This paper was presented at the conference "Policies to Promote Affordable Housing," cosponsored by the Federal Reserve Bank of New York and New York University's Furman Center for Real Estate and Urban Policy, February 7, 2002. It was part of Session 2: Affordable Housing and the Housing Market, and is a commentary on "Government regulation and changes in the affordable housing stock" by C. Tsuriel Somerville and Christopher J. Mayer.Housing - Finance ; Rent control ; Local government ; Rent ; Construction industry ; Metropolitan areas - Statistics

Jack Goodman

English

Research Papers in Economics

FRBNY Economic Policy Review / June 2003 63
ousing affordability is a wide-ranging topic, and the
 conference organizers have wisely chosen to organize the 
program sessions around different themes. The theme of this 
session is housing markets, but it is really about housing 
markets as they are affected by local regulation. It is an 
appropriate and important focus.
I will do two things in these comments. First, I offer some 
thoughts on the paper by Tsuriel Somerville and Christopher 
Mayer, by way of the mandatory critique, and then go on to 
discuss some broader issues related to the topic of their paper.
The authors use a sample of rental housing units from 
thirty-eight metropolitan areas in the 1980s and 1990s to 
examine the effects of regulation on housing affordability. They 
find that regulation and other constraints on new construction 
put upward pressure on rents in the existing housing stock and 
cause units to filter up and out of the affordable stock. This is 
not a surprise. Their finding on rent control is a surprise, 
however, in that they estimate that uncontrolled units are less 
likely to leave the affordable stock in areas where rent control is 
more prevalent. This finding is at odds with previous findings 
and common sense, and as the authors indicate, they think it is 
due to the characteristics of these units.
There is a lot to like about this paper. First is its focus on 
regulation as an influence on housing affordability. There are 
two other ways by which governments influence housing 
affordability: demand subsidies to give people money or tax 
breaks to help them buy or rent housing, and supply subsidies 
to reduce the cost of building or renovating housing. We know 
a fair amount about these two forms of government action to 
promote affordability. One thing we know is that they cost a lot 
of money. Regulation is different in that it involves neither cash 
outlays nor credit guarantees from governments.
But, with the exception of rent control, we do not know 
much about regulation’s effects on housing affordability in the 
existing housing stock. There are many opinions and 
anecdotes, but little hard evidence, in part because it is difficult 
to quantify regulation. It is a tough topic to tackle empirically, 
and the authors are to be commended for taking it on.
Another attraction of this research is that it offers a new 
approach: following individual housing units over time and 
relating their performance to their characteristics and to the 
local market and regulatory structure around them. The 
research looks at multiple possible outcomes for affordable 
units—another innovation. And the authors explain how it fits 
into the literature. The paper is a logical extension of previous 
work by Somerville and Mayer and their coauthors.
Lastly, the data source is potentially quite powerful. The 
same questions are asked of statistically valid samples in a large 
number of metro areas. The data provide the opportunity to go 
way beyond case studies and anecdotes, which are useful but 
are hard to generalize with confidence.
Jack Goodman
The views expressed are those of the author and do not necessarily reflect the 
position of the Federal Reserve Bank of New York or the Federal Reserve 
System.
Commentary
Jack Goodman is president of Hartrey Advisors.
H64 Commentary
These are all strengths of the research. Yet the authors face a 
number of research challenges with this work as well. 
One challenge to all researchers on housing affordability is 
to define what affordable housing is. The Somerville and Mayer 
study adopts a fairly conventional standard in terms of 
household income and how much of it can be allocated to 
housing. But affordability is an inherently subjective notion on 
which reasonable people can and do disagree. Yet even if 
people disagree on what affordable housing is, they may be able 
to agree on whether housing is getting more or less affordable 
over time. For this reason, counting units that cross a threshold 
(which is the approach in this study) can be less controversial 
than selecting the threshold itself. Picking another threshold 
would likely have produced qualitatively similar results. 
Note that the authors only look at rental housing. This does 
not mean that owner-occupied housing presents no 
affordability issues, but renters have lower incomes on average 
than owners, and therefore appropriately receive special 
attention in policy discussions. In addition, measurements of 
housing costs, market dynamics, and government programs all 
differ between rental and owner-occupied housing. For all 
these reasons, it is sensible to study rental housing on its own.
A second challenge is to quantify regulation. It is very tough 
to boil regulation down to a ten-point scale or anything similar. 
Much of regulation’s effect on housing affordability comes down 
to land-use controls, and the authors rightly focus on this effect. 
Another challenge is to use the American Housing Survey 
(AHS) data fully, but to avoid pushing the data beyond their 
limits. I have used the AHS data a lot, and I know that these 
data are not easy to link longitudinally or to aggregate across 
the different metro surveys. Much behind-the-scenes work was 
needed to get the data to where the authors have them, and 
Somerville and Mayer should be credited for that work.
But I am concerned that the resulting data set is a bit of a 
grab bag. It mixes time periods, jurisdictional differences 
within metropolitan areas, and different sampling fractions 
across metro areas. And the timing of the growth management 
survey does not necessarily match the timing of the housing 
unit observations to which it is linked. 
Without getting into the econometrics, let me just say that 
these characteristics of the sample put pressure on the model to 
include all the relevant variables so that influences ascribed to 
one variable are not really reflecting the influence of a variable 
left out of the model. Some of these data issues, as well as simple 
misreporting of rent control and subsidy status in the AHS, 
may help explain the counterintuitive rent control results. The 
interpretation given by the authors is not inconsistent with the 
data, but it seems just a little too easy and convenient. 
Separate from these data issues is the paper’s approach of 
using long-run differences across areas to explain short-run 
dynamics. In particular, land-use regulations are used to 
explain movement of units across the affordability threshold. It 
seems more appropriate to look at the regulations’ effects on 
the proportion of units above and below the threshold. The 
model’s specification calls for caution in drawing conclusions. 
For example, one cannot project from these results that, if 
regulations were changed, a jurisdiction would experience 
within that same three- or four-year period the changes in 
filtering estimated by the model. 
A last comment specifically about the paper regards the 
summary statement that regulation is less important than unit 
or neighborhood characteristics in determining filtering. I take 
exception to this as a portable conclusion that can be applied 
elsewhere. It is very specific to the variables used in this 
analysis, their calibration, and the model specification. This 
will always be the case, so it is unlikely that any general 
statement about the relative importance of regulation, housing 
unit, and neighborhood characteristics in the filtering process 
is a meaningful statement.
The paper is about housing filtering. Let me offer a 
framework and set of charts that I think capture the authors’ 
approach and will help me to illustrate some more general 
points: Every housing unit in a local market can be defined in 
terms of a quality index and a price index. The quality index (q)  
is a single-dimensional summary of all the size, amenity, and 
locational attributes that are valued in housing. The price index 
(p) measures the price per unit of housing quality paid for that 
house or apartment. This price index will vary from house to 
house and from apartment to apartment even within a local 
housing market due to segmentation of the market and various 
market “imperfections.” Speaking loosely, this price index can 
be viewed as a profitability index from the supplier’s 
perspective and as an (inverse) “good deal” index from the  
consumer’s perspective. Chart 1 offers an illustration, where 
each dot represents a house or apartment. Apartments A and B 
provide the same quality housing, but Apartment A is more 
expensive. Similarly, Apartments B and C have the same price 
per unit of quality, but unit B is of higher quality.
To be in the housing stock, units must meet two criteria: 
a minimum quality standard, set by government through code 
enforcement, zoning, and occupancy standards; and a price 
(loosely a proxy for profitability) threshold, set by the market. In 
Chart 1, these two minimums are indicated by the hash marks.
When people think about affordable housing, many think 
about modest but decent housing that is not too expensive and 
fits within a family’s budget. A household’s expenditure on 
housing is the product of how much housing they consume (q) FRBNY Economic Policy Review / June 2003 65
Chart 1
The Affordable Housing Triangle
Housing quality
Rent per unit of housing quality (price index)
Apartment C Apartment B
Apartment A
Chart 2
Gentrification
Housing quality
Rent per unit of housing quality (price index)
and the price per unit of quality (p) that they pay. A fixed budget 
for housing is consistent with various combinations of q and p. 
All households hope, of course, to get a good deal on housing so 
that their housing expenditure gives them a lot of q at a low p.
The triangle in Chart 1 defines the housing units with 
combinations of p and q that meet all three requirements for 
affordable housing: minimum standards, minimum 
profitability, and within a moderate-income household’s 
budget constraint. The downward slope to the hypotenuse 
indicates that households that get a better deal (lower p) on 
their housing can consume more housing (higher q) without 
exceeding their housing budget. Drawn here for simplicity as a 
straight line, the combinations of p and q consistent with a 
fixed budget actually trace out a line that bows inward (concave 
to the origin).
Filtering in its simple form is represented by horizontal 
movement over time of individual housing units in the chart. 
Units increase or decrease in housing quality, but with no 
change in the “profitability” of the units. Vertical movement, in 
contrast, indicates a change in housing price or profitability, 
but with no change in physical characteristics. 
Gentrification, shown in Chart 2, can be represented by a 
unit filtering up in quality level, with a profit incentive driving 
the upgrading, indicated here by the upward tilt to the line.
Housing can also be lost from the affordable stock if its 
profitability turns negative due to insufficient demand relative 
to available supply. This phenomenon is depicted in Chart 3 by 
the price index falling below the threshold level for the site and 
structure to avoid abandonment or redevelopment into 
nonresidential use. Redevelopment can occur on any residential 
site providing any level of housing quality, but it typically occurs 
where the existing structures are reaching the end of their 
economic life and often are in the affordable triangle.
Lastly, housing can be lost to the affordable stock through 
government action. Local governments establish and enforce 
the zoning ordinances, building codes, and occupancy 
standards that set the minimum quality level of housing in a 
neighborhood. If units fall below that threshold, as shown in 
Chart 4, they are subject to removal from the stock, regardless 
of their profitability.
In this paper and in a previous one, Somerville and Mayer 
show that neighborhood influences are especially important in 
determining whether housing filters up and out of the 
affordable stock. They find that, all else equal, units are more 
likely to filter up if they are surrounded by higher value 
housing. In other words, it is hard to maintain housing 
heterogeneity in neighborhoods with strong housing demand. 
Let me say a few things about neighborhood heterogeneity. 
It is a value judgment, to be sure, but many people want 
diversity in their local populations and housing. Despite 
“NIMBYism,” many communities promote diversity, if not 
within blocks, then diversity within neighborhoods, or at least 
within local jurisdictions. 66 Commentary
Chart 3
Lost through Insufficient Demand
Housing quality
Rent per unit of housing quality (price index)
Chart 4
Lost through Government Regulation
Housing quality
Rent per unit of housing quality (price index)
Neighborhood is important to housing affordability 
because mixed, diverse neighborhoods are where a lot of the 
affordable stock is found. But neighborhood diversity tends to 
be transitional, a nonequilibrium condition. Some diverse 
neighborhoods are on their way up, growing in demand and 
being redeveloped into newer, higher density places. Other 
mixed neighborhoods are on their way down, characterized by 
outmigration by those who can leave and by housing 
abandonment. Affordable housing is lost in both instances.
The challenges of maintaining a housing mix in 
neighborhoods and communities growing in popularity are 
different from those that are declining. If citizens should charge 
their government with maintaining a housing mix, what can 
government do to achieve that objective?
Here, I am talking about local governments. Each of the 
three levels of government has a distinct role, I would argue, in 
promoting housing affordability. First, the federal government 
is the program designer and financier for most of the country’s 
largest demand- and supply-side affordability initiatives. 
Second, state governments are the gatekeepers that provide 
legislative authority to local jurisdictions and allocate funds 
from some federal and state revenues. Third, local 
governments are the enablers/implementers that run or 
oversee programs and control development and property 
operations through zoning and building codes. 
Local governments have a lot of sticks and carrots that can 
be brought to bear on maintaining housing diversity. But these 
tools work better in growing areas than in declining ones. In 
declining neighborhoods, government intervention is a bit like 
pushing on a string. Regulation usually means keeping people 
from doing something, and you cannot keep people from 
moving out of a neighborhood.
In growing areas, depending on state laws, local govern-
ments may be able to mandate that development be of a certain 
type and include affordable housing. In other jurisdictions, a 
“carrot” approach of offering density bonuses or other 
regulatory incentives for inclusion of on-site affordable 
housing may be more appropriate. The bonus density 
approach will not always result in diversity in housing types, 
but it can retain diversity in neighborhood incomes. 
There is another, potentially powerful but much more 
controversial, tool that local governments have at their disposal 
for promoting housing affordability: housing-quality 
standards can be relaxed. The housing affordability problem in 
large part is an income problem. People do not have enough 
money to pay rent for the housing that is available. And that 
housing is constrained not only by the cost of building and 
maintaining it, but also by restrictions placed by government 
on the types of housing that can be offered in the community. 
These government restrictions force some residents to consume 
more housing than they would choose to, given their resources.
“Reduce housing-quality standards,” is a phrase certain to 
raise blood pressures among some in the local electorate. But 
closely related policy prescriptions include “eliminate 
exclusionary zoning” and “remove barriers to affordable 
housing.” The latter, by the way, is very close to the name of the 
presidentially mandated Advisory Commission on Regulatory 
Barriers to Affordable Housing, which issued its report in 1991. FRBNY Economic Policy Review / June 2003 67
Chart 5
Effect of Government Easing of Quality Constraint
Housing quality
Rent per unit of housing quality (price index)
A policy focus on housing-quality standards is not a new or 
radical idea, but one that may need reinforcing.
Housing standards typically are set at levels way above those 
required to ensure safety and sanitation. Zoning and building 
code restrictions on lot sizes and required interior space per 
housing unit are good examples of regulations that can force 
overconsumption or exclusion. Easing standards can have 
significant effects on the availability of affordable housing. 
Within the triangle framework, this potential is illustrated in 
Chart 5. 
In conclusion, any way you look at it, local governments, 
through their regulations, directly and indirectly affect the 
affordable housing stock and changes to it. The paper by 
Somerville and Mayer and others similar to it shed light on this 
local government role and help to calibrate it, and by doing so 
provide a valuable resource to the policy debate.
The views expressed are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York 
or the Federal Reserve System. The Federal Reserve Bank of New York provides no warranty, express or implied, as to the 
accuracy, timeliness, completeness, merchantability, or fitness for any particular purpose of any information contained in 
documents produced and provided by the Federal Reserve Bank of New York in any form or manner whatsoever.

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