankfurt Medium 18 14 30 73 79 54
Denmark Copenhagen High 19 21 16 71 68 76
Sweden Gothenburg Low 20 20 22 70 70 67
Finland Helsinki Low 21 28 7 68 57 90
UK Oxford Medium 22 19 34 67 71 48
France Nantes Low 23 41 2 65 37 98
Portugal Lisbon High 24 16 47 63 76 27
Poland Warsaw Medium 25 27 26 62 59 60
France Toulouse Low 26 30 18 60 54 73
Germany Hannover Medium 27 25 35 59 62 46
Netherlands Utrecht Medium 28 39 9 57 40 87
Germany Dresden Low 29 31 19 56 52 71
Spain Madrid High 30 22 44 54 67 32
Italy Bologna Medium 31 44 6 52 32 92
Italy Milan High 32 23 52 51 65 19
France Lille Low 33 36 21 49 44 68
UK Aberdeen Low 34 45 10 48 30 86
UK Cambridge Low 35 37 25 46 43 62
Norway Oslo Low 36 43 20 44 33 70
Belgium Brussels High 37 29 48 43 56 25
Finland Espoo Low 38 61 1 41 5 100
Germany Düsseldorf Medium 39 38 32 40 41 51
Netherlands Eindhoven Medium 40 54 11 38 16 84
Connectivity rankings
12
Country City DensityCategory
TotalRank
EnablerRank
EffectRank
TotalScore
Enabler Score
EffectScore
Germany Leipzig Low 41 33 49 37 49 24
Italy Rome Medium 42 26 63 35 60 2
Germany Mannheim Medium 43 46 27 33 29 59
Spain Valencia High 44 34 54 32 48 16
UK Bristol Low 45 32 55 30 51 14
Germany Dortmund Medium 46 47 33 29 27 49
UK Manchester Medium 47 35 57 27 46 11
France Marseille Low 48 49 29 25 24 56
France Nice Low 49 52 24 24 19 63
France Bordeaux Medium 50 55 23 22 14 65
UK Edinburgh Low 51 42 50 21 35 22
UK Guildford Low 52 53 38 19 17 41
Germany Cologne Medium 53 48 51 17 25 21
Netherlands The Hague Low 54 51 43 16 21 33
UK Birmingham Medium 55 40 64 14 38 0
Belgium Antwerp Medium 56 50 53 13 22 17
Czech Republic Prague Medium 57 63 13 11 2 81
UK Glasgow Medium 58 57 41 10 11 37
Italy Naples High 59 58 45 8 10 30
Denmark Århus Low 60 60 46 6 6 29
UK Leeds Low 61 56 61 5 13 5
Spain Sevilla Medium 62 59 60 3 8 6
France Montpellier Low 63 62 58 2 3 10
Germany Nuremberg Medium 64 64 40 0 0 38
Source: M&G Real Estate, December 2016.
Connectivity rankings (continued)
13
Appendix 2. Methodology
City classification
The reviewed cities are classified into density categories,
as outlined below, and the full list appears at the end of
this section.
For the purpose of density classification, the population
and city area indicators were calculated within the
Local Administrative Unit (LAU) as defined by Eurostat
in 2016. A city is an LAU when the majority of the
population lives in an urban centre of at least 50,000
inhabitants.
City ranking and scores
For the ranking exercise, connectivity indicators for
each city were measured, which were further split into
enablers and effects as outlined in Appendices 3 and 4.
Please refer to Appendix 8 for references to data sources.
Enablers
The enabler indicators measure connectivity maturity
including Wi-Fi speed, vision and strategy for future
mobility, RTPI app coverage (e.g. Citymapper, Ally,
Moovit), share of journeys to work using green transport
modes, length of dedicated cycle paths per square
kilometre, electric vehicle chargers within a 10km radius,
car and ride sharing schemes.
Effects
The effect indicators measure connectivity performance,
i.e. the degree to which connectivity-related goals
are fulfilled in an effective and efficient manner. This
includes affordability in terms of price of a monthly
public transport ticket, share of transport-related carbon
emissions, passenger satisfaction, average commute
time to work, number of hours wasted in traffic per
annum, public transport speed and number of road
fatalities per inhabitant.
Rank and score
For each indicator we defined a point scale, with the
maximum and minimum end of the scale being defined
by the best and worst performance of the 64 cities. For
each indicator, best performing cities were allocated up
to a maximum of 100 and a minimum of 0 points.
These scores were further weighted as outlined in
Appendixes 3 and 4. Among the enabler indicators, we
favoured provision of digital infrastructure such as Wi-Fi
speed, transport app coverage as well as availability of
green transport modes. Among the effect indicators,
we favoured cities that favoured inclusivity of transport
through high affordability scores as well as strong safety
and environmental performance.
The city that achieved the top score on all the weighted
enabler and effect indicators achieved a score of 100.
The cities were also ranked from 1 to 64, corresponding
to the best and worst performer.
Yields
Prime office yields were used as a proxy for All Property
yields as these sector yields were available for all the
reviewed cities.
Average city connectivity score by density category
Density Category
Density criteria
High Above 5,000 residents per square km
Medium Between 2,001 and 4,999 residents per square km
Low Up to 2,000 residents per square km
14
City
con
nect
ivit
y m
etric
s: b
reak
dow
n of
ena
bler
s
Enab
ler i
ndic
ator
sW
eigh
ting
Uni
t of m
easu
reSc
ore
ratio
nale
Dat
a so
urce
Wi-
Fi s
pe
ed
12
.5%
Bro
ad
ba
nd
ave
rag
e d
ow
nlo
ad
sp
ee
d M
bp
sT
he
hig
he
r th
e b
ett
er
Hy
pe
rop
tic
stu
dy/
Sp
ee
d t
est
Ho
tsp
ots
7.5
%Fr
ee
ho
tsp
ots
pe
r ca
pit
aT
he
hig
he
r th
e b
ett
er
Ho
tsp
ot
loca
tio
ns
Publ
ic T
rans
port
Sh
are
of
jou
rne
ys
to w
ork
usi
ng
‘gre
en
’ mo
de
s
10
.0%
% o
f jo
urn
ey
s b
y p
ub
lic t
ran
spo
rt, w
alk
ing
an
d c
yclin
gT
he
hig
he
r th
e b
ett
er
Eu
rost
at
urb
an
au
dit
Len
gth
of
de
dic
ate
d c
ycle
pa
ths/
LA
U5
.0%
Len
gth
of
bic
ycle
ne
two
rk -
km
/Lo
cal A
dm
inis
tra
tive
Un
it (
LA
U)
Th
e h
igh
er
the
be
tte
rE
uro
sta
t u
rba
n a
ud
it
Tra
nsi
t w
eb
ap
ps
12
.5%
Re
al-T
ime
Pa
sse
ng
er
Info
rma
tio
n (
RT
PI)
ap
p
cove
rag
e e
.g. C
ity
ma
pp
er,
Ally
, Mo
ovi
t
RT
PI
ap
ps.
Th
e m
ore
co
vera
ge
the
be
tte
r
Cit
ym
ap
pe
r, M
oo
vit,
Ally
Ap
p, G
oo
gle
Tra
nsi
t
Urb
an
mo
bili
ty s
tra
teg
y5
.0%
CIV
ITA
S m
em
be
rsh
ip: D
em
on
stra
tio
n (
co-f
ina
nce
d
by
the
EU
) o
r n
etw
ork
(se
lf-f
ina
nce
d)
city
+ C
itie
s th
at
take
pa
rt in
EU
RO
PE
AN
MO
BIL
ITY
WE
EK
.
Po
int
sco
red
if c
ity
is a
CIV
ITA
S m
em
be
r/E
MW
ho
st
CIV
ITA
S, E
UR
OP
EA
NM
OB
ILIT
YW
EE
K
Infr
ast
ruct
ure
sp
en
d7.
5%
Tra
nsp
ort
In
fra
stru
ctu
re I
nve
stm
en
t a
nd
Ma
inte
na
nce
Sp
en
din
g p
er
cap
ita
Th
e h
igh
er
the
be
tte
rO
EC
D
Priv
ate
Tran
spor
t
Ele
ctri
c ve
hic
le c
ha
rge
rs2
.5%
Tota
l ava
ilab
le w
ith
in a
10
km r
ad
ius
of
the
cit
y co
reT
he
hig
he
r th
e b
ett
er
Op
en
Ch
arg
e M
ap
Rid
e s
ha
rin
g
5.0
%M
em
be
rsh
ip o
f ri
de
sh
ari
ng
sch
em
es
e.g
. Ub
er
Th
e e
arl
ier
join
ed
th
e b
ett
er
Ub
er
Ca
r sh
ari
ng
2.5
%M
em
be
rsh
ip o
f ca
r sh
ari
ng
sch
em
es
e.g
. Ca
r2g
o,
Dri
veN
ow
, ub
erP
OO
L
Th
e m
ore
co
vera
ge
th
e b
ett
er
Dri
veN
ow
, Ca
r2g
o, u
be
rPO
OL
70%
Ap
pe
nd
ix 3
. En
ab
ler
me
tric
s
15
City
con
nect
ivit
y m
etric
s: br
eakd
own
of e
ffec
ts
Effe
ct in
dica
tors
Wei
ghtin
gU
nit o
f mea
sure
Scor
e ra
tiona
leD
ata
sour
ceA
ffo
rda
bili
ty5
.0%
Co
st o
f a
co
mb
ine
d m
on
thly
tic
ket
(all
mo
de
s o
f
pu
blic
tra
nsp
ort
) fo
r 5
-10
km
in t
he
ce
ntr
al z
on
e -
EU
R/G
DP
pe
r ca
pit
a
Th
e lo
we
r th
e b
ett
er
Eu
rost
at
urb
an
au
dit
Tra
nsp
ort
ca
rbo
n e
mis
sio
ns
2.5
%%
sh
are
ca
rbo
n e
mis
sio
ns
rela
ted
to
tra
nsp
ort
Th
e lo
we
r th
e b
ett
er
C4
0 C
itie
s C
lima
te L
ea
de
rsh
ip G
rou
p
Sa
tisf
act
ion
wit
h t
ran
spo
rt n
etw
ork
2.5
%%
sh
are
of
Ve
ry S
ati
sfie
d p
eo
ple
su
rve
yed
Th
e h
igh
er
the
be
tte
rE
uro
pe
an
Co
mm
issi
on
Aw
ard
s5
.0%
Win
ne
r/fi
na
list
of
the
CIV
ITA
S/
Eu
rop
ea
n M
ob
ility
We
ek
aw
ard
s
Nu
mb
er
of
tim
es
rece
ive
d t
he
be
tte
r
CIV
ITA
S, E
UR
OP
EA
NM
OB
ILIT
YW
EE
K
Pu
blic
tra
nsp
ort
sp
ee
d2
.5%
Urb
an
bu
s o
r tr
am
sp
ee
d (
km/h
ou
r)T
he
hig
he
r th
e b
ett
er
EM
TA
ba
rom
ete
r
Co
mm
ute
to
wo
rk5
.0%
Min
ute
sT
he
low
er
the
be
tte
rU
rba
n T
ran
spo
rt F
act
Bo
ok
Tra
ffic
co
ng
est
ion
2.5
%A
nn
ua
l ho
urs
wa
ste
d in
tra
ffic
Th
e lo
we
r th
e b
ett
er
INR
IX
Sa
fety
an
d S
ecu
rity
5.0
%P
eo
ple
kill
ed
in r
oa
d a
ccid
en
ts p
er
cap
ita
Th
e lo
we
r th
e b
ett
er
Eu
rost
at
urb
an
au
dit
30%
Ap
pe
nd
ix 4
. Eff
ect
me
tric
s
16
Appendix 5: Density categories
Country City Density (LAU population/LAU)* Density categorySpain Barcelona 16,316 High
France Paris 8,800 High
Italy Naples 8,434 High
Denmark Copenhagen 7,664 High
Belgium Brussels 7,279 High
Italy Milan 7,273 High
Portugal Lisbon 6,172 High
Spain Valencia 5,841 High
Spain Madrid 5,225 High
UK London 5,177 High
Spain Sevilla 4,930 Medium
Netherlands Amsterdam 4,817 Medium
Sweden Stockholm 4,596 Medium
Germany Munich 4,531 Medium
Switzerland Zurich 4,377 Medium
Austria Vienna 4,196 Medium
UK Birmingham 4,066 Medium
Germany Berlin 3,837 Medium
UK Glasgow 3,405 Medium
Netherlands Utrecht 3,401 Medium
UK Oxford 3,370 Medium
Poland Warsaw 3,334 Medium
Netherlands Rotterdam 2,951 Medium
Germany Stuttgart 2,914 Medium
Germany Frankfurt 2,824 Medium
Germany Düsseldorf 2,754 Medium
Italy Bologna 2,730 Medium
Germany Nuremberg 2,677 Medium
France Lyon 2,604 Medium
Germany Cologne 2,552 Medium
Germany Hannover 2,539 Medium
Czech Republic Prague 2,513 Medium
Belgium Antwerp 2,505 Medium
Netherlands Eindhoven 2,491 Medium
Germany Hamburg 2,312 Medium
Italy Rome 2,190 Medium
UK Manchester 2,123 Medium
France Bordeaux 2,078 Medium
Germany Dortmund 2,052 Medium
Germany Mannheim 2,047 Medium
City density classification
17
Country City Density (LAU population/LAU)* Density categorySweden Malmo 1,947 Low
Luxembourg Luxembourg 1,940 Low
France Lille 1,895 Low
UK Bristol 1,848 Low
UK Edinburgh 1,838 Low
Germany Leipzig 1,788 Low
France Marseille 1,729 Low
Germany Bremen 1,686 Low
Germany Dresden 1,617 Low
France Toulouse 1,583 Low
UK Leeds 1,377 Low
Norway Oslo 1,374 Low
Ireland Dublin 1,370 Low
UK Aberdeen 1,216 Low
France Nantes 1,183 Low
France Nice 1,175 Low
Sweden Gothenburg 1,155 Low
France Montpellier 1,029 Low
Finland Helsinki 856 Low
Netherlands The Hague 826 Low
Denmark Århus 682 Low
UK Guildford 518 Low
Finland Espoo 494 Low
UK Cambridge 309 Low
* Local Administrative Unit (LAU) as defined by Eurostat. A city is an LAU when the majority of the population lives in an urban centre
of at least 50 000 inhabitants.
Source: Eurostat 2016, M&G Real Estate.
City density classification (continued)
18
Appendix 6: Connectivity scores vs yields
Total Connectivity Score Yield (%, end 2015)
Paris 100 3.5
Berlin 98 4.3
Stuttgart 97 4.5
Zurich 95 3.3
Stockholm 94 3.8
Amsterdam 92 5.1
Munich 90 3.8
London 89 3.5
Bremen 87 5.6
Luxembourg 86 5.3
Hamburg 84 4.2
Lyon 83 5.3
Vienna 81 4.4
Malmo 79 5.3
Barcelona 78 4.3
Dublin 76 4.4
Rotterdam 75 5.5
Frankfurt 73 4.2
Copenhagen 71 4.5
Gothenburg 70 4.5
Helsinki 68 4.9
Nantes 65 6.4
Lisbon 63 5.9
Warsaw 62 5.7
Toulouse 60 6.0
Hannover 59 5.2
Utrecht 57 6.5
Dresden 56 5.4
Madrid 54 4.0
Bologna 52 6.8
Milan 51 4.5
Lille 49 5.3
Aberdeen 48 6.0
Cambridge 46 4.8
Oslo 44 4.3
Brussels 43 5.2
Espoo 41 6.4
Düsseldorf 40 4.4
Leipzig 37 5.2
Rome 35 4.8
Mannheim 33 5.4
Bristol 30 5.0
19
Total Connectivity Score Yield (%, end 2015)
Dortmund 29 5.5
Manchester 27 4.8
Marseille 25 5.8
Bordeaux 22 6.0
Edinburgh 21 5.3
Guildford 19 5.0
Cologne 17 4.5
The Hague 16 6.3
Birmingham 14 4.8
Antwerp 13 6.8
Prague 11 5.4
Glasgow 10 5.3
Naples 8 8.0
Leeds 5 5.8
Montpellier 2 6.5
Nuremberg 0 5.0
Source: M&G Real Estate, December 2016, PMA March 2016.
20
For Investment Professionals only. This document is for investment professionals only and should not be passed to anyone else as further distribution might be restricted or illegal in certain jurisdictions. The distribution of this document does not constitute an offer or solicitation. Past performance is not a guide to future performance. The value of investments can fall as well as rise. There is no guarantee that these investment strategies will work under all market conditions or are suitable for all investors and you should ensure you understand the risk profile of the products or services you plan to purchase. This document is issued by M&G Investment Management Limited (except if noted otherwise below). The services and products provided by M&G Investment Management Limited are available only to investors who come within the category of the Professional Client as defined in the Financial Conduct Authority’s Handbook. They are not available to individual investors, who should not rely on this communication. Information given in this document has been obtained from, or based upon, sources believed by us to be reliable and accurate although M&G does not accept liability for the accuracy of the contents. M&G does not offer investment advice or make recommendations regarding investments. Opinions are subject to change without notice. M&G Investments and M&G Real Estate are business names of M&G Investment Management Limited and are used by other companies within the Prudential Group. M&G Investment Management Limited is registered in England and Wales under numbers 936683 with its registered office at Laurence Pountney Hill, London EC4R 0HH. M&G Investment Management Limited is authorised and regulated by the Financial Conduct Authority. M&G Real Estate Limited is registered in England and Wales under number 3852763 with its registered office at Laurence Pountney Hill, London EC4R 0HH. M&G Real Estate Limited forms part of the M&G Group of companies. M&G Investment Management Limited and M&G Real Estate Limited are indirect subsidiaries of Prudential plc of the United Kingdom. Prudential plc and its affiliated companies constitute one of the world’s leading financial services groups and is not affiliated in any manner with Prudential Financial, Inc, a company whose principal place of business is in the United States of America. DEC 17 / W252007
Vanessa Muscarà Senior Research Analyst
+44 (0)20 7548 6714
Richard Gwilliam Head of Property Research
+44 (0)20 7548 6863
Christopher Andrews, CFA Head of Client Relationships and Marketing, Real Estate
+(65) 6436 5331
For more informationLucy Williams Director, Institutional Business UK and Europe, Real Estate
+44 (0)20 7548 6585
Stefan Cornelissen Director of Institutional Business Benelux, Nordics and Switzerland
+31 (0)20 799 7680
www.mandg.com/realestate