A blueprint for addressing the global affordable housing ...ecahousingforum.eu/wp-content/uploads/2015/11/3_Jan-Mischke.pdf · A blueprint for addressing the global affordable housing

A blueprint for addressing the global

affordable housing challenge

November 2015

McKinsey Global Institute

Dr. Jan Mischke

CONFIDENTIAL AND PROPRIETARY

Any use of this material without specific permission of McKinsey & Company is strictly prohibited

McKinsey & Company | 1

SOURCE: McKinsey Global Institute cityscope database

In the next

18 minutes

~450 ~450 families will have migrated to

a city somewhere in the world


~15,000 of these families will be

hunting for a home


~15,000

By the time we sit

down for dinner


~400,000 of them will be

experiencing the realities of urban

housing shortage


~400,000

By the end of

the month

McKinsey & Company |

The century of cities


~330M households currently

facing affordability challenges




110M new households added by

2025 seeking affordable housing




1.6B, or almost one THIRD of the urban population will face

an affordability challenge by 2025


60

40

50

30

20

10

0

3.0 2.5 2.0 1.5 1.0 0.5 0 Households

Million

Annual income available for housing

$ thousand

SOURCE: McKinsey Global Institute analysis

1 In middle income economies incl. Colombia; smaller/ larger in other economies

Affordability

gap

$ billion

18

Annualized market price

of standard unit

Mortgage interest rate and

amortization over 30

years for a decent non-

city center 50 sqm unit1

2 3 7 6

30% of household

income

Example city

We define the affordability gap as the difference

between the annualized market price of a standard

unit and the income available for housing


1 As defined by World Bank.

0

2

4

6

8

10

12

14

16

13 14 12 10 9 8 11 6 4 3 23 2 1 7 22 20 15 21 37 19 18 17 5 36 38 16

Lagos

Bogota

Tokyo

London

Rio de Janeiro

San Francisco

Mumbai

Paris

Shanghai

Beijing

New York

Population, Million

Affordability gap, % of GDP

Sao Paulo

Barcelona (ESP)

Atlanta

Dhaka

Berlin

High

Mid

Low

Berlin

Affordability gap

$ billion Country income group1

The affordability gap in 2400 cities

SOURCE: McKinsey Global Institute analysis

McKinsey & Company | 0SOURCE: McKinsey Global Institute

Four levers can narrow

the affordability gap


2

100

Financing1

Operations and maintenance

Optimized cost

Subsidies & non‐standard housing2

0-7

52-78

8-23

Development

Land

12-16

Annualized cost

1 Impact of reduced origination and funding costs is quantified; impact of increased access to financing is not

2 Transitional use of basic housing (with communal toilets and kitchens, for example) to serve very low-income households

30% 80%50%Area median

income

INCOME AVAILABLE

FOR HOUSING BY

INCOME SEGMENT

SOURCE: McKinsey Global Institute

Four levers can narrow the affordability gap


16

Viability gap funding required

Private investment

1-3

~8

Construction capital outlay 9-11

Land value 5-7

Total investment


USD trillion

$1 trillion public investment can unlock

housing valued at $16 trillion


LandLand at the right location is the most critical lever.

Enable city expansion, use unused land, or increase density


14.0

2.4

2005 2010SOURCE: Whitney Eulich and Lauren Villagran, “In Mexico, low-income homeowners watch their dreams crumble,” The Christian Science Monitor, June 26, 2013; Eric

Dickson, Judy Baker, Daniel Hoornweg, and Asmita Tiwari, Urban risk assessments: An approach for understanding disaster and climate risk in cities, World Bank,

2012; Google Maps; Encuesta sobre la situación de vivienda de acreditados 2010; Encuesta de casas abandonadas julio 2009 IPSOS (Matamoros, Mexicali);

McKinsey Global Institute analysis

Urban expansion of the Mexico City

metropolitan areas, 1950–2006

Ratio of vacant houses over total housing

(national), %

1950

1960

1970

1980

1990

2000

2006

Enable smart city expansion in transit-oriented

way


Land

market in

a middle

eastern

city

Vacant land since 1999

Urban boundaries 1999

Urban boundaries 2013


Make use of vacant land

McKinsey & Company | 6SOURCE: Shirley Ballaney, The town planning mechanism in Gujarat, India, World Bank, 2008;

McKinsey Global Institute analysis

Sale for residential

Sale for commercial

Garden

Social infrastructure

Low-income housing

Phase 1

Phase 2

Phase 3

Phase 4

Phase 5

Sequence of town planning schemes in Ahmedabad Development Plan, 1999-2009

Redevelop to increase density – while capturing

the value uplift


DevelopmentEnable lower-cost housing production at scale, while ensuring

architectural and construction quality

McKinsey & Company | 8SOURCE: OECD Stat; McKinsey Global Institute analysis

120

110

100

150

90

80

0

140

130

95 2009

UK

UK

05

Germany

United Sates

United States

1989

Germany

2000

Rest of economy

ConstructionValue added (volume)/labor input (hours worked)

Index: 100 = 1989 for United States, 1991 for Germany, 1994 for UK

Labour productivity in construction has fallen for 20 years

McKinsey & Company | 9SOURCE: McKinsey Infrastructure Practice

Purchasing

excellence

Lean

execution

Design-

to-value

Capital productivity strategies and industrial

construction can cut costs by 20 to 30 percentOverview of capital productivity: main cost reduction levers

Time

savings

40-50%

Cost

savings

30%


Operations and maintenanceIncentivize energy efficiency and consolidate maintenance

McKinsey & Company | 11SOURCE: US Consumer Expenditures Survey (2012); Eurostat (2005); Department of Statistics Singapore (2014); China

Statistical Yearbook (2012); McKinsey Global Institute analysis

1 Includes maintenance and repairs 2 Includes electricity, gas, fuel oil, other fuels, and water

14 14 15

27

7 7 6

6

Utilities2

Maintenance1

33

EU-27United

Kingdom

21

United States

21

Singapore

21

Operations and Maintenance (O&M) cost as share of housing expenditures

%

Scale in maintenance and energy efficiency can cut the

20 to 30 percent share of O&M in annual housing costs


FinanceCreate certainty and speed for developers to lower risk,

but don't over-rely on finance in supply-constraint cities

McKinsey & Company | 13SOURCE: Banxico; Comisión Nacional Bancaria y de Valores (CNBV); Global Banking Pools; Fannie Mae; US Treasury; McKinsey Global Institute analysis

0.7

4.3

Cost of funds 3.35

Operating cost 0.2

Risk costs

and margin3 1.540.8

Fees 0.1

Prevailing

mortgage rate

with fees

5.00.7 8.9

2.1

1.7

4.6

2.7

0.1 0.1

6.96

4.8

0.2

13.5

Low to

moderate income

High income

1 Prevailing rate for high income households is 4.3% and for low and moderate income households is 5.0% 2 Prevailing rate for high income households is 8.9% and for low and moderate income households is

13.5% 3 Includes margins charged for risk premium and economic profit. 4 Includes mortgage insurance risk premiums and Federal Housing Administration subsidies 5 Reflects 30-year Treasury note rate with

negligible capital charge due to the prevalence of securitization in the American mortgage market 6 Blended seven- and 10-year bank note rate plus a capital charge of 50 basis points

United States1 Mexico2

Rate break-down; %

Opportunity to lower several drivers of mortgage rates

McKinsey & Company | 14SOURCE: McKinsey Global Institute analysis

De-risking

development

Improving

debt terms

Increasing

equity

Providing

tax relief

Four approaches to improve access to and

reduce cost of developer finance

McKinsey & Company | 15SOURCE: Aida Caldera Sanchez and Asa Johansson, The price responsiveness of housing supply in OECD countries,

OECD Economics Department working paper number 837, May 2011; McKinsey Global Institute analysis

Be cautious about improving financing when housing

supply does not respond to price increasesEstimates of long-run price elasticity of new housing supply

% change in supply of housing in relation to % change in market price

Germany

New Zealand 0.70.6

Australia 0.5Ireland

NorwaySpain 0.5

0.5

Poland 0.4

Switzerland

1.2

France 0.40.4

0.3

United Kingdom

Italy

0.4

Belgium

0.20.2

United States 2.01.4

0.1

Denmark

Austria

1.2Canada

0.4Israel

0.3

Netherlands

Sweden

1.01.0

JapanFinlandTop 6

sample

countries

Average =

1.3

Bottom 15

sample

countries

Average =

0.4


Right delivery platform for each city


Approaches

Control use, misuse, and under-use

Choose PPP, public delivery, private

development in line with the local context

Focus funding on viability gaps and

leverage land value

Contemplate housing delivery units to

streamline processes and governance and

address NIMBY-ism

McKinsey & Company | 17SOURCE: McKinsey Global Institute analysis

Takeaways for Europe

Land

▪ Enable city expansion and build transit infrastructure

▪ Catalogue underused inner-city public and private land and redevelop

▪ Capture land value increases

Develop-

ment

▪ Enable larger scale and planning certainty for developments, possibly as PPP

▪ Ensure architectural and construction quality

O&M▪ Consolidate maintenance

▪ Regulate, finance, and incentivize energy efficiency investments

Finance▪ Don't over-rely on financial measures in constraint/ fast growth cities

▪ Create certainty and speed for investors in terms of demand and approvals

Delivery

platform

▪ Meticulously control use (and misuse), and dis-incentivize under-utilization

▪ Focus funding on viability gaps, with market based approaches for >80%

median income and public shelter or subsidies for those below

▪ Establish cross-departmental housing delivery units

▪ Set-up metropolitan governance structures that overcome NIMBY-ism


Thank you!

The full report is available at

McKinsey Global Institutewww.mckinsey.com/mgi

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A blueprint for addressing the global affordable housing ...ecahousingforum.eu/wp-content/uploads/2015/11/3_Jan-Mischke.pdf · A blueprint for addressing the global affordable housing