HomeMy WebLinkAboutAgenda Report - June 20, 1991 (68)�CW
CITY OF LODI COUNCIL COMMUNICATION
4Fpw+.
AGFIM TITIE: 1991-92 Appropriations spending Limit
MEETING DATE: June 20, 1991
PREPAM BY: Finance Director
RF)OOMWM ACTION: That the City Council provisionally set the 1991-92
Appropriations Spending Limit at $33,441,797 as calculated
using:
1. The percentage increase in the California Per Capita Inccane; and
2. The greater of the percentage .increase in the City's own population growth
or the population growth of the entire San Joaquin County.
These figures were suppliedby the California Department of Finance. The
1991-92 Appropriations Spending Limit YnF require adjusturent if the County
As se. sor ` s Office provides data showing that percentage change in the local
asseskrent roll from the preceding year due to the addition of local
non-residential construction is greater than the percentage increase in the
California Per Capita Income. The County does not have the ability to provide
this information at this titre .
BACKGROUND IWORMATION: Article XIIIB of the California State Constitution
specifies that an annual Appropriations Spending Limit
shall be established to place limits on the amount of
revenue which can be spent by the city. In J1une,
1990, proposition Ill was passed which modified the earlier proposition 4 and
the corresponding legislation regarding calculation.
The current legislation has dwwgud the annual growth adjustrrent factors used
in the calculation of the Appropriations Spending Limit- The City Council must
choose between:
1. The population growth of the city; OR
2. The population gz Lvth within the County.
The recomrendation of the Finance Dunt is to use the percentage which
Will result in the highest Appropriations Spending Limit. The population
growth of the County is higher in fiscal year 1991-92. The population growth
of the City was higher during fiscal years 1987-88 through 1990-91.
APPROVED: t .liter
THOMAS A. PETERSON
City Manager L]
CC..APR0/CO.00M CC -1
1991-92 Appropriations Spending Li dt
June 20, 1991
Page Two
Currently, the county does not have the ability to provide the data for the
change in non-residential assessment. Therefore, vie have no choice but to use
the California Per Capita Insane as part of the calculation. In future years,
the Council w i 11 also have to maks a selection between these two items.
In calculating the 1991-92 Appropriations Spending Limit, the new growth
factors were applied to the 1986-87 Appropriations Limit and each year
thereafter. This did not change the limits €or these years but allowed the
accumulated growth in these years to be applied to the current year.
See attached Exhibit A for the appropriate growth rate factors and
Appropriations Spending Limit calculations.
F'JNDING: Does not apply,
H. Holln
Finance Director
RHH:DW: ss
Attachment (Exhibit A)
Prepared by Diana White, Assistant Finance Director
OC APRO/CO.CCM
City of Lodi
Appropriations Spending LL.Li.t
Growth Factors/Calculations
GROWr ! FACTORS:
FY 87-88: (1.0347)x(1.0572)=1.0939
(1.0939)x$22,654,787=$24,782,072
ISE: $22,654,787 was 86-87 Appropri at3ons Spending Limit.
EY 88-89: (1.0466)x(1.0496)=1.0985
(1.0985)x$24,782,072-$27,223,106
FY 89-90: (1.0519)x (1.0252) =1.0784
(1.0784)x$27,223,106=$29,357,398
FY 90-91: (1.0421)x(1.0226)=1.0657
(1.0657)x$29,357,398=$31,286,179
FY 91-92: (1.0414)x (1.0264)=1.0689
(1.0689)x$31,286,179=$33,441,797
FOIA ASI,/00.OD14
% Increase
Fiscal
Per Capita
city
county
Year
Incxme
. Population
Population
87-88
3.47
5.72
3.33
88-89
4.66
4.96
3.32
89-90
5.19
2.52
2.20
90-91
4.21
2.26
2.23
91-92
4.14
1.19
2.64
FY 87-88: (1.0347)x(1.0572)=1.0939
(1.0939)x$22,654,787=$24,782,072
ISE: $22,654,787 was 86-87 Appropri at3ons Spending Limit.
EY 88-89: (1.0466)x(1.0496)=1.0985
(1.0985)x$24,782,072-$27,223,106
FY 89-90: (1.0519)x (1.0252) =1.0784
(1.0784)x$27,223,106=$29,357,398
FY 90-91: (1.0421)x(1.0226)=1.0657
(1.0657)x$29,357,398=$31,286,179
FY 91-92: (1.0414)x (1.0264)=1.0689
(1.0689)x$31,286,179=$33,441,797
FOIA ASI,/00.OD14
RESOLUTION NO. 91-119
RESOLUTION SELECTING N44 -PL GROWTH ADJUSTMENT FACTORS
AND ADOPTING A PROVISIONAL APPROPRIATIONS SPENDING LIMIT
FOR 1991-92 1 N COMPLIANCE WITH PROPOSITION 111,
ARTICLE X I I I B OF THE CALIFORNIA STATE CONSTITUTION
RESOLVED, that the City Council of the City of Lodi does hereby select the
annual growth adjustment factors and adopt a provisional Appropriations Spending
Limit for 1991-92 in compliance with Proposition 111, Article X I I I B of the
California State as follows:
I. 1991-92 Growth Factors Used:
A. Population growth within San Joaquin County of 2.64%
B. Growth in California Per Capita Income of 4.14%
11. Appropriations Spending Limi t:
Total Appropriations Spending Limit for 1990-91
(allowing for accumulated growth due to new growth
factors being applied and to FY 1987-88 through
1989-90) $31,286,179
Increased by allowable San Joaquin County population
growth of 2.64% multiplied by California Per Capita
Income of 4.14%
Therefore, the Appropriations Spending Limit for 1991-92 $33,441,797
The 1991-92 Appropriations Spending Limit may require adjustment if the
County Assessor's Office provides data showing that percentage change i n the
local assessment roll from the preceding year due to the addition of local
non-residential construction is greater than the percentage increase in the
California Per Capita Income. The County does not have the ability to provide
this information at this time.
Dated: June 20, 1991
1 hereby certify that Resolution No. 91-119 was passed and adopted by the
City Council of the City of Lodi in an adjourned regular meeting held June
20, 1991 by the following vote:
Ayes: Council Members - Pennino, Pinkerton, Sieglock, Snider and
Hinchman (Mayor)
Noes: Council Members - None
Absent: Council Members - None
Alice M. Reimche
City Clerk
RES91119/TXTA.02J
�. Approved by ty Council 4/12/89
Amended 4/11. 25/90 and 12/19/90
FIVE-YEAR PHASING SCHEDULE
CITY OF DAVIS PHASED ALLOCATION PLAN
The following schedule represents the initial schedule for the eligibility
of approved projects to apply for residential building permits. The
figures represent the maximum number of residential building permits which
may be processed for each project with each fiscal year for single-family
units. The multi -family unit allocations may be processed at any time
during the five-year period.
- - - - - - - - - - HOUSING UNITS - - - - - - - - - - - - --
N. Davis Farms
20
4
24
Northstar
107
133
80
20
340
Wildhorse
75
85
104
264
Crossroads
85
135
85
70
100
475
Stonegate East
90
59
83
284
516
Mace Ranch
105
105
105
105
1053
210
735
Oakshade
30
124
72
1 45
17
1
203 1
491
Willowcreek
50
53
103
Waggener
130
130
MacDonald
1
45
1
4
FDC/Southfield
45
40
85
Sunnyside
30
38
68
Evergreen 1
25
25
119
169
willowbank
13
13
I
In 1989 only, building permits may be issued one month
prior to the beginning of the 1989-90 fiscal year.
2
Single-family units to be sold for less than $200,000:
Crossroads, 50 units; Oakshade, 49 units; Sunnyside, 30 units.
3 Living groups, co -housing, and housing developed by non-
profits for permanent affordability, with no more than 150 such
units annually.
The City Council approved 105 units to either Single-
family for 1995/96 or Multi -family for 1990/96.
NUMM aAL rrarAr u
as "39s
RM
ar+q r r'A►uLr eMr•I�t�
snt TABLI&A im
rrrw
Arwy urrY . . .
nr f�ti • nYYr*u�•w • .
titi •NYf•tY.A.�YMrINr
IWVYTIYM• N
r nwTK4IRm i s Asia
Y+r uw
fi WiYM � � • w r��
MYt YY►rr.r.
.rYs V V rN.
C.tbtMVATIri N'M4AMU a Ams
wr naI .uw.•.
MwW ..M.ibY{Ytir
PYMYf tYNNr.
prWMN{
V QU4" ruin w a A"es
r M MIa1r1AL rkwAr111 Is Aralm
�ot.uanal
Muu• :..
• A t Y f f{ t f
��.ssals�l
i,
i
CHILES
j.
P A R K
i aAw _ CALVO{M4
1"Snr RAM
--==M-
Neumiller & Beardslee
A PROFESSIONAL CORPORATION
FOUNDED AS
ASHLEY s NEUMILLER ATTORNEYS AND COUNSELORS
JANUARY f9O3
FIFTH FLOOR WATERFRONT OFFICE TOWER II
509 WEST WEBER AVENUE
STOCKTON. CALIFORNIA 95203
GROWTH CONTROLS AND HOUSING PRICES: SELECTED
NAILING ADDRESS:
PO BOX 20
STOCKTON. CALIFORNIA 3 82 01-3 02 0
TELEPHONE 12091 946-5200
FAX (209) 9a8-4910
-NOVEMBER 1989
0
LINES
LINCOLN
,,INSTITUTE
'-OF LAND POLICY
Inside this Issue
Case in Point 2
Lincoln Calendar 3
b a d Titles 4
Deeds 5
Siting$ 6
THE LINCOLN INS1irt1TE OF LANDPOLICY is a
non -pmt educational institution that enables
policymakem administrators, andother stu•
dents toexplorethe complex linkages betweet.
publiepolicies, including taxation. and land
policy. and the impact of these policies cn
major issues of our society. The major goal of
the Institute is tointegrate t! ! . practice
end understanding of land policy and those
forces influencing that policy, especially taxa-
tion, which hawsignificant impact uponthe
lives and livelihood ofall people. The Institute
is a tax exempt school providing advanced
education in land amoomics, including
property taxation, and offering challenging
opportunitiesfor learning, research and publi-
cation.
LAND rMMSis published six times each
year by the Lincoln Institute of Land Policy
® Copyright 1989
Linco!n Institute of Land Policy
26 Trowbridge Street
Cambridge, NIA 02138
617/6613016
Do Growth Controls
Really Matter?
William A. Fischel
Professor ofEconornics
Dartmouth College
This article is abstracted from a
comprehensive review ofgrowth
controls that Professor Fischel is
now completing for the Lincoln
Institute ofl and Policy, with
funding from the Urban Land
Institute Thestudy reviews the
empirical evidence and findings
of&w, IZO published studies.
Here Professor Fischel provides
the conclusions that he has
reached from the evidence. The
full study, available from the Lin-
colnlnstitute later thisyear, criti-
cally reviews empiriealstudies on
zoning andgrowth controls.
that growth controls are efficient or in-
efficient. While many studies show that
growth controls do have effects, few at-
tempt tomeasure both benefits and costs
of land use regul ation. The few cosUbenefi t
analyses that exist indicate that growth
controls are likely to be inefficient. The
major costs seem to be wasteful decen-
tralization of employment locations and
too much commuting.
The focus of the literature surveyed for
this study was local government control
of development, not national environmen-
tal policy. Theselocat controlis iinidude
tightening Of traditional zoning laws as
well as mom Itoria'on the extension of
water andsewer tines andnonprice ra-
tioning on building permits.
Causes and Consequences
of Growth Controls
Recent growth management programs
most frequently occur in two types of com-
munities. Small, relatively affluent cities
and suburbs are the typical locus of exclu-
sionary zoning policies.' I have argued
elsewhere' that the growth control move-
ment was in part caused by judicial and
state legislative attempts to limit exclu•
sionary zoning. These limitations may
have led the affluent communities that
did not want to accept large amounts of
low-income housing to adopt a fail -back
policy of excluding all new housing.
Growth controls are seemingly beyond ju-
dicial reproach on exclusionary grounds
because they democratically exclude
everyone. Indeed. many growth manage-
ment programs go out of their way to
mention that what little growth does oc-
cur should contain a low and moderate
income housing component. Such benevo.
lence may not offset the overall effects of
reotrirtion on the housing market.
Growth controls also seem to arise
often in states in which citizen ballot in-
itiatives are common. Direct democracy
allows for little of thecompro—i— and
bargaining that goes on in representative
government. Measures that provide a
small benefit for a iarge number of voters
and impose a iarge cost on an isolated
group of citizens are more likely topass
in a plebiscite than in a legislature.
Growth controls adversely affect a rela-
tively small number of voters in the
jurisdiction—landowners and business
interests—while providing financial gains
or community amenities to a large num-
ber of existing residents.
Courts of law might offset this political
imbalance if they were to respond to de-
veloper complaints about such practices
by requiring that the commucity pay just
compensation for the devalued land. No
state court, however, has intervened sole-
ly on the basis of landowner devaluation
unless the errant regulation is so extreme
that it ieaves the landowner with almost
no use for his or her land. The consensus
of legal observers is that the California
courts have been the most accommodat-
ing to community regulation and the
least sympathetic to landowner co=lt
plaints.' This. combined with the wide-
spread use of voter initiatives. has made
(Continued on pg 2)
WILLIAM A. FISCHEL is a Professor of Eco-
nomics at Dartmouth College. where he has
been a faculty member since 1973. Author of
The Economics of2oning Laws: A Property
Rights Approach toAmerican Land Use Con-
trols (Johns Hopkins University Press, 1985).
Recently, ha has organized a conference of
legal scholars on the takings issue (papers pub-
lished in the Columbia Law Review) end a con-
ference of economists on land use controls
(papers to be published in Land Economics)
-2 i LINCOLN INSTITUTE (IF LAND POLICY LAND LINES
Do Growth Controls
Really Work?
(Continued from pg. 1)
California the undisputed leader in
growth controls both in the 1970s and
the 1980s.
The result of these two settings—
small affluent communities or communi-
ties that adopt controls by referendum—
is that growth controls are apt to go too
far. In situations where some type of
controls may be efficient in facilitating
reasonable development, communities
will tend to adopt controls that are too
extreme. The cost of voting for extreme
controls is not brought home to the
voters or suburban councils because
those adversely affected are either a
small fraction of the electorate or not
resident in the community at all.
Aside from their adverse effects on
the cost of housing, inefficiently restric-
tive grnwth controls probably cause
metropolitan areas to be too spread out.
This is not to deny that growth controls
may make development in individual
municipalities more compact. Such local
ordinances cause developers to go to
.other communities. The most likely al-
ternative sites are in exurban and rural
communities, where the political climate,
at least initially, is more favorable to
-� development. As these communities in
turn become partly developed, the new.
comers wrest the political machinery
from the progrowth farmers and busi-
ness interests. Then these communities,
too, adopt growth controls, sending de-
velopment still farther from employment
and commercial centers, Eventually, errF
ployment and cannercial activities also
disperse from traditional population
centers as they find that employees and
c sb=ew ate harder to find.
The long -run effect of this is a lower
standard of living. People will commute
more than they otherwise would, which
reduces their real inwmes; Dispersion of
residences and Jobe promotes more au•
tomobile travel and longer trips, mat-
ing more congeation and pollution and
eventually requiring more highway con-
struction.
A tic>ne subtle consequence of ineffi-
ciently dispersed homes and businesses
is the Ions of agglomeration economies
for firms, 7be advantages of operating a
business in the proximity of many other
businesses is one basis for urban econo-
mies. Location in a city allows firms to
have access to a more skilled and flexi-
ble labor force. It also permits the face-
to-face exchange of ideas, which pro-
motee innovation. Ebroas that tend to
disperse firms erode euch advantages
and reduce potential output from the in-
dustry. Though advances in telecominu-
nications and electronic media have
induced at least some businesses to
leave urban areas without any loss of ef-
ficiency, such firms are still the excep-
tion. Face-to-face contact is an essential
ingredient of most growing businesses.
Conclusions
Is Land use controls do provide some
benefits that would be difficult to ob-
tain under less coercive conditions.
Aboli:,ion of zoning and related con-
tmals would create a demand for alter-
native controls It is not clear that
these alternatives would be less costly
to administer or mare efficient in
their effects than zoning.
■ Gbmkh controls and other aggressive
extensions of land use regulations
probably impose costs on society that
are larger than the benefits they pro-
vide. The higher housing prices as-
sociated with communities that
impose growth controls are more like-
ly the result of wasteful supply con-
straints than benign amenity
production The last conclusion is
more tentative because only a few
studios have addressed it in a persua-
sive framework.
NOTES
'Rolleston, Barbara Sherman, "Determinants
of Restrictive Suburban Zoning: An Empiri-
cal Analysis." Journal of Urban Economics
21 (January 1987Y 1.21.
71whel, William A. The Economics of Zon-
ing L(uvs: A Property Rights Approach to
American Land Use Controls. Baltimore:
Johns Hopkins University Press, 1985. chap-
ter 15.
'Ellickson, Robert C.. and A. Dan Tarlock.
Land Use Controls: Cases and Materials.
Boston: cattle, Brown, 1981, page 75.
Nu%t?t esr.tt lwn
Capitalization of Regulations
in Land Values
study of growth controls in Fair-
fax County, Virginia, provides
good evidence of the effects of
controls on land values. For a 1974 un-
published study on "Land Prices and
Factor Substitution in the Metropolitan
Housing Market" (Urban Institute work-
ing paper 1207-24), George E. Peterson
obtained a sample of almost all of the
vacant, residentially zoned parcels that
sold in Fairfax County during the period
196373. He estimated price per acre of
each parcel with and without the zoning
constraints included. The addition of
zoning constraints showed that zoning
influences land values.
Peterson calculated price per acre ef-
fects by distance. He found that on land
next to the central business district
(CBD), there was a seven -fold price
difference between land zoned for 20
units per acre and land zoned for one
unit per acre. On land fifteen miles
from the CBD, this differential shrunk
to "only" a three -fold difference between
20 units per acre and one unit per acre.
This answers one objection to zoning
studies. which is that even in the ab-
sence of zoning. lots would be larger in
the suburbs. This is true, but in Peter-
son's sample, the large minimum lot
nzeswere still abinding constraint in
the farther suburban areas of the
county. Moreover, this finding shows
that restrictive controls applied to a
large fraction of suburban land can have
significant effects on urban structure,
pushing development to remote locations
as close -in development is precluded.
Peterson's observation period over-
lapped the beginning of Fairfax
County's sewer moratorium, which be-
gan in late 1972. Peterson found that by
1973, the sewer moratorium's effects
radically changed his model's estimated
effects. Having a grandfathered and
thus permissible sewer connection
pushed the value cF a lot way up, while
the implicit value of other characteris-
tics. such as proximity to the CBD , actu-
ally fell. Even his measure of permitted
land use intensity, the zoning variable,
became much less significant. This sug-
gests an important override effect of
growth controls. The existence of new
controls map reduce the apparent impor-
tance cf old controls. such as traditional
zoning.
FROM: "DO GROWTH CONTROLS REALLY
MATTERT' By William A. Fischel
v
!i.
. v
PRINCIPLE HOUSING FINDINGS
CT7\rrIVT.TT TW
o An average of 315,000 housing units need to be built annually through
1985.
o Approximately 4 percent (365,000) of existing housing units need to be
replaced.
o Nine percent (860,000) of existing housing units need to be
rehabi 1 i to ted.
0 23% of all low income households pay more than 250 of their income for
housing.
o The median price of a home in California in 1980 was $97,961 while
nationwide the median price was $62,060.
o 430,000 households are overcrowded.
The following conditions contribute to California housing problem:
o The post-war baby boom generation is moving into the household
formation period.
o Net immigration into California is on the rise.
o The number of households has increased due to high divorce rates and
professional men and women marrying later.
o Housing lots have become increasingly scare in California's
metropolitan areas.
o High inflation has caused savers to turn to other investments, thus
making mortgage funds from banks and savings and loans scarce and
available only at high interest rates.
o.;,, use -.regulation's` pernttsI . and=everchanging building 'standards are
increasing housing Costs.
o Californians now pay an average of 37% of their income towards house
payments. (Nationally, house payments average 24% of inane).
l� SOURCE: Ca Tax Research Bulletin, October 198i pg. 3
UT
i
14EASURE A
THE GREENBELT INITIATIVE
On August 25, 1981, the voters of the City of todi approved
an initiative ordinance which eliminated the City's Planned
Urban Growth Area from the Land Lke Element of the General
Plan. The effect of this Ordinance was to establish the
new urban growth boundary at the city limits as shown cn
Exhibit A. At the present time, annexation of County
property to the City for urban development purposes is not
possible without an amendment to the Land Use Element of
the General Plan.
The effects of this initiative upon housing cannot be
determined at this time. It has affected the assumptions
concerning housing since properties once considered
potentially buildable are now excluded. If construction is
to occur, it will be limited t c those areas already
within the City limits. Any direct relationship betvieen
the Greenbelt Initiative and fluctuations in construction
activity cannot be proved due to innumerable other
variables which include interest rates availability and
development of land in nearby areas, and weather
conditions.
It#<f iaied ghat as theamoc�n of -=vacant Cy`tand
r a
l.'iite prte o�emm#nfng` va�ani: "tend wit ! increase, -and
2. t'he devetopm� t= tfi8' with occur, . in att probability,
be at `higher density �untts:per acre) dee to
increas`d grid casts.
Ix
REAL ESTATE
?:.'^�r r,:' f :wr-:� F:': .-�:.;Ti•. ,,y.. K - F_qy ,:i;��;•` .:.`• r..,K v -`::. '
HE LONG-RUNNING ROOM in
Southern California is the stuff
most chambers of commerce can
only dream of a soaring popula-
tion, office buildings sprouting everywhere.
and prices on some single-family homes
climbing in value by more than 52,000 a
week. But lately something has changed.
Growth isn't such a kick anymore. Increas-
ingly it's looked upon as a threat to a pleas-
ant and prosperous way of life, and as
something to be resisted. The growth -con-
trol movement that has resulted jus: may be
the harbinger of a national trend.
For much of the population of Califor-
nia. and particularly that of the vast moun-
tain-ringed Los Angeles basin. economic
growth now conjures up visions of stupen-
dous traffic jams, overflowing sewer sYs-
terns. and pollution -filled air. The natives
are growing rebeltious. In 1986.69% of the
voters in Los Angeles approved a plan to
slash by half the allowable density of future
commercial and industrial buildings in
most of the city. Last year a slow -growth
candidate won a seat on the Los Angeles
city council, defeating the council presi-
dent. Across California 14 of 20 growth -
control initiatives carried the rote in 1987.
Eight of ten cities in Ventura County. just
west of Los Angeles, have passed slow -
growth measures in recent years. In all. 57
cities and eight counties in California have
voted to limit growth. according to Made-
lyn Glickfeld, an urban planning consultant
in Malibu.
"There was a time when Los Angeles
was going forward and people wanted
growth," says Sandy Brown. a physician's
wife in Westwood, an upscale neighbor-
hood that includes the campus of UCLA.
But then a few years ago. Brown stared out
her kitchen «indow and saw a bulldozer
pulling down yet another home nearby to
make room for apartments. "All of a sud-
den 1 wid to myself, 'What is going on
here?"' She proceeded to help create
Friends of Westwood, a neighborhood as -
Massive housing projects forced into areas far fromwhere residents work have led to jammed Riverside and Orange Countyfreeways.
R �
,,. ■ t A �--, '�. .;let �
Sharon Browningtri es to keep the peace.
sociation that has become the scourge of
developers 'For years growth didn't in-
trude on my comfort mn� says Brown.
"But now it's become an infringement on
my way of life."
UCH SENTIMENT in favor of
stowing or halting growth could
prove a more virulent national
movement than the tax reform
measures that began in California with
Proposition 13 in 1978 and spread to many
other states. "No -growth is
more fundamentally grass roots
than Proposition 13," says
Dwight Worden. a Solana
Beach, California. attorney
who has written nearly a dozen
growth -control measures for
different ballots. "Proposi-
tion 13 had a charismatic lead-
cr in Howard Jarvis," observes
Worden. "This movement has
no single leader. It is spontane-
ous in city after city."
Less vigorous strains of the
antigrowth virus are already
flourishing around the country
in parts of New York. Virginia.
and North Carolina. Former
U.S. Senator Paul Tsongas of
Massachusetts is publicly op-
posing uncontrolled growth on
Cape Cod, and a senior aide to
Governor Thomas Kean in
New Jersey declares growth
management the "biggest
looming public policy issue in
the state." But (ew regions have
ever succeeded in using this
concern to generate support for
useful. comprehensive p hn-
,. ning. J. Ronald Tem illiger, head ofTram-
mell Crow Co.'s residential division, the
biggest builder of apartments in the coun-
try, notes that antigrowth feeling was rare
ten years ago. "``ow." he saes. "of the 60
cities where we operate, wc� see step
it in about half"
If you go back to (he 1970s, "It's 11
you can find some precursors
of the present drive for slower peoplf
growth. The movements then
ostensibly were prompted by bfebo
concern for the environment. .
but sometimes were just dis- a ee
guised opposition to construe- Save f
tion of low-income and
multiracial housing. which op- Selye!
ponents thought were a threat not le,
to properry values. The currenr
sentiment, on the other hand.
more often stems from immedi- anyotl
arc and infuriating problems on bol
created by rapid commercial or
residential development, says
Harvard economist Joseph Kalt: "Thistime
it is the reality of inadequate roads. sewers.
water systems. and other infrastructure,"
Across the country citizens have re-
sponded in ways cften heavy-handed. City
councils and planning authorities arc being
REAL ESTATE
pressured into forcing developers t o pay ev-
ery nickel of the cost of the added public
services that their projects make necessary.
This usually means that new businesses and
new -home buyers wind up paying just that
much more. Ballot measums
have also imposed severe and
inflexible limitations on new
construction. Such extreme
in a steps reflect 3 deeply felt re-
t sentment—often justifiable—
that citizens have lost control
Ig to of their local governments to
developers.
em- For all the sedottsrtess of the
conditions that spark it, the
by push to slow growth can end up
;fng causing severe problems, even
for the people behind the
movement. The short-term re -
else sult of limiting growth in a
A," community iS often to create a
housing shortage, sending
home prices showdrtg skyward
and forcing many of those vdthjobs in the
am to live far away. This only dogs high-
ways all the more. Typicallysach initiatives
curtail the growth of housing more than
they do any increase in the number oflobs,
compounding the problem. Ultimately, a
community can price itself out
of business expansion, and in
fact drive some businesses out.
leading to a loss of tax revenues
and deterioration of services
and Property vAues. As young
workers are forced to live else-
whem employers halve to pur-
sue them.
The movement also sets up a
wrenching conflict between the
haves and the have-nots, -It's
like people in a lifeboat agree-
ing to save themselves by not
letting anyone else on board."
says Frank Mittelbach, a pro-
fessor of urban economics at
UCLA. "The people in the wa-
ter should have a vote."
In Los Angeles consider-
ations as diverse as geography
and taxes have come together
to push slow -growth sentiment
onto fact -forward. The five -
county Loc Angeles area, with
its beaches and good weather,
I,;,% attracted many new resi-
dcntc anxious for a more pleas-
anI life. Between 1975 and
1987 the reputation of the met -
Developer Ray Watsonsays his company's c o sts h ave soared.
41A
k:
il
9
w
REAL ESTATE
ropolitan area grew rapidly, adding almost
three million people, 22 times as many as
the metropolitan New York area gained.
Los Angeles also has become a prime ex-
ample of urban sprawl -95% of the re-
gion'sjobs are outside the downtown area.
Even as the region has boomed, its abili-
ty to handle growth has diminished. Since
the mid -19705, California has fallen to49th
among the 50 states in per capita spending
on roads. Adjusted for inflation. nation-
wide federal spending for many infrastruc-
ture programs has decreased since 1980. At
the Sametime. the California tax initiative,
Proposition 13, has limited property taxes
on homes that have not been sold since
1978. Still other measures severely limit
what a municipality can spend even if it is
growing rapidly.
Nowhere is the pace of development
more visible than in southern Orange
County. down the coast about 50 miles
south of downtown LA What not too
tong ago were vast ranches still largely in-
tact from the rime they were granted to set -
tiers by the King cf Spain, now crawl
with bulldozers and earthmovers. Even in
the face of antigrowth campaigns, vast
stretches of hillside are being stripped
bare for construction.
A double whammy is at work
here: Those Proposition 13 -
style tax -cutting measures have
wound up tempting many fi-
nancially desperate municipal-
ities to ignore good planning in
pursuit of another source of tax
revenues -commercial growth.
"Proposition 13 is driving
changes in land use," says C.
Bradley Olson, an executive at
the Irvine Co.,which owns and
is developing a 100 -square -
mile tract of land in Orange
County. "The city of Costa
Mesa near here gets huge sales
Wes from a big shopping cen-
ter it allowed there. But people
from all over drive there. so Costa Mesa
has huge traffic problems."
Sometimes the hunger for tax revenues is
almost comical. To win city approval for a
big project on its land in Tustin. the Irvine
Co. had to agree to include a dozen auto-
mobile dealerships in its plans so Tustin
could colkct sales taxes on all the new cars
sold within its borders.
More often towns pursue developers of
high-rise office buildings while vigorously
REPORTER ASSOCIATE Kate Gallen
Tom Rogers battlesagainst developers.
opposing new housing, which would re-
quire adding expensive new municipal ser-
vices such as schools. "There is an absolute
imbalance of jobs and houses," says John
Martin. the Jrvine Co.'s head of residential
marketing. "There has been an average of
53,000 new jobs a year created in Orange
County for the last five years.
and for that we should have
built 42,000 housing units. But
at tops, Orange is adding only
20,000 units a year." As 3 re-
sult, workers clog the freeways,
driving long distances to get to
work. "The commute to River-
side used to rake 40 minutes
during rush hours." says Mar-
tin. "Now it takes 2% hours."
Talk about lifestyle.
Infrastructure problems dog
outlying areas too. With plan-
ning commissions there less
sensitive to the growth issue,
builders are able to put up mas-
sive housing developments in
what was previously untouched
terrain. packing the units together as tightly
as if they were in the middle of a city. In
some big developments south of the Irvine
properties. one noteworthy amenity is in
short supply: main roads. Commuters froni
thousands of homes are funneled into a
handful of strecis before reaching the near-
est freeway.
With frustration over growth mounting,
developers usually reel the heat. and no
or.c is turning up the lemper,irure more
vigorously in Orange County than Tum
"it was so-
cialism for
the wealthy,
an attempt
by develop-
ers to put
the cost of
their sins on
the public."
126 FORTUNE DECEMtlLR 5. 19XX
Rogers, who has emerged as an unlit
leader of the slow -growth movem
there. Rogers, 63, a small-scale shopp
center developer himself and a fort
chairman of the Orange County Repu
can Party ("I'm about as right wing
you can get"). proudly displays at,
graphed pictures of Ronald Reagan on
wall. To drive with him through bulido:
and newly developed areas of Orat
County as he points out monotone
rows of houses and clogged intersectio
is to see the full fury aimed at develops
"They're greedy bastards." he fum
"Thugs in three-piece suits."
Rogers's transformation from grov
booster to basher follows a fairly comm
pattern. "I used to be part cf that grow
is -progress crowd," he explains. "But
changed when the government showed
couldn't plan for growth." Orange Cour
traffic already was dreadful in 1984 wh
county supervisors proposed a S5 billi
transportation improvement program
be financed by a sales tan increase t1
required voter approval. Rogers argu
that the major beneficiaries would be s
velopers, who would use the new roads
justify new development. "It was soci.
ism for the wealthy, an attempt by dev
opers to put the cost of their sins on t
public." says Rogers, who pulled togeth
environmentalists. open -space enthusias
antitax groups, and others to oppose t.
measure.
HEN THE SALES TAX Ic
by more than 2 to 1, Roge
figured that was a message
government officials to sic
the pace of development. "Instead, th.
kept right on just like they always did." 1
says. In 1987 he began circulating pet i t i o
for an elaborate Citizens' Sensible Grow
and Traffic Control Initiative, which else.
Bally required developers in Orange Cou,
ty's vast unincorporated areas to provit
roads and public safety facilities for the
projects. His measure was vigorously of
posed by builders and lost last June. B;
polls in Orange County show that two
thirds of the voters continue to be in favi
of slowing growth.
The combination of overburdened it
frastructure and increasingly sophisticate
antigrowth groups is forcing big chang�
in how developers do thing,,,, In the S,,
Fernando Valley to the north of dowt
town Lo; Angeles, Jack SNund faces
bizarre chore: if he is to obtain an exemt
Hotel BeijingToronto is
situated in the heart clfBeijing's
business and diplomatic area,
on Jianguo-Menwai Street;
20 minutes from Tfan'anmen
Square. andwithin walking
distancefrom the Fhmdship Store
We offer superb business and
pleasure amenities, that include
o business center, conference
rooms, and the finest Cantonese
and Continental cuisine.
Along with the unique and
hospitable personal service
that has come to char acterfie
Nikko Hotels International.
Where the heart Is always content
hotel beij ng-toronto
Aangtk Menwal street, Beijing Tet: 5002266
Telex: 210011/210012ILHCN Cable: 5650 MING
Man Wd by
T
nikko hotels internatonal
Foi reserval*ns. Calc yow travel agent.
Japan Air Unes or Mkko Hotels intetnaional.
Toll tree to US. and Canada
t-soli-NIKKO-us t64S5"71.
128 FORTUNE 1)ECEMIJER 5. 19$R
REAL ESTATE
tion from the city's limit on new Sewer
connections. So that his proposed office
project won't add to the strain on the sys-
tem. he will refit 8,000 toi!ets anywhere
in Los Angeles with plumbing that uses
three gallons per flush instead of the usual
five. To overcome the opposi-
tion cf homeowners near his
proposed buildings. he hired
Sharon Browning. a former
social worker with a blossom-
ing career in helping develop-
ers work with slow -growth
groups. Browning persuaded
Spound to go door to door
through the neighborhood
asking how he could change
his design to make it accept-
able. He's gained support but
still awaits approval by the
planning commission.
In Los Angeles, Friends of
Westwood brought a Iat,d-
mark suit that focused on a
proposed 26 -story office tow-
er, winning a ruling from the state court
of appeals that the city has to assess the
environmental impact of major projects
before issuing building permits. Though
the development company. Center Wast,
had won zoning approvals for the ofCoe,
its president. Kambiz Hekmat, negotiated
an agreement with Friends of Westwood
to cut the building's size by 18.5%. In ad-
dition, the city is requiring that he "plant,
water, and prune the trees I put on the
sidewalk," says Hekmat. That's nothing:
As part of settling a dispute over parking
at a new hotel near Beverly Hills, the
owners agreed to pay $250,000 to Friends
of Westwood and other slow -growth
groups, money that presumably can be
used to finance growth -control efforts'--
against
ffortsagainst other new projects.
Developers around Los Angeles rou-
tinely find themselves picking up the tab
for much of what municipalities once pro-
vided. Some have been forced
to donate land and build new ,-
firehouses, police stations,
even city halls, in order to
win municipal approval for
their plans. In parts of orange
County there is talk that de-
velopers may soon have to
pay the Salaries of policemen'
and firemen trade necessary
by their projects. Orange
County forced the Irvine Co.
to build a S45 million, six -lane
road to accommodate a
Planned 2,600 -tank communi-
ty, Normal planning would
call for two lanes for that size
"in the long
term these
antigrowth
areas be-
come elite
communities
without
economic
dynamism."
community.
'ihe cost of meeting such re-
quirements _ rs staggerili& For a. neiv busi-
ness center, the' Irvine_ Co.' is payirtg.225
million for road construction and improve-
ments.' Says once ''chairaian. ;Watson: "In
1963 `imptovemen s on tand`.cost about
515,000 a acre Now rt `costs $250,000 an
NTiGROM f movements may.
bei' emotiouslly.'.satisfy'* to the
participants, but. the ;eventual
outcome inn be a disaster, "No -
growth; -movements hurv. ft people who
wanted them,--.;argaes.prviessoc Kenneth
Rosen, ldmbmin . of the Center : for Real
IEstafe'and i3risari Ecatcuairs.at the Uni-
Earthmovers strip the hills bare to prepare for more building In southern Orange County,
'7'Sa" -r...
f,
f
Hotel BeijingToronto is
situated in the heart clfBeijing's
business and diplomatic area,
on Jianguo-Menwai Street;
20 minutes from Tfan'anmen
Square. andwithin walking
distancefrom the Fhmdship Store
We offer superb business and
pleasure amenities, that include
o business center, conference
rooms, and the finest Cantonese
and Continental cuisine.
Along with the unique and
hospitable personal service
that has come to char acterfie
Nikko Hotels International.
Where the heart Is always content
hotel beij ng-toronto
Aangtk Menwal street, Beijing Tet: 5002266
Telex: 210011/210012ILHCN Cable: 5650 MING
Man Wd by
T
nikko hotels internatonal
Foi reserval*ns. Calc yow travel agent.
Japan Air Unes or Mkko Hotels intetnaional.
Toll tree to US. and Canada
t-soli-NIKKO-us t64S5"71.
128 FORTUNE 1)ECEMIJER 5. 19$R
REAL ESTATE
tion from the city's limit on new Sewer
connections. So that his proposed office
project won't add to the strain on the sys-
tem. he will refit 8,000 toi!ets anywhere
in Los Angeles with plumbing that uses
three gallons per flush instead of the usual
five. To overcome the opposi-
tion cf homeowners near his
proposed buildings. he hired
Sharon Browning. a former
social worker with a blossom-
ing career in helping develop-
ers work with slow -growth
groups. Browning persuaded
Spound to go door to door
through the neighborhood
asking how he could change
his design to make it accept-
able. He's gained support but
still awaits approval by the
planning commission.
In Los Angeles, Friends of
Westwood brought a Iat,d-
mark suit that focused on a
proposed 26 -story office tow-
er, winning a ruling from the state court
of appeals that the city has to assess the
environmental impact of major projects
before issuing building permits. Though
the development company. Center Wast,
had won zoning approvals for the ofCoe,
its president. Kambiz Hekmat, negotiated
an agreement with Friends of Westwood
to cut the building's size by 18.5%. In ad-
dition, the city is requiring that he "plant,
water, and prune the trees I put on the
sidewalk," says Hekmat. That's nothing:
As part of settling a dispute over parking
at a new hotel near Beverly Hills, the
owners agreed to pay $250,000 to Friends
of Westwood and other slow -growth
groups, money that presumably can be
used to finance growth -control efforts'--
against
ffortsagainst other new projects.
Developers around Los Angeles rou-
tinely find themselves picking up the tab
for much of what municipalities once pro-
vided. Some have been forced
to donate land and build new ,-
firehouses, police stations,
even city halls, in order to
win municipal approval for
their plans. In parts of orange
County there is talk that de-
velopers may soon have to
pay the Salaries of policemen'
and firemen trade necessary
by their projects. Orange
County forced the Irvine Co.
to build a S45 million, six -lane
road to accommodate a
Planned 2,600 -tank communi-
ty, Normal planning would
call for two lanes for that size
"in the long
term these
antigrowth
areas be-
come elite
communities
without
economic
dynamism."
community.
'ihe cost of meeting such re-
quirements _ rs staggerili& For a. neiv busi-
ness center, the' Irvine_ Co.' is payirtg.225
million for road construction and improve-
ments.' Says once ''chairaian. ;Watson: "In
1963 `imptovemen s on tand`.cost about
515,000 a acre Now rt `costs $250,000 an
NTiGROM f movements may.
bei' emotiouslly.'.satisfy'* to the
participants, but. the ;eventual
outcome inn be a disaster, "No -
growth; -movements hurv. ft people who
wanted them,--.;argaes.prviessoc Kenneth
Rosen, ldmbmin . of the Center : for Real
IEstafe'and i3risari Ecatcuairs.at the Uni-
Earthmovers strip the hills bare to prepare for more building In southern Orange County,
'7'Sa" -r...
I don't know doctor, ever
since we've made this argrrisition,
I've been seeing doublelf
ci3`!
'.AWN.
of
•VICE ►�t?r'Sto;..
FN7
�,�C� 1'�fStrx-til= ` � � y . 6 •t d t
•' R z
If you find yourself with two phones, t m baskets, too
much inventoryry call EAL. We If turn your doubfie vision
Into tax deductible donations that generate scholarships
for needystudents, and supplies for worthy cofieges.
FAlucational Assistance Ltd Phone (312) 004)(HO. or
write P0. Box 3tt21.Glen Hlyn.It. 0(1133.
t3h FORTUNE DECEMBER S. {9M
REAL ESTATE
versity of- California .at; Berkeley._ ",Th.have a negative;eit`e .. '66"'tite'localrecon,
MY as firms relocate: and* real income go
down In -the long.: term these antigrow
areas becoiae elite communities wither
economic dy ai m`isM.
Trying to send newcomers elsewhe
probably sounds just fine to slov
growthers, but it won't solve Southern Co
ifornia's problems. Only one-third of tl
region's projected growth will come frog
migration. The rest will derive from a hig
birthrate. Even if Southern Californiat
put a wall around the place, the populatie
would grow by three million—equal to ar
other Orange County—in 22 years_.- Faili�y
to provide housing:;toacoommodate sun
N THEORY expensive or inftastruc
tune -short surroundings should driv
unwanted residents away. Troubk is
it doesn't happen that way, observe
Robert Paulson,_ managing director. 0
McKttiseyr 8t Co's:1.os Angeles cilce an, „
head of a chambe. or cxir►iaterce ,study rn �::
Brants, the people `who . the''tmos
services, tare the ones who remaut.'', Com
par its evep!,"lly poll their operatiorig ou .
IDU,
slow-growth regeott:.io trod .surtablr `.
romia s 1. tagy or:Browtrt- trot a '4 i
tlic LA L�-Anaetes rcaion reduced hotisint
growth by 15% and the rate of new com
mercW space by 25%, unemploymen
would double in the 1990s.
Unlike the environmental movement
which was arguably more altruistic, slo%
growth has a distinctly selfish. "sock it to the
newcomers" side to it. That means that in-
convenient changes in lifestyle that might
help accommodate even carefully planned
growth—car pooling, say. or recycling
waste—will be slow in corning. The same
spirit, but on a grander scale, will likely get
in the way ofcoordinated regional solutions
to planning prohlem. "Everyone wants is
see it happen." .,%- Ruth Galanter, the
slow -growth cano ,late elected to the Lo:
Angeles city crnri,:il last yrar, "but without
giving up their prrri,gatives."
a
up'
Public Report
Bulletin of the
INSTITUTE OF GOVERNMENTAL STUDIES r
EUGENE C. LEE. Director
HARRIET NATHAN. STANLEY SCOTT. Editors UNIVERSITY OF CALIFORNIA, BERKELEY
Vol. 21 October 1980 No. 5
GROWTH IN CALIFORNIA:
PROSPECTS AND CONSEQUENCES
l..arry J. Kimbell
Graduate Schooi of Management
University of California, Los Angeles
David Shulman
Graduate School of Administration
University of California. Riverside
Introduction
Several factors influence California's growth in employ-
ment, population 2nd housing supply. These three elements
are interrelated so that they act upon each other, and are
acted upon in turn. To learn more about these interactions,
we propose models and projections highlighting changes
already taking place, and discuss policy options that can
help encourage future change in desirable directions.
Between 1972 and 1979 the California economy ex-
perienced extremely rapid employment growth (3.7 percent
annually), while population growth was substantially slower
(15 percent).' Consequently, during that period the gross,
labor force participation rate (total population divided by
the cMlian labor force), went up from 42 to 48 percent.
We assume that the participation rate will continue to in-
crease in the next two decades, although more slowly.
But these increases cannot continue indefinitely, because
obviously the civilian labor force cannot exceed total
population. Further, basic demographic factors will prcb-
ably keep the gross labor force participation rate fr=
risirg much beyond 55 percent, since about 35 percent of
the population is either over 64 years or younger than 17.
When the gross participation rate is constant the Iabor
force and population must necessarily grow at identical
rates. Therefore, if the high employment growth trend of
1972-1979 were to continue into the future for perhaps
20 years, population growth would have to accelerate
rapidly. (One implication of this alternative is staggering:
a continuation of the 1972-1979employment growth rate
would yield a population of 52 million people in California
by the year 2000, contrasted with current estimates pro-
jecting about 30 million by the turn of the century.) On
the other hand, if the comparatively low population growth
of the 1970s were to continue for the next 20 years,
employment growth would have to slow down dramati-
cally. In short, something has to give.
Current policies are often at emss purposes; some try
to promote job growth, while others try to restrict popu•
lation growth. As long as employment goes up much more
rapidly than population, however, these policies do not
outright conflict. But when it becomes more difficult to
increase the number of workers in a given population, the
dilemmas wall become acute. Thus strong employment
growth under those conditions will lead to strong demo-
graphically based demand for more housing space.: But,
quality,' and it6.......1n thousing sup; y1. in combination,
these and :other factoxs (tg ; inflation) stimulate powedaal
forces raising,Mime prices, producing eztraordi:;ardy high
pricas in most n a2or urian areas afCaiifoinla:` fn such cir-
cumstances. can we develop policies that will provide for
adequate and affordable housing for many more Califor-
nia workers and residents, while still preserving environ-
mental quality? Our study examines the magnitudes of
pressures that seem likely to become much m>Q:Ie intense
between now and the turn of the century.
What follows is divided into several sections. First canes
a discussion of the recent history of employment and
population for the state, and all 17 of its standard metro-
politan statistical areas (SMSA's). Next is a brief discussion
of state and local legislation for environmental protection
that has worked to restrict the supply of housing. This is
followed by a section discussing the implications of high
employment growth and land -use restrictions with respect
The California Rilicy Seninar was established in 1977 as an experimental program in University -state
government cooperation on the study of longer-term policy problems. Chaired by UCPresident David Saxon.
the Seminar membership includes the Governor. President Pro Tempore of the Senate. and Speaker of the
FIAT LUX Assembly, plus other designated governmental and University appointees. Each year the Ser irwoommissions
a number of reswch projects. selected from among research proposals suggested by University faculty mem-
bers. Chosen projects are fended at 150,000each. for work extending overs two-year period. This issue of
the PubficAffairs Report, the first to feature research sponsored by the California Policy Seminar, summanz�s
CALIFORNIAPOLICY SEMINAR a longer technical report for a general sudicnce, Copies of the technical report are available at cost from the
Institute of Governmental Studies while supplies last.
Copyrigh) 1980 ID by the Rcgcnts of the University of California ISSN 00333417
I
20
15
Figure I
Job Growth in California, 1940-1979
(Annual Percent Change in Non -Agricultural Employment)
40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 16 78
Source: Sec end -note I.
Dashed Kne denotes 6 peroent growth to show high growth years.
to housing prices, using a model that links house prices and
employment growth. Next are 20 -year population and
employment projections for California and its 17 SMSA's,
followed by policy implications of the analysis, and a few
concluding comments.
Employment Gmwth and Population
Typically California has experienced its most rapid em-
ployment increases during wartime. The rapid increase in
the late 1970s, however, was not associated with a sharp
escalation in military expenditures. (Figure 1 charts changes
in nonagricultural employment for 1940-1979.) The fifth
fastest growth in employment occurred in 1978, a striking
occurrence because it came before the increase in military
spending associated with events in Iran and Afghanistan.
Job opportunities in California affect in -migration to
the state, and net in -migration is linked with the difference
between the California unemployment rate .and the US.
unemployment rate (see Figure 2). Thus in the early 1960s,
when there was no unemployment rate differential, ap-
proximately 300,000 people a year came to California,
and in the early 1970s when the California unemployment
rate exceeded the U.S. unemployment rate by 3 percent,
net in -migration approximated zero.
This empirical relationship supports a prediction that,
when California and national unemployment rates are the
same, approximately 300,000 people will again move to
California annually. We can also predict that for every
percentage point the California unemployment rate exceeds
the U.S. rate, 100,000 fewer people tend to come to Cali•
fomia each year. Thus it would take a Californiaunemploy-
ment rate three percentage points higher than the national
figure to eliminate inmigration.
But as Figure 2 shows, the relationship broke down in
1979. Instead of the predicted increase in inmigration,
there was an actual decline. Job availability may have
beom-e less of a factor in determining population growth,
being replaced by the rising prices of houses in California's
major urban areas relative to house prices in the nation,
as a key factor that caused the reduction.
If employment growth rates of the 1972-1979 period
persisted, and the dynamic described above did not break
down, California's population would reach 52 million by
the year 2000. 2 -is suggests over 12 million people in
Las Angeles County, and 7 million people in Orange
County—giving Orange County the same population as
Los Angeles County today—and Napa Valley's vineyards
would be shared vith nearly one million people (see Table
1).
Obviously, however, California population as large as
this estimate would exert tremendous pressure to increase
housing prices, and a rise would in turn slow down em•
ployment growth, in turn slowing population growth.
In A - 1-, population projections cannot be bawd on a
continuation of the rapid employment growth observed
in the 19705. The demand pressures that force up housing
prices are likely to reduce California's future employment
growth rates.
350,000
300,000
250,000
200,000
150,0150
100,000
,a
50,00C
0
Predicted vs. Actual Net in -Migration as a Function of the California Unemployment
Eate Minus the U.S. Unemployment Rate 1961-1979*
60 62 64 66 69 70 72 74 76 78 79
'The regression equation is: Net 1n -Migration - 313,982" 103.026 (California Unemployment Rate -US. Unemployment Rare).
Standard Errors in parentheses: (15.790) (10.140)
TM "pply ;.eshidioas Commission. In addition, in t970 the California Environ-
mental Quality Act mandated the preparation cf environ -
While employment was increasing rapidly in the 1970s, mental impact reports for substantial building projects.
a host of physical and legal restrictions on new housing Other more direct: attempts to recttkt:growth'uy._to
supply were developing. As the most readily available maintain {local; amruity valets, and ;lake sikk fortes -as
building sites are used up, the supply of new urban build- buV4ot zoning at lim tationson permits issued for housing
ing sites requires more extensive capital investments to units. The ,pixysilina traAd in`=zoning'actlons has hues' to
make them buildable, i.e., comprises land that is not flat. WsiM
One has only to compare the San Fernando and Santa Clara is lanc4 has, beefs 46i1itssffied `or "dowri , zoned. m many
valleys cf the 1940s and today to dramatize the consump- areas. More'.explidt slo!w•gioroi+th potIcteshave:ifeea "adopted
tion cf flnt land, much less of which is now available for in. such cities; as;.Petaittma;-:Davis, Thotuas d .Oaks and
construction sites. Riverside.. Thesut. iesttktions stave beedespecially harsh on:
In addition, two maaor.categorfesof lust restriciioi's oil multiple-unit,con
development,_have 'Siad siVdffcant--irripactsi environments Perhaps unlntentioiliHk, Proposition 13. appears to have
constraints, and=tsf 4' " ta: lirttit growtlt? Environmental accelerated thc,trend fOW "final zonings vrhich occurs:
constraints associated t�ffi identifiable costs include the when s-eommt+alty-_allows only_:those developmersts that
creation or strengthening of the Air Resources Board, pay their. own .way, a ,'when projected iddltioiiall tax
Water Resources Control Beard, Energy Resources Conser revenues produced iqual or.exeeed estirrtated public spend-
vation and Development Commission, and the Coastal ing necessary to service a development
3
Table 1
Implied Year 2000 Population if Employment Growth Persists at the 1972-1979 Rate
1979 Population 2000 Projected population
SMSA (in thousands) (in thousands) Percent increase
California 22,694 52,122 130
Anaheim -Santa An a -C a rd e n Grove
1,874
-7,494
300
Bakersfield
375
956
155
Fresno
485
1,180
143
Los Angeles -Long Beach
7,128
12,295
72
Modesto
251
651
159
Oxnard -Simi -Ventura
500
1,415
183
Riverside -San Bernardino -Ontario
1,445
3,435
138
Sacramento
980
2,447
150
Salinas -Seaside -Monterey
281
537
91
San Diego
1,800
5,562
209
San Francisco -Oakland
3,194
5559
74
San Jose
1,253
3,953
215
Santa Barbara -Santa Maria -Lompoc
295
695
136
Santa Cruz
176
507
188
Santa Rosa
280
1.053
276
Stockton
320
613
92
Vallejo-Fairfield•Napa
312
901
189
Source: See end -note 1.
Who Benefits? Who Loses?
Who has benefited and who has lost as a result of such
land -use controls? If participation in heated public debate
were a valid guide to who wins and loses, then surely the
local California land developers would appear to have lost.
This may not be the case, however, although the building
industry has publicly denounced both statewide and local
land -use controls. While builders clearly do not wish their
current Iand holdings to be restricted in usage, this does not
mean that they will not, given time and new opportunities,
benefit on balance f= land -use restrictions. Thus, for
example, the aggregate value of land could increase as a
result of supply restrictions.
California home builders experienced record profits
after many of the land -use restrictions were imposed:
(In 1980 the industry may have been depressed by severe
financial strains stemming from US, inflation, but this
situation is clearly not caused by local California land -use
restrictions.) Restrictions on land supply do not stop the
demand for housing, but instead increase the return to
entrepreneurs who can maneuver building permits through
the processes and bring new houses onto the market.
A very general, basic economic principle is at work. A
mobile factor of production cannot readily be deprived of
competitive returns. if restrictions on development in
California should take away the profits of builders, they
would tend to leave California. Indeed, by making building
permits available only to the most adroit. persistent, and
4
knowledgeable builders, governmental regulations may have
enhanced the profits of local entrepreneurs, at the expense
of the nationwide construction firms that can no longer
compete as readily as they did before more extensive land -
use restrictions were imposed. Tighter Iand-use restrictions
mean that nationwide firms have to invest more time and
money to learn how to process permits successfully, If thU
is true, negative consequences of land -use restrictions
probably do not fall on local California builders mnuch as
on others.
A similar argument holds for landowners. In any given
case of a proposed local restriction, the owners of the land
will almost certainly scream loudly in protest—for good
reason. Actions limiting the use of their individual parcels
of land will not alter California's general land housing
prices, while the individual landowner stands to lose in the
decision at hand. But no such presumption holds when
all landowners in California are "threatened" with more
extensive land -use restrictions. In fact they may collectively
benefit from land -use restrictions in general, in the form of
higher prevailing land prices.
As will be discussed below, since the early 1970s home
ownership in California has shown an extraordinary rate of
return, especially for those who enjoyed small down
payments and higher mortgages. Home prices increased
rapidly (see Table 7), whereas the mortgage liability for a
given homeowner remained fixed, Thus dwe who now
own homes do not appear to have suffered from these
restrictions.
Table 2
California and U.S. Home Price Increases, 1971-1979
(Percent change)
Year
Southern California
San Francisez) Bay Ares
Sacramento
US.
1971
3.8
5.2
3.3
7.8
1972
4.6
4.7
6.7
7.6
1973
- 6.3
6.8
7.1
85
1974
9-5
11.4
9.2
10.7
1975
15.4
13.5
11.2
10.1
1976
17.8
14.8
14.3
8.0
1977
26.7
23.7
15.4
12.3
1978
27.9
21.9
21.8
13.9
1979
20.8
15.9
21.6
14.1
Sources: Red Estate Research Councils of Southern and Northern California and National Association of Realtors.
Others who may have benefited include those who
place a relatively high value on preserving the environment,
improving air and water quality, or reducing crowding and
congestion.
Who 1csW. While no defmitive answer can be given, it
seems plausible that nonlandowners and nonhomeowners
have suffered losses, unless they place a higher value on the
environmental benefits they enjoy, than on the increased
housing costs they confront. Residents of other states who
would prefer to work and live in California, but who cannot
afford the high housing costs, may fall into this class.
Obviously, we cannot prove with certainty that land-
owners and builders have benefited from the land -use
restrictions they have opposed so vigorously. But it would
be a serious mistake to ignore this possibility.
HousingPrices and Economic Growth
Califomia's rapid employment growth in the 1970s,
and the emergence of supply restrictions on buildable sites,
combined to intensify the home price explosion of the late
1970s. California's price increases clearly ran ahead of the
rest of the United States. Table 2 represents home price
data for Southern California, the San Francisco Bay Area,
Sacramento and the US. (The prices reported for Cali-
fornia are estimates for an unchanging sample of houses.
This eliminates problems caused by changes in the mix of
houses sold. The US. prices are based on actual trans-
actions and are subject to changes in the types of houses
sold.)
As noted eadier, relative increases in home prices can
slow employment growth. Anecdotal and empirical evi-
dence-i.e„ the decline in in -migration in 1979 -supports
this hypothesis$- Corporate ";aad`governmental ''recruiters
tellus that.-the,prici. of,housirrg is the ngle.gniatest ob
stacic. to' fectuiting out of -state personnel `for California 6
High home prices :end to keep new people from moving to
California, and they tend to motivate current residents to
leave, since equity values in modest California houses will
buy much larger houses in other states.
A More Realistic Set of Projections
The hypothesis -that California's comparatively high
home prices act as a constraint on growth -leads to our
second set of projections. The model employed recognizes
the influence of population growth on home prices, as well
as that of home prices on employment growth. Thuswhen
employment growth tends to increase in -migration, higher
population in turn puts pressure on home prices, while
limit population growth. (IlDtal employment can still grow
if labor force participation rates increase.)
In the model, t -L relationship is calibrated so that
population growth stops completely when the home price/
income ratio for a given area reaches 12, i.e., the home
price is 12 times the per capita income. A home price/
income .ratio of 12 means that housing costs comprise
45 percent of average household income. (The specific
variables translating home prices and per capita income to
household budget share are shown in Table 3,)
Several different home price/income ratios were ana-
lyzed before 12 was chosen as the most plausible value,
bearing in mind related population projections. A value as
high z$ 20 would lead to a population projection for
Table 3
Salient Points in Considering Impact of a 1112 x Per Capita Income" Constraint
for Housing Costs in California
• Per capita annual income (1979)
$9,992
• Average number of persons in household
2.64
• Average annual household income (59,992 x 2.64)
$26.378
• House price at 12 times per capita income (59,992 x 12)
S 119,900
• Annual payments on such a house equivalent to
S 11:598
Payments as percent of average annual household income
($11,898 _ $26,378)
45%
• Payment level as acceptable percent of average annual
household income
30%
Average household annual income required for the annual payments
(S 11,898) to amount to 30 percent of income
539,660
• Based on: 30 -year, 10 percent mortgage of $95,000; property tax payments of 12 percent of market value; and insurance of .3 percent
of market value.
Note that the 10 percent mortgage rate reflects a long-nmestimate of mortgage interest rates rather than current rates.
California of 35.7 million persons in the year 2000, and the
distribution of that population across SWs seemed
implausibly high in some areas. The chosen value of 12
leads to a population projection of 303 million, which is
more consistent with other current population projections.
Moreover home prices as high as 20 times average house-
hold annual income would mean that far more than 45
percent of average household annual income would be
spent on housing, and such a high budget share also sears;
implausible. Further, employment growth in the major
coastal urban areas already appears to be somewhat con-
strained by home prices, even though the home price/
income ratios are now closer to 10. (In a few years we
presumably will have more experience with extraordinarily
high home price/income ratios, and this empirical back-
ground may permit more rigorous econometric estimates
of the appropriate value.)
In areas where the ratio of home prices to per capita
income is as low as 5 or 7, and where building site avali-
ability peanits substantial population increases without
inordinate pressures on home prices, employment can
continue to grow at roughly the same rates as in recent
years. The Riverside -San Bernardino SMSA is an example.
In 1972 house prices were 5.7 times per capita income,
and by 1979 the home price/income ratio was still only
7.4. Not surprisingly, from 1972 to 1979 population
increased by 22.6 percent and payroll employment in-
creased by 36.4 percent.
On the other hand, in areas where home prices are as
high as 10 times per capita anaual income, and where
home prices are also quite sensitive to slight increases i -r
population (e.g., Loo Angeles), employment growth is likely
to slow down considerably as it becomes more difficult to
achieve higher labor force participation rates. In Los
Angeles the home price/income ratio was 6.8 in 1972, and
had reached 10.7 by 1979. During that time, population
increased by only 2.1 percent, whereas payroll employment,
including commuters, grew by 23.8 percent.
In our model, each SMSA is treated independently of
the other urban areas in California. Furthermore, as noted,
home prices in some areas appear to be much more sen-
sitive to population pressures than others. Thus home
prices in Los Angeles appear significantly more sensitive
to demographic pressures than those in Ventura County or
the Riverside -San Bernardino SMSA, in part, no doubt,
because Los Angeles has much less buildable open space
near its urban core than the other two St's. Because
of differences in sensitivity, using the same home price/
income ratio does r&- mean that all SMSA's will grow at
the same rates between now and the year 2000. Table 4
shows the projections using the home price/income ratio
of 12.
(It is important to note that relative home prices are the
only constraint on population and employment explicitly
provided in the modal. Other factors—e.g., the availability
of water and energy, or an increase in air pollution—
presumably could act as ouxtraints long befione the house
price constraint took effect. But the possible impacts of
those other constraints is the subject of another research
effort, and is not examined here.)
Projections Under Home Rice Restraints
We:project: the totalpopulation of ..California to be
30.3. million ; persons - by the'"year, 2000. using the home
price constraint. (Table -4 shows the population estimates
using that constraint; contrasted with Table I, which shows
Population; projections without any tioosirtg cost con-
straint) if employment is'constrairted ;by, housing uosts,
there is likely to be a slowdown in employment growth in
the urbanized ;coastal'areas of California. California's new
growth centers are -therefore likely to , be inland (e g.,
Fresno, Bakersfield) rather titan on the coast. Table S
presents the recent rates of employment growth for all 17
of California's SMSA's, as well as estimates of employment
A
Table 4
Estimated Year 2000 Population if Employment Growth is Constrained by Housing Costs
Sources: See end -note 1.
I
1979 Population
2000 Estimated population
SMSA
(in thousands)
(in thousands)
Percent change
California
22,694
30,292
33
Anaheim -Santa Ana -Garden Grove
1,874
2,986
59
Bakersfietd
375
733
95
Fresno
485
1,061
119
Los Angeles -Long Beach
7,12b
7,266
2
Modesto
251
538
114
Oxnard -Simi Valley -Ventura
500
679
36
Riverside -San Bernardino -Ontario
1,445
2,875
99
Sacramento
980
2,047
109
Salinas -Seaside -Monterey
281
354
26
San Diego
1,800
2,093
16
San Francisco -Oakland
3,194
3,325
4
San Jose
1,253
2,180
74
Santa Barbara -Santa Maria -Lompoc
295
396
34
Santa Cruz
176
219
24
Santa Rosa
280
427
53
Stockton
320
568
78
Vallejo -Fairfield -Napa
3I2
460
47
Sources: See end -note 1.
Table 5
Percentages of Employment Growth 1972-1979 and 1995-2000 Estimated
1972-1979
1995-2000Estimated
SMSA
Growth rate
growth rate
California
3.7
L6
Anaheim-SantaAna-Cyarden Grove
7.8
3.2
Bakersfield
41
4.6
Fresno
4.5
4.9
Los Angeles -Long Beach
22
OS
Modesto
4.6
4.7
Oxnard -Simi Valley -Ventura
4.6
31
Riverside -San Bernardino -Ontario
39
41
Sacramento
43
4.7
Salinas-Seaside-Montercy
33
2.5
San Diego
4.7
L7
San Francisco -Oakland
3.0
0.4
San Jose
5.1
3,2
Santa Barbara -Santa Maria -Lompoc
4.1
2.6
Santa Cruz
5.3
1.6
Santa Rosa
5.6
19
Stockton
3.0
3.7
Vallejo -Fairfield -Napa
4.2
4.5
Sources: See end -note 1.
I
growth for the period 1995-2000. The inland areas showing
the greatest employment growth in the 1995.2000 period
are also those where easily developed land, i.e., relatively
flat land. is available and housing prices are lower. The areas
of high housing cost are, of course, the slowest growing.
i,lajor implications
Major implications can be drawn from this analysis of
the prospects and ccnsequences of future growth in Cali-
fornia. First, almost inevitably Califomia's recent rapid
employment growth will slow significantly. also slowing
economic growth. This development is of considerable
significance to public and private planners alike. Second. if
the state attempts to achieve employment growth that is
greater than our constrained projections, state and local
governments will have to encourage the production of
housing units by relaxing restrictions. This would mean un-
doing many of the zoning restrictions enacted in the 1970s
and increasing the zoning capacity of neighborhoods
already built up. Such a change would represent a major
policy reversal, and go to the heart of the issue of who has
the right to say "no" to new housing development. It
would in all likelihood mean higher density housing—e.g.,
townhouses, condominiums, apartments, and zero -lot line
houses—closer to employment centers. It would also mean
a reduction in local autonomy over Iand-use decisions.
Although the model suggests that California's inland
areas wM grow faster than other areas during the next two
decades, it is of course uncertain whether the inland areas
will in fact accommodate growth by supplying and financ-
ing the needed infrastructure of facilities and services
necessary to urbanization. In addition to imposing infra-
structure costs, such growth would also conflict Po�th the
goal of preserving agricultural land. Failure to supply the
jnfrastntsture, or to achieve some reconciliation between
growth and agricultural land protection policies, will tend
to slow the growth of inland areas.
The model also raises a host of other issues, including
the linkage between rent control and growth controls. The
emergence of supply restrictions helped to increase home
prices. That condition plus the in -migration generated by a
booming economy led to higher rents, and ui.imately to
political pressure for rent control. To increase employment
further without expanding the housing supply would exac-
erbate the problem. In -migration has already helped price
existing residents out of their apartments. Rent control can
In fact be viewed as a form of growth control, because it
prevents new residents from bidding housing away from
existing residents.
ALS» related to rent control is the overall impact of high
relative house prices on the nonhomeowning population.
The model implies that population increases would push
relative home prices higher, thus noldrrg it even more
difficult for nonhomeowners to enter the housing market.
Consequently unless there is either a significant slowdown
in employment gxowffi, or a substantial increase in housing
supply, the hone ownership opportunities are likely to be
foreclosed to a large part of the population for the foresee-
able future. This could exacerbate the existutg tension be-
tween renters and real estate owners.
Another development involves government finance
Onc of the conditions favoring the creation of our huge
state surplus was California's ability to increase employ
ment faster than population. While this continued. revenues
could increase faster than costs, revenues being more a
function of employment, and costs more a function of
population. But if population growth catches up to employ-
ment growth, state and local government budgets could
be severely affected by costs that rise faster than revenues.
Concluding Comment
California is undergoing major changes. Familiar past
trends are unlikely to continue, and a simple extrapolation
of recent employment and population trends does not
provide a reasonable or plausible guide to the future.
Although land -use restrictions have probably limited the
amount of congestion and crowding in California, other
considerations are now looming in importance. Thus the
trade-off between faster employment growth and a better
environment will intensify once it appears unWkely that
labor force participation rates can grow substantially.
The fault lines of the conflict can be identified, even
though it is impossible to predict where and when the
political quakes will occur. We expect political tensions to
grow over the issues of rent control, restrictive zoning,
agricultural land protection, the funding of public infra-
structure and services, higher densities in existing urban
neighborhoods, the overburdening of transportation facili-
ties, and the allocation of urban space among different
socioeconomic groups. The conclusions presented aie
intended to assist in the policy evaluation of these issues.
We do not here attempt value judgments on how these
issues ought to be resolved. Voters and their elected repre-
sentatives will be deciding these matters. In the process,
coalitions that have supported increasingly restrictive land•
use policies are likely to fragment, and conflict among
voting groups is likely to intensify in the coming decades.
In essence, until now California has been able to have
its cake and eat it, too. We have restricted land use signifi-
cantly, while also enjoying very rapid employmrstt growth.
This combination is almost certain to find. Accordingly in
the near future we must either actively fadlitate rapid
expansion of the housing supply, cr accept a dramatically
slowed rate of employment growth.
NOTES
Larry J. Kimbell is Director of Economic Models, UCLA Busi.
ness Forecasting Project; and Associate Professor of Business Eco.
nomics, Graduate School of Management, University of California,
Lor A ngelcs,
David Shulman is Assistant Professor of Administration and
Economics. Graduate School of Administration, Univcrssty of
California, Riverside.
For the find report on which thin paper is based, the writers
have provided the following acknowledgment: We arc grateful for
the assistance of Peter Jaquette, Research Associate at the UCLA
Business Forecasting Project. for his assistance in developing the
economic models discussed herein and for his important insights in
the economic issues involved. We are grateful to Martin ticlmke, Art
Packenham, lames Patterson, Isabel Hambright and John Cummins
for their helpful comments on an cailiet draft.'rhe study benefited
from the substantive and editorial suggestions of Ms. Ruth Galanter.
I. All employment and population data were retri-ed (non thu
Security Pacific National Bank computerized data bank. The origi-
nal source documents are from the Population Research Unit ofthe
Califcrnia Department of Finance and the California Employment
Development Department.
2. See, for example. Fred E. Case, "Housing Prices and Environ-
mental Impact Reports (EIR)," California Heal F.stare !n+dicators,
Graduate School of Management, UCLA (Spring 1980). pp. 2 and 4;
and Robert Kneisel, "The Impact of the California Coastal Zone
Conservation Commission on the Local liousing Market: A Study of
the South Coaw Regional Commission." unpublished Ph,D, dis-
sertation. University of California, Riverside (December 1979).
Both studies reported higher house prices as a result of regulation.
3. See. for example, Jeffrey 1. Chapman and John J. Kiran,
"Land U9eConsequcnas of Proposition 13," pp. 95-I24, and David
1980
Shulman, "Proposition 13 and the Spatial Allocation of Economic
Activities." pp. 125-137, in Southern California lay.• Review 53: i
(November 1979).
4. See. for example. Shap -ell Industries. Annual Report. 1978.
Shapeil is California's largest homebuilder with 3 sales volume of
5243 million in 1978 when it delivered 2.026 houses. Its operating
profit increased from S21.7 million in 1976 to 562.2 million in
1978. During thai same period operating income as a percentage of
saics increased from 16.5 percent to 25.6 percent.
5. See, for example, Scott LcFaver, "µ`ill Success Spoil Silicon
Valley?" inPlannrng 46 (4). 22-25 (April 1980).
6. See, for example, John dlenvin. "When Cities Cct Too Pop-
ular," iibz*w 126 (6): 72-76 (September 15, 1980); this article
discusses the adverse Impact of high housing costs on the Cali-
fornia economy.
RECENT INSTITUTE PUBLICATIONS
Butler. Lewis H., Harold S. Luft, Hekne L. Lipton and
Joan B. Trauner
Medical Life on the Western Frontier: The Competitive Impact
of Prepaid Medical Care Plans in California (California Policy
Seminar Monograph Number 6). 19pp 53.50
Leary, Paul M.
The Northern Marianas Covenant and American Territorial
Relations. Research Report 80-1 55pp 53.75
Mitchell. Douglas E and Laurence Iannacoone
The impact of California's Legislative Policy on Public School
Performance (California Policy Seminar Monograph Number 5).
24pp 53.75
Roenier. Ruth and William Shonick
Private Management of California County Hospitals (California
Policy Seminar Monograph Number 4). 27pp f3.75
Schutt:, Howard G., Lloyd D. Musoif and Lawrence Shepard
Regulating Occupations in California: The Role of Public Mem-
bers on State Boards (California Policy Seminar Monograph
Number?). 22pp $3.50
1979
Balderston, Frederick E, I, Michael Heyman and Wallace F. Smith
Proposition 13, Property Transfers. and the Real Estate Markets
(prepared for the Commission on Government Reform). Re-
searchReport 79.1 5 6 p p + Appendices $3.00
Bowen, Frank M. and Eugene C. Lee
Limiting State Spending: The Legislature or the Electorate
(prepared for the Commission on Government Reform). Rc-
snarch Report 79-4 100pp+Appendices f4.50
Dealt, Terry J. and Ronald J. Heckart, eompilert
Proposition 13 In the 1978 California Primary; A Pre -Election
Bibliography. Omslonal Bibliographies Number 1. 88pp 56.00
Fletcher,Thomas, Dennis Hermanson, JohnTayior, Shirley lienueil
and Dean LineWrger
Alioealing the Cne Percent Local Property Tax In California: An
Analytis (prepartd for the Commission on Government Reform).
Research Report 79.7 35pp + Appendices 33.25
hfcWatters, Ann Robertson
Financing Capital Formation for Local Governments (prepared
for tha Commission on Govemment Reform). Research Report
79.3 51pp $3.00
Scott, Stanley
Policks for Seismic Safety: Elements of a State Governmental
Program. 94pp 175.75
1978
Ames, Bruce N.
Environmental Chemicals Causing Cancer and Genetic Birth
Defects: Developing a Strategy to Minimize Human Exposure
(California Policy Seminar Monograph Number 2). 28pp 53.50
Bradshaw, Ted K. and Edward J. filakely
Policy implications of California's Changing Life Styles (Cali
fornia Policy Seminar Monograph Number 3). 30pp 53.50
Cooper. Michael D.
California's Demand for Librarians: Projecting Future Require-
ments. 128pn 56.50
Eckbo, Garrett
Public Landscape: Six Essays on Government and Environmental
Design in the San Francisco Bay Ares. I35pp 57.75
Cater. Paul W., Ronald B. Roble, John T. Knox and
Norman Y. Mineta
Four Persistent Issues: Essays on California's Land Ownership
Concentration. 1Vater Deficit;, Sub -State Regionalism. and
Congressional Leadership. 79pp 55,75
Mullins, Phil, Thomas O. Leatherwood and Arthur Lipow, eds.
Political Reform in California: Evaluation and Perspective,
Research Report 78.3 160pp 56.50
Nathan, Harrict and Stanley Scott, eds., with I 3local authors
]Experiment and Change in Berkeley: Essays on City Politics,
1950-1975. 501 pp $10.75
Phillips. Kenneth F. and Michael B. Teitz
liuusing Conservation in Older Urban Areas: A Mortgage In-
suranm Approach. Research Report 78-2 39pp 53.50
Pyk, David H.
Changes in the Financial Scrvices Industry in California
(California Policy Seminar Monograph Number I). 17pp 53.00
Stebbins, Kobcrt C.. Theodore J. Psp,enfuss and Florence D.
Amamoto
Teaching and Research in the California Desert. Res arch
Report 78-1 26pp f3.00
Weeks, Kent M.
Ombudsmen Around the World: A Comparative Chart. 2d. ad.
163pp 57.50
Monographs, Bibliographies, Research Reports and a full list of
Institute publications are available from the Institute of Govern-
mental Studies. 109 Moses liall, University of California, Berkeley,
California 94720. Checks should be made payab;e to the Regents of
the University of California. Prepay all orders under f30.California
residents add 6% sales tax; residents cf Alameda. Contra Costa and
San Francisco counties add 6'h% sales tax. Prices subject to change.
Note to Readers
While reading recent issues of the Public Affairs Report, have
you thought of questions, suggestions, criticisms or comments that
you might like to consider sending in to the editors? Do you have
any observations about the choice of topics. or their treatment in
the pages of the Report' 1}o you have any advice or suggestions
regarding future issues?
Letters from readers and requests for copier arrive regularly, but
by including this note, we try to keep open a "reader' window"
that will give us a better sample of what subscribers think about
the Public Affairs Report, and what directions it might take.
Your comments may also provide substantive observations that
cxauki be acknowledged or excr:rpied in future issues.
-The Editort
c
® Institute of University of
bLurl
Business and California,
Economic Research Berkeley
CENTER FOR REAL ESTATE
AND URBAN ECONOMICS
WORKING PAPER SERIES
WORKING PAPER No. 94-173
HODS ING ALLOCAT ION AND METROPOL I TAN CEVELWMENT
BY
JOHN M. QU I GLEY
T1ao� pepen� are preNm&rary ..
*k1 ; tlNa pacpos0 iS { , .
`to: sprmilats discussion and
camnerC Therefore. they
-we not io be rxed or quoted
in any pubkotion without
the express permission of
the author.
GRADUATE SCHOOL OF BUSINESS ADMINISTRATION
Reduced local government support in the wake of
Proposition 13 (limiting property tax rates in California) and
the federal cutbacks in grants for local services have made it
difficult to finance expansion of the infrastructure and
public services necessary for housing development. Because
communities can not increase property taxes enough to pay for
local services needed by new residents (schools, sewers,
etc.), fees are imposed on new housing development, increasing
v
housing prices. Because }locate; revenues are•~ roughly
_proportional .to housing values and''the 'dezriands`"for' services -
are .. >roughly-proportiorta' 'to the number . - of -l ausaii ii local
governments have strong incentives `to-adopt zoning regulations
Th
requiring ..targe amounts °"of hoersing cans2mption. ese
=regi Iatfons, = sa=called° scal � - zoning; n are intended ` to
re. ;new`residents 'to'-=consume (and''to =pay"p _j taxes
yan).":mare reap estate than-they 3d`otiierwise choose.
As a result, much of the new development excludes housing
that could serve lower income persons. New rental
construction approved at the local level tends to be small
units that cater to older couples (who use relatively few
local services); new housing for young families (who use many
public services, particularly schools) is less widely
available. The problems created by Proposition 13 are
unresolved; in consequence, local governments continue to
resist rapid development of housing.
20
Institute of University of
Business and California,
Economic Research Berkeley
CENTER FOR REAL ESTATE
AND URBAN ECONOMICS
WORKING PAPER SERIES
WORKING PAPER NO. 90--173
HOUSING ALLOCATION AND METROPOLITAN DEVELOPMENT
BY
JOHN M. til l GLEY
Ttiesa ps�trs aetp prsuminary : ;„.
4t±rtaetwe a+u purpose is
Wstittaipl�s diudisabn auxt '' ..
-COmme t,1herefore. they
'-are-reed be cited or quoted
in any Publication without
the express permission of
the Sutter.
GRADUATE SCHOOL OF BUSINESS ADMINISTRATION
locations. The most frequently mentioned reason for site
selection was the proximity to th he residences of key employees
and managers. Two fifths of firms mentioned this factor, and
another 15 percent were concerned with proximity to the
workforce. About 20 percent of larger firms (with more than
fifty employees) were concerned with proximity to the homes of
key employees, while 40 percent were concerned with the
location of the workforce, Transportation access and the cost
of space concerned one-fourth of all firms, and were of
somewhat greater importance to larger fi3=.
Further, interviews with tenants in newly constructed
space indicate that firms seek greater labor force
availability, either through reduced commutes or by capturing
secondary earners, and they seek a more highly educated local
work force. Significantly, interviews with many of the
largest developers and builders of the facilities suggest that
they had chosen these building sites for similar reasons in
anticipation of the demand.
b. Competition Between the Bay Area and Other Regions:
Housing Affordability
The San Francisco Bay Area is well Down for its natural
resources and mild weather, its relatively low levels of
pollution and congestion, and its striking architecture,
making it one of the most desirable locations in the U.S. in
which to work and live. Per capita income in the region is
18
sixty percent above the national average, and it has attracted
the highest average educational level of any US local labor
market.
Not surprisingly, housing prices are high. By August
1988, the median price of owner occupied housing in the region
was $216,000, and prices had increased by 71 percent in six
years. 13 In six years median housing prices increased from
1.8 times the national median to almost 2.5 times the median
for the US
as a whole.
At current prices,
only about one
household in
eight already
living in the area
could afford to
purchase the
median priced
house, given widely
accepted rules
of thumb. In large part, of course, high housing prices are
to be expected, given the desirability of the region, There
are, however, strong indications that the regional price level.
for shelter has begun to act as a deterrent in the competition
for new business activity. 14
to`increase°housing grf", above competitive levels: here the
answer'is almost-certainly.yes:
13 These and other background statistics are discussed in
Hird, et al, op cit, and Kenneth T. Rosen and Susan Jordan,
"The Ban Francisco Real Estate Market," Berkeley, CA:
Center for Real Estate and Urban Economics, 1988.
14 For a recent example from the popular press, see Fortune
Magazine, Oct 2, 1989.
is
Reduced local government support in the wake of
Proposition 13 (limiting property tax rates in California) and
the federal cutbacks in grants for local services have made it
difficult to finance expansion of the infrastructure and
public services necessary for housing development. Because
communities can not increase property taxes enough to pay for
local services needed by new residents (schools, sewers,
etc.),_ fees are imposed on new housing development, increasing
housing prices. Because local revenues are'=rot�ghly
s -r-. �--• .� ra. -. a:_2,Y•; a --.a-"' __--mss. ;_ ,
proportional to hot7slnq values and the-- -demands - for services -
are. -_roughly propsrtioial to the number of households, local =
--governn►ents have strong`incentives to'adopt zoning regulations
requi=uiq large wamoun'ts 'of 'Housing uconsuznption. These
aegulations, so-called _ f isca3` zoning, " are inten ` a�
requte.enew `residents=_to consume {and tol- --payproperty taxes
estate than; they would `o choose. ".-
As a result, much of the new development excludes housing
that could serve lower income persons. New rental
construction approved at the local level tends to be small
units that cater to older couples (who use relatively few
local services); new housing for young families (who use many
public services, particularly schools) is less widely
available. The problems created by Proposition 13 are
unresolved; in consequence, local governments continue to
resist rapid development of housing.
J
20
In addition to these direct policy driven causes of high
0 Monopoly power can be exercised by developers who benefit
from restrictive land use regulation, which limits the amount
of land available for development and makes controlling local
land markets easier. Complex: administrative procedures,
lengthy application -.periods,, and' other measures Ghat typify
Bay Area hocal development polcies.,`can-:.induce .monopolistic
„� control of Iocal land markets. Credible studies of
development -have'. %und.that the `excess profits were largely
attriliutable td -' housing supply and the lack of
competition 16 In other suburban areas, the lack of
developable land and high development fees have given dominant
control of the housing market to a few large developers.
15 See David Dowall, The Suburban Squeeze, Berkeley CA:
University of California Press, 1984.
16 See David Dowell, op Cit.
21
These indirect effects may exert a powerful influence
over local land use and development- Any policies hoping to
improve the present housing conditions in the Bay Area must
recognize these important, though subtle consequences of such
policies. Environmentalism and local land regulations
preventing rapid growth are supported by many Bay Area
residents, especially since limitations on property tax rates
have made it more difficult for existing residents to "profit"
from additional housing development- Attempts to change this
pattern are not likely to be initiated by local governments or
their constituents.
The ultimate source of the problem is the balkanized
pattern of bUilding permit and land use regulation.
22
THE IMPACT OF SUBURBAN GROWTH RESTRICTIONS ON
U.S. HOUSING PRICE INFLATION, 1975-1978'
David Segal and Philip Srinivasan
Oxford University and Harvard University
The paper estimates a simultaneous equations model of housing price inflation
1975-1978 for a cross-section of51 metropolitan areas. A two-stage least squares pro-
cedure is used to estimate the demand-side and supply-side determinants of price
changes. One --of the major sources of inflation is shown to be a variable reporting
suburban grow;#opstepie:fnction.:of: potentiUly dey eloped land just beyond
the inatgln=of tiriiait=settietnent: that;is.s tiestered from growth, Nearly two-thirds
of. tht SMSAs'.in:atr sample tiad growthrestui tions 'wthan average of 1.2% of avail-
able,suburbanjpisd:.sef:off timits:to growth- Som a cities barred growth from as much
as 30 to 40% of the nearby surrounding land. Su ch controls were found to have con-
tributed significantly..to iinftation., . The-growwth Controlled cities experienced an infla-
tion` rate that wai �boiit 17"1�hiahef:than those that did notrestrict, ceteris paribus'=
125% instead of 10.8% annually, 1975-1978.
As the purchase price of new and existing homes began to dip in early 1980, hous-
ing prices nationwide had just completed a period of their most dramatic increase since
the start of record keeping. During the period 1973-1979, home prices increased at an
average annual rate just short of 10'/6; toward the end of the period, home inflation
accelerated, reaching 13.41/6 in the last year.
Such figures mask an enol`nious amount of geographic variation. In Denver and
Phoenix, prices rose at an annual rate of 20 to 25%between 1977 and the spring of
1978; price increases were only slightly tower in Chicago, Dallas, and Houston. Some
Phoenix builders reported selling out homes even before streets and curbs had been
laid in. Boom conditions in some California cities had no parallel (Grebier and Mittel-
bach, 1979). At the other extreme, home price increases in Jacksonville and Rich-
mond averaged 5.3° annually, and in Milwaukee a mere 4L20/6.
A literature is emerging on ?he forces behind the housing price inflation of the mid -
to late -1970s, on why price increases in this sector have tended to exceed increases in
the general price level by 2 percentage points or more in all but two of the years since
1974. Frieden, Solomon and Birch (1977), as well as Hendershott and Hu (1979),
have stressed the role of inflationary expectations in inducing a higher demand for
housing than would otherwise have been the case. Schwab (1979) beiieved capital
market imperfections such as the institutional prevalence of the level -payment mort-
gage forced many households to choose differently among three goods, present con-
sumption, future consumption, and housing, in favor of the last.
Remarkably little has appeared on the causes of variation in housing inflation rates
across cities. We address this question by means of a straightforward comparative
statics model, reporting the partial effects of demand and supply forces on housing
price outcomes at two points in time, The model is tested using observations on 51
metropolitan areas for 1975.1978.
14
Urban Geography, 1985, 6. 1, pp, 1426.
Copyright U 1985 by V H. Winston & Sons, Inc All riahts reservsvi
SUBURBAN GROWTH AND HOUSING INFLATION 15
We find that dgmand-side factors—variations in the rates of income, population and
mortgage rate changes within our sample—had a significant influence in housing price
increases, No less important, however, is the role played by suburban growth restrict
tions. They explain as much as 40% of the variation in urban housing price inflation
unexplained by demand-side factors. As a class, growth -restricted cities entered the
mid-1970s with a hatf percentage point higher inflation rate tha.. unrestricted cities,
ceteris paribus. Moreover, every 10% of a city's potential suburban land that was set
off-limits to growth during 1975-1978 contributed an additional 1.0 percentage point
annually to its inflation mte in home prices. Taken together, these considerations
meant that the average growth -restricted city, with more than 12% of its suburban
land off-limits to growth, experienced an inflation rate in housing prices nearly 2 per-
centage points above an average unrestricted city.
The impact of growth restrictions, however, was not linear: Larger fractions of sub-
urban land withdrawn from growth caused increasingly higher inflation rates. Cities
reporting more than 2(?% of outlying land growth restricted added more than 6% to
their annual housing price inflation rates, ceteris paribus.
In the balance of the paper, we describe our underlying model, the data, and the
empirical results.
THE MODEL
An appropriate means for analyzing the effects on housing prices of unanticipated
exogenous demand shocks is the stock -adjustment model. Once we know the nature
of the adjustment process and the magnitude of the adjustment parameter, it is possi-
ble to identify short -run equilibrium prices for all points in time after a shock. If, on
the other hand, there are no demand shifts that are not anticipated, then a statics
model is quite appropriate for examining equilibria at different points in time.
We do allow for the possibility of unanticipated demand shifts within the context
of a comparative statics model by assuming that exogenous changes in demand cause
equilibrium prices to move smoothly, i,e., we assume that the stream of exogenous
demand increases is such as to cause equilibrium prices to grow smoothly. Mathemati-
cally this requires that when we solve lagged -adjustment equations for short -run equ i-
librium housing prices at t and t + 1, the actual values are ahead of the target values by
the same percentage in both time periods.
The above assumptions allow us to present a dynamics process as a comparative
statics result. This is illustrated in Figure 1, in log -log, price -quantity space. Because
slopes of demand and supply functions in such a diagram are elasticities, a demand
shift between times t and t + 1 that leaves demand elasticity unchanged will cause
D t+ 3 to be parallel to D,.
There are two issues of particular interest in this paper. One is whether the supply
function for growth -restricted cities, S or S', has the same y-oxls intercept as that for
cities that do not restrict suburban growth, S. A second is whether the supply elastici-
ties of housing are the same for both kinds of cities. This is a question of whether the
dopes of S or S' and S are the same. Were this the case, cities with growth restrictions
would have the same inflation rate as those without. This is because c is the same
vertical distance above d as is b above a.'
On the other hand, if supply elasticities differ between th � cases of growth restrict
iV
W
U
Ir
Q_
0
O
J
SEGAL AND SRINIVASAN
In Pit+1[..............
N
In Pt+1
In Pt
S�
LOG QUANTITY
—S
Dt
S
Dt+1
Fig. 1. Housing market inflation: A comparison of cities with and without growth restrictions.
tions versus no -growth restrictions (S' versus S), the price inflation rates will alsodiffer.
The mechanism causing this to happen is an interaction effect between the housing
supply function and a variable representing growth restrictions: The fact of interaction
causes the slopes of the supply function (the elasticity in Fig. 1) to be different be-
tween growth -restricted and -unrestricted cities. We shall be interested to test whether
and how growth restrictions affect housing price inflation, i.e., whether the interaction
effect is statistically important; for the present, we suggest as a working hypothesis
that such effects do matter. Specifically we would expect restrictions to increase the
rate of inflation, ceteris paribus—that they render (c' - d') > (b - a). Also we shall be
interested to see whether the two supply functions cross the y-axis at the same point
On a priori grounds we might expect that the supply curve for growth -restricted cities
would have a higher intercept, reflecting a higher initial price level for these cities.
Before proceeding with a discussion of the functional form of equations to be esti
mated, some comments are in order regarding a model structure that might justify the
above hypotheses. Consider two cities of identical size and spatial structure except
that one has growth restrictions while the other does not. Such restrictions might take
the form of environmental ordinances withdrawing from development a portion of the
annulus of open space just beyond currently outlying settlements. This is shown in
the schematic diagram of Figure 2 where the land into which suburban settlement
might ordinarily expand is shown as the outer ring or annulus, and the area that is
sequestered from growth is represented by the shaded portion.
The impact of an increased demand for housing on existing patterns of density and
SUBURBAN GROWTH AND HOUSING INFLATION 17
' Existing
Settlement
Fringe i
Annulus cf Potential
Housing Growth
Fig. 2 Area of potential suburban land restricted from growth.
prices (and hence on mead density or price) is well known (see Muth, 1969; Mills,
1972). Growth restrictions of the sort described, by limiting yrowth at the margin of
settlement, thus upset the trade-off between travel time and for size. Households will
pay higher prices for interior locations to avoid the extra commuting time of living b e
yond the growth -restricted area Accordingly, lot prices at all interior locations, as
well as at locations in the unrestricted portion of the annulus and beyond what would
be the new margin of settlement in the absence of growth restrictions, will be bid to
positions above their no -growth -restriction equilibrium levels. Moreover, in terms of a
dynamic model of the statics version of one presented here, housing prices in the
growth -restricted area will be higher than in its unrestricted counterpart, both initially
and at all future points in time. Assuming the substitution elasticity between land and
noniand factors of production is less than infinite, growth restrictions will lead to an
unambiguous increase in average density and housing prices.
What estimating procedure is suitable for testing the impact of suburban land -use
restrictions? A model analogous to Figure 1 involves a pair of demand equations at
two points in time and one or more supply equations, dependingupon whether growth•
restricted and unrestricted cities have separate supply functions.
Consider the following two -equation model:
(1) Demand equation: In P t = ao - a j In Q t + a2 In Z t t
Supply equation: In Pt = bo + bi In Qt (I+cGt) + bz In Z2 t + b sGt
where Pt is the average price of housing in a city at time t, Qt is the size of the city's
housing stock, Zjt is a set of demand-side variables other than Qt that vary across
cities, ZZ t represents supply variables other than Qt, and Gt reports the fraction of a
18 SEGAL AND SRINIVASAN
city's potential suburban land that is removed from growth—the shaded area in Figure
2 as a fraction of the area of the entire annulus.
Our goal is to study neither the level of housing prices across cities nor the differ-
ence in such levels at two points in time, but instead the percent change in prices. If
the various demand and supply elasticities are unchanged over time, a reasonable as-
sumption for the short run (and also a testable hypothesis), we c2n imagine a pair of
difference equations, one demand and one supply, that take the difference of each
equation of (1) at two points in time, t and t + 1:
(2) p=ao-aiq+a2Zi
p=bo+blq(1+cG)+b2z2 +b3G
where p = (In Pt+1 - In Pt); q = (In Qt+I - In Qt); etc. The lower-case symbols of equa-
tion (2) represent percent changes in the variables represented by capital letters in
equation (1) (see note 2). The object of the analysis, as mentioned earlier, is two-
fold: to learn whether the supply function for growth -restricted cities has a different
elasticity from that for unrestricted cities (e ? 0); and to learn whether the y-axis in ter.
cepts are the same for the supply functions for growth -restricted and unrestricted
cities (b3 = 0).
As we note in the next section, the scarcity of high quality time -series data on
changes in the levels of suburban growth restrictions in different cities led us instead
to consider a variable reporting the average percentage of developable suburban land
put off-limits to growth during the inflationaryperiod under study, G. in the transi-
tion from equation (1) to equation (2) this procedure clearly would cause the G in
(1) to drop from the difference equation of (2) because it is a state variable equally
present in both level equations. Above we argued that the presence of a variable
representing growth restrictions affecting a pair of growing cities (a} that start with
identical size and spatial structure and (b) that otherwise grow identically can be
expected to increase housing prices in the restricted city at all periods of time subse-
quent to the restriction, above their equilibrium levels in the absence of the restric-
tion. Accordingly we include G in only one of the levels equations cf (1) so that it
survives when the subtraction is performed.
Including G in equation (2) rather than (inGtti -InGt) means that testing to
ascertain whether supply elasticities differ between growth restricted and unrestricted
cities (slope cf S'= slope of S in Fig. 1) cannot be done by examining the coefficients
of G alone, when G is entered independently of the other variables ofequaiion (2), its
coefficient would shift the location but not the slopes of the functions of Figure 1.
When G appears in the supply equation cf equation (2), its coefficient reports whether
the y intercept of S' differs from that of a. In addition we must took at the signs and
significance of the interaction between G and q, in an equation that includes q sepa-
rately.
Estimating the parameters a, b and c of equation (2) in reduced form is not an
attractive option. This is because one of the variables, G, remains imbedded in the
parameters of the reduced form equation even after q, or p, is subtracted out
We instead rearranged the variables of the supply equation of equation (2) so as to
linearize it, and we then used the two-stage least squares (2SLS) estimating procedure:
SUBURBAN GROWTH AND HOUSING INFLATION 19
a
(2') p = ao = alq +a2zi
p=bo+bigl+cG)+b2z2 +b3G=bo+biq+dx+b2z2 +b3G
where x = Gq and d = b c. The coefficient cis estimated indirectly: c= d/bl. Fieller
bounds may then be computed for c.
The vector of exogenous demand variables, zI, has three components in the empiri-
cal work below: percentage change in per capita urban income, y; percentage change in
urban population, n ; and percentage change in mortgage interest rates, r. We hypothe-
size that a, , 0. if changes in y and n are fully foreseen by housing suppliers, the
first -order partial derivatives will be close to zero. Otherwise they will be greater than
zero, as supplier quasi -rents accrue. Whether such changes are fully foreseen can be
learned empirically.
We can expect aP— tobe negative. Because mortgage money is a good complemerr,
ar
tary with housing purchases, decreases in r will tend to shift the demand function to
the right. Again, whether we move along a shot cr long run supply curve depends
upon whether the decrease or increase in r was anticipated.
Z2, the set of exogenous supply variables, has but one component, construction
costs, k The hypothesis of .3P. < 0 requires no elaboration.
a
THE DATA
The empirical analysis of the next section is performed on observations on a cross-
section of 51 metropolitan areas for which data were available during 1975-1978. The
areas are listed in Appendix A along with observations on the 19751978home price
increases and the growth restriction variable. The latter variable is the focal point of
much attention in this paper and is discussed at length below. First we offer a brief
description of the other variables and their sources.
Home Prices
Federal Home Loan Board data were used, reporting a weighted average of current
doltar prices for new and existing single-family houses sold in each of the SMSAs in
December 1975 (P7$) and in December 1978 (P78), Only conventionally financed
homes are included by the FHLBB. Data on prices in the 30 largest SMSAs are to be
found in the monthly publication, Terms on ConventionalHome Mortgages (Washing-
ton: FHLBB, 1974 through 1978). Observations on additional SMSAs are made avail-
able by the FHLBB for a small fee.
We employed three demand-side and twc supply-side variables which are presented
in sequence.
Income
Many housing market studies have concluded that permanent income is the best
income measure as an argument of housing demand, Such data are not readily avail-
2O SEGAL AND SRINIVASAN
able for metropolitan areas and we used current per capita personat income as a surro-
gate. The data are drawn from the Survey of Current Business. We used average
annual data, comparing 1975 personal income per capita (Y75) with that for 1978
(Y78) -
Population
The number of households is the measure best suited to study the population com-
ponent of housing demand, particularly households in the demographic categories
most likely to occupy single-family dwelling units. These data cannot be obtained
annually for metropolitan areas so we tried several proxies. The most successful was
straight population taken from the Census Bureau's P-26 Series, for ) my 1975 (N75)
and the same month of 1978 (N7s). We also tried migration data from the same p u b
lication, as well as numbers from annual issues of the Rand McNally Commercial Atlas.
Mortgage Rates
Our final demand-side variable relates the price of a good complementary with
housing, mortgage money. We used FHLBB data from the same source as the price
data reporting contract mortgage rate of interest plus lender fees and charges in
December 1975 (1175) and December 1978 (R78). Although 19 states have usury
laws, the post -1975 recovery saw a mortgage climate sufficiently mild to allow interest
rates to move unconstrained.3
On the supply side our primary variable is the Boeckh index of nonland construc.
tion costs, with Milwaukee, 1967 = 100 as the numeraire. The index captures unit
labor and materials costs in single-family construction and allows for intercity cost
comparisons over time. We used numbers for July 1975 (K7$) and )uly 1978(K78),
published in Boeckh Modifier of Construction Cosmo by the American Appraisal Com-
pany (Washington: 1975, 1978). We assume that the labor and material construction
costs are horizontal with respect to the stock of housing in any particular city, imply-
ing a horizontal supply curve for these costs in that city.
Growth Restrictions
By far the largest part of our effort in data collection involved gathering numbers
on the fraction of otherwise available suburban land during 1975.1978 that was put
off-limits to development. The early part of the decade saw a major increase in the
number of communities employing growth management techniques based on environ-
mental or fuel allotment considerations. In some cases, development was stalled be-
cause of moratoria on water supply (particularly in the South or West) or on sewer
connections. In other cases the unavailability of larger allotments of natural gas was a
factor. (Chlyrecently has the moratorium on natural gas tie-in been lifted from some
of the areas surrounding Baltimore.) In several metropolitan areas there has been
public acquisition of open -space land through fee simple acquisition or annexation. in
still others, rationing devices such as building permit restrictions and zoninghave been
used to sequester some land from growth.
The data were gathered through interviews with the staffs of Regional Councils of
SUBURBAN GROWTH AND HOUSING INFLATION 21
Governments, or of rdgional and local planning agencies, in each of the 51 areas. The
purpose of the interviews was to ascertain, for a given metropolitan area, the extent
of land -use controls within the jurisdiction of various agencies prevailing during the
1975-1978 period.
Data were collected both on the percentage of land in otherwise developable sub-
urban land removed from growth in 1975 (+), in 1978 ((&), and on average
throughout the period (G). As is shown in Appendix A values of this variable ranged
from 0 (about a third of the areas) to 43.5 (Sacramento). The average percentage of
land removed from growth in areas reporting growth restrictionswas 12.7%; for a fifth
of the areas, land sequestered from growth ran over 15%throughoutl975-1978.
For several specifications in the next section we use dummy variables for the per-
centage of land that i s growth managed: 0-5% (Go) ,5-10% (G 1), 10-15% (G2 }, 15-20010
(GA and above 20% (G4)-
Quantity
G4).
Quantity ofHousing Units
As one of the two variabies, along with price, endogenous to our model, the Q (or
q) variable plays a central role. As noted above, eliminating the quantity variable in a
reduced -form equation poses a linearity problem, so we left the variable in the anal-
YsIs•
Unfortunately, annual data on the stock of housing units by metropolitan area are
not available, so it was necessary to estimate them. The q variable has a flow term in
its numerator, net additions to stock between 1975 and 1978, and astock term in its
denominator, the quantity of units in place in 1975. Data were more readily avail-
able for the numerator than the denominator; the latter had to be constructed from
1970data and figures on population shifts in the interim.
The rather crude approach to estimating the denominator of q is mitigated by (a)
the relatively higher quality cf numerator data and (b) the relative insensitivity of
estimates of q to errors in the denominator. The mean value of q in our sample was
.071. Accordingly, a IN measurement error in Q7S for a city which experienced a
change in housing stock 1975-1978 close to the mean will result in a 0.7% error in the
estimate ofQ for that city.
In estimating Q75 we took 1970 Census figures for the total number of housing
units in an area, augmented them by new construction figures (permit data coming
from the Commerce Department), and decremented them by our estimates of with-
drawals (equal to demolitions plus net change in vacancies) from the housing stock.
Lacking good data for withdrawals, we used as a proxy for changes in vacancies 1970-
1975 figures on net household formation (net natural increase plus net migration),
drawn from the Current Population Survey. The numerator data, Q78 - Q75, were
largely drawn from the "Summary of Housing Characteristics" in the Annual Housing
Survey.
Results
Table 1 presents the results of four models that were tested. The first two models
suppress a separate constant term for the supply firnction for growth -restricted cities,
forcing S' to intersect at the y-axis. The second pairof modelsallows for the inter-
R
Model Number: 1
TABLE 1.—TWO STAGE LEAST SQUARES REGRESSION RESULTS
2
3
4
Variable ,, .;
Demand
Equation
Supply
Equation
Demand
Equation
Supply
Equation
Demand
Equation
Supply
Equation
Demand
Equation
Supply
. Equation
CONST
- .084*
' .027t
' .084*
- .074t
,016
.011
q.
-1.171
.74t
-1.031
1.981
- ,017
.7171
- -890•
2.T
Y
1.68•
1.67►
1-58*
1.66•
n,
2.821
2 54t
.536
2.27*
r
1.46•
-1,47*
-1.49*
-1,47*
G
.005*
X,
.297•
.069•
k;
2.46**
252t
1.48**
1-44**
Gs
.009
G:
-030
:Gs
.091
:G4
.172
-14.6*
-3.571
X1
-22.2*
-3.31*
Xs
.18.3t
-3.72*
X♦
62
-1.28
standard
error of
dependent
-211
.211
,211
-211
,211
.211
.211
.211
variable
standard error
of regression ,.
.198
.212
,196
.421
.210
.148
.196
.154
t Coefficient greater than standard error. • Significant at 5% level. ** Significant at 1%levet.
SUBURBAN GROWTH AND HOUSING INFLATION 23
L
section to be other than at the y-axis (by including the growth management variable
separately). Models 1 and 3 treat growth management as a continuous variable; mod-
els 2 and 4, in the form of a dummy variable, as described in the previous section.
The coefficients of the demand equations appear to shed some light on the question
of anticipated versus unanticipated demand shifts. Income and mortgage rate changes
have the right sign and are significantly different from zero in all models, suggesting
the possibility that shifts in these variables were less thzn fully discounted in the mar-
ket place. That is, when shifts are futly anticipated by the market, the new equilib-
rium positions tend to be only slightly above the old ones as demand shifts along a
highly elastic long -run supply function. The inflationary impact of such shifts under
these circumstances would be minimal and might not differ from zero.
While inflationary consequences of income and mortgage rate variation in our cross-
sections sample are in evidence, suggesting less than full anticipation and some amount
of supplier quasi rents, the impact of poputation shifts is more ambiguous, While the
elasticity of the population variable, n, has the same order of magnitude in three of the
four models, it is statistically significant in only the last. The coefficient has the right
sign in all nnde]s. The sign and significance of the q variable follows much the same
pattern as that of n.
It is Interesting to note that the pattern of demand elasticities is very much what
one might expect on the basis of the published literature (e.g., De Leeuw, 1971). Price
elasticity is about unity and income and interest efasticities about 1.5.
We found support for our assumption of no change in the demand elasticities be-
tween t and t + I (parallel shift of DD in Fig. 1). We did this by comparing (a) the
sum of squared residuals for the separate equations for 1975and 1978of equation (1)
in which the equations were partitioned by time period with (b) the sum of squared
residuals for the pooled data set and, employing an F test, could not reject the
hypothesis of a constant elasticity at standard levels of significance.4
On the supply side, construction costs, k, have the right sign and magnitude in all of
the models and a high tevel of significance in alt but one model. The housingsupply
variable, q, has the right sign in all models, but the desired level of significance in only
one.
Jhe growth management variable, whether interacted with q (as in x, x, , ... 7x4)
or standing on its own to report y intercept information (5,G 1, . .. ,G4), almost
everywhere has the anticipated sign, magnitude and significance. Because of the sta-
tistical significance of G, we learn that models 3 and 4 are better specified than the
first two and that when G is specified as a continuous variable the y-axis intercept of
S' is .005 above that of S. This suggests that growth -restricted cities have half a per-
centage point "head start" on inflaticn over unrestricted cities, before the interaction
or elasticity effect (S'versus S) is reckoned.
What is the "elasticity effect"? This, we recall, is the tstimate of c, reckoned as the
coefficient of x divided by thzt of q in the supply equation. When growth manage-
ment is viewed as a continuous variabie—models i and 3—this computation yields 0.4 4
and 0.1, respectively. Becaux the former model forces the intercepts of S` and S to be
equal it makes c higher than would otherwise be the case. Abdel 3 has the greater
credibility.
The estimate of c = 0.1 from this model implies that every 10%of potential sub-
urban land sequestered from growth (as in Fig. 2) causes inflation to be one percent-
24 SEGAL AND SR INIV ASAN
age point higher, ceteris paribus, or 1.5 percentage points higher when the force of the
constant term is included. On average, growth -restricted cities are seen to have a 1.7
percentage point higher inflation rate than that of unrestricted cities when demand -
and other supply-side factors are properly controlled for. On average, growth -con-
trolled cities had an inflation rate In housing that was 3.0 percentage points higher
than that for uncontrolled cities. Our estimation procedure, which brings this down
to 1.7 points, ceteris paribus, suggests that the simultaneity problem, addressed by our
technique, is not trivial.
Fieller bounds for c were estimated at the 95% confidence level and found to be
{.018. This suggests the possibility of a 20% error in our elasticity measure at that
Ieve I of confidence,
Models 2 and 4 suggest that the impact of G may not be linear and that in percent-
age terms there may be a greater inflationary impact from growth restrictions at higher
levels than a linear model would suggest. The percentage gaps in the coefficients of
X1, ... , x4 increase more rapidty than the percentage of land sequestered from
growth. As a result, cities having more than 20% of their potential suburban land re-
moved from growth have a housing inflation rate about 6 percentage points above
unrestricted cities, ceteris paribus.
On the basis of the analysis here we cannot conclude that growth restrictions are
bad on welfare grounds. Some would argue that there are benefits from controls such
as social costs associated with growth that do not have to be borne. Certainly home-
owners in communities that put controls in place gain from their capitalization effect
on property values. Would-be owners who are priced out of such communities by the
inflationary aspects of controls are losers. A careful study is needed before the wel-
fare effects of suburban land -use restrictions can be fully assessed,
One conclusion that foliows from the immediately previous comment is that there
may be an overstatement in housing inflation rates such as are reported for the period
1975-1978. While it is true that growth restrictions lead to higher prices, it may well
be that there is a quality differential between suburban housing located in or near
growth -controlled communities and housing that is not The Tiebout model suggests
that people with a choice who choose to migrate to communities in the former cate-
gory and topay higher prices for the assurance of lesser crowding later OR are getting a
product, or an attribute of one, not picked up in the CP1.
NOTES
'The authors gratefully acknowledge helpful comments from Brian J.L. Berry, Adonis Yat.
chew, and Thomas L Steinmeier. NSF Grant SOS 79-09370 helped support the research.
'That the vertical distance separating b and a is a good proxy for price inflation between t and
t + 1 in the no -growth -restriction case can be easily shown by:
Pt+1 Pt + Pt+1 - Pt 't+1 ` Pt Pt.�i - Pt
In Pt+j . In Pt = to ( Pt ) = In ( Pt )=In (i + Pt`_'.j Pt
"'Residenrial Construction: Three Years of Recovery," in Srivey of Cdjrrent Business, June
1978, pp. 18-28.
'In the case of the pooled regression for the two pairs of "levels" equations in (1)—for 1975
and 1378—we restricted variances of the two residuals to be the same. It should be pointed out
>.hat this is not a necessary assumption. We might just as well have assumed different variances but
SUBURBAN GROWTH AND HOUSING INFLATION 25
identical parameters. In point of fact, the assumption of common variances was not unreasonable
—the sum of squared residuals was approximately the same for the separate equations of (1).
LITERATURE CITED
De Leeuw, Frank, 1971, February, The demand for housing: A review of cross-section
evidence. Review of Economics and Statistics, Vol. 53.
Frieden, Bernard, Solomon, A, and Birch, D., 1977, The Nation's Housing, 1975 to
7985. Cambridge.
Grebler, Leo and Mittelbach, Frank G., 1979, The Inflation of House Prices. Lexing-
ton, MA: Lexington Books.
Hendershott, P. and Hu, S, 1979, Inflation and the benefits from owner occupied
Housing,.. National Bureau cf Economic Research Working Paper No. 383. Cam-
bridge.
Mills, Edwin 5.,.1972, Studies in the Structure ofthe Urban Economy. Baltimore:
The Johns Hopkins Press, for Resources for the Future, Inc.
Muth, Richard, 1969, Cities and Housing. Chicago: The University of Chicago Press.
Schwab, Robert M, 1979December, Inflation Expectations and the Demand for Hous-
ing (Available from author.)
Short Papers
The Effect of Growth Control
on t h e Production of Moderate -Priced "ousing
SeymourL Schwartz, David E. Hansen, and Richard Green
INTRODUCTION
nity of Petaluma, California (Schwartz.
Hansen. and Green 1981). detected statisti-
cally significant price increases for new
houses by comparing price changes for stand-
ardized houses in Petaluma to price changes
in two nearby communities.' This statistical
analysis did not, however, tell the entire story
about the effects of the program on housing
production and OR housing opportunities, es-
pecially formoderate-income h6mebuyers.
To many policymakers the distributive
consequences of growth control, especially
those affecting lower-income households. are
of great concern. The important questions
these policymakers want answered are: What
is the effect ofthe growth control program on
the availability of lower-priced housing. and
how are the housing prospects of moderate -
income families affected? To provide the in-
formation with which to answer these ques
tions, vw examined the characteristics (price
and floor area) of the houses actually built in
Petaluma and a neighboring comparison
city—Santa Rosa- between 1970 and 1976.
In this note we present the results of this
analysis and discuss the reasons for the ob-
sen,ed differences between cities. First, we
describe the characteristics of Petaluma's
growth control program and discuss our
methods.'
Land Economics. Vol. 60. No. t. February 1983
0023.7639/94rtl0t-0110 S1.S0i0
L 1983 by the Board of Regents
of the University of Wisconsin Svstcm
PETALUMA'S GROWTH CONTROL
PROGRAM
Petaluma was a small agricultural trading
center (14,035 population in 1560) until the
mid-1960s. when rapid suburban growth from
Sart Francisco (40 miles south) and Marin
County. spread to Petaluma. This growth.
which increased Petaluma's population to
24,870 in 1970, strained the capacity of the
sewerage system and caused serious over-
crowding in the schools. events which were
largely responsible for Petaluma's adoption
of a pioneering growth rate limitation pro-
gram in 1972.
Petaluma sought to limit its growth rate by
establishing housing quota cf500 new units
per year (single-family plus multi -family)
from 1973 through 1977 (City of Petaluma.
1972). Developers competed in an allocation
process in which a citizens review board eval-
uated subdivision proposals according to two
major sets of criteria: one to ensure that ade-
quate public services were provided by the
Pxe ::: - Schwartz is with the Division of Environ-
mental Studies. University of California. Davis. and
professors Hansen and Green arc with the Department
of Agricultural Economics of that university. They
thank Richard Belzer and Peter J. Hunter for gathering
and processing the data. and Michael Johnson for help-
ful suggestions. The research was supported by grants
from the Public Service Research and Dissemination
Program. and the Institute of Governmental Affas'rs.
both at the University ofCalifornia at Davis.
'An hedonic model of house price was used for the
comparison of price changes. The standardized houses
were statistical composites. using the average of each of
six house characteristics. Price changes wcre compared
for several combinations of house and lot size. See
Schwartz. Hansen, and Green (1981) fordetails.
-A detailed discussion of the growth control program
iscontained in Schwartz. Hansen. and Green i 1991).
Schwartz, Hansen, and Green_ Growth Control
developer, and the other to ensure that house
and subdivision quality and other goals
sought by the city were attained. Housing al-
location and building permit data indicate
that the growth control program reduced the
number cf housing units built. In the first
three years of the program only 37% of the
single-family units proposed by developers
received allocations (permissions to build).
Also, during this peiiod the number of build-
ing permits issuedwas 67% less than the num-
ber issued during the three years before
growth control.
The comparison city of Santa Rosa is 15
miles north of Petaluma, which is at the outer
limits for most commuters to San Francisco.
Santa Rasa is larger than Petaluma (1960
population of 31.027) and has a considerable
industrial and commercial base of employ-
ment. Santa Rosa did not change its policy of
encouraging growth during the period of this
analysis n= did it experience any other
changes that would rule it out as a suitable
control for this comparison between cities.
DATA AND METHODS
Sales prices and physical characteristics cf
new houses sold in Petaluma and Santa Rosa
between 1970 and 1976 were obtained from
the Society of Real Estate Appraisers. Our
sample included approximately 75% of all
sales Curing this period. The total number of
cases was 597 for Petaluma and 784 for Santa
Rosa. Sales prices were deflated to 1970 val-
ues by means cf the Boeckh construction cost
index.` which closely followed the consumer
price index.
We calculated the annual cumulative dis-
tribution of sales prices and floor area for
housessold in the two cities between 1970 and
1976. To determine what percentage of the
houses could have been purchased b%
moderare-income households (or lower). we
calculated the maximurn price that such
households could ha\ -e afforded to pay. Cali-
fornia's Department of Housing and Corn rn u-
nity Development defines the moderate -
income range as between 801i� and 120% of
rhe county's median income for it household
of four people. To calculate the maximum
III
price that a household in this income range
could have paid, we assume that the house-
hold spends 30% of its gross income for hous-
ing and that the buyer makes a 20% down
paymeni and takes a 30 -year. constant -
payment loan at the interest rate that pre-
vailed in that year (in the range of 9.0% to
9.75% for FHA loans). Under these assump-
tions the maximum price that a moderate -
income household could have paid is approxi-
matcly $25,000 in 1970dollars. Taking this as
the cutoff (criterion) price. we compare the
results 1r, Petaluma to those in Santa Rosa.
Comparing Petaluina to another city is neces-
sary to eliminate outside events (other than
Petaluma's program) as possible explanations
for the result.' If the pattern of changes in
Petaluma is different fear that in Santa Rosa
and is in the direction predicted by theory. we
can conclude that the changes were due to
growth control. The degree of confidence in
such a conclusion will depend. of course. on
the appropriateness of the comparison city. It
is important to note that new houses built un-
der the growth control program in Petaluma
did not appear on the market until 1974, sowe
consider the period 1970-1973 as pre -growth
control and the period 197.1-1976 as post -
growth control.
RESULTS
I n Petaluma the percentage of houses that
sold for less than $25,000 ($1970) was be-
tween 48.3%v and 56.7% before growth con-
trol: aftergrowth control it dropped to 15.2%
in 1974, 2.3% in 11, 75 and 3.3% in 1976(Ta-
ble 1). In 1976. 68.2 % of Petaluma houses
sold for more than $30.00() whereas before
erowth control no more than 21.7% sold for
more than $30,000 ($1970); in three of the
four years before growth control fewer than
'The Boeckh index is published in U.S. Department
of Commerce. Bureau of Industrial Economics, Con-
struction Review. `
'Sin -c a true experiment usine random a.sienment i�,
impossible in this situation, %,.e use it quastexperimcnt.
where the comparison city of Santa Rosa serve, a> a
control. See Cook and Campbell t iu%U) for a detailed
&-cu>sion of guusicxpcrime ntaI method,
112
Land Economics
TABLE
DISTRIBUTION OF SA,LiES PRICES OF NEW HOUSES :CUMULATIVE PERCENTAGE OF HOUSF, ,SOLD AT OR BELOW
THE STATED PRICE'
Cumulative Percentage
Sale Price
LessThan: Year: _ 1970 1971 1972 1973 1974 1975 1976
$20.000
9.1
12.5
25.000
52.I
54.2
30.000
97.8
92.5
35,000
99.9
100.0
520.000
26.2
21.5
25.000
43.1
38.7
Kom
66.2
68.8
35.000
78.5
95.7
PETALUMA
than 1,400 square feet averaged 32.1 plc before
$30.000 ($1970). The contrast to Santa Rosa
growth control and 32.8% after growth con -
13.3 6.7
4.4
0.0
0.0
48.3 56.7
15.2
2.3
3.3
78.3 96.2
58.7
51.2
31.8
98.3 98.I
93.5
88.4
74.7
SANTA ROSA
reasons why the disappearance of low-priced
These data,prgytde strong evidence ,of the
houses in Petaiuma can be attributed to its
7.1 5.1
10.4
5.8
10.7
32.9 36.5
39.9
37.4
37.5
78.6 69.4
66.4
67.8
59.8
94.3 88.3
85.3
87.9
74.I
'Prices are in constant 1970 dollars.
°We d o not show the remaining price category which results in an ent ry of 100% in the last row because our interest
is in the lower priced houses. The reader can easily calculate the remaining percentage of houses that sold for more
than S35.000 (the difference between the last entry and 100%).
8% of Petaluma houses sold for more than
than 1,400 square feet averaged 32.1 plc before
$30.000 ($1970). The contrast to Santa Rosa
growth control and 32.8% after growth con -
is striking. There, between 32.9% and 43.1 %
trol. The percentage of very small houses was
of the houses sold for less than $25.000 over
greater in 1975 and 1976 than in any previous
the entire period (1970-1976). From i974 to
year except 1970.
1976 (the post -control period). between
It. Is clear that small. ,lower-priced new
37.4% and 39.9% of Santa Rosa houses sold ..
houses nearly vanished from Petaluma after it
for less than $25,000. Thus, the percentage of.
` Imsed growth control; but that did not hap-
"affordable" housing ,,dropped from"-aDOUt`'
pe^I,iti the comparison city of Santa Rosa dur-
SO_o to Tess than 5% rt Petaiuma bclt`it re-,
ing tilts. same. period:. -There are two major
mained high -nearly 1t0%=tri Santa Rosa:
reasons why the disappearance of low-priced
These data,prgytde strong evidence ,of the
houses in Petaiuma can be attributed to its
shift to Petaturn 's housing away from the low
growth control program. First. the criteria for
end of ttie`tnarket after growth control:
evaluating development proposals and
The data for floor area documentthe dis-
awarding housing permissions (atlocations)
appearance of the small house in Petaluma
were heavily weighted toward quality and
after growth control. This is not surprising
amenity items. More than 50% of the maxi -
since hedonic price studies have repeatedly
mum number cf points awarded in the rating
shown :hat floor area is the most important
of subdivision proposals were for such items
determinant of variation in house price. If we
as architectural design quality, site design
consider 1,400 square feet to be a small
quality, character of landscaping and screen -
house, we see that the percentage cf small
ing. provision of foot or bicycle paths and
houses built in Petaluma dropped from about
equestrian trails, and provision of usable open
39% in 1970 and 1971 to 11.0% in 1976. The
space (City of Petaiuma 1972. General Plan.
percentage of very small houses (below 1.200
Housing Element). Second. the city council
square feet) dropped from about 20% in the
made it clear to buildefs in the first year's
1970-1972 period to 1.1% in 1976. Again the
allocation process that it wanted subdivisions
results from Santa Rosa are in sharp contrast.
cf high quality. Proposed subdivisions cf
The percentage Of Santa Rosa houses smaller
modest quality were rapidly e 1 i m i n a t ed from
Schwartz, Hansen, and Green: Growth Control
TABLE2
113
DISTRIBUTION OF FLOORAREA OF NEW HOUSES: CUMULATIVE PERCENTAGE OF HOUSES WHOSE FLOOR AREA
IS AT OR BELOW THE STATED SIZE (SQUARE FEET)
Floor Area
Less Than:
Year: 1970
1971
Cumulative Percenta_ee"
1972 1973
1974
1975
1976
PETALUMA
1200 sq. ft_
20.4
22.5
20.0 10.6
6.5
2.3
1.1
1400
31L7
39.1
28.3 17.9
23.9
18.6
11.0
1600
58.4
56.7
43.3 13.3
28.3
25.6
23.1
I900
81.0
77.5
71.7 M.3
73.9
55.8
39.6
SANTA ROSA
1200 sq. ft.
4.6
6.5
10.0 11.0
14.0
17.2
16.1
1400
36.9
34.4
15.7 31.4
34.3
35.6
38.6
1600
52.3
57.0
51.4 54.0
62.9
57.5
55.4
1900
70.7
84.9
x2.9 86.9
86.7
81.0
913
consideration (Tarr 1978) We ,conclude ;, In Callforni
therefore, that Petalutha's growth controi- .: pre.me cottrts'1
program' effectively eltmtnated'the prodnc for a gro%wth;
tion �f dower pritgd housing to that retv�:, betzefits QnIy ti
..t-,•..,5 a... �':. n.. . -.».e,
POLICY IMPLICATIONS
Many local government decisionmakers
perceive important benefits to their cont-
munities from growth control, including en--
hanced environmental quality a rid amenities,
maintenance cf "small town character." and
better public services and fiscal status' (Ro-
senbaum 1978;Johnston 1980). However, f& -
cal decisionmakers may not be aware of or.
concerned about. the costs of growth control
because most of the costs fall upon individuals
who live outside the growth control commu-
nity or on renters in t he community. Since the
losers are usually in lower income groups than
the beneficiaries of growth control such pro-
grams have potentially serious equity conse-
quences (Schwartz 1982). To the extent that
the losers lack political power to influence de-
cisions within the growth control jurisdic-
tions, the stage is set for confrontation be-
tween state and focal pohcvmakers over the
acceptability CC growth control programs. Re-
cent actions by some local governments. as
well as by state legislatures and state courts
are evidence of growing concern for the eq-
uitv consequences.
w 3ersev. the state su
ram: to provid4
keniiii;j. com
in a;communit,
negattve.regtona! mpacts on the suppir
tower priced houstr g tf tt :cannot :da so th,
.program: wtlY�be �•oosidered exclusionary Ii
Cahforrtia: thy' Itigisiature mandatedthat to
cai governments act:.af&rmatively to Inee
their Nf shar't of regionalhoustng needs fo
all income groups .(Chapter 1.141- Cali f orni
Statutes• of
tit The legtstature furthe
placed het�iien of proof; -on local- govern
meets t tacr.artt growth control ordinances tt,
•'Less socially acceptable reasons for restricting
growth may exist but are not usually expressed. For e\-
ampie:. Ellicks64 (1979) -asserts that suburban growth
controls a> a designed to enrich existing homeovrner>
who, in effect, form a housing cartel to restrict the vtp-
plv of nev►single=tataily houses. The targe literature on
cxclusionarn land.use practices points to the protection
of property values as :the primary motive for such prac-
tices (Delafons 1969: Babcock and Bossetman 1973).
"in California the relevant case is Associated Howe-
hudders of Greater East gar r. Cin- of Livertrupre. 1 --
Cal 3d 582.557 P. 2d at 483. 135 Cal Reporter 41 (1976 t:
in New JCTSCy the relevant case is Southern Burlington
NAACP v. Township of.ttown Laurel, 161.1.J. Super.
ct. Law Div. ?17. 391. A.2d 415 119781.
114
show,. in; any. court challenge, that the ordi-
nance "is necessary for the protection of the
public health, safety, or welfare of the popu-
lation": (Chapter 1144, California Statutes cf
1%0).?
Although California and New Jersey are at
the forefront of efforts to eliminate exclusion-
ary land development practices and provide
affordable housing, other states seem likely
to follrn" suit. Consequently. stringent
growth control programs may not be able to
withstand legal challenges unless the enacting
communities also make special efforts to pro-
vide affordable housing to lower-income
households. Petaluma s^program withstood a
legal;chalinge shgrtly after ti was adopted.
based largely on the qty's goal of providing
between 8% and=32% `of new,,hous ng in a
pace range `affo'r'dable fo' low= or moderate -
income householdsx Our=analvsis' shows,
however; that Petaluma'failed>to achieve this
goal:.Instead, its°`growth control program
� nt+arlV"'eiiminatPti _nE+ir�'`inwPr nriri.�t-""c�noin_
family housing Petaluma's only incentive for
encouraging affordable; housing was. by
awarding, in;its evaluation of proposed devel-
opments, up to 15 points out of. a total of 130
gotnts bu 6 pro. ion of affordable fitous-
rriosv of the `remaining points ,were awarded
for b.b sd§ dd subdivision'quality and arneni-
ties. A stronger commitment must be made
by the local government if affordable housing
is to be built. Other jurisdictions—for exam-
ple. Davis. California—have combined a
stringent growth control program with
stronger incentives for providing affordable
housing (Schwartz and Johnston 1983). How-
ever. the ability of even these stronger incen-
tives to overcome the adverse impacts of
growth control programs on affordable hous-
ing is very much in doubt.
Land Economics
References
Babcock. Richard R. and Bosselman. Fred P.
I973. Exclusionan, Zoning: Land Use Regula-
tion and Housing in the 1970s. New York:
Praeger Publishers.
Delafons, John. 1969. Land -Use Controls in the
United States. Second Edition. Cambridge.
Nlass.: The NIT Press.
City of Petaluma. California. 1971. General Plan.
Petaluma Housing Element (July 10, 1972).
Cook. Thomas T., and Campbell. Donald T.
1979. Quasi -Experimentation: Design and
Analysis Issuesfor Field Settings. Chicago. Ill.. -
Rand McNally College Publishing Co.
Ellickson, Robert. 1977. "Suburban Growth
Controls: An Economic and Legal Analysis."
The Yale Law Journal. 86 (Jan.: .385-511.
Johnston. Robert A. 1980. "The Politics of Local
Growth Control." Policy Studies Journal 9
(Special # 1): 427-39.
Rosenbaum. Nelson. 1978. "Growth and Its Dis-
contents: Origins of Locill Population Con-
trols." In The Policy Cycle. eds. Judith May
and Aaron Wildayskv. Beverly Hills. Calif-:
Sage.
Schwartz, Seymour L. and Johnston, Robert A.
1983. "Inclusionary Housing Programs."
Journnl of the American Planning Association
49 (Jan.): 3-21.
'1982. "Equity Implications of Local
Growth Management." In Enrironmental Pol-
icy Implementation. ed. Dean E. Mann. Lex-
ington, Mass.: Lexington Books.
Hansen, David E.: and Green. Richard.
1981. "Suburban Growth Controls and the
Price of New Housing." Journal of Environ-
mental Economics and Management 8(Dec. ):
303-20.
Tarr. Fred. senior planner. City of Petaluma.
1978. Interview with Maureen Newby. Nov.
'Chapter 1143 in the Statutes of 19SO is at Culifi rn,a
Government Code. sections 65580 ff.. Chaptcr 11.1.1 in
the Statutes of 1980 is at California Evidence Cade, sec.
tion 669.5
0
THE EFFECTS OF GROWTH MANAGEMENT
ON THE HOUSING MARKET
A Review of the Theoretical
and Empirical Evidence
JANE H. LILLYDAHL
LARRY D. SINGELL
University of Colorado at Boulder
ABSTRt►CT. The no=growth or;slow growth poftctes that Itave.spad rapidly in rhe
past 1 S years vary -an form surd Include ex»hcit population targets, rigid development
controlad
re to ptmvtde expanded public serytce' among other techniques The
Purposeof thtsarttcle uto ret7ew tlusee foaxt The article fust presents a revww of the
economtc :theor,� that tllumtncites the economic motrvwww", or such controls and
idrnstfies some o the mcyor Impacts to tie gtnpncally assessed The next part of
ar iele focuses on the hottsr�t8 price, productrorr, and equity effects of growth �ontm4 as
documental alt the empiritaal kteiiature'The'article concludes witha s�ecdon devoted to
INTRODUCTION
Policymakers in American cities have significantly changed their attitudes regarding
urban growth. For approximately 20 years after World War 11, strong pro -growth
attitudes dominated. Growth was seen as necessary €orproviding expanded employ-
ment opportunities and desirable because it would augment city budgets and provide
greater social, cultural, and economic diversity. In the 1960s and 1970s the perception
ofenvironmental deterioration as a result of urban growth emerged and cities began to
search for ways to obtain higher quality residential environments. Initially, concerns
were focused largely on physical features exemplified by air pollution and noise levels.
However, in the mid-1970s. a number of suburban communities began to feel that
JOURNAL OF URBAN AFFAIRS, Volume 9, Number I, pages 63-77.
Copyright C 1987 by JAI Press, Inc.
All rights of reproduction in any form reserved.
ISSN: 0735-2166.
continued growth threatened a wider range of amenities important to the quality of life.
Limited or no -growth ordinances were seen as a means to maintain a pleasant, small-
town atmosphere and lifestyle as well as to provide for open space, greenbelts, attrac-
tive neighborhoods, n -h n i m al traffic congestion, and high quality public services at
reasonable tax levels. Controls cf this type have now been ena•.ted in a large number of
suburban communities in every region of the country. Indeed, the fervor to stop or slow
growth became as strong in the 1970s and 1980s as that of the pro -growth movement
in the 1960s.
The no -growth or slow-growthpolicies that have spread rapidly in the past 15 years
vary in form and include explicit population targets, rigid development controls, and
refusal to provide expanded public services (e.g., schools, water supplies, or sewage
treatment facilities), among other techniques. Such policies now find support in urban
areas in every region of the United States, even in areas that previously encouraged
rapid growth. Dowall (1982) identified 567 local governments across the country that
had some form of growth control, and Segal and Srinivasan (1985) found that nearly
two-thirds of a sample of 51 SMSAs from every region in the United States had growth
restrictions. Although an average of 12% of the available suburban land was set off
limits to growth in their sample, in some cities growth was barred from 30 to 40% of
the surrounding Iand.
Growth controls are, of course, not a new phenomenon. Local governments have
long had the power to regulate new developments through zoning and other land use
controls. What is new is the introduction of specific growth targets or limits and the
pervasiveness of such policies. For example, a recent survey of 64 San Francisco Bay
area jurisdictions showed that since 1970, approximately half of the jurisdictions had
employed sane sort of moratorium on residential development for some significant
period cftime (Gabriel, Katz, & Wolch, 1980).
Although growth control policies are now widespread, Solomon (1976) was forced
to conclude in his review of the literature that virtually nothing was known about the
size or nature of the impacts of growth control. Since that review there have been a
number of efforts to evaluate the impacts of such controls on the price, quantity,
quality, and other aspects of housing from both theoretical and empirical perspectives.
The purpose of .this article is to review these efforts. The article first presents a review
of the economic theory that illuminates the economic motivations for such controls and
identifies some of the major impacts to be empirically assessed. The next part of the
article focuses on the housing price, production, and equity effects of growth control, as
documented in the empirical literature. The article concludes with a section devoted to
policy implications.
THE THEORETICAL FOUNDATION FOR GROWTH CONTROL
The reduction in social well-being that may result from unguided or uncontrolled urban
growth, and therefore the justification for growth controls, is based on several eco-
nomic arguments. For purposes of summary and analysis, these arguments may be
grouped into three broad categories. First, secondary consequences or side effects of
urban growth as exemplified by congestion occur and may be overlooked by decision -
makers. Economists refer to these effects as externalities and demonstrate that if
( Effects of Growth Management on the Housing Market 173
has been a major source of increased personal wealth for middle-income Americans,
resulting in a major wealth redistribution, between owners and renters (Sternlieb &
Hughes, 1980). Renters may also incur significant losses in other more indirect ways.
For example, rental units may be located in inferior school districts or in areas less
accessibleto employment opportunities. Steger(1973) found, forexample, that limited
housing choice of central city residents results in a 5% loss of income because of
additional commuting costs.
Growth control programs may also create importantjurisdictional inequities When
growth is discouraged in one community, it may be shifted to srrrounding jurisdictions_
Even if housing prices are not increased. if public services are producsd under condi-
tions of increasing costs, this will place a greater burden cal surrounding communities.
In such cases, it may be in the best interest of surrounding communitiesto adopt growth
" control measures also. Schwartz (19 82), €orexample, observed that "there is evidence
to suggest a chain reaction of growth control adoptions in communities between San
Francisco and Sacramento following several years after the pioneering programs of
Petaluma and Davis" (p. 232).
Growth control programs have pronounced effects on the availability of low- and
moderait-income housing. In unique urban environments where permission to build is
based cn amenity and design characteristics, affordable housing for low- and
moderate -income families may vanish. In metropolitan regions where interconnected
housing markets lead to similar types of controls in many adjacent communities, low -
and moderate -income families maybe forcedby such controlsto live in neighborhoods
that further disadvantage them with respect to job opportunities and education. A
postponement or elimination ofthe opportunity for home ownership may also result in
a significant redistribution of income.
CONCLUSIONS AND POLICY IMPLICATIONS
The evaluations of,the impact of growth controls suggest that while these efforts ma}
have.help maintain the desired community character, 'housing pric es have increased
and in manyses'the avatiabiility of low or moderate prtced housing has decline(
substantially .or:evetF Ztsappeai<ed.- This combined. with national inflatioin and higt
mortgage mteresrrates :has created a real crisis to kousing; markets. Currently, a verb
large.percet►tage of families cannot:afford;to'purchasehousrng. r�►n'expanded numbei
of -households hasbeen forced to rent and/or reduce housing..size or quality. Higher
prig siin the Nl rental market also make. the, accumulation of:capital forfuture purchas(
mare difficult The long=term viability of growth control programs cansequentl3
requires that some:means be developed tobffset the price, equity, and extrajurisdic
tionat impacts of these programs,
:,A number of policy recommendations have been advanced. For example, Ellicksor
(1977) proposed a. judicial remedy recommending that. communities be, allowed tc
nursue Qrowth control measures but that. state . courts use ttie taking clause in their
constitutionsto entitle landowners and housing consumers to sue for damages. Certain
landowners could recover damages for land value losses and home buyers or renters
could bring class action suits to recover price increases brought about by growth
741 JOURNAL OF URBAN AFFAIRS 1 Vol. 9iNo. 1/1987
control. if the growkh control community could demonstrate that its program was both
efficient and equitable to consumers of housing; it would not be subject to damages.
As an alternative to Ellickson's judicial remedy, a number of local governments have
sought to overcome the undesirable side effects by establishing inclusionary housing
programs which either provide incentives for or mandate the construction of Iow- and
moderate=cost housing In a recent review of inclusionary housing programs, Schwartz
and Johnston (1983} :provided' evidence for the inadequacy of nationwide efforts to
provide housing forjow or moderate income famines Fofsuch programs to be suc-
cessful;Schwartz and Johnston Argue:that they must: (1) mandate moderate -cost units
frpm medium to large scale developers i-ian requue fees from most other developers;
(2) screen buyer and;renter applications to maxmuze social;benefits; (3) control resale
price ip order to retain units' at`=moiierate prices; and t4) provide? substantial economic
inceaitivesiio developers (p=19).
As an alternative, or perhaps in conjunction with such programs, cities might sell
local revenue bonds for the purpose of providing low-interest loans to moderate-
inc.on ^ t t y : Below market tnterest rates are, hawever� in general inadequate in
b
ringing' housing costs down. to :the :point where they: are: affordable to low and
moderate income families.' Unfortunately, many of the forces that underlie the inflation
in housing costs are beyond the control cif local governments. Hence, if the provision of
low- and moderate -cost housing is considered a desirable social goal, a national hous-
ing policy committed to assisting local governments in this effort may be necessary.
While:a combination of federal`effotts.and inclusionary hpusing programs by;iocal
3 governments might be workable, the larger problem of efficicntIy providing hottsirig in
4
o
a `metropolitan 'region, still remauis, It6 y7 that aggregate housing, prove-
s'ion wile match needs in' an optimal manner, when individaai political "subdivisions
institute" gmw�lt eont�ols and when housing construction `is the primary ,source of
contra!: ,Growth control and inclusionary prpgxams repress or distort ,normal free
market pi�odetction a.reduce�the ttorrn�l l�eiefits of trickle down to Lower income
buyers anii renters in:addition, these programs:are enacted by subinetropolitan com-
tan community. While there is a real need for efforts to maintain the quality of local
environments, metropolitan areawide governments are still too weak to ensure that
such efforts will take cognizance of the benefits and costs to the larger society. All too
often, a disproportionate portion cf the costs of such programs fall on the lowest
income groups who can least afford tbEm.
NOTES
1. The graphical analysis draws on Ellickson's 1977 article in the Journal of Law and
Economics.
2. The actual increase could be more if the price were set by market forces that did not
consider the congestion costs.
3. This raises one of the difficult theoretical and empirical issues in the growth control
literature. If antigrowth policies raise housing prices within municipal boundaries, these higher
prices will make housing in neighboring jurisdictions more attractive to consumers. The result
would be an increase in the amount of housing built outside the boundaries, and potentially. an
increase in housing price in these jurisdictions as well. From a resaarch point of view, this
Effects of Growth Managemen! on the Housing Market 175
frequently causes difficulties since cities with unique environ men.al settings that impose controls
can be compared most easily with cities in the same environment without controls. However, if
the cities are close enough to have similar environments. then their proximity also integrates their
housing markets so that little or no price difference can be observed over time. When compari-
sons are made between cities that are distant enough to have separate housing markets. environ-
mental amenities are less likely to be comparable. From a practical or policy point of view, the
inp3at of growth control on surrounding communities means that one jurisdiction can impose
costs on neighboringijurisdictions who are not free to express their preferences in the ballot box.
4, Some Boulder, Colorado, residents have claimed that due to growth controls, high-density
condominiums and apartments have replaced single-family units with the result that this city is
less family oriented and more oriented toward singles lifestyles.
5. Many of the empirical studies of growth control have used California data. Because of the
atypical housing markets in that slate, it is possible that the results may not be generalizable.
However, the articles which do focus on growth management in other parts of the U.S. (e.g.,
Butler& Myers's [ 19841 article on Austin, Texas, and Knaap's [ 19851 study of Portland, Oregon)
present findings which are consistent with those cf the California studies
6. One externalityassociated with some growth control programs is delays resulting in higher
construction costs. Although this issue is beyond the scope of this paper, it is worth noting that
these costs may be substantial. The Rice Center for Community Design and Research (1979)
estimated that government regulations in ftHouston housing market resulted in costs of $1,400
to $2,100 fora 13 -month delay. The ConstructionIndustry Research Board (1975) cameup with
substantially higher estimates of a delay prior to construction of $1,027 per month.
7. Rosen and Ka tz (1981) criticized th is study because land price increases were completely
a ttnbuted to growth control ignoring inflation and other market factors and because there was no
control city to allow for a determination of increases in profits and costs resulting from growth
management.
8. Some of the econometric problems include: autocorrelation, simultaneous equation bias,
specificationerrar, and partial use of forecasted rather than actual data -
9. It is common for researchers to have concentrated on the price effects and ignored the
production effects. More research needs to be done investigating the growth control effect on
housing quantity and not just on housing price.
REFERENCES
Beadey, T. (1984, Autumn). Applying moral principles to growth management, Journal of the
American Plonning Association, 459-469.
Blewett, R (1983, January). Fiscal externalitiesand residential growth controls: A theory of chtbs
perspective. Public Fumnce Quarteriy, I I(1), 3-20.
Butler, K., & Nkms,D. (1984, Autumn). Boomdme in Austin, Texas: Negotiated growth man-
agement. "Journal
an-
agement."Journal of the American Planning Association. 447-458.
Construction Industry Research Board 0 975, April). Costs of delay prior to construction. Los
Angeles: Author.
Cooley, T., & LaCivita, CJ. (1982). A theory of growth controls. Journal of Urban Economics.
12,129-145.
Correll, M., Lillydahl, J., & Singell, L. (1978, Mky) . The effects of greenbelts on residential
property values: Some findings on the political economy of open space. Land Economics.
54(2),207-217.
Dowall, D. (1982). An examination of population -growth -managing communities. In D. Mann
(Ed.), Environmentalpolicy implementation. Lexington, MA: Lcxington Books,
Dowall, D. (1984). The suburban squeeze. Berkeley: University of California Press.
761 JOURNAL OF URBAN AFFAIRS I Vot. 91No. 111987
Downing, P. (1977, June). Suburban nongrowth policies. Journal of Economics Issues, 11(2),
387-399,
Elliott, M. (1981). The impact of growth control regulations on housing prices in California.
American Real Estate and Urban Economic Association Journal 9.115-133.
Ellickson, R. (1977, January). Suburban growth controls: An economic and legal analysis. The
Yate LAw Journal, 86,395-5 1I.
Gabriel, S., Katz L, & Wol ch, J. (1980, Spring). Local land -use regulation and Proposition 13.
Taxing andSpending, 73-81.
Gabtiel, S., & Wolch, J. (1980, November) -Local land vse regulation and urban housing values.
(Center for Real Estate and Urban Economics Working Paper No. 80-18.) Berkeley:
University of California Press.
Gleeson, M. (1779). Effects of an urban growth management system on land values. Land
Economics, 55, 350-65.
Huszar, P. (1977, July). Equity and urban growth: Real property value appreciation in San Jose,
California. American Journal of Economics and Sociology, 36.25 1-261.
Janczyk, L & Constance, W. (1980). Impacts of building moratoria on housing markets within a
region. Growth and Change, l I, I I -19.
Johnston, R.A. (1980, December). The politics of local growth control. Policy Studies Journal, 9.
(Symposium Issue on Environmental Policy.)
Johnston, RA, Schwartz, S1, & Hartz, W. (1980). The effectiveness of the moderate cost housing
program of Davis, California. Unpublished manuscript, Division ofEnvironmectal Studies,
University of California
Johnston, R.A., Schwartz, S.I., & Tracy, S. (1984, Autumn). Growthphasing and resistance to infill
development in Sacramentocounty. Journal of theAmerican Planning Association, 434-446.
Katz, L., & Rosen, K (19 8 0, September). The effects of land use control o n housing prices. (Center
for Real Estate and Urban Economics Working Paper No. 80-I3.) Berkeley: University of
California.
Knapp, G. (1985, February). The price effects of urban growth boundaries in metropolitan
Portland, Oregon. Land &ctnc nics,61(t ), 26-35.
Landis, J. (1986. Winter). Land regulation and the price of new housing: Lessons from three
California cities. Journal of ft -American Planning Association, 9-21.
Rice Center for Community Design and Research. (1979). The cost of delay due to government
regulation in the Houston housing market. (The Urban Land Institute Research Report 1128.)
Houston, TX: Author.
Richardson, H (1973). The economics cf urban size. Lexington, MA: Lexington Books.
Rosen, K, & Katz, LF. (1981).Growthmanagement and land use controls:The San Francisco Bay
Area experience. American Peal Estate and Urban Economics Association Journal, 9,
321-344.
Schwartz, S. (1982). Equity implications of local growth management. In Dean Mann (Ed.),
Environmental policy implementation (pp. 223-248). Lexington, M A Lexington Books.
Schwartz, S., Hansen, D., & Green, R. (1981). Suburban growth controls and the price of new
housing. Journal of Environmental Economics and Management, 8,303-320.
Schwartz, S., Hansen, D., & Green, R (1984. February). The efffect of growth control on the
production of moderate -priced housing. Land Economics, 60(1), 110-1 14.
Schwartz, S., & Johnston, R.A. (1983). Inclusionary housing programs. Joumalof the American
Planning Association, 49, 3-21.
Segal, D., & Srinivasan,P. (1985). Suburban growth and housing inflation. Urban Geography. 60),
14-26.
Singell, L.D. (1974). Optimum city size: Some thoughts on theory and policy. Land Economics,
50(3), 207-2;.2.
} Ettects of Growth Management on the Housing Market 177
Solomon, A. (1976, February). The effect of land use and environmental controls on housing: A
review. Cambridge, MA: Joint Center €orUrban Studies of MIT and Harvard University.
Steger, W. (1973). Economic and social costs of residential segregation. In bWm Clawson
(Ed.), 1 &xkmbV urban laP4 policy (pp. 83-113). Baltimore, M D The Johns Hopkins
Press.
Sternlieb, G., & Hughes, J. 0 980). Housing and sheltercosts: The schizoidproblem of the central
city. In America's housing. prospects and problems. New Brunswick, NJ: Rutgers University,
Cumty- for Urban Policy Research
-Tiebout, C. (196). A pure theory of local public expenditure. Journal of Political Economy. 64,
416-424.
Tolly, G. (1974). The welfare economicsofcity bigness. Joumal of Urban Ebx=zics. 324.
Urban Land Institute, & Gruen, Gruen, and Associates. (1977). Effects of regulation on housing
costs Twocase studies. Washington, DC: Urban Land Institute.
LAND PRICE INFLATION AND AFFORDABLE HOUSING
'a$ J. Thomas Black and James E. Hoben
U.S. Departmentof Housingand Urban Development
Prices for standard lots and acreage were collected for 1975 and 1980 in 30
metropolitan areas and then analyzed, using multiple regression, to identify factr•-s
which would explain variations among metropolitan areas. Extreme price variations
were observed. For example, from 1975 to 1980, the price of a standard residential
lot increased as little as 31% in one area, white the price r o x 176%in another. Over
80% of the variation in lot price increases was explainable by a model combining land
supply and demand factors. Ik,thelrardero!`linpsnce
ori, the,%ctors`were::(t) an
Index of, regulatory resuiciiozi; (2j popu>:tion increases; (3j percapita Income in
creases. and {4j job increases. The analysis suggests that pubI c regulatory, Inframc-
mre and"fax pollclet 4m'- stgnificantbj affect land, supply and demand and, in turn,
prices. Communities that clwose to manage growth must monitor land supply and
demand' and,`adjvst their potkks,to ensurewnipetitive noninftationaiy land markets.
r,' Otherwise' -major 0.cream, in land prltxs for Housing and- buss nesses may result. _
INTRODUCTION
Land comprises a significant portion of the cost of housingand of many businesses.
Over the decades, that proportion has risen and fallen depending upon the cost of
land, the amounts utilized, and changes in other cost components. In 1980 it ap-
peared that land costs had risen sharply in many growth markets. While the U.S. Cen-
sus showed that land as a component of housing cost was around 21%nationwide, in
some markets, such as the West Coast, FronVrange and Sunbelt, there were reports
that land comprised 40% of single-family housing costs. What makes these increases so
important is that they were in the areas of the nation where housing demand was
greatest
The reason for concern over rising urban land prices is simple: Housing quality and
home ownership are threatened and business costs are increased. Besidescontributing
to problems of housing affordability, a drop in housing production results in reduced
business activity, and increases in housing costs can lead to increased vuage demands,
thus significantly affecting the economy.
To find out if land prices really were increasing, and , if so, why, the authors cal
lected price data from 30 metropolitan areas and, through correlation and multiple -
regression analysis, examined the reasons for variations in levels and trends in land
prioes,' The principal research question was to what extent did demand versus supply
factors explain changes in residential land prices. What follows is a brief three-part
summary of the exploratory research. First, a description of the variation in land
prices between metropolitan areas; second, a report on efforts to identify why prices
vary between markets; and finally, some hypotheses are offered on the operation of
land markets. The research methodology is dmribed in tie text and additional details
are provided in the appendix.
27
Urban Geography, 1985, 6, 1, pp, 27-47.
copyright 0 1985 by V.H. Winston & Sons, Inc. All rights reserved
28 BLACK AND HOBEN
LAND PRICES
A major difficulty in understanding land markets has been the absence of compara-
ble land price data. Data collection has been hampered by the fact that no two parcels
are exactly alike; each pie:e is unique in terms of its size, location, topography, sub
soil conditions, public regulations, supporting services, ownership, and future utility.
Pdcesvary with these attributes and with the conditionsof sale.
Analysts have struggled to develop price data by manipulating sales data or prop-
erty assessment records, performing residual cost calculations or projecOng future
returns for raw lands. None of these efforts has produced a suitable record of com-
parable prices for different areas of the country and for particular years. The US.
Census Survey of Construction includesone item on residential land costs; however, it
is not published because the response rate is lower than the Censusconsiders accepta-
ble. The Federal Housing Administration (FHA) publishes land cost data for FHA -
insured new and existing single-family properties but the sample is not representative
of all single-family housing Finally, the U.S. Department of Agriculture publishes
data on the value of farm acreage but this series excludes land at the urban fringe.
Faced with poor data, the authors developed a survey methodology.2 It involved
defining two types of standard land parcels and asking homebuilders and residential
appraisers in 30 metropolitan statistical areas (SMAS) for estimated prices. Since the
greatest interest was in land as a component of housing costs, the work focused on two
types of parcels considered key to housing production:
An improved single-family lot—defined as having 10,000 square feet, zoned for
single-family, with utilities to the lot, located in an area attractive to buyers of
mid -price, single-family homes and within 20 minutes of a major employment
area.
Unimproved acreage suitable for single-family use—defined as parcels of 20 to
100 acres, with utilities available to the site at negligible cost, at the urban
fringe, within 20 minutes of a major employment center, without any adverse
environmental conditions, and not in a prestigious area.
The definition of a standard parcel est*lished a single image of a piece of land for
which an expert could then estimate a probable price. By using the sane definitions,
prices also could be compared from one market area to another.
The SMAs3 were selected to represent all sections of the country and varying sizes
and growth rates (see Fig, 1). The sample was not random. The nation's largest
metropolitan areas were omitted because of the expectrd difficulties respondents
might have with the survey. No special treatment was given to multi -centered areas.
The authors feel, however, that the areas selected reasonably represent the universe of
metropolitan market areas.
For each metropolitan area, approximately 25 to 40 real estate experts were identi-
fied from referrals and professional membership lists. The experts were mailed a sur-
vey describing the standard parcels and asked to estimate prices for both 1975 and
1980. The average response rate was 10, or about 35%, with a high of 16 and low of
4. In general, individual price tstimates for an area were consistent The prices cited
in this paper are the median values provided by the experts.
Following are the findings on land price variations for residential lots and raw acre-
age among 30 metropolitan markets.
40 BLACK AND HOBEN
1975-1980 Percent Increase in Raw Land Prices
Explanation of Inter -Metropolitan Land Price Variations
Independentvariables
(in order of importance)
Improvements in correlation
with additional variables
R2 Adj. RT
1. Percentage increase in jobs,1975-1980
.331
.302
2. Regulatory restriction rating, 1980
.496
.44S
3. Percentage increase in income, 1975-1979
.570
,508
4. Physical restriction rating
,599
.519
5. Percentage increase population, 1975-1980
.632
.536
increase In raw land prices= 121.1 + 1.0 (jab I nc.) -24.3 (reg. rating) +4.0 (pay Inc.) - 26.8 (phys.
raring) + 3.0 [popu. inc.)
Standard deviation 48.9; cares 28, adtbed San Jose and Cincinnati, the first because of extreme
values and the second for lack of 1975 price data.
Supply and demand factors represented by regulatory restrictions and increases in
population, jobs, and income were the major factors influencing the rate of increase
and land prices. The explanatory power of the raw land model was lower than that for
improved lots since it is believed that the raw land market is less directly influenced by
current changes in supply -demand conditions and more influenced by ownership char-
acteristics and longer term market expectations.
It is important to stress, at the conclusion of this analysis, that the data collected
and its manipulation were exploratory at best. Additional research is needed to con-
firm or refine the observations. Areas for possible improvements include randomly
selecting the sample of metropolitan areas, refining the standard parcel definitions, and
testing the price survey methodology. More time points are needed. Finally, much
work is needed on defining and testing additional explanatory factors. The regulatory
restriction rating needs refinement, and other supply measures need to be developed.
SOME SPECULATIONS
In spite of the methodological limitations, the preceding results support two propos
sitions regarding urban land policy.
7. PrevaZZYng Land frices May Be signlflcantly Affected by the Aggregate Effects of
Govemment Policies
It is well known mat the value of an individual parcel can be increased or decreased
by a change in zoning which affects the economic rate of return from the parcel. Simi-
larly the provision of a sewer, road, or transit line can impact a parcel's value. What
this study suggests, and is not commonly recognized, is that at a much larger scale the
combination of local policies (regulations, infrastructure investments, taxes) probably
changes the overall balance of land supplies to demand and thereby raises er lowers the
average price for land.
LANDPRICE INFLATION 41
The recognition in the 1970s of strong connections between urban development
policies and objectives such as encouraging revitalization, infill and compact develop-
ment, reducing pollution, protecting agriculture, and balancing local budgets has re-
sulted in subtle but far-reaching changes in land markets. Generally, local policieshave
evolved from accommodating growth to the control of growth. New policies include
trying to direct the amount, type, location, and timing of private development_ In
locations where special efforts have been made to manage development, itis likely that
the public sector has greatly reduced the supply of land available for development
Especially serious land/housing price problems occur when local policies seek eco-
nomic growth but limit population (residential) growth. Ifa community adds jobs,
the demand for housing must increase. Ifthe amount of land for residences is limited
and densities are kept low, there is bound to be increased land competifion and price
inflation.
Public officials, interest groups, and citizens need to balance their desire for com-
pact orderly growth and the protection of the environmentand agricultural landswith
policies which -ill also assure competitive land markets with well -located affordable
sites for homes and businesses. For example, the San Francisco Bay area is now com-
ing to this realization. The Bay Area Council, an association of 300 leading businesses,
has issueo a strong call for balanced land policies. San Francisco and Sunnyvale, Cali-
fornia have responded by adopting policies linking economic expansion and housing
Much morethought needsto be given to how tvachieve and maintain these balances.
2
ere,.,. 1T Many., Lard 49 its public Policies and Economic Cycles Are Likely to
i� ffecf Them O/ffe�rit/y � '- `
An interesting finding of the study was the difference in the absolute prices and
rates of increase in prices for the two land types. The median price of improved lots
increased an average of 66.41/6 while the price for raw acreage increased 92.7%. Why
would one increase be so much more than the other?
One explanation of the higher increase in raw land prices is that the price of raw
land is only one of the factors affecting the price of an improved lot. There are other
costs of developing land. The costs of converting raw land to the developable stage
may not have risen as much as the cost of the raw land itself. if they did, the price of
developable land would have risen as much or more than the price for raw land.
Another explanation is that the owner -investors of improved land and the owner -
investors of raw land are influenced by different forces. Each owner -investor group
has different objectives and different financial capabilities and therefore public policies
and economic cydes affect each differently. For example, developers specialize in
purchasing raw land and, through a process of rezoning, subdivision, and the construc-
tion of streets, water systems, etc., produce improved lots. Land improvement involves
considerable equity investment plus funds at relatively high interest rates. The devel-
oper is impatient, if not obligated, to seii his improved lots within a short term. His
financial success i s dependent upon maintaining a Cash flow. I f there i s an excess of
improved lots relative to demand, the deveioper is forced to cut his profit An excess
of tots occurred in the late 1970s and was exacerbated by the onset of the housing
A 42 BLACK AND HOBEN
recession of the early 1980s. The 66% increase in lot prices probably only reflects the
52% inflation for the 5 years, the costs of increasing focal development fees, and a
modest profit, if any. Data for price changes from 1980 to 1983 might reveal no
changes or even declines where developers went bankrupt.
In contrast, the owners of most raw devetopable land are more likely to be patient,
long-term investors who are financially capable of withstanding short-term drops in
demand and who look for long-term price appreciation. A recent study of fringe area
land owners found tfiat as much as 50'% of the improved suburban and rural fringe
land was held by the current owner for 8 years or more (Brown, Phillips and Roberts,
1981), and it was also estimated that only one quarter to half of the owners were
interested in selling their land at any one time (Brown et al., 1981; Real Estate Re-
search, Inc., 1982). The carrying costs for raw land are modest as there are usually
few improvements. Taxes also tend to be modest Such owners don't have to sell to
survive.
3 Thus while the price of improved lots is especially sensitive to national economic
conditions, the price of raw land may be less so. As others have suggested, it appears
that the price of land, especially that of raw land, may follow a ratchet pattern of
moving upward but seldom downward since few parcels 2re subject to forced sales.
Beyond these two explanations, there is the possibility that the imposition of
restrictions on the raw land that may be developed can produce conditions of narrow
or quasi -monopoly control of available raw land Only a relatively small proportion of
raw land is available for sale at any given time, as noted above. if this pool isfurther
diminished through growth controls, the number of*remaining possible sellers may be
reduced enough to grant them significant marker power.
We do not know whether such additional concentration of market power was
3 occurring between 1975 and 1980. Analysis of the types of growth controls imposed
in specific areas and the course of raw land prices in dree areas might provide some
evidence. These remain importantquestions for further research.
CONCLUSION
In many market areas, land for building i s becoming an ever larger cost in housing
and other development when there is no general land shortage. if any one point stands
out from, the findings of this research,' it isthat policy makersshould pay moreatten-
tior.to }and cost''as a component of housing, shopping center, industrial park, and
'office costs;;
We monitor` em ployment levels, money supplies, and interest rates nationally. The
U.S. Department of Agriculture monitors farm and ranch land prices and quantities.
But no one systematically monitors urban land prices, much less the factors which
might explain urban land market behavior.
Policy makers should know the prices for representative parcels and know more
about how public decisions on zoning, the construction cE a sewer tine or mad, an
employment expansion, or adoption cf growth limits can affect the development
market Current trends suggest that the supply aE improved land for building has
diminished considerably because of curtailed infrastructure investments, more regu-
lations, and widespread enactment of agricultural land preservation programs. The
increased costs in some localities are maskedby permitted increases in residential den-
U\NOpn>Ce|mFLAT0m
43
-~`0-_g-_='housing
�
Without beftit knowled of
ge
Jim be be h
i 'ex 'ch e�ffiainte
eal es
�.��,-nanc�-bt-h'ealthy.,comi�dtitive� an mar is red relit6dJ9
NOTES
`Txb article is based upon the findings wfuresearch project jvindvsupported ur the Urban
Land/nmioute (uU) andthoV'S. DoportmontofHousing and Urban Development <*VD>Office
of Policy Development and noaoomh. Thomas Black iothe VLIStaff Vice PmaidontforResearch
and )ume* I- Hoovn is the MVo Chief ofCommunity Planning and Design Research. Frank
Donau, Jay Miller, and Thomas Richardson assisted with the analyses while serving as interns at
uL| and HUD. Tbcviowaand conclusions expressed inthe article are those ofthe authors and not
necessarily those oftheir au*^cim
7 The survey method was first suggested b y Professor J amcs; Brown of the Department of City
and Regional Planning otHarvard University.
'Ono cfthe sample areas, 8ou|do,. Colorado, was notmmetropolitan statistical area atthe time
ofthe survey.
"Twelve areas womaumoyodbm 1900amd lV in 1981.
44 BLACK AND HOSEN
APPENDIX
Land Price Estimates
The !and price data for the 30 metropolitan areas were obtained by requesting rea!
estate experts in each area to estimate the price for prescribed standard parcels in ,heir
area.
Standard parcels were defined tD minimize qualitative and quantitative differences
among properties and to permit comparisons across regions. Two standard parcels
were specified: (1) an improved single family tot, and- (2) raw acreage suitable for
single family development; The survey instrument with a description of each standard
parcel is reproduced below.
URBAN LAND INSTITUTE RESIDENTIAL LAND PRICE SURVEY
Insirurtions
We are requesting your best estimates of typical prices for improved single family
lots and raw single family acreage as described below. Your answers need not reveal
anything about your own business dealings.
Please record two prices for each of the two types of property. The first should be a
recent estimate based on 197980 transactions. The second should reflect the price
of a comparable piece of property in 1975. The latter can be based on either an
actual transaction or a published average. If information is not readily available for
1975, feel free to substitute another year between 1970 and 1975, but be sure to
note that year in the space provided.
It is very imporunt that your estimates refer to residential land which reasonably
meets the stated criteria for size, location, and other characteristics Estimates based
on land which significantly deviates from the standardized characteristics described
belowwIll reduce the accuracy of the survey results. Do not feel obligated to provide
all four estimates if you do notfeel qualified to d oso.
The attached form is provided for your answers.
PROPERTY TYPE ONE: Improved Single Family Residential Lot
Character/st/u
Size: approximately 10,000 square feet (:1000)
Zoning: single family detached
Location:
suburban fringe
within 15-20 minutes driving time of a major employment center (not
necessarily the central business district)
' within 2 miles of an existing grade school or bus zone
Development Rights : No restrictions other than toning and building require-
ments
Utilities to Lot: sewer, water, electricity, telephone
Neighborhood :
nota prestige ::rea (homeprices within $60,000 to $90,000 range)
. area at least 50% developed
• no unusual conditions which might impact the land price such as:
a significant pollution (air, water, noise)
o environmental hazards (floods, etc.)
LAND PRICE INFLATION 45
o close proximity to amenities such as major parks or shopping areas
Financing: The price should reflect normal financing terms for your area.
PROPERTY TYPE TWO: Unimproved Acreage Suitable for Single Family Resi-
dential Use
Charocterlstics
Size: 20-100 acres
Zoning: Residential, suitable forsingtesamily detached development
Location:
- developing fringe area
- within 15-20 minutes cE a major employment center (not necessarily
the central business district)
Development Rights: No restrictions other than zoning, subdivision and build-
ing requirements
Utilities to Property: Connections to network available at negligible cost
Other Characteristics:
- nota prestigearea (home priceswithin $60,000 to $90,000 range)
- no unusual physics! attributes such as slope or soil conditions which
would increase the cost of development
- no unusual environmental conditions, e.g. significant pollution or
hazards
- no unusual amenities such as extremely close proximity to a major
shopping or a recreational area
Financing: The price should reflect normal financing terms for your area.
Approximately 25 to 40 real estate experts in each area were identified from refer-
rals and professional membership lists. They included land developers, builders, pri-
vate appraisers, public assessors, and lenders. The experts were mailed the price survey
and asked to estimate prices for 1975 and 1980. The average response rate from each
region was 10 or about 35% with a high of 16 and low of A In general, individual
price estimates for an area were consistent However, to minimize the distortion of
unusually high or low price estimates, the median price estimate was selected as the
representative price for a standard parcel. No actual sales were analyzed as part of the
price survey cr for validation purposes.
Analysis oMice Variations
The 1975-1980 land prices were analyzed by regressing them against a number of
factors which might approximate land supply and demand forces in each SMA. A
stepwise multiple -regression program was used from the Statistical Package for Social
Sciences (SPSS). The selection of factors was limited to readily. available SMA data,
except in two cases where f?ctors were developed by the researchers. The independent
factors analyzed were:
A. Supply Factors
o Physical restriction rating, 1980. (U Ll research staff estimate—see article for ex-
planation.)
C
Is
46 BLACK AND HOBEN
0 1980 regulatory restriction rating, 1980. (ULI survey—see article for explana-
tion.)
o Single family building permits per 1,000 population, 19751980. (U.S. Bureau
of Census)
o Ratio of employment income increase to issued singie family building permits,
1975-1980. (U.S. Bureau of Labor and Census)
o Ratio of new to existing home loans, 1975-1980. (U.S. Federal Home Loan
Bank Board)
B. Demand Factors
o Population, 1980. (U.S. Bureau of Census)
o Percentage increase in population, 1975-1980. (U.S. Bureau of Census)
o Employment, percentage increase in 1975-1980. (U.S. Bureau of Labor)
o Income per -capita, 1979. (U.S. Bureaucf Economic Analysis)
o Percentage increase in per -capital income, 19751979. (U.S. Bureau of Eco-
nom*.c Analysis)
C Baseline Factors
0 1975 improved lot price. (ULI Survey)
0 1975 raw land price. (ULI Survey)
o Median new single family home price, 1980. (US .Federal Home Loan Bank
Board)
LITERATURE CITED
Barnard, C and Botcher, VIS 1981, Landowner characteristics as determinants of
developerlocational decislons� Paper presented at AAEA meeting, Clemson, SD
Beaton, Q R., 1982, A n Examination of Relationships Between Land Use Planning and
Housing Costs in Oregon, 1970-1980: Focus on the Urban Growth Boundary.
Salem, CR: Willamette University.
Black, T. and Hoben, j., editors, 1980, Urban Land Markets: Price Indices Supply
Measures, and Public Policy Effects. Washington, DC: The Urban Land Institute.
Brown, J., Phillips, R. and Roberts, N, 1981, Land marketsat the urbanfringe—new
insights for policymakers. Journal of the American Planning Association, Vol. 47,
No. 2 131.144.
Coughlin, R., Klein, T. and William, M., 1983, Changes in patterns of land ownership
in use during the early stages of urban development: a case study analysis. Re-
search Report series. Philadelphia, PA: University of Pennsylvania.
Hoben, J., 1981, Monitoring land prices in the United States. WoridCongmss on Land
Policy 1980. Cambridge, MA: Lexington Press.
Landis, J.D., 1984, Land regulation, market structure and housing price inflation:
lessons from three California housing markets. Doctoral dissertation, University of
California, Berkeley Planning School.
LAND PRICE INFLATION 47
Peiser, R, 1981, Land development regulations: a case study of Dallas and Houston,
TX. journal of the American Real Estate and Urban Economics Association, Vol.
9, No. 4,397-417.
Real Estate Research Corporation, 1982, Infill Development Strategies. Chicago, 1L:
American Planning Association. "
Segal, D. and Srinivasan, P., 1980, The impact of suburban growth restrictions on US
housing price inflation 1975-1978. Unpublished paper for the National Science
Foundation.
Land -Use Controls and Housing Costs:
An Examination of San Francisco
Bay Area Communities*
David E Dowall ** and John D. Landis***
3
This paper reports on our efforts to gauge the effects of Iand use
controls OR housing markets, We discuss how land use controls affect
land and housing assts and explain why communities use such con-
tmis to restrict development. We present the results of an econometric
model created to assess the inflationary effects of land use controls on
housing costs. The model is based on data assembled in the San Fran-
cisco Bay Area. The model results indicate that density controls and
land availability do systematically affect the price of new housing units.
INITRODUMON
Confronted with continuing increases in the cost of new housing, city planners
and urban economistsnow find themselves re-examining the validity of local land
use and development controls. In California, the controversy over land LM con-
trols has raged for some five years, sparked to no small extent by housing prices
Financial support for this paper came from the California Department of Real Estate,
the California Air Resources Board and the Construction Industry Advancement Fund.
Associate Professor of City and Regional Planning, Center for Real Estate and Urban
Economics and Institute of Urban and Regional Devebprnent, University ofiCf�+a,
Berkeley, California, 94720.
*** Department of City and Regional Planning, University of California, Berkeley, Cali-
fornia, 94720.
67
rvt111ial l Vol. I
which remain the nation's highest. In his widely -quoted 1979 work, The Environ-
mental Protection Hustle, Bernard Frieden [1 ] concludes that in the case of the
San Francisco Bay Area, unnecessary growth controls are adding thousands of
doLars to the cost of constructing new housing. Perhaps a more important effect,
Frieden notes, is that by constricting supply in the face of burgeoning demand,
local land use controls fuel the flames of housing inflation. Moreover, those
responsible for such restrictive controls often act entirely out of self-interest, for
as the price of new housing rises, so too do the prices of existing housing—in the
process providing existing landowners with windfall profits. Similar conclusions
-' have been voiced by Gruen and Gruen Associates 121 :n a study of the appli-
cation of growth controls in Petaluma, California, and more recently, by Dowall
(31 in a study of land use controls as administered in six representative Bay Area
suburban communities.
Academics and consultants, however, are not the only observers to express
alarm at the current situation; the State of California has also voiced concern. A
recent survey of local land use planning in California, undertaken by the Gover-
nor's Office of Planning and Research [41, revealed that over 5017o of the 93
cities in the San Francisco Bay Area were actively limiting population growth.
To reduce excessive project approval times, the California Legislature in 1977
enacted AB 884, a bill requiring local governments to approve (or reject) major
residential projects within one year of the initial submission date. But, because
of a variety of loopholes, AB 884 has not been effectively enforced.' Most re-
,� cently, in an attempt to break the housing supply deadlock, Sacramento legis-
lators have moved to require that individual communities accept their "fair
share" of new housing supply, and identify and remove local roadblocks to new
construction.Z
Despite the flurry of legislative activity to promote housing construction and
facilitate the availability of affordable housing, little effort has been made to
assess the cost and price -push effects oz local land use controls on housing. The
barriers to such a complete assessment are substantial and center on the lack of '
good quality land supply and price data, difficulties in delineating meaningful
housing submarkets, and separating demand side forces from supply side con- ,
straints. This paper reports on our efforts to overcome these barriers and provide
some further insights into the relationship between local land use controls and
the operation of urban housing markets. The study region is the nine -county San
Francisco Bay Area—a metropolitan area containing over 100 independent units
of local government with widely divergent approaches to controlling development. t
The second part of this paper presents a simple typology for understanding
and organizing the effects of land use/development controls on housing markets,
and within such a context, provides a further review of recent empirical work.
Part three provides soine additional insights into the various rationales behind the
adoption of land use controls, and reasons why the Bay Area's housing supply
i
i
19821 Land Use Controls and Housing Costs [ 69 f
i
crunch has now reached crisis proportions. Part four presents the results of our
empirical analysis of the effects of land use and development controls on new
housing prices.
i
THE DIRECT AND INDIRECT EFFECTS OF DEVELOPMENT !
CONTROLS ON HOUSING PRICES -
California cities and counties have a variety of tecluliques at their disposal for
regulating the type, quality, and timing of new development. In addition to such
traditional controls as zoning and subdivision restriction, cities may:
establish urban limit lines, or borders beyond which new development will
not be allowed to occur—effectively setting vacant land supplies.
routinely bargain with builders to reduce densities and mitigate negative
environmental impacts.
use slope-based/zoning, a technique for reducing hillside development den-
sities.
together with willing farmland owners, establish 20 -year agricultural pre-
serves.
levy development fees and charges to pay for the construction of needed
on-site infrastructure (sewer and water ones), and also to subsidize the
purchase of parkland and the maintenance of local schools.
Lm growth management programs to airectly limit developmsnt.
To summarize the range of effects of land use and development controls on
new housing prices, we have identified four direct and two indirect sous of ef-
fects. Presented in Exhibit 1, these effects are best considered generic; that is,
their relative impact on housing prices will depend largely on the level and char-
acter of housing demand, the proximity of regulated communities to other juris-
dictions, and the cummulative degree of restrictiveness generated by local land
use policies.
Direct Effects
The most common way in which land use and development restrictions af-
fect housing prices is by directly increasing builder costs—increases which under
most circumstances are passed on to homebuyers in the form of higher prices.
701 AREUEA Journal [ Vol. 10
EXHIBIT 1
DIRECT AND INDIRECT EFFECTS OF ENVIRONMENTAL CONTROLS
ON HOUSING COSTS
Effect on Housing Costs
Land -Use Controls Most Likely to Generate Effect
Direct Effects:
Increase in Land costs
Zoning, urban limit lines, density constraints, growth -
management timing ordinances and permit programs
Increase in lot•prepara-
Subdivision requirements, growth -management timing
tion costs
ordinances, dedication requirements
Shifting development
Capital -budgeting programs, fees and development
costs from public to
charges, dedication requirement subdivision require -
project
ments
Administrative and
All land -use controls to some extent. Costs increase with
delay costs
the relative complexity of the regulation
Indirect Effects:
Facilitating monopoly
Controls that restrict the number of developers operat-
power
Ing in communities will allow builders to charge excess
housing prices. Regulations act as barriers to market
entry, reducing competition in the housing market
Market Reorientation
Restrictions on devetopment often force developers to
reorient their projects to higher -income customers
Reducing supplies of vacant land, or restricting the permissible intensity of
residential development can substantially affect land costs. As Ohls, Weisberg
and White [5J have illustrated, zcning regulations which restrict vacant land sup-
plies below the levels which would normally be exchanged in the market tend to
increase land costs. Stull [6) has shown that communities adopting policies
which shift land away from residential uses and toward employment -generating
uses can expect residential land prices to increase as employment growth accele-
rates the demand for housing.
Unfortunately, direct empirical estimates of the inflationary effects of zoning
on housing prices are not widely available. Accordingly, Davies [7] has used a
simulation model of the London, Ontario area to examine how municipal actions
increasing the supply of developable lots would affect housing costs. For 1967,
Davies tested an increase in the supply of lots equivalent to 50 units, or about
11%. The simulation results suggested a corresponding lot price reduction of
about $200 per lot (4.5%). A second simulation experiment for 1973 revealed
that the same absolute increase in land supply (250lots) would generate a $244 -
per -lot decrease in price (3.4%). But although the effect on lot prices is signifi-
cant in both cases, the effect on house prices is less than 1%.
ibir g housing price and land use data for suburban Boston communities,
Stull [8) tested the relationship between land use controls and housing prices.
)82 ] Land Use Controls and Housing Costs [ 71
fter controlling for accessibility, housing stock characteristics and the quality
public services, Stull found that housing prices were lower in communities
ith greater proportions of vacant land.
In addition to reducing the supply of residentially developable land, zoning
:ts to restrict development intensity. While large -lot zoning, on the one hand,
•nds to reduce the per -acre price of raw land, such reductions in price may be
ffset by higher land requirements. Interpolating from Peterson's empirically
etermined land -price gradients for Fairfax County, [9] Virginia, illustrates the
otential cost effect of large -lot zoning. At a distance of ten miles from the ur-
an center, Peterson found that large parcels zoned 1h, 1, 2 and 10units per acre
,ere selling for $5,800,$7,900, $13,700 and $32,000per acre, respectively. Con-
erting these acre prices to per -lot values, the prices implied by the %, 1, 2 and
0 units per acre zoning are $11,600,$7,900, $6,850 and $3,200, respectively.
A second type of direct cost effect of development controls is the increase in
he cost of lot preparation and home construction. Numerous estimates of the
)rice effects of subdivision and building code requirements are available, some
)etter than others. In a 1976 study of Jacksonville, Florida, the Urban Land
nstitute [ l 0] found that locally mandated changes in water system design and
street width requirements added $830 to the cost of producing a "finished" lot
1976 dollars). In an earlier study for the Kaiser Commission, Burns and Mittel-
)ach [ 11] estimated the inflationary impacts of excessive subdivision and zoning
-equirements at 2 to 4% of the price of new housing. While it is difficult to differ-
-ntiate between necessary and excessive requirements, available evidence sug-
gests that some cost reductions might be attainable by reducing subdivision
standards. Short-term cost reductions are unlikely in the case of building codes,
however, as most builders have fully integrated building code requirements into
their production technologies.3
A third direct cost effect of development regulation is generated when local
governments attempt to shift the public service costs to new development back to
private builders. Traditionally, municipal governments have shouldered the pub-
lic service costs of new construction. Recently, however, an increasing number
of communities have begun to impose additional fees, taxes and land dedication
requirements on project developers. This trend was particularly noticeable in
California following the 1978 passage of Proposition 13, which limits home-
owner property tax payments to 1% of assessed value. A recent survey of Bay
Area communities (I2] revealed substantial increases in development fees and
taxes following Proposition 13. For example, in 1976, prior to the passage of
Proposition 13, development, utility and impact fees averaged $ l 121 for the
standard single-family home. By 1979, mean fee levels, in nominal terms, had
risen to $ 1907, an increase of 70%. After discounting for inflation, fees rose by
some 35%. As in the case of subdivision requirements it is difficult to determine
when fees and charges are excessive. Charges that reflect the actual costs of
providing public services to new development are reasonable, equitable and
j uurnai i Vol. 10
desirable. However, in some instances, cost -shifting appears excessive—when
revenues are used to provide services that benefit the general community.
The fourth direct effect of development regulation results from adminis-
trative delays associated with regulatory compliance. With the widespread use
of fiscal and environmental assessments, particularly in California, the time re-
quired to obtain development approval has increased tremendously over the
past decade. A national survey [ 13] of the time Isngth of the development ap-
proval process found that in 1970, 72% of the developers interviewed obtained
project approval in seven months or less. 97% obtained approval in on year or
-1 less. By 1975, only 15%of the survey respondents had obtained permits in less
than Seven months, and only 42% obtained development approval in one year or
less. To be sure, the blame for such delay rests as much with builders who pre-
pare improper submissions, as with overzealous reviewers. Regardless of fault,
however, delays in the development review process generate economic costs -
7) costs generally borne by consumers. Delays result in increased land -holding and
overhead costs, development loan interest costs, exposure to inflation and op-
portunity costs of tying up capital. In a 1978 Rice University study of Houston
area builders, [ 14] the overall costs of approval delays were estimated to add
between $388 and $596 to the per unit cost of new housing. In California,
delays associated with California Environmental Quality Act compliance were
estimated to add between 4 and 7% to the selling price of new units (1974)
[15] .
IndirectEffects
In addition to the direct cost effects of land use regulations, community con-
trol over residential development often confers significant monopoly power on
developers and alters marketing and pricing decisi=. Monopoly power allcm
builders to charge excess prices for housing and increased production costs may
force developers to reorient residential projects to high-income markets.
Regulation establishes monopoly power in a variety of ways. By restricting
developable land supplies, the potential for market entry and the possibility of
increased competition are reduced. Studying the Edmonton, Canada, housing
market, Cook f 16] found substantial concentration among developers operating
in the city's six restricted development areas, with the four largest builders
supplying 64$ of the single-family lots produced between September 1973 and
August 1976. A closer inspection of the six citydesignated development areas
indicates that each is controlled by one developer.
Land use regulations which rely on complex administrative procedures act as
barriers to market entry. If the level of complexity is great, potential developers
may be reluctant to enter a local market, particularly if they perceive that tbose
builders who have already established good working relationships with local
planners arc more likely to obtain development permission. A study of two San
J
19821 Land Use Controls and Housing Costs [ ?3
Jose, California builders [ 17] found that between 1967 and 1976, after holding
land and materials cost increases constant, and discounting for mandated in-
creases in housing quality, the two builders had increased their profit margins
by between 15 8 and 231 % (constant 1976 dollars). The researchers concluded
that such excess profits were partly the result of reduced competition.
The second type of indirect effect of land use regulation is the reorientation
of residential projects. The previous discussion of monopoly suggeststhat devel-
opers may increase prices to merely match cost increases. However, there is an-
other reason for rising prices. Often, builders find that project marketability
declines as prices rise. By changing the product only slightly, many builders are
able to reorient their projects toward higher -income consumers, a reorientation
which increases profits. Development restrictions which limit residential den-
sities and increase production costs often force builders to scrap plans for high-
volume, affordable housing in favor of a more limited number of higher -priced
units [18].
THE BAY AREA PERSPECTIVE
The production cost side is only half the development control story. The other
half, as noted above, concerns the interplay of supply and demand; whether in
the face of rising housing demand, development controls restrict the aggregate
supply response, and in doing so, push housing prices upward. Although such a
market dynamic is difficult to verify empirically (in part because of the afore-
mentioned problems with identifying submarkets and pure -demand side effects),
with respect to the San Francisco Bay Area, there is substantial evidence that
such supply constraints are in fact contributing to the continuing chnib of new
and existing housing prices.
In 1978, the San Francisco Bay Area edged Washington, D.C. for the dubious
distinction of having the highest housing prices of any metropolis in the United
States. In 1981, the median sales price of a new home in the Bay Area stood at
$1 14,000—a figure more than $30,000 above the national average, and repre-
senting a 269% increase over a ten-year period. [19] At the Same time that
prices have been rising, vacancy rates have been falling. According to a recent
estimaie from the Association of Bay Area Governments, in 1981, the average
Bay Area vacancy rate stands at roughly 2%—down from the 5% vacancy rate
of only five years k.;o. [201
What combination of market factors explains these trends? Like many grow-
ing metropolitan regions, the Bay Area has faced considerable demand pressure
from growiryg households and industries. The so-called baby boom generation
has now reached prime house -buying age. Changing cultural and social values
}lave dramatically increased the formation of households as more individuals
seek separate residences. Employment growth and increased immigration to
California and the Bay Area have further accelerated household growth. The
demand for housing is strong in the Bay Area, but it only partially explains
rapid housing price inflation and high prices. The other key ingredient is insuf-
ficient supply.
Unlike other high growth Sunbelt regions, the Bay Area is, relatively speaking,
in short supply of developable land. Extensive land development since World
War II, the increasing use of growth management controls, more restrictive land
use and environmental regulations, and the "go-slow" development posture
created by the passage of Propositions 4 and 13 have significantly affected land
conversion in the region. Despite the existence of what in absolute terms is an
enormous supply of vacant land, much of this total cannot be developed because
of rugged topography or enviromental fragility. Other vacant lands that could be
developed are restricted from um by local land use controls. A 1975 inventory
of land gee recorded that of the region's 4.5 million acres, only 350,000 acres
were vacant and "developable." [21 ] If only the acreage zoned for residential
development and likely to be serviced is considered, the total shrinks to 161,800
acres, a number which at prevailing densities (8.7 units per acre), would accomo-
date some 1.4 million additional housing units. But unfortunately, as ABAG
points out, residential densities are falling, and rather rapidly. If present land
conversion trends continue, the projected 1990 regional housing demand will
not be accomodated— there simply will not be enough land for residential devel-
opment. [221
Are such trends truly worrisome? After all, as vacant land supplies diminish,
land prices can be expected to rise, signaling to developers and planners that land
: use intensities must also rise. Unfortunately, there now appear to be substantial
and permanent forces within the San Francisco Bay Area which will prevent a
move to higher housing densities. Among these forces:
The Rise of Local Growth Controls: The pro -growth attitude of most Bay
Area communities in past decades has been replaced by a slow -growth
posture, brought on by rising fiscal worries generated by Proposition 13.
Cities that once relished being regional growth centers now view growth
with much skepticism. With the new fiscal calculus of Proposition 13,
single-family development usually generates higher public sector costs
th-�n revenues." 2ns fact, in conjunction with a greater recognition of the
environmental impacts of development, has led some communities to
reduce the amount of land available for residential development. Coupled
with the lack of developable land in older Bay Area cities, development
opportunities are becoming scarce, and some builders are leapfrogging out
to exurban agricultural areas.
lobs, But Ab Housing: Another result of Proposition 13 has been that
numerous communutes have altered their approach to land um pianning
and zoning. Caught in a fiscal squeeze, many towns have stepped up efforts
V
19821 Land Use Controls and Housing Costs f 75
4 to increase their tax base by attracting more commercial, office and light
industrial development. But while attempting to attract economic develop-
ment, most communities have not concomitantly adjusted their zoning to
provide housing for additional employees. As a result, new employees,
particularly those just migrating into the region, may find it increasingly
difficult to purchase their own homes, even assuming that currently high
mortgage interest rates abate somewhat.
Increased Development Fees and Charges. In addition to limiting devel-
opment of fiscally "unprofitable" housing, most Bay Area communities
have dramatically increased the fees and charges they levy an developers.
A recent ABAG study found that total development fees for single-family
homes range from $800 to nearly $6,000 per unit. [23) Crucially, the
ABAG study reveals that the twenty-two communities charging the high-
est fees (ranging from $3,000 to $6,000) are all located in the developing
suburban reaches of the Bay Area—communities, which not coincidentally,
boast some of the region's more affordable housing.
How have these various factors affected housing supply? Exhibit 2 shows that
region -wide, new housing production dropped from 46,235 units in 1977, to
38,472 units in 1978, to 33,763 units in 1979. In contrast to the Bay Area ex-
perience, statewide housing starts in 1978and 1979were well above 1976levels.
What is perhaps more alarming than the decline in regional housing starts is the
fact that the greatest absolute 1977-1979 declines occurred in the three counties
--Contra Costa, Santa Clara, and Sonoma—which together contain the majority
of the region's developable land supply.
Falling residential densities, growth controls, job growth at the expense of
housing development, and the "obstructionist" attitudes of citizens and com-
munities toward new development—all of these factors are acting to reduce the
supply of vacant land available to housing development. How are these trends
likely to affect housing costs? Economic theory suggests that if the current reg-
ime of local land use and development control policies remains unchanged, land
and housing prices alike will continue in an upward spiral, placing extreme bur-
dens on low and moderate -income households and ultimately slowing the
region's economic growth rate. Higher land and housing costs may also act to
push up wage rates, as workers struggle to pay higher housing costs. Carried to
their logical extreme, higher land and wage costs may reduce the Bay Area's
attractiveness to business and industry. Such concerns, which may seam exces-
sively "long run" to economists, are nonetheless very real to Bay Area civic and
business leaders.
88 ] AREUEA Journal [ Vol. 10
CONCLUDING COMMENTS
While it is widely agreed that land use regulations contribute to housing
price inflation, little supporting empirical evidence is available. Although tenta-
tive, the results of this paper illustrate that density controls and land availability
do systematically affect the price of new housing units. However, our research
also indicates that the direct cost effects are not as great as some critics of land
use controls allege. For example, according to econometic estimates of new
housing prices, the combined effect of increasing development densities by one
unit per acre, reducing development fees by 50%, and doubling supplies of va-
cant land—all drastic steps—would be to lower the sales price of a new home by
$6,000. This estimate amounts to roughly 6% of the average price of a new Bay
Area home in 1979. New homes prices in growing suburban communities are less
sensitive to limits on development densities and vacant land supplies and slightly
more sensitive to increasing development fees. Our results also support the con-
tentions of suburban builders who report that planning and development fees
are added to the price of new housing on a one-to-one basis. In other words, for
every one dollar increase in fees, the list price of a new home increases by one
dollar. However, we note that land costs are more important to builders, and ac-
cordingly, density limits become critically important in determining project
selling prices and profit. To the extent that builders can distribute higher land
costs, as well as infrastructure costs, over a greater number of constructed units,
higher single-family housing densities are crucial for holding down selling prices
while maintaining profit levels,
The importance of the suburban housing market in acting as a relief valve
for Bay Area housing demand is implied by Exhibit 5. Although changes in sup-
ply do not greatly affect housing prices in the region as a whole, the flow Cf new
units onto the market is a major determinant of housing prices in expanding
suburban markets. For example, a 500 -unit increase in the flow of new homes
into a suburban market would imply a decline in all suburban home prices of
nearly $6,000. Thus policies which greatly restrict new construction and/or den-
sities in active suburban communities are found to be inflationary. A logical
extension of this finding is that if local governments in the San Francisco Bay
Area are committed to reducing housing costs, they should consider loosening
density restriction or other controls which inhibit the flow of new housing onto
the market.
It is important to be careful in drawing rigorous conclusions from the results
of partially specified econometric models, particularly when the observation set
consists of city averages instead of well-defined economic agents. And because
the significance levels of the estimated development policy coefficients vary de-
pending on how the models are specified, the link between development controls
and higher home prices must still be regarded as unproven. Nonetheiess, the
results presented here are surprising for their consistency, and their agreement
19821 Land Use Controls and Housing Costs [ 89
with expectations. They suggest that the housing price effects of pursuing re-
strictive growth.control policies in expanding urban areas, far from being smU
and localized, are significant and widespread.
NOTES
1. Frequently, communities circumvent the intent of AB 884 by requiring builders to
sign a waiver exempting the city from complying with AB 884.
2. Senate BLU (SB) 2853, was enacted by the legislature in 1980. It mandates that re-
gional councils of government (COGS) allocate new housing construction to cities on the
basis of projected growth and land availability. Initial allocations for the San Francisco Bay
Area were to be published during the summer of 1981.
3. According to a recent survey by the National Association of Homebuilders, [ 37]
when asked to list major construction problems, responding homebuilders listed building
codes eighth—well behind increased labor, materials and land costs. Moreover, only 1.31/6 of
those responding listed building codes as their "most Significant" construction -related
problem.
4. Whether or not new residential construction does or does not "pay its own way" will
depend on a number of factors, including the existence of excess capacity in public services,
the level of demand for such services by new residents and prevailing tax rates. In California,
where Proposition 13 limits yearly property tax payments to 1% of assessed value, muni-
cipalities continue to experience substantial revenue si=Lf0s. In the San Francisco Bay
Area, Proposition 13 has led numerous communities to examine the net fiscal costs of new
development through the use of C RIS (Cost -Revenue Impact Study), a municipal finance
model developed by the Association of Bay Area Governments. In most of the cities in
which CRIS has beenused, new single-family development was found to generate insufficient
tax revenues to cover the accompanying increase in public service costs.
5. The extent to which households trade between access to employment and land and
housing prices is the basis of much of contemporary urban economics. For the basic excep-
tion, see Edwin S. MMs [33).
6. This argument, first offered by Tiebout (1956). is best presented in Wallace Oates
[36).
7. Data were provided by Professor Kenneth Rosen, Director of the Center for Real
Estate and Urban Economics, University of California, Berkeley.
8. The use of time -series dummy variables is not without drawback. Although we argue
that the variation in new home prices attributable to increasingly stringent (across time)
land use controls is far less than the price variation attributable to cross -community land
policy differences, the time -series effect is not insignificant. By using single -time dummy
variables (and thus lumping together the time -series variance cf all the independent varia-
bles), we sacrifice the ability to identify precisely these time -series effccts and bias the re-
sulting yearly price indices.
An alternate method for estimating time -series hedonic price indices, one which parti-
ally obviates the problem of time -series dummy variables, has been suggested by Grtiiches
( 381, and more recently by Palmquist [391. In the present case, the technique consists of-
Estimating
£
Estimating the New Housing Price Model for each sample year (1977, 1978, 1979) in
both linear and logarithmic form.
Inserting the mean values of the independent variables for the base year ( 19 7 7) into
the separate equations estimated frr 1978 and 1979.
E
W,
J
901 AREUEA Journal [ Vol. 10
Comparing the estimated values of the dependent variable (NPRICE) for 1978 and
1979 to the base year 1977. The resulting ratios are quality -controlled tithe -series
indices.
In the table below, the indices derived using the Griliehes/Palmquist technique are com-
pared with the hedonic indices derived through the use of time -series dummy variables.
In neither the linear case cr the logarithmic case does the Gri'liches/Palmquist index seem
reliable. We offer two reasons for the discrepancy. First, the observationsare not individual
home transactions (as Palmquist suggests is appropriate), but instead are city-wide averages.
Second, the estimated coefficients vary widely when separate year models are attempted,
in part because we lack a sufficient number of yearly observations.
Year
Time -Series
Quality -Controlled
Dummy Variable
Hedonic Index
Linear Log
Linear' Log
1977
1.00 1.00
1.00 1.00
1978
1.116 1.26
1.33 1.98
1979
1.28 1.38
1.31 1.19
REFERENCES
(11 Bernard Frieden, The Environmental Protection Hustle (Cambridge, MA: MIT Press,
1979).
[2) Claude Gruen, "The Economics of Petaluma: Unconstitutional Regional Socio -
Economic Impacts," in R. Scott, ed., The Management and Control of Growth,
Vol. II (Washington, D.C.: The Urban Land Institute, 1975), pp. 173-186.
131 David Dowall, The Suburban Squeeze: An Examination of Suburban Land t:om,er.
cion and Faqulaticn in the San Francisco Bay Area. Draft (Institute for Udm
and Regional Development, 1981).
(4) Office of Planning and Research, Local Government Planning Summary: 1975 (Sac-
xamento, CA: State Office of Planning and Research. 1975).
151 James Ohls, Richard Weisberg and Michelle White, "The Effects of Zoning on Land
Value," Journal of Urban Economics, 1(1974): 428-444.
[6) Wiliam J. Stull, "Land Use and Zoning in an Urban Economy," American Economic
Review, 64 (1974): 337-347.
[7) Gordon Davies, "A Model of the Urban Residential Land and Housing Markets,"
Canadian Journal ofEconomics, 10(1977) : 393-410.
f 8 William J. Stull, "Community Environment, Zoning and the Value of Sitgle Family
Homes," Journal ofLaw and Economics, 18 (1975): S3S-SS7.
(9) (barge Peterson, "Land Prices and Factor Substitution in the Metropolitan Housing
Market." Working Paper No. 0875-02-01 Washington, D.C.: The Urban Institute,
1974).
(10) The Urban Land Institute, "Effects of Regulation on Housing Costs: Two Case Stu-
dies." UM Research Report No. 27 (Washington, D.C., 1977).
(11) Leland S. Burns and Frank Mittelbach, "Efficiency in the Housing Industry," in Re-
port cf the President's Committee on Urban Housing,A Decent Home, Vol. Il
(Washington, D.C.: U.S. Government Printing Office, 1968),p. 133.
[12) Stuart Gabriel, Jennifer Watch and Lawrence Kau, "Land use Regulation and R -
position 13," IBER Working Paper No. 84.4 (Berkeley, CA: University of Cali-
fornia —Berkeley
ali.fornia—Berkeley,1980).
1982 J Land Use Controls and Housing Casts 1 9 1
[131 Srephen Seidel, Housing Costs and Government Regalatim (New Brunswick, NJ:
Center for Urban Policy Research, L978).
1141 Rice Center for Community Design and Research, The Delay Costs of Government
Regulation in the Houston Housing Market (Houston, TX: Rice Center, 1M).
1151 Environmental Analysis Systems, Inc., "The California Environmental Quality Act,"
prepared for the State Assembly Committee on Local Government, 1975.
[161 Richard Cook, "Lot Prices and the Land Development Industry in Edmonton, Can-
ada" (Berkeley, GA: Department of City and Regional Planning, University of
California—Berkeley, 1977)_
117] The Urban Land Institute, Effects ofRegulation on Housing Costs, op. cit.
1181 Bernard Frieden, The Environmental Protection Hustle, op. cit.
1191 Real Estate Research Council of Northern lif=da,Northern California Real Estate
Report (San Francisco, CA: 1980) .
(201Association of Bay Area Governments, 1981.
1211 Association of Bay Area Govetnments, Summary Report: Provisional Series 3 Projec-
tions (Berkeley, CA: ABAG. 1977) .
1221 Theresa Hughes and Associates, from ABAG, San Francisco Bay Area HousingActi-
vity Report, No. 2, 1980.
(231 Association of Bay Area Governments, Development Fees in the San Francisco Bay
Area: A Survey (Berkeley, CA: ABAG, 1980) .
[241 Ronald Lafferty and H. E. Frech, "Community Environment and the Market Values
of Single Family Homes: The Effect of the Dispersion of Land Uses,"Journal of
Law and Economics, 21 (L978): 381-394-
1251 Stull, op. cit.
1261' Frederick Reuter, "Externalities in Urban Property Markets: Arl. Empirical. Test of the
Zoning Ordinance of Pittsburgh," .'ournal ofLaw and Economics, 16 (1973):
313-349.
1271 J. P. Crecine, 0. A. Davis and j. E. Jackson, "Urban Property Markets: Some Empiri-
cal Results and Their Implications for Municipal Zoning," Journal of Law and
Economics, 10 a 967) : 79-99.
1281 Association of Bay Area Governments, Local Land Poky Survey (Berkeley, CA: A -
BAG, 1977) .
[291 Ibid.
[301 Gabriel, op. cit.
[311 California Department of Finance, Yearl} CensusReports (Sacramento, CA: Depart-
ment of Finance, 1980).
(321 Ibid.
1331 Edwin S. Mills, Urban Economics (Chicago, IL: Scott Foresman, Inc., 1M).
[34) Metropolitan Transportation Commissin, "1978 Travel Demand Study" (Berkeley,
CA: MTC, 1M).
1351 Urban Decision Systems, "Updated Household Income" (Los Angeles, CA: Urban
Decision Systems, 1980).
[361 Wallace Oates, Fiscal Federalism (New York, NY. Harcourt, Brace and Jovanovich,
1972) .
[371 Michael Sumichrart, et al., Profile of the Builderand His Industry (Washington, D.C.;
National Association ofHomebuilders, 1979).
[381 Zvi Griliches, Price Indexes and Quality Change (Cambridge. MA: Harvard University
Press, 197 1.
(39) Raymon(' Palmquist, "Alternative Techniques for Developing Real Estate Price In-
dexes," Review of Econcadcsand Statistics, 62 (August 1980):442-448.
BIBLIOGRAPHY FOR FURTHER RESEARCH
Avrin, M. E. "Some economic effects of residential zoning in San
Francisco." In Residential Location and Urban Housing Markets,
edited by G. X, Ingram. Cambridge: Ballinger, 1977.
Babcock, R. F. and F. P. Bosselman. Exclusionary zoning: Land -use
regulation and housing in the 1970s. New York: Prager, 1973.
Bergman, E. M., et al. Internal validity of policy related research
on development controls and housing costs. Chapel Hill: Center
for Urban and Regional Studies, University of North Carolina,
August, 1974.
Bergman, E. M., et al. A Policy guide to evaluations of policy
related research on development controls and housing costs.
Chapel Hill: Center for Urban and Regional Studies, University
of North Carolina, August, 1974.
Bergman, E. M., et al. External validity of policy related research
on developnent controls and housing costs. Chapel Hill= Center
for Urban and Regional Studies, University of North Carolina,
August, 1974.
B.ickert, Browne, Cuddington & Associates. An analysis of the impact
of state and local government intervention on the home
,. building process in Colorado 1970-1975. Denver: Colorado
Association for Housing and building, April, 1976.
Brooks, M. E. HousS.ng equity and environmental protection: The
Needless conflict. Washington, D.C.: American Institute of
Planners, 1976.
Brooks, M. E. "Housing trust funds: Lessons from inclusionary
zoning." In Inclusionary zoning moves downtown, edited by D.
Merriam, D. 3. Brower and P. D. Tegeler, 7-22. Washington,
D.C. = Planners, 1985.
California Planning Roundtable. "'Welcometo California 1990s, jobs,
housing and transportation. ..the great balancing act."
Sacramento, California, October 1988.
Center for Real Estate and Urban Economics. "San Disgo County's
housing cap and growth debates," Quarterly Report. Berkeley:
University of California, 1968.
Chambers, D. N., and D. B. Diamond, Jr. "Regulation and land
prices." Unpublished manuscript, National Association of
Realtors and National Association of Homebuilders, June 1,
1988.
Dowall, D. E. "Reducing the costs effects of local land -use
controls." Journal of the American Planning Association (April
1981): 145-153.
Dowall, D. E. "Local -regional planning conflicts: ASAG's compact
growth plan and its effect on the metropolitan housing
market," Presented at the Annual Conference of the American
Institute of Planners, New Orleans, September 28, 1378.
Downs, A. The Costs of sprawl, Washington, D.C.: The Real Estate
Research Corporation, 1974.
Evans, M. S. "Costs of regulation." Fort Lauderdale Sun Sentinel
(December 31, 1975) : 6A, col. 4.
Feagin, J. R. "Tallying the social costs of urban growth under
capitalism: The Case of Houston," in Business Elites and Urban
Development, edited by S. Cummings, 205-234. Albany: State
University of New York Press, 1988.
Fischel, W. E. "Does zoning matter? Empirical evidence on zoning,
externalities, and housing costs." In the Economics of Zoning
Laws: A Property rights approach to American land -use
controls, chapter 11, 231-251. Baltimore: Johns Hopkins
University Press, 1985.
Frech, H. E., III. "The California Coastal Commission- Economic
impacts." In Resolving the housing crisis, edited by M. Bruce
Johnson. San Francisco: Pacific Institute for Public Policy
Research, 1982.
Frieden, B. J. and A. P. Solomon. "The Controversy over home
ownership and affordability," AREUEA Journal 5 (1977).
Greiner, A, "'The Housing affordability gap and Boston's economic
growth: Potential for crisis." M.I.T., Department of Urban
Studies and Planning (October 1987). Draft for discussion
only.
Johnson, R. A., S. I. Schwartz, G. Wandesford- Smith, and K. E.
Savage. "Mandating affordable housing by the use of state
permit powers." Unpublished paper, University of California,
Davis, 1986.
Katz, L. and K. Rosen. "The Interjurisdictional effects of growth
controls on housing prices." Journal of Law and Economics 30
(April 1987): 149-160.
Kroll, C. A. and J. D. Landis. "San Diego County's housing cap and
growth debates.'" Quarterly Report, Center for Real Estate and
Urban Economics, vol. 3, 1988.
Schwartz, S. I., D. E. Hanson, and R. Green. "The Effect of growth
control on the production of moderate -priced housing." In
Growth management: Keeping on target? edited by D. R. Porter,
15-20. Washington, D.C.: Urban Land Institute, 1986.
Seidel, S. Housing costs and government regulation: confronting the
regulatory maze. New Jersey: Center for Urban Policy Research,
1978.
Seidel, S. Government regulations and housing costs. New Brunswick.
Center for Urban Policy Research, 1977.
Sidor, J. "Affordable housing, land supply, and land development:
California." Council of State Comnunity Affairs Agencies,
Washington, June 1983.
The Benefits and costs of metropolitan growth: A Research approach.
The Institute for Policy Studies, Johns Hopkins University,
Baltimore, Maryland, 1989.
The Costs and benefits of local growth control ordinances: A
Preliminary assessment. Proposal to the California Policy
Seminar.
Turner, M. A. Housing needs to the year 2000. Washington, D.C.:
National Association of Housing and Redevelopment Officials,
1987.
Urian land Institute. The cost of delay due to government
regulation in the Houston housing market. Washington, D.C.:
Urban Land Institute, 1979.
Urban Land Institute. "The Effects of growth management on housing
costs in San Jose, " ULI Research Report #2? , Washington, D.C.,
1977.
U.S. Department of Housing and Urban Development. Final Report of
the task force on housing costs. Washington, D.C.: HUD, 1978.
U.S. Department of Housing and Urban Development. The President's
National Urban Policy Report. Washington, D.C.: HUD, 1978-88.
White, J. R. "Large lot zoning and subdivision costs: A Test."
Journal of Urban Economics (May 1988): 370-84.