HomeMy WebLinkAbout2001-10-16 City Council (2)City of Palo Alto
City Manager’s Report
TO:HONORABLE CITY COUNCIL
ATTN:FINANCE COMMITTEE
FROM:
DATE:
CITY MANAGER
OCTOBER 16, 2001
DEPARTMENT: PLANNING AND
COMMUNITY ENVIRONMENT
CMR: 383:01
SUBJECT:INCREASE TO COMMERCIAL HOUSING IN-LIEU FEE AND
REVIEW OF UPDATE TO HOUSING FEE LINKAGE STUDY
REPORT IN BRIEF
In 1984, the City of Palo Alto adopted an ordinance (Chapter 16.47 of the Municipal
Code) requiring developers of commercial and industrial projects to develop below
market rate housing or pay a housing fee as mitigation for the impacts on housing
attributable to jobs created by commercial development. Neither the provisions of the
ordinance nor the fee formula have been altered since minor amendments were made in
1985. The current fee rate is $4.21 per net new square foot. Revenue collected under the
ordinance is placed in the Commercial Housing In-Lieu Fund and has been used
exclusively to subsidize the cost of housing affordable to very low- and low-income
renter households. Over 400 rental units have been assisted with these funds. An
economic nexus study recently has been completed for the City that demonstrates that the
cost of providing housing affordable to the low and moderate-income households
attributable new commercial development has increased significantly since the last study
conducted in 1993. An increase in the housing fee base rate to $12.00 per square foot is
recommended by staff to ensure that commercial projects mitigate a significant portion of
the affordable housing impacts.
CMR:383:01 Page 1 of 12
RECOMMENDATION
Staff recommends hat the Finance Committee:
1)Review the attached Housing Linkage Update Analysis, which quantifies the current
cost of providing affordable housing for low and moderate income employee
households attributed to new commercial development;
2)Recommend to the City Council that Chapter 16.47 of the Municipal Code be
amended to increase the Commercial Housing In-Lieu Fee from its current level of
$4.21 per square feet to an initial base fee of $12.00 per square foot, with annual
revisions to accotmt for inflation; and direct staff to prepare appropriate amendments
to Chapter 16.47 for formal Council adoption;
3)Recommend to the City Council that the housing fee increase apply only to
development projects currently in the "pipeline" where a complete application for
discretionary approval, including a complete preliminary Architectural Review Board
application, has not been submitted as of the effective date of the ordinance;
4)Provide direction to staff on changes to the list of uses currently exempt from the
housing fee and other issues that may be of concern to Council for consideration in
the second phase of the housing fee study.
BACKGROUND
Palo Alto began collecting housing mitigation payments from industrial and office
developers in 1976 on a case-by-case basis through the environmental review process
under the California Environmental Quality Act (CEQA). On August 6, 1984, in
response to changes in State law, the City adopted Ordinance No. 3560 adding Chapter
16.47 of the Municipal Code, Approval of Projects with Impacts on Housing. The
ordinance codified the housing mitigation fee and established a new uniform fee rate,
starting at $2.43 per square foot, which applied uniformly to new commercial
development including retail, hotel, office and industrial space. Chapter 16.47 was
amended in 1985 to exempt from the housing fees certain square footage that either did
not generate a significant numbers of jobs, or was considered beneficial to the employees
and the community in general, such as employee cafeterias, child care space and
hazardous materials storage areas. A second amendment was also adopted in 1985 to
provide for penalties for nonpayment. Neither the content of the ordinance nor the
formula for the housing fee has been changed since 1985.
When Chapter 16.47 was enacted, the City relied on a housing impact analysis that had
been completed for environmental studies under CEQA for different major office and
industrial projects to justify the initial fee amount. An affordable housing demand and
cost was calculated by the City and the decision was made that commercial developers
should provide actual units or pay an equivalent fee that represented the cost of meeting
CMR:383:01 Page 2 of 12
10 percent of the affordable housing demand generated by their project. In 1993, the City
contracted with the firm of Keyser Marston Associates, Inc. to prepare a formal economic
nexus study. The purpose of the nexus study was to more carefully document the linkage
between new commercial square footage and the demand for additional housing, and to
confirm that the City’s housing fee, which was $3.34 per square foot at the time, was
within the maximum limits justified by a rigorous economic analysis.
Commercial housing fees are deposited in a special revenue fund, the Commercial
Housing In-Lieu Fund (Commercial Fund), with the fees and Fund’s interest earnings
used exclusively tO subsidize the development of new affordable housing. The "Housing
Reserve Guidelines" adopted by Council in 1985 set City policy for use of the
Commercial Fund. While the guidelines permit subsidies to both ownership and rental
housing and to housing serving a broad range of income levels, in practice only rental
housing developments have been assisted and the majority of the units have been for
occupancy by very low-income households. There are several reasons for the emphasis
on providing very low-income rental housing, including:
¯ The priority (on the part of both the City and the housing non-profits) for
assisting households with the greatest difficulty competing for Shelter in the
private market;
¯Opportunities to leverage City housing funds and attract State and federal
housing subsidies that tend to only be available for rental projects and very
low-income rental housing in particular; and
¯Maximizing the impact of City housing funds, as relatively higher density,
modest rental units allow more units to be created for a given amount of City
subsidy than other housing types.
Housing developers may apply for financial assistance for a project from the Commercial
Fund at any time. The City Council must approve all funding awards and assistance is
usually in the form of a loan secured against the property. Eight rental housing projects
have been developed, or in the case of Oak Court, land has been secured, with assistance
from the Commercial Fund. The projects are summarized in the table below:
CMR:383:01 Page 3 of 12
Name of Project Year Built Total Units Commercial Housing In-
Lieu Funds Provided
Webster Wood Apts
Terman Apts
California Park Apts
Lytton Courtyard
Barker Hotel
Alma Place SR0
Page Mill Court Apts
Oak Court Apts
Total Units Assisted
1978 68
1985 92
1989 45
1994 51
1994 5 (new
units added)
1998 107
1998 24
2001 51 (est)
443
Record of funds expended
not available
Est. $996,838 [See above]
Est. $925,000 [See above]
$500,000
$400,000
$2,221,976
$505,400
$3,475,000 (to d~e)
Without the availability of the revenue from housing fees, few of these 443 units could
have been developed in Palo Alto. Other funding sources are insufficient in amount, are
restricted by federal rules, require extremely competitive grant applications or have not
been available in Palo Alto. Redevelopment housing °’set aside" funds are an example of
one of the principal local housing funding sources in California that have not been
available to the City because there has not been a redevelopment project within the City
generating such funds.
The City’s only other ongoing funding sources for affordable housing production are the
annual Community Development Block Grant (CDBG) allocation and fees received from
residential developers in-lieu of providing Below Market Rate (BMR) units. While a
large percentage of the CDBG allocation is typically committed for housing, federal
regulations place many restrictions on how CDBG funds can be used in connection with
new housing construction. The principal barrier is that CDBG funds cannot be used for
actual construction costs, but only for land acquisition and predevelopment expenses.
Also, the small size of Palo Alto’s grant (about $750,000 annually) and other program
priorities limit the amount of housing production that can be assisted with CDBG funds.
Nevertheless, CDBG funds have been used in combination with housing mitigation fee
funds to subsidize several of the projects listed above, including Lytton Courtyard,
Barker Hotel and Page Mill Court.
The monies in the Residential Housing In-Lieu Fund are available for new housing
construction subsidies but, by Council policy, may also be used to acquire and renovate
existing units. Due to the City requirement to provide actual BMR units in market
housing, the BMR program in-lieu fee revenue is much lower on an annual average than
the revenue from the commercial housing fee. Generally, there is a continual need to use
whatever funds are available in the Residential Fund to support the acquisition and
preservation of existing rental housing.
CMR:383:01 Page 4 of 12
During the ten fiscal years from 1990-91 through 1999-2000, a total of almost $5.7
million in fees was collected, or an average of $568,600 per year. This period covered
both prosperous times and recessionary periods when there were years with almost no
fees received. In the fifteen months ending September 2001, fee payments accelerated,
with $2.3 million collected due to several major office projects, additions to Stanford
Mall, and the Cancer Center under construction. As of September 30, 2001, the
Commercial Fund balance was just over $1.7 million. Most of those funds will be
needed for construction subsidies for the Oak Court project being developed by Palo Alto
Housing Corporation at Channing Avenue and Ramona Streets in the South of Forest
Area (SOFA). A drop in the volume of fee revenue over the near-term future is expected,
commensurate with the downturn in the office market and the economy in general.
DISCUSSION
Housing Linkage Fees
Under State law, in order to charge a housing mitigation fee, a local government must
make findings that a reasonable relationship exists between the proposed use of the fee
and the type of development project on which the fee is imposed; that a reasonable
relationship exists between the need for the proposed use and the type of development
project on which the fee is imposed; and that there is a reasonable relationship between
the amount of the fee and the cost of the public facility (use) attributable to the
development on which the fee is imposed. To support the required findings, most local
agencies prepare an economic analysis to justify that the proposed fee rate does not
exceed the cost of meeting the affordable housing impacts generated by the development
of various types of new commercial space. Without an adequate and up-to-date nexus
study a jurisdiction would be in a weaker position should there be a legal challenge to the
fee.
The first step in the nexus study is to quantify the linkages between the construction of
new commercial buildings and the demand for housing at various affordability levels.
The number of low to moderate wage workers that would be expected to occupy new
commercial buildings of different uses is calculated and then converted into numbers of
households of very low, low and moderate incomes. A housing affordability gap analysis
is then completed to determine the difference between what worker households can
afford to pay for housing and what it costs to develop housing in Palo Alto. By
combining the number of new households expected to work in new commercial space
that can’t afford local housing with the affordability gap for those households, a total
linkage cost per new square foot is determined. This is the maximum housing linkage fee
justified by the economic analysis. However, since many assumptions, judgements and
interpretations go into the analysis, localities typically take a very conservative approach
and set the actual housing fee at a much lower amount than the maximum level justified
by the economic analysis.
CMR:383:01 Page 5 of 12
The City’s existing housing fee revenue has not kept pace with increases in the cost of
developing housing, especially over the last six years. The housing fee has been adjusted
annually since 1984 to account for inflation based on changes in the bay area Consumer
Price Index (CPI). The CPI is a measure of inflation and covers a broad selection of
consumer goods and services. Over the 17 years from 1984 to 2001, the housing fee
increased from $2.43 to $4.21, a 73 percent increase. However, housing development
costs have increased at a much greater rate. Land is the key component influencing the
extremely high housing development costs in Palo Alto. The City’s Housing Element
adopted in June 1984 reported that residential developers were paying $10 to $25 per
square foot for residential land. Keyser Marston estimates that multi-family zoned land
would sell for $75 to $100 per square foot in late 2001. This indicates that land costs
alone have increased from 300 percent to 650 percent versus the 73 percent CPI-based
increases in the commercial housing fee over the same time period. Housing construction
costs have risen dramatically also, although not as rapidly as the cost of land.
The slowing economy and the reduction in the initiation of new commercial projects
presents an opportunity to consider significant increases in impact fees without affecting
many projects already in the early site acquisition and planning process. Reduced
escalation of the principal cost components of commercial projects (e.g., land and
construction costs) due to current economic conditions should help the impact fee
increases be absorbed into development budgets. Councilhad also directed staff to study
possible impact fees for parks and community facilities. By considering both the new
proposed community facilities fees and increases in the housing fees simultaneously,
Council will be able to better evaluate the total effect of the City’s impact fees on the
commercial development sector. A companion staff report (CMR:381:01) covering the
parks and community facilities fees is being forwarded to the Finance Committee.
In July 2001, staff contracted with Keyser Marston to update its 1993 nexus study, to
develop a revised total linkage cost and assist staff in recommending an increase to the
base fee rate for adoption by Council. The 1993 study used 100,000-square-foot
prototype buildings for each of five commercial land uses commonly built in Palo Alto.
The consultant calculated average employment per square foot and workers’ salary
levels. Low- and moderate-income workers were then translated into households by
income level and adjustments were made for households likely to live in Palo Alto if
affordable housing was available. Keyser Marston evaluated each component of its 1993
study to judge how conditions may have changed that would alter the results of the
analysis. All major inputs to its computerized jobs housing model were examined in light
of more recent information and data. Key factors that had, indeed, changed included
typical employment densities, numbers of employees per household, and increases in
compensation and household incomes. However, the consultants found that adjustments
that could be made to the model’s inputs would tend to cancel each other out, that is,
some would increase the nexus amount and others would tend to decrease it. None of the
adjustments would be so substantial as to invalidate the basic nexus finding, or
CMR:383:01 Page 6 of 12
significantly reduce the number of low and moderate-income households demanding
housing in Palo Alto associated with the construction of new commercial space.
Because Chapter 16.47 subjects all types of commercial projects to a single mitigation fee
requirement, the consultant needed to develop a composite nexus conclusion for a generic
commercial building. The range of low- to moderate-income households generated by
different commercial uses ranges from 22 households for the average hotel to 47
households for office uses. Keyser Marston recommends that a reasonable composite
affordable housing nexus covering all commercial uses is 38 low- to moderate-income
households generated by a prototype generic 100,000-square-foot commercial building,
as shown in the table below.
Consolidated Housing Nexus for Generic Commercial Building
Affordability Level
(Percent of County Median Income)
Very Low Income (Under 50%)
Low Income (50% to 80%)
Lower Moderate Income (80% to 100%)
Upper Moderate Income (100% to 120% )
TOTAL AFFORDABLE UNITS
Housing Units Needed per 100,000
Square Feet of Commercial Space
7 units
15 units
8 units
8 units
38 units
Housing Affordabilitv Gap Analysis
The consultant completely revised the analysis of the affordability gap, the cost of
providing housing affordable to low- to moderate-income households, due to the dramatic
increases in ownership and rental housing costs since preparation of the 1993 study.
Keyser Marston reviewed the development costs for actual rental and condominium
projects recently constructed in the City and from that information estimated costs of
prototype two-bedroom rental and condominium units. It was assumed that households
with higher income would demand ownership housing. An analysis was made of what
households at each of the four different income levels could afford to pay for housing.
The difference between the cost of housing and the amount the households could afford is
the affordability gap per unit. The factors are then put together in a formula that gives the
nexus cost per square foot for a prototype commercial building. The $57.81 per square
foot of net new commercial development is the full value of the gap between what low-
and moderate-income households can afford to pay for housing and the development cost
of modest, but adequate housing to meet those households’ needs.
CMR:383:01 Page 7 of 12
Affordability Gap
Rental Affordability Gap:
Under 50% of Median
50% to 80%
Ownership Affordabili _ty Gap:
80%-100% of Median
100% to 120%
Number of Households
(per 100,000 sq. ft)
Nexus Cost Per Sq. Ft.
7 $15.75
15 $20.70
8 $12.72
8 $8.64
TOTAL 38 $57.81
Note: Nexus Cost Per Square Foot = Affordability Gap Per Unit x Number of Units /
100, 000 square feet
Recommended Housing Fee Increase
Other cities with similar office and business markets have set their impact fees so that the
fees represent a relatively small percentage of a commercial developer’s total project
development costs. To aid the City in its decision on the amount of the housing fee,
Keyser Marston collected and summarized development costs for four of the most
common commercial projects built in the Palo Alto. The building types were: 1)
industrial park office/high tech, 2) downtown office with retail, 3) upscale hotel, and 4)
retail building at a shopping center. Interestingly, the lower-end cost of all building types
ranged from $330 to $352 per square foot.
Current housing impact fees are about 1.2 percent to 1.25 percent of the lower end of the
cost ranges. Increasing the housing fee to $12 per square foot brings the percentage of
total development costs due to the fee to 3.3 percent to 3.5 percent. Table 13 of the
Keyser Marston study summarizes the housing fees of other local cities and some of the
major large cities with fees. A $12 housing fee would be comparable to the fee rate in
San Francisco, Menlo Park and Seattle. These cities, like Palo Alto, have traditionally
had a strong commercial office market and a corresponding lack of affordability in
housing. Staff believes that it is appropriate for Palo Alto to set the commercial housing
fee at a level that is comparable to cities with similar market conditions. The table below
lists current and pending housing fees of comparable cities.
CMR:383:01 Page 8 of 12
Comparison of Housing Fee Rates in Cities with Similar Housing Costs &
Commercial Development Markets
Fee Amount Date Set or Effective
San Francisco Office $14.00 2002
Retail $14.00
Hotel $11.00
Seattle Office & Hotel: $12.00 2001
Menlo Park Office: $10.00 2001
Other Commercial: $5.45
Mountain View Office: $6.00 Pending, new
Hotel: $3.00 ordinance being
Retail: $2.00 reviewed
Timing of Effective Date of Proposed Fee Increase
Staff also requests direction from Council on whether to apply the increased fee to
proposed development projects already in the application or development review process.
The requirement to pay the housing fee is a condition of approval for every commercial
project subject to the ordinance. Developers generally contact staff in the preliminary
stages of planning a new project to determine the City’s impact fees and the amounts.
Most commercial projects subject to the housing fee go through a preliminary review
process. The developer is informed at that time that the housing fee will apply and the
approximate amount of the fee. In order to minimize adverse financial effects on projects
currently in the development pipeline, staff recommends that the fee increase apply only
to those projects where a complete application for discretionary approval, including a
complete preliminary Architectural Review Board application, has not been submitted, as
of the effective date of the ordinance.
Work Program for Second Phase of Housing Fee Revision Study
Staff divided the consultant’s work into two phases primarily to bring the proposed
housing fee increase to Council as quickly as possible. Accelerating the completion of
the housing fee portion of the work program also made it possible to present the
recommendation for the housing fee increase, and the proposals for new park and
community facilities fees, to Council at the same time. The other provisions of the
housing fee ordinance that need to be examined, and possibly revised, function
independently of the fee rate. Separating the work program into two phases may facilitate
public discussion of the more detailed aspects of the ordinance when staff brings the
second phase report to Council.
In Phase II of the study, the consultant will assist the City with a review and possible
revision of all aspects of the current ordinance. Ordinances from other jurisdictions will
be compared and evaluated. The existing ordinance may be modified or substantially
restructured. One objective of this review is to increase efficiency in administering the
impact fee program. Presently the use exemptions, square footage thresholds, special
CMR:383:01 Page 9 of 12
exempt spaces within a project, and fee collection process are fairly complex and are
administered by professional-level planning staff. If the new and revised impact fees
applied uniformly to all net new square footage without exemption for certain uses of
space or for threshold space, administration would be less time-consuming and less
expensive. The housing fee ordinance currently exempts the first 20,000 square feet on a
site from the impact fee and also exempts additions of less than 2,500 square feet.
Further exemptions are allowed for uses within a project considered desirable, such as
employee cafeterias. The timing of the fee payment will be also reviewed. The housing
fee is paid in two parts; half at building permit issuance and the remaining half at
completion. Payment in full at building permit issuance would reduce administrative
time and is how the transportation fee is paid: Alternatives to the use of the CPI for the
annual fee adjustment will also be examined. The transportation impact fee uses an
inflation index based on construction cost changes. Using an inflation index that better
reflects increases in land and development costs and applies to all the various impact fees
will be considered.
Phase II will also examine whether some or all the land uses listed in Section 16.47.030
of the ordinance should become subject to the housing fee. The non-residential uses
currently exempt from the housing fee are:
¯Churches
¯Colleges and universities
¯Commercial recreation
¯Hospitals
¯Convalescent facilities
¯Private clubs, lodges, and fraternal organizations
¯Private education facilities [includes child care facilities]
¯Public facilities [includes public schools, government buildings, etc]
Some of the exempt uses, such as hospitals and private schools, are important
employment generators and probably have many low- to moderate-income workers.
Other uses would be expected to have much lower employment per square feet of space.
If Council supports eliminating specific land use exemptions, the housing nexus cost for
those land uses will need to be determined by the consultant. Staff is requesting direction
from Council on which land uses, if any, should be exempt from the housing fee and any
other aspects of the existing ordinance that may be of concern to Council.
ALTERNATIVES TO STAFF RECOMMENDATION
Council may consider the following alternatives to staff’s recommended housing fee
increase:
1) Decide not to increase the housing fee rate leaving the fee at its current $4.21 rate;
2) Decide to postpone, or phase-in, the recommended fee increase;
CMR:383:01 Page 10 of 12
3)Set the housing fee at a higher (or lower) level than recommended by staff:
The nexus study update justifies a housing impact fee rate of up to $57.81 per square
foot, which would on average cover 100 percent of the affordable housing costs
generated by a prototype commercial project. Council could choose to set the housing
fee at any amount from the current $4.21 up to the $57.81 maximum supported by the
consultant’s study;
4)Establish different fee rates for different types of commercial uses:
Staff does not recommend different fee rates for office, research and development,
industrial, and retail/services uses, although the nexus analysis does demonstrate there
are some differences in the numbers of low- to moderate-income households
generated by these uses. The range in low- to moderate-income households per
100,000 square feet of commercial space (other than hotel uses) extends from a low of
29 households for research and development uses to a high of 47 households for
office uses. The construction and floor plans of these types of commercial structures
may be adapted from one use to another, often with few exterior changes or structural
alterations. In many zoning districts, only a building permit is needed to change from
one use to another. Adopting multiple housing fee rates would necessitate an
increased level of use and occupancy monitoring of commercial structures which
would require additional staff resources.
Hotels are a more unique commercial structure that would not normally be converted
to another commercial use. While the 1993 nexus analysis found 22 low- to
moderate-income households per 100,000 square feet of hotel use, Keyser Marston
has completed more recent analysis of hotel jobs and salaries for other communities
that demonstrates a higher hotel jobs nexus. Should Council decide to establish a
separate housing fee rate for hotel uses, then staff recommends that an updated nexus
analysis should be completed by Keyser Marston for use in setting the new hotel
housing fee.
RESOURCE IMPACT
Precise revenue projections for future housing fees if the proposed increase to $12 per
square foot is adopted are not possible. Given the current weak office market, major
additions of office space are unlikely. Most commercial pro.jects presently in
development review, such as Hyatt Rickey’s and 800 High Street, provide a significant
number of housing units within the project and therefore, under the provisions of the
current ordinance, will not be required to pay a commercial housing fee. Thus, it will
probably not be until the economy is well into recovery that the results of the proposed
fee increase will be seen in Commercial Fund assets. However, if the $12 fee rate had
applied to the commercial projects paying housing fees during the last fiscal year (2000-
01), about $4.2 million would have been deposited to the Commercial Fund versus the
$1.4 million received with the current $4.21 fee. An acre to an acre and one-half of
residential land could have been purchased at current values with $4 million in funds.
....Pagellofl2CMR.~8~.01
POLICY IMPLICATIONS
The housing fee ordinance is based on the long-standing City policy that commercial
developers should contribute to the cost of meeting the affordable housing needs of their
work force. The housing fee increase recommended by staff is intended to ensure that a
significant portion of the affordable housing impacts of such projects are mitigated but, at
the same time, commercial development remains viable in Palo Alto.
TIMELINE
Once the Finance Committee recommends specific fee levels to staff, staff will prepare
ordinance amendments for Council adoption to enact the new housing fee. The new fee
can be instituted 60 days following adoption of the ordinance. Staff also intends to hold
discussions with local business organizations and developers prior to the first public
hearing on the fee changes.
Staff plans to initiate the second phase of the review and evaluation of the housing fee
after adoption of the fee increase. A draft work program extending the current contract
with Keyser Marston has been prepared, but staff has not executed the contract
amendment pending Council input and direction on policy issues that affect the work
program. After completion of the second phase, staff will return to Council with a
revised ordinance for review and adoption.
ENVIRONMENTAL REVIEW
This action does not require California Environmental Quality Act (CEQA) review.
ATTACHMENTS
A. Housing Linkage Update Analysis by Keyser Marston Associates, Inc. September
2001
B. Jobs Housing Nexus Analysis, by Keyser Marsto~ Associates, Inc. 1993/1995
Catherine Siegel, Housing C6.~rdinator
REVIEWED BY:
Lisa Grote, Chief Planning Official
CITY MANAGER APPROVAL:
Emil~y Harrison, Assistant City Manager
CMR:383:01 Page 12 of 12
ATTACHMENT A
¯ City of Palo Alto
Housing Linkage Update
Analysis
Keyser Marston Associates, Inc.
September 2001
EXECUTIVE SUMMARY
Introduction
This report is an update of the Jobs Housing Nexus Analysis, Prepared for the City of Palo
Alto, October 1993, Portions Revised March 1995, Prepared by Keyser Marston Associates,
Inc. (KMA). The report has been prepared per request of the City to serve as a basis for
considering an adjustment to the City’s jobs housing impact program and its in-lieu component
(Chapter 16.47 of the Municipal Code originally adopted in 1984.)
The update is drawn from KMA’s extensive experience over the past ten years in the
preparation of jobs housing nexus analyses, including recent assignments for other cities in
Silicon Valley.
Nexus Analysis
A nexus analysis is an analysis that quantifies the linkages between the construction of new
commercial and industrial buildings and the demand for housing at various affordability levels.
The conclusions are expressed in terms of the number of housing units at various affordability
levels associated with a given amount of building area.
The update consisted of a review of each of the inputs to the analysis, which had been
performed using a computerized model, for evaluation as to whether conditions have changed
that would alter the conclusions of the analysis. It was found that while a number of inputs
would be adjusted, on balance, the changes would mostly cancel each other out. None of the
adjustments would be so substantial as to invalidate the basic nexus findings.
All commercial and industrial projects are subject to a single mitigation requirement per
Chapter 16.47 of the Palo Alto Municipal Code. Therefore, a hybrid nexus conclusion is
needed. The set of figures below is KMA’s recommended hybrid. The average is higher than
the 1993 analysis would suggest is appropriate for the hotel component, but is consistent with
KMA’s more recent analysis of hotel jobs housing nexus, based on better information on the
employment composition and compensation levels of hotel workers.
Affordability Level
Very Low Income (Under 50% median)
Low Income (50% to 80% median)
Lower Moderate (80% to 100% median)
Upper Moderate (100% to 120% median)
Housing Units per
100,000 sq.ft.Sq.Ft.
Bldg. Area Bldg. Area
7 .00007
15 .00015
8 .00008
--8 .00008
38 .00038
Keyser Marston Associates, Inc.
17175.003\001-005.doc; 9/27/2001 Page 1
Affordability Gap Analysis
The affordability gap component of the analysis has been completely updated as part of this
work program. Significant changes in housing affordability have occurred since the earlier
analysis. A new two-bedroom apartment in Palo Alto now rents for $2,760 per month,
requiring a three-person household with an income at about 140% of median. The $350,000
two-bedroom condominium requires the three-person household to have an income over
150% of median
Affordability gaps are based on an analysis of the costs to develop rental and condominium
units, inclusive of land and all indirect costs, which are summarized on a range basis. The low
end of the range is utilized. Other assumptions are based on City policies. Conclusions used
in the analysis are:
$225,000 for households in the under 50% of median income category, based on a
three person household at 40% of median income in a two-bedroom apartment unit.
$138,000 for household in the 50% to 80% of median income category, based on a three-
person household at 70% of median in a two bedroom apartment units.
$159,000 for households in the 80% to 100% of median income category, based on a
three-person household at 90% of median in a two-bedroom condominium unit.
$108,000 for households in the 100% to 120% of median income category, based on a
three-person household at 110% median income in a two-bedroom condominium unit.
The gap for the 90% of median income category is higher than for the lower income category
(50% to 80%) due to the fact that the median income household is assumed to be
accommodated in a condominium unit, which is more expensive to build, while the lower
income category is in a rental unit.
Total Linkage Costs
Total linkage costs are determined from the combined findings on the number of households
and the affordability gaps. Conclusions are:
Rental Affordability Gap
Under 50% Median Income
50% to 80% Median Income
Ownership Affordability Gap
80% to 100% Median Income
100% to 120% Median Income
Total
Number of Nexus Cost
Households1 Per Sq.Ft.
7 $15.75
15 $20.70
8 $12.72
_~8 $ 8.64
38 $57.81
1per 100,000 sq.ft, of building area
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These costs express the total linkage or nexus costs for commercial and industrial building types.
These total nexus findings and cost represent the ceiling for any requirements placed on new
construction for affordable housing.
Many conservative assumptions were used in the preparation of the nexus analysis and costs.
Alternative assumptions would produce higher costs.
Information to Assist in Fee Setting
Total cost information for the development of various commercial and industrial projects in
Palo Alto provides a context for evaluating alternative fee amounts. Development cost
information was assembled for a range of prototype projects, based on input from developers,
research on land costs, and other projects KMA is working on throughout the Silicon Valley/SF
Peninsula area. Virtually all commercial and industrial project costs over $300 per square foot
"all in" (land, construction, all indirects, financing, etc.) and frequently the cost is in the $400
per square foot range. As a result a $5 fee would represent a 1.0% to 1.5% cost increase,
while a $10 fee would be in the 2% to 3% range.
Information on linkage programs adopted in other jurisdictions was also assembled for context
and comparison. The chart in the report notes not only the housing fee amount, but also other
citywide impact fees, and provides an estimate of the percent range of development costs in
the jurisdiction of the fee. San Francisco has the highest fee structure in the U.S. (to our
knowledge), but other cities such as Seattle and Menlo Park may also be of interest as
models.
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INTRODUCTION
The following report is an update of a jobs housing nexus analysis report prepared by Keyser
Marston Associates, Inc. (KMA) in the mid 1990’s which, at that time, had been prepared to
further support the program in place since 1984. In this update, the KMA nexus analysis is
reviewed step by step for validity at the current time and the portions of the analysis
addressing the costs of housing mitigations are revised. The City of Palo Alto requested this
update analysis to serve as a basis for considering adjustment to the City’s jobs housing
impact program and its in-lieu component.
Background
In 1984 the City of Palo Alto adopted Chapter 16.47 of the Municipal Code which requires
commercial and industrial projects contribute to programs that increase the City’s low and
moderate income housing stock. Chapter 16.47 requires a developer to provide affordable
housing units as a condition of development, or alternatively, pay an in-lieu fee. In 1992, the
City decided to review the code and program and to commission the preparation of a nexus
analysis consistent with new legislation and court rulings since the original program. This firm,
Keyser Marston Associates, Inc. prepared the analysis as summarized in a report entitled Jobs
Housing Nexus Analysis, City of Palo Alto, October 1993, Portions Revised March 1995.
Qualifications
In addition to our prior work on the preparation of the Palo Alto Jobs Housing Nexus Analysis,
this update is also drawn from KMA’s extensive experience over the past ten years in nexus
analyses prepared for other jurisdictions to serve as a basis for housing impact programs.
Over the past year we have worked for other cities in the San Francisco Peninsula/Silicon
Valley area. In recent years, we have prepared similar analyses for the cities of San Francisco
and Seattle and have examined the major demographic trends and other factors that are
incorporated into a nexus analysis.
The nexus reports for Palo Alto and for other jurisdictions were prepared to meet the
requirements of AB 1600 in support of ordinances to increase the supply of affordable
housing.
Nexus Analysis Defined
A nexus analysis is an analysis that quantifies the linkages between the construction of new
commercial and industrial buildings, the employees that work in them, and the demand for
housing units on the part of the employee households by affordability level. The conclusion of
a jobs housing nexus analysis is expressed in terms of the number of housing units in demand
by affordability associated with each square foot of commercial (or industrial) building area.
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The cost of delivering housing units affordable to the lower income components of the
employee households constitutes the cost of mitigation and the basis for an in-lieu fee.
There are a number of important underlying assumptions in any nexus analysis, such as that
growth in the Palo Alto area is largely job driven and that new construction (over and above
demolition of !der space) represents net new local employment. These and other
assumptions discussed in the nexus analysis report.
Organization
This report is divided into three sections:
Section I - Nexus Analysis Update Review
Section II - Affordability Gap and Total Linkage Cost
Section III - Materials to Assist in Selecting the Fee Level
The tables are at the end of the text along with a set of Appendix Tables which provide
additional supporting materials.
Data Sources and Qualifications
The analyses in this report have been prepared using the best and most recent data available.
Local data was used wherever possible. Other sources such as the 1990 U.S. Census and
the California Employment Development Department were used extensively. While we believe
all sources utilized are sufficiently accurate for the purposes of the analysis, we cannot
guarantee their accuracy. Keyser Marston Associates, Inc. assumes no liability for information
from these other sources.
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SECTION I - NEXUS ANALYSIS UPDATE REVIEW
In this section each step of the 1993/95 KMA nexus analysis is reviewed for evaluation as to
how conditions may have changed that would or could alter the results of the analysis. The
original analysis was performed by use of a computerized jobs housing model. Each of the
major inputs to the model are examined in light of more recent information and data.
Major Analysis Inputs
The change in the analysis that could increase the nexus, or number of lower income
households associated with a given building area, in Palo Alto is:
Employment Density- or the number of employees related to building area. If
anything, employment became more dense over the last decade. The 1993 analysis
used 250 square feet per office employee. In recent years, particularly in high tech
space (which is no longer distinguishable from office as a building type), densities are
often closer to 200 square feet per employee. A. survey conducted for the Valley
Transportation Authority (VTA) found an average of 205 square feet per employee.
Given that the VTA survey was conducted during the high tech boom, we would
caution against the use of that density as a long-term average. Were we doing a new
analysis today we would recommend 225 square feet per employee, a change that
would increase the number of workers by about 11% over the 1993 analysis.
Factors in the analysis that have changed very slightly or that would decrease the nexus are:
The number of employees per household at 1.66, which was based on the 1980
Census, increased to 1.78 by the time of the1990 Census. With more workers per
household, a given number of workers means fewer households and fewer housing
units in need. More recent information is not yet available. This change decreases the
number of households per given number of workers by about 7%.
Occupational composition of workers - in some cases such as office, the share of all
workers that are in the lower paid clerical category has declined somewhat. In others,
such as hotel and retail, jobs in the lower paying categories are either stable or
increasing.
Income of workers has changed dramatically in Santa Clara County since 1993, but not
uniformly across all occupations. In general, the higher skilled types of occupations
such as the Professional, Paraprofessional and Technical category have seen huge
increases in compensation over the past eight years, while many clerical, sales and
service workers, such as those in the hospitality industry have seen lower increases.
Median income in Santa Clara County has increased substantially. As a result,
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workers that were in lower income households per the 1993 analysis would still be
lower income given current compensation levels vis-&-vis median income levels. While
we are not rerunning the analysis and model as part of this update, we are able to
provide current materials on compensation levels to provide further support to these
conclusions. (See Appendix Tables A, B, and C)
A nexus analysis for a limited geographical area, such as a city, must make an adjustment for
the share of housing demand generated by a new commercial or industrial project, to be
located within the city. This adjustment may be based on historic experience and/or it may
reflect policy goals. The 1993 analysis used 33% as a share, a conservative judgment about
the share of total worker households generated by the project that would seek out housing in
Palo Alto were it affordable. Of those who work in Palo Alto, the 1980 U.S. Census found that
19.7% also lived in the City. By 1990 the share had dropped to 15.3%. The most recent
Census information is not yet available. The 33% used in the 1993 analysis was based on an
examination of the other Silicon Valley and Peninsula cities where it was found that several
cities of comparable size did realize about a 33% share. If we were revising the analysis, we
would recommend to the City to stay with the 33% share.
Conclusions on Update Review
On balance the changes that would increase or decrease the number of lower income
households would mostly cancel each other out. Adjustments in both directions in the range of
11% or less are in evidence. None of the adjustments would be so substantial as to invalidate
the basic nexus finding, or significantly reduce the number of lower and moderate-income
households found in the 1993 analysis
Following is a summary of conclusions from the 1993 analysis (see Tables 2, 3, and 4):
Affordability Level
Households per 100T000 sq.ft. Building Area
Office R&__..~D Industrial Retail/Services Hotel
Very Low Income 7 5 4 7 4
Low Income 18 12 12 18 11
Moderate Income 2..~2 1..~2 1___6 1_Z7 7
Total 47 29 32 42 22
Following are a few comments on each of the categories:
Wareho~.se - The 1993 analysis also included warehouse buildings. Given the
economics of developing in Palo Alto, warehouse is no longer a viable land use and no
such projects have been developed for many years.
¯Office, R&D, Industrial and High Tech - The 1993 analysis addressed office, industrial
and R&D as separate uses. At that time there were different density experiences and
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different occupational profiles on average that could be identified. In recent years, in
Silicon Valley these categories have merged together to the extent that building
departments regard them as a single type and indeed do not distinguish them as such.
The activity that occurs within a building can change from one tenancy to another and
many activities no longer meet old definitions at all.
Retail - More recent analyses by our firm have examined entertainment uses, such as
cinemas, along with retail and found them to be similar to other retail. As such the
definition for retail holds for entertainment uses as well.
Hotel- KMA has done a substantial amount of work on hotel projects and hotel jobs
housing nexus questions in recent years. Working with superior data on the job
composition in hotels and the income of hotel workers than existed in 1993, we have
found hotels to be far more intensive in employment at very low compensation levels
than the 1993 analysis indicates. In Santa Clara County the condition exists that most
hotel jobs (which are in the services) pay under $20,000 per year while median income
is in the range of $87,000 per year. As a result, even when there are multiple workers
per household, household income still ranks in the lower categories vis-&-vis the
median.
Consolidated Nexus
All commercial and industrial projects in Palo Alto are subject to the requirements of Chapter
16.47 of the Municipal Code. This code section contains threshold levels for size of projects
and exempted uses, but all commercial and industrial projects are subject to a single
mitigation requirement. Therefore the City wishes to utilize a hybrid nexus conclusion as
opposed to the multiple building types analyzed in the 1993 report.
In developing a single set of nexus figures for the number of households at various income
levels, we are recommending:
Housing Units per
100,000 sq.ft.Sq.Ft.
Affordabilit¥ Level Bldg. Area Bldg. Area
Very Low Income (Under 50% median)
Low Income (50% to 80% median)
Lower Moderate (80% to 100% median)
Upper Moderate (100% to 120% median)
7 .00007
15 .00015
8 .00008
8 .oooo8
38 .00038
The hybrid indicates more lower income units for hotels than determined by the 1993 analysis,
but based on more recent information, as indicated above, we believe the hybrid is well within
the supportable range.
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These figures are utilized in the next section to quantify the total mitigation or nexus cost. The
per square foot figures are provided for use in performance or build requirements. The figures
indicated above can be adjusted in a manner similar to the fee as a relationship to the total
nexus cost.
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SECTION II - AFFORDABILITY GAP AND TOTAL LINKAGE COST
The component of a nexus fee analysis that has undergone the most change since 1993 is the
affordability gap or cost of delivering housing affordable to lower- and moderate-income
households. Rent levels and housing prices have escalated dramatically over the past eight
years, making housing in Palo Alto increasingly out of reach to newcomers, except for the very
upper portion of the income spectrum. The market rent for a new two-bedroom apartment in
Palo Alto is now $2,760 per month (Table 1), requiring a three-person household to have an
income at about 140% of median income. Even older units now command rents that require
incomes over and above median levels. The picture for ownership units is even more severe.
A two-bedroom condominium that sells for $350,000 requires an income at a little over 150%
of median.
This section presents the affordability gap analysis or cost to make housing units affordable to
various income level households in Palo Alto. The conclusions of a nexus analysis, expressed
as the number of households in the lower and moderate income categories associated with
commercial/industrial buildings, is joined with the cost of assistance required to produce the
nexus or linkage cost.
Per City policy, the analysis is conducted assuming rental housing for the lower income tiers
and ownership units for the moderate-income tiers.
Income and Household Size Assumptions
Income definitions are established by HUD annually for varying household sizes. For estimating
the affordability gap, there is a need to match a household of each income level with a unit type
and size according to governmental regulations and policies.
The analysis provides evaluations for rental apartments as well as ownership condominiums.
While the analysis is conducted assuming four income categories, the total nexus cost is
calculated assuming the most likely occupancy scenario. Thus, multi-family rental units is the
assumed housing type for the under 80% of median income groups. A condominium unit is the
assumed type for the 80% to 120% of median group. The average three-person household is
assumed to be accommodated in a two-bedroom unit per industry standard.
Cities have a policy choice in the selection of the income level for the analysis. When addressing
an income range, the city can use the upper end of the range or the average. Not all households
demanding housing will have incomes as high as the upper limit of households in each median
category. In this analysis, the income level is 10% below the upper end of the range. In other
words, very low income households are assumed to average 40% of median, low income
households 70% of median, lower moderate income households 90% of median and upper
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moderate inco ouseholds 110% of median income. This is similar to the approach used in
the 1993 analysis and is employed by most cities.
Tables 2 through 6 present the analysis summarizing affordable rent levels and prices for
ownership units for various size households at the income levels. The analysis commences with
current income median levels for Santa Clara County which are:
1 Person:$61,100
2 Person:$69,850
3 Person:$78,550
4 Person:$87,300
In Table 2 the income level is multiplied by 30% to estimate total cost of affordable housing,
adjusted for utility allowance to arrive at affordable rent for various size units. In Table 3, the
affordable rent level is adjusted to annual rent from which operating expenses are deducted to
establish net operating income. Net operating income is converted to a value supported
assuming an 8% capitalization rate. The value supported is the amount that can be spent to
develop the unit without subsidy. If development costs exceed the value supported, there is an
affordability gap for which a subsidy is needed to bridge the gap.
A similar analysis was conducted for ownership units. Table 4 summarizes the analysis for
households at 110%, 90% and 70% of median income. For ownership units, the assumption has
been used that affordable homeownership costs do not exceed 30% of gross including
condominium homeowners association dues, insurance and property tax. Again, this analysis
was conducted consistent with City of Palo Alto policies and practices.
Development Costs
The development cost for new residential units in Palo Alto was assembled from a number of
sources. We reviewed appraisals and spoke with developers to estimate land cost. KMA
contacted developers of both rental and condominium projects in Palo Alto and nearby cities.
Finally, KMA is actively working on a number of rental and condominium projects at various
locations in the Silicon Valley area and has recent developer pro forma financial analyses.
From the above sources, KMA prepared a summary of total development costs, broken down
into the major cost components: land, direct or construction costs, and indirect costs, such as
design and engineering, fees, financing, etc. Tables 5 and 6 summarize total development
costs for a typical two-bedroom unit. Costs expressed on a per unit and per square foot basis
are indicated below:
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Unit Size Apartment Condominium
Two Bedroom Unit
Per Unit
Per Sq. Ft.
950 Sq. Ft
$258,000-$340,000
$270-$360
1,200 Sq. Ft.
$350,000-$430,000
$29O-$36O
It is important to note that costs are especially high in Palo Alto primarily due to high land
costs. Another factor that impacts costs is the small parcel sizes available for development.
Building and parking configuration for multi-family projects on smaller lots can become very
expensive.
Housing development costs are intended as averages, and are, in fact, at the lower end of the
average range. The lower end of the range represents a minimum; it is probably virtually
impossible to construct units at the lowest end of the range at this time.
A note about the timing of this analysis (late summer 2001) is important. Most of the recent
development projects were marketed (renting or selling) or were assembled as projects at the
peak of the economic boom of the late 1990’s. It has been less than eight months since the
boom crested, and for the most part, only the very top end of the residential market has begun
to soften. But in order to avoid using residential prototypes and values that represent a boom
period that may not return for some time, we have utilized hypothetical projects using
somewhat modified land prices and development costs. In this manner, we believe we have
avoided an overstatement of the affordability gap in the event the current downturn continues
for a period.
Affordability Gap
The affordability gap is the difference between the cost of developing a residential unit and the
amount a household can afford to pay.
Tables 7 and 8 summarize the affordability gap analyses for a three-person household at various
income levels. To calculate an affordability gap, the total development cost is subtracted from
the supportable unit value. As previously discussed, it is assumed that households with less
than 80% median are ~accommodated in apartment units while the higher income categories
are in condominium units.
The affordability gaps are presented on a range basis. To be conservative, the lower end of
the range is utilized in the analysis.
As shown in Tables 7 and 8, the affordability gap conclusions used in the analysis are:
¯$225,000 for households in the under 50% of median income category, based on a
three person household at 40% of median income in a two-bedroom apartment unit.
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¯$138,000 for household in the 50% to 80% of median income category, based on a three-
person household at 70% of median in a two bedroom apartment units.
¯$159,000 for households in the 80% to 100% of median income category, based on a
three-person household at 90% of median in a two-bedroom condominium unit.
¯$108,000 for households in the 100% to 120% of median income category, based on a
three-person household at 110% median income in a two-bedroom condominium unit.
The gap for the 90% of median income category is higher than for the lower income category
(50% to 80%) due to the fact that the median income household is assumed to be
accommodated in a condominium unit, which is more expensive to build, while the lower
income category is in a-rental unit.
TotalLinkage Costs
The last step in the linkage fee analysis marries the findings on the numbers of households at
each of the lower income ranges associated with commercial/industrial type buildings to the
affordability gaps, or the costs of delivering or housing for them in Palo Alto.
Tables 9 and 10 (rental and condominium) summarize the numbers of households associated
with commercial/industrial building presented at the end of Section I and the affordability gaps.
Each evaluation identifies the "Nexus Cost Per Square Foot" presenting the results of the
calculation: number of units times affordability gap, divided by 100,000 square foot to bring the
conclusion back to the per square foot level.
The Summary Table presents the following conclusions:
Rental Affordability Gap
Under 50% Median Income
50% to 80% Median, Income
Ownership Affordability Gap
80% to 100% Median Income
100% to 120% Median Income
1per 100,000 sq.ft, of building area
Total
Number of Nexus Cost
Households1 Per Sq.Ft.
7 $15.75
15 $20.70
8 $12.72
~$ 8.64
38 $57.81
These costs express the total linkage or nexus costs for commercial and industrial building types.
These total nexus findings and cost represent the ceiling for any requirements placed on new
construction for affordable housing. The totals are not recommended levels; they represent only
the maximums established by this analysis, below which fees or other requirements may be set.
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In establishing the total nexus cost several conservative assumptions were employed in the
analysis that result in a total nexus cost that is probably understated. These conservative
assumptions include:
The methodology for discounting double income households essentially removes almost
all two-income households from the lower income strata (by assuming the multiple
incomes place the households in higher income categories).
Using small households produces lower affordability gaps than larger households in larger
units.
Assuming the lower end of the development cost and affordability gap range produces
the low end of the nexus cost range.
Only direct employees are counted in the analysis. Many indirect employees are also
associated with each new workspace. Indirect employees in an office building, for
example, include janitors, window washers, landscape maintenance people, delivery
personnel, and a whole range of others. Hotels do have many of these workers on staff,
but hotels also "contract out" a number of services that are not taken into account in the
analysis.
In summary, many less conservative assumptions could be made that would result in higher
linkage costs.
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SECTION III - MATERIALS TO ASSIST IN SELECTING THE FEE LEVEL
The purpose of this section is to provide information to assist policy makers in identifying an
appropriate fee level for Palo Alto. As indicated in the previous section, the nexus analysis,
coupled with the affordability gap, established the total nexus or linkage cost supported by the
analysis. The fee may be set at any level below the maximum to recognize other policy
objectives of the City.
Two different sets of information are provided in this section. The first is a summary of total
development costs to put fee amounts in context. The second is a summary of what other
cities, both locally and nationally, are charging for housing and other mitigations.
Total Development Costs
Total development costs for four different prototype projects in Palo Alto have been
assembled. These costs were developed from projects in processing by the City, from
contacts with developers, and from KMA’s experience with projects elsewhere in the Silicon
Valley area.
Palo Alto is an expensive city in which to develop real estate projects. Primarily it is land that
is costly over and above other cities. In addition, parking and other city requirements increase
costs.
Land and high costs in Palo Alto are supported by a very strong rent and value structure. In
fact, roughly a year ago, Sand Hill Road in adjacent Menlo Park made national news for
achieving rents in excess of downtown Manhattan. While Sand Hill Road may not be
representative of the broader area, Palo Alto in general is a prestigious address that
commands the top of the rent and value spectrum in Silicon Valley. As a result, building
design, materials and other aspects of development are usually at a higher standard, again
costing more on average than if built in another city.
As with residential development costs, we note that this is an uncertain time in the economic
cycle. Most of the projects now in development in Palo Alto were created and financed over
the past two or three years when the high tech economic boom was in full force. The high
tech boom crested about a year ago and since fall 2000 conditions have declined with no clear
indications about what lies ahead. As a result, we recommend leaning toward the lower end of
the cost range expressed in the tables since projects in the future may be a little more modest
than what has been produced over the last five years.
Four prototypes were selected for cost summary as presented in Tables 11 and 12. A few
comments on each.
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Office/High Tech, Research Park - This prototypical project is intended to address
new buildings in Stanford Research Park and elsewhere in the "industrial" area of the
City. The prototype is for large buildings, in excess of 100,000 square feet. Parking in
above grade, or in ? cases underground for a portion of the spaces, at a ratio of 1
space per 300 squa~- eet of building space. The land component is an estimate to
cover a range of conditions: in the Stanford Research Park, sites are large and floor
area ratios (FAR’s) lower, and land lease terms information is difficult to obtain; in
other situations FAR’s are higher. Because vacant parcels are very rare, most sites
entail demolition or other expense, resulting in costs of at least $75 per square foot of
land area. The cost range is estimated at $350 to $450 per square foot of building
area.
Office/Retail Downtown - This prototype is a small project on a downtown area site.
The building is three stories, the ground floor being retail and office on the upper floor.
The assumption is that the project meets the City’s conditions to make an in-lieu
payment for parking rather than providing it on site. According to City staff, most
properties have been paying into an assessment district and do not have the
obligation to pay for all the code-required space at four per thousand square feet. The
assumption is that 50% to 75% of the spaces are still owed. Clearly land values for
individual parcels in the downtown are partly driven by the status of the parking
obligations. The estimated cost range is $330 to $415 per square foot.
Hotel- The hotel prototype is a full service hotel, upscale product. The room rates
achievable make this the logical product to build. Parking is probably below grade for
at least a portion of the need at 1.1 spaces per room. All in costs are estimated at
$212,000 to $290,000 per room, which is roughly equivalent to about $350 to $450 per
square foot.
Retail- The prototype example is drawn from new construction in Stanford Shopping
Center where three free standing buildings, ranging in size from about 7,000 square
feet to 63,000 square feet, have recently been constructed. Outside of shopping
centers and strong downtowns, retail construction has been minor in Silicon Valley
during the boom due to the high land prices and the inability of most retail to compete
with other land uses in site acquisition. Again, total development costs are estimated
in the $330 to $440 per square foot range.
In summary the "all-in" cost range in Palo Alto, inclusive of land, financing and all indirect
costs, is in excess of $300 per square foot and frequently exceeds $400 per square foot.
Alternative fee levels can be evaluated in the context of total costs. For example, a fee of $5
per square foot would represent approximately 1.0% to 1.5% of total costs. A fee of $10 per
square foot would be more in the 2% to 3% range.
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Other Jurisdictions Housing Fee Programs
It is always of interest to policy makers to know what other cities and counties have in place in
the way of similar fee programs. Table 13 provides a chart summarizing other programs
ranging from elsewhere in Silicon Valley to other major cities in the United States.
In Silicon Valley, Menlo Park’s recently enacted $10 housing fee stands out from other
programs in place. Most cities in the Valley have no programs in place but several are (or
were until recently) actively considering new fee programs. The Silicon Valley Manufacturer’s
Group even considered a position on the matter but decided to stand back.
The programs of other major metropolitan areas should be of interest to Palo Alto, because
Palo Alto, unlike most small jurisdictions, commands a rent and value structure similar to major
city downtowns. San Francisco recently raised its housing fee to $11.34 and is scheduled to
go to $14.00 in 2002. In addition, San Francisco currently has another $8 of impact fees in
place to cover transit ($5), parks ($2) and childcare ($1). A study has recently been completed
to determine the ceiling for a new transit fee with a finding that would allow the fee to be
increased substantially on some building types.
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TABLE 1
RENTAL UNIT - MARKET RENT LEVELS - SUMMER 2001
HOUSING LINKAGE UPDATE ANALYSIS
CITY OF PALO ALTO
Recently Completed Projects
Older Existing Units
Studio
$1,400
1 BR
$1,800
$1,600
2 BR
$2,780
$2,100
Sources: Yahoo Real Estate; ApartmentGuide.com; Homestore.com
Prepared by: Keyser Marston Associates, Inc.
17175.003~Multi-family Rental update.xls\Tablel ; 9/14/2001
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TABLE 5
RENTAL UNIT DEVELOPMENT COSTS
HOUSING LINKAGE UPDATE ANALYSIS
CITY OF PALO ALTO
Numbers Rounded 000’s
Assumptions - RM 30 Zoning
Land size (Acres)1.5
Based on a 45 unit project
Average two-bedroom unit @ 950 Sq Ft.
Garage or Podium Parking with Units Above
Cost Ran~te Per Avera~le Unit
Low Ranqe Hiqh Ran.qe
Land $80,000 -$150,000
Construction1 130,000 -140,000
Indirects (Includes Impact Fees)38,000 -40,000
Financing 10,000 -11,000
Total Development Cost $258,000 $341,000
Total per Sq. Ft.$270 $360
Excluding Land $190 $200
Note: This is a hypothetical development reflecting a slowed economy rather than late 1990’s peak activity.
Prepared by: Keyser Marston Associates, Inc.
17175.003~Vlulti-family Rental update.xls\Table5; 9/14/2001
TABLE 6
CONDOMINIUM UNIT DEVELOPMENT COST1
HOUSING LINKAGE UPDATE ANALYSIS
CITY OF PALO ALTO
Numbers Rounded 000’s
Assumptions
Land Size (Acres)1.50
Dwelling Units/Acre 30
Average two-bedroom unit @ 1,200
Parking One Level Underground
Sq Ft.
Land ($75-100/sf)
Construction
Indirects (Includes Impact Fees)
Financing
Total Development Cost
Total per Sq. Ft.
Excluding Land
Cost Range Per Average Unit
$110,000 -$150,000
170,000 -200,000
56,000 -65,000
14,000 -16,000
$350,000 -$431,000
$290 $360
$200 $230
This is a hypothetical development representing a slowed economy rather than late 1990’s peak.
Prepared by: Keyser Marston Associates, Inc.
17175.003kMulti-family Ownership update.xls\Table6; 9/14/2001
TABLE 7
RENTAL UNIT AFFORDABILITY GAP
HOUSING LINKAGE UPDATE ANALYSIS
CITY OF PALO ALTO
Assumes two bedroom unit; three person household.
Target
Income Level
% AMI
40%
70%
90%
110%
Affordability
Gap Per Unit1
Low Range
$225,000
$138,000
$78,000
$19,500
High Range
$308,000
$221,000
$161,000
$102,500
Prepared by: Keyser Marston Associates, Inc.
17175.003\Multi-family Rental update.xls\Table7; 9/14/2001
TABLE 8
CONDOMINIUM UNIT AFFORDABILITY GAP
HOUSING LINKAGE UPDATE ANALYSIS
CITY OF PALO ALTO
Assumes two-bedroom unit and three person household
Target Supportable
Income Level Home Price1
% AMI
110%$242,000
90%$191,000
70%$140,000
Development Cost2
$350,000
$350,000
$350,000,
Affordability Gap Per Unit
$108,000
$159,000
$210,000
See Table 4
See Table 6 assuming low range cost
Prepared by: Keyser Marston Associates, Inc.
17175.003\Multi-family Ownership update.xls\Table8; 9/14/2001
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TABLE 11
HOTEL AND RETAIL PROTOTYPES
TOTAL DEVELOPMENT COSTS
HOUSING NEXUS UPDATE ANALYSIS
CITY OF PALO ALTO
Product Type
Hotel
Full Service/Upscale
Retail
Shops/Restaurants
In Centers
Parking
Ratio
Development Costs
Site Work
Building
FF&EFF.I.’s
Indirects
Financing
Parking:
Room/Bldg. Area
Garage/Subterranean
1:1 RM
Cost Per Room
$2,000 $4,0Q0
$90,000 $110,000
$25,000 $35,000
$117,000 $149,000
$35,000 $45,000
$12,000 $15,000
$164,000 $209,000
$28,000 $50,000
Structure/Sub
4:1000 Sq Ft
Cost Per Sq Ft
Leasable Area
$5
$90
$35
$130
$33
$13
$176
$8
$100
$50
$158
$4O
$16
$214
$55 $75
Land $20,000 $30,000 $100 - $150
Total, incl Land (rounded)
Per Sq. Ft. Bldg. Area
(Sq. Ft/Room)
$212,000 $289,000
$353 $482
(600)(600)
$330 - $44O
Prepared by Keyser Marston Associates, Inc.
File name: 17175.003\commercial.xls;other;9/14/2001;mtn
TABLE 12
OFFICE PROTOTYPES
TOTAL DEVELOPMENT COSTS PER SQUARE FOOT OF BUILDING AREA
HOUSING NEXUS UPDATE ANALYSIS
CITY OF PALO ALTO
ProductType
Size
Parking
Ratio
Development Costs ($/SF Bldg, Area)
Site Work
Building
Tenant Improvements
Indirects (25%)
Financing
Parking
(S/space)
Land (psf bldg. area)
Total, including Land (rounded)
Office/High Tech
Research Park
3-4 stories
Over 100,000 sq.ft.
Above grade structure
3.3:1,000
$4 -$6
$80 -$100
$40 - $50
$124 $156
$31 -$39
$12 -$15
$167 $210
$65 $100
$20,000 -$30,000
$100 -$150
$352 -$460
Office/Retail
Downtown
3 stories
In-Lieu Payment
4:1,000
$3 -$5
$125 -$150
$30 -$40
$158 $195
$40 -$49
$16 -$20
$214 $264
$66 $99
$50 -$50
$330 -$413
’ Assumes obligation for In-Lieu Parking Fee ($33,000/space) for 50%-75% of spaces required.
Prepared by Keyser Marston Associates, Inc.
File name: 17175.003\commercial.xls;office;9/14/2001 ;mtn
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ATTACHMENT B
Jobs Housing Nexus Analysis
City of Palo Alto
Prepared for:
City of Palo Alto
October 1993
Portions Revised March 1995
Keyser Marston Associates, Inc.
Golden Gateway Commons
55 Pacific Avenue Mall
San .Francisco, California 94111
500 South Grand Avenue, Suite 1480
Los Angeles, California 90071
12555 High Bluff Drive, Suite 160
San Diego, California 92130
KI~¥~ER MARSTON ASSOCIATES
TABLE OF CONTENTS
Introduction
Section I - The Nexus Concept and Major Issues
Section II - The Palo Alto Economy and Employment Growth
Section rn - The Nexus Numerical Analysis
Section IV - Total Housing Linkage Costs
Page
i
1
8
14
22
Appendix
K E Y S E R M A R 5 T O N A s s o/;__I,# T E Sr=g .I N C.
INTRODUCTION
The following report is an analysis of jobs and housing relationships in the City of Palo
Alto, prepared by Keyser Marston Associates, Inc. for the City of Palo Alto according
to the contract agreement. The report is a "nexus" study to meet the requirements of
AB 1600, as amended to Government Code Section 66001 of the California Code, in
support of the City’s housing linkage fee program.
In 198~ the City of Palo Alto adopted Chapter 16.47 of the Municipal Code which
specified that commercial and industrial projects contribute to programs that increase the
City’s low and moderate income housing stock. This chapter provides that the develop~
provide affordable housing units as a condition of development or may, as an alternative,
pay an in Iieu fe. In consideration of changing times and the current state of the law,
the code and program were reviewed in 1992 and it was determined that a nexus study
would be advisable. In addition, it was concluded that certain modifications to the
program and use of fee revenues should be considered. This analysis is the nexus study
consistent with current statutes and standards.
The report is organized into four sections as follows:
Section I -- presents a summary discussion of the nexus concept and
some of the key issues surrounding nexus analyses for jobs and housing
relationships.
Section II -- contains an overview of the Palo Alto economy and
employment growth which is fundamental to the linkage of jobs and
housing in Palo Alto.
Section 1~I -- contains the numerical analysis which determines the
number of median, low, and very low income households associated with
each ~ of commercial and industrial building.
Section IV -- presents an affordability gap analysis and a quantification
of the costs to deliver affordable housing for each type of building, or the
"Total Linkage Cost" which sets a maximum fee level.
Appendix A -- provides more information on data sources and
assumptions utilized in the analysis.
The analyses in this report have been prepared using the best and most recent data
available. Local data as prepared by the City of Palo Alto Planning Department and
other sources was utilized wherever possible. Other sources such as the U.S. Census,
17172\0OO1.027 K E "f 5 E R M A R 5 T O N A s 5 olt~leJi T E 5 ] N C.
the State of California were utilized extensively. While we believe that all the sources
of data are sufficiently accurate for the purposes of this analysis, we cannot guarantee
their accuracy. As a result, Keyser Marston Associates, Inc. assumes no liability for the
conclusions drawn from information from other sources.
K~¥s~R MARSTON ASSOI~TES IN(:.
17172\0001.027
SECTION I: THE NEXUS CONCEPT AND MAJOR ISSUES
Introduction
This section ouflin= the nexus concept and some of the k~y issues surrounding the
enactment of a fee on non-residential construction to provide a source of revenue for
affordable housing programs. These programs are utilized to increase the supply of
affordable units or sezvices related thereto. The program in Palo Alto assists in making
housing affordable to median and lower income households.
The nexus analysis and discussion focuses on the relationships among development,
growth, employment, income and housing. The analysis yields a causal connection
between new commercial/industrial construction and the need for additional affordable
housing, a connection that is quantified in terms of total housing linkage costs related to
commercial!industrial space expressed in dollars per squaxe foot. This analysis, and the
re.suiting maximum nexus amount, does not address existing housing problems and needs;
nor does it suggest that development and its relationships are the only cause of housing
affordability problems, nor that the development community should bear the full cost of
addressing affordability problems.
The NoIlan Decision and the Enactment of A.B. 1600
The law has always required the existence of a rational basis for implementing a fee on
one activity to raise funds for another activity. In Nollan v, C..~lifornia Coastal
~0mmission, the United State, s Supreme Court sharpened and clarified this requirement,
and specified that there exist a "rational nexus" between a development charged a fee and
the purpose of the fee. The d~velopment subject to the fee must cause or contribute to
the social problem the fee is designed to address.
Partially in response to the Nollan decision, the California State Legislature enacted
AB 1600 (sections 66001 et seq. of the Government Code). AB 1600 requires local
agencies proposing to enact a fee on a development project to identify the purpose of the
fee, the use of the fee, and to determine that there is "a reasonable relationship between
the fee’s use and the type of development project on which the fee is imposed." The
local agency must ensure that there is a reasonable relationship between the amount of
the fee and the cost of mitigating the problem the fee is addressing. (Government Code
$66001). AB 1600 also imposes special accounting requirements which track the use of
fees.
17172\0001.027 K E "z S E R M A R S T O N A s s OF~gb ~, T E S I N C.
Studies prepared by local governments designed to carry out the intent of the Nollan
decision and AB 1600 are kne~~ as "nexus" studies. The study establishes and
quantifies a causal link or "nexus" between new commercial/industrial development and
the need for housing affordable to the new workers.
The Nexus Methodology
This section sets forth the basics of the nexus methodology. In summary, the calculation
works in the following manner. We assume a prototypical 100,000 sq.ft, building of a
certain type; say, office. For that office building we then make the following types of
calculations.
¯¯We estimate the total number of employees working in the building based
on average employment density experience.
¯We use occupation and income information for typical job types in the
building to calculate how many of those jobs pay at very low, low, and
median income levels.
We know from the Census that most of these lower income employees are
members of households where more than one person is employed; we use
various factors to calculate the number of low income households
represented.
We then make a number of adjustments, some of which are discussed in
the paragraphs below, to discount for people entering the work force who
already have housing in the City, ,:~2r people who will work at jobs in the
City but live outside of the area, and for existing jobs that are phased out
because of changing industries and density in existing buildings.
Finally, we tak~ the lower income households and multiply them by the
capital and related costs of delivering (through either purchase or new
construction) lower income housing units, and then divide that by the
100,000 sq.ft, to come up with a dollars per square foot figure.
Causation and other issues are discussed below, and the nexus methodology, analysis,
and findings are set forth in more detail.
17172\0OO1.027
The Relationship Between Job Growth and Population Growth
The social issue driving this analysis is the growth in new lower income households.
New population growth in most U.S. regions occurs primarily as a result of growth in
jobs. Over the long term, the vast majority of growth in the State of California and its
subregions is job driven. The arrival of new population creates a new "secondary"
demand for jobs in retail outlets and services which follow. Growth in the greater Bay
Area region is predominantly job driven. Most people coming to the region would not
come to the area ff they could not expect to find a job. If born there, they would not
stay without jobs. This is a long-term occurrence. In the short-term, economic cycles
and other factors can result in population growth without the jobs to support the growth.
If an economic region in the U.S. does not maintain job growth, there is an out-migration
to regions where job growth is occurring. Many cities in the Midwest are examples.
At the lower income levels, relocation and migration are particularly job driven. No
housing is affordable to those groups without a job (or without public assistance).
The Relationship Between Construction and Job Growth
Once it is understood that population growth, especially low income population, is
predominantly job driven in the greater Bay Area region, the question arises as to the
cause of employment growth itself.
Employment growth does not have "one cause." Many factors underlie the reasons for
growth in employment in a given region; these factors are complex, interrelated, and
often associated with forces at the national or even inmmational level. The nexus
argument does not make the case that the construction of new buildings is responsible for
growth. However, especially in the Bay Area region, new construction is uniquely
important, first, as one of a number of parallel factors contributing to growth, and
second, as a unique and essential condition precedent to growth.
As to the first, construction itself encourages growth. In times of growing economy, the
most rapidly growing areas in the state have been those where new construction was
vigorous as a vital industry. In regions such as the Bay Area where multiple forces of
growth exist, the political and regulatory environment often join forces with the
development industry to attract growth by providing new work spaces, particularly those
of a speculative nature. The development industry frequently serves as a proactive force
inducing growth to occur or be attracted to specific geographic areas or jurisdictions.
17172\0001.027 K E Y S E R M A R S T O N A s s Ol~hg T E S ] N C.
Second, commercial/industrial buildings bear a special relationship to growth, different
from other parallel causes, in that buildings are a condition preeeden~ to growth. Job
growth does not occur in modern service economies without buildings to house them.
Unlike other factors that are responsible for growth, buildings play the additional unique
role that growth cannot occur without them.
The nexus argument does not rna~ the cas~ that new buildings a_~ the unique cause of
growth. In economically distressed areas of the country, new buildings often stand
empty, and even in healthy economies, markets become overbuilt from time to time
leaving large amounts of vacant space waiting for job growth to catch up. However, the
special relationships between buildings and growth means that the new comme.rcial/
industrial construction activity bears a special relationship to new employment growth.
Outside of recessionary periods when there is no growth, the most rapidly growing areas
in the state ~ those where new construction is occur~g most vigorously.
Addressing the Housing Needs of a New Population vs. the Existing Population
The City of Pale Alto has clearly documented that the housing needs of a substantial
portion of the existing median and lower income families are not met. This existing
housing shortage, especially at the very low, low, and moderate income levels, is
manifested in numerous ways such as exceedingly long home-to-work commutes and
payment of far more than the percentage of income for housing set forth in fedt,-ral and
state gnidelines. According to the 1990 Census, a full 73 % of the renters with household
incomes under $20,000 per year pay 35 % or more of their income on rent.
This nexus study does not address the housing problems of the existing population.
Rather, the study focuses exclusively on documenting and quantifying the housing needs
of new working population accommodated in new non-residential structures. The
analysis is a "marginal" one; since it is concerned only with fees on new
commercial/industrial construction; it addresses only new housing demand in the median
to lower income categories.
This analysis also assumes that new housing affordable to lower income households is
not being added to the supply. This assumption derives from data relating to the cost and
profitability of development of such housing, which leads to the conclusion that such
housing is not financially feasible for development by the private sector unassisted. If
this were not the case and significant numbers of units were being added to the supply
to accommodate the same income groups as addressed by the fee, then an adjustment
would be in order. If the Pale Alto area were experiencing significant vacancy levels in
residential units, particularly units affordable to lower income households, then the need
for the units would require reexamination.
17172\0001.027 K E Y S E R M A R S T O r; A s s O~P ~, 7 E S ~ N C
Employee Mobility
It is obvious that a given new building may be occupied partly, or even perhaps totally,
by employees relocating from elsewhere in the City. Buildings are often leased entirely
to firms relocating from somewhere else in the same jurisdiction. However, when local
people take a new job, or when a firm relocates to a new building, there is a space in an
existing building which is vacated somewhere else in the region or city. That building
in turn may be filled by some combination of newcomers to the area and existing
residents, but somewhere in the chain there are jobs new in the City of Palo Alto.
Except for a certain mount of demolition which is addressed in the ordinance, space for
employees does not disa~. In summary, new buildings bring in new employees,
although not necessarily inside of those new buildings themselves.
A related question deals with what income level employees are finding the new jobs.
Recruiting for some new employees, particularly at the lower skill levels is often done
locally. However, the chain of events is similar to the chain discussed above with
respect to office space; ff local lower income people fill new jobs, additional work
opportunities become available for new residents. Overall, at the regional level, there
is a new net increase in low income jobs. People at any skill level move to areas where
jobs are known to be available for them.
Changing Indastry Factor
Another question of particular interest in a built-up urban area is that of demolition and
changing use or density in existing buildings. For commercial and industrial buildings,
the issue is addressed in two ways. First, the ordinance provides for an adjustment in
the event one non-residential building is removed to make way for another on site. If
a 10,000 sq.ft, office building is demolished to build a 50,000 sq.ft, office building, then
the net new space is 40,000 sq.ft.
An adjustment is also made in the linkage analysis to recognize changes that may be
occurring in existing buildings. When induslries are declining or undergoing adjustment,
there may be a reduction in the employment in existing space such that some of the new
space added to the inventory is occupied by employees that are transfers from existing
buildings and not replaced. An example of a declining industry at this time is aerospace;
many buildings that housed aerospace firms may be less densely occupied at this time
than they were five years ago. In Palo Alto there was a shift in the 1980’s of R&D
buildings transitioning into more dense office use. In the 1990’s there is evidence of a
shift back to laboratory type activities, now in the bioteeh field. As a result there is a
reduction of employment density occurring in some buildings, particularly in Stanford
Research Park. This loss of density may not be made up by the pressures towards
increasing density in other existing buildings due to maturity and cost factors. To
17172\0001.027 K E v s E R M A R S r O ,~ A s s o~ T E S I r< C.
recogniz~ this shift, a 10% discount adjustment has been made in the analysis. This is
to say that for every 10 employees that will work in new space in Palo Alto, one is
assumed to be a transfer from an existing space that is not replaced. (See Section II for
more discussion).
Indir~ Employment and Multipliers
The numerical nexus analysis addresses direct employment only. In the case of the office
building, for example, direct employment coven the various managerial, professional and
clerical people that work in the building; it does not include the janitorial wodmt’s, the
window washers,, the security guards, the delivery services, the landscape maintenance
workers, and the many others that are associated with the normal functioning of an office
building. These indirect employees tend to be the many service workers at the lower end
of the pay scale. No data sources were located that deal with indirect employees in
various type buildings. If one thinks about who the lowest income workers are, one can
observe that lower income workers include construction laborers, transportation worlaa’s,
and a whole host of service workers who do not work in any type of building as regular
employees but whose jobs are associated with such structures. In other words, any
analysis that ties lower income housing to particular types of buildings will continue to
understate the demand. Thus, confining the analysis to the direct employees does not
address all the low income workers associated with each land use (or type of buildings)
and significantly understates the impacts.
If the door were open to the indirect employees, one could take the analysis further and
deal with the question of multipliers. Multipliers refers to the concept that the income
generated by certain types of jobs through the economy resulting in additional
jobs. We are not aware of any ec~:~:~c models that have addressed multipliers for
lower income households specifically, and for purposes of producing a conservative
nexus amount, our study omits such multiplier effects.
Lower Income Households and Assistance Needs
If a region is growing and jobs are being created at all ends of the pay scale, how do
people with the low paying jobs manage? Will not lower income people come for the
jobs even without affordable housing7 A very short answer to this question from a
regional economics perspective is that the following will occur:
(1)Lower income households will continue to be forced to pay higher and
higher percentage of trieir household income on housing, causing stress
and related social problems and resulting in less available income for other
essential needs. Crowding multiple households into single units is
another. Some share of households may eventually become homeless;
KEYSER M A RSTON ASSOCIATES INC.
17172\OOO1.027 Paoe 6
(2)Lower income households will be forced to live at greater distances from
their place of employment, causing greater traffic and related problems;
and
O)Ultimately, the limited expansion capabilities of an inexpensive labor pool
constrain growth, as has been occurring in Palo Alto and Silicon Valley
over the past decade.
Discount for Employees that will Live Outside Palo Alto
The analysis makes an adjustment for the fact that not all of those who work in Palo Alto
would elect to live in Palo Alto even ff housing were affordable. At the current time
somewhere in the range of 15 % to 20% of those who work in Palo Alto actually live
there. The percentage has been falling over recent decades, primarily due to the
extremely high cost of housing in Palo Alto. As the 1990 Census and studies conducted
of Stanford Research Park employees indicate, the percentage of workers that commute
from significant distances such as Alameda County has risen substantially ovor the last
30 years. The work/live factor in Palo Alto utilized in the analysis is 33%, or
conversely an out commute of 67%. The 33 % factor is similar to the experience of other
Peninsula cities that have a more diverse and affordable housing stock than does Palo
Alto and thus are better able to house local employees.
This is an extremely conservative approach and it is arguable that no discount should be
made at all. Subsidized housing opportunities are in short supply; if housing were built
for all low income employee.s, 67% would not remain vacant. If such housing were
offered with a priority given to households with members employed in the City, most
would be taken. This is all that the nexus requires; the statutory and constitutional nexus
standard mandates that the housing units built with the funds contributed by commercial
structures are reasonably available, from a regulatory and practical perspective, to the
workers in those structures. Most non-resident workers, especially poor workers, would
live closer to their jobs if they had the opportunity to do so, but instead arc required to
commute long distances primarily for economic reasons. Given this shortage of
subsidized units and commute-driven impetus to live close to jobs, this study could
reasonably have assumed that a far higher percentage of the units offered would be
occupied or occupiable by workers in the structures contributing the fees.
KEYSER M A RSTON A 5So¢1 T E S INC.Page "~17172\0001.027
Qualifiers to the Analysis
The analysis presented in this report has been based on readily available information.
The 1990 U.S. Census, which is now being distributed in sections, was frequently
utilized. For some inputs, we did have to rely on the 1980 Census since the release of
current 1990 data is still in progress. The other principal data source was the California
State Employment Development Department (EDD). Local data was taken into account
wherever available. The appendix section presents a full documentation of sources and
data utilized.
It should be recognized that any analysis of this nature, no matter how in-depth, contains
a great many numbers and judgments relating to them. It will always be possible to take
issue .with a specific number. We do not believe, however, that adjusting one or several
individual numbers would fundamentally alter the conclusions of the analysis.
K E Y s E R M A R s T O N A S S O.C I ~ T E S I N C.
17172\0001.027
SECTION !!:THE PALO ALTO ECONOMY AND EMPLOYMENT GROWTH
Introduction
The nexus concept is based on a series of linkages: economic and employment growth
and building construction, employees and households, households and housing demands,
with the linkages being capable of segmentation by income level. Through these linkages
a direct relationship between construction of new work places and demand for additional
housing units affordable to median and lower income households can be established. To
initiate the review, it is useful to examine the dynamics of the city of Palo Alto’s
economy and growth dynamics and how they affect the linkages that are the foundation
of the linkage fee program.
The City of Palo Alto is a small geographic area (about 26 square miles) located within
larger geographic and economic regions. Since Palo Alto is within Santa Clam County,
most of the economic data available is for the county as a whole. More accurately from
an economic activity perspective, Palo Alto is located at the heart of the Mid-Peninsula
economy, the area coveting the middle and lower third of San Mateo County and
northern Santa Clara County. This area, familiarly known as Silicon Valley, has been
one of the a leading growth areas in the United States over the past decades and a world
leader in technological developments. These areas are sub~ of the San Francisco Bay
Region economy.
Historic Context and Stanford University
Palo Alto was incorporated in 1894 on lands purchased and subdivided by an
entrepreneur for the purpose of providing a college town for newly established Stanford
University. Over the decades the city grew with residential and-commercial
neighborhood areas largely related to the university activity. The Stanford University
complex remained outside the city limits. In the 1950’s, Stanford Shopping Center,
Stanford Research Park and a portion of the medical center were incorporated into the
City, but the University itself and portions of the medical center remain outside the City.
Stanford University has always played a key role in the Palo Alto economy and the
evolution of the City. As an institution of international stature, Stanford has attracted
faculty, staff, visitors, scientists and entrepreneurs to the area. The presence of Stanford
is often given credit to the establishment of the Silicon Valley and the center of U.S.
computer oriented technology in the latter 20th century.
K E Y S E R M A R S T O N A s s O c I A "f E S l N C.
17172\0001.027 P,,g= 9
Stanford Research Park has played a particularly key role. Founded in 1951 as Stanford
Industrial Park, it was the first modern industrial park to be developed by an educational
institution. The concept was fostered by a Stanford administrator who helped a network
of Stanford graduate students strengthen ties between their fledgling companies and the
University and create a center of high technology. In 1980, the name was changed from
"Industrial" to "Research" to recognize the changing character of the park. Hewlett
Packard, Varian, Lockheed, and Syntex are a few of the Well recognized giants located
in the park, bearing the Palo Alto address.
Population and Households
As a largely built out city, the population of Palo Alto has remained fairly constant over
recent decades; the 1990 Census count was 55,900 persons. Like most of California, the
composition of the population has shifted. It is now older and more ethnically diverse.
Also consistent with state and national trends has been the decrease in household size,
which accounts for the condition that the number of housing units has continued to rise
while the population has been stable.
The single most outstanding characteristic of the Palo Alto population is its affluence.
During the 1980’s decade median household income increased by 123.6% to a level of
$55,333 in 1990. During this period the value of the median owner occupied housing
unit jumped by over 200% to a figure of $457,800. Median rent also inerea~
substantially at a rate of 137% over the period. At these levels, housing affordability is
a major issue for new workers in the area.
Employment in Palo Alto
Palo Alto is a "job rich" city with substantially more jobs than local resident workers.
The City estimates that there are now approximately 72,000 jobs located .within the Palo
Alto city limits, a number that has increased by nearly 12,000 since 1980. Other sources
indicate similar increases over the 1980’s decade. Precise data on the number of jobs
within a small geographic area such as Palo Alto is not prepared by the Employment
Development Department of the state, generally the most reliable source on employment
information.
The U.S. Census data primarily focuses on population and is the most accepted source
of information of occupation, industry and place of work of workers by place of
residence. Indirectly the Census computes the total number of jobs in each place or
jurisdiction. In a situation such as Palo Alto with a significant share of the employment
base being on lands owned by Stanford, some of which are outside the City limits, the
methodology of the Census leads to confusion and inconsistency with other data sources.
The Census methodology is to have households fill out questionnaires with a series of
KEYSER M ARSTON ASSOCIATES INC.
17172\0001.027 Page 10
choices about place of work. Stanford is not available as a choice; the result is that some
who work at Stanford indicate Palo Alto while others indicate "Other unincorporated
Santa Clara County." The Census figures for jobs in Palo Alto, therefore, tends to be
higher than estimates from other sources. The Census does, however, estimate that job
growth in Palo Alto over the 1980’s decade was about 13,000 jobs.
In summary, it appears that employment in Palo Alto grew by at least 10,000 jobs over
the 1980 to 1990 decade. In 1980 there were approximately 60,000 jobs within the City.
The figures used by the City as a basis for the General Plan Update (1993) is a 1990
estimate of ?0,000 jobs and a 1992 estimate of 72,000. Employment will continue to
increase in number in the future as the Stanford Research Park completes its build out
and as parcels in the Park and elsewhere in the City are redeveloped with n~w buildings
at higher densities.
Commercial and Industrial Construction
New construction activity within the City of Palo Alto is recorded in building permits and
is closely monitored by the City’s Planning D~artment which tracks building type,
location within the City and other characteristics. According to the City there was 20
raison square feet of commercia! and induslxial floor area within the City in 1980. In
the twelve year p~od to 1992, 4,281,785 net additional square feet were built, which
is to say demolition of existing space has been taken into account. The sunmmry by
geographic area is indicated below:
Employment Distri~
BaylandsfEmbarcad~ro Road
California Avenu~
Downtown
San Antonio/W. Bayshor~ Road
Stanford Medical C,~nt~.r
Stanford Re~earch Park
Other
To~
Ne~ Change
Floor Area in Floor Area Total Floor Area
913,210 414,390 1,327,600
759,058 137,901 896,9.59
2,E54,000 504,956 3,358,956
2,843,231 326,267 3,169,498
1,076,234 844,645 1,920,879
7,362,820 1,655,605 9,018,425
4,905,129 ~5.303.150
20,713,682 4,281,785 24,995,467
Sours: City of Palo Alto Planning Department
The City’s estimate of employment was based on construction activity, utilizing
employment density factors for each type of space, such as office space, industrial, retail,
R&D, etc. In addition, the City made other adjustments to the employment figures based
K E ¥ $ E R M A R s "T o N A S S Op~ell~ T E S I N C.
on surveys and other research. In Palo Alto there has been a clear relationship between
employment growth and building construction. This relationship is expected to continue
into the future (although short term fluctuations in the economy could result in temporary
aberrations to the relationship. As a one time fee addressing the long term utilization of
buildings, short term aberrations are of little relevance.)
The relationship between employment growth End the buildings that house the growth is
fundamental to the analyses that underlie me public policies in other areas of
governmental action. Examples include traffic and transportation analysis and planning,
air quality management, and land use planning from community area plans to regional
plans. Transportation corridor fees are placed on buildings per square foot based on the
conversion of building space to the employees or customers and the traffic they cause.
Other types of fees are similarly based: buildings themselves do not drive cars, flush
toilets, drink water or send children to school. General plans, land use plans, and
growth management plans all translate employment growth to commercial and industrial
buildings and population growth to dwelling units.
Changing Densities in Existing Space
Since the nexus study links new construction to employment growth, it is important to
review trends affecting the utilization of existing space to determine if any adjustment
is in order. If employment density is found to be decreasing in existing space, then new
space may not represent 100% net new employment; rather a portion of it could
represent a transfer from existing space.
The long term trend of density in office space is generally one of increase. Existing
spaces become more intensely used over time as firms mature, add staff and resist
moving until necessary, and then relocate to space that is generous for current needs.
National data also indicates new space is also being utilized at increasing density, pushed
by cost and other factors. The West Coast lags behind other areas of the country in the
utilization or density of employment in newer space, according to a national study.
In retail and service space, density is related to economic health or sales per square foot
as well as type of activity. As commercial neighborhoods revitalize, existing space
becomes more intensively used and density increases. As commercial areas deteriorate
the trend is the reverse. With industrial space, the patterns are less clear and the nature
of the activity dominates.
Overall, then in office and commercial space, the general trend for a place like Palo Alto
would be one of stable to increasing density of employment within buildings.
Two other economic trends are in evidence in the Palo Alto area that need recognition
at this time. The first is the decline in the aerospace sector as a result of the end of the.
Cold War and altered government spending. Most aerospace related firms are reducing
employment with the result that for a period, aerospace firms will utilize their space less
intensively. Many former aerospace employees will remain in the area and seek
employment in other firms or other fields.
The second trend in Palo Alto is the shift in space utilization from office to
bioteehnology research and development. This trend has been identified in an in depth
study of Stanford Research Park (City of Palo Alto, September 1991). This study
projects that "Higher employee density functions will continue to leave and tend to be
replaced by lower density functions. Research and development activities will increase
and administrative functions will remain relatively constant. Pilot and small scale
manufacturing functions will remain within the Park because of the close link required
to R&D."
At the current time the Research Park represents approximately 36% of the commerdal
and industrial space in the City. Within the Park, less than half the employees are
elassi.fied as administrative as opposed to being in R&D, rnanufaeturing, warehouse or
other, and certainly, not all space occupied by administrative employment is subject to
transitioning to R&D. In another classification format of employment at the Park, 11%
of the 1988 employment was classified as Defense related. Presumably, this percent has
already decreased significantly. The conclusion of the evaluation is that less than 10%
of the work space and employees in Palo Alto are subject to the transitions leading to
decreased employee density.
To identify an adjustment factor for the linkage analysis, we took into account the above
conclusion and assumed the transition would occur over a five to ten year time frame.
If space transitions from office use to R&D use, the decrease in density is 25 % to 35 %.
Taking all these factors into account, we conclude that an appropriate adjustment factor
for Palo Alto is 10%, or to say that for every 10 jobs represented by net new work
space, one job will be an offset to decreasing employment density in existing space.
Commute Relationships
Since not all new workers in Palo Alto will live in Palo Alto, an adjustment to the
analysis is in order. In determining an appropriate adjustment factor, it is useful to
review existing relationships but it is also important to recognize that existing
relationships may not represent demand. Taken to the extreme, one can hypothesize a
city that has no lower income workers living in it because none can afford to. Were
affordable housing available would lower income workers not choose to live there’?.
17172\0001.027
Based on Census information and other surveys, somewhere in the range of 15% to 20%
of all those who now work in Palo Alto also live in Palo Alto. This percentage has been
decreasing, but for the City overall, the percent is believed to be in this range (Census
material is both not yet available and subject to the methodology problems discussed
previously). Studies have been conducted of Stanford Research Park employees at
various points in time, one in 1962 and one in 1991. The findings shed light on the
pattern of employment residence. In 1962, 21% of the Park employees also lived in the
City, in 1991 the percent had dropped to 11%. In 1962, 7% of the worlans commuted
to places in counties other than San Mateo and Santa Clara; in 1991, this percent had
doubled. In spite of increased congestion, higher costs of gasoline and a host of other
factors, the cost. of housing in Palo Alto has been even more influential in forcing
workers to live outside the City.
To identify a more realistic demand factor, we examined the commute relationships of
other mid peninsula cities to see if cities with a more diverse housing supply, in terms
of affordability, had a higher incidence of workers living in the City. The results of the
survey using the 1980 Census (the most recent available for this tabulation) are as
follows.
Other Silicon Valley Cities
(1980)
% of Workers in
WQrking Po_vulation City who Live in City
San Jose 301,679 64.0%
Mountain View 35,732 20.4%
Palo Alto 30,550 19.7%
Santa Clara 48,262 16.8 %
Redwood City 29,267 33.5%
San Mateo 41,383 33.4%
The finding is that there is considerable variation in the percent of worsts who reside
in the same city. Factors such as jobs housing balance, affordability of the local housing
supply, and sheer size all come into play. A very large city like San Jose has a
substantially higher capture rate. Several comparably sized cities relative to Palo Alto
have a worker residence capture in the 30% to 35%, and it is our conclusion that Palo
Alto would attract at least a third of its workers to live in the City if housing were made
affordable.
KEYS ER M A RSTON A s socl A"f ES 1N C.~:~ll~n 1417172\0OO1.027
The following analysis therefore applies a 33 % adjustment to the demand for housing
units at varying income levels as the share of households that would live in Palo Alto
were affordable housing available. Given the overall desirability of Palo Alto as a place
to live, we believe this is a highly conservative assumption. (See Section I discussion).
17172\0001.027 K E v S E R M A R S T O N A s 5 ~1~11’~ T E S ~ N C.
SECTION IIh THE NEXUS NUMERICAL ANALYSIS
This section presents a summary of the analysis of the linkage between non-residential
building types and the number of lower income households that will, on average, be
associated with them. This section should not be read or reproduced without the
narrative discussion presented in the previous sections.
Analysis Approach and Framework
Since it is our understanding that the City of Pale Alto has developed programs to assist
in making housing affordable to very low income, low income and moderate income
households, this analysis determines the number of employee households in each
category. Collectively these three groups are referred to as "lower" income households.
For information on income levels, the annual estimates of median income prepared by
HUD and published by the State Department of Housing and Community Development
is u "tflized because the estimates are both current and utilized for essen~y all affordable
housing programs. As the estimates are prepared by county, the Santa Clara County
figures are u~ here. Median income for a family of four is indicated at $59,300 as
of May 1993. For the same size household, low income refers to up to 80% of median
or $47,440, and very low refers to up to 50% of median or $29,650.
The analysis approach is to examine the employment associated with the development of
100,000 square foot building modules of six building types. The six building types are:
Office
Research and Development (R&D)
Manufacturing
Warehousing
Retail/Service
Hot~
The analysis was conducted for the City of Pale Alto.
Qualifiers to the Analysis
The analysis presented in this report has been based on readily available information.
The 1990 U.S. Census, which is now being distributed in sections, was frequently
utilized. For some inputs, we did have to rely on the 1980 Census since the release of
current 1990 data is still in progress. The other principal data source was the California
State Employment Development Department (EDD). Data for the City of Pale Alto was
taken into account wherever available. The appendix section presents a full
documentation of sources and data utilized.
17172\O001.027 K E v s E R M A R 5 T O N A s s ea~rls~ r E S [ ~ c.
It should be recognized that any analysis of this nature, no matter how in-depth, contains
a great many numbers and judgments relating to them. It will always be possible to take
issue with a specific number. We do not believe, however, that changing adjusting one
or more individual numbers would fundamentally alter the conclusions of the analysis.
Step I - Eftimates of Total New Employees
The first step identifies the total number of direct employees who will work at or in the
building type being malyzed. Employment densities are based on City of Palo Alto
surveys and density factors used in other applications, on our firm’s familiarity with the
Palo Alto market, and on general industry trends.
In starting with a number of employees in the building there is an implicit assumption
that all employees are new employees to the City. If the employees in a building have
relocated from other buildings, they will have vacated spaces somewhere else and
somewhere in the chain new employees will have come to this area to work.
In the office example, the building houses 400 employees.
Step 2- Changing Industry Adjustment
This step eliminates new employees who were previously working in another job but
have changed employment due to declining employment in specific industries such as
aerospace. This factor also recognizes the transition of some of-flee space to R&D space.
(See previous section.) A factor of 10% is utilized. With their adjustments the number
of employees is 360.
Step 3 - Estimate of Number of Households
This step recognizes that there is frequently more than one employee per household and
reduces the number of employees to the number of households. The 1990 U.S. Census
figure for Palo Alto of 1.66 employees per household was used.
The number of employee households in our office building is 217.
Step 4- Breakdown of Employees by Occupation
This step divides the employees representing new households into occupational groupings
using industry by occupation matrices prepared by the U.S. Department of Labor and
EDD. The occupational categories are Professional/Managerial, TechnicaYSa~es,
Clerical, Service, Craft and Operator/Laborer. "industry" categories closely approximate
the building types used in the analysis.
17172\0001.027 K E Y 5 E R M A R 5 T O N A s 5 q~ell"~ T E 5 1 N C.
Step 5 - Estimates of Employees Meeting the Lower. Income Definitions
In this step, occupation is translated to income distribution without consideration to
household size which is accounted for in the next step. Therefore, the analysis identifies
the number of employees who earn the qualifying amount for the largest size household,
or $34,400 in the ease of very low income households, and $46,000 in the ease of low
income households. Sources of information for this analysis step included wage data
from the Bureau of Labor Statistics. See the Appendix section for more information.
Step 6 - Estimate of I-lousehold Size Distribution
In this step, household size distribution was sought in order to move from income
distribution to the income and size combinations that meet the income definition
established by HUD. Since household size varies with income and age, we used the
closest U.S. Census tally and calculated the size distribution for the three income
categories (very low, low, and moderate).
Step 7- Estimate of Households that meet HUD Size and Income Criteria
In this step we had to build a matrix of household size and income to establish
probability factors for the two criteria in combination. For each occupational group a
probability factor was calculated for each of HUD’s income and household size levels.
This step is performed for each occupational category and multiplied by the number of
households.
Step 8 - Adjustment to Eliminate Most Multiple Earner Households
This last step makes an adjustment to eliminate or reallocate to higher income groups
most of the household that have two or more earners, in that these multiple earner
households may have incomes that make them no longer qualify in the lower income
categories. Based on data from the U.S. Census, we have calculated the number of
multiple earner households that fall in each income category. From this data we were
able to eliminate from the income category those multiple earner households with
incomes in excess of the HUD limits.
This is the last step of the analysis and identifies the number of employee households
associated with each of the five building types that meet the very low, low income and
moderate criteria.
17172\0001.027 K ~ Y s z .R M A R S T O N A s s ~gCelll~ T E S 1 N C.
Step 9 - Adjustment to Discount for Non-Resident Worker
Up to this point, the analysis has assumed all workers would live in the City of Palo
Alto. As presented in the previous section, it is assumed 33% of the employees will
demand housing in Palo Alto.
As noted, a strong case can be made for no commute adjustment at all.
Analysis Conclusions
The conclusions, of the analysis for the six building types, each 100,000 sq.ft, in size,
as presented in Tables 2, 3, and 4, are summarized below (figures are rounded):
Retail/
~R&_.._~DIndustrial Wareho~~
Total Employees 360 225 180 128 257 150
Employees Demanding 118 74 59 42 85 49
Housing in Palo Alto
(33 %)
Very Low Income 7 5 4 3 7 4
Employee
Low Income Employee 18 12 12 9 18 11
Hous~olds
Employee Hous~old~
Total 47 29 32 14 24 16
% of Employ~s Living 40%39%54%~2%49%
in Palo Alto
% AllEmployees 13.0%12.9%17.8%17.1%16.3% 14.6%
Because buildings differ so widely in employment density and composition of employees,
significant differences in the conclusions emerge when absolute levels are examined,
especially at each income level. When the lower income categories are joined with
moderate income the differences in terms of share of all employees demanding housing
in Palo Alto evens out to the 13% to 18% range.
KEYSER M A RSTON ASSOCIATES INC.Page 19
17172\0001.027
..JO0
TABLE 8
REPRESENTATIVE CONDOMINIUM SALES1 FOR TWO BEDROOM UNITS
PALO ALTO MARKET
PALO ALTO HOUSING NEXUS STUDY
1993
1992
~ale~ Price Unit So.~.Pri¢~/So.Ft.
$220,000 950 $232
$151,500 928 $163
$225,000 1,044 $216
$217,500 890 $244
$215,000 1,247 $172
$221,000 1,106 $200
$147,000 899 $164
$220,000 1,247 $176
$150,000 906 $166
$225,000 901 $250
$236,000 1,117 $211"
$211,000 1,060 $199
$205,000 1,595 $129
$223,000 850 $262
$225,000 1,145 $197
$202,000 1,030 $196
Average $198
tAll units ere 2 bedrooms.
Source:Keyser Marston Associates, Inc.
COMPS, inc.
March 1993
17172\0001.031
SECTION IV: TOTAL HOUSING LINKAGE COSTS
This section takes the conclusions of the previous section on the number of households
in the lower income categories associated with each building type and identifies the total
cost of assistance required to make housing affordable. The previous section identified
the number of households in the very low, low, and median income categories associated
with each building type.
The first step in this section is to summarize the costs per unit of assisting households
of the thr~ income levels. The cost of assistance is the cost of subsidizing housing in
Palo Alto as quantified in the affordability gap analysis. This quantification is not to
suggest that all units can be or ought to be provided in Palo Alto; the quantification is
oniy to illustrate total cost of assistance under the conditions prevailing in Palo Alto.
Income and Household Size Assumptions
In estimating the affordability gap we have matched a household of each income level
with a unit size and type of tenure according to governmental regulations and policies.
The average income of the qualifying households in each category has been utilized.
That is to say that while the upper limit of very low income households is 50% of
median income, not all very low income households demanding housing will have
incomes as high as 50% of median. Many will have an income level far lower. The
average income of very low income households is more akin to 35% of median and
therefore the 35 % has been utilized in the analysis. For ownership units, median income
is used in the analysis since the program serves households as high as moderate income
(120% of median) as well as those of lesser income. For each income level, the
assumptions for analysis purposes are as follows:
Very low income households -- a three-person household with an income
of $18,673, or 35% median for the household size, in a two bedroom
apartment.
Low income households -- a three-person household with an income of
$32,010, or 60% of median for the household size, in a two bedroom
apartment.
Moderate income households, a three-person household with an income
of $54,350 or at median, in a two bedroom condominium unit.
The match for other household size and unit sizes (such as a one person household in a
studio unit, a two person household in a one bedroom unit, etc.) bear out similar
relationship and subsidy needs. The above household size and subsidy needs are a rough
KE YS ER M A RSTO N ASSOCIATES INC.
17172\0001.027 Page 24
average. The income levels are established annually by I-IUD. The above levels are as
of May 1993.
Per Unit Housing Co~ts
The Palo Alto program will have two major options available for providing housing
affordable to target households. The City can build (or cause to be built by another
entity) new units or it can purchase existing units and make them available at affordable
rent or sales prices through a range of mechanisms.
There are many constraints to developing affordable housing in Palo Alto as articulated
in the Housing Element. The single greatest constraint is the very minimal land
availability and costs associated with the land that is available. These constraints apply
to the public sector in its efforts to develop units as well as the private sector. As noted
in the Housing Element, costs of land in Palo Alto are substantial:
"Land cost in Palo Alto constitutes a major component of overall
development cost. Residential developers pay between $25 to $55 per
square foot for land in Palo Alto, depending upon the location and
development potential of a l~rcel. This cost alone ean add $45,000 per
unit for multiple-family developments and up to $500,000 a unit for
single-family developments. The City in the past has used local and
federal revenue sources to reduce the cost of land for the development of
low- and moderate-income housing."
For these reasons the City of Palo Alto may opt to purchase existing units to meet
housing needs as well as construct new units. The City’s program has the specific goal
of "lessening the shortage of low and moderate income housing in Palo Alto by requiring
developers ... to contribute to programs that increase the City’s low and moderate
income housing stock." (Section 16.47.010) This program does not have as a goal the
preservation of the stock for market or upper income households.
The City needs to maintain the flexibility to either rehabilitate existing residential units
or build new ones because the costs of doing one versus the other shift from lime to
time, as do opportunities to purchase land or buildings. The build option may be cost
effective when state or federal programs or other non-profit funding are available to
leverage local funds and reduce the local cost burden. At the current time, the costs of
rehabing existing units have been rising, some buildings requiring as much as $30,000
per unit over and above the purchase price. Overall an average of five projects suggests
a rehab cost of at least $15,000 per unit should be anticipated over and above a purchase
price average of $90,000 per unit. Given land costs in Palo Alto, most development
projects cost far more than $115,000 per unit, but when the City has the opportunity to
KEYSER MARSTON ASSOCIATES INC.
17172\0001.027 Page 25
acquire a site at reduced cost (or a city owned parcel becomes available), costs can be
brought down to a competitive level with the rehab alternative. In summary, both
options must remain available to the city.
Since the purchase of existing units is more often the less expensive option compared to
development of new units, the linkage analysis is based on the purchase option. The
purchase option represents a more conservative approach to the cost accounting linkage.
The Affordability Gap
The first step in .the affordability gap analysis is to establish the amount affordable for
housing for each income level, or each of the households described above. Table 5
summarizes the analysis for rental units and Table 6 for ownership units.
The analysis procedure commences with the income level and then proceeds through a
series of adjustments to determine the amount available for annual housing costs and
purchase price. A key factor is the share of income available for housing. Federal
rental housing assistance programs use a 30 % standard for all housing costs including
utilities. The City of Palo Alto uses the same standard for all types of housing.
After the affordable rent is established, adjustments are made for operating expenses and
vacancy allowance. Net operating income is then capitalized to establish per unit value
or purchase price supported.
The final step in the analysis is to compare the cost of purchasing a unit in the City of
Palo Alto market place to the purchase price supported, with the difference being the
subsidy required or affordability gap. To determine the purchase price of units in Palo
Alto, we obtained information on sales transactions completed over the last four years.
Table 7 summarizes the experience of eleven such sales covering over 300 units. While
the average price per unit was $86,321, a significant share of total units were studios and
one bedroom units which command a lower price. Projects where two bedroom units
represented a majority of the units were in the mid to upper $90,000 range or higher.
For an average two bedroom unit, it is conservatively estimated that units could be
acquired for $90,000 to $95,000. Rehabilitation costs have been running an average of
$15,000 per unit as previously noted.
At $115,000 for a two bedroom unit, the affordability gap for the very low income three
person household is $84,000 per unit, and the low income household $36,000 per unit.
There is no affordability gap for median income households (Table 5).
For ownership units the same general procedure is followed. Annual affordable housing
cost is estimated at 27% for principal and interest payments, allowing the other 3% for
KEYSER MARSTON A S SQ~-C-eI2t~T ESrill ~ iNC.
17172\0001.027
property taxes and insurance and ~: ~eowners association. Assuming mortgages are
available at 7% interest for 90% of the purchase price, the affordable pdee is
established. Again, to determine the purchase price, condominium sales in Palo Alto
were reviewed for local values. Sixteen sales were reviewed which produce an average
sales price of $199 per square foot. At the average per square foot value, an 1,150
square foot two bedroom unit would cost $225,000.
The affordability gap for a three-person household is $155,000 at very low income,
$105,000 low income, and $25,000 median income. (Table 6)
Single family detached units or duplex units would cost significantly more than $225,000
each, resulting in higher subsidy needs. Using the condominium unit in the analysis is
the more conservative approach to calculating linkage costs, but does not preclude the
City from aeqniring detached units as part of the program.
Total Linkage Costs
The last step in the linkage fee analysis marries the findings on the numbers of very low,
low and median income households associated with each type of work space building to
the costs of delivering or subsidizing housing for them in Palo Alto. The rental
affordability gap is applied to the very low and low income households, while the
ownership gap is applied to the median income households. Since the linkage analysis
to determine the number of households has been based on a 100,000 square foot building,
the findings are divided by 100,000 to produce findings per square foot. The summary
findings are:
SUMMARY TABLE
Total Housing Linkage Cost (Per Sq.Ft. Building Area)
Very Low Low Median Current
Income Income Income Total Palo Alto Fee
Office $5.88 $6.48 $5.50 $17.86 $3.34
R & D 4.20 4.32 3.00 11.52 3.34
Industrial 3.36 4.32 4.00 11.68 3.34
Warehousing 2.52 3.24 2.50 8.26 3.34
Retail 5.88 6.48 4.25 16.61 3.34
Hotel 3.36 3.96 1.75 9.07 3.34
KEYS ER M A RSTON ASSOCIATES INC.
17172\0OO1.027 P=ge 27
These costs quantify the total linkage between new commercial/industrial construction
and the demand for new affordable housing, expressing that connection in terms of a cost
per square foot of commercial/industrial space. These total nexus costs represent the
legal ceiling for potential fees; the nexus costs far exceed actual fees that the City has
enacted in the past or is likely to enact in the future.
In establishing the total nexus cost, or maximum fee amount, it is noted that many
conservative assumptions were employed in the analysis that result in a total nexus cost
that is probably understated by a considerable amount. These conservative assumptions
include:
The commute adjustment assumes that 67% .of all employee households
will demand housing outside of Palo Alto even if units are made
affordable.
The methodology for discounting double income households essentially
removes most two income households from the lower income strata (by
assuming the multiple incomes place the households in the middle and
upper income categories). The high and growing number of single parent
households probably results in more households in the lower income
eamgories than indicated in the analysis.
The rebound purchase of existing units alternative for establishing the cost
of housing subsidy results in a lower cost per unit than would land
purchase and new construction.
Only direct employees are counted in the analysis. Many indirect
employees are also associated with each new workspace. Indirect
employees in an office building, for example, include janitors, window
washers, landscape maintenance people, delivery personnel, and a whole
range of others.
In summary, less conservative assumptions could be made that would result in higher
linkage costs than are concluded in this analysis.
KEYSER M A RSTON ASSOCIATES INC.
17172\0001.027 P~e 28
APPENDIX A
Nexus Methodology and Documentation
Step 1 - Estimate of Total New Employees
The estimate of the number of employees is derived based on an employment density
factor for each land use. As shown below, the gross building area is divided by the
employment density factor to calculate employees.
Gross Building divided Employment =Employees
Area by Density Factor
The employment density factor is different for each land use and can vary widely within
each land use depending on land use types. Densities for industrial uses, for example,
vary within a huge range. Other land uses axe more constant. Employment density
factors in this analysis are based on density factors developed by the City of Palo Alto,
KMA’s experience in working in the Northern California market general industry trends.
The office employment density factor is estimated at 250 sq.ft, per employee. This
estimate assumes a 5 % office vacancy factor. The employment density factor for retail
is 350 sq.ft, per employee and for hotel 1.00 rooms per employee. These density factors
are based on typical tenant types in the Northern California and palo Alto markets.
For industrial and warehouse employment density factor, KMA has relied on trends in
several meu’opolitan areas in California and City of Palo Alto data.
The employment density factors used in this analysis are the following:
Office
R&D
Industrial
Warehouse
Retail
Hotel
250/sq.ft./employee
400/sq.ft./employee
500/sq.ft./employee
700/sq.ft./employee
350/sq.ft./employee
1.O0/room/employee
Step 2 - Changing Industry Adjustment
See Section II of the Report.
K EYS ER M A RSTON ASSOCIATES INC.
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Step 3 - Estimate of the Number of Households
This step estimates the number of households represented by a given number of
employees. The number of households needs to be estimated since housing assistance
is based on household income and household size. The 1990 U.S. Census estimates there
are 1.66 wage earners per non-elderly household in Palo Alto County. Using this factor
the number of households can be calculated.
Employees in divided Average Number of New
New Households by Workers per =Households
Household
Data Source:
(i)Estimate of Total Households:1990 Census of Population and
Housing
(2)Estimate of Elderly Households:1990 Census of Population and
Housing
(3)Estimate of Employee Labor
Force:
1990 Census of Population and
Housing
Calculation of Average Number of Workers per Household:
Estimate of Employee°~ divided (Est. of HH(’)
by
Est. of Elderly HHat)
Step 4 - Breakdown of Households by Occupation
This step divides households by occupational groupings for each land use. For purposes
of this analysis, we have relied on the occupational groupings defined by the State of
California Employment Development Department and the US Census. Occupational
groupings include ManagerlaYPmfessional, TechnicaYSales, Clerical, Craft!Kindred,
Service, and/or Laborer. For each land use category, such as office, the total number
of households identified in Step 4 are desegregated into occupation categories. In this
step, we have relied on U.S. Census data which provides comprehensive occupational
data for the United States. We then used EDD data for the Santa Clara County as a
refinement to the national data.
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New Households x Percentage of =
Households in each
Occupation Category
Dam Source:
New Households
in each Occupation
Category
"1985-1990 Projections of Employment by Industry and Occupation," Santa Clara
County, Employment Development Department.
"1980 Census of Population; Occupation by Industry Survey," U.S. Department of
Commerce.
Step 5- Estimate of Employees Meeting the Income Definition
The number of households in each occupation category that fall within the respective
income categories are estimated in Step 5. To accomplish this step, KMA first reviewed
available wage survey data collected by the U.S. Department of Labor, State of
California Employment Development Department.
For most occupations data was available for a select number of job types. ]’udgements
were made based on extrapolation of available data to estimate the percentage of
households that have a wage earner that may qualify for assistance. Income l~,els for
the median and lower income categories, axe set by I=IUD. This does not necessarily
mean the household qualifies for assistance since the household must also meet household
The most comprehensive wage data was found for office workers, particularly for clerical
and professional/technical occupations. Available wage data for other land uses and
related occupational groups was less complete and provided data for only select job
types, such as welder and cashier. KMA, therefore, made estimates of income
distribution by occupation. To estimate the percentage of households earning less than
the upper income limit in the crafffkindred, service and operative/laborer occupations,
we used the clerical wage data as a benchmark and have made adjustments relying on
available wage data for selected job types in each of the occupational categories. This
methodology requires adjustments to correct for the possibility that households earning
less than the upper income limit for each of these occupations is not based on a
representative range of job types~ but rather on specific job types which may not
adequately reflect the range of salaries in an occupation category. Additional research
could be undertaken to see if more comprehensive wage data is available.
The next step estimates the number of households in each of the six income subgroups
defined by HUD. This is done for the very low and low and moderate income
categories. For tiffs step, we have again relied on clerical wage data. As previously
KEYSER MARSTON ASSOCIATES INC.17172\0001.027 P~ge 31
discussed, this data is the most comprehensive and this is u~ to estimate the number
of households in each of HUD’s income subgroups. This is done for the cra_tVklndred,
service and laborer/operative occupational categories and applies to all land use
categories.
The clerical income distribution was utilized to estimate the number of households in
each of HUD’s six income subgroups. From that distribution, estimates for the four
other occupational categories were made based on wage data from a representative
sample of jobs. Additional research could be undertaken to-obtain more comprehensive
and detailed wage data for each occupation category.
Data Source:
"Area Wage Survey, Santa Clara Area, U.S. Department of Labor, December 1992.
Using Table A-1 "Weekly earnings of office workers" estimate the percentage of workers
that fall within HUD’s income level for one, two, three, four, five and six person
households. This was done for each income grouping.
"Annual Planning Information: Santa Clara County," State of California Employment
Development Department, June 1989.
"Handbook of Labor Statistics," U.S. Department of Labor, August 1989.
Step 6 - Estimate of Household Size Distribution
HUD’s criteria for assistance is dependant on a household meeting a combination of
income and household size requirements. Step 6 estimates the number of households in
each household size category ranging from one person per household to six pexsons or
more per household. The income levels are based on }KID’s income assistance level for
a four person household in 1990.
Household
1 33%
2 35%
3 14%
4 12%
5 4%
6+2%
Data Source:
U.S. Census: Detail Population Characteristics, California.
K E Y S E R M A R S T O N A s s 0~=13~ T E S~0 - i N C.
17172\0001.027
To determine household size distribution, we calculatexl the number of non-elderly
households for each household size.
Estimate of HH by Income (HH over 65 x % of Elderly
Step 7 - Estimate of Households That Meet Income and Size Criteria for Assixtance
This st~ calculates the number of households that meet HUD’s lower income assistance
criteria. Using a matrix format, a probability factor is calculated for each of the five
subgroups. To detem~e the probability factor for each occupation category, the
probability factors calculated for each HUD level are totalled. This number represents
the probability that new households in a given occupation category will meet both income
and household size criteria established by I:IUD.
To determine the number of households that qualify for assistance, the probability factors
are multiplied by the number of households by occupation estimated in St~ 4. This is
done for each land use category.
Land Use: Office
Occupation: Ciedcel
Asslstan¢~ Level: Very Low
~....of Household by Income
% of=
Income Levels Households
< $20,750 15%
< $23,700 25%
< $26,700 44%
< $29,650 62%
< $32,000 75%
< $34,400 85%
Total
.~.....~f..Householda by Size=
2 _2 _a _4
[.088]
[.062]
[.071 ]
[.030]
[.017]
[.371]
Households Requiring Assistance: .371 x 88 cledcal households ,= 33 households
3
Step 5
Step 6
To calculate probability factor multiply the percentage of households by income figure by the 1 person
household size percentage
17172\0001.027 K E ¥ S E R M A R S T O N A S S (J~e|3~ T E S I N ¢.
Step 8 - Adjustment to Eliminate Most Mula’pte Earner Households
This last step makes an adjustment to eliminate most of the households that have two or
more earners such that the incomes in combination make the household no longer qualify
for the lower income categories.
From the U.S. Census, we can estimate the number of multiple earning households that
fall within each income category. For example, of all multiple earning households we
estimate that 6 % fall in the very low income category. Our methodology in the nexus
analysis estimates the number of multiple earner households based on the assumption of
1.72 earners per household (this is an average for all households). This estimate of
earners per household overstates the number of multiple e.amers in the lower end income
categories. As a result, we have adjusted the number of multiple earner households
presented in the nexus analysis to the estimated number indicated by the U.S. Census
data.
Land Use: Office
Income Level: Very Low
Number of Multiple Wage Households (Step 3)
% of Multiple Wage Households as Very Low1
Number of Multiple Wage Households
(Multiply 143 by 6%)
Estimate of Multiple Wage Households
based on 1.66 earners/household
143
6%
8.6
22.0
Elimination of Multiple Earner Households
(22 - 8.6 = 13.5)
13.5
To estimate the number of households that qualify for assistance, we need to subtract the
13.5 multiple earner households from the 33.4 households estimated in Step 7. Based
on this adjustment, households qualifying for assistance is 19.9 for the office building.
Data Source:
(1)Wife in Labor Force: 1980 U.S. Census; Detailed Population Characteristics,
California.
KEYSER MARSTON ASSOCIATES INC.17172\0001.027 Pago ~
Step 9 - Adjustment to Discount for Non-Resident Workers
See Sections I and II of the Report.
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