DISCUSSION PAPER
..Report No. UDD-102
RENT CONTROL IN DEVELOPING COUNTRIES:
A FRAMEWORK FOR ANALYSIS
by
Stephen Malpezzi
and
C. Peter Rydell
September 1986
Water Supply and Urban Development Department
Operations Policy Staff
The World Bank
A
The views presented herein are those of the author(s), and they should. not be
interpreted as reflecting those of the World Bank or of the Rand Corporation.



Stephen Malpezzi is an economist in the Water Supply and Urban
Development Department of the World Bank, and director of a Bank research
project on "Rent Controls in Develo?ing Countries" (RPO 674-01). He has
recently completed a study of tK& costs and benefits of rent control in
Cairo, Egypt, under a Bank research project on "Housitg Demand and Finance
in Developing Countries" (RPO 672-46). C. Peter Rydell, a consultant to
the Water Supply and Urban Development Department, is a Senior Social
Scientist at the Rand Corporation. He has participated in a study of rent
control in New York City, and directed a recent study of Los Angeles' rent
control.
This paper is an edited version of a proposal for the new rent
control research project. Because it is a proposal, there are specific
recommendations about timing, technique, and choice of case studies which
will be revised as the project is executed. The basic framework for
analysis will remain unaffected. Opinions expressed herein are solely
those of the authors, and should not be interpreted as those of any
organization. The authors have benefited from comments by too many
colleagues to list in full, but especially Stephen Mayo and Michael
Murray.
A companion paper gives more details on the design of the case
studies:
Stephen Malpezzi and Stephen K. Mayo, Measuring the Costs and
Benefits of Rent Control: Case Study Design (Forthcoming as a
Water Supply and Urban Development Department Discussion Paper).



ABSTRACT
Economists commonly model rent control as a simple effective
price control or tariff. However, remarkably little empirical research
has been done on the magn-itudes involved.  Even less has been done on the
analysis of real world rent control regimes, which often diverge from the
simple textbook model. Little policy advice is available from the simple
price control model other than that immediate blanket decontrol will
restore equilibrium after some unknown lag.
Preliminary research under RPO 672-46, "Housing Demand and
Finance in Developing Countries", has demonstrated (1) that simple
analysis of rent control as an effective tariff does not predict the
consequences of all laws in all market conditions, and hence is not
sufficient as a guide to policy, and (2) alternative methods of decontrol
exist, and vary in-their effects depending on type of law, enforcement,
market condition!;, and how lrndlords and tenants adjusted to the prior
rent control regime.
A new research project is therefore now underway to study "Rent
Controls in Developing Countries" (RPO 674-01). Generally, the purpose of
this research is to extend that work and increase understanding of one of
the most widespread and potentially potent housing market policies extant.
Specifically, the proposed research project will have the following
objectives:
(1) Survey rent control laws across countries, with special
emphasis on developing countries.
(2) Produce several case studies of particular controlled
markets.
(3) Integrate the results from the case studies in an
internally consistent model of market behavior.
This project will lead to recommendations regarding alternative
methods of decontrol for different rent control regimes, under different
market conditions.



TABLE OF CONTENTS
INTRODUCTION AND SUMMARY.     ..................... 1
I.   OBJECTIVES AND STRATEGY         ............................. 5
Introduction        ...................................5
General Framework and Research Strategy Overview......... 7
General Consequences of Rent Control................. Q9
Rent Reduction........................... .........      . 1O
Housing Deterioration....     *be*................11
Rental Housing Losses: Demolitions,
Cornversions, and Foregone Starts ............... ...12
Decomposing Changes in Rent into Price and
Quantity Changes...... e...o      ...................12
Present Value of Tenant and Landlord Gains
and Losses................ ...e     ............. 13
Effects of Rent Control on Household Location,
Mobility, and Tenure Choice.....................14
Effects of Rent Control on Property Taxes ............ 14
Alternative Adjustment Mechanisms.................... 15
Indexing:   Keeping Real Rents Constant.......... 15
Reassessment for New Tenants ...................16
Differential Pricing of New and
Existing Units       ......       ............ 16
Differential Pricing for Upgraded Units......... 16
Side Payments.............................. .17
Policy Issues................o.oeeg...........19
II.  PREVIOUS RESEARCH ON RENT CONTROL e.     gooe.oooooo.  eobe.o....g....21
Analysis of Rent Control Viewed as a Tax on
Housing Capital ..........................................21
Dynamic Models of the Effect of Rent Controls on
Maintenance, g...e.e..ge..e.e.e..e..............e.........24
Estimates of Costs and Benefits, and their Incidence......25
Rent Control and MobiLity......................... e.....27
Studies which Analyze Alternative Adjustment
Mechanisms and Methods of Decontrol0....................28
The Relationship between Controlled and
Uncontrolled Market.............................             32ee  * e32
Summary of Rent Control Research Under RPO 672-46.........32
The Need for Additional Research .........................34



III. RESEARCH DESIGNC..0000000000000o.000000000000000.0000o0000000      0.37
Overview   ........0 ... 090 0000....0 ....000 ....0.0 0 00o... 0 37
Task 1:   Survey of Rent Control. Laws as Written
and as Enforced.............. 0o00    000.0000.000 37
Key Features of Rent Control Laws...............37
Rent Control and Property Taxes..0000.0       ......00040
Survey Execution. ....0..      00.....        0 ..............0..40
Task 2:   Case Studies of Selected Markets............41
Case Study Design0 ...........                 0 00o0.....41
Choice of Case Study Markets ..................42
Data Collection. .0...0..0.....0000..000.00..0.....45
Outputs  000000  00o .000 .00o ..0 o000 .......00000  0. . o0 0 46
Task 3: Integrating Case Study Results in A
Consistent Housing Market Model............ 46
Introduction..0000.0.000 000o .000...0...00000000.0046
Modeling Strategy. ....00o.....0.000000000.0  0 0o00.48
Overview of the Model. .e.0......o...............48
Task 4:   Dissemination of Research Results...........55
IV. ORGANIZATION      00000000000000000000000000000. o 000 o...........9
General Principles. 0..0oo..0..0.0.000..0o.0..00a.....0....    59
Links to Other Bank-Funded Research ..........*......60
The Work Program, and Proposed Timing..o .000....0....60
ANNEX: DRAFT RENT CONTROL CHECKLISTo ...........O.........     . O Q...o....63
REFERENCES           o...oooo.o....oooo..ooooo..o....oo......o.......71



LIST OF TABLES
Page
1.   Key Questions about Rent Control and How to
Answer Them ............ . ................ ..... .8
2.   Welfare Measures and Their Components:
Cairo Renters .............. ..............         la
3.   Comparison of Rent Control Laws for
Several Markets ..................   ...........39
4.   List of Case Study Markets .......................... 43
5.   Interaction Between Market Conditions and Rent
Control, (Phase One) Case Study Market......... 44
6.   Key Model Inputs from Case Studies.................. 56
7.   Project Outputs............................... ..... 57.
8.   Work Schedule   ....................................61



LIST OF FIGURES
Page
1.   Rent Control as an Effective Price Control .......... 23
2.   Rent Control as Expenditure Control ..........ee .... *23
3.   Effects of Alternative Rent Control Laws,
From Rydell et al .* . . . e   o e o.o. oo..... . . ... 31
40   Overall Structure of the Model ............ o .......a 50
5.   Effect orL Housing Services ...............            51
6.   Effect on Landlord Profits ........ a  ................. 52
7.   Effect on Government Objectives... ................. 53
8.   Effect on Tenant Benefits...........................54



INTRODUCTION AND SUMMARY
Government policies regarding housing and housing finance
obviously have extensive impacts on the availability of affordable shelter
in developing countries, but they also affect the efficiency and equity of
resource use and public expenditures generally, because shelter is such a
large sector of the economy. Housing investment ranges ftom two to eight
percent of GNP in developing countries; it can be a third of total
investment; and the relative importance of the sector increases
systematically as countries develop. Among the housing policies that have
the most substantial impacts and are the most widespread are regulations
that control the rents that landlords can charge.
Rent control is often treated as the most important single
shelter policy issue by project officers and Bank managemernt. Rent
control has been a key negotiating point in several Bank urban projects
(in India, Portugal, and Tunisia for example), and promises to resurface
in future projects, especially as the Bank pursues sector based lending
strategies. Despite the importance of the issue, little work has been
done to examin:e actual rent control laws, their effects, and alternative
methods of decontrol. In 1952 Leo Grebler could write:
It is perfectly astounding to find that the quantity and quality of
analytical materials oGX rent control are wholly incommensurate with
the social and economic importance of the problem.
Over 30 years later, Joseph Gyourko and Peter Linneman found the situation
little improved:
Considering the large number of cities that have investigated or
adopted rent controls, there is little empirical research documenting
the effects of rent controls.
They go on to point out that the few studies which have been done are
studies of New York, Los Angeles, and a handful of other developed country
cities. Almost no work has been done on rent control in developing
countries.
The simple analysis of rent control as an effective price
control or a tariff has a straightforward conclusion. This model suggests
that rent control reduces the quantity and quality of housing Available,
and has other undesirable consequences as well. For practical policy
applications, however, more specific information is needed -- about the
magnitudes of the costs and benefits of alternative policies, their
distribution, and about various methods of decontrol. On these points,
little is known yet. Past research has demonstrated that the simple
textbook model of rent control as an effective tariff does not predict the
consequences of particular rent control regimes adequately enough for
policy use; and past studies offer little guidance at all on decontrol
options, the appropriate phasing of decontrol measures, and their likely
consequences. Examples of the kinds of questions which need to be
answered for policy work include the following:



-2-
How extensive are rent controls in developing countries? What are
the major types of controls? What are the stated policy
objectives? How are rent controls enforced in various places?
What are the magnitudes of the effects of rent controls in developing
countries? Are the effects of different rent control regimes
qualitatively and quantitatively similar? How do these magnitudes
compare to other distortions, e.go, lack of housing finance, poorly
functioning land markets, etc.? How do landlords and tenants adjust
to the presence of such controls? Who benefits and who loses from
rent controls; what are the distributional effects?
How can rent control be modified to have more appropriate
distributional impacts while producing fewer economically inefficient
market distortions? When should rent controls be abolished or
retained? What alternative policies exist to achieve comparable
goals; what practical problems in implementing alternative policies
and exist?
This research will contribute toward filling these important
gaps in current knowledge about an area of housing policy that potentially
has significant implications for the pace of development. Specifically,
the proposed research project will have the following objectives:
(1) Survey rent control laws across countries, with special emphasis
on developing countries. The survey will focus on such details as
which units are controlled, how controlled units are appraised, how
rents are adjusted over time, and what related laws exist (e.g.
occupancy laws, land price controls, etc.). The survey will
distinguish between laws as written and as enforced.
(2) Produce several case studies of particular controlled markets.
The case studies will provide empirical results which will shed light
on the e£fects of different rent control regimes on the supply of
housing, and costs and benefits to tenants. Reports prepared for two
markets (Cairo, Egypt and Bangalore, India) under RPO 672-46, Housing
Demand and Finance in Developing Countries, will be used; since that
research has highlighted the diversity of rent control regimes,
additional case studies will be prepared.
(3) Integrate the results from the case studies in an internally
consistent model of market behavior. Internally consistent means
that the costs and benefits of rent control to different agents
(landlords, tenants, governments) from different sources (changes in
prices, changes in consumption, changes in mobility) are all
included. Such a framework is needed to correctly analyze the
cost/benefit and distributional implications of rent control0 It
will be used to study alternative methods of decontrol for different
stylized rent control regimes, under different market conditions.



- 3 -
General Framework and Research Strategy
The research project can be conveniently divided into three
analytical tasks which approximately correspond to each of the objectives
just enumerated. Conceptually, there is a natural ordering of the
tasks. The first task is to survey rent control regimes in many markets,
in order to learn more about the scope and details of rent control laws as
enforced. Little is known about the extent of rent control generally, and
even less about the prevalence of specific provisions of rent control
laws, how they are enforced, and what market conditions are like in
controlled markets. The first task is designed to fill this gap.
The second task is to produce case studies of markets which
represent a w'de range of actual rent control regimes. Few econometric
studies have been done of the costs and benefits of rent control laws, and
only two in developing countries. Even less has been done on estimating
supply side impacts, and the effects of rent control on public finance,
household mobility, tenure choice, and the labor market. The second task
aims to expand the available knowledge dramatically.
The third task is to integrate the costs and benefits to all
agents (landlords, tenants, owner-occupants, governments), and consider
the likely dynamic effects of changes in rent control. Research done to
date has not integrated estimates of gains and losses from different
impacts, or considered the interests of all agents in a consistent (i.e.,
accounting) framework. Also, the dynamics of rent control have been
neglected. The case study results will be integrated in a simple but
consistent model of market behaviour, which will be used to study costs
and benefits of alternative methods of decontirol. This effort will draw
on the first two tasks so that the essential features of rent control
regimes as desigred and enforced will be captured.
In practice, of course, all three tasks are interrelated. For
example, the design of the case studies (Task 2) requires knowledge of the
inputs required by the cost/benefit model (Task 3), to ensure that data
collection is complete and efficient. The choice of case studies and
stylized situations to study in Tasks 2 and 3 will be influenced by the
broad survey of housing markets undertaken in Task 1. However, the case
studies require the bulk of the project's resources.
Table 7 in the text, below, presents a proposed list of project
outputs. Each of the three analytical tasks (survey, case studies, and
integrated model) will produce written outputs which will stand on their
own. In addition, a synthesis paper will be written which describes the
results of the research in nontechnical terms, and which will present the
key results in a manner accessible to project officers in the Bank and our
client governments. The project final report will be an edited
compilation of results from all three tasks, including the synthesis. The
synthesis paper will also be used as background reading for a workshop on
the results for Bank staff. The workshop will mark the beginning of an
additional effort, to widely solicit the views of Bank staff and
management, in light of the research findings, on what the Bank's and our
client's position and strategy on rent control should be, Assisting our
clients in developing practical strategies for effecting needed changes in
the regulation of rental housing is the ultimate goal of this project.



-4-
The project will be undertaken in two phases. Phase One will
consist of the broad survey of laws and market conditions, and five case
studies. Phase Two will consist of additional case studies, if needed;
the integrated model, which will be used to study alternative methods of
decontrol; and synthesis of results.



-5-
I. OBJECTIVES AND STRATEGY
Ittroduction
The theoretical analysis of rent control rests on some
principles which are quite elementary, indeed
distressingly so. They are so obvious that one-would
feel the greatest reluctance to repeat them in a
professional journal were it not that a great public
policy has been erect7d upon either ignorance or a
repudiation of them.-
Economists as a group have no trouble reaching a consensus on the
qualitative effects of rent control on housing markets. A recent study
revealed that only two percent of economists surveyed disagreed with the
proposition that "a ceiling on rents reduces the quantity and quality of
housing available" (Kearl et al. 1979). This consensus rests on the
analysis of rent control as a simple effective price control or tariff.
However, remarkably little empirical research has been done on the
magnitudes involved. Even less has been done on the analysis of real
world rent control regimes, which often diverge from the simple textbook
model. Little policy advice is available from the simple price control
model other than that immediate blanket decontrol will restore equilibrium
after some unknown lag.
Preliminary research under RPO 672-46, Housing Demand and
Finance in Developing Countries, has demonstrated (1) that simple analysis
of rent control as an effective tariff does not predict the consequences
of all laws in all market conditions, and hence is not sufficient as a
guide to policy, and (2) alternative methods of decontrol exist, and vary
in their effects depending on type of law, enforcement, market condition I
and how landlords and tenants adjusted to the prior rent control regime.-
Generally, the purpose of this proposed research is to extend
that work and increase understanding of one of the most widespread and
potentially potent housing market policies extant, namely rent controls.
Specifically, the proposed research project will have the following
objectives:
(1) Survey rent control laws across countries, with special emphasis
on developing countries. The survey will focus on such details as
which units are controlled, how controlled units are appraised, how
rents are adjusted over time, and what related laws exist (e.g.
occupancy laws, land price controls, etc.). The survey will
distinguish between laws as written and as enforced.
1/   Grampp (1950), cited in Block and Olsen (1981).
2/   Malpezzi (1986 a, b).   This work under RPO 672-46 is discussed   in
more detail in the literature review (Chapter 2). Other links to the
Housing Demand and Finance project are explained in Chapter 4.



- 6 -
(2) Produce several case studies of particular controlled markets.
The case studies will provide empirical results which will shed light
on the effects of different rent control regimes on the supply of
housing, and costs and benefits to tenants. Reports prepared for two
markets (Cairo, Egypt and Bangalore, India) under -RPO 672-46,
"Housing Demand and Finance in Developing Countries", will be used;
since that research has highlighted the diversity of rent control
regimes, additional case studies will be prepared.
(3) Integrate the results from the case studies in an internally
consistent model of market behavior. Internally consistent means
that the costs and benefits of rent control to different agents
(landlords, tenants, governments) from different sources (changes in
prices, 6hanges in consumption, changes in mobility) are all
included. Such a framework is needed to correctly analyze the
cost/benefit and distributional implications of rent control. It
will be used to study alternative methods of decontrol for different
stylized rent control regimes, under different market conditions.
A recent U.N. study estimates that about 42 percent of the
world's urban dwellers are renters. It is not yet known how many of those
roughly 150 million households lived under rent control regimes, but
preliminary research suggests the proportion is probably quite high; 30
percent is a conservative guess. The motivation for a research project on
rent control is therefore clear and needs little elaboration. Rent
control is very often treated as the most important single shelter policy
issue by project officers and Bank management. Rent control has been a
key negotiating point in several Bank urban projects (in India, Portugal,
and Tunisia for example), and promises to resurface in future projects,
especially as the Bank pursues sector based lending strategies. Despite
the importance of the issue, little work has been done to examine actual
rent control laws, their effects, and alternative methods of decontrol.
The Bank's current policy advice is not well informed by the simple
textbook models of rent control as a simple tariff; these models only
predict the consequences of rent control for very specific rent control
regimes and certain market conditions, and lead to little useful policy
advice beyond "remove all controls immediately."
In some situations the use of such oversimple models can be
counterproductive. The policy dialogue is better served if Bank policy
advice is based on models which can be shown to predict the actual
consequences of the regime in question. In some situations the textbook
model predicts quite well, but in other cases it does not. For example,
previous research on Cairo demonstrates that high vacancy rates and high
rates of new construction can be found in a market which is (in a very
particular sense) tightly controlled. Also, alternative methods of
decontrol do exist, and vary in their effects depending on market
conditions and the ways in which landlords and tenants adjusted to the
previous rent control regime. Examples of the kind of questions which
need to be answered for policy work include the following:
How extensive are rent controls in developing countries? What are
the major types of controls? What are the stated policy
objectives? How are rent controls enforced in various places?



-7-
What are the magnitudes of the effects of rent controls in developing
countries? Are the effects of different rent control regimes
qualitatively and quantitatively similar? How do these magnitudes
compare to other distortions, e.g., lack of housing finance, poorly
functioning land markets, etc.? How do landlords -and tenants adjust
to the presence of such controls? Who benefits and who loses from
rent controls; what are the distributional effects?
How can rent control be modified to have more appropriate
distributional impacts while producing fewer economically inefficient
market distortions? When shotuld rent controls be abolished or
retained? What alternative policies exist to achieve comparable
goals; what practical problems in implementing alternative policies
and progiams exist?
The proposed project will greatly increase understanding of the
scope and effects of different types of rent control regimes, and of the
effects of changes in those regimes.
The proposed research project is therefore consistent with the
new research program objectives and yriorities as enunciated in the Report
on the World Rank Research Program.-    That report emphasized the need for
"imore studies of factual behavior patterns of individual agents and
institutions," and for more '"multicountry comparative studies of important
policy related issues." Emphasizing the need for research that both
supports Bank operations and keeps the Bank "in the forefront of thinking
on the economics of developing countries," the report listed five broad
research priorities (Part I, pp. 13-14). This project is most clearly
related to the first two: (1) estimating the costs and benefits of
government intervention, and (2) studying the interrelationships between
institutions and incentives.
This project supports Bank operations, because rent control has
become an important issue in the urban policy dialogue. For this reason,
the Water Supply and Urban Development Department is planning to prepare a
strategy paper on rent control in developing countries. This paper
requires more specific information on the effects of different rent
control regimes under different market conditions than currently exists.
The research project is designed to provide that information.
General Framework and Research Strategy Overview
The research project can be conveniently divided into three
analytical tasks which approximately correspond to each of the objectives
just enumerated. Table 1 illustrates some of the important questions to
be answered by each task. Conceptually, there is a natural ordering of
the tasks. First, survey rent control regimes in many markets, in order
to learn more about the scope and details of rent control laws as
3/   World Bank (1984), Part I, pp. 12-17, and Part II, p. 1 and pp. 12-
20.



-8
Table 1
Key Questions about Rent Control and How to Answer Them
Task 1:  Survey     Task 2:   Case      Task 3:  Integrated
Rent Control Laws     Studies of the       Accounting Model
and Enforcement   Costs and Benefits   of Costs and Benefits
Practices in       of Rent Control      to All Agents From
Many Markets                               All Sources
How widespread is rent        **                    *
control? What are the
major types of controls,
and how are they enforced?
What related regulations
exist?
What are the costs and
benefits of rent control?
What are the. effects on
housing prices and
consumption, mobility,
landlord profits and
investment? Distribu-
tional implications?
How do landlords and          *                      *                    *
tenants adjust to rent
controls, e.g., key
money, other side
payments, changes
in maintenance and
upgrading?
What are the indirect
impacts of rent control
on e.ga  labor markets,
tax revenue, tenure
choice?
What is the net effect
of rent control on each
agent (landlord, tenant,
owner-occupants,
government)?
What are the dynamic                                                      **
responses of markets, and
their implications for
alternative methods of control?
**: Primary means of answering these questions.
*: Will also provide information on these topics.



-9-
enforced. Second, produce case studies of markets which represent a wide
range of actual rent control regimes. Third, integrate the case study
results in a simple but consistent model of market behaviour, and use it
to study the costs and benefits "f alternative methods of decontrol.    This
effort will draw on the first two tasks so that the essential features of
rent control regimes as designed and enforced will be captured. In
practice, of course, all three tasks are interrelated. For example, the
design of the case studies (Task 2) requires knowledge of the inputs
required by the cost/benefit model (Task 3), to ensure that data
collection is complete and efficient. The choice of case studies and
stylized situations to study in Tasks 2 and 3 will be influenced by the
broad survey of housing markets undertaken in Task 1. Also, note that the
three tasks do not require equal resources; about two thirds of the
project's resources will be used for the case studies.
While the execution of the three analytical tasks is less neat
in practice because of these interrelationships, outputs from each of the
tasks will be designed to stand on their own. In particular, the case
studies will be tailored to local conditions and data availability, while
at the same time the necessity of providing consistent inputs to the
modeling effort will impose a certairn discipline to the case study design,
and ensure comparability of results.
The fourth task is dissemination of the research results. This
proposal will contain specific suggestions for dissemination activities to
be funded now as part of the research project. We shall also propose,
more generally, other types of research dissemination which m8y be carried
out separately from the project itself.
General Consequences of Rent Control
To potivate this proposed analytical framework, it is important
that we understand the three ways in which rent control affects housing
markets.
Rent control limits the amount by which rents can increase. As
a consequence, rents of controlled dwellings are less than they would be
in the absence of rent control. Landlords can respond to these rent
reductions in three ways. First, they can operate their properties the
same as they would without controls. In that case, tenants will continue
to receive the same "quantity of housing services" (a summary measure of
shelter, amenities and convenience provided by a dwelling). Since they
will pay less rent for the same quantity of housing services, the price of
those services is reduced. Second, landlords can reduce maintenance to
offset, at least in part, their revenue losses. As a result of the
lowered maintenance, dwellings deteriorate, causing a drop in the quantity
of housing services they provide. Finally, landlords can remove their
dwellings from the rental market by abandoning them or converting them to
other uses, such as owner occupancy, and over time, potential starts may
be foregone. In fact, all three responses occur: some results in cuts in
the quantity of housing services available in the rental housing market.



10
Consequently, we need a set of models which can estimate three
primary impacts of rent control law:
o Rent reductions
o Housing deterioration caused by rent reductions
o Other rental housing losses (demolitions, conversions and
foregone starts) caused by rent reductions
From these primary impacts a variety of secondary or derived effects can
readily be studied. Examples of importanit derived effects are:
o Price and quantity changes derived from rent charges
o Present values of gains and losses to tenants and landlords
o Effects of rent control on household location, mobility, and
tenure choice
o Effects of rent control on locU public finance, mainly
through property taxes
o Alternative adjustment mechanisms, e.g. key money4/
These are key results to be gleaned from the case studies, and once we
have these estimates of the magnitudes involved under different rent
control regimes and market conditions we can generalize the results in the
modeling effort. Each primary and derived impact will be discussed
briefly, in turn.
Rent Reduction
To assess the percentage rent reduction caused by rent control,
we will first estimate what the rents would have been in the absence of
rent control, and then compare those results with what the controlled
rents actually are. Because the former (free market rents) are not
directly observable in cities where controls are pervasive, indirect
estimation methods must be used. The principal options for that purpose
are: to rely on proxies for market rents where they have been collected
through household surveys; to apply a hedonic index procedure; or to
utilize the cross-country housing expenditure model of Malpezzi and Mayo
(1985). These methods are described briefly in the section on case
studies, below.
4/   Key money refers to lump-sum paymerits made to landlords when a new
tenant moves in. In some uncontrolled markets such payments are
customary and legal (e.g. Korea) but in rent controlled markets they
are usually illegal.



- 11 -
It is widely known that most rent control laws often treat
housing units differently when the tenants are new than when they have
been there longer. What is not so widely known, however, is that the
uncontrolled housing market also" treats the two types of units
differently: landlords set first rents higher than the market average,
and raise later rents by less than the growth in average rent. That
pattern of rent payment may not appear to have much effect on tenants, who
on the average pay the same rent they would if landlords set first rents
at the market average and afterwards raised them. by the growth in average
rent. However, individual tenants can be much affected.
In Light of the above, projected average rent increases without
rent control must be split between the two types of units; rents for units
that keep the same tenant increase by less than rents for units that
acquire a new tenant. For example, Rydell et al. (1981, p. 51) found that
in Los Angeles during eight years of 10 percent average rent inflation,
annual rent increases for units keeping the same tenant would be only 8.2
percent, while annual rent increases for units obtaining a new tenant
would be 14.3 percent. The case studies will provide new evidence on the
extent of this differential treatment of new and continuing tenants in
other markets.,
This rent-setting behavior in uncontrolled markets has two
important implications for assessing the impact of rent control. First a
limit on rent increases for units that keep the same tenant during a year
can be less than the average growth in uncontrolled market rate and still
not cause rent reductions overall. Second, since landlords are accustomed
to raising rents above average market rents upon a vacancy, they will
continue to do so under a rent control law that has a vacarncy decontrol
provision. However, under rent control, landlords will set first rents
even farther above the market average to compensate for the smaller
subsequent rent increases allowed by control (we assume that tenants are
willing to pay somewhat higher first rents because they know the
subsequent annual increase will be low).
Similar examples can be worked through for other types of rent
control regimes. For example, the use of key money to clear markets "on
average" has similar, strong, distributional implications.
Housing Deterioration
Rent control offers landlords an incentive to allow their
properties to deteriorate. When the rent reduction caused by rent control
is 10 percent, landlords can charge the market price for only 90 percent
of the housing services they produce. In the long run, landlords will
allow the portion of their output that yields no revenue to disappear
through deterioration.
However, knowing that in the long run landlords will allow their
properties to deteriorate in proportion to the size of the rent reduction
tells us little about deterioration in the short or intermediate run.
Also, incentives can be created for tenants to invest in or maintain units
if an increase in occupancy rights (tenure security) associated with rent



- 12
control implies that tenants can now capture the gains from such
expenditures. The existence and size of this effect will vary with type
of law, ma-rket conditions, and with landlord and tenant characteristics.
The question is not only whether rent controt induces
deterioration or by how much, but rather how rapidly it does so. Rydell
et al. have provided one estimate of a bound on such deterioration.
Comparable data on variation in depreciLtion rates in 59 U.S. cities
(Malpezzi et al. 1985) will enable estimation of the differential effects
of different laws, albeit in a developed country0 Hedonic indexes from
the case studies will provide additional information from developing
countries.
Rental Housing Losses: Demolitions, Conversions, and Foregone Starts
Regardless of the cause--declining demand or rent control--rent
reductions motivate landlords to consider alternate uses for their
property. Some remove the property from the housing stock (by either
demolishing it or converting it to nonresidential use); others convert
their rental 4inits to owner-occupancy units. Only a small fraction,
however, make such changes in any one year, even in the face of large rent
reductions0 Probably more serious, especially for developing countries,
are future starts foregone. For all three components of inventory change,
as in the case of deterioration, the question of rental housing losses
caused by rent control becomes a question of the pace at which change
occurs.
Time series data from the case study markets wiLl. be used to
relate variation in removal and tenure-conversion rates to variation in
revenue caused by different housing market conditions. Applying the
results of that analysis to the revenue losses cauised by rent control we
previously estimated gives the estimates of losses in the rent-controlled
housing supply from removals, conversions, and foregone starts.
Decomposing Changes in Rents into Price and Quantity Changes
If landlords undermaintain rent-controlled units, the resulting
housing deterioration offsets, in part or in toto, the tenant's seeming
rent bargain0 We therefore require a measure of how much of a bargain
rent control actually creates for a tenant; that is, we must measure how
much rent control lowers the price of rental housing services, and how
much the quantity changes. The notions of the quantity of housing
services, and its corresponding price, are developed elsewhere (Muth,
1969).
The method of hedonic equations is one way expenditures on
housing can be decomposed into measurable prices and quantities so that
rents for different dwellings or for identical dwellings in different
places can be predicted. A hedonic equation is a regression of
expenditures (rents or values) on housing characteristics and is explained
in detail in Malpezzi et al. (1980). Briefly, the independent variables
represent the individual characteristics of the dwelling, and the



- 13 -
regression coefficients are estimates of the implicit prices of these
characteristics. The results provide us with estimated prices for housing
characteristics, and we can then compare two dwellings by using these
prices as weights. For example, the estimated price for a variable
measuring number of rooms indicates the change in val-ue or rent associated
with the addition or deletion of one room. It tells us in a dollar and
cents way how much "more house" is provided by a dwelling with an extra
room.
Ordinarily we would prefer to estimate such a regression
separately in each market, where prices and quantities ideally clear. For
many purposes it will be useful to define submarkets by tenure and degree
of control. The definition of markets will be addressed in some detail in
the research project.
Once we have estimated the implicit prices of measurable housing
characteristics in each submarket, we can select a standard set of
characteristics, or bundle, and price a dwelling meeting these
specifications in each submarket. In this manner we can construct price
indices for housing of constant quality across submarkets. In a similar
fashion we can use the results from a particular submarket's regression to
estimate how prices of identical dwellings vary with location within a
single submarket (e.g., with distance from the city center), and to
decompose the differences in rent or house values into price and quantity
differences.
A related method of estimating the rent reduction due to
controls is to rely on direct proxies for market rents which can be
collected for controlled units in some markets. For example, in Cairo,
Egypt, information was collected on the rents units would command in the
furnished, uncontrolled market (Malpezzi, 1984a). Such proxies must be
used with caution, however. The presence of a large controlled market can
radically affect the price paid in the uncontrolled market (see Fallis and
Smith, 1984). In the Egyptian case, the market proxies were found to be
strongly correlated with dwelling characteristics and other expected
correlates, but they were found to be much higher across the board than
the long-run equilibrium market rents predicted by a cross-country model
of housing demand (Malpezzi and Mayo 1985, Ch. 3). The proxies were
adjusted downward accordingly, and then decomposed into prices and
quantities using the method of hedonic indexes, as above.
Present Value of Tenant and Landlord Gains and Losses
Tenant gains from rent control are derived from the price
reductions (rent reductions net of deterioration) less the value of any
distortion in tenant behavior (e.g. because households are unlikely to be
able to consume the quantity of housing services they would like to
consume at controlled prices). Landlord losses are the revenue losses
from rent reductions and stock removal plus rent control fees paid by
landlords less savings from reduced maintenance expenditures. These gains
and losses can be straightforwardly estimated in consumer's and producer's
surplus models. Examples of such estimates include Olsen (1973), Malpezzi
(1984a), and Linneman (forthcoming).



° 14 -
The present value of landlord losses will, in general, be
greater than the present value of tenant gains. This "transfer
inefficiency" of rent control has two causes. First, the administrative
burden of rent control is commonly borne by landlords-. Second, the losses
of housing benefits to tenants from deterioration can exceed the savings
to landlords from undermaintenance.
Effects of Rent Control on Household Location, Mobility, and Tenure Choice
The first order welfare change tenants experience under rent
control stems from disequilibrium in the consumption of housing
services. The price per unit of housing services may be lowered in the
short run, but the consumption of housing is constrained: households
cannot, in general, consume as much housing as they desire at the
prevailing price. Changes in consumer's surplus (and the related changes
in producer's surplus to landlords) have been the focus of most cost-
benefit studies to date. However, there are several second order effects
which could be quite important. Household mobility can be sharply reduced
by rent control, especially if there are accompanying laws restricting the
ability of landlords to evict and choose tenants.   For example, the median
length of tenure for renters in the Cairo market is 13 years. This
compares to medians of 1 to 3 years in uncontrolled markets in the U.S.
Restricted mobility can have serious implications for the labor market,
transportation, fuel consumption, etc.
The ability of tenants to choose the form of tenure they desire
can be impg;red by rent control. Not all households are better off as
homeowners- ; if rent control shrinks the rental sector, households may be
forced to choose a form of tenure inappropriate to their current economic
circumstances.
Effects of Rent Control on Property Taxes
The effects of rent control on property taxes can be studied for
two cases: when controlled rents are the basis for assessments, and when
market values are the basis for assessments0
The first case is the more extreme. India is an oft cited
example, where even units in the uncontrolled submarket, including owner-
occupied units, are assessed at the controlled rents. Once we are armed
with reductions in rents, calculation of rough estimates of the losses are
straightforward. Once the rent reduction is further decomposed into price
and quantity changes, and information is collected about reassessment
practices, more refined estimates of the effects of changes in the rent
control law on property tax collections can proceed (see Rydell and
Murray).
5/   See The Urban Edge (1984).



- 15 -
In the second case rent control also affects tax revenues,
because market values are related to the present value of rents. Under
some conditions rent control will, for example, depress values of
controlled units but increase values of uncontrolled units (Fallis and
Smith 1984). Sorting out the net effect on tax revenues correctly
requires taking this effect on related markets into account.
In both cases key administrative features, mainly the rate of
reassessment and other assessment practices, are keys to predicting actual
effects. Both the survey and the case studies will collect information on
these practices.
Alternative Adjustment Mechanisms
There are at least seven alternative gqjustment mechanisms which
can equilibrate a notionally controlled market." The maintained
hypothesis is that markets must adjust in some fashion in a long run,
given alternative opportunities for landlords and a housing stock of
limited durability; Four of the adjustments are embodied in rent control
laws: (1) indexing (keeping real rents constant), (2) reassessment for
new tenants, (3) differential pricing of new and existing units, and (4)
differential pricing for upgraded units. Three are market responses which
policymakers would generally consider undesirable outcomes, namely (5)
accelerated depreciation and abandonment, (6) side payments such as key
money and tenant maintenance expenditures, and (7) distortions in
consumption, not only in the composite housing services but also crowding,
length of stay, mobility and tenure choice. Mechanism (5) has already
been discussed in some detail; here the others are treated briefly.
Indexing: Keeping Real Rents Constant.-/ This adjustment
scheme has attracted much interest from the proponents of "moderate" rent
control in the U.S. It has a great deal of superficial appeal, because it
addresses the short-run problem of quick price runups in reaction to
market swings, while presumably retaining incentives for landlords to
invest because they can earn long-run normal profits. Arguments against
it are that such a scheme would mitigate the role of prices as a signal
for new investment, that once imposed it will be tightened because of the
political clout of tenants relative to landlords, that choice of an actual
index is problematic, and that landlords are so nervous about controls
that imposition of moderate rent control would scare off investment
anyway. What has not been emphasized in the rent control literature is
the fact that in a well functioning market housing price increases vary
spatially for good reasons. For example, in the simple monocentric model
of a growing city with a putty-clay housing stock, rents rise faster on
the periphery than in the center. A system which tended to equalize rent
changes would seriously distort the spatial structure of a city over time,
with appreciable attendant welfare losses.
6/   For now assume laws are enforced as written.   The research project
will study laws as enforced.
71   Of course alternative indexing schemes can be analyzed, but this is
one commonly put forth by moderate rent control advocates.



- 16 -
Note that indexing schemes which are not tied to a price index
but which are set at some a priori "reasonable" annual rate of increase
will place landlords (and eventually tenants) at the mercy of variable
general inflation.  Schemes which only permit partial price changes up to
the index will also have deleterious effects relative- to full indexing.
The survey will examine the frequency of alternative indexing
mechanisms. The case studies will be of markets with different indexing
schemes, yielding estimates of the effects of alternative indexing
methods. One of the key features wihich will be used to differentiate the
stylized regimes used in the Task 3 modeling will be the type of indexing.
Reassessment for New Tenants.  Perhaps thr, appeal of this method
is tied to the image of elderly tenants on small fixed incomes who are
attached to their neighborhood and who Would adjust to a move only with
some difficulty. Presumably if tenants moved voluntarily, the new tenant
should the.i face market prices since they choose to move in. However, it
is not clear why landlords should bear the cost to society of maintaining
the elderly's real income. A subsidy or cash transfer would be more
appropriate. One advantage of such a system is that at least landlords
will gain from tenant's leaving, so there is some incentive to buy out the
sitting tenant.  This could yield a more efficient allocation than a
system with no such gains to mobility (see the following discussion on key
money and mobility). All three tasks--survey, case studies, and case
study integration--will take assessment practices into account.
Differential Pricing of New and Existing Units0 This has become
quite common, although the details vary greatly from market to market.
For example, in Egypt, controlled rents which are based on value at the
date of construction yield rents which vary more by age of structure than
does the quantity of housing services produced by those structures
(Malpezzi 1984 b, pp. 10-13).  In India, the rent holiday scheme and
assessment bafsed on historical cost have a qualitatively similar effect.
In Egypt, with tight controls on monthly rents, but higher rents (and key
money) from newer units, new construction continues at an impre'ssive pace;
in India the rates may have been more seriously depressed. However,
Ghanaian controlled rents do not appear to vary in this fashion, and it
appears that new construction had ground to a halt by the period studied
(1981). Note that a key money system also works as an incentive to new
construction, since new units have new tenants from whom such payments can
be extracted. Data on new construction will be collected for the case
study markets to permit stronger tests and generalizations.
Differential Pricing for Upgraded Units. This is very similar
to the above, It provides an incentive for additional housing investment
per unit through upgrading. Cairo and Los Angeles, among other cities,
share this provision. Malpezzi (1985) provides simulation results that
suggest that such a system could prove highly stimulatory to upgrading,
since the entire unit can usually be revalued, Empirical work shows that
such upgrading exists in Cairo but on a modest scale (Malpezzi 1985,Ch.
4). Further evidence from additional markets is needed.



Side Payments. Once a tenant is in place, monthly rents
collected usually correspond to the controlled rents, according to survey
evidence from Cairo, Bangalore, and Kumasi. If tenant protection laws are
enforced, then landlords will have difficulty extracting more than the
legal rent from sitting tenants. But there are other payments for housing
services which can make up much of the difference between controlled and
market rent. Key money, or luWy-sum payment at the time of occupancy, is
a common adjustment mechanism.-    Such payment systems can work most
efficiently if finance is available. Low-income tenants in developing
countries do not, in general, have easy access to such finance; even for
higher income tenants, and in countries with well developed capital
markets, financing key money is made difficult by the fact that the right
of tenure purchased is not recognized as collateral. Other side payments
which can help equilibrate include: (1) utility payments, and payments
for public services; (2) tenants can take over maintenance and repair
expenditures which would otherwise be incurred by landlords; (3) where the
tenant's occupancy rights are very strong, they may make major physical
changes to the structure. The last point in particular points out that
renting in a controlled market is actually a vpy different bundle of
property rights than renting in a free market.-
The data from Cairo have particularly good information about
these side payments. Those data have been extensively analyzed in
Malpezzi (1986), and Table 2 presents summary results from that study.
The method used can be outlined as follows. Hedonic regression models
were used to estimate market prices of controlled units, and the quantity
of housing services produced for each unit. Next, data from both
controlled and free markets was used to estimate the demand for housing
services. Demand estimates were used to co T8te cost and benefit measures
of the households in the controlled market.-° The analysis was done
twice, once using net controlled rents, and again using gross rents which
are controlled rents plus side payments (utilities, tenant maintenance and
repair expenditures, amortized key money, and amortized tenant upgrading
expenditures).
Table 2 demonstrates that side payments equilibrate much of the
Cairo market. The key result is the following: whein net rents are used
in the analysis, renters appear to pay less than 40 percent of estimated
market prices for housing services. In addition, according to the demand
relation estimated with net rents (based on owners and renters, but
adjusted for length of tenure), renters consume less in housing services
8/ Loikkanen (1983) and Skelley (1986) present theoretical treatments.
9/ See Malpezzi (1986), Chs. 4 and 5, for elaboration.
10/ Details can be found in Malpezzi (1986). The method used is similar
conceptually to Olsen's, outlined above. The exact method of
computation borrows heavily from Schwab (forthcoming), who integrates
Hausman's (1981) analysis of the computation of consumer's surplus
measures from log-linear demand equations, with Neary and Roberts'
(1980) exposition of using shadow prices to analyze rationed demands.



- 18 -
Table 2: Welfare Measures and their Components:
Cairo Renters
Quantity of                  Implicit    Welfare Cost       Net
Housing Service     Price       Subsidy      of Ration      Benefit
Sample Statistics
Based on      Q3*   1409          0.66       19.94          12.14         10.10
Net Rents     Med    8.2          0.38        8.24           4,78          5.76
(naive       Q1     1.4          0.23        2.25           1.06         -0.59
model)
N      312          297         239            239            239
Prob > |sj                     .001           .001           .001
Based on      Q3  - 29.4          1046       12D00          20.89          8e11
Gross Rents   Med   17.0          0.71        3.27           5.84         -1.04
(correct     Q1    10.1          0.42       -3.76           1.36         -27.66
model)
N     312           297         237            237            237
Prob > |s8                     .001            0001          0001
Representative Consumer **
Net                  8.2         0.38         5.08           0.27          4.82
(native
model)
Gross               17.0         0.71         4.93           0.63          4o30
(correct
model)
*   Notation: Q3: third quartile; Med: median; Ql: first quartile;
Prob > jsf: Probability of observing such a large centered signed
rent statistic (not reported) if the population mean is zero,
Units: estimated equilibrium competitive price normalized at one;
all other variables in Egyptian pounds. One pound was approximately
one U.S. dollar in 1981 at unofficial rates. Median renter income
is 85 pounds.
**  Income, Quantity, Price set at each variable's median.
For other demand determinants, use median of dot product
of sampLe values and demand coefficients,



- 19 -
than their estimated equilibrium demand. In fact, they consume less than
they would demand at higher market prices. This ration imposes a welfare
cost which reduces, but does not eliminate, the overall benefit to
tenants.
This naive conclusion is radically changed when rents are
corrected by including side payments. The median price paid is now seen
to be much closer to the estimated market price of housing.   Side payments
allow landlords to recover, on average, 71 percent of estimated market
prices, although there are certainly many households who pay less than
estimated market prices; for that matter, many pay more. The
distributional implications of this wide variation are discussed in
Malpezzi (1986).
Policy Issues
Clear policy analysis of rent control has been hindered by the
lack of empirical estimates of the impacts of controls, and can be greatly
improved by (1) additional estimates of gains and losses from different
types of regimes, in different markets, and (2) consistent accounting of
the gains and losses to different agents (landlords, tenants, government,
deadweight losses) from different sourc2s (changes in prices and the
quantity of housing services, but also changes in mobility, tenure,
employment, and tax revenue).
By themselves case studies can yield insights into the policy
issues, but they are limited by their partial nature. The purpose of the
third task is to clearly and sharply define the costs and benefits to all
agents from all sources. Of course, the case studies will yield useful
policy advice of a partial nature.
For example, the research on Cairo has shown that (1) the rent
control regime extracts a welfare cost from tenants as well as landlords,
because their housing consumption and mobility are constrained; (2) that
aggregated resuLts mask large welfare gains and losses to individual
tenants. These results suggest that decontrol is desirable in the Cairo
market. However, immediate blanket decontrol would adversely affect not
only long-term tenants who pay lo;w monthly rents, but recent movers who
paid large amounts of key money in anticipation of future low rent.
Landlords would unambiguously benefit from decontrol; owners of older
units would receive market rents, and owners of (mostly newer) units with
recent tenants could receive a windfall from increasing rents while
retaining key money. In effect, recent tenants have purchased a property
right which decontrol abolishes.
Vacancy decontrol would have the general advantages (and
disadvantages) of a gradual adjustment to a newly competitive market.
Landlords could in some cases accelerate the process by offering financial
incentives for tenants to move. On the other hand vacancy decontrol could
take decades to move to a competitive market, with continuing welfare
losses for a generation or more. For vacancy decontrol to work, it would
be important to change tenancy laws so that rights of occupancy at
controlled rents cannot be passed on to heirs.



- 20 -
An alternative scheme would be to combine vacancy decontrol with
"floating up and out"; controlled rents would be no longer nominally fixed
but c:ould rise within limits based on a general price index. The actual
formuzla alopted could speed adjustment. For example, rents could be
adjusted by larger fractions (or multiples) of the CP-I change for older
units or units with long-term tenants.
Which decontrol scheme is optimal? Firm recommendations on
alternative policies are hard to make at the present time0 They should be
based on consideration of the effects of the change on all agents from all
sources. The cost-benefit estimates to date are limited to changes in
consumer surplus from price and consumption changes0 Changes in mobility,
tenure, tax revenue, etc. are ignored. The dynamics of adjustment are not
well understood. In a market for a good so durable, explicit
consideration of these dynamics, even if they must rely on assumptions of
the speed and nature of the adjustment process, are essential0 The model
built for the third task will consider these dynamics0



- 21 -
II. PREVIOUS RESEARCH ON RENT CONTROL
In this chapter, previous research on rent control is very
briefly reviewed, so that the reader can put the proposed project into
context, and in particular understand how our reading of the literature
has motivated the development of this proposal.   The review makes clear
the potential gains from a modest amount of additional research.
Economic research on rent control has so far largely focused on
the comparative statics of a simple price control, or on dynamic
disincentives to landlord investment and maintenance from a simple price
control. Many rent control regimes, as implemented, are quite different
from simple price controls. In particular, rent determination schemes are
often quite complex, resulting in a schedule of prices which vary by
vintage of housing capital, length of tenure, recent upgrading, etc.
Theoretical work to date has taken little account of this complexity.
Even within the simple analytic framework, only a handful of studies have
put forth empirical results. In addition, most empirical work has been
done in North America.
The purpose of this proposal is to illustrate how the framework
for applied research on rent control can be expanded to model policy
regimes that, while still stylized, capture some of the important features
of actual rent control policies. Here we briefly review both the standard
neoclassical views on rent control, and a few recent extensions.
Analysis of Rent Control View2 as a Tax on Housing
Capital m
Simple rent control 2/ can be viewed as a tax on the profits of
landlords, or a tax on the return to housing capital. The traditional
textbook analysis of rent control as a price control then follows
directly. When rent control is imposed, the price per unit of housing
service charged by landlords is reduced by fiat. In Figure 1,
representing market demand and supply, this is represented by a move from
PO to P1. If rather than being reduced, rents are frozen at existing
levels, then an assumed shift in demand or price inflation leads to a
similar divergence between equilibrium and controlled prices. In the
1/ This section is based upon Olsen's (1969) unpublished paper, and on
similar published work by Frankena (1975). These and similar analytic
treatments present arguments developed earlier in, for example,
Friedman and Stigler (1946), Grampp (1950), and Paish (1950). This
review is not exhaustive. See Thibodeau (1981) for an excellent
review. Malpezzi (1985) contains an expanded literature review. Two
useful compendiums are Block and Olsen (1981) and Gilderbloom
(1981). United Nations (1979) reviews rent control in developing
countries.
2/ Simple in the sense that dynamic price adjustment mechanisms are
ignored.



- 22 -
short run, the housing stock is fixed, (So), so at P1 there exists excess
demand (Q1 - Q0), and housing is rationed. The divergence between Po and
P1 also provides a strong incentive for the development of a key money
system, where amortized key money makes up the difference (POQO     PlQO)
In the longer run, the supply schedule has more elasticity CS1),
and so if key money has not become an effective equilibrating mechanism
(because of strict enforcement, or because it is difficult to collect key
money from tenants already in place, or simply because low incomes and
poor capital markets make it difficult for many renters to finance key
money payments) then landlords decrease the quantity of housing services
supplied to Q2. Some houses are demolished early, and new starts are
foregone. Obviously, shifts in demand as population and income increase
will exacerbate this situation. In the very long run, with an elastic
supply 02), the simple competitive model implies an unhoused population.
In fact, landlords even have some ability to alter the quantity
of housing services from an existing unit. Figure 2 therefore presents an
alternative model, based on Olsen (1969) and Frankena (1975), which models
rent control as an expenditure control, not a price control.
Suppose that rent control is imposed, and initially lowers real
rents to  P    That is, the supply curve in the immediate market period,
which is no! shown, is vertical, and the immediate effect of the
unanticipated imposition of controls is to effectively reduce the price
from  P0 to P1.  Rent is fixed at   P Q0.
But in the intermediate run landlords have some latitude to vary
the quantity of housing services available in the market, as represented
by the slo7 of S. Also, virtually all real world rent control regimes
fix rents - s not the price per unit of housing services. Specifically,
rental expenditure is fixed at P Q , that is, landlords are constrained
by the rectangular hyperbola E, tie Yocus of all quantitiesand prices
yielding P1 QOs
Now there is no longer a market clearing equilibrium, and, in
fact, the final price per unit of housing services can exceed the original
uncontrolled price. As drawn, landlords can reduce supply to Q during
the intermediate period, but charge   P2 Q1.   Note that at  P2 tAere is
excess demand   2   Q1-    If the minimum quantity which could be offered
in the intermediate run (the vertical portion of the supply curve) were
less than Q (where E intersects with the demand curve), Q3 would become
the binding constraint because at prices higher than   P   consumers would
demand less housing than was offered.
3/ Some rent control regimes try to limit the landlord's supply response
with building codes and maintenance provisions. These are difficult
to enforce and cannot in any case prevent some supply response.



Figure   2
Figure   1
Rent Control as Expenditure Control
Rent Control an an Effective Price Control
so
Price
0                                                           S2                                         P 0
Pi,
pE
Q2        0            n3                                                                        41     Q2     40                   '(uantity
l'he "equilibriumi" quantity of liotising supplied at the controlled
price P  is the minimum of housing demanded and offered after                                             Rens, not prices, are controlled. llere attempt by
imposition of the control. The outcome depends largely on the                                             controlling authority to reduce rent to P1 results in
supply elasticity: if zero (S ) no effect on quantity: in very                                            reduced quantity Q1 at price P2, rent PIQ0.
lnig run (S2) no housing produced: in the intermediate run, min
(Ql'Q2) = Q2.



- 24 -
The existence of an alternative owner occupied market further
complicates the analysis. In one polar case, if the supply of housing
services from this sectoer is perfectly elastic (and transactions costs
broadly defined are ignored), the existence of this sector will limit
prices tz, P0,    since if prices rise farther household will switch
sectors - . In the other polar case, assume that there is no available
owner housing or that transactions costs, lack of finance, etc. constrain
households to remain in the rental market. Then the analysis presented
earlier stands.
The extension of the price control model by Olsen and others to
expenditure control is therefore shown to lead quickly to further
complications.  Data requi.rements for predicting consequences of rent
control using this model are quite high: in particular the existence of
alternative submarkets complicates the analysis. Further, little insight
is given into dynamics.
Dynamic Models of the Effect of Rent Controls on
Maintenance
We have just seen that comparative static models which allow for
some price elasticity of supply of housing services imply that rational
landlords will permit their dwellings to deteriorate over time. If the
rent control regime fixes rent, it can be modeled as a tax or a tariff in
the immediate market period, but a reduction in the quantity of housing
services supplied over a longer period results in a fixed expenditure,
i.e., lower quantity, with a return to market price.
Dynamic models of profit maximizing landlords have provided some
insight into this process, and a little empirical support. One of the
first studies in this vein was by Moorehouse (1972), who examined the
optimal choice of maintenance inputs by a value maximizing landlord.
Using a three input production function (capital, current inputs which
must be employed at some exogenous fixed rate, and variable maintenance
inputs), and assuming geometric physical depreciation of the unit,
Moorehouse investigates a rent control regime which freezes nominal rents
during an inflationary period. In other words, the time path of real
rents falls by the rate of general price inflation, and rises by the rate
of depreciation not offset by maintenance. His model predicts that in a
competitive market with general inflation, dynamic equilibrium requires
concomitant increases in rents; but in a rent controlled market, the
burden of adjustment falls on maintenance.
Related studies by Dildine and Massey (1974), Arnault (1975),
and Kiefer (1980) reach the same conclusion: rent control reduces
maintenance of housing units ceteris paribus, Kiefer additionally studies
the optimal economic life of a structure, and finds that rent control
leads to premature abandonment, compared to the uncontrolled case. In a
4/ Note that under such extreme assumptions the rental demand curve would
not have slope above P0



- 25 -
related empirical study of an uncontrolled market, Bender (1979) finds
that declining housing prices in general are associated with higher rates
of demolition. This unsurprising finding indirectly supports Kiefer's
conclusions that rent control reduces the optimal life of a dwelling. It
can do this because (i) the present value of rents is- lowered relative to
alternative uses; and (ii) lower maintenance can directly shorten the life
of a structure.
Rydell and Neels (1982) estimate directly the elasticity of
housing services with respect to maintenance using data from the Housing
Assistance supply experiment. In any period, housing services are the sum
of housing services last period, plus some (nonlinear) function of the
last period's maintenance and repair inputs, minus gross depreciation:
H    = H  + aM  - bH
t+l    t     t      t
Using iterative techniques, they find that the best fit is-obtained when a
gross depreciation rate of eight percent is assumed (the elasticity, A ,
is estimated to be .17). In other words, without maintenance dwellings
will depreciate by-eight percent per year. This places a bound on how
fast landlords can decrease the quantity of housing services as a response
to the imposition of controls.
Estimates of Costs and Benefits, and their Incidence
Perhaps the first careful s ydy of the costs and benefits of
rent control is Olsen's (1973) paper.- Using data from New York City in
1958, he used estimates from a hedonic index of uncontrolled units to
predict the uncontrolled rentals of controlled units. In an analogous
fashion, he used the data from the uncontrolled portion of the market to
estimate the free market Engel curve for housing serv;ces. The average
controlled rent for an apartment was $999 per annum;- the average
uncontrolled rent predicted by the hedonic results for those same units
was $1,405, implying a subsidy of $406. The average free market
expenditure for the controlled households was $1,470, indicating that they
consumed slightly less housing than they would have in the free market.
The average household in the controlled market consumed about four and a
half percent less housing than they would have in the free market.
Olsen computed the economic benefit of rent control to each
tenant under the assumption of a unitary price elasticity:
Rc + R [log R - log R]
where  R  is the (fixed) market demand at market prices (conditional on
income and other demand determinants?, and i is the market rent of the
controlled unit. Olsen's estimate of the average net benefit is $213,
little more than half the gross subsidy implied by rent control.
5/ Other such studies include Malpezzi (1984 a) and Linneman
(forthcoming).
6/ The average income, for comparison, was $6,229.



- 26 -
The benefits are found to be slightly negatively related to
income, larger for larger households, and larger for households headed by
older people. The annual benefit is estimated to decrease by about one
cent for every dollar of additional i7come, $9 per year of head's age, and
$69 per additional household member.7 Benefits do not vary significantly
by race or sex of head of household. Rent control in New York City in
1968 appears to redistribute income, but very weakly, and in no way
proportional to its cost. Olsen showed that there is a slight tendency
for lower income households in New York City in 1968 to receive slightly
larger benefits.
A Recent paper by Peter Linneman (Linneman, forthcoming) updated
Olsen's study. In 1969, 1971, and 1974 New York made important changes in
its system of controls, with two key effects: (1) most post-1947 units
were brought into the rent control system, and (2) a distinction was drawn
between "controlled" and "stabilized" units. Controlled units (roughly,
pre-1947 units with tenants who moved in prior to 1947) have rents set by
the Rent Control Division while stabilized units (newer units, or pre
1947 units with new tenants) have rents set by negotiations between
landlord and tenant, subject to approval of a board comprising landlord,
tenant, and government representatives (see Linneman for details). In
1981, about 1i percent of privately rented units were in the controlled
sector; 62 percent were stabilized; and 19 percent were uncontrolled.
Private rental housing was about 72 percent of stock.
Linneman examines (1) the length of tenure in each sector
(controlled, stabilized, and uncontrolled), and (2) rents paid in each
sector compared to predicted rents from hedonic regressions from the
stabilized sector. He find that, after controlling for age and other
household characteristics, (1) tenancy duration in the stabilized sector,
and (2) the controlled sector has a much longer tenancy duration (12
years) than the other two sectors. The hedonic confirms large differences
between the controlled and stabilized sector rents, after controlling for
quality: controlled units rented for $951 per year less (on average) than
the hedonic predicted they would rent for if stabilized. And in fact,
rents are actually lower in the uncontrolled sector than predicted if in
the stabilized sector ($200 per year less, on average). A detailed
analysis of the distribution of the benefits of rent control demonstrate
that the New York system does, on balance, redistribute income from high
to low income households, but the effect is weak and very poorly targeted.
Daniel Pena and Javier Ruiz-Castillo (1984) carried out a
similar household level cost-benefit analysis for Madrid. Madrid also
has, in effect, a two tiered system. Roughly, units occupied before 1964
have their rents controlled by the government. Only small increases in
their rents have been permitted. Units occupied after 1964 are under a
7/ Olsen notes that these regression results may understate the
regressivity of benefits because lower income people are more likely
to rent in the controlled market and, hence, appear in the regression
sample.



- 27 -
slightly more liberal system: leases must be renewed, but at a rent agreed
upon by the landlord and tenant, subject to a government ceiling which is
more generous than the increases permitted in the strictly controlled
sector.
The authors treat the post 1964 sample as approximately
uncontrolled, a limitation imposed by the data. They find an average
monthly rent of 945 pesetas in the strictly controlled sector, while the
average predicted rent for these units (using moderately controlled
hedonic prices) is 4694 pesetas. The average income in the strictly
controlled sector is about 75 percent of the average income in the
moderately controlled sector, suggesting some redistributive effect.
However, extepsive multivariate tests suggest that the subsidy is poorly
targeted: personaL characteristics, including income, explain only 30
percent of the variances in benefits. The size of the benefit is
positively correlated with income. Further, households with lower
socioeconomic or educational status, unemployed household heads, and
female household heads receive systematically lower benefits.
Rent Control and Mobility
Two studies, by Clark and Heskin (1982) and Boersch-Supan
(1983), examine the relationship among rent control, tenure discounts, and
mobility. It has been well documented that even in the absence of rent
control I7ng-term tenants pay lower prices for rental housing, ceteris
paribus.-   Landlords find it difficult to raise rents for sitting tenants
relative to increases for new tenants, landlords have an incentive to keep
desirable tenants in place through discounts, and tenants themselves are
less likely to move when they receive a good deal. The first study to
examine the length of tenure discount and mobility in the context of rent
control was Clark and Heskin (1982). They examined length of tenure
discounts and mobility rates, with and without controls, in southern
California in the late 1970s. They disaggregated their results by
geographic location, race, and income, among other things. They found:
length of tenure discounts increased under rent control; tenant mobility
decreased, except for the youngest group of renters; and the differences
were slightly larger for lower income households.
Boersch-Supan (1983) provides a detailed micro-economic model of
a housing market which implies that rent control of a particular type--a
freeze in real rents which is lifted whenever a new household moves in--
will result in larger length of tenure discounts and lower mobility
rates. He finds empirical support from Follain and Malpezzi's (1980)
estimates of the length of tenure discount for renters in 39 U.S.
metropolitan areas: the average annual discount is .95 percent for
uncontrolled cities, and slightly higher--l.1 percent in controlled
cities. The average length of stay is half a year longer in the rent
controlled markets--4.7 years versus 5.2 years.
8/ Follain and Malpezzi (1979), Malpezzi et.al. (1981).



- 28 -
Studies which Analyze Alternative Adjustment Mechanisms and
Methods of Decontrol
Two recent studies emphasize the analytical.and empirical
implications of alternative real world price adjustment mechanisms:
Richard Arnott's (1981) study of Ontario's rent control regime, and the
study of Los Angeles by Peter Rydell and his associates (1983).
Arnott presents a complete analysis of an actual law and its
enforcement. Ontario has had rent control since 1975. The law applies to
the existing stock (pre-1975), but rents are not frozen. Landlords choose
an automatic six percent annual increase, or can apply for exceptions
based on one of three criteria: (1) on the basis of cost increases
exceeding the guideline; (2) to attain a modest rate of return, currently
two percent; (3) because of a documented increase in the quality of the
unit, presumably through increased maintenance and repaid expenditures.
Most landlords take the automatic increase, and the third option for
exceptions had not been used at all as of the study date.
Arnott's analysis is primarily theoretical, some of it an
extension of the analysis cited earlier. He reiterates several important
arguments from the literature: (1) controls unambiguously hurt landlords
but their true distributional implications are unknown; (2) spillover
effects into the uncontrolled market are also ambiguous (see also Fallis
and Smith, 1984, and Marks, 1984); (3) effects on new construction of laws
that currently exempt new units depend on expectations of landlords, so
new construction may still be adversely affected. An interesting new
result from his analysis is that rent control could actually increase book
profits in early years, which would be more than offset by later losses.
Arnott also provides one of the few cogent discussions of alternative
decontrol schemes.
Decontrol is an important topic not often analyzed in the
literature. The familiar comparative static models provide little
guidance on how best to get there from here; by their static nature they
assume blanket decontrol works best in all circumstances. Arnott, on the
other hand, lists seven forms of decontrol (pp. 74-75):
Vacancy decontrol. Units are decontrolled as they become
vacant.
Vacancy-rate decontrol.  Particular housing submarkets
(defined on the basis of the location or type of unit) with a
vacancy rate above some statutory level are decontrolled.
Rent-level control,  Rent-level decontrol could be more
appropriately termed decontrol from the top down, since it
involves decontrolling the most expensive units first and the
cheapest last. The rent level above which units are
decontrolled can depend on the location or the type of unit.



- 29 -
-     Floating up and out.  This designation covers any gradual
relaxation of controls that applies uniformly across housing
submarkets. When controls are the GI/CPT type, floating up
and out entails gradually raising the guide-line increase.
Where the control program contains a rate-of-return provision,
this kind of decontrol could entail raising the rate of
return.
-     Contracting out.  This is a form of vacancy decontrol; the
landlord and tenant negotiate a sum that the landlord pays the
tenant if he vacates.
-     Local option.  A higher jurisdiction that currently
administers controls allows lower jurisdictions to choose
whether or not to retain them. Usually, the higher
jurisdiction requires the lower to administer the controls if
the latter decides to retain them.
-     Blanket-lifting.  All rent-control provisions are suddenly and
completely lifted.
After a thorough discussion of these alternatives, he concludes that lack
of quantitative estimates of relative effects precludes choosing a clear-
cut winner for Ontario's rent control regime, much less one method best
for all regimes. In particular, the method implied by comparative static
analysis, blanket decontrol, can have high costs:
The advantage of blanket-lifting is obvious: it eliminates at a
stroke what could become a malignant cancer in the housing market.
Such precipitate action has its costs, however, and the greater the
degree of excess demand in the market, the greater these costs will
be. If there is even moderate excess demand in the housing market
as a whole, there is probably substantial excess demand in certain
submarkets. The sudden and dramatic increase in rents that tenants
in these submarkets will experience with blanket-lifting may have
serious social and political repercussions. Many tenants will have
to find alternative, often unsuitable, accommodation in a hurry, and
for some the experience will be traumatic. The press is likely to
focus on instances of extreme hardship caused by decontrol, and in
response to the resulting clamor of protest, the government may
decide, against its better judgment, to reimpose controls. In
short, blanket-lifting is an attractive option only if there is
little or no excess demand in any housing submarket (p. 98).
Rydell et al. (1981) present an analysis of Los Angeles' rent
control regime. Los Angeles rent control has been in force since 1978.
After an initial freeze, rents for units occupied by sitting tenants could
be increased to recover repaid costs, or in recent years by some fixed
percentage (7 percent) which has been lower than the general rate of
inflation. Units are decontrolled as they are vacated, however, and
several classes of rental accommodation are uncontrolled: newly
constructed units, luxury housing (defined by pre-control rents), and
single family structures. Substantial rehabilitation ($10,000 - $17,000,
depending on size of units) also exempts units from controls.



30 -
The authors use a combination of empirical and simulation
methods to m7asure the effects of the laws on rents, depreciation, and
conversion.-   In addition to analysis of the effects from recent years,
they forecast the effects of six proposals for decontrol or tighter
control (see Figure 3):
-    End rent control immediately (labeled no law)
-    Phase out current law over two years, meaning two years of
rent increases up to 75 percent of the general price level,
followed by complete decontrol (labeled phaseout law)
-    Extend the current law (7.6 percent increase for sitting
tenants, no cap for units when they turn over)
-    Lower the increase for sitting tenants to 5.6 percent, with no
cap on turnovers
-    Keep the 7.6 percent increase for sitting tenants, but cap the
increase-at turnover at 10 percent.
-    Lower sitting increases to 5o6 percent, cap turnover increase
at 10 percent
On recent effects, the authors find only modest real reductions
in rents and in the quantity of housing services provided in the rental
market. Half of the decrease is from deterioration and abandonment, and
half from conversion to owner occupancy. The modest effects are almost
entirely due to the small divergence between assumed market outcomes
(prices rise with the CPI) and the increases permitted under the regime.
Two related questions which deserve more analysis are, first, what happens
in a market when controlled and market prices do diverge, and second, if
they did not diverge, what is the point of controls?
Examination of Figure 3 highlights the wide range of outcomes
from alternative policies. All simulations assume a 10 percent increase
in the general price level, and that in the absence of controls the
relative price of housing would remain flxed.   Blanket decontrol results
in rapid price adjustment, and a slower adjustment back to the long-run
equilibrium housing stock. A two-year phase in period, unsurprisingly,
has similar effects with a lag. Note that large real rent reduction of
the tightest law (5.6 percent allowable increase in rents for sitting
tenants, a 10 percent cap at turnover), is accompanied by a large decrease
in the quantity of housing services available0 Note that in this case
prices are being reduced at a rate which is declining over time, while the
quantity reduction ,is accelerating.
9/ The set of models used forecast the time path of rents, maintenance,
demolition, conversions, and new construction0 They are described in
Rydell et al. (1981).



Figure 3
Effects of Alternative Rent Control Laws, from                  Rydell et al.
14                                                                            14
12                                      1                                     12 7
10                                                                                               I, 10
6   -'
44
1978      1980      1982     1984      1986      1988     190098                        16         92       194       18         M      10
Percentage reduction in quantity of rent-controlled housing srvices            Percentage reduction in price of rent-controlled housing services
caused by alternative Los Angeles rent control laws                          causud by alternative Los Angeles rent control laws
Source:     Rydell et al., pp. 85-86.



- 32 -
The Relationship Between Controlled and Uncontrolled Market
Several papers have addressed the potential effects of a price
control on a related, though nominally uncontrolled, market: Needleman
(1965), Gould and Henry (1985), and Fallis and Smith- (1984). We focus on
the last paper.
Fallis and Smith actually develop two related models, one for
rent control regimes which exempt new units from price controls, and one
for regimes with vacancy decontrol provisions. Their short-run models
predict that under most conditions excess demand spills over into the
uncontrolled market, and, in the short run, drives up the uncontrolled
price. In thg long run, they implicitly assume an elastic supply function
that implies a reduction in the quantity of housing services from the
controlled sector, and an expansion in the uncontrolled sector, narrowing
the wedge between prices.
They also present an empirical test of the model using data from
Los Angeles (1969-1978). Following Rosen and Smith (1983), they assume
that there is a sttaightforward relationship between rental rates, R,
operating expenses, E, and the vacancy rate, V, estimated as:
Rt  -  6.25  +   .078 E  + 34.09 (1/V ) + 26.49 (i/V    )
(3.30)   (1.64)     (4.12)          (3.10)    t1
where dots, indicate time derivatives and standard errors are in
parentheses. Rent control was introduced in Los Angeles at the end of
this period, 1978. The estimates are' used to forecast what rents would
have been in the absence of controls, and the forecast compared with rents
in the controlled and uncontrolled sector. After two years, controlled
rents had risen by 10 percent less than the forecast, and uncontrolled
rents by 22 percent more, confirming the hypothesis that rent control
increses pric.es in the uncontrolled sector in the short run.
Summary of Rent Control Research Under RPO 672-46
As noted above, research on rent control in developing countries
has been undertaken as pert of RPO 672-46, "Housing Demand and Finance in
Developing Countries"-.L' That work includes several studies of Cairo
(Malpezzi 1984a and 1985; and Mayo et al. 1982, which predated the current
project), and studies of Bangalore, India (Tewari and Kumar 1985, and
Tewari and Malpezzi, forthcoming). A synthesis of those first studies can
be found in Malpezzi (1984b). Each will be summarized briefly, in turn.
10/ Little work had been done before this on rent control in developing
countries, other than a description of rent control laws in several
countries (United Nations 1979).



- 33 -
The research carried out by Mayo and his associates before the
research project noted several interesting facts about the Cairo market,
including a strong rate of new construction and a vacancy rate of almost
six percent despite enforced controls on monthly rents.paid and strict
tenant protection laws. The research by Malpezzi was designed to explore
the behavioral foundations for those facts, which are not predicted by the
standard price control model.
The simulation model presented in Malpezzi (1985) shows clearly
that the effect rent control has on housing investment is not robust to
type of rent control regime. While simple rent control (pure price
reduction, or an excise tax on housing capital) unambiguously reduces
investment by optimizing landlords, if the rent control regime allows
price to be a function of investment, the gain from revaluation can offset
this effect partiaLly or, in extreme cases, result in more investment in
housing capital than in the competitive case.
Casual observation suggests that controlled units in Cairo rent
for much less than.estimates of their market rent in the absence of
controls. However, Malpezzi (1984a and 1985) showed that when account is
taken of side payments, including key money, utilities, maintenance and
repair and upgrading by tenants the discount disappears--for the typical
(median) household. When these are included the median estimate of the
price per unit of housing services differs by only one percent from the
estimated long-run equilibrium free market price. But it must also be
emphasized that there is a wide distribution around this median. Quite a
few Cairo households to receive large discounts, just as some a few pay
rery high prices for housing services. These differences appear to be
largely unrelated to tenant characteristics measuring ability to pay,
raising questions of horizontal equity. Otherwise equal households
receive quite different housing "deals."
Most Cairo renters are well off their demand curve--much farther
off than can be explained by the stochastic nature of the estimated demand
relation. Corresponding to this departure from equilibrium, many
households have significant welfare losses from under and over consumption
of housing services. Underconsumption dominates, but about a third of the
renters constulme more housing than predicted by their demand relation.
This conclusion holds up even if households very far from their demand
relation are analyzed separately from those within a 95 percent confidence
interval of their equilibrium demand.
Indirectly, this offers evidence of a market where some
landlords adjust by charging key money and reducing the quantity of
housing services, and other landlords adjust by rehabilitating their
units. It is not consistent with other evidence, however, which suggests
that far fewer than a third of rental units have undergone large upgrades
which would permit revaluation of the unit.
A strong prima facie case can be made that rent control
decreases mobility because the median length of tenure for renters--13
years--far exceeds that in other markets.  For comparison, the median
length of tenure for renters in U.S. markets is typically one to three
years. The preliminary analysis in Chapter 2 also indicated that at least



- 34 -
some renters spend considerable amounts of money maintaining and upgrading
their units. However, estimation of a preliminary behavioral move/upgrade
model does not provide much information about what causes people to change
consumption.
Complementary research has been undertaken in collaboration with
the Indian Institute of Management, Bangalore. Tewari and Kumar describe
the quite complex set of rent control laws and practices,-and their
historical and institutional setting. An interesting feature of the
Bangalore regime is that tenants are allocated by the rent controller to
newly vacant units. Currently the costs and benefits of the rent control
regime are being estimated in the Olsen framework described above. Those
results will be presented in a forthcoming joint paper by the Institute
and the Bank (Tewari and Malpezzi, forthcoming).
Synthesis of these results from Cairo and BangalQre, as well as
some results from Ghana, can be found in Malpezzi (1984b). This paper
will be revised as additional results are produced this fall, and it
serves as a model for the cross-country comparisons to be undertaken in
this project. In its present form, it highlights the differences in
outcomes from :rent control in several markets. For example, the standard
model of rent control predicts a halt in new construction following the
imposition of controls. In Ghana the standard model predicts quite well,
in the sense that the supply of new construction has ground to a halt by
the study period (1981). This was clearly not the case in Cairo, as has
been noted several times already. India seems to be somewhere between
these polar cases.
The Need for Additional Research
Most theoretical research to date has focused on analysis of a
simple price 'control without much reference to common methods of
adjustment of the controlled price. Two exceptions, by Arnott and by
Rydell et.al., suggest that the effects of different stylized laws can
vary drastically. The little empirical research which has been done has
been inconclusive as regards the effects of rent control on investment.
Research on benefits to tenants suggests that rent control yields very
small benefits when compared to its costs. There is no evidence that rent
control operates as an effective redistributive device, and rent control
seems to decrease household mobility.
This review of previous research demonstrates important
practical gaps in our knowledge about rent control. There are at least
three reasons for the proposed additional research. First, little is
known about the extent of rent control generally, and even less about the
prevalence of specific provisions of rent control laws, how they are
enforced, what related laws exist, and what market conditions are like in
controlled markets. The first task is designed to fill this gap.
Second, few econometric studies have been done anywhere of the
costs and benefits of rent control laws, and only two in developing
countries. Even less has been done on estimating supply side impacts, and
the effects of rent control on public finance, household mobility, tenure
choice, and the labor market. The second task aims to expand the
available knowledge dramatically.



- 35 -
Third, research done to date has not integrated estimates of
gains and losses from different impacts, or considered the interests of
all agents in a consistent (i.e. accounting) framework. The third task is
designed to integrate results from household cost-benefit studies,
aggregate effects on supply, changes in mobility and taxes, etc., and
clearly identify the gains and losses to different agents (landlords,
tenants, governments, and deadweight losses). The synthe-sis of case study
results will also yield the first systematic look at alternative methods
of decontrol to be firmly grounded in a consistent model with behavioral
foundations and based on actual empirical results.



C;4
fit
Nl
I.                                                             I
II
I   I                                       (



37
III. RESEARCH DESIGN
-Overview
The purpose of this chapter is to explain the research design in
more detail. The preceding chapter has emphasized that only a few studies
have attempted to study the effects of real world rent control regimes;
fewer still have presented empirical estimates of the costs and benefits
of these regimes. To reiterate, the purpose of the research project is to
study real world regimes as enforced, under different market conditions.
To this end, we propose three interrelated tasks: (1) survey rent control
laws, enforcement practices, related laws, and market conditiofis in many
urban housing-markets; (2) carry out detailed case studies in several
markets, including the costs and benefits to tenants, and the effects of
different regimes on housing supply from new construction and the existing
stock; (3) use an integrated cost-benefit model based on case study
results to develop guidelines for the most important and desirable
changes, by studying the effects of changes in the rent control regime
under different market conditions, and studying optimal decontrol
strategies.
First, each of these three tasks will be discussed in turn.
Next, the interrelationships among these tasks will be explicitly laid
out. Finally, a plan will be proposed for the fourth task, the
dissemination of results from the research project.
Task 1: Survey of Rent Control Laws as Written and as Enforced
Key Features of Rent Control Laws
The purpose of rent control laws is to limit the rate at which
rents increase. The market consequences of any rent control law depend on
how broadly and deeply they cut that rate of increase. Below, we identify
the key features of rent control laws and note how choices about each
affect the breadth and depth of the implied rent reductions.
Any rent control law can be well characterized by the
answers to five questions.
o How long has/will the law be in effect?
o What is the coverage of the law--which dwellings are subject
to it, which are exempt?
o What rent increases are permitted for continuing tenants--that
is, if a dwelling does not turn over, how much can the
landlord raise the current tenant's rent?
o How much can landlords raise rents when their dwellings do
turn over?
o Under what circumstances does a dwelling become permanently
decontrolled?



- 38 -
The range of answers to those questions can be arrayed so that
the potential effects of the law for the housing stock range from trivial
to severe. Laws of longer duration have more severe effects on the
housing stock--longer durations imply greater rent reductions, which
reduce a landlord's cash flow and increase incentive to undermaintain his
property. Table 3 illustrates the variation in four important details of
rent control laws in six markets.
Three key local economic factors condition how rent control
would affect a locality's housing market:
O How tight is the local housing market--that is, what is the
demand for rental housing relative to the supply?
o Do current housing market conditions reflect long-term
trends, or are they aberrant?
O How much background price inflation is there?--when inflation
is driving up all prices, there will be pressure for rents to
follow.
As with the terms of rent control laws, the economic conditions
can be arrayed so that the potential effects of rent control on the
housing stock range from trivial to severe. Very tight market conditions,
signaled by correspondingly low vacancy rates, may arise from recent
surges in demand or from recent increases in producers real costs of
providing housing services. In either case, rent controls imposed in
tight markets will have more severe effects on the housing market than if
the market were loose. In the absence of rent controls, tight markets are
characterized by rising real rents and loose markets by stable or falling
real rents. Consequently, in tight markets rent controls will have
considerable bite, while in loose markets they may not.
If current low vacancy rates reflect only a temporary surge in
demand (as, say, in an isolated area during a major construction project,
or hosting a large temporary event like the Olympic games) or a sudden
unanticipated loss of supply (as, say, after a natural disaster), rent
controls may hold down rents without much affecting housing production or
maintenance. But if current low vacancy rates reflect economic conditions
which are likely to persist over time, especially recent population
increases which are expected to continue, then rent controls may indeed
short circuit housing production or maintenance.
When the prices of all goods and services are rising, rents will
tend to follow, even in relatively loose housing markets. The stronger
this pressure from background price inflation, the more severely rent
controls press downward on real rents--and consequently the greater impact
the laws have on the workings of the housing market.



- 39 -
Table 3
Comparison of Rent Control Laws for Several Markets
Approximate                           Rent                  Rent
Duration of                        Adjustments           Adjustments
Jurlsdtction            Current Regime      Coverage           Over Time         for New Tenants
Bangalore, India           24 years     All rental hous-        Frozen        "Fair rent" remains
Ing except very                      fixed; rent can de-
low income                           cine because exist-
(<15 rs/mo) and                      Ing controlled units
new construction                     can come under law
(<5 years)                            Wien tenant changes
Cairo, Egypt               23 years     All rental hous-        Frozen        Nb legal adjustment;
Ing except fur-                      key money changed
nished luxury
market
Goteborg, S eden           17 years     All rental units    Rent changes      Nbne
negotlated
betieem land-
lord and tenant
Kumasl, Ghana              22 years      Single-family      Frozen            Nbne
(high cost)
units exempted
Los Angeles,
California                 7 years      Rental units        Annual increass   Unit decontrolled
pre-1978; new      permitted; tied
construction,      to general price
luxury and         Index
single family
exem,pt
Ontario, Canada           9 years       Luxury units        Fixed percentage
and new con-       each year; some
struction          exemptions for
exempt             cost
Source: Pre-Test of Rent Control Checklist, Annex I.



- 40 -
The second objective of the broad survey will be to survey the
rent controlled cities, as well as a representative sample of cities
without rent controls, to explore how much variation there is in these key
market conditions.
Rent Control and Property Taxes
The relationship between current controls and property taxes is
decribed in the case study section, below. Here, merely note that the
survey will garner information on several key details of the property tax
laws and administrative practices, including methods and frequency of
assessments. e
Survey Execution
Task 1 of the research project is to survey laws as written and
enforced, and to survey market conditions, as widely as possible within
given resources. In addition to yielding important general information
about the scope of rent control laws and practices, the survey will also
feed into Tasks 2 and 3. The survey will ensure that the case studies
chosen represent a broad spectrum of actual rent control regimes and
market conditions (Task 2). In addition, they will be used to develop a
taxonomy, or several stylized rent control regimes, which will be studied
in the modeling effort which integrates the case study results (Task 3).
The survey will revolve around a questionnaire, or checklist,
designed to elicit essential information on each market surveyed. The
unit of observation for the Task 1 survey is the market or, roughly the
city. A draft checklist is included in the proposal as Annex I. The
draft is already being pretested in several markets. The checklist will
be completed by experts on individual markets, and checked against
published statistics and other sources to the extent possible. The
desired coverage is broad: we would like to gather information about at
least one important market in every country. Such broad coverage is
ambitious but not unrealistic. Even partially completed questionnaires
will yield useful information on the scope of rent controls. Of course,
in many countries several markets will be surveyed, and in some countries
several experts will be asked to prepare responses for the same market, in
order to examine the consistence of responses. This implies two to three
hundred surveys will be sent out. Data from the chetklists will be
verified and entered into a microcomputer database for analysis, but the
questionnaire is also designed to elicit comments and sources of
additional information, which will be studied carefully.
The key to the success of the survey is follow-up. The follow-
up on the questionnaire will emphasize (1) complete coverage of the
world's major cities, and (2) learning at a minimum which countries have
widespread controls and which do not. Preliminary analysis of survey
results can be undertaken as they come in, providing essential background
information for the case study analysis plans, and for designing the
simulation model. Approximately six months into the survey effort, a
preliminary working draft will summarize key findings from the survey, and



41
identify problem areas which need more follow up. For example, it is
quite likely that the property tax questions will have a high initial
nonresponse rate, requiring more-follow up (see Part III of the draft
checklist in Annex II). Approximately one year into--the project a revised
summary of the survey results will be produced.
Task 2:  Case Studies of Selected Markets
This section of the proposal will briefly describe three aspects
of the proposed case studies: the design of the case studies, the outputs
from case studies, and the choice of markets to be studied.
Case Study Design
t   Each case study will be tailored to the particular market under
study; after all, a maintained hypothesis of the project is that local
conditions matter,-and are in fact the focus of the study. Still, each
case study will contain a set of core elements:
1. An institutional analysis of the rent control acts and
enforcement mechanisms
2. A literature review of previous housing market research in
that market, with emphasis on rent control
3. Describe important features of the market, including recent
price behavior, population change, income changes, vacancy
rates, new construction, and the role of the informal
sector. This will include an explicit evaluation of the
quality and usefulness of the data
4. Where time series data permit, relate variation in the
above measures to the introduction and major changes in
rent control laws and enforcement practices
5. Estimate the effects of rent control on housing expendi-
tures, using household survey data
6. Estimate the costs and benefits of rent control based on
consumer's surplus and cash equivalent value models,
similar to that of Olsen (1973)
7. Estimate the distributive impacts of rent control, using
these cost/benefit estimates
8. Based on interviews with local experts, provide recommen-
dations on the most feasible methods of decontrol or
modification of the current law
9. Estimate the effects of the current regime on property tax
revenue



42
The actual design of the case studies will be set out in an
analysis plan which will be developed by each case study team. A
companion discussion paper has been drafted which provides much more
detailed guidelines for the case studies. This will-ensure that all core
areas are adequately treated, that results will be as comparable as
possible across case studies, and that the case studies generate the
information needed for Task 3.
Each case study will go beyond the core questions, to take
advantage of particular features of available data. For example, in
Cairo, the project will produce econometric estimates of the effects of
rent control on household location, mobility and tenure choice. However,
a set of simple models will also be estimated, so that they may be
compared (1) to more complete models from the same market, in order to
judge their reliability, and (2) across markets and hence across type of
rent control regime and market conditions. Table 4 summarizes the
proposed case studies.
Choice of Case Study Markets
Two principles guide the choice of markets for study: obtaining
needed variation in rent control regimes and market conditions (a
benefit), and data availability and timing (a cost). Fortunately a number
of high quality data sets are available for analysis, and they represent a
good cross-section of rent control laws and market conditions (see Table
2, above). Phase One will include five case study markets. Table 5
presents some information on the four markets which have already been
chosen on Cairo, Egypt; Kumasi, Ghana; Bangalore, India; and Harare,
Zimbabwe. Note that we have been fortunate to acquire data from markets
with reasonable variation in the types of rent control regimes in place,
and in maAket conditions. Primary responsibility for the Egyptian case
study will rest with Stephen Malpezzi and other project staff at the Bank;
the Ghana case study will be undertaken by Graham Tipple and Ken Willis of
the University of Newcastle upon Tyne; Vinod Tewari of the Indian
Institute of Management (Bangalore) is in charge of the Bangalore study;
and Marja Hoek Smit, Peter Linneman, and Joseph Gyourko will carry out the
Phase One research on Zimbabwe.
An additional case study will be developed. A high priority is
being given to locating a market which has undergone decontrol or a
significant relaxation of controls. Several possibilities are being
explored, including several Latin American cities. The broad survey of
housing markets (Task 1) will be used to develop a taxonomy of rent
control regimes, and this taxonomy will be used to decide whether any
additional case studies will be required in Phase Two of the project.
Three areas for potential collaboration between the Bank and
other research organizations have been identified. First, the Indian
Institute of Management, Bangalore will collaborate in additional research
on the interaction between rent controls and property taxes in India.
Seconrd, the National Planning Office of Hungary is interested in doing a
study of the costs and benefits of their administered housing system which
will follow our case study format. This collaboration could yield



43
Table 4: List of Phase One Case Study Markets
Country                       Current Status
Egypt           Data in hand. Descriptive statistics and
(Cairo)         cost/benefit model complete.  Additional
work to be undertaken on location/mobility
and tenure choice.
Ghana           Data in hand.  Additional household
(Kumasi)        survey and supply data to be collected.
India           Institutional analysis completed.
(Bangalore)     Descriptive statistics and cost/
benefit model forthcoming.
Additional work to be done on
property taxes.
Zimbabwe        Data in hand.
(Harare)
Additional      To be chosen; prefer a market with
Case Study      a history of decontrol, perhaps
Market          in Latin America.
Hungary         Data has been collected by Hungary's
National Planning Office. They wilL
undertake the case study using their
own resources.
United Kingdom  Specific case study opportunities
are now being identified. Case
studies will be carried out and
financed by the Centre for Housing
Research.



- 44
Table 5:  Interaction Between Market Conditions and Rent Controlf
(Phase One) Case Study Market
Treatment of New
Rent Adjustment               Construction
Inflation     Indexed       Frozen         Relaxed     Strict
High                        Egypt           Egypt       Ghana
Ghana
Moderate      Zimbabwe      India           Inidia    Zimbabwe
Additional Comments on Case Study Markets
Cairo, Egypt      Excellent data on location, mobility, key
money. High rate of new construction observed.
Kumasi, Ghana     Very high inflation, strict rent control regime.
Have some data over time.
Bangalore, India Good data from one market already (Bangalore).
Rent controls vary markedly from one city to
another, so other markets may be included.
Keen interest in property tax issue.
Harare, Zimbabwe  Strict law but relatively low inflation. Some
adjustment in rents has been permitted.



- 45 -
interesting insights on the effects of administered housing prices in a
mixed economy where the housing sector is largely centrally planned.
Third, the Centre for Housing Research of the University of Glasgow is
interested in carrying out case studies of the U.K. and possibly other
European markets. Note that the research at Hungary'-s'Central Planning
office and the University of Glasgow requires no Bank resources.
Data Collection
The guiding pr.inciple of data collection in this project is to
rely on existing data as much as possible. Much of the data to be used
was gathered or generated during the earlier states of RPO 672-46, Housing
Demand and Finance in Developing Countries. For that study we assembled
high quality household level data sets from eight countries. Additional
data from Kenya are about to come "on line." The philosophy during that
project and during this project is to exploit available opportunities to
develop new data sets when they exist at a modest cost, developing a "data
pipeline." For example, during RPO 672-46 the project designed data
collection efforts for two governments (Korea and Kenya), and funded a
survey in Manila, the Philippines. The Bank (and the countries) received
three high quality data sets at a total cost to the project of three trips
and $10,000.
There are several compelling reasons to continue modest data
collection activities during this research project. First, only three of
the eight countries from the earlier project have enforced rent controls,
making generalization difficult. Second, in one of the countries (Ghana)
an opportunity exists to colrect improved data and data from two time
periods, enabling estimates of dynamic effects of controls. Third, data
collection in new countries allow us to tailor the questions asked, e.g.,
obtaining information on landlord and tenant maintenance, key money, etc.,
which are not. available in many housing surveys. Fourth, in any cross-
country study of this general scale the gains from increasing the "degrees
of freedom" can be great. Fifth, the new household data will be collected
from Ghana, and other existing data is being assembled from Zimbabwe,
enabling the project to analy7 African housing markets in more detail
than has ever been possible.11- There is a felt need for such analysis.
For example, in his comment on this proposed project the Division Chief of
West Africa Urban Projects stated:
I hope in formulating any proposal for research, you will focus
attention on African case studies.., there is need for research at
all levels... [and] ...there is some evidence that work in Africa
has a greater chance of influencing decision makers.
11/ Data will be collected from other countries to improve calibration of
the cross country demand model, results from which will be used as
inputs to this study.



- 46 -
With data from Ghana and Zimbabwe this project can respond to this
concern. Most of the household survey data required for the cost-benefit
analysis is already in hand and ready for computer analysis. Ghana is the
exception. A household survey from Kumasi is in hand, which was collected
by Graham Tipple in 1981. Anecdotal evidence suggests that given the
freeze in controlled rents since that time, despite rapid general price
inflation, a re-survey of those households would yield valuable
information on the dynamics of the market, including changing key money
practices. The re-survey has just been carried out by the University of
Science and Technology (Kumasi), under the direction of Dr. Tipple.
In all of the case study markets additional collateral data will
be collected,'especially time series data such as starts, vacancy rates,
and other aggregate supply measures, where available. These are
especially important in studying lags in supply side responses to changes
in rent regulation where possible.
In addition, a key piece of information for each case study is
what quantity of housing each sample household would consume in the
absence of rent controls. The cross-country model of Malpezzi and Mayo
(1985, Ch. 3) will be extended, using more countries and an improved
specification, including a better price term. This improved cross-country
model will be estimated by project staff using inputs from each case study
market, the 15 cities studied in Malpezzi and Mayo, and data from
additional cities as available. Doubling or tripling the degrees of
freedom, and improving the specification, will permit improved imputation
of long-run competitive rents for case study households. In some markets
these will serve as a check for other methods of imputation; in a few
markets they may be the primary method of imputation. In addition, the
improved precision of the cross-country estimates will have an important
spillover effect, as these estimates are currently being used to evaluate
past Bank shelter projects and improve the design of current projects (see
The Urban Edge, 1985).
Outputs
A separate report will be produced for each market studied,
integrating findings on the nine topics just enumerated. In addition, the
project will produce a final summary report which will compare results
across case study markets, with special emphasis on relating the outcomes
(elements 5,6,7 and 9, above) to market conditions and variation in the
laws (elements 1 and 2).
Task 3: Integrating Case Study Results in A
Consistent Housing Market Model
Introduction
The proposed model will estimate the benefits and costs of
relaxing or ending rent control of a given type in a given situation. All
parts of this statement of purpose are important. Any change in rent
control confers both benefits and costs on a variety of interest groups--a



- 47 -
change i! never unambiguously good or unambiguously bad. Alternative ways
to relo-/ rent control should be considered along with alternative ways
to end- rent control because relaxation might reap much of the benefits
of decontrol but incur only a fr'action of the cost. Finally, the result
of any change in rent control depends upon the nature of the law being
revised and the socioeconomic circumstances in which the law exists--for
example, removing controls that have frozen rents in a city with a growing
population will have very different effects than removing controls that
have allowed rents to increase with inflation in a city with a shrinking
population.
Before building such a model, it is useful to speculAte on what
answers it will yield. In this instance, many qualitative results are
easy to predict. Relaxing or ending rent control will (a) increase the
amount of housing services in a housing market, (b) increase landlord
profits, (c) increase government revenue from property taxes, and (d) hurt
some tenants in the short run and help many if not all tenants in the long
run.
Housing services from the existing housing stock will increase
because the restoration of market incentives will induce landlords to
in-croase housing maintenance and to decrease the removal rate of old
housing. Housing services from new housing stock will increase because
housing development will be more profitable. Equally important, the
proportion of new housing that is non-luxury will increase.
Landlord profits will increase for the obvious reason that rents
go up. However, they will also increase for the less obvious reason that
in the absence of rent controls, landlords can operate their properties in
the most economically efficient way. For example, a $1000 improvement
might have a market value of $1100 (in discounted rent increases), but it
would be made only if the necessary rent increases are allowed.
Government revenue from property taxes will increase, assuming--
as is usually the case--that property taxes are related to real estate
profitability. However, the amount and timing of the increased revenue
will depend on the specifics of the tax law as well as on the specifics of
the rent control law.
Tenants enjoying rent bargains under rent control will obviously
be hurt in the short run when those bargains are reduced or eliminated.
However, if rent control has existed for a long time, deterioration due
to undermaintenance may have reduced housing quality to the point where
market rent is not much greater than controlled rent. In other words,
there might not be much of a bargain left for tenants to regret losing.
In the longer run, absent rent controls, tenants will be free to adjust
1/   Examples of ways to relax rent control are (a) indexing rents to
price inflation and (b) temporary vacancy decontrol.
2/   Examples of ways to end rent control are (a) immediate repeal and (b)
permanent vacancy decontrol.



- 48 -
their housing consumption and their residential location as their
household composition and job location change. No longer will they have
to suffer the disutility of a wrong size apartment or a lengthy commute in
order to hang on to their rent control bargain. -0
The proposed model will make quantitative estimates of these
qualitative effects. It will show which are larger and which are smaller
under alternative modifications of rent control in a giveh situation.
Modeling Strategy
Model construction will be guided by three principles. First,
we will develop a "complete" perspective. All interests--housing,
landlords, tenants, and government--will be included and analyzed
consistently, and we will use double entry accounting to enforce
consistency. For example, the rent increase paid by tenants will be
explicitly related to the revenue increase enjoyed by landlords, taking
into account the effect of vacancy rate adjustments. Second, we will
build "portable" submodels. For examplet although the effect of rent
control on rent *is dependent upon the specific rent control law and market
situation, the effect of rent reduction on housing maintenance is
presumably similar in all cases. Finally, we will look for "robust"
conclusions. Uncertain estimates will be bounded by high-low estimates
that can be made with confidence, and attention will be directed to those
conclusions that are valid no matter where in the high-low range the true
result lies.
Equally important, the model will be constructed with an
appropriate degree of modesty. We are attempting a generally applicable
model of rent control's impacts not because we think that the state-of-
the-art of housing market analysis makes an excellent model possible, but
rather because we believe that even a moderately successful model will be
of great value when making rent control decisions. Even if the model does
no more than credibly distinguish between places where rent control has
major effects and where it has only minor effects, the model will justify
the resources devoted to its construction.
Overview of the Model
The broadest perspective on the model emphasizes the necessity
of starting with a precise definition of the proposed change in rent
control, and the necessity of ending with interpretation, evaluation and
(possibly) judgmental modification of model out--rtt. Any model is only a
tool that in knowledgeable hands can be useful. Without careful, critica]
use, the model will be worse than useless.
An overview of the model is provided by Figure 4. Rent control
laws will be defined by the rent increase allowed for dwellings having no
change in tenant9 and the annual change in rent allowed for dwellings that
do have a change in tenant. The demand for and supply of housing in a
market will be assessed inter alia by population growth rates and new
construction rates, The property tax law will be analyzed to find the
relationship between taxes and rent, and the timing of how taxes adjust to



- 49 -
changes in rents. Finally, household characteristics, such as the
frequency of moves by demographically defined household types, and the
rate of household formation and dissolution by household type will be
necessary to completely assess the effect of rent control on tenants.
The housing services output category includes assessment of
dwelling quality (as affected by landlord maintenance decision) as well as
the number of dwellings (as affected by rates of new construction and
demolition). Landlord profits are the present value of rental revenue
less expenses such as maintenance and property taxes. Government
objectives affected by rent control include property tax revenue, the cost
of administering the controls, gross domestic product (as influenced by
the construction industry), and foreign exchange (again as influenced by
the construction industry). Finally, tenant benefits include rent
reductions as partially offset by declines in housing quality, and the
disutility of dwellings that have inappropriate characteristics or
inappropriate locations for the current household composition or job.
We will measure the disutility of consumption distortions by the
amount of extra income that would just compensate the tenants for the
nonoptimal dwelling characteristics and/or location.
Figures 5 through 8 outline the core of the model by tracing how
inputs flow into submodels and how the submodels lead to outputs. Figure
5 shows the effect on housing services. The rent control law determines
controlled rents, and demand for and supply of housing determines what
rents would be if there were no control. Together, those inputs determine
the change in rents caused by rent control. That rent change, in turn,
determines landlord decisions on maintenance and developer decisions on
new construction and demolition. Figure 6 shows the effect on landlord
profits by adding the influence of the property tax law to the components
in Figure 4. Figure 7 shows that the effect on government objectives
flows from changes in taxes and changes in the quantity of housing (from
which the effects on the construction industry and hence gross domestic
product and foreign exchange will estimated).
Finally, Figure 8 shows the effect on tenants. This is the most
complex chain of logic in the model. There are three fundamentally
different sources of tenant benefits (or costs). First, rent control
increases tenant well being by guaranteeing secure tenure to a greater
degree than any lease agreement, and by greatly reducing uncertainty about
future rents. Second, rent control reduces the price paid per unit of
housing services (by reducing rents less than housing quality is reduced
by undermaintenance). Third, rent control causes distortions in housing
consumption as tenants move less frequently in order to hang onto their
rent control bargain.
This model will be an extension of the model constructed by
Rydell et al. (1981) for the city of Los Angeles. The model will be
parameterized using data generated by the case studies. Table 6
summarizes some of key inputs. The model will ensure that costs and
benefits to all agents (landlords, tenants, homeowners, governments) will
be consistently analyzed. The modeling effort will produce a set of
simulations of the market effects of different methods of decontrol under



- 50
Fig. 4--Overall structure of the model
Rent                                          Housing
Control                                        Services
Law
Demand      --                                 Landlord
Core of                Profits
Model
Property                                       Government
Tax
Law                                       |Objectives
Household                                      Tenant
Characteristic1                                  Benefits



51 -
Fig. 5--Effect on housing services
Rent           1      Change
Rent              ~~inHosn
Control                                       Services
Law           l_l
I          I         I
Demand               Changes
and       - .J     in Quantity   -
Supply              and Price
I _____________.-____________________________



- 52-
Fige 6-Effect on landlord profi-ts
Rent           -Change
Control             Iini
Law                      Rents
l           l
Demand            l       Changes                   Landlord
and                    in Quantity       r -       Profits
Supply                   and Price'
-LI-               I
Property                    Change
Tax                         in
Law                       Prof its



-53    .
Fig. 7-Effect on government object'ires
Rent      J       -.       Change
Control                       in
Law                      Rents
I           II
DemandChange
supply~                       and
.nd         ...~        in Quantity
Price
Property     -              Change          Wo;ernment
LProfits Lr                                      j Objectives
Change
Taxes       F
p,-.-,,



- 54 -
Fig. 8-Effect on tenant benefits
Security
of
- -    -       Tenure
Rent                                       I
Concrol
Law-      ---
.T           Change
in
Rents
Demand       --I
and           T
Supply                      Change      It
in Quantit     -
and Price'
Change
in             I
Mobility           I
I            I
I           I I
Household                            . -       -
haracteristic               Consumption       Lenant
vhrc  el tCSDistortion              -        -   Benefitcs
- -



- 55 -
alternative market conditions and alternative laws. The report on this
task will document and explain the model but, most importantly, it will
present outcomes from different situations in a format which will assist
in the evaluation of different rent control systems and proposals for
changes in those systems. These results will also be important inputs to
the synthesis paper described below.
Task 4: Dissemination of Research Results
Much of the dissemination of research results between now and
April 1987 will consist of written reports. Table 7 presents a proposed
list of project outputs.  Each of the three analytical tasks (survey, case
studies, and integrated model) will produce written outputs which will
stand on their own. An interim report will be written at the end of Phase
One which will synthesize the results from Phase One case studies and the
broad descriptive survey. The report will serve as the basis for a
detailed proposal for Phase Two of the project.
In addition to these papers, the following specific
dissemination activities are planned. A final synthesis paper will be
written which describes the results of the research in nontechnical terms,
and which will present they key results in a manner accessible to project
officers in the Bank and our client governments. This paper will be
submltted to the World Bank Economic Review. The project final report
will be an edited compilation of results from all three tasks plus the
synthesis. This volume will be submitted to the Publication Committee of
the Bank.  The synthesis paper will also be used as the main background
reading for a workshop on the results to be given to Bank staff at the
completion of the project. The workshop will mark the beginning of an
additional effort, funded by the Water Supply and Urban Development
Department, to widely solicit the views of Bank staff and management, in
light of the research findings, on what the Bank's strategy on rent
control should be. This strategy paper--and indeed the process of writing
that paper--are an additional key dissemination activity for project staff
which will be undertaken upon the completion of the project. Its costs
will be borne by the Water Supply and Urban Development Department.



56
Table 6
Key Model Inputs From Case Studies
I.     Rent Control and Related Laws
-  coverage                           treatment of new tenants
-  enforcement                    -   tenant protection
-  rent indexation                -   property tax provisions
-  treatment of new construction  -    other related taxes
II.    Market Conditions
-  rental '`tarket share          -   background inflation
-  demographic changes            -   real growth
-  level of.development           -   rate of new constructin/
demolition
III.   Households
-  observed rents                     mobility rates
-  estimated equilibrium rents         incomes
IV.    Structures
-  observed rents                 -    age of structures
-  estimated equilibrium rents    -    structure type
V.     Supply Side
- market responsiveness           -    rate of new construction
-  depreciation (net and gross)   -   maintenance



- 57
Table 7
Project Outputs
Output                                   Form
Survey of Rent Control                  Discussion Paper
Laws and Enforcement
Practices
Extension of Cross-                     Discussion Paper
Country Housing Demand
Model
Case Studies of                         Discussion Paper
Inditidual Markets                       Study for Each Case
(Egypt, Ghana, India,
Zimbabwe, additional
Case Study)
Integrated Cost-                        Computer Software;
Benefit Accounting                      Report Documenting
Model                                    Model and Selected
Results
Synthesis Paper                          Submit to World Bank
Economic Review
Project Final Report                     Edited Volume of Survey.
Case Studies, Simulation
Results, submit to
Publication Committee
Project Workshop                         Bank-wide Seminar
Presented Key Findings
to Project Staff



r-
-1e      -



59
IV. ORGANIZATION
General Principles     --
This project's major goal is to produce research results on the
effects of rent control which will provide a sound guide for Bank and
client policies. To do this requires clear communication between
researchers and Bank operational staff, and other souces of information
such as local experts on particular markets. In fact such collaboration
has already begun; the views of operational staff, and of experts on
several rent control regimes, have been solicited during the proposal
writing process. Action has already been taken on several valuable
suggestions, e.g. highlighting the possible effects of rent control on
property tax revenues, aggregating cost and benefit estimates into macro
numbers more easily worked into sector work and other analysis, and
numerous suggestions on emphasis and presentation. From dissemination
activities of previous research on housing demand and finance, we have
identified several.operational staff members who have a strong interest in
this research, and have formed an advisory group. The survey (Task 1)
offers an excellent opportunity to identify additional Bank staff and
other interested parties who can continue to advise the research project
as intermediate results are written up and presented at informal seminars.
The research project will be the responsibility of the Water
Supply and Urban Development Department. Stephen Malpezzi will direct the
project, in collaboration with Stephen Mayo. They, along with a
consuLtant economist and a researcher, will form the core team who will
work on the project at Bank headquarters. The headquarters team will have
primary responsibility for (1) the survey of rent control laws and market
conditions, (2) the management of the case studies, (3) the execution of
some of the case studies, (4) the integrated modeling effort, and (5)
synthesizing results in a final Bank report, and (6) disseminating those
results.
The case studies will be performed by teams of researchers
familiar with the markets under study, and with the data to be used.
Table 4 in Chapter 3, above, listed the proposed case studies and the
corresponding consultants. Each team will prepare an analysis plan, as
described above under Task 2, consistent with this framework and with
Malpezzi and Mayo (1986). The case studies will cover the core areas
described above, and will provide inputs to the model used to study
alternative methods of decontrol.
The integrated model (Task 3) will be developed in Phase Two of
the project. It will be written in a portable microcomputer language
which will allow research project staff to run additional simulations as
necessary to study actual policy situations.



- 60 -
Links to Other Bank-Funded Research
As mentioned above, this proposed research project builds upon
earlier research on housing markets conducted under R.PO 672-46, Housing
Demand and Finance in Developing Countries. The Department staff
responsible for that project are also responsible for the proposed
project. Summaries of that project can be found in Mayo et.al. (1986) and
in The Urban Edge (1985).
It is worth noting that the proposed research project will have
significant spillover effects. For example, one of the major products of
the earlier housing demand research project is a model which predicts
housing consurhption at different income levels within cities at different
levels of development (Malpezzi and Mayo 1985). The model has been
parameterized using data from 15 cities in 8 developing countries, and is
used to estimate improved "affordability ratios" for urban.shelter
projects. Data being collected for this research project will permit
doubling the number of countries used to fit the model at almost zero
marginal cost0 If.improved forecasts from this model make a single urban
project, say, 10 percent more efficient because of better pricing
policies, this proposed project will have paid for itself several times
over from a spillover effect. Results from the rent control research
project will also provide insights on the value placed on different tenure
types, housing finance, the spatial character of urban labor market, and
other related issues.
The Work Program, and Proposed Timing
The activities proposed for Phase One of this project will take
place over a period of 12 months, beginning in July 1986. The approximate
timing of principal activities is indicated in Table 6. Work will be
initiated in July with the launch of the Task 1 survey effort, data
collection from Kumasi, and the preparation of analysis plans for the case
studies. The extension of the cross-country demand model will begin
shortly thereafter.
After the Task 1 survey and the case study results are described
in individual papers, a project interim report will be written which will
describe these results, and serve as the basis for Phase Two (additional
case studies if required; integrated model and study of decontrol options;
and final report). Table 8 also contains a tentative schedule for Phase
Two research.



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Table 8: WORK SCHEDULE
Calendar Year           1986              1987                                 1988
Month           J A   S O   N D   J F   M  A M   J J A    S O    N D   J F M    A M   J
Flscal Year          FY87                                 FY88-.
PHASE ONE
Survey Rent Control Laws
Complete pretest and    *       *
begin survey
Tabulate resurts and w-ite       *          *
preliminary report
Follow up and Irte report                 *          *
Case Studies
Prepare analysis plans *      *
Revise cross-country    *            *
demand model
Household Survey       *       *
(Kumasi)
Execute case studies             *                    *
DTssemtnation
Prepare Interim                                    *        *
Report
Submit Phase 11
Proposal                                                 *
PHASE TWO
Case Studies                                              *
(if Required)
Integrate Case Studies and
Simulate Oecontrol
Preliminary sketch           Completed
Destgn and calibrate Model                                *                 *
Draft report                                                            *               *
Disneilnation
Nbn Technical Synthesis
Paper (Final Report)
Edlted Book of Case Studles                                                                   *
and Other Results



I A
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h k
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ANNEX
DRAFT
RENT CONTROL CHECKLIST
Return to:
Stephen Malpezzi
Room N-859
Water Supply and Urban Development Department
The World Bank
1818 H Street, N. W.
Washington, D. C.  20433    U.S.A.
Telephone: (202) 676-1351
The "market'" will usually correspond to a city or metropolitan area. If not,
please explain. If market is currently controlled, answer all questions. If
not controlled, answer questions 1 to 9, 28 to 33, and 35 to 38. If neces-
sary, use best guesses so that as many questions as possible are answered, but
put an asterisk (*) beside answers that may well be wrong. Place comments in
margin where appropriate.   Elaborate on a separate sheet if necessary. If a
question requests an interval answer, but you happen to know a more precise
figure, check off the interval and write the figure in the margin.
Market (city): *     _-_--
Country:
Submitted by: __.
I.    Market Conditions
1.    Population
Less than 500,000
500,000 to 2,000,000
More than 2,000,000
2.    Annual population growth rate
Less than 2 percent
2 to 5 percent
Over 5 percent
3.    Per capita income in 1984 U.S. dollars for (check
one)  -  city/market or      country
Less than 500
500 to 1,500
1,501 to 5,000
Over 5,000



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4.    Rate of general price inflation, average over last 5
years
Less than 10 percent per annum
10 to 20 percent
Greater than 20 percent per annum
5.    Proportion of all housing that is private rental
1/3 or less
__   2/3 or less (but more than 1/3)
Over 2/3
6.   Proportion of all housing that is public sector or
directly subsidized
Less than 5 percent
5 to 15 percent
More than 15 percent
7.   Relationship between new construction and population
growth over last five years
Housing starts have more or less exceeded
population growth over the last 5 years
Housing starts and population growth have been
roughly in line
Starts have not kept up with population growth
8.   Current rental vacancy rates (including formal and
informal sectors)
Tight market (vacancy rate less than 3 percent)
Moderate (3 to 6 percent)
Loose market (greater than 6 percent)
9.   Are rents currently controlled in any significant
markets in this country?
Yes
No
Note: All questions which follow pertain to this
market, i.e. the place listed at the first line of
the form.
10.   Has this market been under rent control anytime
during the last 10 years?
Yes
No



- 65 -
II.   Details of Rent Control Law
11.   Is any part of the residential rental market
currently under rent control?
Yes (go to question 12)
=_   No (go to question 31)
12.   Is there any "sunset provision" or indication that
this law will be lifted or repealed at a specified
date or under some specified market condition?
-_   Yes (give details)
No
13.   Proportion of rental housing that is controlled
1/3 or less
2/3 or less (but more than 1/3)
Over 2/3
14.   Start of rent control
--_Before 1950
1950 to 1959
1960 to 1969
1970 to 1979
1980 or later
15.   Date when major features of current law were all in
place
Before 1950
1950 to 1959
1960 to 1969
1970 to 1979
1980 to later
16.   Please give a brief chronology of rent control laws.
17.   Are rent control laws perceived to be enforced?
Yes, vigorously (go to Q. 19)
Yes, but selectively
No



- 66 -
18.   If rent control laws are not vigorously enforced,
check off perceived reasons
Insufficient enforcement resources, court
backlog
Fines, penalties insufficient
Officials do not choose to enforce
19.   When current law was introduced, controlled rents
for existing stock were set at
Their current market rents
Repts - years previous (fill in blank)
Initial rent at time of construction
Percent of historical value at time of
construction (give percentage)
Percent of market (give percentage) when law
introduced
Other (describe briefly)
20.   Rent for sitting tenants
Rent frozen
Annual increase, less than general price
inflation
Full indexing to general price inflation
Rents determined by "rate of return" formula
Other (describe briefly)
21.   Initial rent for new tenants
--_ Same as for old tenant
New rent, but allowed increase is capped by an
administrative formula
.  Market rent
Other (describe briefly)
22.   Do monthly rents actually paid usually correspond to
legal rents for controlled units?
Yes, for most units
-_   Yes, but with significant exceptions (describe
briefly)
Rarely
23,   Is key money (initial lump-sum payment from new
tenant to landlord) widespread?
Yes, many tenants pay (more than 30 percent)
Some tenants pay key money (10-30 percent)
Not widespread (less than 10 percent)



- 67 -
24.   Do other forms of key money exist in this market?
Landlords pay sitting tenants to leave unit
New tenants have sometimes paid original
tenants to leave
Deposit of key money is sometimes (partially)
returned to tenants when they vacate
No
25.   Check off any legal grounds for evicting current
tenants
Nonpayment of rent
To upgrade unit
Owner takes personal possession of unit
Other legal grounds (describe)
No legal grounds for eviction
Eviction is not prohibited by law
26.   Treatment of new construction
Controlled, initial rent set below market rent
by administrative formula
Controlled, initial rent set at market rent
Not controlled
27.   Treatment of upgraded units
No change in controlled rent
New rent, but set below market rent
New rent set by market, but future increase
subject to controls
Unit no longer controlled
28.   Has a past promise, in a rent control law, to exempt
new construction ever been broken in this place?
Yes
No (go to Q. 30)
29.   If the answer to Q. 28 is yes, how many years passed
between the time the promise was made and when it
was broken?
Less than 5 years
5 to 15 years
Over 15 years
30.   Is the rent control currently scheduled to end at a
given date, or being phased out over time by some
mechanism such as permanent vacancy decontrol?
No
Yes



- 68 -
31.   Are commercial or agricultural properties subject to
rent control?
Yes, commercial properties
Yes, agricultural properties
Yes, both commercial and agricultural
properties
No (go to Q. 33)
32.   Are these controls enforced?
Yes, vigorously
Yep, but selectively or partly
No
33.   Check off any of the following laws which exist
(1) restrictions on sale of units
(2) land price controls
(3) restrictions on land transactions
(4) controls on building materials
None (go to Q. 35)
34.   Of the above laws which exist, circle the numbers of
those which are:
Vigorously enforced (1) (2) (3) (4)
Selectively or partly enforced (1) (2) (3) (4)
Not enforced         (1) (2) (3) (4)
III. Details of Property Tax Law
35.   Proportion of local government revenue (including
intergovernmental transfers) from property taxes
(residential and commercial)
Less than 20 percent
20 to 50 percent
Over 50 percent
36.   Assessments as a percentage of market value
Typically less than 20 percent
-- 20 - 50 percent of market value
50 - 80 percent
Over 80 percent



- 69 -
37.   Local mill rates (range) (a mill is one-one
thousandth of assessed value).
Less than 5 mills
5 to 10 mills
11 to 20 mills
21 to 30 mills
More than 30 mills
to      mills (fill in)
38.   Who (legally) pays taxes on rental units?
Landlords
Tenants
If the answer to Q. 11 was yes (part or all of the
residential rental market is controlled), answer
Q. 39. If the answer to Q. 11 was no (the resi-
dential market is uncontrolled), skip to Q. 40.
39.   Are residential assessments based on controlled
rents?
Yes, rental units only
Yes, both rental and owner-occupied units
No, market rents or values are basis of
assessments for both tenure types
40.   How often are residential units reassessed?
Every 5 years, or more often
Every 6 to 15 years
Rarely (more than 15 years, on average, between
assessments)
When properties are sold or exchanged
41.   Are commercial and/or agricultural assessments based
on controlled rents?
Yes, rental units only
Yes, both rental and owner-occupied units
No, market rents or values are basis for
assessments for both tenure types
Source of this information, person(s) or
document(s):
Potential sources of additional information:



- 70 -
Additional Comments:
r
I



- 71 -
REFERENCES
Albon, Robert. The Value of Tenancies Due to Rent Control in Post War New
South Wales. Australian Economic Papers, December 1979, pp. 222-228.
Arnault, Jane. Optimal Maintenance Under Rent Control with Quality
Constraints. AREUEA Journal, Summer 1975, pp. 67-82.
Arnott, Richard, with the assistance of Nigel Johnston. Rent Control and
Options for Decontrol in Ontario. Ontario Economic Council, 1981.
Bender, Bruce. The Determinants of Housing Demolition and Abandonment.
Southern&Economic Journal, 46, July 1979, pp. 131-144.
Block, Walter and Edgar Olsen. Rent Control: Myths and Realities.
Vancouver: The Fraser Institute, 1981.
Clark, W.A.V., and Allan D. Heskin. The Impact of Rent Control on Tenure
Discounts and.Residential Mobility. Land Economics, 58(1),
February 1982, pp. 109-117.
Dildine, Larry L. and Fred A. Massey. Dynamic Model of Private Incentives to
Housing Maintenance. Southern Economic Journal, 1974, pp. 631-639.
Fallis, George and Lawrence B. Smith. Uncontrolled Prices in a Controlled
Market: The Case of Rent Controls. American Economic Review, 74(1),
March 1984, pp. 193-201.
Frankena, Mark. Alternative Models of Rent Control. Urban Studies, 12, 1975,
pp. 303-308
Friedman, Milton, and George J. Stigler. Roofs or Ceilings? The Current
Housing Problem. In Block and Olsen (eds.)
Gilderbloom, John. Rent Control: A Source Book. Santa Barbara,
California: Foundation for National Progress, 1981.
Grampp, William D. Some Effects of Rent Control. Southern Economic Journal,
April 1950, pp. 425-447.
Grebler, Leo. Implications of Rent Control -- Experience in the United
States. International Labor Review, 65, April 1952, pp. 462-85.
Gyourko, Joseph and Peter Linneman. Equity and Efficiency Aspects of Rent
Control: An Empirical Study of New York City. Wharton School,
University of Pennsylvania. Mimeographed, 1985.
Hausman, Jerry A. Exact Consumer's Surplus and Deadweight Loss. American
Economic Review, 71(4), September 1981, pp. 662-675.
Kearl, J. R., Clayne Pope, Gordon Whiting, and Larry Wimmer. A Confusion of
Economists? American Economic Review, 69(2), 1979, pp. 28-37.



- 72 -
Kiefer, David. Housing Deterioration, Housing Codes and Rent Control. Urban
Studies, February 1980, 53-62e
Linneman, Peter. Income Distribution Effects on Renters of Rent Controls:
The Case of New York City. Wharton School, University of Pennsylvania.
Mimeographed, 1985.
Loikkanen, Heikkanen A. On Availability Discrimination Under Rent Control:
Scandinavian Journal of Economics, 87(3) 1985, 500-510.
Malpezzi, Stephen. Economic Analysis of Alternative Rent Control Policies,
With An Application to Cairo, Egypt. Paper delivered to -the Regional
Science Association, 1984a.
Malpezzi, Stephen. Rent Controls: An International Comparison. Paper
delivered to the American Real Estate and Urban Economics Association,
1984b.
Malpezzi, Stephen. Rent Control and Housing Market Equilibrium: Theory and
Evidence from Cairo, Egypt. Ph.D. Dissertation, The George Washington
University, 1986.
Malpezzi, Stephen and Stephen K. Mayo with David J. Gross. Housing Demand in
Developing Countries, World Bank, Staff Working Paper No. 733, 1985.
Malpezzi, Stephen, Larry Ozanne and Thomas Thibodeau. Characteristic Prices
of Housing in 59 SMSAS. Urban Institute Contract Report 1367-1, 1981.
Malpezzi, Stephen, Larry Ozanne, and Thomas Thibodeau. Microeconomic
Estimates of Housing Depreciation. Mimeographed, 1985.
Margolis, Stephen E. Depreciation and Maintenance of Houses. Land Economics,
February 1981, 57(1), pp. 91-105.
Marks, Denton. The Effect of Rent Control on the Price of Rental Housing: An
Hedonic Approach. Land Economics, 60(1), February 1984, pp. 81-94.
Mayo, Stephen K., and others. Informal Housing in Egypt, Abt Associates,
1982.
Mayo, Stephen K., Stephen Malpezzi, and David Gross. Shelter Strategies
for the Urban Poor in Developing Countries. World Bank Research
Observer, 1(2) 1986, pp. 183-203
Moorhouse, John C. Optimal Housing Maintenance Under Rent Control. Southern
Economic Journal, July 1972, 93-106.
Neary, J. P. and K.W.S. Roberts. The Theory of Household Behavior Under
Rationing. European Economic Review, January 1980, pp. 25-42.
Olsen, Edgar 0. The Effect of a Simple Rent Control Scheme in a Competitive
Housing Market, Rand Working Paper P-4257, December 1969.



- 73 -
Olsen, Edgar 0. An Econometric Analysis of Rent Control. Journal of
Political j'Economy, 1972, pp. 1081-1100.
Olsen, Edgar 0. A Competitive Theory of the Housing Market. American
Economic Review, 1969, pp. 612-622.
Paish, F. W. The Economics of Rent Restrictions. Lloyd's Bank Review, April
1950, pp. 1-17.
Rydell, Peter C. and Michael P. Murray. How Rent Control Affects Property
Taxes. Rand Corporation. Mimeographed (n.d.)
Rydell, C. Peter, and Kevin Neels. Rent Control, Undermaintenance, and
Housing Deterioration. Mimeographed, 1982.
Rydell, C. P., C. L. Barnett, C. E. Hillestad, M. P. Murray, K. Neels and
R. H. Sims. The Impact of Rent Control on the Los Angeles Housing
Market. Rand Note N-1747-LA, August 1981.
Schwab, Robert. The Estimation of the Benefits of In-Kind Government
Programs. Journal of Public Economics, forthcoming.
Skelley, Chris.  Rent Control:   A Contractual Approach.   Colloquium on Rent
Control, Lincoln Institute of Land Policy, 1983.
Tewari, Vinod K. and T. Krishna Kumar. Rent Control in India: Its Economic
Effects and Implementation in Bangalore. Indian Institute of
Management. Mimeographed, 1985.
Tewari, Vinod K. and Stephen Malpezzi. Costs and Benefits of Rent Control in
Bangalore, India, forthcoming.
Thibodeau, Thomas. Rent Regulation and the Market for Rental Housing
Services. Urban Institute Research Paper No. 3090-01, November 1981.
United Nations. Review of Rent Control in Developing Countries. Department
of Economic and Social Affairs, ST/ESA/85, 1979.
The Urban Edge. Rental Housing: A Rediscovered Priority. Vol. 8,
No. 2, February 1984.
The Urban Edge Making Shelter Projects Replicable. Vol. 9, No. 10,
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