A blueprint for addressing the global affordable housing...
Transcript of 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
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~15,000 of these families will be
hunting for a home
SOURCE: McKinsey Global Institute cityscope database
~15,000
By the time we sit
down for dinner
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~400,000 of them will be
experiencing the realities of urban
housing shortage
SOURCE: McKinsey Global Institute cityscope database
~400,000
By the end of
the month
McKinsey & Company |
The century of cities
SOURCE: McKinsey Global Institute cityscope database
~330M households currently
facing affordability challenges
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The century of cities
SOURCE: McKinsey Global Institute cityscope database
110M new households added by
2025 seeking affordable housing
McKinsey & Company |
The century of cities
SOURCE: McKinsey Global Institute cityscope database
1.6B, or almost one THIRD of the urban population will face
an affordability challenge by 2025
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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
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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
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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
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16
Viability gap funding required
Private investment
1-3
~8
Construction capital outlay 9-11
Land value 5-7
Total investment
SOURCE: McKinsey Global Institute
USD trillion
$1 trillion public investment can unlock
housing valued at $16 trillion
McKinsey & Company | 3SOURCE: McKinsey Global Institute
LandLand at the right location is the most critical lever.
Enable city expansion, use unused land, or increase density
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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
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Land
market in
a middle
eastern
city
Vacant land since 1999
Urban boundaries 1999
Urban boundaries 2013
SOURCE: McKinsey Global Institute
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
McKinsey & Company | 7SOURCE: McKinsey Global Institute
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
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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%
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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
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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
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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
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Right delivery platform for each city
SOURCE: McKinsey Global Institute
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
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Thank you!
The full report is available at
McKinsey Global Institutewww.mckinsey.com/mgi