WHO BENEFITS FROM RENT CONTROL? EFFECTS ON TENANTS IN
The objective of Santa Monica's rent control law, in effect since 1979, is to protect renters--particularly "the poor, minorities, students, young families and senior citizens"-from rapidly rising rents. Comparing 1 987 and 1 979 tenant surveys indicates that the rent control ordinance has fulfilled some of its goals. Length of tenure has increased, while lower-income tenants and the elderly have benefited most. In addition, the law may have contributed to stopping the decline in households with children. However, it has not stopped a decline in the proportion of black and Latino households. The results suggest that the vacancy control provision of the ordinance is the major factor offering protection to tenants. Since rent control does not increase the supply of affordable rental units nor prevent housing discrimination, it should be viewed as one of a number of housing policy strategies for maintaining affordable housing for specific target populations.
To date, there has not been a thorough evaluation of the rent control law in
Much of the rent control literature consists of debates about the existence of inequities and market dysfunctions caused by rent control's redistribution of wealth from landlords to tenants (Friedman and Stigler 1946; Grampp 1950; Johnson 1951). Some literature, however, suggests the existence of another rent control-created distributional inequality, that within the tenant population itself. Grebler (1952) worried that too much attention was being given to the question of redistribution between landlord and tenants and not enough to the question of redistribution among tenants. Grebler's concern was that the "have nots" would have less access to controlled units than the "haves," and thus forced into the uncontrolled housing market, would have to pay a premium for their housing. The argument is that, under rent control, landlords will engage in noneconomic rationing of the units. Since rent increases beyond regulated levels are not permitted, landlords are assumed to become more selective in choosing tenants. To protect their property, they will tend to choose more affluent tenants who are in a more stable life stage. This mechanism would be detrimental to low income people and minorities and to people in a less stable stage in life (e.g., single people, female-headed families) and would thereby continue the "gentrification" that rent control was supposed to retard, as well as circumvent fair housing laws.
Some studies have substantiated this position. For example, Kristof (1970),
A more recent argument claims that rent control is economically neutral, benefiting all classes of tenants irrespective of need. For example, Gyourko and Linneman (1985) found that, "while many poor families were aided by the rent controls, the same was also true for middle and upper income families." Further, Gilderbloom (1978), Clark and Heskin (1982), Linneman (1980,1987), and Levine and Grigsby (1985) have shown evidence that, although the middle class benefited the primary beneficiaries are those most in need, e.g., lower income households.
Some critics, while acknowledging that a broad cross-section of tenants have
benefited from rent control, have questioned the wisdom of a policy that
benefits both middle- and lower-income persons. Their criticism is that while
the needs of the poor may justify a rent control policy, the targeting of rent
control toward low income people is very inefficient. For example, one study
argued that tenants who could afford the rent took their savings and used it
for "down-payments on suburban single-family homes or on retirement
condominiums or homes in
The following discussion focuses on the question of which groups among the
The survey providing the basis of this discussion was conducted in May and
June 1987. Funded by the
Results of the 1987 survey were compared with a 1979-80 survey of
A comparison of the two surveys suggests that the composition of rental
A comparison of the two data sets disclosed a significant increase in the
average length of tenure of renters in
Undoubtedly, rent control has contributed to the increased tenure. But it
probably would be a mistake to attribute all of the increase to rent control
alone. An evaluation of the rent control ordinance in the nearby city of
Whatever the contribution of rent control, it is clear that, because of the
decrease in turnover rates, there are fewer units available for rent in
The data suggest that "gentrification" has slowed. Residents are staying longer in their units and, when a unit does become available, it is more likely to pass from one tenant to another through personal contact. One would expect that personal contacts tend to reinforce demographic characteristics of the population (i.e., people tend to replicate themselves by choosing people like themselves).
The single most important goal of rent control is, of course, controlling rent levels. Tenants were asked for their current monthly rent, including the monthly registration fees. Table 2 presents the average rent and that of the 25th, 50th (median), 75th, and 90th percentiles. These are broken down separately for the units covered under rent control. Not all units in the 1987 survey were covered by the rent control ordinance. Twenty-one of the 411 households surveyed were not under the rent control law and 14 additional households did not know whether they were or not.
The average monthly rent was $508; rents varied from $157 to $3,250. The four percentiles indicate the approximate rent levels of that proportion of renter households. That is, 25 percent of renter households were paying $345 or less a month; 50 percent were paying $444 or less a month; 75 percent were paying $591 or less a month; and 90 percent were paying $734 or less a month. The lower rent levels for the rent-controlled units indicate that the tenants of units under rent control were paying less than those not under rent control. The average rent for units not covered under rent control was $824, but small sample sizes for units not under rent control make the true difference indeterminate.
To estimate how much rent control has affected the rent levels of tenants in Santa Monica, the current rent levels in Santa Monica were compared to rent levels in the Los Angeles metropolitan area.(n7) The 1979-80 survey, which was conducted between September 1979 and March 1980, was used. In order to estimate market rent levels, the rent levels obtained in the 1979 survey were adjusted back to April 1978.(n8) Since not all landlords raised their rents in September 1979, this adjustment would also underestimate slightly the actual market levels.
The standard way of adjusting monetary levels for different time periods is
to utilize the Consumer Price Index (CPI), published monthly by the U.S. Bureau
of Labor Statistics. The CPI is broken down into separate price components,
including housing, and for major urban areas. The housing component is, in
turn, broken down into several components, including residential rents. Even
though these indices are rough, they can be used to estimate what the average
cost of residential rent would have been if rents in
The most appropriate index for comparing changes in rent levels would be the
residential rent index for the Los Angeles-Long Beach SMSA. In April 1978, the
residential rent index for
Figure 1 contrasts percentiles for the expected rent levels in May 1987,
based on the residential rent CPI, with the actual rent levels found in the
survey; these are presented from I percent to 99 percent in increments of 5
percent. The adjusted April 1978 rent levels are superimposed on the graph.
Overall, the actual rent levels in May 1987 were substantially lower than what
we would have expected if the April t978 rents had increased at the same rate
as residential rents throughout
The graph shows that the savings in actual dollars is greater for those who
pay higher rents. Relative to the rent levels, however, there is only a slight
difference in savings. For example, for those at the 25th percentile, the
savings represent a relative decrease of 25 percent below what
A primary goal of rent control laws is to reduce the pressure that
escalating rents impose on household incomes, particularly low incomes. Over
the past 20 years, tenants in the
To examine the effect of Santa Monica's law on the tenants' rent burden, an index of shelter cost was calculated by taking annual rent as a proportion of household income.(n9) Figure 2 graphs the index of shelter cost (on the Y-axis) by the percentile distribution of renters (from 1 percent to 99 percent in 5-percent increments) for both the 1979 and 1987 surveys.(n10) The estimated 1986 household incomes based on a regression of household income by shelter cost have been superimposed on this graph. (n11)As can be seen, between the first percentile and the eightieth percentile, there is no fundamental difference in shelter cost between the 1979 survey and the 1987 survey. For the top 20 percent, who were paying the highest proportion of their income for rent (above 40 percent), however, the 1987 survey shows a definite decrease in shelter cost. These are households whose income tended to be below approximately $23,000 a year in 1986.
In 1979-80, the average shelter cost was 34 percent.(n12) In 1987, the
average rent for a tenant household had declined to approximately 30 percent.
Much of these savings were accrued by lower-income households. For example, at
the 90th percentile, where the expected household income was less than $
15,000, almost 67 percent of the renter households' income was paid on rent in
1979-80, a percentage that was reduced to 56 percent by 1987. To sum up, the
While there clearly has been a relative saving in shelter costs for low income tenants in Santa Monica, low income people may not have been able to move into or remain in the city. Grebler's (1952) concern that low income tenants might be denied access to housing because of rent control suggests that there should have been a decline in the proportion of low income tenants. Yet, the finding that tenants located their apartments through personal contacts indicates a contrary result. With a turnover of 71 percent of the rental units in the nine years of rent control, there should have been ample time and activity to allow a test of these two arguments.
To test which argument is correct, we conducted a quartile analysis
comparing the distribution of incomes in
As the graph indicates, every percentile up to approximately the 90th percentile falls at or below the expected 1986 household income level. Only from the 90th percentile on has there been a tendency to replace those who already have high incomes with people who have even higher income levels. Whether the replacement of higher income tenants by even higher ones represents an aberration from the general market conditions--that is, an exception--or whether it is the beginning of a trend cannot be determined from the data at this point.
What these data do suggest is that, so far, for the vast majority of the renter population, the household income distribution is similar to what it was in 1979. At least at this point gentrification appears to have been attenuated.
While income distribution in
Because the population of
The data suggest, nevertheless, that the decline relates to access to units
rather than security of tenure. There has been a substantial decline in the
proportion of Latinos and blacks that have moved into
The first possible explanation for this change is the racial discrimination
feared by the critics of rent control. Racial discrimination, of course, exists
with or without rent control. The argument has been, however, that it would
increase because landlords would select tenants on different criteria than
income if rents were controlled. Other factors, however, may also be
contributing to the decline. The black population of
The trend for Latinos, however, is different. Similar figures for
A significant portion of the increase in the Los Angeles Latino population has
been absorbed in overcrowded renter households. A 1988 city of
While shelter cost has improved for low income tenants in
More data on rent control and ethnic change are needed. But the fact remains
Another goal of the rent control ordinance was the protection of young
families with children. Between 1970 and 1980, the percentage of all households
that were families in
After nine years, the average household size of 1.86 persons has not changed.
On the other hand, the number of children in families has decreased. In 1979-80, there was an average of 1.8 children (under the age of 18) for households with children, whereas in 1987 this number had dropped to 1.3 children per household with children. Whether this decrease is due to declining fertility levels, as is generally true throughout the Los Angeles area, or to a lack of incentive by landlords of rent-controlled units to accept large families cannot be determined from the data. Among renter households that moved into their units after the rent control ordinance was passed in 1979,15.5 percent were families with children, almost the same percentage that had existed in 1979-80 (16.2 percent). Further, the distribution of incomes of families with children has also remained constant over the period. Therefore, on the face of it, there is no direct evidence of discrimination against families. Thus, while the rent control ordinance has not increased the proportion of families among the renter population, it may have helped to stem a decline that was occurring in Santa Monica prior to the rent control ordinance. However, it is possible that landlords are restricting household sizes more in rent-controlled units. More data on this will be necessary.
The proportion of the population who are elderly has increased significantly and appears to be a direct consequence of the rent control law. To see this, we have to examine changes in the age distribution of Santa Monica tenants. Figure 4 is a graph of the percentage of renters in each of five age groups for the 1979-80 and 1987 surveys. As the graph shows, in 1987, compared to 1979, there was a lower proportion under the age of 30, a higher proportion between the ages of 30 and 44, and a higher proportion age 65 and older. In other words, the 1987 renter population was, on average, older than the 197980 renter population; the differences were statistically significant (chi-square = 22.87 with 4 d.f.; p </= .001).(n16)
To explore this phenomenon more systematically, we constructed a model of the age distribution that would have been expected in 1987 if the 1979 renter population had merely stayed in place. If none of the renters who were living in Santa Monica in 1979 had moved, the only changes would have come about through births and deaths; children born in the eight-year period would have been added to households, while people who died would have been subtracted. In the model, no one is allowed to move out of the city nor is anyone allowed to move in. The goal of the model is to analyze the effect of the aging process on the population. Any differences between the "expected" population and the population actually enumerated are usually due to changes in net-migration (i.e., either more people moving into the city than moving out, or the opposite).
Using the HALLEY cohort component population model, we constructed a model of the proportional age distribution (i.e., the proportion of the population in each age group) that the 1987 renter population would have if there had been no migration since 1979 and if the birthrate had stayed essentially constant.(n17) Figure 5 is a graph of the actual age distribution compared to the distribution that would have been expected if there had been no migration and constant fertility. Figure 6 graphs the differences between the actual proportions of people in each age group and that expected if there had been no migration.
Three discrepancies emerge from these analyses. The most apparent is the higher-than-expected number of people in the age group 18 to 29 and the lower-than-expected number of people in age groups 30 to 44 and 45 to 64 (see Figure 6). Since Santa Monica is a city of renters, near the beach, one would expect a high influx of unmarried young people. After people get married and establish a family, they may find better job opportunities elsewhere, may find the size of rental units inappropriate, or may buy a house. Thus, one might expect that people would move out during their 30s and 40s. The data in Figure 6 suggest this.
A second discrepancy is the smaller-than-expected proportion of children under age 18. This finding was discussed in the previous section. The third discrepancy is a greater proportion of elderly people than expected. Santa Monica has been a desirable residential location for the elderly for some time. However, given the competition for rental housing in Los Angeles and the generally lower incomes of the elderly, one would expect there to be a decrease in elderly people. Part of the increase is due to the aging in place of tenants who were already in their units (the "expected" elderly population in the model), but part is due to new rentals to elderly persons. For example, 6.2 percent of the households that had moved into their units within the previous three years had an elderly person, age 65 and over, living in them. The fact that new rentals have been made and that there are more elderly than expected suggests that the rent control policy has been effective in keeping housing affordable for the elderly. This phenomenon contrasts with conditions in the city of Los Angeles where there has been a significant decline in the elderly renter population between 1977 and 1987, particularly on the west side of Los Angeles adjacent to Santa Monica; this decline started in the 1970s and has accelerated during the 1980s.(n18) Even though the city of Los Angeles has rent control, its law is less strict than Santa Monica's and has not prevented a decline in the elderly population. The Los Angeles rent control law allows vacancy decontrol, a five-year pass-through of capital improvements, and a permanent decontrol if capital expenditures exceed a certain level. The Santa Monica law has vacancy control and a 15-year pass-through of capital expenditures and does not allow permanent decontrol.
The findings from this study indicate that the 1979 Santa Monica rent control ordinance has fulfilled some, but not all, of its stated goals. On one hand, the community has not been destabilized. Length of tenure increased and the socio-economic makeup of the city has remained approximately the same. Lower-income tenants have gained proportionately more from the rent control law, realizing a significant reduction in their shelter cost. This is particularly true of elderly people; there has been a slight increase in the elderly tenant population in Santa Monica. The proportion of households with children has remained constant, though family sizes have declined. This result may be an additional benefit of rent control, and may represent the stopping of a decline in rentals to families before the law's enactment that may still be continuing in adjacent areas. On the other hand, there has been a decline in black and Latino tenants, a trend that started prior to the rent control law and that has continued.
Our results show that, in relation to the intent behind it, the Santa Monica rent control law has been most beneficial for low income households. There is no evidence to support the argument that rent control is providing a disproportionate benefit to middle- and upper-income groups. In cities like Santa Monica, where there is vacancy control, rent control appears to be effective in keeping many units affordable. Savings passed on to renters from such laws could be considerable, and could perhaps allow some people to accumulate enough in savings eventually to purchase their own homes.
Many of the economic arguments that have been raised against rent control take place in a theoretical "vacuum" where the effects of price control are seen as detrimental for the building of new rental units.(n19) Perhaps if rent control were the only price distortion affecting a housing equilibrium, then we might have found that it had a negative effect on the total rental stock. But, in reality, rent control usually emerges in tight and worsening housing conditions and in locales where the majority of the housing stock is renter-occupied. The Santa Monica law emerged under housing conditions where land speculation (rapid buying and selling of units) was occurring.
Given the current housing crisis in large urban areas, rent control should be viewed as one of a number of policy strategies that can be employed to improve the housing situation for selected target populations, specifically low--and moderate-income households. As a policy strategy, rent control does not directly address questions of expanded supply of affordable rental units and family-sized units, nor will it eliminate housing discrimination (it may actually provide an effective vehicle for some landlords to discriminate against minorities). Rent control is most effective at protecting those who have housing already. For these other housing problems to be solved, a number of different housing strategies focused on specific objectives and target populations would have to be developed. Such policy strategies should address questions related to financing, stimulating production of affordable units, obtaining a balance among unit sizes, yielding an appropriate geographic distribution, and avoiding housing discrimination. In short, rent control primarily has been a response to rapidly escalating rental rates, rather than a cause. The real problem is those factors affecting housing costs (e.g., land speculation, low vacancy rates, high interest rates, etc.), which lie well beyond the limited arena for landlord-tenant debates.
We believe it is fair to ask what the consequences of rent control are and whether rent control can improve the housing situation in urban areas today. Needless to say, other housing policies are rarely examined for their abilities to provide housing for the less advantaged members of our society. In uncontrolled markets, supply and demand are the governing factors underlying the pricing mechanisms for rental units, and in tight housing markets, like the Los Angeles area, rent increases have escalated rapidly. Rent control has been of limited success in protecting low income households, but market conditions may have been even less successful. Any housing policy that is developed must address these questions and must be subjected to the same empirical criteria applied to rent control. We cannot assume that market conditions will solve urban housing problems without some form of public intervention.
(n1.) A key factor in the analysis of rent control is the strength of the ordinance. Appelbaum and Gilderbloom (1988) categorize rent control ordinances into three types: restrictive, moderate, and strong. They have argued that all three types have little impact on the amount of investment in rental housing, though they do show differences in the effects on long-term rent levels, with the stronger ordinances leading to lower average rents. In particular, vacancy control measures appear to have the strongest impact in controlling rent levels.
(n2.) This method involves selecting telephone prefixes that cross the city and then generating random telephone numbers. Even though most numbers are not working or are businesses, the sample produced represents a random sample of households with telephones. Since a high proportion of the Santa Monica renter population have telephones (the 1980 Census documented 96 percent of all renter households having telephones), the method was appropriate for accurately estimating the characteristics of renter households. Details of the survey methodology can be obtained either from the authors or from the study report (Levine and Grigsby 1987). Supplemental interviewing efforts were undertaken for those households that did not speak English.
(n3.) There was a slight difference in the way these items were measured in the two surveys. The 1979 survey rounded off length of residence to the nearest year, whereas the 1987 survey calculated residence in exact years (e.g., 0 to 11 months is "0" years, 12 to 23 months is "1" year, etc.). This difference is not critical, especially in comparing groups of years.
(n4.) For example, the average number of years of residence for tenants within the city of Los Angeles increased by 1.93 years compared to 1.53 years for tenants in the surrounding non-rent-controlled cities. A more dramatic increase was seen for tenants residing in their units six or more years. In 1984 within Los Angeles, 34.1 percent of the renter population had lived in their units six or more years, compared to 22.9 percent of tenants in the surrounding cities that were studied.
(n5.) The 1980 Census indicated that the vacancy rate in Santa Monica was 1.7 percent (U.S. Bureau of the Census 1980). We don't have 1987 figures for the vacancy rate, but it appears to be low.
(n6.) Among tenants who moved in prior to 1979, 3.2 percent used a rental agency, compared to 8.6 percent who have moved in since 1984. It has been argued within the city of Santa Monica that rental agencies are required to gain entry and that significant "extra" payments must be made to such agencies. We found that three-quarters of those who used a rental agency paid a fee; the median fee was $50. While it has been frequently argued locally that prospective tenants need to go to rental agencies and pay a large fee to obtain units, our results do not support this.
(n7.) We also constructed a hedonic pricing model. It yielded a figure of $ 191 in savings due to rent control in Santa Monica. Such models raise methodological issues, the resolution of which are beyond the scope of this article. We decided to use the more conservative Consumer Price Index (CPI) variation test with the assurance that the hedonic model yields a larger savings figure.
(n8.) The April rent control law rolled back rents to the April 1978 level. In September 1979, a 7-percent increase was allowed, based on the April 1978 rent levels.
(n9.) We calculated this proportion by multiplying the monthly rent in 1987 by 12, and then dividing by the total household income in 1986. Even though the method is rough, it gives an indicator of the proportion of income spent on shelter.
(n10.) The figures are indeterminate for those at the very top of the distribution. In both the 1979 and 1987 surveys, there were households with an annual rent-to-income ratio greater than 1.00. We have truncated their shelter cost index to 1.00.
(n11.) We estimated expected household income by the equation
Y = $43,536 - $49,623*S
where Y is 1986 household income and S is the ratio of annual rent to household income (as a proportion). The R2 was 0.35.
(n12.) The figure for average shelter cost in 1979 was 34.2 percent, with a standard deviation of 30.7 percent; for rent-controlled units in 1987 the mean was 30.4 percent with a standard deviation of 23.1 percent. The difference is highly significant (t = 10.38, p </= 001).
(n13.) We also constructed Lorenz curves and Gini coefficients for both surveys (see Shryock and Siegel 1976). The Gini for 1979 was 0.3463, while the Gini for 1986 was .3646.
(n14.) Ten-percent increments were used because of insufficient numbers of income increments.
(n15.) Note: this "gentrification distribution" is arbitrary. We have calculated it by taking the average difference between rent-controlled and non-rent controlled units and adding it to the household income at each percentile. In 1986, the average income in non-rent-controlled units was $42,343, compared to only $27,473 for those in rent-controlled units; the small number of household not under rent control makes this difference uncertain.
(n16.) It should be noted that the increased proportion of elderly is a phenomenon occurring throughout the state. In 1985, for example, the state's elderly population comprised 10.8 percent of the population. By the year 2000 the proportion of the state's elderly population is expected to reach 12.3 percent, according to the State Department of Finance.
(n17.) See Levine (1985). The model assumed that survival rates would remain constant over the next ten years and that child-women ratios (the ratio of children, 0 to 4 and 5 to 9, compared to women, l 0 to 49) would remain stable. We assumed that there was no net-migration, neither people moving in nor out. This is a necessary assumption in order to examine the age distribution that would occur if there had been no migration. We can then compare this expected distribution with that actually observed to see in which age groups migration had the greatest effects.
(n18.) For example, the 1977 Annual Housing Survey of the Los Angeles area showed that 20 percent of the heads of renter households within the city of Los Angeles were aged 62 years or older. By 1984, this percentage had declined to 16 percent and by 1987 to 15 percent (Hamilton et al. 1984, 1988). Similar conclusions have been reached from an analysis of net migration trends in the city of Los Angeles between 1970 and 1980 (Grigsby, Levine, and Leavitt 1986).
(n19.) In a recent study, Baar and Squier (1987) examined both new construction and apartment sales in Santa Monica and nearby areas. They showed that new construction in Santa Monica since 1980 has been higher than in many coastal cities south of Santa Monica, which do not have rent control. They also showed that, from a sample of apartment buildings that had sold recently, Santa Monica units sold at a price about 12-percent lower than units from adjacent areas.
TABLE 1: Length of residence 1979-1987 (frequencies and
Percentage of 1979-80 survey 1987 survey
sample who had (in rounded years) (in exact years)
lived in unit n = 758 (%) n = 411 (%)
Less than 6
months 16.0 5.3
Less than 3 years 54.5 32.8
Less than 5 years 72.8 46.4
Less than 8 years 87.4 73.4
More than 10 years 9.2 19.6
OF RESIDENCE 3.9 6.2
Standard deviation (6.6) (4.5)
means (t-value) 6.9
chance p </= .001
TABLE 2: Various indicators of 1987 monthly rent levels (monthly
All units rent control
Indicator n = 384 n = 352
25-percentile $345 $335
50-percentile $444 $439
75-percentile $591 $571
90-percentile $734 $703
Average rent $508 $489
TABLE 3: Racial-ethnic distribution of renter population[a]
Race/ethnicity of survey 1987 survey
all household Percent
members n % n % change
White (non-Latino) 1,028 73.4 587 78.3 +4.9
Black 71 5.1 24 3.2 -1.9
Latino 249 17.8 99 13.2 -4.6
Islander 41 2.9 24 3.2 +0.3
Native American 11 0.8 6 0.8 +0.0
Other -- -- 10 1.3 --
1,400 100.0 750 100.0
[a.] Assuming that race/ethnicity of the respondent applies
to all household members.
GRAPH: FIGURE 1: Expected and actual rents, 1978-1987 expected on basis of residential rent CPI.
GRAPH: FIGURE 2: Shelter cost, 1979- 1987, annualized rent as a percentage of household income.
GRAPH: FIGURE 3: Household income percentiles, 1986, expected and actual for rent-controlled units.
GRAPH: FIGURE 4: Santa Monica renter age distribution, percentage of renter population in each age group
GRAPH: FIGURE 5: Modeling 1987 renters' age distribution, expected and actual percentage in each age group.
GRAPH: FIGURE 6: Migration tendencies of renters, actual minus expected percentages in each age group.
Appelbaum, Richard P. 1983. The Effects of Rent Control on the Santa Monica Rental Housing Market. Paper presented at the Lincoln Institute of Land Policy Colloquium on Rent Control. Cambridge, MA, November.
Appelbaum, Richard P., and John I. Gilderbloom. 1988. The Impact of Modern Rent Control on Landlords and Tenants. Typescript.
Baar, Kenneth. 1983. Guidelines for Drafting Rent Control Laws: Lessons of a Decade. Rutgers Law Review 35, 41: 721-885.
Baar, Kenneth, and Gary Squier. 1987. Perspectives on the Rental Housing Market in the Santa Monica Area. Report prepared for the Rent Control Board of the City of Santa Monica, August.
City of Los Angeles. 1979. Rent Stabilization Ordinance. Ordinance No. 152, 120. April 21.
City of Santa Monica. 1979. Rent Control Charter Amendment 1805.
Clark, W. A. V., and Allan David Heskin. 1982. The Impact of Rent Control on Tenure Discounts and Residential Mobility. Land Economics 58, 1: 109-117.
De Salvo, J. S. 1971. Reforming Rent Controls in New York City: Analysis of Housing Expenditures and Market Rents. Regional Science Association Paper, 195 227.
Devine, Richard J. 1985. Who Benefits from Rent Control? Oakland, CA: Center for Community Change.
Friedman, Milton, and George Stigler. 1981. Roofs or Ceilings? The Current Housing Problem. In Rent Control: Myths and Realities, edited by W. Block and E. Olsen. Vancouver, British Columbia: Fraser Institute.
Gilderbloom, John 1.1978. The Impact of Moderate Rent Control in the United States: A Review and Critique of Existing Literature. Sacramento, CA: California State Department of Housing and Community Development.
Grampp, William D. 1950. Some Effects of Rent Control. Southern Economic Journal 16, 4: 425-47.
Grebler, Leo. 1952. Implications of Rent Control: Experience in the United States. International Labour Review 65, 4: 462-85.
Grigsby, J. Eugene, III, and Mary L. Hruby. 1985. A Review of the Status of Black Renters, 1970-80. Review of Black Political Economy 13, 4: 77-91.
Grigsby, J. Eugene, III, Ned Levine, and Jackie Leavitt. 1986. City of Los Angeles Elderly Needs Assessment. Los Angeles, CA: The Planning Group.
Gyourko, Joseph, and Peter Linneman. 1985. Equity and Efficiency Aspects of Rent Control: An Empirical Study of New York City. Wharton School, University of Pennsylvania, Philadelphia. Typescript.
Hamilton, Rabinovitz, Szanton & Alschuler, Inc. 1984. Rental Housing Study Rent Stabilization System: Impacts and Alternatives. Prepared for the Los Angeles City Rent Stabilization Division.
------. 1988. 1988 Rent Stabilization Review. Prepared for the Los Angeles City Rent Stabilization Division.
Hayek, F. A. 1981. The Repercussions of Rent Restrictions. In Rent Control: Myths and Realities, edited by W. Block and E. Olsen. Vancouver, British Columbia: Fraser Institute.
Heskin, Allan David. 1983. Tenants and the American Dream: Ideology and the Tenant Movement. Praeger: New York.
Johnson, D. Gale. 1951. Rent Control and the Distribution of Income. American Economic Review 41, 2: 56985.
Kristof, Frank B. 1970. Housing: Economic Facets of New York City's Problems. In Agenda for a City. Issues Confronting New York, edited by L. C. Fitch and A. H. Walsh. Beverly Hills, CA: Sage.
Lavrakis, Paul J. 1987. Telephone Survey Methods: Sampling Selection and Supervision. Beverly Hills, CA: Sage.
Levine, Ned. 1985. The Construction of a Population Analysis Program Using a Microcomputer Spreadsheet. Journal of the American Planning Association 51, 4: 496-511.
Levine, Ned, and J. Eugene Grigsby III. 1985. A Survey of Tenants and Apartment Owners in West Hollywood. Report prepared for the City Council of the City of West Hollywood. The Graduate School of Architecture and Urban Planning, University of California, Los Angeles, April.
------. 1987. The Impacts of Rent Control on Santa Monica Tenants. Report prepared for the Rent Control Board of the City of Santa Monica. Los Angeles: The Planning Group.
Linneman, Peter. 1980. Some Evidence on the Functional Form of the Hedonic Price Function for Urban Housing Markets. Journal of Urban Economy 15: 129-48.
------. 1987. The Effect of Rent Control on the Distribution of Income among New York City Renters. Journal of Urban Economy 22: 14-34.
Olsen, E. A. 1972. An Econometric Analysis of Rent Control: An Empirical Analysis of New York's Experience. Journal of Political Economy 82: 1081-1110.
President's Commission on Housing. 1981. Interim Report. October 30, 1981. Washington, D.C.: Government Printing Office.
Roistacher, E. A. 1972. The Distribution of Tenant Benefits under Rent Control. Doctoral dissertation, University of Pennsylvania.
Shryock, Henry J., Jacob S. Siegel and Associates. 1976. The Methods and Materials of Demography, condensed edition. New York: Academic.
Shulman, David. 1981. Real Estimate Valuation under Rent Control: The Case of Santa Monica. AREUEA 9, 1: 38-53.
Sternlieb, George, James W. Hughes, and Connie O. Hughes. 1982. Demographic Trends and Economic Reality: Planning and Markets in the '80s. New Brunswick, NJ: Center for Urban Policy Research.
Temporary Commission on City Finances. 1977. The Effects of Rent Control and Rent Stabilization in New York City. Fifteenth Interim Report to the Mayors. New York: City of New York.
Tuchfarber, Alfred J., and William R. Klecka. 1976. Ran c Digit Dialing: Lowering the Cost of Victimization Surveys. Cincinnati, OH: University of Cincinnati Police Foundation.
U.S. Bureau of Labor Statistics, U.S. Department of Labor. Monthly Employment and Earnings. Monthly.
U.S. Bureau of the Census. 1970. Summary Tape File IA of the 1970 Census. Washington, D.C.: U.S. Department of Commerce.
------. 1980. Summary Tape File IA of the 1980 Census. Washington, D.C.: U.S. Department of Commerce.
------. 1987. Household and Family Characteristics. Current Population Reports, Series P. 20, No. 424, March 1987. Table 20, 108-111. Washington, D.C.: U.S. Department of Commerce.
J. Waksberg. 1978. Sampling Methods for Random Digit Dialing. Journal of the American Statistical Association 73, 361: 40-46.
Ned Levine, J. Eugene Grigsby III, and Allan Heskin
Levine is a lecturer in the Graduate School of Architecture and Urban Planning, University of California at Los Angeles. His research interests are planning information systems, social policy evaluation, and security planning. He also developed the HALLEY population analysis program. Grigsby is an associate professor in the Graduate School of Architecture and Urban Planning, University of California at Los Angeles. He earned his doctorate in urban sociology from UCLA in 1971. His research interests are social policy planning and urban impact assessment. Heskin is an associate professor and head of the urban planning program in the Graduate School of Architecture and Urban Planning, University of California at Los Angeles. He is the author of Tenants and the American Dream (Praeger, 1983), a book about the tenant movement in Los Angeles and Santa Monica.
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