Reshaping Metropolitan America - Planning · Reshaping Metropolitan America Arthur C. Nelson, Ph.D., FAICP Executive Director, Metropolitan Research Center Director, Master of Real

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


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


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


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


Homeownership Rate, Householders <35, 2000-2012


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


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



mean ratio of home values in 2012

compared to 2005.

R2 = 0.78

Compactness Increases Economic Productivity over Time



mean ratio of ratio of Gross Regional

Product between 2000 and 2010.

R2 = 0.64

Compactness Improved

Economic Resilience during the Great Recession



mean ratio of ratio of Gross Regional

Product between 2005 and 2010.

R2 = 0.51

Compactness Improves Employment Over Time



mean ratio of jobs in 2010

compared to 2000.

R2 = 0.49

Compactness Improves Employment Resilience


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


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


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

Reshaping Metropolitan America - Planning · Reshaping Metropolitan America Arthur C. Nelson, Ph.D., FAICP Executive Director, Metropolitan Research Center Director, Master of Real

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