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 This study reexamines the conventional claims made by economists and policy analysts concerning modern rent control. We look at 76 New Jersey rent-controlled cities over a 30-year period and pose questions about the impact of rent control on rents, number of rooms, quality of units, and new rental construction using the latest Census data on cities for 2000. Our study is a comprehensive empirical study of rent control using multiple regression as the primary form of analysis. We find the intended impacts of New Jersey rent control over a 30-year period seem minimal when you compare cities with and without regulations. Housing activists and policymakers need to look at new kinds of approaches to address rental affordability problems.
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University of Louisville
Roosevelt University
ABSTRACT: Thisstudyreexaminesthe conventional claims madeby economists and policy analysts
concerning modern rent control.We look at 76 New Jersey rent-controlled cities over a 30-year period
and pose questions about the impact of rent control on rents, number of rooms, quality of units, and
new rental construction using the latest Census data on cities for 2000. Our study is a comprehensive
empirical study of rent control using multiple regression as the primary form of analysis. We find the
intended impacts of New Jersey rent control over a 30-year period seem minimal when you compare
cities with and without regulations. Housing activists and policymakers need to look at new kinds of
approaches to address rental affordability problems.
Rent control as public policy has been in existence for over 2000 years. Historians have noted
that even before the birth of Christ, Julius Caesar enacted a form of rent control in Rome (Keating,
Teitz, & Skaburskis, 1998). In the last several decades, there have been various responses to this
policy. Some economists oppose rent control, arguing that it causes the quality and quantity of
the housing stock to fall (for example, Alston, Kearl, & Vaughan, 1992; Kearl, Pope, Whiting, &
Wimmer, 1979). Other economists suggest that a better way to create affordable housing is through
market-equilibrium pricing, especially in markets that are reasonably competitive (Arnott, 1995;
O’Sullivan, 2006).
This study attempts to look at modern-day rent control and reexamine the claims made by
economists and policy analysts. Our study looks at 76 New Jersey rent-controlled cities and poses
the following questions: Are rents significantly lower in rent-controlled cities when compared to
the other 85 non-rent-controlled cities? What has been the impact on the size and quality of the
rental unit? What has been the impact of new rental construction? The next section provides a
review of the literature on rent control.
Rent control has been a major type of government regulation of housing for many years (See,
for example, Epple, 1998; Gilderbloom, 1981a, 1981b; Gilderbloom and Appelbaum, 1988;
Direct Correspondence to: John I. Gilderbloom, School of Urban and Public Affairs, Center for Sustainable Urban
Neighborhoods, University of Louisville, 426 West Bloom Street, Louisville, KY 40208. E-mail:
JOURNAL OF URBAN AFFAIRS, Volume 29, Number 2, pages 207–220.
Copyright C
2007 Urban Affairs Association
All rights of reproduction in any form reserved.
ISSN: 0735-2166.
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IVol. 29/No. 2/2007
Gilderbloom and Markham, 1996; Glaeser and Luttmer, 2003; Heskin, Levine, & Garrett, 2000;
Keating, Teitz and Skaburskis, 1998). Keating et al. (1998, p. 3) described rent control as “a product
of crisis” and “typically imposed during periods of wartime housing shortages or peacetime
inflation when rents increased beyond the ability of many tenants to pay without hardship.”
The “conventional wisdom” on rent control suggests that rent regulation has an adverse effect
on local housing (see Alston, Kearl, & Vaughan, 1992; Epple, 1998; Kearl et al., 1979; Moon and
Stotsky, 1993). In their surveys of economists, Alston et al. (1992) found a consensus (over 93.5%)
of agreement that “A ceiling on rents reduces the quantity and quality of housing available.” In
an earlier survey, Kearl et al. (1979) also found a similar consensus toward rent control. One
economist even went so far as to declare that rent control is a weapon of mass destruction “the
same as a nuclear blast in very slow motion” (Fisch, 1983, p.18). The majority of the literature
opposes rent control on the grounds that it creates major inefficiencies that are unnecessary to
achieve the desired goals. Economists argue that rent control interferes with a landlord’s ability to
respond to market signals, thus reducing the profitability of rental investment and discouraging new
construction. By limiting rents, rent control could lead to under-maintenance of property and the
deterioration of the housing stock (Keating et al, 1998; Moon and Stotsky, 1993). Opponents assert
that a disproportionate share of the burden of assisting low- and moderate-income households is
shifted onto landlords. A final concern is that rent control might discourage residential mobility
since rent increases for continuing tenants are generally smaller than for new residents (Strassman,
However, we have to recognize that there have been several phases of rent control regulations
throughout the United States in the 20th century. Different rent control regulations have different
provisions and these differences can lead to different results. Rent control prevailed across the
country during World War II as a national emergency measure. After the war, the postwar building
boom eased the housing shortage considerably and landlord groups across the country raised
strong challenges about the constitutionality of rent control. By the 1950s, rent control had been
abandoned almost everywhere except in a few cities in the state of New York, including New
York City. During the 1970s and early 1980s, due to concern about the number of inflating rent
prices, there was a resurgence of rent control ordinances in Massachusetts, New Jersey, Virginia,
the District of Columbia, Florida, and California. Starting in the mid 1980s, the number of cities
with rent control policies began to decline. Cities in Massachusetts, Florida, Virginia, Maryland,
and the District of Columbia eliminated them, and state laws (as in California) were passed to take
the teeth out of the policies. Nevertheless, by the 1990s, over 200 localities in the United States
had some form of rent regulation and more than 10% of all private rental units were covered by
different types of rent control policies (Olsen, 1998).
Increasingly, contributions to the literature reflected the differences between the first-generation
(between WWII and the 1960s) and second-generation (after the 1970s) rent control regulations
in the United States (Arnott, 1995; Heskin et al., 2000; Moon and Stotsky, 1993; Olsen, 1998).
Rent control was imposed in the United States shortly after the country’s entry into WWII to
ensure affordable housing and to prevent profiteering. This form of control was a restricted freeze
on nominal rents, that is, absolute ceilings on rent were set without any consideration for the
landlords’ rate of return. After the housing boom in the late 1940s and early 1950s, the first-
generation restrictive rent freeze was essentially abandoned across the country, except in New
York. Yet even in New York these restrictive laws were already being phased out, with generous
annual increases not limited by the CPI, vacancy decontrols, and now luxury decontrols. New
York’s restrictive rent control laws only apply to a shrinking number of rental units. The rent control
regulations imposed during the 1970s differed significantly from the first-generation rent control
policies because they were seen as moderate as opposed to restrictive. The second-generation
IThirty Years of Rent Control I
rent control regulations “entail a complex set of regulations governing not only allowable rent
increases, but also conversion, maintenance, and landlord-tenant relations” (Arnott, 1995, p.102).
As rent control regulation changed over the years, particularly after the 1970s as the second-
generation rent control emerged, economists started to respond and modify their conventional
oppositions toward this policy. For example, Arnott (1995) argued that economists “appreciate
the virtues of free markets more than the average citizen”; therefore, they tend to oppose any type
of price controls. However, due to the substantial flexibility in their regulations, second-generation
rent controls are “so different that they should be judged largely independently of the experience
with first-generation controls” (Arnott, 1995, p.118).
In the 1970s, over 120 communities in New Jersey and five Massachusetts areas adopted a
particular type of rent control, moderate rent control. The adoption of rent control in New Jersey
was due to a significant rent increase between 1960 and 1970, with median rents increasing by 64%,
compared to the 33% increase in the Consumer Price Index (CPI) during the same period (Baar,
1998). In 1970, the New Jersey Tenants Organization (NJTO) was formed and tenant-organizing
efforts were successful in changing a state law that eventually allowed municipalities to have
the power to adopt rent control ordinances. By 1975, more than 100 municipalities had adopted
ordinances, with many cities setting allowable percentages of rent increases according to changes
in the full CPI. As the inflation rate soared in the mid-1970s, many cities then amended their
ordinances to limit annual increases to a portion of the increase in the CPI or a flat percentage
(Baar, 1998, p.144). With the exception of refinancing costs, a mortgage is mostly fixed and
therefore unaffected by increases in the cost of living (Gilderbloom, 1981b, pp. 35–36) Studies
of rental housing operating costs show that in the 1970s landlord costs increased by only one-half
or less of the CPI (Sternlieb, 1974, 1975; Gilderbloom, 1981b). In the decade of 2000, with
spiraling rents, refinancing, and cash outs, landlord’s fixed mortgage payments are more likely
to represent about 75% of a landlord’s operating costs—suggesting that landlords could keep up
with inflationary costs by raising rents by one-fourth of the CPI.
Although the use of the CPI standard for annual allowable rent increase has been controversial, it
is not easy to find an across-the-board index to capture the cost-of-living change for both landlord
and tenant. Most of the places that have adopted rent control policies, such as many jurisdictions
in California and New Jersey, use the CPI as an acceptable index for increased cost-of-living and
maintenance costs annually (Keating, 1998).
In order to achieve the criterion of a fair rate of return, most moderate rent control laws in New
Jersey share some other common features, including guaranteed annual rent increases sufficient
to cover increases in landlord operating expenses, the exemption of new construction, requiring
sufficient maintenance as a condition for allowing rent increases, and provisions for passing
through major capital expenses. The non-restrictive nature of moderate rent control laws can also
be demonstrated in terms of landlord requests for “hardship appeals.” These appeals are requests
by landlords for additional rent increases above the allowable rent ceilings to guarantee a fair
and reasonable return on investment. In a survey of 46 rent-controlled cities in New Jersey, Baar
and Keating (1981) found that, on average, a city’s rent control board received only three or four
requests annually for “hardship increases” from landlords. Hardship appeals were granted either
full or partial approval 70% of the time by the rent control boards.
Baar and Keating (1981) also found that moderate rent control ordinances were usually ad-
ministered by nonelected local rent control boards. Tenants rarely constituted a majority on these
boards, since board members were typically appointed by the city government, which ordinarily
took care to ensure a balance between landlord, homeowner, and tenant interests. The typical
New Jersey rent control board consisted of five members: two tenants, two landlords, and one
homeowner. In addition, these authors found that, of 46 rent-controlled cities in New Jersey, 27
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out of 65(42%) rent control board members surveyed in these cities identified themselves as either
a “landlord or realtor”; no board members identified themselves as “tenant organizers” (p. 60).
Though diverse in specific attributes, moderate rent control has the common purpose of balanc-
ing the interests of tenants and landlords, obtained by guaranteeing a fair and reasonable return
on investment to the landlord while eliminating the practice of excessive annual rent increases.
(For a thorough review on this subject, see Gilderbloom & Markham, 1996).
A number of studies have examined the empirical results of conventional rent control on
American cities, such as Santa Monica (Booher, 1990; Capek & Gilderbloom, 1992; Levine,
Grigsby, & Heskin, 1990), Los Angeles (Murray, Rydell, Barnett, Hillestad, & Neels, 1991), San
Francisco (Lima, 1990), New York (Moon & Stotsky, 1993; Rapaport, 1992), and Cambridge,
Massachusetts (Navarro, 1985). Other literature examines the impact of rent control on some other
social issues, such as homelessness (Appelbaum, Dolny, Dreier, & Gilderbloom, 1991; Early
and Olsen, 1998; Gilderbloom, Appelbaum, Dolny, & Dreier, 1992), misallocation of housing
(Glaeser & Luttmer, 2003), owner-occupied housing price (Hackner & Nyberg, 2000), and resident
mobility (Strassman, 1991). California adopted its strong rent control ordinances during the
overheated rental market in the 1980s. New York City has had typical restrictive rent control into
the post-war era. Due to the strong rent control characteristics in these two areas, most of the
empirical studies concluded some negative impact of rent control on the quality of the housing
market, including reduced affordability in the rental market, deterioration of the housing stock,
and de-investment on rental units (Levine et al., 1990; Moon and Stotsky, 1993; Murray et al.,
However, there have been very few studies measuring the impact of moderate rent control in New
Jersey, which was seen as a compromise between restrictive New York style rent control and the
free market (Appelbaum & Gilderbloom, 1990; Gilderbloom & Appelbaum, 1988; Gilderbloom
& Markham, 1996; Marcuse, 1981). Gilderbloom and Markham (1996) surveyed over 60 New
Jersey cities and found that due to the nonrestrictive nature of the ordinances, moderate rent control
did not significantly affect most measures of cost, quality, and quantity of rental housing stock.
An earlier study (Gilderbloom, 1984) examined allowable rent increases in 89 rent-controlled
New Jersey cities between 1975 and 1976. The data showed that a majority of rent-controlled
cities allowed rent increases similar to those in non-rent-controlled areas. Only 35% of the rent-
controlled cities had allowable rent increases that were below the national CPI rent index. This
figure, however, is almost identical to the percentage of non-rent-controlled cities surveyed by
the Bureau of Labor Statistics. Furthermore, all but two of the rent-controlled cities were only
one or two percentage points below the national CPI rent index.
While restrictive rent controls appear to have a negative impact on the quality and quantity of
the rental housing market, moderate rent control may be able to avoid these problems. Due to the
limited number of empirical studies on this topic, our investigation hopes to fill the gap in this
area; our study seeks to examine the impact of moderate rent control by performing quantitative
analyses of data and to develop a model for evaluating different types of rent control.
The data in this study were collected by the New Jersey Tenants Organization (NJTO) in its
2003 Rent Control Survey. All of the 104 New Jersey cities that had some form of rent control were
IThirty Years of Rent Control I
surveyed. Questions in the survey included allowable increase, tax surcharge, capital improvement,
hardship provision, vacancy decontrol, fuel passalong, fair return clause, new rental unit exclusion,
tenant return on tax appeals, substantial compliance, and multiple dwellings coverage rent control
provisions. Detailed descriptions about the questionnaire items and descriptive statistics of the
104 cities can be found in the Appendix.
For the data analyses in the following section, cities that had a population of over 10,000 were
chosen. Out of the 104 cities that had rent control in 2000, 76 cities had population over 10,000.
There were 85 other cities in New Jersey that did not have rent control and had a population more
than 10,000 in 2000. Therefore, the total number of cases in this study is 161. Census provides
us with more detailed information on cities over 10,000 for this kind of analysis.
A between-group bivariate analysis of the data was conducted for cities that have and do not
have rent control policies. The results show statistically significant differences on various housing
measures. (Table 1).
Monthly median contract rents were $36 lower in rent-controlled cities, but the difference was
not significant. Cities that did not have rent controls had a significantly (at .001 level) higher
median number of rooms in rental units than cities that had rent controls. Rent per room was also
higher in rent-controlled cities but, once again, the difference was not significant. Cities with rent
control had a significantly higher percentage of rental units with a plumbing deficiency (at the
.001 level) than cities without rent control. Rent control did not have a significant impact on new
construction between 1990 and 2000. Median household income was significantly higher in non
rent control cities. The median household income in the rent-controlled cities in 2000 was $53,027.
Our data also revealed that in these cities, the median household income for renters (not shown)
was roughly over $40,000 in the same year. Twenty-three percent of renters had household income
lower than $25,000 and 31% lower than $35,000. These households are considered to be those
that have had the greatest benefit from rent control. Rent control cities had larger populations, and
Rent Control and Non Rent Control Cities
Non rent control cities Rent control cities
(n=85) (n=76) TTest
Mean Std. Dev. Mean Std. Dev. (2-tailed)
Dependent variables
Median monthly contract rent $780 $183 $744 $129 1.43
Median rooms 4.1 0.56 3.7 0.31 5.74∗∗∗
Rent per room $190 $42 $202 $40 1.79
Units built 1990—2000 (%) 6.81 7.73 5.43 4.02 1.40
Plumbing deficiency (%) 0.45 0.45 0.86 1.16 2.98∗∗∗
Control variables
Vacancy rate 3.91 3.58 3.21 1.96 1.52
Percent units renter occupied 28.13 15.87 44.20 18.47 5.96∗∗∗
Median household income $62,904 $22,230 $53,027 $15,450 3.23∗∗
Population 17,803 8,696 39,511 44,820 4.38∗∗∗
Population change 1990–2000 (%) 5.97 17.59 15.08 19.69 0.22
Black (%) 9.09 13.81 15.09 19.69 2.26
Units built before 1940 (%) 20.70 14.80 26.11 12.94 2.45
∗∗ Sig.<0.01.
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a larger percentage of the population was nonwhite. Non rent control cities had an older housing
stock. The rent-controlled cities had a higher percentage (16% higher) of housing units that are
renter occupied, with a slightly lower (0.7% lower) vacancy rate.
Ordinary Least Squares Regression
In order to further test whether moderate rent control had a significant impact on the rental hous-
ing market, regression models were built to control for other intervening variables. This study
operationalizes rent control in two ways: (1) as a nominal variable (1 =rent control enacted,
0=no rent control); and (2) as an interval scale measuring the strictness of rent control
laws given the different components of rent control ordinances. The main focus was on the
impact of rent control on variables that measure the quality, quantity, and price of rental
As shown in the Appendix, there are ten ways for landlords to request an additional increase in
rent over and above the across-the-board increase: tax surcharge, capital improvement, hardship
provision, vacancy decontrol, fuel passalong, fair return clause, new tenant exclusion, tenant
return on tax appeals, substantial compliance, and multiple dwellings covered. For each category,
a value of 0 was given to the cities that allowed landlords to appeal against rent control or increase
rent (e.g., increasing rent due to tax surcharge, capital improvement, hardship provision, etc.).
A value of 1 was given to the cities that do not allow landlords to appeal against rent control or
increased rent. In 2000, the CPI was 3.4% nationwide. A value of 0 was given to the cities that
allow landlords to increase rent by more than 3% and a value of 1 was given to the cities that
allow landlords to increase rent by less than 3%.
Therefore, an ordinal score was given to every city; the higher the score, the more restrictive its
rent control ordinances. Cities without rent control have a score of 0. The next section explains
other variables included in the model.
Supply Variables
Measures of supply include vacancy rate and the proportion of housing units that were renter
1. Vacancy rate 2000
The rental vacancy rate is the single best predictor of rent levels. A low vacancy rate indicates
a shortage in rental housing, which reduces competition among landlords and thus causes
rent to be higher. Conversely, areas with high vacancy rate have lower rents.
2. Percentage units renter occupied 2000
The percentage of the housing stock that is rental can also influence rents. Gilderbloom and
Appelebaum (1988) found two conflicting arguments about the effects of this variable on
rents. Nevertheless, the variable is important in any model that predicts the rental housing
3. Older housing stock
The percentage of housing built prior to 1940 reflects the overall age of the housing stock.
IThirty Years of Rent Control I
Demand Variables
Variables measuring demand include income, total population, population change, and ethnicity
1. Median household income 2000
Median household income is a standard measure of demand for rental housing since landlords
are able to charge rents based on a tenant’s income.
2. Population 2000
Since more populous areas may offer more amenities than smaller areas, the total population
needs to be taken into account in examining the rental market.
3. Percentage African-American Population 2000
The percentage of African-American population can affect demand and rents although the
direction is unclear.
4. Population change from 1990 to 2000
The rate of population is a measure of growth-induced demand for housing. Research
indicates that rapidly growing cities tend to have higher rents because of the inability of the
rental housing market to meet the increasing demand.
Dependent Variables
1. Median monthly contract rent
2. Median numbers of rooms
3. Median monthly contract rent per room (used to control for the size of rental units in different
housing markets)
4. New construction during 1990–2000
Existing economics literature argues that rent control will drain the landlords’ profit return,
and thus limit landlords’ and developers’ financial capability to build more new rental hous-
ing (for example, Gilderbloom & Appelbaum, 1988; Keating et al., 1998). The introduction
of this variable can test this argument empirically.
5. Quality of rental housing stock
This is measured by the proportion of units lacking complete plumbing, which has been
identified as a reasonable proxy indicator for rental housing quality (Baar & Keating, l981;
Gilderbloom & Appelbaum, 1988; Gilderbloom & Markham, 1996). However, the quality
of the rental housing stock is an extremely complicated variable and there are many other
alternative indicators to measure this variable. Due to the limitation of available data, plumb-
ing deficiency is the most appropriate indicator we can identify, and therefore it is used as a
proxy for the quality of rental housing stock. Future research should attempt to incorporate
more indicators to measure this variable.
Prior to the regression analysis, we examined the correlations between the control variables
(see Table 2). An examination of zero-order correlation coefficients indicated acceptable (lower
than .70) correlations among the independent variables. Other tests we have looked at also found
no evidence of multicollinearity. After performing additional diagnostics,1ordinary least squares
regression was performed to examine whether rent control affects the five dependent variables:
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IVol. 29/No. 2/2007
median monthly contract rent, median rooms, rent per room, plumbing deficiency, and new
construction (Tables 3 and 4).
All the models in Tables 3 and 4 have predictive power. The models explain over 60% of the
variation in median monthly rent, plumbing deficiency, and new construction in our sample of
cities. Our models explain a slightly lower percentage of the variation in median rooms and rent
per room, with R2ranging from 38% to 57%.
We found that moderate rent control had almost no significant impact on median monthly
contract rent, plumbing deficiency, and new construction. It is noticeable that almost 85% of the
76 New Jersey cities that had rent control ordinances had some kind of vacancy decontrol policy.
Typically, vacancy decontrol policy allows landlords to charge the new tenants of vacated units
at a market rent with certain criteria met, such as the “no-harassment” statement from departing
tenants. The introduction of vacancy decontrol eased the heated opposition to rent control from
landlords since they can have market rate increases in many units, particularly with a high rental
turnover rate. Vacancy decontrol policy could have offset some of the significant impacts rent
control might have had on rents.
In Table 3, rent control seems to reduce the median number of rooms; therefore, when median
monthly rent remains the same, rent per room was significantly higher when rent control existed.
A similar association was found in Table 4. When rent control got more restrictive, it tended to
limit the median number of rooms, and thus increase rent per room. This suggests that landlords
might be subdividing rental units to increase rents.
The results indicate that moderate rent control had no significant impact on the quantity (mea-
sured by new constructions between 1990 and 2000) and quality (measured by the percentage of
rental units’ lack of plumbing) of the rental housing market. The nonrestrictive nature of moderate
rent control often provides a fair return for the landlord on investment, and the construction of
new residential buildings continues because builders are exempt and reluctant to leave a familiar
community (Gilderbloom, 1981a, 1981b; Gilderbloom & Appelbaum, 1988).
Other studies argue that rent control may affect the quality of rental housing due to the inability
of rent to keep up with rising costs (Arnott, 1995; Glaeser and Luttmer, 2003; Heskin et al. 2000).
Our results indicate that, other than appearing to decrease the size of rental units, rent control did
not have a significant impact on the quality of the rental housing market.
In general, this study found that New Jersey’s moderate rent control laws had almost no signif-
icant impact on the quality and quantity of the rental housing stock, an exception being a small
decrease in the median number of rooms in rent control cities. While traditional literature tends
to agree that restrictive rent controls appear to have a negative impact on the quality and quantity
of the rental housing stock, due to its nonrestricted ordinances and fair considerations for both
tenants and landlords, moderate rent control appears to have avoided these problems.
Our research is one of the most comprehensive empirical studies on this topic, but there are some
limitations due to data availability. First, a better measure of rental housing quality, rather than only
using plumbing deficiencies as a proxy, would be an improved approach (e.g., a multiple indicator
index). Second, there has been a controversy in using CPI as the standard for rent increase, but
since a majority of the New Jersey communities continued using this policy our study did not
develop an alternative criterion to measure reasonable rent increase. Third, future research should
extend to different geographical areas across the country to see how rent control has evolved over
IThirty Years of Rent Control I
Zero-Order Correlation Among Control Variables (n=161)
Population Median Units renter Units built Plumbing
Black change household occupied Vacancy before deficiency
Population (%) 1990–2000 income (%) rate 1940 (%) (%)
Population 1.000
Black (%) 0.395∗∗∗ 1.000
Population change 1990–2000 0.009 0.046 1.000 0.037 0.108 0.100 0.035 0.036
Median household income 2000 0.285∗∗∗ 0.398∗∗∗ 0.037 1.000 0.675 0.327 0.116 0.459
Units renter occupied (%) 0.415∗∗∗ 0.435∗∗∗ 0.108 0.675∗∗∗ 1.000 0.032 0.434 0.509
Vacancy rate 0.029 0.214∗∗ 0.100 0.327∗∗∗ 0.032 1.000 0.035 0.075
Units built before 1940 (%) 0.1830.1920.035 0.116 0.434∗∗∗ 0.035 1.000 0.248
Plumbing deficiency (%) 0.342∗∗∗ 0.430∗∗∗ 0.036 0.459∗∗∗ 0.509∗∗∗ 0.075 0.248∗∗ 1.000
∗∗ Sig.<0.01.
∗∗∗ Sig. <0.001.
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Impact of Rent Control (Nominal) on Rental Housing Characteristics in 2000 (n=161)
Rent New
Rent Median per Plumbing construction
2000 rooms room deficiency 1990–2000
Rent control, nominal 18.262 0.244∗∗ 17.874∗∗∗ 6.446 71.812
(16.133) (0.072) (4.969) (29.794) (105.007)
Population 0.001 0.000 0.000 0.003∗∗∗ 0.043∗∗∗
(0.000) (0.000) (0.000) (0.001) (0.033)
Black (%) 1.1220.001 0.3072.38311.910∗∗∗
(0.493) (0.002) (0.152) (0.991) (3.209)
Population change 1990–2000 0.005 0.000 0.004 0.009 0.288
(0.028) (0.000) (0.008) (0.051) (0.179)
Median household income 0.007∗∗∗ 0.000 0.002∗∗∗ 0.0020.002
(0.001) (0.000) (0.000) (0.001) (0.003)
Units renter occupied (%) 1.779∗∗ 0.015∗∗∗ 1.141∗∗∗ 0.761 1.346
(0.607) (0.003) (0.187) (1.121) (3.950)
Vacancy rate 2.224 0.009 1.010 0.039 87.543∗∗∗
(2.696) (0.012) (0.830) (4.978) (17.546)
Units built before 1940 (%) 0.007 0.000 0.002; 0.018 0.125∗∗∗
(0.004) (0.000) 0.000 (0.007) (0.025)
R20.697 0.393 0.574 0.649 0.728
Adjusted R20.682 0.362 0.552 0.631 0.714
F44.611∗∗∗ 12.559∗∗∗ 26.150∗∗∗ 35.814∗∗∗ 51.742∗∗∗
∗∗ Sig.<0.01.
∗∗∗ Sig.<0.001.
Note: Numbers above indicate unstandardized coefficients. Numbers in parenthesis indicate standard errors.
time and what new ordinances may have been adopted in response to various legal and political
In general, conventional generalizations about rent control do not distinguish between moderate
and restrictive controls in the housing market. There has been a great deal of change in the last few
decades as rent controls have moved from being restrictive to more moderate forms. This article
examined a moderate form of rent control, looking at 76 regulated cities in New Jersey. Moderate
rent control in New Jersey stands as symbolic rather than distributional reform. Our research
suggests that the pressure of real estate groups, government, and the courts has made modern-day
rent control laws toothless in terms of their impact on rents. A similar finding has been found
in southern California (Heskin et al., 2000). About the only measurable impact is that landlords
may have cleverly reduced the size of rental units to create more units and profit in rent control
cities. At best, it appears that most rent control ordinances have only succeeded in preventing
rent increases that are excessive. These ordinances have also provided protection against arbitrary
evictions, incentives for maintenance of rentals, and knowledge to tenants about the level of rent
increases to expect in the future. Certainly, this is a small improvement for tenants who have had
none of these protections in the unfettered market. Our study shows that, as a moderate type of
rent control, the rent regulations in New Jersey may have avoided some of the negativity of the
conventional regulations.
IThirty Years of Rent Control I
Impact of Rent Control (Ordinal) on Rental Housing Characteristics in 2000 (n=161)
Rent New
Rent Median per Plumbing construction
2000 rooms room deficiency 1990–2000
Rent control, ordinal 3.471 0.046∗∗ 3.422∗∗∗ 0.932 5.712
(3.378) (0.015) (1.047) (6.234) (21.998)
Population 0.001 0.000 0.000 0.003∗∗∗ 0.043∗∗∗
(0.000) (0.000) (0.000) (0.001) (0.003)
Black (%) 1.1350.000 0.3202.38111.867∗∗∗
(0.493) (0.002) (0.153) (0.911) (3.213)
Population change 0.004 0.000 0.005 0.008 0.281
1990–2000 (0.027) (0.000) (0.009) (0.051) (0.179)
Median household income 0.007∗∗∗ 0.000 0.002∗∗∗ 0.0020.002
(0.001) (0.000) (0.000) (0.001) (0.003)
Units renter occupied (%) 1.789∗∗ 0.015∗∗∗ 1.1477∗∗∗ 0.619 1.777
(0.610) (0.003) (0.189) (1.125) (3.791)
Vacancy rate 2.405 0.011 1.182 0.190 88.850∗∗∗
(2.682) (0.012) (0.831) (4.949) (17.464)
Units built before 1940 (%) 0.007 0.000 0.002 0.0180.125∗∗∗
(0.004) (0.000) (0.001) (0.007) (0.025)
R20.697 0.384 0.569 0.649 0.727
Adjusted R20.681 0.353 0.546 0.631 0.713
F44.505∗∗∗ 12.098∗∗∗ 25.540∗∗∗ 35.805∗∗∗ 51.559∗∗∗
∗∗ Sig.<0.01.
∗∗∗ Sig.<0.001.
Note: Numbers above indicate unstandardized coefficients. Numbers in parenthesis indicate standard errors.
Studies of rent control too often focus on just one city or a small comparative sample (or
worse a computer simulation); this study attempts to look at a large sample of both regulated
and unregulated municipalities in order to generate conclusions. Rents, after 30 years of rent
control, are about the same as they are in cities in the same region without controls. Across the
nation rental affordability worsens and rents in New Jersey (whether rent controlled or not) are
much higher than the national average (Gilderbloom, 2007). The intended impacts of New Jersey
rent control over a 30-year period seem minimal when you compare cities without regulations.
Housing activists and policymakers need to look at new kinds of approaches to address the rental
housing affordability crisis.
ACKNOWLEDGMENT: An earlier version of this paper was presented at the 36th Annual Conference of the
Urban Affairs Association, April 19–22, 2006, Montreal, Canada. The authors thank four anonymous reviewers
of the Journal of Urban Affairs for their valuable comments. All mistakes and omissions are the responsibility of
the authors.
1 For all the regressions, the tolerance values were always greater than .35 and the VIF smaller than 3. The only
moderately significant correlations appeared to be between the total population and old housing stock, with
tolerance values between .15 and .20 and VIF between 5 and 7.
218 I
IVol. 29/No. 2/2007
Key to Rent Control Chart (New Jersey Tenants Organization)
Rent control is not a state matter. Each town that has rent control has its own rent law. Some or
all of the columns listed in the Rent Control Chart apply.
Allowable Increase: How much the landlord can raise the rent per month depends upon the
ordinance within each town, sometimes based on the Consumer Price Index (CPI), which is a
measure of the rate of inflation.
Tax Surcharge: In some towns, the landlord is allowed to pass increases in taxes along to
the tenants. This special rent increase is called a tax surcharge and sometimes requires special
approval of the Rent Board.
Capital Improvement: This increase is sometimes a permanent increase or is based on the life
of the improvement to a unit. An application procedure and ruling by the Rent Board are required.
Hardship Provision: Landlord pleads hardship by showing that he is not making enough of a
profit on the building. A hearing is required and the landlord must prove his case.
Vacancy Decontrol: A new tenant may have to pay a higher rent than the old tenant (a tenant
who was living in the dwelling before the rule was enacted) would have had to pay. This may be
a one-time increase (temporary vacancy decontrol) or the tenant may never fall under rent control
(permanent vacancy decontrol).
Fuel Passalong: Some towns enacted fuel surcharges during the oil crisis to cover landlords’
increase in oil prices. Some towns still have this provision.
Fair Return Clause: Tied to “Hardship Provision,” definition of Fair Return on investment
included in some ordinances.
New Tenant Exclusion: Applies to new buildings. Usually, for the first tenants of each newly
constructed building there is no rent control; rent for subsequent tenants depends upon each
Tenant Return on Tax Appeals: Landlord goes to the tax board saying that he is being taxed
unfairly, and wants a refund. A percentage of all of the refund will or will not be passed on to the
Substantial Compliance: In order for the landlord to raise the rent he must have repaired
almost everything in the building and had few violations for the building.
Multiple Dwellings Covered: Number and type of apartments (dwelling units) per building
required for rent control to apply.
Characteristics of Rent Control Policies in New Jersey
Rent control Yes No Conditional
Tax surcharge 48.1% 39.2% 12.7%
Capital improvement 54.4% 6.8% 38.8%
Hardship provision 73.8% 1.9% 24.3%
Vacancy decontrol 45.7% 15.2% 39.1%
Fuel passalong 6.1% 82.7% 11.2%
Fair return 47.9% 38.0% 14.1%
Excludes new rental 26.4% 12.6% 60.9%
IThirty Years of Rent Control I
Allowable Rent Increases in New Jersey
Allowable Rent Increases Number of Cities Percent of 104 Cities
0–2% 2 1.9%
2.01–3% 3 2.9%
3.01–4% 8 7.7%
4.01–5% 7 6.7%
More than 5% 11 10.6%
CPI 21 20.2%
Limited CPI 20 19.2%
Based on rent charged or number of units owned 3 2.9%
Dependent upon whether tenant or landlord pays heating bill 16 15.4%
Dependent upon age of tenant (65 years or older) 3 2.9%
Conditional 10 9.6%
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... Median Contract Rent: This variable measures the monthly median rent price per city (Gilderbloom and Ye, 2007;. ...
... As the price of homeownership rises, as reflected in median house values, the demand for rental housing will increase, and in so doing, it will elevate the rental prices, all else being equal. Gilderbloom et al. (1992), Gilderbloom and Appelbaum (1988) and Gilderbloom and Ye (2007) found a positive relationship between the price of housing and renting, showing that the costs of rent and the price of homeownership is related to a ceiling on rents (Dieleman, Clark and Deurloo, 2000;Bitter et al., 2007;Glaesar and Gyourko, 2002;Ozanne and Thibodeau, 1983;Thibodeau, 1995). At some point, tenants realize that they could pay a mortgage payment for the price they are paying to rent (Beer, Kearins and Pieters, 2007). ...
... For economists, vacancy rates are an excellent indicator of supply. When vacancy rates are low, rents are believed to be high (Gilderbloom and Ye, 2007;De Leeuw andEkanem, 1971, Gabriel andNothaft, 2001;Deng, Gabriel and Nothaft, 2003;Lai, et al., 2007;Gilderbloom, et al., 1992, Dreier, et al., 1991. Sociologists believe that social and political interferences, along with megalandlords controlling a large portion of the rental housing stock, cause vacancy rate impact to be diminished relative to other concerns. ...
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... l In second-generation schemes, where rents are more or less indexed to inflation, the tenant benefits and landlord costs are both lower in an economic welfare sense and this can significantly increase transfer efficiency compared to first-generation schemes (although this aggregate result obscures bigger individual impacts which may not be so benign). Gilderbloom and Ye (2007*) and Ambrosius, et al, (2015*) are linked papers looking at long term data from New Jersey (76 New Jersey cities studied over several decades). The earlier paper examined the long-term impacts of the introduction in the 1970s of several similar forms of limitations to annual rent increases. ...
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... Cities and voters may be influenced to support rent control by a desire to ensure affordability in a rental market glutted with new renters who lost their homes during or after the crash (Tatian, 2013). This paper updates four decades of research on rent control ordinances in New Jersey communities to today's climate by replicating and expanding past analyses with 2010 U.S. Census data (for examples, see past studies by Gilderbloom and colleagues: Gilderbloom, 1983;Gilderbloom & Markham, 1996;Gilderbloom & Ye, 2007). New Jersey, a national leader in tenants' rights since the 1960s, is an excellent case study of the effects of moderate rent controls because so many (over 100) of its municipal governments have adopted these controls (Baar, 1998). ...
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In this article I explore the question of rent control: one of the most despised yet misunderstood policies across a variety of disciplines and professions concerned with urban and housing issues. The hegemonic view is that rent controls - in any form, in any context - will eventually hurt those on whose behalf they are supposedly introduced (people struggling to find somewhere affordable to live). I use the concept of agnotology - the study of the intentional production of ignorance - to demonstrate that this view is riddled with vested interests and grounded in deep contempt for state regulation and in veneration of the supposed “efficiency” of the “free” market. I expose and dissect three of the prevalent myths of rent control: (1) that it negatively affects the quality of rented properties; (2) that it negatively affects the supply of housing; and (3) that it leads to ‘inefficiencies’ in housing markets. I take a close look at different kinds of rent control and, more broadly, at what leads to high housing costs, and by doing so I shift the analytical and political focus towards the urgent question of housing justice.
Housing affordability is an issue of increasing importance and interest, particularly in the United States. Much of this interest is due to skyrocketing rents in coastal cities with tight housing markets. Shrinking cities, in contrast, are often characterized as rich in low-cost housing, providing an affordable alternative to superstar cities. This paper compares income and rent dynamics in cities with growing versus shrinking populations. While costs may be lower in shrinking cities, falling incomes have likely rendered housing unaffordable for many residents. We employ multiple lines of evidence to test for different dynamics between growing and shrinking cities. Matching is used to explore changes in income and rent between 1980 and 2017 in shrinking and the most similar non-shrinking cities. After controlling for baseline conditions, shrinking cities exhibit faster falling incomes and growing cities exhibit faster rising rents, while rent burden increases at a very similar rate in both groups. We also use a fixed effects regression model to test for differences between growing and shrinking cities in sensitivity of rent burden to changes in income and rent. Rent burden has considerably increased across US cities since 1980, yet growing and shrinking cities exhibit clearly different pathways toward that end. Shrinking cities are more sensitive to identical changes in income and rent, likely because a greater share of their residents live near the edge of affordability.
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This report is concerned with the nature of housing occupancy for households that rent, particularly low-income and vulnerable households. It describes and compares provisions for secure occupancy across a variety of rental systems in Australia and similarly developed countries, and attempts to interpret to what extent such provisions are adequate and appropriate to the needs of households, especially those who rely on renting for significant periods (or all) of their lives. To inform and broaden consideration of this current policy issue in Australia, the study's methodology has been designed to enable an assessment of the means by, and the extent to which, secure occupancy in rental housing is provided in a cross-section of local and international jurisdictions. The primary aims of the study are to explore how different types of rental systems shape the nature of occupancy, and to generate new ways of thinking about secure occupancy and policy settings to help promote this in Australia. facilitate the study's comparative approach, the Australian authors have worked in close collaboration with a group of international housing research colleagues (named in Table 4) with expertise in one or more of the eight national and provincial jurisdictions that have been selected for comparison. These are: Austria New Jersey (US) Flanders (Belgium) Ontario (Canada) Germany Scotland Ireland 8. The Netherlands. As the rental systems of these countries differ considerably, they provide a rich laboratory for exploring ways that secure occupancy is shaped by multiple factors, including historical conditions, market functioning, cultural influences and institutional settings, and generate a variety of challenging ideas about how rental systems might best support the housing needs of their residents, while also encouraging appropriate and secure levels of rental investment. A concise summary of the rental system and policies of each of these case studies can be found in Appendix 1. These summaries are provided to complement the thematic analysis that is adopted in the body of the report. The international case studies were augmented by local research on the current framework for secure occupancy in Australia, as well as by a more in-depth review of the situation in two jurisdictions (New South Wales and Victoria), which was conducted by the authors.
This article examines changes between 1980 and 1990 in the number of rental units and the demographic composition of tenants in four California cities that adopted rent control with vacancy control provisions. Six border areas within the four cities were compared to border areas of adjoining cities that did not have vacancy control. A spatial lag regression model was constructed to estimate the changes in regional and neighborhood components in addition to vacancy control policies. Vacancy control contributed to lower rents and longer tenure by tenants compared to non-vacancy-controlled areas. There were also fewer rental units in part because of a shift from rental housing to owner-occupied housing.
A provocative look at the true forces that shape housing markets, challenging mainstream theories of supply and demand and calling for a new way to provide shelter to our cities' most overlooked inhabitants-the elderly, the disabled, and the poor.
This article finds no evidence to support the contention that moderate rent control over a three- to five-year period has led to a reduction in multifamily residential construction, a decline in maintenance, an erosion of the tax base relative to non-rent-controlled cities, or an increase in abandonments or demolitions. Those studies arguing the reverse are characterized by data rendered suspect because of nonrepresentative sampling and highly selective statistics. While all available data suggest that short-term moderate controls have no measurable negative impact, this does not imply that no such relationship exists. More research is needed to study the long-term effects of moderate controls.