THINK Europe: Picking Tomorrow’s World Cities

Data generating art Using data from the GPD per capita, growth and size chart in this report, the graphic represents a spatial analysis of the GDP size of various cities across Europe.

1

THINK Europe: Picking Tomorrow’s World cities

This document is solely for the use of professionals and is not for general public distribution.

Why cities?

57%

THINK Europe: Picking Tomorrow’s World cities

Zurich

Hamburg

16%

Copenhagen

23% 23% 21%

Stuttgart

28%

Dublin

Helsinki

Stockholm

Brussels

Geneva

Basel

Munich

41% 39% 37% 36% 34% 32% 32%

Source: Oxford Economics, 2014

Fig.2: Cities are younger (proportion of population under the age of 40, difference to national level)

6.1% 6.0%

Birmingham

Sofia

Belfast

Geneva

Oslo

Manchester

Lille

Brussels

Málaga

Stockholm

Munich

Hamburg

3.9% 3.7% 3.5% 3.5% 3.3% 3.2% 3.1% 3.0% 2.8% 2.8% 2.7% 2.5% 2.4% 2.2%

Sevilla

Leeds

London

Palermo

Paris

Murcia

4.4% 4.3% 4.2%

Helsinki

6.5%

Source: Oxford Economics, 2014

2

Düsseldorf

Amsterdam

London

Edinburgh

Milan

50% 48% 47% 47%

Frankfurt

63%

Naples

As we have explored these megatrends, it has become apparent that their impact will be much more notable, for better or worse, at the city level, as opposed to nationally. Therefore, our global strategic advice is now centred on cities, not countries, meaning we can give investors more clarity as to what a portfolio might look like. This approach is consistent with the way occupiers think about their requirements and representation. It means that compelling opportunities do not get missed due to negative country–level perception, and vice versa. We have adopted an innovative, two–pronged approach to top-down analysis, capturing both structural megatrends and tactical real estate fundamentals, to identify “futureproof” cities.

Fig.1: Cities are more productive (GDP per capita, difference to national level)

Paris

Challenging market conditions and evolving investor requirements, means we are increasingly looking at longer term drivers of real estate performance. Megatrends — notably urbanisation, rising middle classes, ageing population, technology, and the shift of economic power from the West — are having a major impact on the built environment and will have significant implications on demand for real estate. These trends are an important component of our global research; we have analysts assigned to understanding each of them. While short–term performance of real estate will continue to be determined by economic cycles, there is a risk that these will mask the longer term erosion of value as megatrends play out. Understanding long-term structural trends will be key to preserving value and growth.

A strategy for Europe

This approach is not at the exclusion of traditional measures of real estate attractiveness. We also filter all the cities through our global risk model, which scores locations according to liquidity, transparency, income security and volatility; again, all long-term measures of attractiveness. This process has helped us filter over 200 cities in Europe, down to under 50. We believe these cities have the ability to attract talent, tourists and international tenants, based on long-term fundamentals. They are then grouped according to their real estate fundamentals and growth prospects. For core investment strategies, we place a greater emphasis on those cities that score well on key fundamentals today (Defensive Cities), and naturally want to focus on those that score well both today and tomorrow (Defensive Growth Cities). These are leading cities today that we expect will capture an even greater share of global output and demand in the future.

Fig.3: GDP: Per capita, growth and size

160% Bursa

Size of bubble represents size of GDP

Gaziantep Izmir Istanbul

140% Antalya

Ankara

120% Konya GDP growth (%, 2010-2030)

We have scored a number of European cities according to the qualities that make them attractive to people and occupiers, today and in the future. This first stage of our filter process is not about real estate investment fundamentals, but purely about finding economically and environmentally future-proof cities. Cities are scored according to their size, affluence, age profile, adoption of technology and quality of life. And as we are looking for long-term investment opportunities, they are also scored according to the growth potential for all of the above.

Bucharest

Adana 100%

Sofia Cracow

Warsaw

Bratislava 80%

Lódz WroclawPoznan

London Edinburgh Dublin

Prague

Reykjavik Manchester Bristol Budapest Nicosia Munich Leeds - Bradford Toulouse Gothenburg Málaga Copenhagen Szczecin Nürnberg Madrid Zagreb Helsinki Lyon Berlin Hannover Leipzig Amsterdam Murcia Stuttgart Bordeaux Hamburg Dresden Zaragoza Brussels Paris Marseille Bremen Vienna Dortmund Nice -CannesRotterdam Barcelona Lille Duisburg Sevilla Liege Antwerp Frankfurt Düsseldorf StrasbourgMilan Valencia (Spain) Thessaloniki Athens The Hague Rome Cologne Lisbon Bergamo Essen Porto Palermo Turin Genova Naples

60%

40%

20%

0% 0

20,000

40,000

60,000

GDP per capita ($) Source: Oxford Economics, 2014

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THINK Europe: Picking Tomorrow’s World cities

Stockholm

Oslo

Zurich

80,000

100,000

A strategy for Europe (continued)

An obvious question here is, why would we not just focus on perhaps the 10 largest Defensive/Defensive Growth Cities?

16 14 12 10 8 6 4

Budapest

Warsaw

Izmir

Lisbon

Vienna

Stuttgart

Hamburg

Munich

Birmingham

Athens

Rome

Berlin

Naples

Milan

Barcelona

Ankara

Madrid

Paris

2 0 Istanbul

In all categories we classify cities as Tier 1 and 2. This predominantly relates to their size and the scale of opportunity we see there, rather than their attractiveness. We would anticipate a pan–European portfolio being biased towards Tier 1 Cities in the Defensive and Defensive Growth categories based on market size and risk profile.

Fig.4: Scale: population (million, 2014)

London

There are some cities which do not score well in traditional real estate terms today, due to illiquidity, lack of transparency or market size, but whose growth rates cannot be ignored (Growth Cities). These are the cities whose position in the hierarchy is expected to change markedly over the next couple of decades, in terms of economic output or consumer demand. In turn, they should see their perception as real estate investment markets improve and enjoy, over the longer term, a structural correction in both rents and yields. Investments in these markets need to be highly selective, but made smartly and ahead of the curve to enhance portfolio returns.

Source: Oxford Economics, 2014

Fig.5: Productivity: GDP per capita ($, 000s, 2014)

120 100 80 60 40 20

Source: Oxford Economics, 2014 4

THINK Europe: Picking Tomorrow’s World cities

Gothenburg

Hamburg

Stuttgart

Brussels

London

Dublin

Edinburgh

Munich

Helsinki

Frankfurt

Düsseldorf

Aberdeen

Copenhagen

Paris

Amsterdam

Stockholm

Zurich

Oslo

Geneva

Basel

0

Growth Cities improve diversification

160% 42 City rank 2030: total GDP

45

64

13

21

7

40%

36

40

26

31

50

5

49

51

Gothenburg

1

Toulouse

68

Munich

23

60%

Bristol

74

80%

Leeds

27

100%

Manchester

3

120%

Budapest

140%

20% Prague

Stockholm

Dublin

Oslo

Edinburgh

London

Bratislava

Warsaw

Sofia

Bucharest

Ankara

0% Izmir

Investing across different real estate sectors can offer further diversification benefits. Not all of our cities are appropriate for all sectors, and for some we might only target one sector, whilst actively avoiding others. Broadly speaking, the Tier 1 Cities should be attractive for all sectors, while in the Tier 2 Cities we would target mainly retail or logistics. The Growth Cities will likely be focused on retail, their growth really being underpinned by consumer and tourist economies.

Fig.6: Fastest growing cities: GDP growth (% change, 2010-2030)

Istanbul

In addition to identifying long-term performance, we also want to maximise the benefits of diversification by location, sector and drivers of demand. The largest real estate markets are typically closely-correlated, driven by financial and business services, and so offer little benefit to geographical diversification. Seeking a balance of occupiers by industry, should help lower volatility of rental growth, and avoid over-dependence on any one sector. Investments underpinned by financial and business services, for example, should be complemented with investments in resource or commodity-led cities. Our Tier 2 and Growth Cities tend to offer greater diversification benefits to real estate investors — hence their inclusion in our target list — and in the case of the Growth Cities, should also enhance returns.

Source: Oxford Economics, 2014

Fig.7: Tomorrow’s World cities: Size of retail market 2030 (US$bn) (US$bn) 700

60

600

50

500

40

400

30

300 200

20

100

10

All retail sales 5

THINK Europe: Picking Tomorrow’s World cities

Fashion & Footwear (RHS)

Source: Oxford Economics, 2014

Frankfurt

Izmir

Stockholm

Warsaw

Vienna

Stuttgart

Hamburg

Berlin

Rome

Athens

Manchester

Key

Birmingham

Milan

Ankara

Munich

Barcelona

Madrid

Paris

Istanbul

0 London

0

Market timing While we advocate a top-down strategy that is underpinned by long-term fundamentals, structural growth and risk management, market timing, cycles and short–term pricing will of course play an important role in day–to–day portfolio management. At any one point in time, some markets will look more attractive than others, based on where they are in their cycle. While our universe of 42 cities will remain unchanged, our short– to medium–term buy, or indeed sell, priorities, will change regularly to enhance performance via early cycle entry. We conduct five–year sector–level, city forecasts for all our Defensive and Defensive Growth Cities. Forecasting the Growth Cities is more of a challenge, but the opportunity in these markets is structural rather than cyclical, meaning short–term forecasts are less relevant. For all cities, our global risk model gives us a required return hurdle allowing us to assess the relative attractiveness of individual opportunities.

A city–based real estate strategy, underpinned by long–term, structural trends, that strikes the right balance of risk and diversification, while taking advantage of short–term pricing opportunities, should enjoy above–average portfolio-level returns, lower–than–average volatility, and modest downside risk, for long–term investors.

Alice Breheny Global Co-Head of Research

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THINK Europe: Picking Tomorrow’s World cities

Fig. 8: GDP breakdown by industry group

Consumer services

Transport & communication

Consumer services

Financial & business services London

Industry

Public services

Madrid

Public services

7

Industry

Public services

Industry

Transport & communication

Frankfurt

Public services

Financial & business services

Industry

Transport & communication

Bordeaux

Industry

THINK Europe: Picking Tomorrow’s World cities

Transport & communication

Public services

Financial & business services

Istanbul

Public services

Consumer services

Financial & business services

Industry

Consumer services

Gothenburg

Public services

Consumer services

Transport & communication

Paris

Financial & business services

Transport & communication

Consumer services

Financial & business services

Public services

Financial & business services

Transport & communication

Consumer services

Transport & communication

Consumer services

Industry

Consumer services

Financial & business services Stuttgart

Industry

Transport & communication

Public services

Financial & business services Leeds

Industry

City focus: London London

UK

Rank within European cities*

14,620

-

1

Population growth (2010-2030, %)

22%

13%

7

GDP 2014 ($bn)

865

-

1

59,143

40,092

16

GDP growth (2010-2030, %)

77%

56%

15

Retail sales 2014 ($bn)

395

-

1

27,041

23,798

2

65%

53%

15

Population (000)

GDP per capita 2014 ($)

Retail sales per capita 2014 ($) Retail sales growth (2010-2030, %) Clothing & footwear sales 2014 ($bn)

24

1

Clothing & footwear per capita 2014 ($)

1,608

1,491

5

Clothing & footwear sales growth (2010-2030, %)

178%

156%

1

% population under the age of 65

80%

82%

13

2,423

-

1

Number of households with income >$100,000 2030 (000) *Rank out of 100 European cities (excludes Russia and Ukraine)

GDP per capita

137%

GDP growth 2010-2030

Source: Oxford Economics, 2014 8

THINK Europe: Picking Tomorrow’s World cities

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Key $100,000+ $70-100,000 $35-70,000 $20-35,000 $0-20,000

2010

2030

Age structure (% of population) 80+ 70-74 60-64 50-54 40-44 30-34 20-24 10-14 0-4

Key London UK

-8.0% -6.0% -4.0% -2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

GDP breakdown (% of output)

Outperformance vs national

148%

% of households by income

London 114%

Retail sales per capita

122%

Retail sales growth 2010-2030

European cities Average

Key Consumer services Financial & business services Industry Public services Transport, information & communication

City focus: Istanbul

Population (000) Population growth (2010-2030, %)

Istanbul

Turkey

Rank within European cities*

14,024

-

2

28%

20%

2

239

-

4

17,048

11,140

85

140%

127%

3

195

-

3

13,913

10,954

81

121%

116%

5

GDP 2014 ($bn) GDP per capita 2014 ($) GDP growth (2010-2030, %) Retail sales 2014 ($bn) Retail sales per capita 2014 ($) Retail sales growth (2010-2030, %) Clothing & footwear sales 2014 ($bn)

11

Clothing & footwear per capita 2014 ($) Clothing & footwear sales growth (2010-2030, %) % population under the age of 65 Number of households with income >$100,000 2030 (000)

2

816

639

66

100%

95%

30

91%

92%

2

2,062

2

*Rank out of 100 European cities (excludes Russia and Ukraine)

Key $100,000+ $70-100,000 $35-70,000 $20-35,000 $0-20,000

2010

2030

Age structure (% of population) 80+ 70-74 60-64 50-54 40-44 30-34 20-24 10-14 0-4

Key Istanbul Turkey

0.0%

2.0%

4.0%

6.0%

8.0%

GDP breakdown (% of output) Istanbul

153% 110%

GDP growth 2010-2030

Source: Oxford Economics, 2014 9

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

-8.0% -6.0% -4.0% -2.0%

Outperformance vs national

GDP per capita

% of households by income

THINK Europe: Picking Tomorrow’s World cities

127%

Retail sales per capita

105%

Retail sales growth 2010-2030

European cities Average

Key Consumer services Financial & business services Industry Public services Transport, information & communication

City focus: Madrid

Population (000)

Madrid

Spain

Rank within European cities*

6,677

-

4

1%

-3%

74

243

-

3

36,443

28,343

51

40%

33%

53

136

-

4

20,439

18,317

38

33%

30%

60

Population growth (2010-2030, %) GDP 2014 ($bn) GDP per capita 2014 ($) GDP growth (2010-2030, %) Retail sales 2014 ($bn) Retail sales per capita 2014 ($) Retail sales growth (2010-2030, %) Clothing & footwear sales 2014 ($bn)

6

5

Clothing & footwear per capita 2014 ($)

894

922

57

Clothing & footwear sales growth (2010-2030, %)

32%

25%

55

% population under the age of 65

77%

82%

55

Number of households with income >$100,000 2030 (000)

577

5

*Rank out of 100 European cities (excludes Russia and Ukraine)

% of households by income 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Key $100,000+ $70-100,000 $35-70,000 $20-35,000 $0-20,000

2010

Age structure (% of population) 80+ 70-74 60-64 50-54 40-44 30-34 20-24 10-14 0-4

Key Madrid Spain

-8.0% -6.0% -4.0% -2.0%

129%

112%

Source: Oxford Economics, 2014 10

THINK Europe: Picking Tomorrow’s World cities

2.0%

4.0%

6.0%

8.0%

Madrid

121%

GDP growth 2010-2030

0.0%

GDP breakdown (% of output)

Outperformance vs national

GDP per capita

2030

Retail sales per capita

111%

Retail sales growth 2010-30

European cities Average

Key Consumer services Financial & business services Industry Public services Transport, information & communication

City focus: Munich Munich

Germany

Rank within European cities*

3,905

-

12

Population growth (2010-2030, %)

16%

-1%

19

GDP 2014 ($bn)

238

-

5

60,839

43,742

13

49%

34%

36

94

-

7

23,958

20,699

8

50%

30%

33

Population (000)

GDP per capita 2014 ($) GDP growth (2010-2030, %) Retail sales 2014 ($bn) Retail sales per capita 2014 ($) Retail sales growth (2010-2030, %) Clothing & footwear sales 2014 ($bn)

5

8

Clothing & footwear per capita 2014 ($)

1,175

991

26

Clothing & footwear sales growth (2010-2030, %)

25%

11%

62

% population under the age of 65

74%

79%

73

Number of households with income >$100,000 2030 (000)

421

6

*Rank out of 100 European cities (excludes Russia and Ukraine)

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Key $100,000+ $70-100,000 $35-70,000 $20-35,000 $0-20,000

2010

2030

Age structure (% of population) 80+ 70-74 60-64 50-54 40-44 30-34 20-24 10-14 0-4

Key Munich Germany

-8.0% -6.0% -4.0% -2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

GDP breakdown (% of output)

Outperformance vs national

139%

% of households by income

167%

146%

Munich

116%

GDP per capita

GDP growth 2010-2030

Source: Oxford Economics, 2014 11

THINK Europe: Picking Tomorrow’s World cities

Retail sales per capita

Retail sales growth 2010-2030

European cities Average

Key Consumer services Financial & business services Industry Public services Transport, information & communication

Contact us Alice Breheny Global Co-Head of Research TH Real Estate 201 Bishopsgate London, EC2M 3BN T: +442037278122 E: [email protected]

www.threalestate.com [email protected] Follow us on Twitter

@THRealEstate14

Any assumptions made or opinions expressed are as of the dates specified or if none at the document date and may change as subsequent conditions vary. In particular, the document has been prepared by reference to current tax and legal considerations that may alter in the future. The document may contain “forward-looking” information or estimates that are not purely historical in nature. Such information may include, among other things, illustrative projections and forecasts. There is no guarantee that any projections or forecasts made will come to pass. International investing involves risks, including risks related to foreign currency, limited liquidity particularly where the underlying asset comprises real estate, less government regulation in some jurisdictions, and the possibility of substantial volatility due to adverse political, economic or other developments. Past performance is no guarantee of future performance. The value of investments and the income from them may go down as well as up and are not guaranteed. Rates of exchange may cause the value of investments to go up or down. Any favourable tax treatment is subject to government legislation and as such may not be maintained. The valuation of property is generally a matter of valuer’s opinion rather than fact. The amount raised when a property is sold may be less than the valuation. Nothing in this document is intended or should be construed as advice. The document is not a recommendation to sell or purchase any investment. It does not form part of any contract for the sale or purchase of any investment. TIAA Henderson Real Estate (TH Real Estate) is a name under which Henderson Real Estate Asset Management Limited provides investment products and services. Issued by Henderson Real Estate Asset Management Limited (reg. no. 2137726), (incorporated and registered in England and Wales with registered office at 201 Bishopsgate, London EC2M 3BN) which is authorised and regulated by the Financial Conduct Authority to provide investment products and services. Telephone calls may be recorded and monitored. TIAA Henderson Real Estate Limited (TH Real Estate) is a real estate investment management holding company owned by Teachers Insurance and Annuity Association of America (TIAA). TH Real Estate securities products distributed in North America are advised by UK regulated subsidiaries or TIAA-CREF Alternatives Advisors, LLC, a registered investment advisor and wholly owned subsidiary of TIAA, and distributed by Teachers Personal Investors Services, Inc., member FINRA. COMP201500042