When and How Should Cities Implement
Inclusionary Housing Policies?
Ann Hollingshead
This page is intentionally left blank
AUTHOR’S NOTE
This report was prepared by Ann Hollingshead with funding from the Cornerstone Partnership, a
program of the Community Solutions Group, LLC, which is a subsidiary of Capital Impact Partners.
The author prepared this report as part of the program of professional education at the Goldman
School of Public Policy, University of California, Berkeley. This report is submitted in partial
fulfillment of the course requirements for the Master of Public Policy degree. The judgments and
conclusions are solely those of the author, and are not necessarily endorsed by the Cornerstone
Partnership, the Goldman School of Public Policy, the University of California, or by any other
agency.
Academic Advisor: Jack Glaser, Associate Professor, Associate Dean, Goldman School of Public
Policy, University of California, Berkeley
Client Advisor: Sasha Hauswald, Senior Program Officer for Inclusionary Housing Policy,
Cornerstone Partnership
Acknowledgements
I first and foremost would like to thank Sasha Hauswald for her guidance from start to finish. Thank
you for giving me this opportunity, your interminable support, and your willingness to take the time
to impart your depth of knowledge.
I am grateful to Jack Glaser for his guidance and helpful feedback along the way; Emily Thaden for
her assistance and insights; Anna Scodel for the thoughtful edits of a seasoned editor-in-chief;
Lindsay Cattell for quantitative feedback and advice; and Alex Marqusee for cartographical
contributions and indiscriminate assortments of housing knowledge and connections.
On a personal note, I am thankful for the support and friendship of Sarah Marks who believes in me
more than I deserve; Sarah Chevallier for comic, yogic, and Thai reprieves; Patti Hollingshead, my
lifelong cheerleader; and, of course, Cameron Stone Adams for living up to his middle name.
Finally, I am grateful to all of the interviewees who lent me their time and expertise. Your insights
were invaluable and without them this report would not have been possible.
prepared for
PURPOSE AND AUDIENCE
This report aims to inform the policy debate for municipalities in the United States pursuing or
modifying inclusionary housing policies in the rental market. The primary audience of this report is
advocates, policymakers, and researchers looking to design, modify, adopt, or eliminate existing
inclusionary housing policies. For those municipalities that already know they would like to
implement an inclusionary housing policy, this report can provide guidance on the choice between
policies that focus on the provision of units or the provision of fees. While this analysis focuses on
the rental market, many of the lessons and recommendations would also apply to an inclusionary
housing policy applied to an ownership market.
CONTENTS
Background ......................................................................................................................................................... 1
Report Overview ................................................................................................................................................ 4
Policy Alternatives ............................................................................................................................................. 7
Policy Design and Legal Considerations ........................................................................................................ 9
Criteria ...............................................................................................................................................................15
Do Inclusionary Housing Policies Have Unintended Market Consequences? .......................................18
Do Inclusionary Housing Policies Promote Housing Affordability? .......................................................37
Do Inclusionary Housing Policies Promote Socioeconomic Integration? ..............................................47
Analysis of Alternatives...................................................................................................................................53
Summary of Recommendations.....................................................................................................................58
Case Study Interviewees and Key Informants .............................................................................................60
Works Cited ......................................................................................................................................................62
This page is intentionally left blank
When and How Should Cities Implement Inclusionary Housing Policies?
EXECUTIVE SUMMARY
Over the past decades, and in particular since the Great Recession, housing has become less
affordable. Today, renters in the bottom fifth of the income distribution spend nearly two-thirds of
their income on housing. In dollar terms, this means that if a two-earner household makes $1,800
per month in after-tax income, it spends, on average, $1,190 on rent, leaving $600 per month for
utilities, transportation, food, clothing, childcare, and any other expenses. This share has grown over
time: as incomes for most Americans have stagnated, rental prices have increased.
Public policy at the state and federal level has failed to keep pace. In fact, federal funding for lowincome households has declined and state programs fall short of filling the gap. This situation has
prompted localities to take action, with many turning to inclusionary housing policies. Under these
policies, municipalities require developers building new market-rate development to set aside a
certain percentage of the development’s units as affordable or pay a fee.
While there are a range of design elements associated with these policies, most fall into three main
categories: (1) fee-focused policies, or those that emphasize the collection of fees from developers,
(2) units-focused policies, or those that emphasize the production of affordable units by
developers, and (3) blended policies, or that make significant use of both fees and units. As of
2014, there were nearly 500 municipalities in the United States that had pursued one of these types
of inclusionary housing policies.
Despite this prevalence, many cities face a dearth of information about when and how to implement
an inclusionary housing policy. Specifically, cities face competing and contradictory information
about whether these policies promote or restrain overall affordability. When a city decides to
implement an inclusionary policy, there is still debate over which policy type—a fee- or unitsfocused policy—is in the best interest of its residents. Finally, there is no formal, objective guidance
that cities may use to inform this decision.
This report aims to fill this gap. It provides formal and objective guidance for advocates,
policymakers, and researchers looking to design, adopt, modify, or eliminate existing inclusionary
housing policies that target low-income renters. Should a city decide to implement an inclusionary
housing policy in the rental market, this report outlines the most efficient and effective designs of
those policies, emphasizing the conditions under which a city might choose one type over another.
To support these recommendations, this report relies on a mixed-methods approach that blends
evidence from quantitative, qualitative, and theoretical perspectives. The four major analytic
components are: (1) a detailed review of the existing literature, (2) interviews with experts in the field
of inclusionary housing and housing economics, (3) a quantitative analysis of inclusionary housing
policies in California, and (4) qualitative case studies of eight cities with experience in a variety of
policy types.
On the debate of the effects of inclusionary housing on rental markets and overall affordability, this
report makes three key contributions to the existing literature. These are:
1. Inclusionary housing policies contribute to overall housing affordability in the rental
market. This report examines whether weakening a rental inclusionary housing policy has an
effect on housing affordability. I find that weakening an inclusionary housing policy is
associated with a 2 percent increase in median rental prices and a 3 percent increase in the
price of low-cost units.
2. Developers did not lower rental prices among after cities eliminated or weakened
their rental inclusionary housing policies. This report fails to find evidence that
weakening a rental inclusionary housing policy is associated with a reduction in the price of
high-cost units. This evidence may suggest that rental inclusionary policies are not
systematically or aggressively associated with higher prices among high-cost units.
3. Fees associated with inclusionary housing policy are often set below their efficient
level. An analysis of several case studies and interviews with experts reveal that cities would
be able to produce more affordable housing, with few additional costs to developers and the
public, by raising their fee levels.
There is no “one-size-fits-all” inclusionary housing policy for all municipalities. However, this
analysis provides some guidance on when and how municipalities should implement various forms
of inclusionary housing policies. This report makes the following three key recommendations:
1. The ideal policy design is a blended policy that makes significant use of both units
and fees. If properly structured, a blended policy can be the most effective for minimizing
unintended market consequences and generating affordable housing. However, these policies
only achieve these outcomes when the implementing city sets the fee schedule at the
appropriate level. As noted earlier, however, cities commonly set these fees too low. As a
result, cities should only pursue this alternative when they have the administrative capacity
and political will to set fees appropriately.
2. In general, a units-focused policy is the most reliable alternative. This alternative may
provide a good default option. The likelihood of a city achieving its desired outcomes under
this alternative is highest. Cities that are not able to set the fee level appropriately for
political or administrative reasons should prefer a units-focused policy.
3. In general, cities should not pursue a fee-focused policy. With few exceptions, from
both an economic and a policy perspective, these policies do not have any advantages unitsfocused policies or blended policies.
While I cannot conclude that every municipality should pursue an inclusionary housing policy, in
general this analysis shows that these policies are flexible, effective tools for cities to achieve better
housing affordability. Moreover, it is unlikely that these policies have significant or systematic costs
in terms of housing prices and production. As such, any city currently facing, or expecting to face,
challenges related to housing affordability may want to consider adopting an inclusionary housing
policy to help meet its housing affordability needs.
When and How Should Cities Implement Inclusionary Housing Policies?
BACKGROUND
Housing Has Become Less Affordable
The combination of falling wages for middle income Americans and rising home prices have raised
concerns about housing affordability. Rising rental prices are of particular concern for low-income
and minority Americans, about half of whom are renters (Joint Center for Housing Studies of
Harvard University 2013b).
Compared to incomes, housing costs have increased in real terms. In 1960, the median renter spent
about 18 percent of her income on housing. Today, she spends about 30 percent. For renters in the
bottom fifth of the income distribution, the share of income spent on rent has increased from 47
percent in 1960 to 63 percent today (Collinson, Ellen, and Ludwig 2015). In dollar terms, this means
that if a two-earner household makes $1,800 per month in after-tax income, they spend, on average,
$1,190 on rent, leaving $600 per month for utilities, transportation, food, clothing, childcare, and any
other expenses. Meanwhile, the population of very low-income renters has nearly doubled from 10.7
million in 1978 to 19.3 million in 2011 (Joint Center for Housing Studies of Harvard University
2013a), outpacing total population growth by a factor of two.
In addition to its financial importance, housing is an important component of family well-being.
Housing that costs more than a family can afford threatens its stability, exposing the family to the
threat of eviction or foreclosure. Access to good-quality housing is of fundamental importance to
other aspects of a family’s life, including employment, education, nutrition, and health. When facing
housing affordability challenges, many families must settle for low-quality or geographically remote
housing so that they can afford other basic necessities. This places additional stress on the family as
housing that is isolated, overcrowded, or in substandard condition presents health and well-being
concerns.
State and Federal Assistance for Affordable Housing Has Declined
While incomes have declined relative to rental prices nationwide and the population of low-income
renters has grown relative to the total population, federal housing assistance for these populations
has waned. For instance, funding for public housing has declined (Turner and Kingsley 2008) and
programs targeted toward very low-income renters—for example Section 8 project-based rental
assistance and programs for the elderly and disabled—have faced budget cuts and uncertainty in
recent years (Pelletiere et al. 2008). More recently, federal budgetary pressures have curtailed any
further expansion of the federal housing voucher program, putting additional downward pressure on
federal assistance.
In a study of states’ efforts to fill the gap from federal programs, Pelletiere et al. (2008) found that
state programs fall short. The authors note that “despite the declining commitment of the federal
government to serving the lowest income Americans, states often direct resources away from rental
programs serving the lowest income populations with the greatest need.”
Background | Page 1
When and How Should Cities Implement Inclusionary Housing Policies?
Cities Have Responded with Inclusionary Housing Policies
Eroding housing affordability and declining federal and state assistance have together prompted
many localities to take action. While there are several policy interventions that cities can pursue to
fill this gap, many have turned to inclusionary housing policies.
Under these policies, a municipality requires a developer building a new development to either set
aside a certain percentage of the units as affordable or to pay a fee. Most of these policies therefore
fall into three main categories: policies that emphasize the provision of fees, policies that emphasize
the provision of units, and policies that make significant use of both fees and units. As of early 2014,
there were nearly 500 municipalities across 27 states and Washington, D.C. that had pursued some
type of inclusionary housing policy (Hickey, Sturtevant, and Thaden 2014).
The Great Recession Has Deepened Concerns about Housing Affordability
The aim of inclusionary housing policies is to promote housing affordability, particularly among
low- and moderate-income residents. Yet some have argued these policies create unintended market
consequences that erode their ability to meet this objective. For example, to the extent that
inclusionary housing policies act like a tax on development, they may stifle housing production and
increase the price of market-rate units, reducing overall affordability in a housing market. The
validity of this concern is open to debate, and indeed it is a topic of major discussion of this report.1
This debate has become increasingly salient in the wake of the Great Recession, which contributed
to a slump in housing production, increasing rents, and falling incomes (Ellen and Dastrup 2012).
FIGURE 1. RENTAL PRICES HAVE OUTPACED INCOMES
From: Collinson, Ellen, and Ludwig (2015), figure 3, page 63
Note: These prices are all expressed in real terms (i.e., they are adjusted for inflation)
1
See “Do Inclusionary Housing Policies Have Unintended Market Consequences?” beginning on page 37.
Background | Page 2
When and How Should Cities Implement Inclusionary Housing Policies?
As Figure 1 above shows, the gap between incomes and housing prices has increased since the Great
Recession. Specifically, real rental prices rebounded after a small dip in 2007, but real income growth
has remained low since 2009.
In response to these concerns, cities have become wary of implementing or having policies in place
that restrain housing markets. Some cities with inclusionary policies have responded by weakening
or eliminating them. Some states have responded by banning inclusionary policies at the municipal
level. For example, Arizona recently passed a law that prohibits its cities and counties from passing
land use regulations, plan provisions, or zoning conditions that establish the sales or lease price for
any housing units (Arizona Daily Star 2015) – effectively prohibiting inclusionary housing policies.
This report explores a variety of policy-relevant characteristics of inclusionary policies—from a
program’s potential to promote well-being through socioeconomic integration to its administrative
costs. However, the debate over markets lies at its core. In short: What are the economic effects of
inclusionary housing policies? And do inclusionary policies promote or suppress housing
affordability?
SUMMARY
Housing has become increasingly unaffordable, in particular in the years since the Great Recession.
Meanwhile, federal and state assistance for affordable housing has remained stagnant, or by some
measures, declined. Cities have responded to these challenges with inclusionary housing policies.
Under these policies, a municipality requires a developer building a new market-rate development to
either set aside a certain percentage of the units as affordable or to pay a fee. Yet some have argued
these policies create unintended market consequences that erode their ability to meet their objective
of preserving housing affordability. This debate lies at the heart of this report.
Background | Page 3
When and How Should Cities Implement Inclusionary Housing Policies?
REPORT OVERVIEW
This section describes the report’s objective and methodology. It concludes with a brief overview of
the structure of the remainder of the report.
REPORT OBJECTIVE
When grappling over the question of whether, and how, to implement an inclusionary housing
policy, cities face competing and contradictory information about whether these policies promote or
restrain overall affordability. Even when a city decides to implement an inclusionary policy, there is
still debate over which policy type—fees or units—are the most efficient and effective. For example,
some cities have pursued fee-focused policies, convinced by the argument that these policies grant
flexibility to developers, reduce market impacts, and promote more affordability overall. Others
cities have pursued units-focused requirements. Their proponents argue these policies result more
affordable housing and more economic and racial integration by neighborhood.
In part, this debate remains unresolved because of the limited available research. To date, there has
been no comprehensive study on the market impacts or effectiveness of units- versus fees-focused
policies. Existing evidence on inclusionary policies focuses on large metropolitan areas and bears
few implications for small and mid-sized cities. There are also no academic studies that address
whether a city that has an inclusionary policy will experience better market outcomes if they repeal
or weaken that policy. Finally, there are no convincing studies that estimate the effect of inclusionary
housing policies on housing affordability.
As a result, municipalities adopting inclusionary housing policies sometimes make arbitrary or
politically-driven decisions about the structure and design of those policies, which may limit their
effectiveness. In short, despite many cities’ long history with inclusionary housing policies,
municipalities lack formal and unbiased guidance on whether to implement an inclusionary policy
and how that policy should be designed. This report aims to fill that gap.
REPORT METHODOLOGY
Both quantitatively and qualitatively, this report exploits the variation in rental inclusionary housing
policies observed in response to the decision by California’s Second District of Appeal in
Palmer/Sixth Street Properties LP v. City of Los Angeles. I use this decision quantitatively to analyze the
market effects of inclusionary housing policies and qualitatively to determine the appropriateness of
a fee-focused policy versus a units-focused policy.
In the 2009 decision by the Second District Court of Appeals in Palmer/Sixth Street Properties LP v.
City of Los Angeles case, the court ruled that inclusionary housing requirements on rental
developments without cost-offsets or city benefits violate the Costa Hawkins Rental Act of 1995.
The Costa Hawkins Act (Civ. Code §1954.50 et seq.) allows developers to set initial rents on newly
constructed and voluntarily vacated units in jurisdictions with rent control. Units-focused policies
inhibit developers’ abilities to set those initial rates.
Report Overview | Page 4
When and How Should Cities Implement Inclusionary Housing Policies?
The Palmer ruling therefore called into question the legality of existing mandatory on-site
performance requirements for rental projects in California. While the legal interpretation of the
Palmer decision varies, in general cities interpreted the decision to mean that they could no longer
maintain a units-focused policy that did not include a fee alternative.2 Some cities responded to this
legal uncertainty by eliminating their entire inclusionary housing policy and some by replacing their
existing policy with a fee-focused policy. As a result, fee-focused policies grew in popularity in
California in response to the Palmer decision.
Palmer presents a unique opportunity to compare the outcomes, successes, and challenges of unitsfocused policies against those of fee-focused policies. For the quantitative portion of my analysis, I
use the variation resulting from the Palmer decision to examine the effects of inclusionary policies on
unintended market consequences (like increased prices of market-rate housing) and housing
affordability. For the qualitative portion of my analysis, I interviewed key informants in eight cities
in the Bay Area, each of which had an inclusionary policy pre-Palmer, but had varying responses to
the Palmer decision (see Table 1 below).
TABLE 1. CASE STUDIES
Jurisdiction
Cupertino
Fremont
Livermore
Los Altos
Palo Alto
Pleasanton
Santa Clara
Santa Rosa
County
Santa Clara
Alameda
Alameda
Santa Clara
Santa Clara
Alameda
Santa Clara
Sonoma
Pre-Palmer
Rental Policy
Units
Fees and Units
Fees and Units
Units
Fees and Units
Primarily Fee
Units
Fees
Post-Palmer
Rental Policy
Fees
Fees and Units
None
Units
None
Primarily Fee
None
Fees
Case Study
Page 41
Page 45
Page 43
Page 22
Page 51
Source: Author’s Analysis
Note: Los Altos authorizes its inclusionary housing policies under the State Density Bonus Act and therefore was
able to legally maintain a units-focused policy post-Palmer.
Each of these case studies presents a unique opportunity to examine the tradeoffs cities may face
when choosing whether to pursue a units-focused policy, a fee-focused policy, or a blended policy
that makes significant use of both fees and units. While all of these case studies inform my analysis, I
present five full case studies in this report. These case studies appear throughout the report as
indicated in Table 1 above.
In addition to the quantitative analysis and case study interviews, I conducted a thorough
examination of the existing empirical and qualitative literature on inclusionary housing policies. A
full list of my citations begins on page 62. Finally, I conducted a variety of key informant interviews
with economists, policy experts, advocates, and planners. The findings from these expert interviews
appear throughout the report. A list of the experts consulted for this report appears on pages 60-61.
Some cities, however, have maintained a units-only requirement by authorizing that requirement under the State
Density Bonus law. See, for example, the case study of Los Altos on page 43.
2
Report Overview | Page 5
When and How Should Cities Implement Inclusionary Housing Policies?
ORGANIZATION OF THIS REPORT
In structure, form, and framing, this report relies on Eugene Bardach’s method for policy analysis
known as the Eightfold Path (Bardach 2012). Using this method, I compare four alternative policies
(pages 7-8) against a set of pre-defined criteria (pages 15-17) to make a recommendation about the
preferred policy alternative.
The remainder of the report is organized as follows. I first present the four policy alternatives under
consideration in this report. I then present an overview of the design and structure of these policies
and legal considerations for municipalities considering adopting one of these policies.
The remaining sections of the report project the outcomes of each of the policy alternatives,
organized around the three major criteria outlined in this report. Specifically, the first section in this
part presents the five criteria I will use to evaluate the policy alternatives. The following three
sections address the three key criteria in this analysis. They analyze each alternative’s effectiveness in
minimizing unintended market consequences, promoting housing affordability, and promoting
socioeconomic integration. These sections include the results of my quantitative and qualitative
analyses described above.
The following section summarizes the results of my analysis, systematically comparing each of the
alternatives against each of the criteria. The last section of this report provides my
recommendations.
Report Overview | Page 6
When and How Should Cities Implement Inclusionary Housing Policies?
POLICY ALTERNATIVES
In this section, I present the four major alternative policies that cities may consider when deciding
whether and how to implement a rental inclusionary housing policy. First, a city may choose to
adopt no inclusionary housing policy or eliminate an existing policy, which in general is the baseline
condition. Second, I classify three distinct types of inclusionary housing policies based on their
emphasis on the production of units or payment of fees: fee-focused policies, units-focused policies,
and blended policies that make significant use of both units and fees.
Typically the term “inclusionary housing policy” refers to mandatory units requirements. This term
is also generally interchangeable with others’ use of the term “inclusionary zoning.” In this report,
for the sake of simplicity and parsimony, I use the term “inclusionary housing policy” or
“inclusionary policy” to refer to units, fee, and blended policies.
As discussed in more detail below, there is a distinction between a legal emphasis and a practical
emphasis on units or fees. From a legal perspective, a municipality may make a units-focused policy
its default, but through the program structure, emphasize the payment of fees. It may accomplish
this, for example, by setting the fee level relatively low, which creates an incentive for developers to
pay fees rather than build units. The classifications below reflect a policy focus, but need not also
reflect a legal focus.
ALTERNATIVE 1: NO INCLUSIONARY HOUSING POLICY
Under the first policy alternative, which in some cases serves as the baseline condition, a
municipality may choose not to implement an inclusionary housing policy. Other municipalities that
have inclusionary housing policies may choose to repeal these policies, in which case this alternative
is not the baseline condition.
ALTERNATIVE 2: A UNITS-FOCUSED POLICY
Under units-focused policy, developers must sell or rent a certain percentage of newly-developed
housing at below-market-rate to lower-income households. The most straightforward example of a
units-focused policy is one where the developer may only choose to build units and does not have
the option to pay a fee.
However, a units-focused policy may also include a legal alternative for the payment of fees. From a
legal perspective, these may include fee-first policies, where the legal default is for the developer to
pay fees, or units-first policies, where the legal default is for the developer to produce units. In either
case, to qualify as a units-focused policy, the policy structure must encourage the production of units
such that the majority of developers will choose to build units rather than pay a fee.
ALTERNATIVE 3: A FEE-FOCUSED POLICY
Rather than asking a developer to build units, municipalities can charge a fee to developers and then
use the revenue from that fee for the provision of affordable housing. The most straightforward
Policy Alternatives | Page 7
When and How Should Cities Implement Inclusionary Housing Policies?
example of a fee-focused policy is one where the city requires the developer only to pay a fee, usually
called a housing development impact fee, and does not allow the developer to build units as an
alternative.
However, a fee-focused policy may also include a legal alternative for the provision of units. As
discussed previously, these may include fee-first policies, where the legal default is for the developer
to pay fees, or units-first policies, where the legal default is for the developer to produce units. In
either case, however, to qualify as a fee-focused policy, the policy structure must encourage the
payment of fees such that the majority of developers will choose to pay the fee, rather than build
units.
ALTERNATIVE 4: A BLENDED POLICY
Under a blended policy, the developer may choose to either pay a fee or build units. In its ideal
form, the municipality structures the program so that the median developer faces a meaningful
choice between paying a fee and building units. This design results in a significant provision of both
units and fees for the city. From a legal perspective, the default option for a blended policy could be
either the payment of fees or the production of units.
Policy Alternatives | Page 8
When and How Should Cities Implement Inclusionary Housing Policies?
POLICY DESIGN AND LEGAL CONSIDERATIONS
This section provides the legal justification for inclusionary housing policies, which vary by policy
type. These legal considerations are important for municipalities to consider when implementing any
type of policy. Next, this section presents an overview of the design elements for units-focused, feefocused, and blended policies. Again, these design elements are important for the success of an
inclusionary housing policy, although their details are not a focus of this report. Finally, while
municipalities often apply inclusionary housing requirements to both rental and ownership
developments both this section and this report focus on the rental market.
LEGAL JUSTIFICATION FOR INCLUSIONARY HOUSING POLICIES
The legal justification and requirements are different for units-focused policies, fee-focused policies,
and blended policies.
In general, a city’s legal ability to impose a units-focused inclusionary housing policy falls under its
authority to regulate land use under its police powers. This standard is widely-accepted and relatively
robust under the Supreme Court ruling in Penn Central Transportation Co. v. New York City. Under Penn
Central, inclusionary policies can vary significantly in terms of their impacts on developers as long as
they leave property owners with some profitable use of their properties.
Municipalities’ legal requirements and justifications for fee-focused policies are stricter. The most
important legal justifications for these policies come from a pair of U.S. Supreme Court cases, Nollan
v. California Coastal Commission and Dolan v. City of Tigard, together known as Nollan/Dolan.
Under the Nollan/Dolan standard, municipalities imposing fee-focused policies must meet two
requirements. First, there must be an “essential nexus” between the impact of the development and
the required fee. Second, the fee must be “roughly proportional” to the impact of the development.
Municipalities may address these requirements using a nexus study, which I discuss in greater detail
on page 12.
Municipalities’ legal requirements and justifications for implementing a blended policy or a unitsfocused policy with a fee option are less strict. According to the ruling in San Remo Hotel v. City and
County of San Francisco, as long as the fee structure does not allow for much latitude in calculation and
application, it is not subject to the heightened scrutiny requirements under Nollan / Dolan.
Nonetheless, in Elrich v. City of Culver City, California courts determined that in-lieu fees must still
bear a “reasonable relationship” to their impacts. This standard lies somewhere between Penn Central
and Nollan / Dolan in terms of its deference to local authority (Jacobus and Beech 2015).
While inclusionary housing is largely a local issue, these requirements and restrictions can also vary
by state. Some states have expressly granted municipalities with the authority to, or in some cases
prohibited municipalities from, implementing inclusionary housing policies (Hollister et al 2007).
While it is outside of the scope of this report to discuss all of these differences, a few states bear
Policy Design and Legal Considerations | Page 9
When and How Should Cities Implement Inclusionary Housing Policies?
mentioning. On the prohibition side, Oregon, Texas, and Arizona are the only three states that have
banned inclusionary housing requirements.3
On the facilitation side, New Jersey is the state with the closest example of a statewide inclusionary
housing requirement. In a series of two landmark decisions in New Jersey, the 1975 Mount Laurel
decision and the 1983 Mount Laurel II decision, the Supreme Court interpreted the New Jersey State
Constitution to mean that municipalities must use their zoning powers in an affirmative manner to
provide realistic opportunity for the production of affordable housing. Since 1985, the state has
imposed detailed state regulations that govern the scope, character, and features of inclusionary
housing policies. As a result, while inclusionary housing is not explicitly mandatory in the state, the
cost of alternative means of achieving the state’s legislative and judicial goals has led to
circumstances where it “is at the heart of nearly every suburban fair-share plan” (Calavita, Grimes,
and Mallach 1997).
OVERVIEW OF POLICIES THAT INCLUDE A UNITS REQUIREMENT
In this section, I provide an overview of policies that include a requirement for developers to build
units, either through a units-focused policy, a blended policy, or a fee-focused policy that includes a
units alternative. This section includes the legally required or recommended analyses municipalities
must or should conduct before implementing such a policy and the general structure and design
elements of these policies.
Relevant Analyses
According to a forthcoming legal analysis by Jacobus and Beech (2015), jurisdictions should
undertake economic feasibility studies for inclusionary housing policies with unit requirements. The
goal of a feasibility study is to determine how a new inclusionary policy would affect market-rate
housing development costs and profits. These studies also help policymakers ensure that new
policies are economically sound, will not deter development, and will deliver the types of new
affordable units the local community needs. These studies aim to satisfy the Penn Central test by
showing that the proposed requirements leave property owners with some profitable uses of their
properties.
Design Elements
Inclusionary housing policies are diverse and often flexible. In this section I describe the various
design elements that municipalities may consider when designing a units-focused policy.
Compliance Type. Municipalities may make their inclusionary housing policies voluntary or
mandatory. Under voluntary policies, municipalities offer developers incentives to build units onsite. Municipalities also use these incentives, or cost offsets, under mandatory policies. Under a
mandatory policy, however, a developer does not have a choice about whether or not to build units,
regardless of the cost offsets offered. For the purposes of this analysis, I focus primarily on
mandatory inclusionary housing requirements.
3
Arizona recently passed its ban. The Oregon Legislature is currently considering repealing its state ban.
Policy Design and Legal Considerations | Page 10
When and How Should Cities Implement Inclusionary Housing Policies?
Inclusionary Percentage Requirements. Municipalities vary the percentage requirements of their
inclusionary housing policies—that is, the percentage of units that developers must build as
affordable. These requirements usually range from 10 to 25 percent.
Trigger Size. Some municipalities require developers to build units only when the development is
above a certain size. For example, a developer may only be required to build affordable units in
developments with 10 or more units. Other municipalities do not have a trigger size and the policy
applies to all market-rate development.
Area Median Income (AMI) Targeting. Municipalities require developers to build units so that
they are affordable to families earning various income levels expressed as a percent of area median
income (AMI). This calculation is based primarily
TABLE 2. AREA MEDIAN INCOME TARGETING
on the U.S. Department of Housing and Urban
Development’s (HUD’s) estimates of the median
Category
Income Range
family income for every county each year. HUD
Extremely Low Income < 30% of AMI
defines four income categories based on
Very Low Income
31 - 50% of AMI
Low Income
51 - 80% of AMI
percentages of AMI shown in Table 2.
Moderate Income
81 - 120% of AMI
Municipalities often require developers to build a
certain percentage of units as affordable according to these classifications. For example, a city might
require developers to build 50 percent of their affordable units at very low income and 50 percent at
low income. However, these requirements can be set to any level of AMI. For example, the City of
San Francisco requires developers to build at 55 percent of AMI in the rental market and 90 percent
of AMI in the ownership market.
Source: U.S. Department of Housing and Urban Development
Term of Affordability. Municipalities may set varying affordability control periods, which is the
length of time that the units must remain affordable at the level prescribed. Affordability control
periods can range from 10 years to 99 years (Hickey, Sturtevant, Thaden 2014). A subset of
municipalities requires developers to keep affordable units affordable “in perpetuity” or as long as
possible by law (Mulligan and Joyce 2010).
Alternatives to Construction. Many municipalities allow developers to meet their affordable
housing requirements with other alternatives to building units. Most notably, some communities
allow developers to pay a fee, which is a focus of this report.
Other options include allowing a developer to: (1) build or partner with a non-profit housing
developer that agrees to build the units off-site; (2) convert or rehabilitate existing units and offer
them as affordable; (3) dedicate land to the local government that will accommodate at least a
comparable number of units; or (4) build more units than required in exchange for building fewer
units in a future development.
Cost Offsets. Municipalities offer a variety of cost offsets to either incentivize developers to build
beyond their requirements or to offset the costs associated with building their required number of
affordable housing units. These offsets include: (1) subsidies; (2) fee reductions, waivers, and
Policy Design and Legal Considerations | Page 11
When and How Should Cities Implement Inclusionary Housing Policies?
deferrals; (3) tax abatements; (4) growth control exemptions; (5) design flexibility; (5) fast track
processing; (6) density bonuses; (6) reduced parking requirements; and others.
Density bonuses are some of the most popular cost offsets. Under these allowances, developers are
permitted to build a larger number of units on a given parcel than allowed under conventional
zoning. Design flexibility is another example of a cost offset. Under this allowance, developers still
must design affordable units to look identical or similar to the market-rate units, but are allowed to
vary internal features to facilitate financial feasibility (California Coalition for Rural Housing and
Non-Profit Housing Association of Northern California 2009).
Geographic Tiering or Targeting. Some cities, especially geographically large or heavily populated
cities, have a diverse range of neighborhoods that have different economic and local housing
markets conditions. These cities occasionally use geographic tiering or targeting to add flexibility to
their inclusionary housing policies, allowing them to address the individual needs of their
neighborhoods.
Under these policies, cities will either limit the geographic scope of their policies or adjust their
requirements by neighborhood. For example, in Charlotte, NC and Tallahassee, FL, inclusionary
housing policies apply only to specifically designated census tracts. In Austin, TX and Washington,
D.C., inclusionary policies apply only to specific zoning or planning districts. In Chicago, IL and
Denver, CO, inclusionary policies are calibrated by project type. For example, Denver’s policy only
applies to developments with buildings that have more than three stories, elevators, and over 60
percent of the parking in a garage.
OVERVIEW OF POLICIES THAT INCLUDE A FEE REQUIREMENT
In this section, I provide an overview of policies that include a requirement for developers to pay a
fee, either through a fee-focused policy, a blended policy, or a units-focused policy that includes a
fee requirement. This section includes the legally required or recommended analyses municipalities
must or should conduct before implementing such a policy, the general approaches municipalities
use when setting fees, and how municipalities usually use fee revenues.
Relevant Analyses
Before implementing a fee-focused policy, jurisdictions often complete two types of studies: (1) a
nexus study and (2) a feasibility study.
To satisfy their legal requirements under Nollan/Dolan, a municipality considering imposing a feefocused or fee-first policy should commission a nexus study. These studies establish both the
essential nexus and the rough proportionality required by the Court in those cases.
A nexus study quantifies the new demand for affordable housing that is generated by new
commercial or market-rate housing development. Specifically, using a hypothetical development of
one or more market-rate development projects, the study analyzes how increased household
spending on goods and services would lead to the creation of jobs for lower-income workers. It then
Policy Design and Legal Considerations | Page 12
When and How Should Cities Implement Inclusionary Housing Policies?
estimates the associated demand for housing generated by these workers. The nexus study identifies
the legal maximum supportable fee, or the upper bound, for the municipality when setting a fee.
Jurisdictions should also undertake economic feasibility studies for a fee-focused policy. The goal of
a feasibility study is to determine how a new inclusionary policy would affect market-rate housing
development costs and profits. These studies also aim to satisfy the Penn Central test by showing that
the proposed requirements leave property owners with some profitable uses of their properties.
Approaches for Setting Fees
While the nexus study produces the maximum legal threshold for the fee, most municipalities do not
usually set their fees at this level. Instead, there are three ways a municipality would usually
determine its fee schedule. These are through:
The funding gap or existing production cost. Municipalities use the proceeds from fees to build
or fund affordable housing. Under this specification, the municipality sets the fee to be at least as
much as the gap in funding it must provide to a developer to build affordable housing. That is, the
amount that the public has historically invested to produce each affordable unit. Cities could
calculate this funding gap either including or not including their potential to leverage fee revenue
with state and federal funding sources.
The affordability gap or developer’s opportunity cost. The opportunity cost of a units
requirement is the present value discounted difference between the proceeds of the below-marketrate rent and the rent the developer would have earned at market-rate. Under this alternative, the fee
is based on the typical difference in price between market-rate and affordable units.
A percent of development costs. Finally, making assumptions about profitability and prices,
municipalities can set fees as a fixed percentage of estimated development costs.
All of these are uniform approaches, which use averages that do not vary by development type or
cost. In practice, however, these approaches set an average rate and municipalities may use this
average to construct a fee schedule that is adaptable to various development types and costs.
How Municipalities Use Fees
The proceeds of inclusionary housing fees do not go to General Funds, but rather, often to Housing
Trust Funds or Local Housing Funds for the provision of affordable housing. Municipalities can use
proceeds from Housing Trust Funds in several ways. For example, they can use them for direct
loans or grants to owners or developers of low-income housing; to underwrite bonds sold to
support low-income housing; or for direct low-income rental assistance or homebuyer subsidies.
Some municipalities will also combine fee revenue with a housing levy or voter-approved bonds in
these funds.
Municipalities often leverage these local funding sources with state or federal funding for affordable
housing. The most notable federal funding sources are the Low Income Housing Tax Credit
(LIHTC), which is a dollar-for-dollar tax credit for affordable housing investments; and two HUD
Policy Design and Legal Considerations | Page 13
When and How Should Cities Implement Inclusionary Housing Policies?
programs: the HOME Investment Partnerships Program and the Community Development Block
Grant Program. Many of these federal and state sources require the input of local funds to receive
any funding.
If the city has a high leveraging ratio it may more than triple its funding for affordable housing using
fees as a local commitment to match or complement other funding sources (Jacobus 2015). If the
fee revenue from the inclusionary housing policy is the community’s only source of funding for
affordable housing, then this leveraging may result in a substantial increase in the amount of
affordable housing the community has the capacity to build.
Rather than building units, some cities use their funds to preserve or maintain existing affordable
housing. This may include acquisition and rehabilitation of existing buildings, often done in
partnership with non-profit organizations. Other cities will spend their funds directly to maintain
public housing or other affordable housing projects.
Finally, some cities restrict or target their funding to certain populations, socioeconomic groups, or
neighborhoods. For example, cities can use fees specifically to support housing developments for a
formerly homeless or veteran population. Often funding is not restricted to these uses, but rather
city staff members are given the flexibility to pursue these types of policy priorities.
OVERSIGHT AND MONITORING
Once the affordable units are built, municipalities must dedicate a level of ongoing administration
and oversight to effectively preserve the affordable housing. According to Jacobus (2007) there are
four major administrative tasks associated with overseeing a rental inclusionary housing policy. They
are:
Overseeing the production of new affordable housing units;
Pricing (i.e., setting rents) so that these units are affordable initially and over time;
Marketing of inclusionary housing opportunities and selection of eligible residents; and
Monitoring the units to ensure appropriate occupancy and payment of taxes and insurance.
As Jacobus (2007) notes, to deliver on their potential, “inclusionary housing programs must be well
run.”
While this report does discuss the administrative costs associated with various forms of inclusionary
policies, it does not address these administrative challenges in great detail.
SUMMARY
Cities implementing any type of inclusionary housing policy face a range of policy design options,
which may each contribute to that policy’s effectiveness in promoting lasting housing affordability
or achieving socioeconomic integration. While these design options are not a focus of this report,
they are important to bear in mind for any municipal official who is designing or implementing an
inclusionary housing policy.
Policy Design and Legal Considerations | Page 14
When and How Should Cities Implement Inclusionary Housing Policies?
CRITERIA
This section outlines the five criteria that I use to compare the four policy alternatives described
above. Using Bardach’s (2012) methodology, I outline these criteria so that I can be explicit about
the evaluative standards that I will use to judge the relative merits of each of the proposed policy
alternatives. In short, these criteria define and operationalize the meaning of “success.”
I present these criteria in the order in which they will appear in the remainder of the report, but this
order does not necessarily indicate their relative importance.
Criterion 1: Effectiveness in Minimizing Unintended Market Consequences
A policy is effective in minimizing unintended market consequences to the extent that it minimizes increases in the
price of market-rate housing and decreases in the production of market-rate housing.
The primary criticism levied against inclusionary housing policies is that they may have unintended
market consequences. In particular, critics argue that if inclusionary policies are sufficiently
restrictive they may impose additional costs on developers, restrain the production of housing, and
possibly result in increased prices of market-rate units. These effects could have the added negative
consequence of restraining housing affordability (see criterion below). In the context of still-stifled
housing production from the Great Recession, many municipalities may be particularly concerned
about the potential for an inclusionary policy to further dampen a still-weak housing market.
The extent and magnitude of these relationships is under debate and is a primary focus of this
report. This analysis begins on page 18.
Criterion 2: Effectiveness in Promoting Housing Affordability
A policy effectively promotes housing affordability to the extent that it results in lower rental prices, particularly among
low-cost rental units.
Inclusionary housing policies may promote more housing affordability by: (1) promoting the
production of affordable housing; (2) preserving existing affordable housing; and (3) putting
downward pressure on market-rate units through competitive pressures. However, some have
argued the unintended market consequences listed above erode the policy’s ability to meet this
objective. As a result, it is critical to understand the net effect of an inclusionary housing policy’s
impact on affordability.
Cities seeking to maximize the well-being of their residents may care about housing affordability for
many reasons. The amount that a family spends on housing directly affects its overall well-being. A
dearth of affordable housing in a jurisdiction limits families’ access to employment and good
schools. It requires low-wage workers to make long commutes and therefore inhibits their ability to
participate in their community and household lives. It may also negatively impact businesses that are
unable to meet their employment needs with local workers.
Criteria | Page 15
When and How Should Cities Implement Inclusionary Housing Policies?
The analysis of the extent to which the various policy alternatives promote housing affordability
begins on page 37.
Criterion 3: Effectiveness in Promoting Socioeconomic Integration
A policy is effective in promoting socioeconomic integration to the extent that it provides opportunities for low-income
residents to live in low-poverty neighborhoods.
Municipalities may care about socioeconomic integration either for its own sake or to the extent it
promotes better outcomes among low-income residents or has value to the entire community.
Neighborhood conditions can play a powerful role in the quality of life for individuals in terms of
educational, economic, and social opportunities. Neighborhoods vary in terms of peer influences,
exposure to violence and environmental contaminants, amenities, and social networks and
organization. Better educational and economic opportunities are more likely to be located where
new market-rate housing is being produced or existing housing is high-cost. As a result, to be
effective on this parameter, inclusionary housing policies must promote socioeconomic diversity in
residential neighborhoods so that low-income households are better connected to better educational,
economic, and social opportunities.
Socioeconomic diversity may be the means to promote better outcomes for low-income families,
but it may also be an end itself. On its own, socioeconomic integration may be important to a
municipality that values diversity. As a result, the degree to which a municipality prioritizes this
criterion over others may depend on its own values.
The analysis of the extent to which the various policy alternatives promote socioeconomic
integration begins on page 47.
Criterion 4: Minimizes Administrative Costs
This criterion refers to the extent to which the alternative minimizes administrative costs for the jurisdiction that has
implemented it.
Inclusionary policies may vary in terms of their costs to city taxpayers. These expenses may vary in
terms of the cost of implementation, monitoring, or oversight. Many localities are increasingly costconscious and as a result may want to minimize administrative costs of an inclusionary housing
policy.
While this report does not include a separate analysis of the administrative costs of each of the
policy alternatives, a discussion of these costs appears in the Analysis of Alternatives, beginning on
page 53.
Criterion 5: Likelihood of Achieving Intended Outcomes
This criterion refers to the probability that the alternative will achieve its desired outcomes.
All of the proposed alternatives vary not only in terms of their outcomes under an ideal design but
also in terms of their probability of achieving those outcomes given the political and administrative
Criteria | Page 16
When and How Should Cities Implement Inclusionary Housing Policies?
challenges municipalities face when implementing an inclusionary policy. This criterion captures the
relative certainty with which a policy will achieve its desired outcomes.
While this report does not include a separate analysis of this criterion, a discussion of these
uncertainties appears in the Analysis of Alternatives, beginning on page 53.
SUMMARY
Five criteria, which define the “success” of an inclusionary housing policy, provide the backbone of
the analysis in this report. They are: (1) Effectiveness in Minimizing Unintended Market
Consequences; (2) Effectiveness in Promoting Housing Affordability; (3) Effectiveness in
Promoting Socioeconomic Integration; (4) Minimizes Administrative Costs; and (5) Likelihood of
Achieving Intended Outcomes.
The reminder of the report is organized around the analysis of these criteria. Specifically, the
remaining sections analyze the extent to which various policy alternatives: have unintended market
consequences; promote housing affordability; and promote socioeconomic integration. While this
report does not include a separate analysis of the administrative costs of each of the policy
alternatives or their likelihood of their intended outcomes, a discussion of each of these criteria
appears in the Analysis of Alternatives.
Criteria | Page 17
When and How Should Cities Implement Inclusionary Housing Policies?
DO INCLUSIONARY HOUSING POLICIES HAVE UNINTENDED
MARKET CONSEQUENCES?
The primary criticism levied against inclusionary housing policies is
that they may have unintended market consequences. In particular,
effective in minimizing
critics suggest that when inclusionary policies are restrictive they
unintended market
restrain the production of housing. Alternatively, if they impose
consequences to the
additional costs on developers, those developers may be able to pass
extent that it
along their increased costs to market-rate renters, resulting in
minimizes increases in
the price of market-rate increased prices of those units. These effects could have the added
negative consequence of restraining housing affordability (see
housing and decreases
criterion 2, beginning on page 37). In response to this concern, many
in the production of
municipalities, uneasy about still-stifled housing production leftover
market-rate housing.
from the Great Recession, have either weakened their inclusionary
housing policies or decided not to implement a new one. Yet there is debate over the extent and
magnitude of these relationships.
Criterion 1: A policy is
In this section, I examine whether inclusionary housing policies have unintended market
consequences on housing production and prices. In support of this analysis, I review the literature,
report findings from my case study interviews, and present the results of my quantitative analysis. I
conclude this section by presenting my framework for analyzing whether a units- or fee-focused
policy would have greater unintended market consequences.
REVIEW OF THE LITERATURE AND THEORY
Theory and Evidence on Housing Prices
Based on economic theory, the simple hypothesis of the market effects of inclusionary housing
polices is that they are tax on market-rate development. If an inclusionary policy operates like a tax,
and consumers are not perfectly mobile, the developer would be able to pass along some its costs to
consumers in the form of higher rental prices on new market-rate units. This can only occur if
consumers are willing to pay a premium to live in the location with the inclusionary housing policy
or willing to accept price increases (Padilla 1995). Figure 2 below illustrates this theory, showing that
a tax on housing production will increase equilibrium housing prices from P* to PIH.
In the interest of dispelling a common misunderstanding, it is important to note that these market
effects are aggregate, not individual. That is, a single developer cannot pass along or increase his
prices above the market equilibrium. He would not be able to do this because, seeing his excess
profits, another developer would enter the market, charge the equilibrium price, and draw the
customers away from the more profitable developer. However, if costs increase for all developers
(e.g., a tax or an increase in the price of land or construction costs) then the supply curve will shift to
the left and prices may increase.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 18
When and How Should Cities Implement Inclusionary Housing Policies?
FIGURE 2. SUPPLY AND DEMAND EFFECTS OF A TAX ON DEVELOPMENT
Consumers may not be willing to accept price increases in new market-rate development in the
relevant market because they are able to move to another market or because there are plenty of
housing substitutes in the relevant market. In short, these reactions describe the slope of the
demand curve, which may either be steep and inelastic (i.e., consumers are not price sensitive and
will accept price increases) or shallow and elastic (i.e., consumers are price sensitive and will not
accept price increases).
If consumers are price sensitive, developers have three other possible responses. First, if the
developer does not own land at the time the policy is enacted, it could bargain with landowners for a
lower land price (Calavita and Grimes 1998). Second, some developers may accept that they cannot
raise prices and be able to reduce their profits (Calavita and Grimes 1998, Padilla 1995). Third,
developers may shift housing production to another type, exit the market, or reduce the number of
homes they build (Been 1991, Clapp 1981, and Ellickson 1981). The third response would cause a
reduction in the supply of housing, including market-rate housing, in the market impacted by the
inclusionary housing policy. This unintended effect is discussed further below.
The existing empirical literature on the effects of inclusionary housing policy on prices has generally
found these policies will lead to an increase in the price of market value homes of up to 3 percent.
In a study of California between 1988 and 2005, Bento, Lowe, Knaap, and Chakraborty (2009)
found that inclusionary housing policies had a positive effect on the price of single-family houses,
increasing prices by about 2 to 3 percent. Similarly, and again using evidence from California,
Knaap, Bento, and Lowe (2008) replicated their findings, estimating that in jurisdictions with
inclusionary housing policies, housing prices increase, on average, by 2.2 percent.
In a study of San Francisco and Boston, Schuetz et al. (2009) examined the impact of inclusionary
housing policies on prices and production of market-rate housing production. In Boston, Schuetz et
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 19
When and How Should Cities Implement Inclusionary Housing Policies?
al. (2009) found that a 1 percent increase in years the program was in place leads to a 1.4 percent
increase in the prices of single family homes. In San Francisco, they fail to find an effect of
inclusionary housing policies on prices.
Theory and Evidence on Land Values
The discussion of the effects of inclusionary housing policies on land values is highly related to the
question of home prices. This is the other side of the same coin: when levying a tax on development,
a developer may choose to shift the cost of the tax forward to consumers, through higher housing
prices, or backward to landowners, through lower land values. In fact, on the whole, many
economists believe that, in the long run, the cost burden of an inclusionary housing policy is
capitalized into decreased values of residential land (Calavita and Grimes 1998, Mallach 1984). As
such, in the long-run, it is likely that landowners, and not homebuyers, bear the costs of inclusionary
housing (Calavita and Grimes 1998). It is important to note that this relationship is theoretical and,
to date, there have been no empirical studies of the association between inclusionary housing
policies and land values.
Theory and Evidence on Housing Production
If mandatory inclusionary housing policies are a tax on new residential development, they would
reduce the production of residential properties (Been 1991, Clapp 1981, Ellickson 1981). A
reduction in supply could occur either because the same developers are willing to build fewer units
or because only certain types of developers are willing to build at all (Clapp 1981). Powell and
Stringham (2005) add that many national firms have a choice in setting up or closing shop in any
given state or city and, in the long run, the number of firms will adjust. Figure 2 in the previous
section illustrates this theory, showing that if developers are mobile, a tax on housing production
will reduce equilibrium housing production from Q* to QIH.
Not all inclusionary policies operate as a pure tax on development, however. In some cities, cost
offsets offered to developers may fully offset, or possibly more than offset, the costs of building the
affordable units. In those places, inclusionary policies may even promote more market-rate
development. For example, in cities with very constrained housing markets (e.g., strict density
requirements and other forms of exclusionary zoning) a flexible inclusionary policy that gives density
bonuses and subsidies create opportunities for developers to build more. While this assessment is
theoretical, the implication is that it is not necessarily the case that inclusionary policies would result
in a decrease in the production of market-rate housing.
While the literature is not robust, the available empirical evidence has failed to find credible evidence
of negative relationship between inclusionary housing policies and housing production.
Several studies find no evidence of an effect. Schuetz et al. (2009), for example, found a minor effect
of inclusionary housing on housing production in Boston and no evidence in the Bay Area. Using
data from Los Angeles and Orange Counties, Mukhija et al. (2010) found no statistically significant
evidence of inclusionary zoning’s adverse effect on housing supply in cities with inclusionary
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 20
When and How Should Cities Implement Inclusionary Housing Policies?
mandates. The authors conclude that critics of inclusionary housing policy “overestimate its adverse
effects on housing supply.”
In a study of 28 Californian cities over a 20-year period, Rosen (2004) examined building permit data
to test the effect of inclusionary housing policies on the pace of development. He found no negative
effect on overall production. In some cases, housing production increased. The California Coalition
for Rural Housing and the Non-Profit Housing Association of Northern California (2004) examined
107 inclusionary zoning policies in California and did not find any evidence that the policies slowed
development. Neither of these studies, however, used a methodology that establishes credible
causality and their results should be interpreted as descriptive only.
Other studies have mixed results. In the study of Californian cities, Knaap, Bento, and Lowe (2008)
found that inclusionary housing policies have no significant effect on the number of permits for
single-family housing units. However, they do find that single-family permits as a share of total
permits are lower in jurisdictions with inclusionary housing policies. Bento et al. (2009) found that
cities with inclusionary housing policies did not experience a significant reduction in the rate of
single-family housing starts; however, they did experience a marginally significant increase in multifamily housing starts.
Powell and Stringham (2004) offer the most robust findings that associate inclusionary housing
policies with negative effects on housing production. On average, they found that in cities with
inclusionary housing policies permits declined 10 to 30 percent in the seven years after the policies
were adopted. However, critics have raised concerns about several questionable assumptions and
technical limitations of this study (see Basolo and Calavita 2004). These critics have noted that this
study should be interpreted only as descriptive, not as evidence of a causal relationship between
inclusionary housing policies and housing market outcomes.
Limitations of the Existing Literature
The extant literature suffers from a number of weaknesses. First and foremost, none of the studies
adequately addresses the issue of reverse causality. There is no doubt that cities enact inclusionary
policies in response to eroding affordability (i.e., when prices are increasing). These studies use
difference-in-difference models, controlling for year and city fixed effects, which would not account
for this fact. If, for example, cities adopt inclusionary housing policies when their rates of rental
price growth are higher than typical or higher than their peers that do not adopt these policies, then
the coefficient would be biased upward.
The current literature also fails to address two additional questions: first, it does not address what
would happen to market outcomes if a city removed its existing inclusionary housing policy. Second,
most studies do not address the effects of inclusionary housing policies on mid-sized and small
cities, but rather focus on large cities with hot housing markets, such as Boston and San Francisco.
This analysis aims to respond to these limitations.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 21
When and How Should Cities Implement Inclusionary Housing Policies?
IDENTIFICATION STRATEGY
Before 2009, many jurisdictions in California had mandatory units-focused policies for both
ownership and rental developments. Some, but not all, of these policies allowed developers to use a
fee in place of the units requirement.
In 2009, the California’s Second District of Appeal made a ruling in Palmer/Sixth Street Properties LP
v. City of Los Angeles that called the legality of units-focused policies into question. In the Palmer case,
the court ruled that inclusionary housing requirements on rental developments violate the CostaHawkins Rental Act of 1995. As an alternative that would likely stand up to legal scrutiny,
jurisdictions were able to assess fees on new rental developments rather than require units.
CASE STUDY: SANTA CLARA
In response to the Palmer decision, Santa Clara eliminated its units-focused policy and now has
no rental inclusionary housing requirement.
The City of Santa Clara is located about 45 miles southeast of San Francisco and in the heart of
Silicon Valley. With a population of about 116,000, Santa Clara is one of the ten largest cities in
the San Francisco Bay Area. It is home to the San Francisco 49ers stadium and the headquarters
of several tech companies including Applied Materials, Intel, and Texas Instruments, which are
the city’s largest employers.
Median household income in Santa Clara is about $91,000, above the state median of $61,000.
Median rental prices are $1,609, also above the median state price of $1,224. According to the
most recent estimates from the American Community Survey, Santa Clara’s rental vacancy rate is
low, at about 4 percent, and 55 percent of Santa Clara’s occupied housing units are renteroccupied.
Pre-Palmer. In 2009, Santa Clara had a mandatory, units-focused inclusionary housing policy
established in the city’s housing element. The policy applied to developments with ten or more
units and required developers to build 10 percent of units on-site as affordable. It distributed
affordability levels based on the city’s Regional Housing Needs Allocation (RHNA)
requirements. In general, these resulted in a required distribution of 60 percent of units at 50
percent AMI (very low income) and 40 percent of units at 80 percent AMI (low income). The
program had no fee option.
Post-Palmer. In response to the Palmer decision, Santa Clara suspended its entire inclusionary
housing rental policy. As a result, Santa Clara no longer has an inclusionary housing program that
applies to rental development, although it does have a policy for ownership development.
In the immediate aftermath of Palmer, most jurisdictions with inclusionary policies did one of two
things. First, some jurisdictions stopped enforcing their inclusionary housing rental policies entirely.
For example, before the Palmer decision, both the City of Palo Alto and the City of Livermore had
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 22
When and How Should Cities Implement Inclusionary Housing Policies?
mandatory inclusionary housing policies for rental development that allowed developers to pay a fee
as an alternative to the construction of units. In reaction to the Palmer decision, both cities stopped
enforcing their entire inclusionary housing policy. Similarly, the City of Santa Clara had an
inclusionary housing policy without a fee option. In response to the decision, Santa Clara suspended
its entire rental inclusionary housing policy (for more information about Santa Clara’s policy changes
after Palmer, see the case study description on page 22).
Second, many jurisdictions that had policies that included a fee option stopped enforcing their unit
requirements and converted to a fee-focused policy. For example, before the Palmer decision, the
City of Cupertino had a mandatory units-requirement for developers building seven or more units
and a fee option for developments with six or fewer units. After the Palmer decision, Cupertino
transitioned to a fee-focused policy, requiring all developers to pay a fee (for more information
about Cupertino’s policy changes after Palmer, see the case study description on page 41).
Another subset of jurisdictions continued enforcing both aspects of their policies, although they
maintained the units requirement as an option for developers in conjunction with a fee. Jurisdictions
that had no inclusionary policy, or already had a fee-focused policy, did nothing.
There are two possible ways to interpret this policy change. First, we may interpret this as a
transition from largely units-focused policies to largely fee-focused policies. Second, we may
interpret this policy change as an overall weakening of inclusionary requirements. However, because
fee levels are relatively low in many places, it is reasonable to assume that on average, it was easier
for developers to meet inclusionary housing policy requirements post-Palmer.
Palmer was a state-level ruling, so at the local level the decision to suspend inclusionary requirements
is plausibly exogenous. Exploiting this exogenous shock, I compare outcomes post-Palmer among
those cities that had inclusionary housing policies to those that did not. Unfortunately, my data do
not allow me to systematically identify which cities continued to enforce a fee-focused policy postPalmer. However, the Palmer decision on average weakened inclusionary housing policies statewide,
which means this method allows me to compare market outcomes on average for municipalities
with no inclusionary requirements to those that weakened their policy.
The treatment period begins in 2010. While the Palmer decision occurred in July 2009, it took at least
a few months for cities and developers to react. In one of the quickest reactions, the City of
Cupertino stopped enforcing its unit requirements for rental developments within a few months.
Other cities took longer. For example, the City of Pleasanton did not finish analyzing the legal
implications of Palmer for its inclusionary policy until May of 2010. As a result, 2010 is the first year
that we might expect to see market effects from Palmer.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 23
When and How Should Cities Implement Inclusionary Housing Policies?
EMPIRICAL DESIGN
For the technical reader, I present my two primary model specifications in this section.
Basic Model
Equation 1 below shows the general specification that I estimate for prices and production.
(1) log⁡(𝑦𝑐𝑡 ) = ⁡𝛼 + ⁡𝜏𝐷𝑐𝑡 + ⁡𝛿𝟏(𝑡 = 1) + ⁡𝛾𝟏(𝑐 = 1) + 𝑋𝑐𝑡 𝛽⁡ + ⁡ 𝜀𝑐𝑡
where log(yct) is the natural log of the outcome variable: either rental prices or housing units
produced. D is a dummy variable that equals 1 if the city had a rental inclusionary housing policy
before Palmer and for the treatment period, and 0 otherwise. This variable identifies the model’s
main treatment effect (i.e., treated cities in the treated period). The interpretation of 𝜏 is therefore
the average effect, by city, of the Palmer decision, which on average resulted in a weakening of
inclusionary housing policies.
The model includes year and city fixed effects: t is a vector of dummy variables for years and c is
vector of dummy variables for cities. These fixed effects control for city-specific characteristics that
do not vary over time (e.g., geography) and time-specific characteristics that do not vary by city (e.g.,
statewide economic conditions). X is a vector of time-variant individual city characteristics, including
population size, racial composition, and rates of educational attainment. These variables control for
additional attributes that vary both by time and city.
Standard errors are clustered at the county level because housing market outcomes between cities
that are geographically close to each other are likely correlated with one another.
Event Study Model
Equation 2 below shows the event study specification that I estimate for prices and production.
(2) log⁡(𝑦𝑐𝑡 ) = ⁡𝛼 + ∑𝑇𝑗=𝑡 0 𝜏𝑗 [𝟏(𝑡 = 𝑗)𝑥⁡𝐷)] ⁡ + ⁡𝛿𝟏(𝑡 = 1) + ⁡𝛾𝟏(𝑐 = 1) + 𝑋𝑐𝑡 𝛽⁡ + ⁡ 𝜀𝑐𝑡
Rather than a estimating a single treatment effect, this model allows me to specify a vector of
treatment effects by year, 𝜏𝑗 . This specification gives me the flexibility to examine differences in
treatment and control, year by year. In short, it “unpacks” the pre- and post-period trends into yearby-year estimates.
The event study specification has two advantages over the basic model. First, it allows me to
examine pre-trends in the period before Palmer (i.e., 2007 to 2009). Given that the parallel trends
assumption is a key identifying assumption for the difference-in-differences model, if I find no
statistically significant differences in the pre-treatment coefficients it will strengthen the validity of
the estimate. Second, it allows me to examine the time path of the effect of treatment.
Standard errors are again clustered at the county level.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 24
When and How Should Cities Implement Inclusionary Housing Policies?
DESCRIPTION OF THE DATA
My analysis covers 120 cities in California, which are those cities for which I have 1-year ACS
estimates.4 This section describes the sources for the dependent and independent variables included
in the model.
Dependent Variables: Price
I measure rental prices using annual median rental prices, by city, from the U.S. Census’ one year
American Community Survey (ACS). These one year data are available from 2007 to 2013. To test
whether there is a difference in this outcome for high-cost versus low-cost properties, I run the
same model using two additional outcome variables from the 1-year ACS data: upper quartile rental
prices and lower quartile rental prices. I adjust all rental prices for inflation using the Consumer
Price Index (All Urban Consumers, Current Series).
Dependent Variables: Production
Ideally, to measure the impact of the Palmer decision on housing production, I would use a measure
of the production of rental
FIGURE 3. INCLUSIONARY CITIES IN CALIFORNIA, BY COUNTY, 2009
units. No such data are
available, however, so I
measure housing production
of rental units with a proxy
from the RAND California
Residential Construction
Statistics. RAND reports
monthly permits for various
types of new privately-owned
residential construction, by
city, in California. RAND
imputes some the data from
the U.S. Census. These data
are available from 2006
through the end of 2012.
They include permits by
single-family homes,
duplexes, buildings with
three to four units, and
building with five or more
Source: Author’s analysis with data from California Coalition for Rural Housing.
units.
Image credit: Alex Marqusee.
In general, single-family
homes and duplexes are associated with ownership development and buildings with three or more
The U.S. Census Bureau publishes 1-year estimates for all cities with populations sized 65,000 or more. The fact that
my sample only includes these larger cities may mean that these results are not generalizable to smaller cities.
4
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 25
When and How Should Cities Implement Inclusionary Housing Policies?
units are associated with rental development. As a result, I use the permits for single-family homes
and duplexes to proxy for ownership production and permits for multifamily buildings to proxy for
rental production. I also report my findings using total building permits.
Key Independent Variable
I measure the presence of a mandatory rental inclusionary housing policy with survey data from the
California Coalition for Rural Housing (CCRH), the Non-Profit Housing Association of Northern
California, the Sacramento Housing Alliance and the San Diego Housing Federation. Led by CCRH,
these organizations conducted a survey of inclusionary housing policies between 2008 and 2009. The
data are not time-series, but rather only give a snapshot of what existed in the beginning of 2009. As
a result, I assume that if a city had an inclusionary housing policy in this dataset, it also had that
policy in 2007. I also assume that no city passed a rental inclusionary housing policy between the
survey date (January 2009) and the Palmer decision (July 2009). The qualitative evidence from my
case studies supports these assumptions.
Figure 3 shows the geographic concentration of inclusionary cities, by county, in 2009. It shows the
percent of cities in each county with an inclusionary housing policy. In general, cities with
inclusionary housing policies in 2009 were in coastal counties. The map also shows that few cities in
the Central Valley or Sierra Nevada regions had inclusionary policies.
Control Variables
Table 3 below shows the covariates included in all of the model specifications. This list of variables
follows from those used in Schuetz et al. (2009).
TABLE 3. OTHER INDEPENDENT VARIABLES
Variable
Log of total population
Percent of 19 year-olds and over who are employed
Percent of population that is white
Percent of population that is black
Percent of population that is Hispanic
Percent of population with a BA degree or above
Source
American Community Survey, U.S. Census
American Community Survey, U.S. Census
American Community Survey, U.S. Census
American Community Survey, U.S. Census
American Community Survey, U.S. Census
American Community Survey, U.S. Census
The dataset from CCRH also includes a number of descriptive dimensions of program
characteristics, such as information on set-aside requirement; income targeting; and the presence of
various alternatives to construction; trigger size for requirements; and cost offsets for developers.
These variables are not pre-determined, so it would not be appropriate to include them as covariates.
To test whether the strength of the inclusionary housing policy has an effect on prices or
production, I also ran stratified samples using the models above. I do not report the results from the
stratified samples for two reasons, however. First, I do not find a substantial difference in the effects
of a “strong” policy (defined in various ways) from the effects of an average policy. Second, my
qualitative interviews revealed the policy attribute data are unreliable and subject to excessive
measurement error. Given these facts, I concluded it was inappropriate to report these results.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 26
When and How Should Cities Implement Inclusionary Housing Policies?
DESCRIPTIVE STATISTICS
In 2009, there were 125 cities in California that had inclusionary housing policies in the rental
market, which I will refer to as “treatment” or “inclusionary cities.” I refer to cities without an
inclusionary housing policy in 2009 as “control” or “non-inclusionary cities.” As Figure 3 in the
previous section showed, in 2009 inclusionary cities were largely clustered in the coastal counties,
particularly in the Bay Area and in southern California.
Table 4 shows that, on average, inclusionary and non-inclusionary cities are similar on a variety of
metrics. However, in general, inclusionary cities are more educated and less Hispanic than their noninclusionary counterparts. Cities with inclusionary housing policies also tend to be slightly larger,
although not strikingly so. Excluding San Francisco and Los Angeles, the mean population of
inclusionary cities is 171,977 and the mean population of non-inclusionary cities is 143,598.
TABLE 4. MEAN OF KEY VARIABLES FOR TREATMENT AND CONTROL CITIES IN 2009
Population Mean
Mean Median Rental Price
Mean Percent Employed
Mean Percent White
Mean Percent Black
Mean Percent Hispanic
Mean Percent with BA or above
Treatment Cities
194,136
$1,319
59.9%
65.3%
6.4%
26.9%
39.1%
Control Cities
188,035
$1,241
58.4%
61.7%
8.4%
40.5%
24.8%
Source: Author’s analysis with data from the U.S. Census
The Palmer decision occurred at very unusual time for housing market in California. Residential
permits plunged in 2009, down to 35,000 statewide, about half their rate in 2008, before picking
back up in 2010. Overall housing production continued to lag between 2010 and 2012, however,
housing production in the multi-family market rebounded much quicker (Department of Housing
and Community Development 2012).
Figure 4 below displays the unconditional means of annual multifamily housing construction permits
for inclusionary and non-inclusionary cities.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 27
When and How Should Cities Implement Inclusionary Housing Policies?
FIGURE 4. MEAN ANNUAL RENTAL HOUSING PRODUCTION OF CITIES WITH AND
WITHOUT I NCLUSIONARY HOUSING POLICIES , 2001-2012
Source: Author’s analysis with data from RAND
As Figure 4 above shows, 2009 was the inflection point of rental housing production in California.
While the trends are similar in inclusionary and non-inclusionary cities before and after 2009, it is
clear that inclusionary cities rebounded from the crisis much faster and likely for reasons separate
from the Palmer decision. Given that I cannot completely control for these differences with a
reasonable set of covariates, any estimate for the effect of Palmer on housing production is likely
invalid. In short, the cross-currents in the housing market were just too strong in 2009 to reasonably
isolate an effect of the Palmer decision on housing production.
The basic analysis above shows that these estimates are likely to fail the assumption of parallel
trends. As a result, I do not present results from a production model in this report.
While this period was also a relatively unusual time for housing prices, a basic analysis of median
rental prices reveals that they were much more stable over this period. Rental prices also stagnated
between 2008 and 2010, although generally followed the same trends before 2008 and after 2010.
Figure 5 below shows the unconditional means of median rental prices among inclusionary and noninclusionary cities over the period for which I have data: 2007 – 2013.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 28
When and How Should Cities Implement Inclusionary Housing Policies?
FIGURE 5. MEAN ANNUAL RENTAL HOUSING PRICES OF CITIES WITH AND WITHOUT
INCLUSIONARY HOUSING POLICIES, 2001-2012
Source: Author’s analysis with data from the U.S. Census
According to this basic analysis of pre-trends, a price model is less likely to fail the parallel trends
assumption, which is the key identifying assumption for the analysis below.
RESULTS
In this section I present the results of my analysis for median housing prices, upper quartile housing
prices, and mean residential valuation of multi-family units.
Effects of Palmer on Median Housing Prices
Table 5 below displays the results of my analysis from Equations (1) and (2) on median rental
housing prices. The results in 1a and 2a show the results without the inclusion of covariates.
Specifications 1b and 2b include all covariates listed. Keeping with the convention in the economics
literature, I designate statistically significant coefficients using astrices on the standard errors.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 29
When and How Should Cities Implement Inclusionary Housing Policies?
TABLE 5. EFFECTS OF PALMER DECISION ON MEDIAN RENTAL PRICES
Dependent Variable
Log(Median Rental Prices)
Variable
(1a)
Treatment
0.025
(0.008)**
0.019
(0.008)*
7.041
(0.006)**
0.70
790
0.001
(0.001)
0.002
(0.001)*
0.177
(0.071)*
-0.001
(0.000)**
-0.002
(0.001)
-0.001
(0.001)
0.001
(0.001)
4.878
(0.847)**
0.71
753
2007 Treatment Effect
(1b)
2008 Treatment Effect
2010 Treatment Effect
2011 Treatment Effect
2012 Treatment Effect
2013 Treatment Effect
Percent with BA Degree
Percent Employed
Log of Total Population
Percent White
Percent Black
Percent Hispanic
Percent Under 19
Constant
R2
Observations
(2a)
0.013
(0.012)
-0.010
(0.009)
0.011
(0.009)
0.014
(0.013)
0.035
(0.014)*
0.044
(0.015)**
7.037
(0.007)**
0.70
790
(2b)
0.015
(0.012)
-0.006
(0.009)
0.011
(0.009)
0.014
(0.012)
0.030
(0.013)*
0.035
(0.013)*
0.001
(0.001)
0.002
(0.001)*
0.171
(0.073)*
-0.001
(0.000)**
-0.002
(0.001)*
-0.001
(0.001)
0.001
(0.001)
4.957
(0.871)**
0.71
753
Robust standard errors clustered by county. Table excludes year and city/town fixed effects. * p<0.05; ** p<0.01
The basic specification 1b implies that Palmer is, on average, associated with an increase in median
rental prices of about 2 percent. The event study specification in 2b informs these average results,
showing there is no statistically significant difference between treatment and control groups in the
pre-period trend. After the Palmer decision, the treatment effect is statistically significant in 2012 and
2013, although it is not significant at the .05 level in 2010 and 2011. For the event study specification
the omitted year is 2009, which is also the base year for interpretation. This is the standard
specification for an event study model.
None of these results change substantially if I omit either or both Los Angeles or San Francisco
from the model.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 30
When and How Should Cities Implement Inclusionary Housing Policies?
Using the results from specification 1b, on average, a weakening of inclusionary housing policies
from Palmer is associated with an average increase of 1.9 percent in median rental prices. This
finding is inconsistent with the simple hypothesis that inclusionary housing leads to increased prices.
The result could occur, however, if the reduction in below market-rate units led to increased prices
in the low-cost market and that effect outweighed a decrease in price for new market-rate units.5 If
this is the case, it could be that developers did reduce prices among new units in response to Palmer,
but that effect is washed out on average. To explore whether developers on average lowered prices
in response to the Palmer decision among market-rate units, I use the same specifications, instead
analyzing the effect on upper quartile price.
Upper quartile price is a compelling measure of the price of new market-rate development. First,
most new development is more expensive than average. Second, upper quartile prices are stable
measures. Specifically, unlike measures of quality that would suffer from composition effects, they
are not defined based on a baseline measure of quality. Developers may respond to a tax either by
reducing the number of units built or by reducing the quality of those units. If they are reducing
quality, then a measure of rental prices for new market-rate development that relies on a quality
index could fail to measure an effect of the policy, although one exists. Using upper quartile price
solves this problem.
However, upper quartile price, as measured by the U.S. Census, does not include the value of new
market-rate development. This price would only reflect price effects if the price changes in new
market-rate units also affected the price of existing, high-end units that are substitutes for those new
units. While this is not an unreasonable assumption, I also test the model using the per unit
residential value of multi-family construction permits. This value is not explicitly a rental price, but it
does directly measure changes in the value of new market-rate development, which eases some
concerns associated with upper quartile price.
To test whether developers responded to Palmer by reducing prices among new market-rate units, I
test the same models using upper quartile housing prices as my outcome variable. If there was an
effect of Palmer on price of new development, we would likely observe this as a decrease in upper
quartile rental prices or a decrease in the value of multi-family units.
5
I explore the effect of inclusionary policies on the low-cost market in more detail beginning on page 37.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 31
When and How Should Cities Implement Inclusionary Housing Policies?
TABLE 6. EFFECTS OF PALMER DECISION ON UPPER QUARTILE RENTAL PRICES AND RESIDENTIAL
VALUATION OF MULTI-FAMILY UNITS
Dependent Variables
Log (Upper Quartile
Rent)
(1)
Treatment
2007 Treatment Effect
(2)
0.007
(0.009)
2008 Treatment Effect
2010 Treatment Effect
2011 Treatment Effect
2012 Treatment Effect
2013 Treatment Effect
Percent with BA Degree
Percent Employed
Log of Total Population
Percent White
Percent Black
Percent Hispanic
Percent Under 19
Constant
R2
N
0.003
(0.001)*
0.003
(0.001)**
0.080
(0.074)
-0.001
(0.000)
-0.002
(0.001)
-0.001
(0.001)
0.000
(0.001)
6.086
(0.845)**
0.65
781
0.013
(0.012)
-0.001
(0.010)
0.009
(0.011)
0.007
(0.017)
0.013
(0.014)
0.016
(0.015)
0.003
(0.001)*
0.003
(0.001)**
0.078
(0.076)
-0.001
(0.000)
-0.002
(0.001)
-0.001
(0.001)
0.000
(0.001)
6.115
(0.865)**
0.65
781
Log (Residential Valuation
of Multi-Family Units)
(1)
-0.057
(0.089)
-0.009
(0.008)
-0.003
(0.010)
-0.696
(0.338)*
-0.004
(0.003)
0.007
(0.013)
0.018
(0.013)
0.005
(0.021)
11.674
(0.026)**
0.01
416
(2)
0.049
(0.154)
-0.127
(0.111)
-0.014
(0.102)
-0.227
(0.202)
0.022
(0.165)
-0.010
(0.008)
-0.003
(0.010)
-0.777
(0.376)*
-0.004
(0.003)
0.006
(0.012)
0.016
(0.013)
0.008
(0.021)
20.817
(4.236)**
0.06
400
Robust standard errors clustered by county in parentheses. Table excludes year and city/town fixed
effects. * p<0.05; ** p<0.01
However, as shown in Table 6, in both the basic model (1) and the event study model (2), I fail to
find a statistically significant effect of the Palmer decision on upper quartile rental prices. In general,
this finding is in line with statements from case study interviewees, none of whom reported a
decrease in the price of new market-rate development in response to Palmer. These findings may
suggest that developers do not lower prices of new market rate development in response to a city
repealing or weakening its inclusionary housing policy.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 32
When and How Should Cities Implement Inclusionary Housing Policies?
LIMITATIONS
My specifications identify on an exogenous shock to inclusionary housing policies (the Palmer
decision) so they are less likely to suffer from the typical form of endogeneity present in empirical
investigations of inclusionary housing policies.
Nevertheless, there are other limitations. For one, 2009 was a unique year for housing production
and pricing in California. In particular, housing production was beginning to recover from the
substantial decline that occurred with the housing crisis in 2007-2008. To the extent that
inclusionary cities had different reactions to the post-recession period as non-inclusionary cities, or
recovered at different times, and these reactions affected rental prices differently among these
groups, the recession poses a threat to the internal validity of this study.
One other major policy change occurred in this time frame that also substantially affected the
affordable housing market in California. As part of the 2011 Budget Act, the California Legislature
approved the dissolution of the state’s 400 redevelopment agencies. After a period of litigation,
these agencies were officially dissolved as of February 1, 2012. To the extent that this policy change
affected cities with inclusionary policies at greater rates than cities without inclusionary policies, it
could confound my results. However, given that the timing of Palmer and the elimination of RDAs
are not concurrent, and I find effects in my events study models that occur before dissolution in
2012, it is unlikely that this policy change has impacted my results.
My model almost certainly is affected by a heterogeneous treatment effect. Not all municipalities
entirely suspended their inclusionary housing policies post-Palmer because some municipalities
continued to enforce their fees and some cities maintained a unit-focused policy that included a fee
option. I do not have a way of systematically identifying these cities. From my interviews, I found
that the decision to maintain a fee policy is unlikely to be related to market prices or production, but
rather a municipality’s legal interpretation of the Palmer decision. As a result, this issue likely does not
bias my results, but to the extent that it operates like classical measurement error, it may present
problems for precision.
DOES A FEE- OR UNITS-FOCUSED POLICY HAVE GREATER
UNINTENDED MARKET CONSEQUENCES?
To date, there has been no empirical work to address whether a fee- or units-focused policy would
have greater unintended market consequences. In this section, I develop an economic theory to
analyze this tradeoff.
With a units-focused policy, municipalities can mitigate the potential market consequences for
developers with cost offsets. For example, Padilla (1995) points out that by offering incentives like
low-interest financing, bond programs, or density bonuses municipalities can offset the costs
imposed by inclusionary housing policies. With generous cost offsets, the inclusionary housing
policy may have no impact on prices, profits, or land values. In some cases, cost offsets can make
inclusionary development more profitable and, in theory, could results in an increase of housing
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 33
When and How Should Cities Implement Inclusionary Housing Policies?
production. Without cost offsets, it is unclear whether a units-focused policy would have a greater
cost to developers than a fee-focused policy.
From economic modeling, however, is clear that a blended policy would have the lowest costs to
developers and therefore the lowest unintended market consequences. I develop a model in Figure 6
through Figure 9 to illustrate this point.
FIGURE 6. COST TO DEVELOPERS OF UNITS-ONLY POLICY
Figure 6 above show the marginal cost (MC) to two different developers, of building a development
of the same size. Under this policy, both developers would need to build the same number of units
Qreq, but the cost of building those units is different for the low cost developer than the high-cost
developer. For both developers, the cost of building those units is shown as the area under the
marginal cost curve.
An ideally structured blended policy is structured such that the median developer is indifferent
between paying the fee and building the units. Figure 7 below shows this median developer.
FIGURE 7. IDEAL STRUCTURE OF A POLICY THAT INCLUDES FEES AND UNITS
In Figure 7, the median developer can choose to either build units (on the left) or pay a fee (ont e h
right). If the developer chooses to build units, his costs are shown by the shaded area on the left of
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 34
When and How Should Cities Implement Inclusionary Housing Policies?
the figure above. If he pays the fee his costs are shown by the shaded area on the right. This median
developer is indifferent between building Qreq units and paying the fee level because the costs to that
developer are equivalent under the two policies, i.e., the shaded regions in Figure 7 are geometrically
equivalent.
Returning to the example of the high- and low-cost developers, we see that both developers would
face the same fee burden under a fee-only policy that did not include an option to build units. This is
shown in Figure 8 below.
FIGURE 8. COST TO DEVELOPERS OF FEE-ONLY POLICY
Under a fee-only policy, the high-cost developer is clearly better off than he was under the unitsfocused policy (the shaded area on the right of Figure 8 is smaller than the shaded area on the right
of Figure 6). The low-cost developer, however, is clearly worse off (the shaded area on the left of
Figure 8 is larger than the shaded area on the left of Figure 6). On net neither of these policies is
unambiguously better.
FIGURE 9. COST TO DEVELOPERS OF BLENDED POLICY
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 35
When and How Should Cities Implement Inclusionary Housing Policies?
However, under a policy where the developer has the choice of whether to build on site or pay a fee,
the total costs to developers are unambiguously lower for a blended policy than a fee- or unitsfocused policy. Figure 9 illustrates this point.
Under this option, the low-cost developer would choose to build units and the developer with high
marginal costs would pay the fee. The total cost to both developers is minimized. Minimizing
developer costs will minimize unintended market consequences because increases in prices or
decreases in production of market-rate units depend on the costs to the developer.
SUMMARY
The primary criticism levied against inclusionary housing policies is that they may have unintended
market consequences. In particular, critics suggest that these policies lead to lower levels of
production and higher market-rate prices. The existing empirical literature finds inclusionary housing
policies lead to increases in prices of up to 3 percent and fails to find evidence of an effect of these
policies on housing production. These studies, however, suffer from problems with causal
identification that makes their interpretation problematic.
In the analysis above I examined the effects of a statewide weakening of inclusionary housing
policies on median rental prices and rental building valuations, which addresses some of the
problems associated with causality in the previous literature. I fail to find an effect of repealing an
inclusionary policy on either measure of price.
Theory suggests that repealing an inclusionary policy would have the same, but opposite, market
effects as introducing one (that is, rents should decrease). However, the reality is that these two
policy interventions are not mirror images. We may not expect to see a negative price response in
the upper quartile from the repeal of an inclusionary policy if consumers are not expecting to see a
reduction in price or the rental market is not competitive. Indeed, I fail to find that effect. This does
not mean, however, that there may not be a positive price response associated with the introduction
of an inclusionary policy.
However, the evidence in this report may cast doubt on the strength of that relationship. Indeed if
developers consistently and aggressively increased prices in response to an inclusionary policy and
we assume the rental market is competitive, then developers would lower those prices in response to
a reduction in these requirements. Given that I fail to find an effect of Palmer on upper quartile
rental prices and the valuation of multifamily building permits, we may cautiously interpret these
results as evidence against the claim that inclusionary policies lead to higher prices among marketrate units.
There is no empirical evidence on whether a fee-focused or a units-focused policy more effectively
minimizes the limited unintended market consequences of inclusionary housing policies. However,
relying on evidence from economic modeling, I find that a blended policy would more effectively
minimize unintended market consequences than either a fee- or units-focused policy would.
Do Inclusionary Housing Policies Have Unintended Market Consequences? | Page 36
When and How Should Cities Implement Inclusionary Housing Policies?
DO INCLUSIONARY HOUSING POLICIES PROMOTE HOUSING
AFFORDABILITY?
Inclusionary housing policies may promote more housing
affordability through three avenues: (1) by directly adding to the stock
effectively promotes
housing affordability to of affordable housing; (2) by preserving existing affordable housing;
the extent that it results and (3) by putting downward pressure on market-rate units through
competitive pressures. Inclusionary policies may promote
in lower rental prices,
affordability by affecting rental prices in the overall market or in the
particularly among
low-cost market. Cities may also care about housing affordability in
low-cost rental units.
terms of the price or production of affordable or assisted housing
units for special populations (e.g., seniors or individuals with disabilities).
Criterion 2: A policy
In this section, I analyze whether inclusionary housing policies promote housing affordability in
terms of the three avenues described above. First, I review the existing empirical literature on the
effects of inclusionary housing policies on the production of affordable housing and overall housing
affordability for low-cost housing. Next, I present the results of my analysis of the effects of the
Palmer decision on housing affordability by examining lower quartile rental prices. I conclude by
discussing whether a fee-focused or a units-focused policy would promote more affordability,
defined in various ways.
EFFECT ON THE PRODUCTION OF AFFORDABLE HOUSING
Several studies have descriptively addressed the relationship between inclusionary housing policies
and the stock of affordable housing. In a study of Boston and San Francisco, Schuetz et al (2009)
examined the relationship between inclusionary policies and the quantity of affordable housing built.
The authors use regression analysis to determine which program characteristics are associated with
more or less affordable housing. They found that the number of years a program has been in place
has the strongest positive association with the number of affordable units produced under the
program. According to their estimates, a 1 percent increase in the number of years the inclusionary
housing policy was in place is associated with a nearly 1 percent increase in the city’s total number of
affordable units. In other words, the authors come to the intuitive conclusion that older inclusionary
programs have produced more affordable housing than newer programs.
Mukhija et al. (2010) also described the number of affordable housing units produced under various
inclusionary housing policies in a number of cities in Southern California. Their analysis is largely
descriptive, but the authors conclude that it suggests “inclusionary zoning has the potential to be an
important source of affordable housing (but perhaps not for the very poor).”
In a survey of inclusionary housing before Palmer, NPH (2007) estimated that municipalities in
California developed about 4,500 affordable units per year as a result of their inclusionary policies.
Rusk (2005) estimated that inclusionary housing policies with at least a 15 percent set aside produce
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 37
When and How Should Cities Implement Inclusionary Housing Policies?
twice as many affordable housing units as LIHTC funds. Brown (2001) estimated that inclusionary
policies can double the number of affordable houses produced.
EFFECT ON THE PRICE OF AFFORDABLE HOUSING
While theory may suggest that inclusionary policies would cause price increases among new marketrate development, they should have the opposite effect in the unregulated low-cost market. Figure
10 below shows the theoretical mechanism by which inclusionary policies would affect both the lowcost and high-cost market.
In the low-cost market, inclusionary policies’ requirements result in an increase in the supply of lowcost housing that would not have occurred in the absence of the policy. As shown in the first panel
below, this would increase quantity supplied from Q* to QIH and reduce price from P* to PIH. The
second panel of Figure 10 displays the effect on market-rate development displayed earlier in this
report. In other words, according to economic theory, an inclusionary housing policy leads to price
increases in the market-rate or high-cost market, but price decreases in the low-cost market. As a
result, inclusionary housing policies may promote housing affordability.
FIGURE 10. PRICE AND PRODUCTION EFFECTS OF INCLUSIONARY IN LOW- AND HIGH-END OF MARKET
The studies in the previous section examine the relationship between inclusionary policies and the
provision of affordable housing (i.e., quantity). Few studies have tried to examine whether these
affordable units—or the presence of an inclusionary housing policy—has an effect on affordability
(i.e., price). One exception is a study of inclusionary housing policies in California by Knaap, Bento,
and Lowe (2008). The authors first examined overall price effects, finding that in jurisdictions with
inclusionary housing policies, housing prices increase, on average, by 2.2 percent. The authors broke
out these effects by market segment, finding that these policies are associated with a price increase
of about 5 percent for above-median priced houses, but a price decrease of about 0.8 percent for
below-median price households. Their study suggests that inclusionary policies may promote
affordability among low-cost units.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 38
When and How Should Cities Implement Inclusionary Housing Policies?
Effects of Palmer on Lower Quartile Rental Prices
Using the empirical strategy described in the previous section, if Palmer resulted in a weakening of
inclusionary housing policies, we may expect to see an increase in the price of low-cost units
(movement from PIH to P* in the first panel above). Using the same specifications from the previous
section, I examine the effects of the Palmer decision on lower quartile rental prices. As with upper
quartile prices, I expect this measure is robust to composition effects.
TABLE 7. EFFECTS OF PALMER DECISION ON LOWER QUARTILE RENTAL PRICES
Dependent Variables
Variables
Treatment
2007 Treatment Effect
Log(Lower Quartile Rental Price)
(1)
0.032
(0.009)**
2008 Treatment Effect
2010 Treatment Effect
2011 Treatment Effect
2012 Treatment Effect
2013 Treatment Effect
Percent with BA Degree
Percent Employed
Log of Total Population
Percent White
Percent Black
Percent Hispanic
Percent Under 19
Constant
R2
Observations
-0.002
(0.002)
0.002
(0.001)*
0.154
(0.066)*
-0.000
(0.000)
-0.002
(0.001)
-0.001
(0.001)
-0.000
(0.002)
4.872
(0.719)**
0.64
753
(2)
0.033
(0.015)*
0.008
(0.015)
0.037
(0.012)**
0.040
(0.018)*
0.051
(0.015)**
0.054
(0.016)**
-0.002
(0.002)
0.002
(0.001)
0.150
(0.068)*
-0.000
(0.000)
-0.002
(0.001)
-0.001
(0.001)
-0.000
(0.002)
4.922
(0.753)**
0.65
753
Robust standard errors clustered by county. Table excludes year and city fixed effects. * p<0.05; ** p<0.01
In the basic model (1) in Table 7, I find a statistically significant and positive effect of the Palmer
decision on lower quartile housing prices. Under the average model, the Palmer decision is associated
with a roughly 3 percent increase in lower quartile rental prices. This finding is robust to the event
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 39
When and How Should Cities Implement Inclusionary Housing Policies?
study specification (2), which shows there is limited evidence of a pre-period difference between the
treatment and control groups, but there is a difference in prices in every year following Palmer.
In general, these findings are consistent with reports from case study interviews. For example, city
staff members from both Cupertino and Santa Clara—two cities that weakened their inclusionary
policies in response to Palmer—reported that since the Palmer decision, their cities have experienced
challenges with meeting their community’s affordable housing needs. Moreover, a Cupertino city
staff member expected that, in the years after Palmer and to come, the city will experience an overall
loss of its affordable rental housing stock as the affordability term on existing affordable housing
built with its inclusionary housing program expires.
Are These Price Effects Realistic?
Some might argue that it would be difficult to see a price effect from a small addition of below
market-rate units that results from an inclusionary policy. First, this argument underestimates the
amount of affordable housing produced under inclusionary policies in California. As noted earlier,
pre-Palmer, municipalities with inclusionary policies in California produced about 4,500 affordable
units per year, these programs may produce twice as many affordable housing units as produced
with LIHTC funds, and these policies can double the total number of affordable houses produced.
This argument also dismisses the competitive pressures of the marketplace. Interviews with housing
experts and economist revealed that, either through signaling or by directly adding to the stock of
low-cost housing, small changes in production can have discernable effects on rental prices,
particularly when rental vacancy rates are low.
For example, when a city adds units at the lowest levels of affordability, renters take those units who
otherwise would have competed for moderate income units. This occurs frequently with students
and day laborers who are often willing to live together in larger groups to afford a rental unit that
individually they would not have been able to afford. Often, these groups can out-compete families
whose collective incomes are lower, although the families’ individual members’ incomes may be
higher. To the extent that inclusionary weakens these competitive pressures, it may reduce housing
prices even above the lower quartile.
Finally, the estimate in this report is not substantially greater than the estimate of the effect of
inclusionary housing policies on below median prices found in Knaap, Bento, and Lowe (2008). In
that report, the authors estimated that inclusionary housing policies are associated with a reduction
in price among below median priced units of 0.8 percent. Cities implement inclusionary policies
when prices are rising, particularly at the low-end of the spectrum. Knaap, Bento, and Lowe’s (2008)
model cannot completely account for this reverse causality. Given these facts, it is plausible that the
authors underestimate the magnitude of the negative effect of inclusionary policies on affordability
of low-cost units. In this context, a 3 percent price effect is not unreasonable.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 40
When and How Should Cities Implement Inclusionary Housing Policies?
CASE STUDY: CUPERTINO
With its transition from a units-focused to fee-focused policy after the Palmer decision, Cupertino provides a
helpful qualitative comparison of these two alternative policy types.
Cupertino lies directly west of San Jose. It is a wealthy city, with median household income of
$130,000 and median gross rents above $2,000 per month. Its economy is in large part supported
by Apple, Inc., which employs over 15,000 people in its headquarters located in Cupertino.
In 2013, the population of Cupertino was about 55,000. According to the most recent estimates
from the American Community Survey, the rental vacancy rate is 4.9 percent and just over a third
of Cupertino’s occupied housing units are renter-occupied. Fewer than 15 percent of renters pay
gross rental cost of $1,500 or less.
Pre-Palmer: Cupertino has had a housing mitigation program in place since 1993. Under this
program, developers building market-rate residential rental developments with between one and
six units had to pay a fee. Residential developments with seven or more units were required to
construct 15 percent of the units as below market-rate (BMR). For residential rental BMR units,
60 percent had to be made available to very low income residents (up to 50 percent of AMI), and
the other 40 percent to low income households (up to 80 percent of AMI).
The program generated 138 BMR on-site rental units between its inception and 2009. These units
are generally scattered throughout the city in high-density areas.
Post-Palmer: In response to Palmer, Cupertino removed its units requirement for residential
rental developments with seven or more units and charged them the fee instead. All market-rate
residential rental developments in Cupertino must pay this fee.
The existing fee level is $3 per square foot for all floor area, excluding parking structures. The fee
increases each year automatically with the Consumer Price Index (CPI). City staff reported this
fee level is the lowest in the County of Santa Clara for jurisdictions that have a housing
mitigation program. Cupertino is interested in increasing its fee level and is currently in the
process of conducting a nexus study update to explore the increase.
Cupertino collects the proceeds of its fees into the Below Market-rate Affordable Housing Fund.
To distribute the funds, Cupertino publishes an annual request for proposals (RFP). Cupertino
has used the funds for acquisition of small subdivisions for ownership and new construction, for
example by granting funding to Habitat for Humanity and Charities Housing. The City also uses
funding for preservation and maintenance of existing affordable housing units.
As in many places, it is costly to build developments at less than 80 percent of AMI in Cupertino,
so the fee-focused policy does not achieve a lower level of affordability than the units-based
program achieved. Significant administrative costs are required for both programs. On the unitsbased side, staff time is required to get developer through the development process. On the feebased side, the city monitors the existing database, reporting requirements, and the RFP process.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 41
When and How Should Cities Implement Inclusionary Housing Policies?
DOES A FEE- OR UNITS-FOCUSED POLICY PROMOTE MORE
AFFORDABILITY?
The first part of this section describes the tradeoffs fee- and units-focused policies face in terms of
generating affordable housing through the production of affordable housing, which may put
downward pressure on unregulated low-cost units through compeition. Cities may also care about
housing affordability for special populations, like veterans or seniors. The second part of this section
addresses the relative strength of fee- or units-focused policies to promote housing affordability for
special populations.
Promotion of Housing Affordability
The previous analysis in this report suggests that inclusionary housing policies promote housing
affordability in the low-cost market. However, this analysis cannot address the differences between
fee- and units-focused policies in terms of these effects. This section qualitatively describes some of
the considerations and factors that would lead a units-focused, fee-focused, or blended policy to
promote more or less affordability.
First, neither policy is capable of promoting affordability in cities with no market-rate development.
Without development, no affordable units are produced under an inclusionary policy and none of
the avenues listed above achieved. The remainder of this discussion applies to cities with some nonzero level of development.
There are several factors that determine the effectiveness of a fee-focused policy relative to a unitsfocused policy in terms of achieving more housing affordability.
In financial terms, land costs and leveraging ratios play the most significant roles in terms of a city’s
ability to produce more affordable units under a fee- or units-focused policy. Land costs can be
significant. This means the marginal cost of an additional unit in an existing development is often
lower than the marginal cost for a unit in a new development off-site, even if those units are
produced in a lower-cost area. Leveraging ratios are also critical. If the city cannot leverage its fee
revenue to gain additional state and federal funding, it is likely to achieve more units with a unitsfocused policy. If the city has a high leveraging ratio and the cost and availability of land is relatively
low, it may build more units with a fee-focused policy.
A city also needs the administrative capacity to effectively spend and use the fee revenue should it
select a fee-focused policy. Los Altos, for example, a small city with population of 30,000, has had a
units-focused policy since 1992 (see case study on page 42). A city staff member from Los Altos
reported that since the City has never had a redevelopment agency, a big commercial base, and was
never a net provider of housing, it lacks the administrative capacity to spend fee revenue.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 42
When and How Should Cities Implement Inclusionary Housing Policies?
CASE STUDY: LOS ALTOS
Los Altos is one of the few cities that has maintained a units-focused rental program post-Palmer.
Los Altos is a city in Santa Clara County, at the southern end of the San Francisco Peninsula.
Los Altos was once a primarily agricultural town, but is now primarily a commuter town.
Commercial zones in Los Altos are strictly limited to the downtown area, a commercial
thoroughfare (SR 82), and small shopping and office centers.
In 2013, the population of Los Altos was less than 30,000. Median household income in Los
Altos is about $157,000, well above the state average of $61,000. Median rental prices in Los
Altos are above $2,000 per month. According to the most recent estimates from the American
Community Survey, the rental vacancy rate is nearly zero and only 15 percent of Los Altos’
occupied housing units are renter-occupied.
Pre-Palmer: Los Altos has had an inclusionary housing policy in place since the early 1990s.
Many community members in Los Altos struggled to accept the inclusionary policy at first and
even threatened to referendum the City Council to repeal the policy. After city staff conducted
outreach and education around the program, the community accepted it.
Since 1992, Los Altos has built 105 BMR units through its inclusionary program, including 32
rental units. Its AMI targeting for rental developments is low and very low.
The policy initially had a negotiable units requirement percentage. In 2009, Los Altos adjusted
the policy to fix the percentage on site. It is now 10-15 percent or 20 percent depending on the
category of development. It applies to developments with five or more units (developments with
fewer units are exempt). Developments with five to nine units can petition for an exemption if
the requirement is financially unfeasible and those with ten or more units must build. Los Altos
does not offer developers an in-lieu fee, although they do allow developers to build off-site
under some circumstances.
Post-Palmer: Los Altos is one of the few municipalities in California that has maintained its
units-focused rental inclusionary requirement post-Palmer.
Los Altos’ program is exempt from Palmer because the city authorizes its program under the
State Density Bonus Law. In short, there is an exemption to the Costa Hawkins Act that allows
rent restrictions on units developed pursuant to a contract with local government to provide
incentives and concessions similar to those in the State Density Bonus Law. That exemption
does not apply when the developer is mandated by local law to enter into a contract to provide
affordable units. As a result, Los Altos has not substantially changed its units requirement since
the Palmer decision or in response to the Palmer decision.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 43
When and How Should Cities Implement Inclusionary Housing Policies?
NIMBYism may also pose an additional complication for fee-focused policies not inherent in unitsfocused policies. In some cases, community opposition to affordable housing creates a significant
and sizeable delay or barrier to using fees to build affordable housing off-site. When developers
build units on-site in an existing development, there is a smaller chance of the project confronting
NIMBY challenges.
However, the most critical factor determining the effectiveness of a fee- versus a units-focused
policy for achieving housing affordability is the level of the fee. According to both expert interviews
and case study interviews, cities often set their fees below the optimal rate (see page 34 for a
discussion of the optimal fee level). Politically, it is often difficult to set a fee at the level determined
in the nexus or feasibility study. Yet a low fee rate fundamentally compromises the ability of a city to
provide affordable housing since its funding stream will be small relative to the units it would have
achieved with a units-focused policy. As a result, if a city is unable to set a fee appropriately under a
fee-focused policy, a units-focused policy would be much more effective in promoting housing
affordability. The importance of this uncertainty is a topic of discussion in the Analysis of Alternatives,
beginning on page 53.
Cupertino (case study on page 41) is an example of a city that transitioned from a units-focused to a
fee-focused policy post-Palmer. While Cupertino is unique in many ways, its experience may provide
a helpful case study on this subject. After transitioning to a fee-focused policy with a relatively low
fee ($3 per square foot) Cupertino experienced a reduction in its ability to provide affordable
housing through its inclusionary housing policy, in part because its fee and associated revenues are
insufficient to build affordable housing at the rates it experienced under a units-focused policy.
Finally, it is possible, but not yet documented, that a blended policy has the highest likelihood of
successfully promoting housing affordability. Under these ideally-structured policies, when
developer opportunity costs are high, the developer would pay a fee. In these cases the municipality
is likely to be able to build more units for the same price elsewhere, and perhaps also achieves lower
levels of affordability. When developer opportunity costs are low, by contrast, the developer would
build the additional units, plausibly at the same, or lower, cost than the city would be able to fund
off-site.
Promotion of Housing Affordability for Special Populations
Depending on their individual needs, municipalities may care about promoting affordability among
special populations such as seniors, individuals with disabilities, veterans, formerly homeless
residents, or extremely low-income residents.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 44
When and How Should Cities Implement Inclusionary Housing Policies?
CASE STUDY: LIVERMORE
Before the Palmer decision, Livermore exhibited a well-designed and implemented blended inclusionary housing
policy. The city eliminated its rental policy after the Palmer decision.
Livermore is a city in Alameda County, about 30 miles east of the coastal range of mountains
that surround the Bay Area. It is home to Lawrence Livermore National Laboratory and the
California site of Sandia National Laboratories, which are the city’s largest employers. The south
side of the Livermore is surrounded by agricultural land, including vineyards.
In 2013, the population of Livermore was about 85,000. Median household income in
Livermore is about $99,000, well above the state average of $61,000. Median rental prices in
Livermore are $1,448, above the state average, but in general low compared to the city’s median
income. According to the most recent estimates from the American Community Survey, the
rental vacancy rate is 4.2 percent and less than 30 percent of Livermore’s occupied housing units
are renter-occupied.
Ownership development is much more common in the City of Livermore than rental
development. In part, this may be the result of the city’s relatively low rental prices (compared to
incomes) and relatively high cost of land.
Pre-Palmer: Livermore has had an inclusionary housing policy in place since the 1990s. The
city had a strong mandatory on-site performance requirement, but also allowed developers to
pay a fee. This fee was set at the threshold of the developers’ opportunity costs. At its peak, the
fee was about $11.65 / square foot and increased with the Consumer Price Index (CPI).
City staff used revenue from the fee to support a diversity of development projects. For
example, the city used the fees to build senior housing and extremely low income housing, fund
homeless shelters and other housing services like tenant-based rental assistance programs, and
provide mortgage and down-payment assistance. During the housing downturn, city staff used
proceeds of the fee to pivot to an “acquisition and rehabilitation model.” For example, city staff
worked with Habitat for Humanity to acquire single family homes, rehabilitate them, and sell
them to low-income residents and, in particular, veterans.
Post-Palmer: In response to Palmer, Livermore eliminated its on-site rental requirement.
Moreover, in response to the housing downturn around the same time, Livermore also
eliminated its impact fees assessed on rental development and must-build requirement for
ownership development. As the economy recovered, Livermore reinstated its ownership
inclusionary program and is now seeking to reinstate its fee program for rental development.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 45
When and How Should Cities Implement Inclusionary Housing Policies?
In this domain a fee-focused policy may be stronger than a units-focused program. With a unitsfocused policy, some cities require the developer to take a role in managing the newly-built
affordable rental housing. Commercial developers often do not have the capacity to manage serviceenriched housing. Fee-focused policies always involve administration and oversight by the city’s
staff or a non-profit developer. For example, the City of Livermore, which uses a blended policy, is
able to effectively support housing for seniors, individuals with disabilities, and the formerly
homeless population with revenue from the fees (see case study on page 45).
Units-focused policies also do not typically target very low levels of affordability because the perunit cost to developers is much higher than it would be for alternative targeting (Hughes and
Vandoren 1990). As such, a fee-focused policy may achieve lower levels of affordability and
affordability for special populations.
While it is often the case that a fee-focused policy can reach lower levels of affordability, it is not
always the case. For example, in Cupertino where development costs are relatively high, it is
difficult—sometimes impossible—to build developments at less than 80 percent of AMI in
Cupertino. As a result, the City’s fee-focused policy does not achieve a lower level of affordability
than the units-focused policy achieved pre-Palmer.
SUMMARY
While there is little evidence of the effect of inclusionary housing policies on housing affordability in
the existing literature, the analysis from this report provides some guidance on this question. In my
analysis above, I find a strongly statistically significant and positive effect of weakening an
inclusionary housing policy on the price of low-cost units. Specifically, on average, the Palmer
decision is associated with a 3 percent increase in price among lower quartile rents. In general, these
quantitative findings are also consistent with reports from case study interviews. These results
suggest that, on average, inclusionary housing policies help promote housing affordability for lowincome residents.
Neither a fee-focused nor a units-focused policy is capable of generating affordable units in cities
with no development. The extent to which a fee-focused policy will generate more affordable
housing than a units-focused policy depends on a range of characteristics, including the city’s cost of
land, leveraging ratio, administrative capacity, and NIMBY challenges. The most important factor,
however, is the fee level. If the city has the political will to set the fee appropriately then a feefocused policy can be more effective in promoting housing affordability. Otherwise, a units-focused
policy is more effective in promoting housing affordability.
Do Inclusionary Housing Policies Promote Housing Affordability? | Page 46
When and How Should Cities Implement Inclusionary Housing Policies?
DO INCLUSIONARY HOUSING POLICIES PROMOTE
SOCIOECONOMIC INTEGRATION?
Municipalities may care about socioeconomic integration either for
its own sake or to the extent it promotes better outcomes among
effective in promoting
low-income residents or has value to the entire community.
socioeconomic
Neighborhoods vary in terms of peer influences, exposure to
integration to the
violence and environmental contaminants, amenities, and social
extent that it provides
networks and organization. Better educational and economic
opportunities for lowopportunities are more likely to be located where new market-rate
income residents to
housing is being produced or existing housing is high cost. As a
live in low poverty
result, to be effective on this parameter, inclusionary housing policies
neighborhoods.
must promote socioeconomic diversity in residential neighborhoods
so that low-income households are connected to better educational, economic, and social
opportunities.
Criterion 3: A policy is
Socioeconomic diversity may be the means to promote better outcomes for low-income families,
but it may also be an end itself. On its own, socioeconomic diversity may be important to a
municipality that values diversity. As a result, the degree to which a municipality prioritizes this
criterion over others may depend on its own values.
In this section, I analyze whether inclusionary housing policies promote socioeconomic integration.
First, I review the existing empirical literature on the effects of inclusionary housing policies on
socioeconomic integration. I then discuss the implications of this research for outcomes among
recipient households, such as employment and education. I conclude by discussing whether a fee- or
units-focused policy would promote more socioeconomic integration.
REVIEW OF THE LITERATURE
To date, there have been few robust empirical studies of the effects of inclusionary policies on
economic or racial integration. No studies analyze the effect of inclusionary policies on outcomes
for recipients, such as improved educational outcomes or higher employment rates. This analysis
reviews the literature on the effects of inclusionary policies on integration and then uses studies of
other integration programs to predict the effect of inclusionary policies on outcomes.
Effects of Inclusionary Housing Policies on Socioeconomic Integration
The most rigorous study on this subject to date—called Is Inclusionary Zoning Inclusionary?—was
published by the Rand Corporation in 2012. In the study, Schwartz et al. (2012) tested the
assumption that inclusionary policies promote social inclusion by examining 11 inclusionary
programs across the United States. Specifically, they examine the extent to which inclusionary
policies “serve low-income families and provide IZ [inclusionary zoning] recipients with access to
low-poverty neighborhoods and residentially assign them to high-performing schools.”
Do Inclusionary Housing Policies Promote Socioeconomic Integration? | Page 47
When and How Should Cities Implement Inclusionary Housing Policies?
FIGURE 11. PERCENTAGE OF INCLUSIONARY UNITS LOCATED IN LOW-POVERTY NEIGHBORHOODS ,
2005-2009
From: Schwartz et al. (2012) page 13, figure 2.1
The authors conclude that these policies do promote economic integration. They find that
inclusionary homes are dispersed throughout jurisdictions, in low-poverty neighborhoods, and are
assigned to relatively low-poverty public schools. Figure 11 above displays the results of their
findings on the percent of inclusionary homes located in low-poverty neighborhoods. As the figure
shows, however, this percentage varies widely by locality. For example, these percentages are
relatively high in Fairfax County and Irvine, but low in Boulder and Cambridge. The authors do not
offer a detailed analysis on the drivers of these differences, but program design elements are likely
responsible for the discrepancies.
The authors also examine the assignment of inclusionary units to high-performing schools. On
average, they find that inclusionary units were “residentially assigned to schools that had lower
poverty rates and performed slightly above average within their state.” By city, the authors also find
that elementary school poverty rates in inclusionary schools closely tracked poverty rates among
non-inclusionary schools (Schwartz et al. 2012). On the whole, the authors conclude that these
results suggest that inclusionary policies “offer the potential, if not the promise, of social inclusion
for recipients.”
Homquist (2009) analyzed the effect of an inclusionary policy on racial integration, economic
integration, and access to social services using a case study of Davis, California. The author
compared trends in residential patterns of race, income, and social services using a census tract-level
analysis before and after the implementation of the policy. She found that there is a relationship
between Davis’ inclusionary policy and “increased racial integration and access to social services”
but failed to find evidence of integration for income groups.
Do Inclusionary Housing Policies Promote Socioeconomic Integration? | Page 48
When and How Should Cities Implement Inclusionary Housing Policies?
Krefetz (2001) analyzed the effects of a program in Massachusetts that allowed local zoning boards
to streamline application procedures for developments that include affordable housing. The author
found that the number of communities with 10 percent or more affordable units rose and the
number of communities with no affordable housing dropped 15 percent.
In a study of Montgomery County’s inclusionary housing policy, Rusk (1999) found that in 15 of 18
of the County’s planning areas, townhouses that sold for an average of about $84,000 were sited
next to a detached single-family home selling for about $550,000.
Effects of Socioeconomic Integration on Well-Being
As noted earlier, while a city may care about socioeconomic integration for its own sake, integration
is important to the extent that it promotes better outcomes for recipients. These outcomes might
include improved physical and mental health, better employment opportunities, and improved
educational outcomes. As a result, it is important to ask: What are the effects of inclusionary policies
on outcomes for recipient families and individuals?
While there is no available literature to address this question directly, we might gain insights from
the robust empirical literature that estimates the effects of moving to a lower-poverty neighborhood
on outcomes. While there are a wide range of studies on the subject, the literature that presents the
most convincing evidence relies on the Moving to Opportunity project.
Under the Moving to Opportunity (MTO) demonstration project, the U.S. Department of Housing and
Urban Development used a random lottery to offer some public housing families, but not others,
the chance to move into a less distressed area. Several researchers have collected data on participants
for a number of years after randomization, allowing them to estimate the short- and long-term
effects of the program.
There has been other empirical and qualitative research in this area. However, the MTO literature
has two important advantages for the purposes of this discussion. First, because papers based on the
MTO program rely on random assignment for identification, they establish causality much more
credibly than other studies that use observational data. In short, compared to the MTO literature,
the findings from any non-randomly assigned programs are lower quality and less credible. Second,
for one treatment group, the MTO program required that participants move to a lower-poverty
neighborhood in order to participate. Other studies that have examined the effect of housing on
outcomes that do not rely on this mechanism cannot credibly establish the outcomes of
socioeconomic integration and therefore are less relevant to this discussion.
The findings from the MTO program have been disappointing to those who believe that integration
will confer significant economic and educational benefits to its beneficiaries.
For adults, a number of empirical studies have failed to find an effect of MTO on traditional,
objective measures of well-being and economic outcomes, such as employment, earnings, or welfare
receipts (Katz et al. 2000; Sanbonmatsu et al. 2011; DeLuca, Duncan, Keels, and Mendenhall, 2010;
Jacob 2004; and Oreopoulos 2003).
Do Inclusionary Housing Policies Promote Socioeconomic Integration? | Page 49
When and How Should Cities Implement Inclusionary Housing Policies?
For children, the studies found positive outcomes in the short-run, but failed to find evidence of
positive outcomes in the long-run. In widely-cited study of the short-run effects of the MTO study,
Katz et al. (2000) found that children in beneficiary families are less likely to be personally victimized
by crime, be injured, or suffer from an asthma attack. In a study of long-run impacts of MTO on
children, Gennetian et al. (2012) found that the program had few detectable effects on a range of
schooling outcomes—including test scores, dropout rates, and delinquency—and physical health
outcomes. These patterns were slightly more favorable among female youth than male youth.
Yale Law School Professor and influential housing economist Robert Ellickson summarized the
literature this way: “recently published studies have begun to destabilize the former consensus that a
poor adult or child is significantly disadvantaged by residing among other poor people … the case
for dismantling an entire poor neighborhood … is hardly so plain” (2009).
A later study by Ludwig et al. (2012) provides a note of optimism among these results. The authors
estimated the effects of moving out of a distressed community on the well-being of low-income
adults. For outcome variables, Ludwig et al. (2012) examined both traditional “objective” measures
of well-being, such as physical and mental health, and a self-reported measure of subjective wellbeing. The authors found that “a 1-standard deviation decline in neighborhood poverty increases
subjective well-being by an amount equal to the gap in subjective well-being between people whose
annual incomes differ by $13,000.” This is a significant amount given that the median control group
income is $20,000.
Despite the strength and credibility of the MTO literature, readers may want to be cautious when
extending its results to the potential beneficiaries of inclusionary housing policies. There are
important differences in the target populations of these programs that may alter their effects among
the two groups. Specifically, families were only eligible for MTO if they resided in public housing or
project-based Section 8 assisted housing in census tracts with a poverty rate of 40 percent or more.
Beneficiaries of inclusionary housing policies, by contrast, are often low or moderate income
families with incomes up to 50 or even 100 percent of area median income. These families may live
in higher-poverty neighborhoods but are unlikely to live in public housing or project-based Section 8
assisted housing.
As a result, the findings from the MTO literature, while insightful, may not perfectly extend to
inclusionary housing.
Do Inclusionary Housing Policies Promote Socioeconomic Integration? | Page 50
When and How Should Cities Implement Inclusionary Housing Policies?
CASE STUDY: SANTA ROSA
Santa Rosa has had a fee-focused policy in place since 1992. As a result, the City did not revise or modify that
policy in response to the Palmer decision.
The City of Santa Rosa is the county seat of Sonoma County, located about 55 miles north of
San Francisco. With a population of about 180,000, Santa Rosa is the largest city in California’s
North Coast and the fifth largest city in the San Francisco Bay Area. The largest employers in the
city are the County of Sonoma and Kaiser Permanente.
Median household income in Santa Rosa is about $60,000, just below the state average of
$61,000. The median rental price in Santa Rosa is just above state averages, at $1,244, compared
to $1,224. According to the most recent estimates from the American Community Survey, the
rental vacancy rate is 4.7 percent and 46 percent of Santa Rosa’s occupied housing units are
renter-occupied.
Pre-Palmer: Santa Rosa established its inclusionary housing program in 1992 as a units-focused
policy. However, the development community struggled to meet the program’s requirements,
finding building units on-site to be cost prohibitive. City staff reported that most developers in
Santa Rosa build single family homes and that these are too expensive to build affordably.
Meanwhile, it was difficult for developers to market a single family development with multifamily units nearby. In response to these concerns, the City Council amended the inclusionary
program to allow developers to pay a fee rather than build units on site.
At the time of the Palmer decision in 2009, Santa Rosa had a fee-focused policy in place.
Post-Palmer: It already had a fee-focused policy, so Santa Rosa did not substantially change its
inclusionary housing program in response to the Palmer decision. Developers still have the choice
to build on-site, although few take this option. Developers who build a development with 70 or
more units are required to meet with the Department of Community Development to consider
providing units on-site. The current fee schedule ranges by the size of the unit built, from $1.16 /
square foot to $6.55 / square foot.
The proceeds of Santa Rosa’s housing development impact fee are distributed into the Santa
Rosa Housing Trust Fund. These resources are pooled with others and the Housing Authority
makes funding commitments. The proceeds of the impact fee are restricted to new construction
and are not used for the preservation of existing units. The City does not acquire land with these
funds, but rather relies on non-profit developers to buy land for development. Santa Rosa also
leverages the proceeds from its fee-focused policy to get tax credit funding from other state and
federal resources.
Most of Santa Rosa’s affordable housing is built on the west side of highway 101, where land is
flat, there is a greater availability of vacant land, and development costs are lower than in other
parts of the city. This distribution of affordable units may result in lower administrative costs for
the City because units are not scattered throughout the community and are therefore easier to
monitor for compliance.
Do Inclusionary Housing Policies Promote Socioeconomic Integration? | Page 51
When and How Should Cities Implement Inclusionary Housing Policies?
DOES A FEE- OR UNITS-FOCUSED POLICY PROMOTE MORE
SOCIOECONOMIC INTEGRATION?
In theory, a well-designed fee-focused policy is capable of producing socioeconomic integration at a
neighborhood level if the city’s program administrators prioritize affordable housing development in
low-poverty neighborhoods.
However, in practice, a units-focused policy is more likely to more socioeconomic integration than a
fee-focused policy. New development tends to occur in higher-income neighborhoods, so unitsfocused policies increase concentrations of affordable units in high-income neighborhoods.
Fee-focused policies, which rely on the city’s or developer’s ability to pay for cheap land, tend to
produce units in lower-demanded and less desirable neighborhoods. For example, most of Santa
Rosa’s affordable housing from its fee-focused program is built in an area where development costs
are lower (see case study on page 51). Housing advocates have argued that, since this area of the city
is also less desirable, this program does not sufficiently promote socioeconomic integration.
According to experts, cities using fee-focused policies also are more likely to encounter NIMBY
challenges that prevent them from building in higher-income neighborhoods where residents are
often more vocal and resistant to assisted housing.
SUMMARY
Municipalities may care about socioeconomic integration either for its own sake or to the extent it
promotes better outcomes among low-income residents or has value to the entire community. The
limited available literature does find evidence that inclusionary housing policies lead to more
socioeconomic integration. Both theory and findings from expert interviews and case studies suggest
that units-focused policies lead to more socioeconomic integration than fee-focused policies.
Neither a fee-focused nor a units-focused policy is capable of promoting socioeconomic integration
in cities with no development.
The best quality existing empirical literature on the effect of integration on outcomes comes from
randomized housing vouchers. This literature finds that moving a family from a high-poverty to
low-poverty neighborhood has varying outcomes on well-being. On the one hand, these programs
did not lead to better employment or long-term educational outcomes for their beneficiaries. On the
other hand, the literature has found that these moves improve subjective well-being of adults and
short-run health outcomes for children. While these studies provide the best evidence available, their
results may not extend to inclusionary housing policies because beneficiaries of inclusionary policies
tend to be higher-income than their counterparts from the randomized voucher literature.
Do Inclusionary Housing Policies Promote Socioeconomic Integration? | Page 52
When and How Should Cities Implement Inclusionary Housing Policies?
ANALYSIS OF ALTERNATIVES
This section summarizes the analysis above by criteria and alternative. It systematically describes the
outcomes associated with each of the four alternatives according to the five criteria.
To provide the reader with a sense of their magnitude, I evaluate each of the five criteria by
alternative in a scorecard. If a policy is likely to achieve a given criteria, it receives a score of 3. If a
policy is unlikely to achieve a given criteria, it receives a score of 1. For example, if a given
alternative is ineffective in achieving socioeconomic integration, it would receive a score of 1 for that
criterion. If a given alternative minimizes administrative costs, it would receive a score of 3 for the
relevant criterion.
This analysis does not pertain to one specific municipality or policy decision. As a result, this section
gives a general discussion of the extent to which each of these criteria would or would not hold
under the alternatives’ outcomes, and the characteristics that would lead to a more effective or
feasible alternative.
It is for the reason, as well, that I do not weigh the criteria below. A city considering adopting an
inclusionary policy may choose to use these scorecards, but must weigh each criterion according to
its local importance. Since there is no weighting in these generic scores, it would be inappropriate
for the reader to sum the scores and use a “total score” to compare the alternatives.
ALTERNATIVE 1: NO INCLUSIONARY HOUSING POLICY
Under this scenario, a municipality would either choose not implement an inclusionary housing
policy or it would repeal an existing inclusionary housing policy.
TABLE 8. NO INCLUSIONARY HOUSING POLICY SCORECARD
Criterion
Effectiveness in Minimizing Unintended Market Consequences
Effectiveness in Promoting Housing Affordability
Effectiveness in Promoting Socioeconomic Integration
Minimizes Administrative Costs
Likelihood of Achieving Intended Outcomes
Score
3
1
1
3
3
There are no market distortions associated with no inclusionary housing policy. The findings from
the analysis above, however, suggest that this alternative would not result in substantially different
market outcomes than those under an inclusionary housing policy. If there is a difference, the results
from the literature suggest that an inclusionary policy could result in increased prices for market-rate
housing of up to 3 percent and no difference in terms of housing production. Moreover, in the
analysis above, I fail to find evidence that weakening an inclusionary policy is associated with a
decrease in the rental price of high-cost housing units. As a result, I fail to find evidence of any
additional market benefits to repealing an existing inclusionary housing policy.
Analysis of Alternatives | Page 53
When and How Should Cities Implement Inclusionary Housing Policies?
The results from the analysis above suggest that inclusionary housing policies, in general, promote
affordability, particularly in the low-cost market. Without an inclusionary housing policy, a
municipality could build affordable housing using other funding sources, but it would be
substantially less effective in doing so than it would with an inclusionary housing policy. As a result,
no inclusionary housing policy receives a score of 1 for promoting housing affordability.
Similarly, a municipality without an inclusionary housing policy would be constrained in its ability to
promote socioeconomic integration. As the analysis above shows, inclusionary housing policies,
particularly units-focused policies, are effective in promoting socioeconomic integration, in
particular compared to other methods of building affordable housing. As a result, this alternative
receives a score of 1 for promoting socioeconomic integration.
There would be no administrative costs associated with the policy. As a result, this alternative
receives a score of 3 for that criterion.
This outcome is relatively certain and so receives a score of 3.
ALTERNATIVE 2: A UNITS-FOCUSED POLICY
This analysis assumes that a municipality would set its performance requirement in the typical range
(about 10-20 percent) and would use AMI targeting ranges of moderate, low, and very low. These
results are sensitive to various other program design elements, in particular cost offsets. For
examples of units-focused policies, see the case studies of: Santa Clara pre-Palmer (page 22), Los
Altos (page 43), and Cupertino pre-Palmer (page 41).
TABLE 9. A UNITS-FOCUSED POLICY SCORECARD
Criterion
Effectiveness in Minimizing Unintended Market Consequences
Effectiveness in Promoting Housing Affordability
Effectiveness in Promoting Socioeconomic Integration
Minimizes Administrative Costs
Likelihood of Achieving Intended Outcomes
Score
2
3
3
1
3
In general, inclusionary housing policies have few unintended market consequences. On average,
they may raise the price of market-rate housing by up to 3 percent and likely do not have an effect
on housing production. As such, these policies generally have few unintended market consequences
compared to no policy and receive a score of 2, compared to 3 under no policy. Depending on the
underlying market dynamics, a units-focused policy could have either a greater or a smaller market
impact than a fee-focused policy. Cities can mitigate these potential impacts by providing developers
with cost offsets.
As with fee-focused and blended policies, a units-focused policy is effective in terms of generating
affordable units. The analysis above suggests that the presence of an inclusionary housing policy
keeps prices about 3 percent lower in the low-cost market. As a result, this policy receives a score of
Analysis of Alternatives | Page 54
When and How Should Cities Implement Inclusionary Housing Policies?
3. There is no available empirical evidence on whether a blended, units- or fee-focused policy would
promote more housing affordability. However, evidence from case studies and experts suggest that
several elements would determine this tradeoff. In particular, cities with low administrative capacity,
high cost of land, a low leveraging ratio, or problems with NIMBYism would likely find that unitsfocused policy is more effective in promoting housing affordability than a fee-focused policy.
Of the alternatives, units-focused policies create the most socioeconomic integration by requiring
developers to build units in existing new market-rate developments—which are generally located in
low-poverty neighborhoods. As a result, this alternative receives a score of 3 for this criterion.
The administrative costs associated with an inclusionary housing policy can be significant. In
Cupertino, a case study city that has clear experience with both policy types, the city interviewee
reported that neither policy has been significantly more expensive than the other. As a result, both
units- and fee-focused policies receive a score of 1 for minimizing administrative costs.
The likelihood of a city achieving the desired outcomes under this policy design is relatively high.
There is some uncertainty associated with a city’s capacity to negotiate effectively with developers,
particularly if the program involves a number of cost offsets. However, the typical design of unitsfocused policies matches their ideal design. Specifically, cities usually set the performance standard
between 10 and 20 percent, which is the accepted best practice. As a result, this alternative receives a
score of 3 for its high likelihood of achieving the desired outcomes.
ALTERNATIVE 3: FEE-FOCUSED POLICY
This analysis assumes that a municipality would set its fee schedule at the efficient level (the median
developers’ opportunity cost). For examples of a fee-focused policy, see the case studies of Santa
Rosa (page 51) and Cupertino post-Palmer (page 41).
TABLE 10. FEE-FOCUSED P OLICY SCORECARD
Criterion
Effectiveness in Minimizing Unintended Market Consequences
Effectiveness in Promoting Housing Affordability
Effectiveness in Promoting Socioeconomic Integration
Minimizes Administrative Costs
Likelihood of Achieving Intended Outcomes
Score
2
3
1
1
1
As with units-focused policies, fee-focused policies have few unintended market consequences.
Depending on the underlying market dynamics, a fee-focused policy could have either a greater or a
smaller market impact than a units-focused policy. As a result, both fee-focused and units-focused
policies receive a score of 2 in terms of minimizing unintended market consequences, compared to a
score of 3 under the baseline condition.
As with units-focused and blended policies, a fee-focused policy is effective in terms of generating
affordable units. The analysis above suggests that the presence of an inclusionary housing policy
keeps prices about 3 percent lower in the low-cost market. There is no available empirical evidence
Analysis of Alternatives | Page 55
When and How Should Cities Implement Inclusionary Housing Policies?
on whether a blended, units- or fee-focused policy would promote more housing affordability. As a
result, this policy receives a score of 3. However, cities with high administrative capacity, low cost of
land, a high leveraging ratio, and no problems with NIMBYis may find that fee-focused policy is
more effective in promoting housing affordability than a units-focused policy. In addition, a welldesigned fee-focused policy may be more effective for generating housing for special populations,
such as seniors or individuals with disabilities.
Compared to a units-focused policy, a fee-focused policy, which relies on the City’s or developer’s
ability to pay for cheap land, tends to produce units in lower-demanded and less desirable
neighborhoods. As a result, fee-focused policies are unlikely to promote socioeconomic integration
and receive a score of 1.
For the reasons discussed above, both fee- and units-focused policies result in similar administrative
costs. Both policies receive a score of 1 for this parameter.
The likelihood of a city achieving the ideal outcomes under this policy type is low compared to a
units-focused policy. For political reasons, most cities set fees well below the amount determined in
the nexus study or feasibility study. These rates are often lower than developers’ opportunity costs.
Under these typical designs, municipalities often have to wait several years to pool enough money to
build an affordable housing development. This uncertainty casts doubt on this alternative’s ability to
meet the outcomes under other criteria. Specifically, setting the fee schedule incorrectly would
compromise the city’s ability to promote housing affordability and socioeconomic integration. As a
result, this alternative receives a score of 1 in terms of its likelihood of achieving its desired
outcomes.
ALTERNATIVE 4: BLENDED POLICY
This analysis assumes that a municipality would set its average fee at the median developer’s
opportunity cost, but also allow developers to build units. In this case, the median developer would
face a meaningful choice between paying a fee and building the units. From a legal perspective, the
default option for a blended policy can be either units or fees. For an example of a well-designed
blended policy, see the case study of Livermore on page 45.
TABLE 11. BLENDED POLICY SCORECARD
Criterion
Effectiveness in Minimizing Unintended Market Consequences
Effectiveness in Promoting Housing Affordability
Effectiveness in Promoting Socioeconomic Integration
Minimizes Administrative Costs
Likelihood of Achieving Intended Outcomes
Score
3
3
2
1
1
If properly structured, this type of policy can be the most effective for both minimizing unintended
market consequences and generating affordable housing. By allowing a developer to pay a fee or
build units, developers with low opportunity costs will build units and those with high opportunity
Analysis of Alternatives | Page 56
When and How Should Cities Implement Inclusionary Housing Policies?
costs will pay the fee. This minimizes costs to developers and is therefore more effective in terms of
minimizing unintended market consequences.
A blended policy is effective in terms of generating affordable units. The analysis above suggests
that the presence of an inclusionary housing policy keeps prices about 3 percent lower in the lowcost market. As a result, this policy receives a score of 3. There is no available empirical evidence on
whether a blended, units- or fee-focused policy would promote more housing affordability.
Theoretically, this type of policy would achieve less socioeconomic integration than a units-focused
policy, but more integration than a fee-focused policy. As a result, in terms of its ability to achieve
socioeconomic integration, this alternative receives a score of 2, higher than the score for a feefocused policy, and below the score of a units-focused policy.
Blended policies may involve more administrative time and capacity to execute successfully because
city staff members must take on a wider variety of responsibilities and roles. For example, this
variety in responsibilities may require extra staff time for training on new duies, although this
additional staff time is likely to be limited. As a result, while the administrative costs associated with
a blended policy may be slightly higher than among the other alternatives they are unlikely to be
substantially higher. As with fee- and units-focused policies, a blended policy receives a score of 1
for minimizing administrative costs.
As with a fee-focused policy, the likelihood of a city achieving the ideal outcomes is the lowest
under a blended policy. In fact, well-designed blended policies are unusual in practice. For political
reasons, most cities set fees well below the amount determined in the nexus study or feasibility
study. These rates are often lower than developers’ opportunity costs. Consequently, the city has
effectively enacted a fee-focused policy, and not a meaningful blended policy. This uncertainty again
casts doubt on this alternative’s ability to meet the desired outcomes under other criteria, such as
socioeconomic integration and housing affordability. As a result, this alternative receives a score of 1
in terms of its likelihood of achieving the desired outcomes.
Analysis of Alternatives | Page 57
When and How Should Cities Implement Inclusionary Housing Policies?
SUMMARY OF RECOMMENDATIONS
Based on the analysis above, I cannot conclude there is a one-size-fits-all inclusionary housing policy
for all municipalities. Nor can I conclude that every municipality should pursue some type of
inclusionary housing policy.
Table 12 below shows the projected outcomes of each of the alternatives in terms of the five key
criteria. Since this analysis does not pertain to an individual city, I cannot make judgments about the
weighting (importance) of each of the criteria. Therefore, to avoid confusion for readers that may
result from an unweighted numeric scoring table, this table displays marks instead. A policy receives
a for scores of 2 or 3 and a for a score of 1.
TABLE 12. COMPARISON OF ALTERNATIVES
Criterion
No Policy
Units-Focused Fee-Focused
Policy
Policy
Blended
Policy
Effectively Minimizes Unintended
Market Consequences
Effectively Promotes Housing
Affordability
Effectively Promotes
Socioeconomic Integration
Minimizes Administrative Costs
Certainly Achieves Intended
Outcomes
The “no policy” alternative is generally not preferable unless the city has very low levels of
development. Moreover, cities without current or future challenges associated with housing
affordability should prefer a no policy condition, although it is unlikely that such cities would be
exploring the option of establishing an inclusionary housing policy. The analysis here suggests that
eliminating or weakening an existing policy will not confer additional benefits to market-rate or
high-cost renters.
The analysis reveals that a units-focused policy is a good default alternative. It robustly achieves its
intended outcomes, is the easiest to implement, and is effective in terms of generating affordable
housing, promoting socioeconomic integration, and minimizing unintended market consequences.
Small cities with low administrative capacity, in particular, should consider implementing this policy.
In addition, cities should also consider this option when land is scarce and expensive or when
community members may oppose the development of affordable housing in their neighborhoods.
Cities that have the political will to set fees at the correct level should consider a blended policy. If
the fee level is set appropriately, the policy has a high probability of success (although in general
there is a low probability that a given city will set the fee level correctly). In particular, a city would
Summary of Recommendations | Page 58
When and How Should Cities Implement Inclusionary Housing Policies?
want to consider implementing a blended policy if: it has a high leveraging ratio, there is community
support for fees and affordable housing, and NIMBYism is generally not a problem. Cities should
also consider this alternative if they are seeking to create affordable housing for extremely lowincome residents or other special populations.
Cities generally should not implement a fee-focused policy unless, for legal reasons, it is the only
option. In general, a fee-focused policy does not have any benefits over a units-focused policy or a
blended policy.
CONCLUSION
It is impossible to make any definitive broad claims about inclusionary housing policies because
there is no one-size-fits-all inclusionary housing policy for all municipalities. However, while I
cannot conclude that every municipality should pursue some kind of inclusionary housing policy, in
general this analysis shows that these policies are appealing policy options for municipalities
confronting challenges related to housing affordability.
Specifically, inclusionary housing policies are adaptable to local needs, are associated with few
unintended market consequences, and are effective in achieving their policy goals. As the analysis
above shows, they promote housing affordability and socioeconomic integration. It is also unlikely
that they have significant costs in terms of increased housing prices or and likely have no effect on
the production of market rate housing.
As such, cities with development that are currently facing, or expecting to face, challenges related to
housing affordability may want to consider adopting some form of an inclusionary housing policy.
Summary of Recommendations | Page 59
When and How Should Cities Implement Inclusionary Housing Policies?
CASE STUDY INTERVIEWEES AND KEY INFORMANTS
CASE STUDY INTERVIEWEES
Scott Erickson, Housing Specialist, Housing Division, City of Pleasanton
Hillary Gitelman, Director, Planning and Community Environment, City of Palo Alto
(correspondence by email)
Nancy Gornowicz, EDH Manager, Economic Development and Housing, City of Santa Rosa
David Kornfield, Planning Services Manager, Community Development, City of Los Altos
Lisa Kranz, Supervising Planner, Community Development, City of Santa Rosa
May Lee, Housing Project Manager, Housing, City of Fremont
Eloiza Murillo-Garcia, Housing Development Officer, Housing and Community Services, City of
Santa Clara
Eric Uranga, Housing and Human Services Manager, Housing and Human Services, City of
Livermore
Christopher Valenzuela, Senior Housing Planner, Community Development, City of Cupertino
KEY INFORMANTS & EXPERT INTERVIEWS
Josh Abrams, Consultant, Cornerstone Partnership
Dewey Bandy, Deputy Director, California Coalition for Rural Housing
Carol Galante, University of California, Berkeley, I. Donald Terner Distinguished Professor in
Affordable Housing and Urban Policy
Hilary Hoynes, Professor of Public Policy and Economics, Haas Distinguished Chair in Economic
Disparities, University of California, Berkeley
Rick Jacobus, Consultant, Cornerstone Partnership
Danielle Mazzella, Policy and Research Intern, Nonprofit Housing Coalition of Northern California
Alastair McFarlane, Director, Economic Development and Public Finance Division, Office of Policy
Development and Research, U.S. Department of Housing and Urban Development
Mark Obrinsky, Senior Vice President of Research and Chief Economist, National Multifamily
Housing Council
Monica Palmeira, Program Specialist, California Coalition for Rural Housing
Case Study Interviewees and Key Informants | Page 60
When and How Should Cities Implement Inclusionary Housing Policies?
Danilo Pelletiere, Economist, Economic Development and Public Finance Division, Office of
Policy Development and Research, U.S. Department of Housing and Urban Development
Paul Peninger, Economist, Principal, Peninger Consulting
Carolina Reid, Assistant Professor of City & Regional Planning, University of California, Berkeley
Larry Rosenthal, Assistant Adjunct Professor of Public Policy, University of California, Berkeley
Lisa Sturtevant, Executive Director of the Center for Housing Policy and Vice President for
Research, National Housing Conference
Emily Thaden, Research & Policy Development Manager, National Community Land Trust
Network
Case Study Interviewees and Key Informants | Page 61
When and How Should Cities Implement Inclusionary Housing Policies?
WORKS CITED
Altshuler, Alan A. and Jose ́ A. Gomez-Ib́añez. 1993. Regulation for Revenue: The Political
Economy of Land Use Exactions. Washington D.C.: Brookings Institution and Cambridge, MA:
Lincoln Institute of Land Policy.
Arizona Daily Star. 2015. “New law bars affordable housing requirements.” April 1.
Baden, Brett M. and Don L. Coursey. 1999. An Examination of the Effects of Impact Fees on
Chicago’s Suburbs. Harris School Working paper 99, 20, University of Chicago, Harris Institute.
Basolo, Victoria and Nico Calavita. 2004. “Policy Claims with Weak Evidence: A Critique of the
Reason Foundation Study on Inclusionary Housing in the San Francisco Bay Area.” Working
paper.
Bardach, E. 2012. A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving
(4th edition). Richard and Rhoda Goldman School of Public Policy, University of California,
Berkeley. Los Angeles, CA: Sage Publications, Inc.
Been, Vicki. 2005. “Impact Fees and Housing Affordability” Cityscapes, 8, 139.
Bento, Antonio, Scott Lowe, Gerrit-Jan Knaap, and Arnab Chakraborty. 2009. “Housing Market
Effects of Inclusionary Zoning” Cityscape, 11.2, Regulatory Innovation and Affordable Housing
7-26.
Burge, Gregory. 2008. "Impact Fees in Relation to Housing Prices and Affordable Housing Supply,”
Book chapter in A Guide to Impact Fees and Housing Affordability. Editors A. Nelson, J.
Juergensmeyer, J. Nicholas, and L. Bowles, Island Press.
Burge, Gregory S. and Keith R. Ihlanfeldt. 2006a. “Impact Fees and Single-Family Home
Construction” Journal of Urban Economics, 60, 284-306.
Burge, Gregory S. and Keith R. Ihlanfeldt. 2006b. “The Effects of Impact Fees on Multifamily
Housing Construction” Journal of Regional Science, 46, 5-23.
California Coalition for Rural Housing and the Non-Profit Housing Association of Northern
California. 2004. “Inclusionary Housing in California: 30 Years of Innovation.” Inclusionary
Zoning: The California Experience. National Housing Conference 3 (1).
Calavita, Nico and Kenneth Grimes. 2007. “Inclusionary Housing in California: The Experience of
Two Decades.” Journal of the American Planning Association, 64 (2), 150-169.
Collinson, R., I. Ellen, and J. Ludwig. 2015. Low-Income Housing Policy. Washington, D.C.: National
Bureau of Economic Research. March.
Works Cited | Page 62
When and How Should Cities Implement Inclusionary Housing Policies?
Clapp, John M. 1981. “The Impact of Inclusionary Zoning on the Location and Type of
Construction Activity.” AREUEA Journal, 9: 436-456.
Delaney, Charles J. and Marc T. Smith. 1989a. “Impact Fees and the Price of New Housing: An
Empirical Study.” AREUEA Journal, 17, 41-54.
Delaney, Charles J. and Marc T. Smith, 1989b. “Pricing Implications of Development Exactions on
Existing Housing Stock.” Growth and Change, 20, 1-12.Delaney and Smith 1989 and 1989b,
DeLuca, S., G. J. Duncan, M. Keels, R. Mendenhall. 2010. Housing Policy Debate 20(7).
Downing, Paul B. and Thomas S. McCaleb. 1987. “The Economics of Development Exactions.” In
Development Exactions, edited by James E. Frank and Robert M. Rhodes, 42-69. Washington
D.C.: Planners Press.
Dresch, Marla and Steven M. Sheffrin. 1997. Who Pays for Development Fees and Exactions. San
Francisco, California.: Public Policy Institute of California.
Ellen, I. and S. Dastrup. 2012. “Housing and the Great Recession.” The Russell Sage Foundation
and the Stanford Center on Poverty and Inequality. October.
Ellickson, R. 1981. “The Irony of ‘Inclusionary’ Zoning.” Southern California Law Review 54(6):
1167-1216.
Ellickson, R. 2009. Property Rights and Land Policies, G. Ingram, Y.-H. Hong (eds). Cambridge, MA:
Lincoln Institute of Land Policy, pp. 418–452.
Evans-Cowley, Jennifer S., and Larry L. Lawhon. 2003. “The Effects of Impact Fees on the Price of
Housing and Land: A Literature Review,” Journal of Planning Literature. Vol. 17: 351–359.
Evans-Cowley, Jennifer S., Fred A. Forgey, and Ronald C. Rutherford. 2005. “The Effect of
Development Impact Fees on Land Values.” Growth and Change, 36, 100-112.
Gennetian, L., M. Sciandra, L. Sanbonmatsu, J. Ludwig, L. Katz, G. Duncan, J. Kling, and R.
Kessler. 2012. “The Long-Term Effects of Moving to Opportunity on Youth Outcomes.”
Cityscape: A Journal of Policy Development and Research 14(2): 137-68.
Hickey, R., L. Sturtevant, and E. Thaden. 2014. “Achieving Lasting Affordability through
Inclusionary Housing.” Lincoln Institute of Land Policy.
Huffman, Forrest E., Arthur C. Nelson, Marc T. Smith, and Michael A. Stegman. 1988. “Who Bears
the Burden of Development Impact Fees?” Journal of the American Planning Association, 54,
49-55.
Works Cited | Page 63
When and How Should Cities Implement Inclusionary Housing Policies?
Hollister, T., A. McKeene, and D. McGrath. 2007. National survey of statutory authority and practical
considerations for the implementation of inclusionary zoning ordinances. Washington, DC: National
Association of Home Builders.
Ihlanfeldt, Keith R. 2004. “Exclusionary Land-use Regulations within Suburban Communities: A
Review of the Evidence and Policy Prescriptions”. Urban Studies, 41(2), 261-283.
Ihlanfeldt, Keith R. and Timothy M. Shaughnessy. 2004. “An Empirical Investigation of the Effects
of Impact Fees on Housing and Land Markets”. Regional Science and Urban Economics. 34(6),
639-661.
Iglesias, Michael. 2014. “Application for Leave to File Amici Curaie Brief and Amici Curiae Brief of
Leo T. McCarthy Center for Public Service and the Common Good and Forty-Five Housing
Scholars in Support of Defendant and Respondent city of San Jose.” California Building Industry
Association (Petitioner) v City of San Jose and City Council and Mayor of the City of San Jose. Affordable
Housing Network of Santa Clara County.
Jacob, B.A. 2004. American Economic Review 94, 233.
Jacobus, R. 2007. “Delivering on the Promise of Inclusionary Housing: Best Practices in
Administration and Monitoring.” PolicyLink.
Jacobus, R. 2015. “Inclusionary Housing: Fees vs. Units.” Cornerstone Partnership Webinar.
February 12.
Jacobus, R. and B. Beech. (Forthcoming: 2015). “Chapter 6: Addressing Legal Concerns” from
Inclusionary Housing: Creating and Maintaining Inclusive Communities. Lincoln Institute of Land Policy.
Joint Center for Housing Studies of Harvard University. 2013a. “Rental Housing Assistance.”
America’s Rental Housing—Evolving Markets and Needs.34-40.
Joint Center for Housing Studies of Harvard University. 2013b. “Renter Demographics.” America’s
Rental Housing—Evolving Markets and Needs.15-20.
Katz, L., J. Kling, and J. Liebman. 2000. “Moving to Opportunity in Boston: Family Results of a
Randomized Mobility Experiment.” National Bureau of Economic Research.
Knapp, Gerrit-Jan, Antonio Bento and Scott Lowe. 2008. Housing Market Impacts of Inclusionary
Zoning. College Park, MD: National Center for Smart Growth Research and Education.
Krefetz, S. 2001. “The Impact and Evolution of the Massachusetts Comprehensive Permit and
Zoning Appeals Act.” Western New England Law Review 22(2): 383-430.
Mallach, Alan. 1984. Inclusionary Housing Programs: Policies and Practices. New Brunswick, NJ: Center for
Urban Policy Research, Rutgers University.
Works Cited | Page 64
When and How Should Cities Implement Inclusionary Housing Policies?
Mathur, Shishir, Paul Waddell, and Hilda Blanco. 2004. “The Effect of Impact Fees on the Price of
New Single-Family Housing.” Urban Studies, 41 (7), 1303-1312.
Mayer, Christopher J. and C. Tsuriel Somerville. 2000. “Land Use Regulation and New
Construction” Journal of Urban Economics, 48 (1), 85-109.
Mukhija, Vinit, Lara Regus, Sara Slovin, and Ashok Das. 2010. “Can inclusionary zoning be an
effective and efficient housing policy? Evidence from Los Angeles and Orange Counties.”
Journal of Urban Affairs 32.2, 229-252.
Mulligan, T. and J. Joyce. 2010. Inclusionary zoning: A guide to ordinances and the law. Chapel Hill, NC:
School of Government, The University of Chapel Hill.
Nelson, Arthur C., Jane H. Lillydahl, James E. Frank, and James C. Nicholas. 1992. “Price Effects
of Road and Other Impact Fees on Urban Land.” Transportation Research Record 1305, 36-41.
Oreopoulos, P. 2003. Quarterly Journal of Economics 118, 1533.
Padilla, Laura. 1995. “Reflections on Inclusionay Housing and a Renewed Look at its Viability.”
Hofstra Law Review 23 (3), 539-626.
Pelletiere, D., M. Canizio, M. Hargrave, and S. Crowley. 2008. Housing Assistance for Low Income
Households: States Do Not Fill the Gap. National Low Income Housing Coalition. October.
Powell, Benjamin and Edward Stringham. 2004a. “Housing Supply and Affordability: Do Affordable
Housing Mandates Work?” Los Angeles: Reason Public Policy Institute, Policy Study No. 318.
Powell, Benjamin and Edward Stringham. 2004b. “Do Affordable Housing Mandates Work?
Evidence from Los Angeles County and Orange County.” Los Angeles: Reason Public Policy
Institute, Policy Study No. 318.
Powell, Benjamin and Edward Stringham. 2005. “The Economics of Inclusionary Zoning
Reclaimed: How Effective Are Price Controls?” Florida State University Law Review 33 (2).
Read, Dustin. 2009. “The Structure and Potential Economic Effects of Inclusionary Zoning
Ordinances.” Real Estate Issues 34 (2), 1-9.
Rosen, David. 2004. “Inclusionary Housing and its Impacts on Housing and Land Markets.” 2004.
Inclusionary Zoning: The California Experience. National Housing Conference 3 (1).
Sanbonmatsu, L. et al. 2011. Moving to Opportunity for Fair Housing Demonstration Program: Final Impacts
Evaluation, Washington, DC: U.S. Department of Housing and Urban Development, Office of
Policy Development and Research.
Schuetz, Jenny, Rachel Metzler, and Vicki Been. 2009. “Silver Bullet or Trojan Horse? The Effects
of Inclusionary Zoning on Local Housing Markets.” Urban Studies.
Works Cited | Page 65
When and How Should Cities Implement Inclusionary Housing Policies?
Singell, Larry D. and Jane H. Lillydahl. 1990. “An Empirical Examination of the Effect of Impact
Fees on the Housing Market.” Land Economics 66 (1), 82-92.
Skaburskis, Andrejs and Mohammad Qadeer. 1992. “An Empirical Estimation of the Price Effects
of Development Impact Fees.” Urban Studies 5, 653-667.
Skidmore, Mark and Michael Peddle. 1998. “Do Development Impact Fees Reduce the Rate of
Residential Development?” Growth and Change 29 (3), 383-400.
Snyder, Thomas P., Michael A. Stegman, and David H. Moreau. 1986. Paying for Growth: Using
Development Fees to Finance Infrastructure. Washington, D.C.: Urban Land Institute.
Turner, M. and G.T. Kingsley. 2008. Federal Programs for Addressing Low-Income Housing Needs: A Policy
Primer. Washington, D.C.: The Urban Institute. December.
Works Cited | Page 66