AMERICAN DREAM BOUNDARIES:
Urban Containment and its Consequences
Published by the Georgia Public Policy Foundation
(www.gppf.org)
July 2001
By Wendell Cox
INTRODUCTION
The Oregon portion of the Portland metropolitan area1 has adopted the nation’s
strongest so-called “smart growth” policies. There, Metro, the regional government, has
adopted a wide range of policies to fight what is pejoratively referred to as “urban
sprawl” and restrict the expansion of the developed (urbanized) area. Smart growth is
also referred to as “urban containment.” Strategies include an urban growth boundary,2
that forbids most urban development on the outside, incentives for “infill” development in
older areas and other measures to increase population densities, especially along
corridors served by public transit. Moreover, Metro’s policies are generally opposed to
the expansion of highways and the area has constructed a light rail system that
provides services from the east and west to the downtown area.
State law requires expansion of the urban growth boundary to accommodate 20 years
of development. However, Metro decided to largely freeze the boundary in the middle
1990s, intending to force all new growth within the existing boundary.
At the same time, housing affordability has dropped substantially in Portland, with critics
of smart growth attributing the shortage of land resulting from the urban growth
boundary. For advocates of smart growth, who generally favor incentives for low income
housing, Portland’s decline in housing affordability has raised concern. This concern,
however, has been allayed by findings published by Dr. Arthur C. Nelson, Professor of
Urban Planning and Public Policy at the Georgia Technological Institute (Georgia Tech)
in Atlanta. In an American Planning Association publication, Economic Development
1
Formally the Portland-Vancouver PMSA, which includes five Oregon counties and one Washington
county. The core area, which has an elected regional government (Metro), is within Clackamas,
Multnomah and Washington counties in Oregon. Since 1990, the metropolitan area (CMSA) has been
expanded to include counties far beyond the impact of Portland’s smart growth policies (though under the
impact of their own), which is why the PMSA is used.
2
The area inside urban growth boundaries are sometimes called “growth areas.”
and Smart Growth,3 Dr. Nelson theorizes that rising housing prices may be the result of
Portland having become more desirable as a result of smart growth.4 This tentatively
stated proposition has been stretched into received wisdom by some smart growth
proponents. Economic Development and Smart Growth compares Portland and Atlanta
with respect to a number of factors, generally finding that Portland performance is
superior.
Period Evaluated
Economic Development and Smart Growth generally evaluates the differences between
Portland and Atlanta over a period of the middle 1980s to the middle 1990s. In fact,
however, such a period is somewhat premature, since there was considerable
developable land within the UGB in the middle 1980s and smart growth had not created
the land shortage that has now become apparent. In 1980, shortly after adoption, the
US Census Bureau estimated the Oregon portion of the Portland urbanized area to be
equal to 79 percent of the land inside the UGB. By 1990, urbanized land was estimated
at nearly 91 percent of the land inside the UGB. In the intervening years, Metro decided
not to expand the UGB, and the developable area within the UGB has been reduced by
at least one-quarter since 1990.5
The consequences of the UGB became evident only as land became more scarce in the
1990s. Housing prices have risen inordinately and there is now a shortage of
commercial land for development.6 This paper analyzes trends in Portland and Atlanta,
during which Portland’s urban containment policies have begun to have serious effect.
POPULATION, EMPLOYMENT & INCOME GROWTH
From 1990 to 2000, metropolitan Atlanta grew at more than 1.5 times the rate of
metropolitan Portland, a somewhat higher differential than reported in Economic
Development and Smart Growth (Table #1). However, unlike the earlier period
evaluated in Economic Development and Smart Growth, Atlanta’s employment and
income have risen more rapidly during the 1990s than in Portland (all latest data
available).
•
Employment in metropolitan Atlanta grew 37.3 percent, compared to 30.5
percent in metropolitan (Table #2).
3
Arthur C. Nelson, PhD, ASCE, AICP, “Economic Development and Smart Growth,” News & Views,
(American Planning Association, Economic Development Division), October 1999.
4
Arthur C. Nelson, “Effects of Urban Containment on Housing Prices and Landowner Behavior,” Land
Lines, Lincoln Institute of Land Policy, May 2000.
5
Based upon information in Samuel Staley, “Line in the Land: Urban Growth Boundaries, Smart Growth
and Housing Affordability,” Reason Public Policy Institute, November 1999 www.rppi.org/housland.html,
6
“Kristina Brennerman, Space Crisis a Threat to Region’s Future,” The Business Journal of Portland,
April 2, 2001
2
•
Median household income rose 52 percent from 1990 to 2000 in Atlanta,
compared to 44.7 percent in Portland (Table #3).7
In all three indicators, both Atlanta and Portland performed more strongly than the
nation as a whole. Economic Development and Smart Growth indicates that one of the
promises of smart growth is “improving incomes.” In fact incomes in Portland are rising
slower than in Atlanta, and the area is attracting fewer new residents and fewer new
jobs.
Finding: Contrary to the earlier period evaluated by Economic Development and Smart
Growth, Atlanta has performed more strongly than Portland with respect to employment
growth and income growth. Because Portland’s performance is inferior, smart growth
cannot be credited with having induced superior performance.
Table #1
Metropolitan Area Population
1990
2000
Change
Atlanta
2,959,500
4,112,198
38.9%
Portland
1,517,442
1,918,009
26.4%
Nation
248,709,873 281,421,906
13.2%
Source: US Census Bureau
Table #2
Employment
Metropolitan Area
1990
1999
Change
Atlanta
1,661,807
2,281,664
37.3%
Portland
769,586
1,004,460
30.5%
Metropolitan Average
98,802,939 114,705,379
16.1%
Nation
117,640,000 136,617,000
16.1%
Source: US Department of Commerce, Bureau of Economic
Analysis
Table #3
Median Household Income
1990
2000 Change
Atlanta
41,500
63,100
52.0%
Portland
37,100
53,700
44.7%
United States
35,700
50,200
40.6%
Source: US Department of Housing & Urban
Development
7
Calculated from US Department of Housing & Urban Development data.
3
GOVERNMENT REVENUES AND EXPENDITURES
Advocates of smart growth claim that more sprawling or scattered development results
in higher public infrastructure costs. The efficiencies of smart growth, according to
proponents, require less government revenue and less government spending.
Economic Development and Smart Growth finds that government revenues have grown
less slowly in Oregon and Portland than in Georgia and Atlanta. In fact the record during
the 1990s shows the opposite (Table #4). From 1990 to 1997 (latest data available):8
•
•
•
•
Annual state and local government revenue in Oregon grew 64 percent per
capita, compared to Georgia’s 40.5 percent. Georgia’s revenue growth was at
approximately the national average, while Oregon’s was significantly higher.
Total state and local government expenditures rose 29.5 percent per capita in
Oregon, nearly double Georgia’s 15.5 percent. Both figures were above the
national average of 12.6 percent.
Utility and sewer expenditures declined 1.2 percent per capita in Georgia, while
rising 46.3 percent in Oregon. These results are the opposite of what would be
predicted if less dense development, such as in Georgia, is inherently more
costly than more dense development. The national average was minus 2.3
percent.
State and local government construction costs rose 13.3 percent per capita in
Georgia, and 82.3 percent per capita in Oregon. This is also the opposite of what
would be expected, since the scattered development is more costly thesis
predicts higher infrastructure construction costs (for longer utility lines, more
highways and more schools). The national average was similar to that of
Georgia, up 10.8 percent.
In education, as smart growth advocates would predict, Georgia expenditures have
risen faster than in Oregon, but examination of the data shows that smart growth is not
the reason. Oregon expenditures per capita on elementary and secondary education
rose only 1.4 percent per capita, compared to a much larger 12.8 percent in Georgia
and the national average of 9.3 percent. It might be expected that this reflects the higher
cost of building more schools in scattered suburban areas. It does not.
In November 1990, the voters of Oregon approved Measure 5, which placed limits on
property tax increases. Expenditures on elementary and secondary education, which is
heavily reliant upon property taxes, appears to have been more materially impacted by
Measure 5. From 1990 to 1997 (Tables #5):9
8
9
Calculated from US Census Bureau data. All data is inflation adjusted.
Calculated from data in US Department of Education, Digest of Educational Statistics, multiple years.
4
•
•
•
Oregon expenditures on instruction have increased 0.9 percent per pupil. This is
much lower than the 9.8 percent per pupil in Georgia and the national average of
5.6 percent.
Perhaps indicating that at least part of the Measure 5 intention has been
achieved, administrative and other costs per pupil have declined 7.9 percent in
Oregon. Georgia administrative and other costs have risen 3.9 percent per pupil,
while the national average is up 0.2 percent.
If the “more dense development is less expensive” thesis is correct, the one
measure that Oregon should perform better than Georgia would be elementary
and secondary education capital costs and debt service on schools. But on this
issue, Oregon spending has risen at a much greater rate than both Georgia and
the nation. Despite its policies that favor more compact development, Oregon’s
capital and debt service costs increased 102.2 percent per pupil, nearly seven
times the 15.7 percent Georgia increase. Oregon’s increase was nearly four
times the national average.
In light of Measure 5 and the intention of the referendum’s authors to reduce state
expenditures, it seems surprising that Oregon per capita state and local revenues and
expenditures have risen so much more steeply than in Georgia, which implemented no
such tax limitation.
Economic Development and Smart Growth indicates that property taxes have risen less
quickly in Portland than Atlanta, using American Housing Survey data. Part of
Portland’s advantage is due to the impacts of Measure 5, which has shifted some of the
government funding burden from property taxes to other sources. But there is much
more to taxation than property taxes. In Georgia, property taxes represent 13.4 percent
of all government revenue, down 22.5 percent from 1990. In Oregon, property taxes
represent 12.9 percent of all government revenues, down 53.8 percent from 1990,
largely due to Measure 5. Moreover, there is no readily available and reliable source of
total state and local taxation or expenditure by metropolitan area.10 In both metropolitan
areas, like others around the country, local government revenues and expenditures
involve a mix of multiple general purpose governments, school district and special
districts that complicate comparisons. In short, such comparisons require far more
research than is represented by generally available sources.
Further, there is reason to question the “sprawl costs more” thesis.
•
Lower infrastructure costs do not necessarily mean lower overall public costs, nor
do higher infrastructure costs mean higher overall public costs. For example, the
10
An appropriate analysis would require state data attributable to the metropolitan areas, together with
data from all local and regional governments, school districts and special districts in the metropolitan
areas. Such data is simply not readily available. It is not sufficient to compare the local areas, such as the
cities of Atlanta and Portland, since both represent only part of their metropolitan areas, and their
governments do not collect or expend all public revenues attributable to their geographical areas.
5
per capita cost of roadways may be higher in one jurisdiction, but overall
government costs may be lower. What is important to consumers and taxpayers
is the total costs, not individual elements of costs that, while lower or lower,
cannot be separated from the package of taxes and fees that must be paid.11
•
•
•
It cannot simply be assumed that the greater distances that result from less
dense development mean higher infrastructure costs. There is much more than
infrastructure costs than the cost of materials. Differing labor costs, variations in
labor productivity, differences in bureaucratic costs, the environment in which the
work is performed (developed or non-developed area) and other factors can
create impacts that more than nullify any advantage that might be obtained from
lower materials costs. Further, infrastructure does not last forever, and it is more
expensive to rehabilitate infrastructure in more dense areas than in less dense
areas.
Differing government practices can have a material impact with respect to
infrastructure costs. Generally, newer suburban areas are more open to
innovative strategies such as competitively contracting and privatization, which
significantly lower infrastructure costs.12 Older central cities are more likely to
have enacted provisions that artificially raise costs, such as living wage
ordinances.
Some services simply cost less in lower density environments. Helen Ladd
generally found higher unit costs to be associated with higher density --- up to 71
percent higher in unit capital costs and 43 percent higher in unit operating
costs.13 For example, larger municipalities, which are generally central cities,
tend to have higher unit operating costs than smaller municipalities, which tend to
be more suburban.14 US public transit unit costs are generally higher in higher
density areas than in lower density areas.15
11
An example of this dynamic is a recent report by the Surface Transportation Policy Project, which found
that the costs of transportation were higher in more sprawling urban areas than in less sprawling areas
(“Surface Transportation Policy Project, Driven to Spend,” December 2000). However a subsequent
report found, using the same data set, that the costs of housing and food in the more sprawling urban
areas much more than made up for the difference (Wendell Cox, “”Smart Growth and the Quality of Life,”
Environment & Climate News, March 2001).
12
For example, the city of Indianapolis has reduced the costs of a number of functions through
competitive contracting and privatization (Stephen Goldsmith, The Twenty First Century City, Regnery
Publishing Co., 1977). Public transit services, largely operated by publicly owned monopolies in the
United States, have and are being converted to competitively tendered systems in Australia, New
Zealand and Europe, with savings on the order of 20 percent to 50 percent
(www.publicpurpose.com/t5.htm). Moreover, public transit unit costs for buses are lower in suburban
areas than in central cities (www.publicpurpose.com/ut-us97mbecsc.htm).
13
Ladd, Helen F. “Population Growth, Density and the Costs of Providing Public Services.” Urban
Studies 2 (1992): 273-295.
14
Wendell Cox, Local and Regional Governance in the Greater Toronto Area: A Review of the
Alternatives: Report Prepared for the City of Toronto, January 1977. www.publicpurpose.com/tordemo.htm.
15
www.demographia.com/db-ptcitysub.htm
6
The data generally shows that Georgia has achieved lower revenue and expenditure
increases per capita than Oregon since 1990, the period during which Portland’s smart
growth policies have had the most impact. However, it is not suggested that Georgia’s
superior performance reflects the superiority of its land use planning policies. What can
be said is that the lower cost and revenue government performance that advocates
attribute to smart growth is not evident in the data for Oregon. Doubtless, a multiplicity
of factors account for the differences in government performance between Oregon and
Georgia.
Finding: During the 1990s Georgia has generally performed better than Oregon, and
especially in infrastructure measures that advocates claim are improved by smart
growth. The smart growth policies of Oregon have not produced more efficient
government than in Georgia.
Table #4
Per Capita Government Revenues & Expenditures
1989-1990
1996-1997
Change
Total State & Local Government Revenue
Georgia
$3,593
$5,048
40.5%
Oregon
$3,826
$6,274
64.0%
United States
$3,864
$5,411
40.0%
Total State & Local Government Expenditures
Georgia
$4,409
$5,092
15.5%
Oregon
$4,925
$6,379
29.5%
United States
$4,911
$5,528
12.6%
Utility and Sewer Expenditures
Georgia
$494
$488
-1.2%
Oregon
$387
$567
46.3%
United States
$469
$458
-2.3%
Elementary & Secondary Education Expenditures
Georgia
$987
$1,113
12.8%
Oregon
$1,129
$1,144
1.4%
United States
$1,017
$1,111
9.3%
Government Construction
Georgia
$460
$521
13.3%
Oregon
$391
$716
82.8%
United States
$448
$497
10.8%
Source: US Census Bureau
7
Table #5
Elementary & Secondary Expenditures per Pupil
1989-1990
1996-1997
Change
Total Expenditures
Georgia
$5,686
$6,175
8.6%
Oregon
$6,554
$6,868
4.8%
United States
$6,413
$6,789
5.9%
Capital Expenditures
Georgia
$759
$878
15.7%
Oregon
$473
$958
102.2%
United States
$652
$831
27.5%
Instructional Expenditures
Georgia
$2,988
$3,281
9.8%
Oregon
$3,531
$3,561
0.9%
United States
$3,432
$3,624
5.6%
Administration & Other Expenditures
Georgia
$1,939
$2,016
3.9%
Oregon
$2,550
$2,349
-7.9%
United States
$2,329
$2,334
0.2%
Source: US Department of Education
TRANSPORTATION
One of the principal objectives of smart growth is to reduce reliance upon the private
automobile. Perhaps the most attractive promises made by smart growth advocates
relate to the improvements they anticipate in traffic congestion, which would be
accomplished by transferring travel to transit, car pools, bicycles and walking.
State Auto Use: The Claim Economic Development and Smart Growth reports
impressive results in both Oregon and Portland. From 1990 to 1995, Economic
Development and Smart Growth finds that annual vehicle miles traveled rose only 1.5
percent, compared to Georgia’s 16.9 percent and the national rate of 10.8 percent.
However, Economic Development and Smart Growth relies on a data source (the
Nationwide Personal Transportation Survey, or NPTS) that is not recommended by its
sponsor (the United States Department of Transportation) for use at the state or local
level.16
State Auto Use: The Reality: The definitive source for data on state vehicle miles
traveled is the Federal Highway Administration’s annual Highway Statistics report.17
16
E-mail from Bryant Gross (Federal Highway Administration) to Wendell Cox,30 October 2000. The
Nationwide Personal Transportation Survey is comparatively small, and designed to provide statistically
reliable data at the national level.
17
Data is estimated by state departments of transportation, based upon mechanical counts taken on
roadways.
8
From 1990 to 1995, Highway Statistics data indicates a similar 1.6 percent rise in
Oregon vehicle miles traveled per capita. However, the Georgia figure is much smaller
than the NPTS sample, at 6.5 percent.18 Moreover, traffic volumes have accelerated in
Oregon, rising 9.4 percent per capita in Oregon from 1995 to 1999, compared to
Georgia’s 6.1 percent. The result is that, during the 1990s, Oregon’s rate of traffic
growth per capita is, at 11.2 percent, similar to that of Georgia (13.0 percent), though
both states are below the national increase rate of 14.3 percent (Table #6) The
accelerating automobile use trend in Oregon relative to Georgia is the opposite of what
would be expected if smart growth policies were reducing automobile use.
Table #6
Per Capita Vehicle Miles
1990
Georgia
Oregon
United States
Source: USDOT Federal Highway Administration
11,230
9,408
8,635
1999
Change
from 1990
12,693
13.0%
10,458
11.2%
9,870
14.3%
Portland Trends: The Claims: Economic Development and Smart Growth reports
that “use of alternative modes of commuting has increased dramatically in Portland
relative to Atlanta.” Again using the NPTS sample,19 Economic Development and Smart
Growth finds major progress from 1990 to 1995:
•
•
Transit is reported to have increased its work trip market share from 5.9 percent
to 17.0 percent, a 188 percent increase. This compares to a 36 percent market
share loss in the 1980s.20 This is an extraordinary increase and might be the
most significant transit work trip market share turnaround in history.21
Gains were also reported by Economic Development and Smart Growth for
Portland in carpools, walking and bicycling. Carpool use is reported to have risen
from 12.3 percent to 14.1 percent. Walking and bicycling is reported to have
increased 158 percent, from 1.9 percent to 4.9 percent.
18
Calculated from Federal Highway Administration and US Census Bureau data.
As with the state data, the sponsor of NPTS does not recommend use of metropolitan data, because of
an insufficient sample size (E-mail from Bryant Gross to Wendell Cox, 9 May 2001.)
20
US Census Bureau data.
21
While complete international trend data is not readily available, data indicates that Ottawa has achieved
the largest increase in overall transit market share among urban areas with below 10 percent shares
(Portland’s overall transit market share is reported by the city of Portland Department of Transpiration to
be under three percent). Ottawa increased its overall market share from 5.7 percent to 9.4 percent from
1960 to 1990, an increase of 65 percent. A work trip market share increase in Portland of 188 percent in
five years seems implausible.
19
9
•
•
•
Similarly, a substantial reduction in single occupant automobile commuting is
reported for Portland. Single occupant commuting is reported by Economic
Development and Smart Growth to have dropped from 73.8 percent to 64.0
percent, a reduction of 13.3 percent. This five year reduction in single occupant
commuting would be 12 times the largest 10 year reduction reported in any major
urban area in US history 22
At the same time, average commuting time is reported by Economic
Development and Smart Growth to have dropped 8.8 percent in Portland, from
21.7 to 19.8 minutes.
Generally, using the NPTS sample, Economic Development and Smart Growth
finds Atlanta transportation performance to be inferior to that of Portland.
Portland Trends: The Reality Such impressive transfers of demand from cars to
transit should be reflected in the transit ridership data. They are not. The reported
increase in transit work trips would have added 58.4 million transit trips from 1990 to
1995.23 This is more than 60 percent higher than the actual ridership in 1995 (Table #7).
The actual increase in transit ridership was barely one-fifth the amount that would have
been reflected by the transit increase reported by Economic Development and Smart
Growth.
The Economic Development and Smart Growth cited data are also at odds with 1994
local survey information, as reported by the city of Portland Office of Transportation,24
that shows much different results:
•
•
•
5.2 percent of metropolitan area commuters used transit, a slightly lower figure
than the 5.6 percent reported by the US Census Bureau in 1990, and far lower
than the 17.0 percent reported by Economic Development and Smart Growth.
9.5 percent of commuters car pooled, well below the 12.8 percent reported in
1990.
80.1 percent of commuters drove alone, somewhat more than the 77.0 percent in
1990.
22
Among metropolitan areas of more than 1,000,000, only Houston has ever reported a decline in work
trip automobile use. From 1980 to 1990, Houston’s automobile market share declined from 91.6 percent
to 90.8 percent, less than a one percent decline.
23
This estimate is very conservative. It assumes that none of the new transit commuters would transfer
from one vehicle to another during the work trip. Tri-Met, the large Portland transit agency had a transfer
ratio of 1.38 in 1997, which if applied to this calculation would predict daily ridership more than 90
percent above 1995 levels.
24
Facts about Portland, City of Portland Office of Transportation., 2000 Edition.
10
Table #7
Calculation of Expected Transit Ridership from 1990-1995 NPTS Trend
1990
1995
Change
Portland Employment
769,586
891,422
15.8%
Transit Work Trip Market Share
5.9%
17.0% 188.1%
Transit Commuters
45,406
151,542 233.8%
Daily Trips (Commuters x2)
90,811
303,083 233.8%
Annual Trips in Millions (Average Workdays: 255)
23.2
77.3 233.8%
New Commuter Trips (Millions)
54.1
Actual Trips (Millions)
58.4
69.2
18.4%
Shortfall
-38.5%
Calculated from US Department of Commerce, Bureau of Economic Analysis data, and
Federal Transit Administration data.
Later, but similar data has been reported by the US Census Bureau’s American
Community Survey (ACS) for the core county of Multnomah (in which the city of
Portland is located). In 1999 transit and car pooling were reported at 22.7 percent, down
from the 1990 US Census Bureau figure of 23.3 percent.25 In contrast to the Economic
Development and Smart Growth reported 13.3 percent decline in single occupant
commuting, ACS found a 69.7 percent 1999 figure, down 0.4 percent from the 70.0
1990 US Census Bureau number. In further contrast to the findings of Economic
Development and Smart Growth, ACS found average work trip travel time to be 22.7
minutes, up from the Census Bureau’s 21.1 minutes in 1990.
Portland & Atlanta: The Transport Reality: It true that transit trends are more
positive in Portland. But transit’s market share is so small in both urban areas (two to
three percent in both metropolitan areas), that virtually no traffic impact can be
perceived. Less than three percent of new travel in Portland is on transit, more than
Atlanta’s one percent, but both figures are insignificant. Further, transit ridership per
capita in the MARTA service area is more than double that of Portland’s Tri-Met.26
If so many trips had been diverted from highways to transit, highway travel per capita
travel should have declined. The opposite is true. The latest Texas Transportation
Institute traffic congestion data shows that, among the nation’s urban areas with more
than 1,000,000 population, Portland experienced the largest per capita increase in daily
vehicle miles traveled from 1990 to 1999 (Table #8), at 28.5 percent.27 This is 2.5 times
that major urban area average, and more than one-third higher than the increase rate of
Atlanta. It is true that per capita travel in Atlanta is much higher than in Portland, but this
was true before Portland’s smart growth policies began to have an impact.
25
There is no ACS data for other counties in the Portland area or for Atlanta area counties.
Passenger Miles per capita (Fulton and DeKalb counties in Atlanta, Clackamas, Multnomah and
Washington counties in Portland).
27
Texas Transportation Institute, 2001 Mobility Study, http://mobility.tamu.edu/2001/study.
26
11
Table #8
Per Capita Daily Vehicle Miles Traveled
1990
1999
Change
Atlanta
29.1
35.1
20.6%
Portland
16.2
20.9
28.5%
Average
20.6
22.9
11.4%
Source: Calculated from Texas Transportation Institute
data
Both Atlanta and Portland experience some of the worst traffic congestion in the nation.
The Texas Transportation Institute indicates strikingly similar data with respect to
roadway congestion and travel time (Table #9).
•
•
•
Portland’s Travel Time Index 28is 1.65, slightly above Atlanta’s and well above
the national average for urban areas of more than 1,000,000.
Atlanta’s Roadway Congestion Index29 is 1.27, slightly above Portland’s and well
above the national average.30
The indices in Atlanta have risen faster than Portland since 1990, but only as a
direct consequence of Atlanta’s failure to provide sufficient highway capacity for
its rising population. Atlanta’s freeway and principal arterial lane miles per capita
were reduced 9.3 percent, compared to Portland’s reduction of 2.6 percent.
Table #9
Texas Transportation Institute Indicators
Travel
Change
Roadway
Change
Change in Lane
Time Index from 1990 Congestion from 1990 Miles per Capita
Index
(1990-1999)
Atlanta
1.63
29.4%
1.27
29.6%
-9.3%
Portland
1.65
23.1%
1.24
22.8%
-2.6%
Average
1.50
12.1%
1.13
14.5%
2.2%
Source: Calculated from Texas Transportation Institute data.
28
Measures the amount of time required to complete a trip during peak travel hours, compared to travel
time in “free flow” conditions.
29
Measures the volume of traffic compared to the capacity of roadways.
30
Atlanta is something of an anomaly with respect to traffic congestion. Overall traffic intensity is not high,
with 55,700 daily vehicle miles traveled per square mile in 1999. This ranks Atlanta 19th out of the top 39
urban areas, and below the average (57,200), Portland (63,400) and leader Los Angeles (120,900).
Atlanta’s principal problem is its virtual complete dependence on its freeway system and lack of an
effective arterial street system (Wendell Cox, “A Common Sense Approach to Transportation in the
Atlanta Region, Georgia Public Policy Foundation, June 2000,
www.gppf.org/pubs/projects/transportation/transportationinfo.htm). Atlanta has the highest Roadway
Congestion Index of any low density urban area.
12
The Future: The traffic situation can be expected to deteriorate further. Portland’s
adopted Regional Transportation Plan, which relies on smart growth strategies and
includes little highway capacity expansion, projects a 600 percent increase in daily
hours of delay on roadways by 2020. Commercial vehicles (trucks) will see an even
larger increase in delay hours, at nearly 700 percent.31 The Atlanta Regional
Commission, which seeks similar development patterns, also projects deterioration in
traffic delays.32 At the same time, Portland’s aggressive public transit strategies will
accommodate little of the projected increase in travel through Metro’s 2040 planning
horizon (Figure #1). Indeed, the total traffic increase in the entire urbanized from 1990
to 1999 represents 1.5 times the amount projected for the 1990 to 2040 period inside
the urban growth boundary (which contained more than 80 percent of the population in
1990).33
Portland’s worsening situation is consistent with both international and national data on
the relationship between traffic volumes and density. Generally, the more dense urban
areas of Europe and Asia have considerably greater traffic congestion than the more
low density American urban areas (Figure #2). US Department of Transportation
research also indicates such a relationship. At the 1,500 to 3,500 per square mile
population densities typical of US urbanized areas, traffic volumes tend to increase
approximately 0.8 percent for each 1.0 percent increase in density.34 The 1999 Texas
Transportation Institute data indicates a strong association between traffic congestion
and population density.35
Finding: Smart growth promises to reduce the amount of travel by automobile. In fact,
the opposite is occurring in Portland, where daily vehicle miles traveled has risen at a
higher rate than any other major urban area.
31
Metro, 2000 Regional Transportation Plan.
According to the adopted Regional Transportation Plan, time spent in traffic congestion is expected to
increase 28 percent by 2025.
33
Estimated using Texas Transportation Institute and Metro 2040 Plan data.
34
Calculated from US Census Bureau data and Catherine E. Ross and Anne E. Dunning, “Land Use and
Transportation Interaction: An Examination of the 1995 NPTS Data,” Searching for Solutions: Nationwide
Personal Transportation Survey Symposium, US Federal Highway Administration, October 29-31, 1997.
35
Each 1,000 increase in population density is associated with an 11 point increase in the Roadway
Congestion Index, for urban areas over 1,000,000 in 1999 (r2=0.377, statistically significant at the 99
percent confidence level, degrees of freedom 37).
32
13
14
AIR QUALITY
Economic Development and Smart Growth notes that the “apparent result” of Portland’s
superior transportation performance is improved air quality. Considerable progress has
been made in improving air quality in Atlanta. From 1988 to 1997, Atlanta days with a
Pollution Standards Index (PSI) of more than 100,36 fell 41 percent, from 44 to 26. While
36
The Pollutant Standards Index (PSI) integrates information on 5 major pollutants (particulate matter
less than 10 microns in diameter, sulfur dioxide, carbon monoxide, ozone and nitrogen dioxide) across an
entire monitoring network into a single number that represents the worst daily air quality experienced in
an urban area. A PSI greater than 100 indicates that at least 1 criteria pollutant exceeded air quality
15
traffic volumes were increasing 215 percent from 1982 to 1997, maximum NOX
concentrations barely changed (Figure #2)
But Portland has done better. Over the same period, Portland fell 100 percent, from
nine to zero. But this improvement has not resulted from any superior transportation
performance in Portland. As was noted above, Portland’s per capita vehicle miles has
risen at the highest rate in the nation. Moreover, from 1988 to 1997, daily per capita
traffic increased 27 percent in Portland, one-third more than Atlanta’s 20 percent rate.
standards on a given day; therefore, air quality would be in the unhealthful range on that day. Data from
the Environmental Protection Agency.
16
In fact, highway air pollution has been improving around the nation for years, largely
due to advances in vehicle emission technology. According to the city of Portland, only
38 percent of pollution results from highway sources. Atlanta’s less successful
performance in air pollution control is the result of factors other than transportation
(such as climate, wind, elevation, upwind power plants, etc.).
Finding: Portland’s superior performance in air quality is not a reflection of its smart
growth policies, because its more rapid increase in highway use would have contributed
to greater, not less air pollution.
ENERGY CONSUMPTION
Economic Development and Smart Growth assumes that smart growth will result in
greater energy efficiency and finds that from 1979 to 1995, per capita energy
consumption fell 7.5 percent in Oregon and rose 11.3 percent in Georgia.37 Economic
Development and Smart Growth refers to the Oregon energy consumption decline as
“dramatic” and the Georgia increase as “surprising.”
Data from the 1990s indicates that the consumption rate differences have been virtually
eliminated. During the period evaluated by Economic Development and Smart Growth,
annual per capita energy consumption rose 1.1 percent in Georgia compared to
Oregon. From 1990 to 1999, the rate was reduced, with Georgia’s per capita
consumption rising 0.9 percent annually compared to Oregon’s. But in the latter part of
the period (since 1995), Georgia’s rate of per capita energy consumption has declined
1.1 percent compared to Oregon’s (Table #10).38
Table #10
Change in Per Capita Energy Consumption
1979 to
1990 to
1995 to 1999
1995
1999
Georgia
0.7%
0.0%
-0.5%
Oregon
-0.5%
-0.9%
0.6%
National
-0.1%
0.6%
1.1%
Georgia in Relation to Oregon
1.1%
0.9%
-1.1%
Source: Calculated from US Department of Energy data.
37
Data for the two metropolitan areas is not readily available.
38
Calculated from data in US Department of energy, Energy Information Administration, State Energy
Data Book 1999: Consumption Estimates, May 2001
17
Moreover, other states that have not implemented Oregon’s strong smart growth
policies have been more successful in controlling the growth in energy consumption:
•
•
•
National Resources Inventory data for 1992 to 1997 indicates that the density of
new urban development was lowest in West Virginia, which developed land at
more than 18 acres per new resident --- more than 40 times the rate of Oregon.
Yet, West Virginia’s per capita energy consumption rose less during the 1990s
than Oregon’s (minus 10.5 percent compared to Oregon’s minus 7.4 percent)
During the 1990s, neighboring Washington, without smart growth policies,
reduced its per capita energy consumption more than Oregon (minus 8.1 percent
compared to minus 7.4 percent).
From 1990 to 1995, Texas, renown for its sprawl and without smart growth
policies, experienced a lower rate of energy consumption increase than Oregon
(an increase of 0.7 percent, compared to Oregon’s increase of 2.3 percent).39
If smart growth were reducing the rate of energy use, Oregon would be reducing its per
capita energy consumption relative to states such as West Virginia, Washingto and
Texas, which have not implemented such strong policies. Moreover, Oregon’s
advantage over Georgia would not have disappeared in the late 1990s, it would have
accelerated.
Finding:
Because Oregon’s recent performance with respect to per capital energy consumption
is not superior to that of states without smart growth policies, including Georgia, smart
growth cannot be credited with generating lower rates of energy consumption.
NEIGHBORHOOD QUALITY
Economic Development and Smart Growth uses American Housing Survey (AHS)40
data on recent movers to indicate that neighborhood quality is declining in Atlanta and
improving in Portland. In Portland, there was an increase in people who had recently
39
40
All data from State Energy Data Book 1999: Consumption Estimates.
US Census Bureau, American Housing Survey.
18
moved who rated their new neighborhood better than their old.41 The same indicator
dropped in Atlanta, but remained above the Portland level.42
But, as in the case of many opinion surveys, the results obtained depend upon the
measure selected. For example, the AHS asks all residents to rate the quality of their
neighborhood on a one to ten scale, with ten being the highest rating. From the middle
1980s to the middle 1990s, the percentage of people rating their neighborhoods in the
bottom one-half (from one to five) rose 41.4 percent in Portland. Over the same period,
the percentage rose a smaller 17.6 percent in Atlanta and 2.6 percent in the nation as a
whole (Table #11).
Table #11
AHS Below Par Neighborhood Ratings (0-5)
1985-7
1995-6
Atlanta
12.1%
14.3%
Portland
12.7%
18.0%
United States
13.8%
14.2%
Source: Calculated from American Home Survey.
Change
17.6%
41.4%
2.6%
Data from the American Housing Survey surprisingly indicates superior ratings for
Atlanta neighborhoods. In 1995-6:
•
32.6 percent of Atlanta respondents rated their neighborhoods as “10,” compared
to 28.5 percent in Portland.
•
72.4 percent of Atlanta respondents rated their neighborhoods as “8” or higher,
compared to 68.3 percent in Portland.
•
Neighborhood composite ratings43 were 8.13 according to Atlanta respondents,
and 7.97 in Portland.
Recent movers also rate Atlanta higher than Portland --- 48.5 percent consider their
new neighborhoods better than their old, compared to 46.4 percent in Portland. Finally,
the American Housing Survey indicates that Portland has a 38 percent higher share of
mobile homes than Atlanta (6.0 percent compared to 4.4 percent), which might be
considered an indicator of inferior neighborhood quality.
41
It might be hypothesized that new movers to Portland are more positive with respect to their evaluation
of their neighborhoods because smart growth policies are attracting an inordinate percentage of upwardly
mobile households. At the same time, there would be fewer movers of lower socio-economic status, and
thus fewer people likely to move into neighborhoods that are no better than previous.
42
The middle 1990s surveys (1995 for Portland and 1996 for Atlanta) are the latest available. Economic
Development and Smart Growth calculates the corresponding changes at +19 percent for Portland and
minus 11 percent for Atlanta. It was not possible to duplicate these calculations.
43
10 points for a 10, 9 for a 9, etc.
19
Curiously, over the same period, Atlanta residents became less concerned about traffic,
according to the American Housing Survey, while Portland residents became more
concerned. In fact, the percentage of Portlanders rating traffic as a problem in their
neighborhoods was nearly double that of Atlanta and the national average in 1995-6
(Table #12).
Table #12
AHS Survey: Traffic Problems in the Neighborhood?
1985-7
1995-6
Atlanta
8.3%
7.1%
Portland
11.3%
13.2%
United States
7.3%
7.4%
Source: Calculated from American Housing Survey data.
Change
-14.7%
16.4%
0.1%
Indeed, Portland scores below a number of urban areas not generally perceived to have
particularly high qualities of life. Approximately 40 percent of Pittsburgh respondents
rate their neighborhoods as “10,” compared to Portland’s 28.5 percent. St. Louis, Detroit
and Philadelphia residents give a “10" to their neighborhoods at rates of 37 percent, 37
percent and 33 percent respectively.44 These comparative scores are surprising in view
of the reputation that Portland has developed as a good place to live. Indeed, Portland’s
composite ranking of 7.97 ranks it at 22nd, virtually in the middle of the 43 metropolitan
areas that are included in the AHS.45
Finding: Subjective surveys can yield contradictory results, as is the case with the
American Housing Survey. Data from AHS can be used to demonstrate both the
superiority or inferiority of neighborhoods and trends in both Portland and Atlanta. The
data is insufficiently precise or consistent to make any judgment with respect to smart
growth and its impact upon neighborhoods.
HOUSING AFFORDABILITY
Economic Development and Smart Growth notes that housing prices have risen more
rapidly in Portland than in Atlanta and are higher than the national average. Indeed,
Portland housing prices have escalated well ahead of both Atlanta’s rate and that of the
nation. From 1991 to 2000 (Table #13):46
•
•
The median priced house in Portland have risen 110 percent from $80,000 to
$168,000..
The median priced house in Atlanta has risen 64.8 percent from $91,000 to
$150,000
44
Calculated using 1994-1998 American Housing Survey results (latest complete iteration of reports)
www.demographia.com/db-metronhdqual.htm
46
Fourth quarter 2000 compared to first quarter 1991. These are the earliest and latest data available on
the National Association of Home Builders database.
45
20
•
The median priced metropolitan house has risen 48.5 percent from $102,400 to
$152,100.
Table #13
Median House Prices
Median House Price
1991
2000
Atlanta
$91,000 $150,000
Portland
$80,000 $168,000
84 Metropolitan Areas
$102,400 $152,100
National
$100,000 $151,000
Source: National Association of Home Builders
Change
64.8%
110.0%
48.5%
51.0%
Economic Development and Smart Growth suggests that:
Despite higher housing prices in Portland than in Atlanta or the nation, the
combination of higher neighborhood quality of life, lower taxes, more accessibility
to land uses, more transportation choices, lower commuting time, lower energy
requirements and lower pollution perhaps means that benefits of smart growth
lead to savings that make households willing to pay more for housing in Portland
than in Atlanta.
In a similar vein, Dr. Nelson theorizes (but does not conclude) that: benefits of smart
growth are capitalized in housing prices that are higher.47
These tentatively stated hypotheses have led to strident claims by supporters of smart
growth. For example, in characterizing work by Dr. Nelson, Utne Reader editor Jay
Walljasper noted that the urban growth boundary was not the cause of higher housing
prices in Portland:
Instead the urban growth boundary and other planning measures turned
Portland into such a choice destination for new businesses, jobs, and families,
that demand for homes is soaring along with wages.48.
But Portland’s housing price increases are not the result of demand caused by rapid
population or employment growth. As indicated above, Atlanta has been more attractive
to both new residents and new employment than Portland since 1990, yet has
encountered much smaller house price increases. The same is true of all other major
metropolitan areas that have grown faster than Portland, such as Phoenix, Denver and
Las Vegas.
47
Effects of Urban Containment on Housing Prices and Landowner Behavior
Jay Walljasper, “Portland: A City that Works Draws Conservative ire: Planning, Transit and the Good
Life Exasperates Free Marketeers (Elm Street Writers Group, Michigan Land Use Institute; www.mlui.org
accessed 24 October 2000).
48
21
Moreover, Economic Development and Smart Growth notes that over the period
studied, the percentage of home owner income committed to housing changed little in
the two urban areas. But this is not a sufficiently precise indicator of housing
affordability, since it includes all home owners, including those who purchased their
homes before the beginning of the study period.
The Housing Opportunity Index: It is with respect to housing affordability that
Portland’s smart growth policies have been most destructive. For most middle income
Americans, home ownership represents a principal source of wealth accumulation.49
The National Association of Home Builders “Housing Opportunity Index estimates the
percentage of homes sold in each metropolitan area that can be afforded by the median
income household. 50 Since 1991, the first year available (Table #14):
•
•
•
The Housing Opportunity Index among 84 metropolitan areas51 has risen 8.0
percent, from 57.352 in 1991 to 61.9 in 2000.53
Atlanta’s Housing Opportunity Index has risen 3.7 percent, from 66.7 to 69.2.
This increase ranks 47th out of 84 areas.
Portland’s Housing Opportunity Index has fallen 55.8 percent, which ranks it last
among the 84 metropolitan areas. Portland’s Housing Opportunity Index is lower
than all of the 84 metropolitan areas except for San Diego, New York and areas
in the San Francisco Bay Area.54
In 1991, Portland’s Housing Opportunity Index was 2.4 percent above Atlanta’s. Now
Portland’s Housing Opportunity Index is 56.4 percent below Atlanta’s (Figure #4).55
49
Wendell Cox and Ronald D. Utt, “Smart Growth, Housing Costs, and Home Ownership,”
National Association of Home Builders (www.nahb.org).
51
All metropolitan areas of more than 500,000 for which data is available.
52
57.3 percent of homes sold could be afforded by the median income household.
53
Data used for 84 metropolitan areas for 1991 (earliest available) and 2000 (latest available).
54
Nonetheless, none of these areas experienced the loss in housing affordability that occurred in
Portland. The California metropolitan areas have long imposed expensive impact fees on new housing,
which has driven up prices artificially.
55
Oregon’s smart growth law applies to all communities. Similar losses in housing affordability have been
documented in Oregon’s smaller metropolitan areas (Eugene, Salem and Medford). See Wendell Cox,
Amendment 24: Pulling Up the Ladder of Housing Affordability,
http://121.org/Sup/Docs/Enviro/HousingAffordability.htm.
50
22
Table #14
Housing Opportunity Index
1991
2000
Atlanta
Portland
84 Metropolitan Areas
National
66.7
68.3
57.3
49.1
69.2
30.2
61.9
59.3
Change
Rank Out of
84
Metropolitan
Areas
3.7%
47
-55.8%
84
8.0%
20.8%
Portland Relative to Atlanta
2.4%
-56.4%
Portland Relative to National
19.3%
-51.2%
Source: Calculated from National Association of Home Builders data
23
Home Ownership: The result is that home ownership has declined in Portland, while it
has improved in Atlanta. From 1990 to 2000, Portland home ownership was down 6.6
percent in Portland, in contrast with an 11.0 percent rise in Atlanta and a national
metropolitan improvement of 6.9 percent (Table #15).56 If Atlanta had experienced the
same loss in home ownership during the 1990s as Portland, 240,000 households who
currently own their homes would be renters instead.57 Alternatively, if Portland had
56
Phoenix, the fastest growing metropolitan area with more than two million residents experienced a
home ownership increase of 10.0 percent from 1990 to 2000.
57
All data from the US Census Bureau.
24
enjoyed the increase in home ownership of Atlanta, 140,000 more households would be
owners rather than renters.58
Table #15
Home Ownership Trends: Atlanta & Portland
1990
2000
Change
Atlanta
61.0%
67.7%
11.0%
Portland
66.5%
62.1%
-6.6%
Metropolitan
61.3%
65.5%
6.9%
National
63.9%
67.4%
5.5%
Source: US Census Bureau
Because of their lower income, racial minorities are disproportionately impacted by
higher housing prices. Minority home ownership in the United States remains at well
below majority White Non-Hispanic rates, despite considerably efforts to spread
economic prosperity to all population groups. In 1999, the African-American home
ownership rate was 47.2 percent, 36 percent below the White Non-Hispanic Rate.
Hispanic home ownership was 46.3 percent, 37 percent below the White Non-Hispanic
rate. Because minorities have generally lower incomes and are entering the home
ownership market at greater rates, any policy, such as smart growth, that reduces
housing affordability will especially disadvantage minorities.
But, progress is being made:
The national home ownership rate reached an all-time of 66 percent in 1997, with
minorities accounting for fully one-third of new home owners. Since 1993 home
mortgage lending for Blacks was up 67.2 percent and for Hispanics 48.5 percent
in an overall market where home lending rose only 18 percent.59
Atlanta is a diverse urban area, with an African-American population of 29 percent and
a Hispanic population of seven percent. This is in contrast to Portland, which has an
African American population of thee percent and a Hispanic population of seven
percent. Up to this time, Atlanta has performed better in expanding minority home
ownership than Portland, but less well than the national rates. In 1995/6, 42.5 percent of
Atlanta African-American households owned their own homes compared to the Portland
33.3 percent share. Similarly, 43.6 percent of Atlanta Hispanic households were home
owners, compared to Portland’s 34.2 percent (Table #17).60
Based upon applying the national minority home ownership increase rates,61 it is
estimated that if Portland trends had applied to Atlanta from 1990 to 2000, 25,000 fewer
58
Assumes 1995 household size.
Paul S. Grogan and Tony Proscio, Comeback Cities, (New York: Westview Press), 2000.
60
Calculated from American Housing Survey data, 1995 & 1996.
61
Annual 1994 to 2000national rates applied for the 1990 to 2000 period for Atlanta Black and Hispanic
households.
59
25
African-American households would own homes, and 3,400 fewer Hispanic
households.62
In Atlanta, and elsewhere across the nation, the reduced affordability that accompanies
smart growth could end, if not reverse the progress currently being made in minority
home ownership.
Moreover, it is not realistic to expect that housing subsidies can be effectively an
effective tool to neutralize the negative effects of smart growth on home ownership. Any
such program would require a large bureaucracy and budget. Moreover, no serious
proposals have been proposed for such a purpose.
The extent to which Portland’s urban containment policies are responsible for its
exclusionary home ownership trend is not definitively known. However, since Portland is
the only major metropolitan area with such draconian policies, and its housing
opportunity performance is so singularly negative suggests a strong causal relationship.
Moreover, such a relationship is consistent with economic principles that associate
higher prices with rationing (in this case, land rationing)..
After decades of efforts to improve the economic status of lower income citizens,
especially minorities, smart growth’s unintended but inevitable promise appears to be to
nullify some or all of the progress. And of course, it is not just those who are denied
economic advancement who are injured, it is entire communities, in which economic
growth is less than it would otherwise be.
Re-lining reincarnated as green-lining: Until recent years, lending institutions “redlined” entire neighborhoods. Red-lining consistent of not making mortgage loans in
entire neighborhoods considered to be of greater risk. The practice was established with
the federal government’s Home Ownership Loan Corporation and was continued by the
Federal Housing Administration (FHA). Loans were not made on property within
neighborhoods deemed to have “detrimental influences,” such as “infiltration of a lowergrade population” or an “undesirable population.”63 Typically such neighborhoods
included large percentages of minority residents. While red-lining has ended, the
imposition of urban growth boundaries threatens to establish a similar practice, which
might be called “green-lining,” by fencing out thousands of lower income, principally
minority households.64 The term “green-lining” is proposed because much of the
justification for urban growth boundaries is environmental --- preservation of open space
and farm land from urbanization. There is no such imperative, because urban
development represents virtually no threat to the enrivonment. From 1960 to 1992 , 1.2
acres of park land has been created for every acre of new urbanization (not including
Alaska). Moreover, the new urbanization has been barely one-seventh that of the farm
62
Atlanta is considerably more diverse than Portland. The 2000 census found that 29 percent of
metropolitan area residents were Black, compared to three percent in Portland. Portland has a slight
advantage in Hispanic population share, 7.4 percent, compared to Atlanta’s 6.5 percent.
63
Kenneth Jackson, as quoted in Comeback Cities.
64
Calculated from United States Department of Agriculture data.
26
land acreage lost. It is estimated that only 2.6 percent of the nation’s land area was
urbanized in 1992 (based upon data from the United States Department of
Agriculture).65 Red-lining and green-lining thus have differing policy objectives, but the
net effect on lower income, especially minority households is virtually the same. Redlining excluded large numbers of lower income and minority households from home
ownership by restricting loans to their neighborhoods. Green-lining will exclude large
numbers of lower income and minority households from home ownership by artificially
and unnecessarily raising the price of housing.
Finding: It appears that the expected economic relationship --- that rationing raises
prices --- holds with respect to housing and smart growth. Portland’s housing
affordability has declined at a far greater rate than any other major metropolitan area. It
appears that a major factor is its smart growth policies.
Table #16
Home Ownership Rates by Race
National
1994
White Non-Hispanic
70.0%
Black
42.3%
Compared to White Non-Hispanic
-39.6%
Hispanic
41.2%
Compared to White Non-Hispanic
-41.1%
Source: US Census Bureau
2000
Change
73.8%
5.4%
47.2%
11.6%
-36.0%
46.3%
12.4%
-37.3%
Table #17
Home Ownership Rates in Atlanta & Portland
1995-6
AfricanHispanic
White &
American
Other
Atlanta
42.5%
43.6%
71.6%
Portland
33.3%
34.2%
66.4%
Atlanta
27.6%
27.5%
7.8%
Compared
to Portland
Source: American Housing Survey, 1995-6
PORTLAND’S URBAN FORM AND EARLY 2000 CENSUS RESULTS
Portland’s planning policies have been favorably reviewed both in this nation and
internationally. An impression has arisen that Portland achieved significant
densification, at least in transit oriented corridors. The Portland urbanized area,66
65
Paul S. Grogan and Tony Proscio, Comeback Cities, (New York: Westview Press), 2000. attributes the
termination of re-lining with contributing to increased levels of minority home ownership and new
development in lower income areas, such as in the south Bronx.
66
Developed area.
27
however, is not particularly dense. The Oregon sector, over which Metro has
jurisdiction, had approximately 3,000 persons per square mile. It is likely that the 2000
census data will show some densification. But, the urban area most associated with
sprawl, Los Angeles, was nearly twice as dense in 1990, at 5,800 per square mile.
Portland’s transit oriented corridors are not nearly so dense as most of Los Angeles,
which contains the broadest expanse of above 10,000 per square mile density in the
developed “new world (Figure #5).”67
67
United States, Canada, Australia and New Zealand.
28
Metro hopes to raise Portland’s density to near that of Los Angeles by 2040.68
Early census data, however, does not bode well for Portland’s smart growth policies.
One of the principal objectives of smart growth is inner city “infill” development. In fact,
modest amounts of infill development have begun in inner city cores around the nation.
Data in a Fannie Mae/Brookings Institution report indicates that downtown areas gained
population in 18 of 24 metropolitan areas, including both Portland and Atlanta.69
However, in the metropolitan context, these gains were small. In Portland, downtown
area captured 0.8 per cent of the metropolitan area’s growth, while Atlanta’s downtown
area accounted for 0.4 percent of growth.
In fact the core counties of Atlanta (Fulton and DeKalb) grew considerably faster than
Portland’s core county (Multnomah) from 1990 to 2000. Atlanta’s core grew 24.0
percent compared to Portland’s 13.1 percent.70
In spite of all its planning, in many ways Portland is a typical sprawling American urban
area. This was noted by respected new urbanist architect Andres Duany in a column for
the Portland Oregonian following a recent visit.
To my surprise, as soon as I left the prewar urbanism (to which my previous
visits had been confined), I found all the new areas on the way to the urban
boundary were chock full of the usual sprawl one finds in any U.S. city71
Finding: Despite its smart growth policies, Portland is little different from other urban
areas. Most growth is in peripheral areas, with comparatively little growth in the center.
PORTLAND’S AMERICAN DREAM BOUNDARY
The conclusions of Economic Development and Smart Growth were not only tentative,
but premature (Table #18).
•
•
•
•
Employment is growing at a higher rate in Atlanta than Portland.
Income is growing at a higher rate in Atlanta than Portland.
Government revenues and expenditures are growing at a slower rate in Georgia
than Oregon.
Per capita automobile use is rising less in Atlanta than Portland.
68
Metro’s 2040 Plan calls for densities inside the urban growth boundary to be approximately 5,000 per
square mile by 2040, approaching the 5,800 of Los Angeles.
69
Rebecca R. Sohmer and Robert E. Lang, Downtown Rebound, Fannie Mae Foundation and The
Brookings Institution, 2001.
70
Both cores approximately one-third of the metropolitan population.
71
“Punching Holes in Portland,” Andres Duany, The Oregonian, December 19, 1999.
29
•
•
•
While Portland’s air pollution trends are more positive than Atlanta’s, smart
growth is not the cause.
Oregon’s increase in energy consumption is only slightly below that of Georgia.
Housing affordability has declined precipitously in Portland, while it has increased
in Atlanta.
This latter impact may be the most important. In Portland, the “American Dream” of
home ownership appears on the way to extinction for most. The economic and social
impacts of such a policy are at odds with both the tradition and the promise of this
nation.
30
Table #17
Summary of Atlanta and Portland Smart Growth Impacts
Issue
Trend Potentially
Trend Identified in
Assessment
Attributable to Smart
this Report
Growth Trend
(Identified by Nelson)
Employment Growth
Portland greater than Atlanta greater than
Expected smart
Atlanta
Portland
growth impact not
Income Growth
Portland greater than
Atlanta
Atlanta greater than
Portland
Government
Revenues &
Expenditures
Oregon rate of
growth less than
Georgia
Georgia rate of
growth less than
Oregon
Transportation
Portland growth in
per capita vehicle
miles less than
Atlanta
Portland trend More
favorable than
Atlanta due to
reduced auto use
Atlanta growth in per
capita vehicle miles
less than Portland
Air Quality
Portland trend more
favorable than
Atlanta despite
greater increase in
Portland auto use.
Oregon energy use
advantage fell to
2.5% in the 1990s
Energy Consumption
Oregon energy use
fell more than 15%
relative to Georgia
Neighborhood Quality
AHS recent mover
data shows more
positive Portland
trend.
Other AHS data
shows more positive
Atlanta trend.
Housing Affordability
Superior community
value is capitalized in
higher housing
prices.
Portland affordability
has fallen far faster
than any other major
metropolitan area.
Infill and Population
Density
No statement by
Nelson, but smart
growth promises to
direct growth back to
the center.
Census data
indicates most
Portland growth was
on the periphery.
Atlanta core counties
growth stronger..
31
evident
Expected smart
growth impact not
evident
Expected smart
growth impact not
evident
Expected smart
growth impact not
evident
Superior Portland
trend not
attributable to
smart growth
Trend of
convergence is
opposite expected
smart growth
Impact
AHS data is
insufficiently
conclusive to
make a judgment.
Smart growth is
having the
expected impact of
artificially
excluding lower
income
households from
home ownership
Expected smart
growth impact not
evident.
WENDELL COX
Wendell Cox is a senior fellow at the Georgia Public Policy Foundation. He is principal
of Wendell Cox Consultancy, an international public policy and demographics firm
located in St. Louis. Mr. Cox was appointed to three terms on the Los Angeles County
Transportation Commission (1977-1985) by Mayor Tom Bradley and was appointed by
Speaker of the House Newt Gingrich to complete the unfulfilled term of New Jersey
Governor Christine Todd Whitman on the Amtrak Reform Council (1999). He authored
the Georgia Public Policy Foundation study “A Common Sense Approach to
Transportation in Atlanta,” in 2000.
Wendell Cox holds an MBA from Pepperdine University in Los Angeles, and a BA in
Government from California State University in Los Angeles. He was born in Los
Angeles, grew up in British Columbia, Washington and Oregon and was Oregon state
high school champion in the mile run and cross country.
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