Reshaping
Metropolitan
America Arthur C. Nelson, Ph.D., FAICP
Executive Director, Metropolitan Research Center
Director, Master of Real Estate Development
University of Utah
June 1, 2013
Outline
Trends
Preferences
Redevelopment
The benefits of compact development
New Housing Market Realities
Sub-prime mortgages are history.
20% down-payments are the new normal.
Meaning
□ Smaller homes maybe more people per unit
□ Smaller lots more attached units
□ More renters including doubled-up renters
Still Living with the Excess
Source: Census
2M more units permitted than needed 2000-2012
Household Size Has Stabilized
Source: Census.
Rise of Multi-Generational
Households
Source: Census Current Population Reports.
3+-Family
McMansion (Accommodates 15+)
Source: Arthur C. Nelson, Presidential Professor & Director, Metropolitan Research Center, University of Utah.
Population Change
2010-2030
Source: Arthur C. Nelson, Reshaping Metropolitan America (2013).
Metric
United
States
Population 2010 309,350
Population 2030 373,924
Population Change 64,574
Percent Change 21%
New Majority Pop Change 55,649
White Non-Latino Change 8,925
New Majority Share 86%
Population 65+ Change
2010-2030
Source: Arthur C. Nelson, Reshaping Metropolitan America (2013).
Metric
United
States
Population 65+ 2010 40,331
Population 65+ 2030 72,337
Population 65+ Change 32,006
Population 65+ Percent 79%
65+ as Share of Growth 50%
Net Change in Households by
Type, 2010-2030
Source: Arthur C. Nelson, Reshaping Metropolitan America (2013).
Metric
United
States
HHs w/ Children Change 3,544
HHs w/o Children Change 22,743
Single-Person HHs Change 13,793
Total Households Change 26,287
HHs w/ Children Share 13%
HHs w/o Children Share 87%
Single-Person HHs Share 52%
Net Change in
Households by Age
1990-2010 & 2010-2030
Source: Arthur C. Nelson, Reshaping Metropolitan America (2013).
Metric 1990-2010
United
States
<35 Growth Share 1990-2010 0%
35-64 Growth Share 1990-2010 77%
65+ Growth Share 1990-2010 23%
Metric 2010-2030
<35 Growth Share 2010-2030 10%
35-64 Growth Share 2010-2030 16%
65+ Growth Share 2010-2030 74%
Distribution of Units Built, United States,1989-2009
Type Volume Total Share Detached Share
New Units 24.5
Detached 20.7 85%
2500 sf+ 6.6 27% 32%
0.5-10 ac 8.7 35% 42%
Source: American Housing Survey
77% 23% 0% 10% 16% 74%
1990-2010 2010-2030
What a Difference a Generation Makes
Number of Seniors 1970-2040
Source: Arthur C. Nelson, Metropolitan Research Center, University of Utah
Buy-Sell Rates by 5-Year Age Cohort
75-79
80+
Census
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
20-
24
25-
29
30-
34
35-
39
40-
44
45-
49
50-
54
55-
59
60-
64
65-
69
70-
74
75-
79
80+
Sell Rate
Buy Rate
AHS
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
20-
24
25-
29
30-
34
35-
39
40-
44
45-
49
50-
54
55-
59
60-
64
65-
69
70-
74
75-
79
80+
Sell Rate
Buy Rate
Source: Dowell Myers & Sung Ho Ryu, “Aging Baby Boomers and the Generational Housing Bubble: Foresight and Mitigation of an Epic Transition”, Journal of the American Planning Association 74(1): 1-17 (2007).
The Great Senior Sell Off
Begins 2016
Seniors may be unable to unload 4M+ homes during the 2020s. They may “age-in-place” involuntarily. Source: Adapted from American Housing Survey raw data, Metropolitan Research Center, University of Utah
Householder Age
Owners Who
Move Annually
Owner to Renter
Percent
All HHs 70+ 4.0% 52%
All HHs 75+ 3.9% 60%
All HHs 80+ 4.1% 68%
All HHs 85+ 4.5% 79%
Net Buying or Selling Rate at Age 65-69
-1.20
-0.80
-0.40
0.00
0.40
0.80
1.20
1.60Califo
rnia
Alask
a
Wyo
ming
Mon
tana
Was
hing
ton
Haw
aii
Colorad
o
Orego
n
Utah
Idah
o
New
Mex
ico
Arizo
na
Nev
ada
Michiga
n
Indian
a
Illin
ois
Ohio
Wisco
nsin
North D
akota
Iowa
Minne
sota
Neb
rask
a
Kan
sas
Sou
th D
akota
Louisian
a
Wes
t Virginia
Virginia
Misso
uri
Ken
tuck
y
Alaba
ma
Mississippi
Texa
s
Oklah
oma
Geo
rgia
Tenn
esse
e
North Carolina
Arkan
sas
Sou
th Carolina
Florida
Con
necticut
New
York
Rho
de Islan
d
Penn
sylvan
ia
Marylan
d
Maine
New
Jerse
y
Mas
sach
usetts
Vermon
t
New
Ham
pshire
Delaw
are
WEST MIDWEST SOUTH NORTHEAST
Note:
Annual rates
as a percent
of people in
the age
group,
calibrated in
the late 1990s
Source: Dowell
Myers and Sung
Ho Ryu
Buy
Sell
3-May-07
Source: Dowell Myers & SungHo Ryu, “Aging Baby Boomers and the Generational Housing Bubble: Foresight and Mitigation of an Epic Transition”, Journal of the American Planning Association 74(1): 1-17 (2007). Figures for net buying or selling rate age.
BUY SELL
THE GREAT SENIOR SELL-OFF 2020
Weekly US Gasoline Prices In Nominal Dollars
2002-2012 gasoline prices rose at 10%+ per year, compounded. At this rate gasoline prices will be
$8+/gallon by 2020 ~$15/gallon by 2030
R2 = 0.70; t-ratio = 35.86; p > 0.01
Source: Adapted from Energy Information Administration (2012).
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=EMM_EPM0_PTE_NUS_DPG&f=W
Home Ownership Rates
US 1965-2012
Source: Adapted from Census
Homeownership Rate,
Householders 35-64, 2000-2012
Source: Adapted from Census
Homeownership Rate, Householders <35, 2000-2012
Source: Adapted from Census
Reading Gap Whites & Hispanics Age 17
NAEP-long term Hispanic reading score gap. US Dept. of Education
Ownership Trends by
Race/Ethnicity
Home Ownership Rates 2030
Notes: Owner rates in 2030 by ethnicity in 2010 held constant to 2030. Owner
rates in 2030 @ 95% assumes underwriting comparable to 1980s and reduced role of GSEs.
Source: Arthur C. Nelson, University of Utah.
Geography
Owner
Rate 2010
Owner Rate
2030 @
Constant
2010 Rates
Owner Rate
2030 @
95% of
2010 Rates
United States 66% 63% 60%
Renter Share of Growth 48% 65%
Education and Income
Source: http://www.bls.gov/emp/ep_chart_001.htm
Optimistic Ownership
Change, 2010-2030
Source: Arthur C. Nelson, Reshaping Metropolitan America (2013).
Metric
United
States
Ownership Rate, 2010 65.1%
Owner ship Rate, 2030 63.1%
Change in Households 26,287
Change in Homeowners 13,558
Change in Renters 12,728
Renter Share of Change 48%
Renter Share of Net Change in
Occupied Housing Units
83%
6.6M of 7.9M
59%
5.1M of 8.9M
US Preference
Demand vs. Supply
House Type Nelson RCLCo* NAR AHS
Attached 38% 34% 38% 28%
Small Lot 37% 35% 37% 29%
Conventional Lot 25% 31% 25% 43% *Owner demand only
Source: Nelson (2006), RCLCo (2008), NAR (2011), American Housing Survey (2011)
Housing Type Preference
by Age
Source: National Association of Realtors (2011)
Age-Based 2030 Demand
Compared to 2011 Supply
House Type 2011
Supply 2030
Demand Difference
Attached 34M 60M 26M
Small Lot 20M 51M 31M
Conventional 61M 33M (28M)
Total 115M 143M
Source: Arthur C. Nelson. Figures in thousands.
Supply 2011 Compared to
Demand 2030
Source: Arthur C. Nelson.
Space v. Commute Time Community A: Smaller houses on smaller lots
with shorter commute to work <20 minutes
Community B: Larger houses on larger lots
with longer commute to work 40+ minutes
Source: National Association of Realtors 2011.
59%
39%
0% 20% 40% 60% 80% 100%
Smaller houses and lots, shorter commute
Larger houses and lots, longer commute
What Gen-Y & Millennials Want
1/3 will pay more to walk to shops, work,
entertainment
1/2 would trade small lot size for proximity to
work, shop
1/3 with children would trade small lot size
for walkable, mixed-use communities
Source: Adapted from RCLCo.
Boomers Will Lead the Way
Boomers looking for something different:
• Many seek urban/close-in suburban
locations
• Most want “urban amenities” in suburban
location
Walkable communities with amenities, culture,
education:
• The village center is the new club house
• Seek convenience, healthy living, staying
engaged
Source: Adapted from RCLCo.
The New Promised Land?
Tear Up a Parking Lot,
Rebuild Paradise
Large, flat and well drained
Single, profit-motivated ownership
Major infrastructure in place
4+ lane highway frontage “transit-ready”
Committed to commercial/mixed use
Can turn NIMBYs into YIMBYs
Slide title phrase adapted from Joni Mitchell, Big Yellow Taxi, refrain: “Pave over paradise, put up a parking lot.”
Life-Span of Building Function
Retail
Office
Warehouse
Education
Nonres.
Homes
0
50
100
150
200Y
ears
Life-Span of Building
Source: Arthur C. Nelson, Presidential Professor & Director of
Metropolitan Research, University of Utah, based on DoE Commercial
Buildings Energy Consumption Survey.
Jobs & Nonresidential
Development 2010-2030
Source: Arthur C. Nelson, Reshaping Metropolitan America, Island Press (2013)
Metric
United
States
Jobs 2010 (k) 157,249
Jobs 2030 (k) 235,799
Change 2010-30 (k) 78,549
Percent 2010-30 (k) 50%
Space Supported 2010 (m) 83,349
Inventory Change (m) 38,261
Space Replaced 2010-30 (m) 91,742
Total Space Built 2010-30 (m) 130,003
Space Built as Share in 2010 156%
Pent-Up
Nonresidential Demand [Figures in billions of square feet]
Demand 2008-2013 Figure
Average Annual Growth 0.75B
Average Annual Replacement 2.00B
Total Ave. Annual Construction 2.75B
Total Construction Demand 19.25B
Supply 2014-2018
Total Space Built 2008-2013 (est) 14.50B
Pent-Up Demand 4.75B
2014-2018 Ave. Annual Construction 3.70B
Proportion of Normal 135%
Source: Arthur C. Nelson.
TOD Succession Planning
Don’t plan ahead of the market.
Encourage low-rent, low-rise activities to
jump-start the TOD market.
Encourage wood-frame, low-rise, low-
cost structures – they won’t last.
Think long-term 1st generation
structures will give way to high-
density, high-value in 10-20 years.
Ewing Compactness
Index Elements (14 total) DENSITY (6 elements)
Gross density of urban and suburban census tracts
Percentage of the population living at low suburban densities (<1500)
Percentage of the population living at medium to high urban densities (>12500)
Urban density based on the National Land Cover Database
Density of the densest population center to which county block groups relate
Gross employment density of urban and suburban census tracts
MIXED USE (3 elements) Job-population balance (tract)
Service job-population balance (tract)
Degree of job mixing as the countywide average degree of job mixing
CENTERING (3 elements) Coefficient of variation in census block group population densities Coefficient of variation in census block group employment densities
Percentage of the county population relating to at least one population center
STREET ACCESSIBILITY (2 elements) Intersection density for urban and suburban census tracts within the county
Percentage of 4-or-more-way intersections for urban and suburban census tracts
General Analytic Form
H0 = no effect of compactness on outcomes, ceteris
paribus.
Ordinary least squares.
Double-log regressions so outcomes are interpreted as
a X% change in independent variable associated
with/causes Y% change in dependent variable.
Depending on situation, independent variables include
base year metrics on population, income, job mix,
region, and the dependent variable.
Compactness Increases Home Values over Time
A 10% increase in Compactness is
associated with 2.8% increase in the
mean ratio of home values in 2012
compared to 2000.
R2 = 0.44
Compactness Made
Home Values More Resilient during the Great Recession
A 10% increase in Compactness is
associated with 4.9% increase in the
mean ratio of home values in 2012
compared to 2005.
R2 = 0.78
Compactness Increases Economic Productivity over Time
A 10% increase in Compactness is
associated with 1.0% increase in the
mean ratio of ratio of Gross Regional
Product between 2000 and 2010.
R2 = 0.64
Compactness Improved
Economic Resilience during the Great Recession
A 10% increase in Compactness is
associated with 0.05% increase in the
mean ratio of ratio of Gross Regional
Product between 2005 and 2010.
R2 = 0.51
Compactness Improves Employment Over Time
A 10% increase in Compactness is
associated with 0.6% increase in the
mean ratio of jobs in 2010
compared to 2000.
R2 = 0.49
Compactness Improves Employment Resilience
A 10% increase in Compactness is
associated with 0.035% increase in
the mean ratio of jobs in 2010
compared to 2005.
R2 = 0.39
Compactness Reduces Water Consumption over Time
A 10% increase in Compactness is
associated with 1.4% decrease in
the mean per capita water
consumption between 1990 and
2005.
R2 = 0.38
Compactness Reduced
Bank-Owned Homes during the Great Recession
A 10% increase in Compactness is
associated with 19% decrease in the
mean share of homes owned by
banks between 2006 and 2011.
R2 = 0.80
Revealed Market
Preferences
Attribute Value
“New urbanism” community +
Walkable destinations +
Higher walk- & transit-score +
Mixed-housing options in neighborhood +
Value near transit stations +
Low-density, single-use subdivisions —
Distance from activity centers —
… Let’s seize new markets Demand for rental homes will dominate most metro
markets to 2040.
1/3 to 1/2 want walkable, mixed-use communities
with transit options but <10% have those
options now.
Even if all new housing provided these options to 2030
demand will still not be met.
Redevelopment of commercial corridors can meet
large share of emerging market demand but
nimble public-private-nonprofit partnerships
needed
Is market is changing faster than we are?
Don’t Waste a
Once-in-a-Lifetime Opportunity 20+ years of residential mismatch ahead: Suburban fringe home values won’t return to pre-crash levels
soon if ever in most markets.
Demand for small home/small lot and attached products likely
unmet to 2020 if not beyond.
Stop Baby-Boom time-warp over-zoning for large lots.
5+ years record nonresidential development: Highest returns in urban/close-in suburban infill/redevelopment.
Unparalleled opportunity to reconfigure metropolitan
America along transit/transit-ready corridors & nodes.
All new development could go on existing parking lots
and still be less than European suburban density.
Thank You
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