Residential Attitudes and Choice: A Study of Housing Voucher Holders in Santa Ana, California

Transcription

1 Residential Attitudes and Choice: A Study of Housing Voucher Holders in Santa Ana, California A report prepared for the Santa Ana Housing Authority Victoria Basolo, Ph.D., AICP Department of Planning, Policy, & Design University of California, Irvine July 2003

2 Acknowledgements This report presents data from a study conducted by Dr. Victoria Basolo in collaboration with the Santa Ana Housing Authority. Without the cooperation and assistance of key personnel at the Housing Authority, the study would not have been possible. In particular, the contributions of Linda Foster and Destin Blais were invaluable. In addition, three students at the University of California, Irvine provided substantial assistance to the project. Mai Nguyen, a doctoral candidate in Urban and Regional Planning, offered advice on the survey instrument, helped with language translation, and managed a significant portion of the survey implementation including oversight of 10 undergraduate student assistants. George Avila, a master s student in Urban and Regional Planning assisted in communication with Spanish-speaking voucher holders, as well as translated the survey questionnaire into Spanish. Stan Bailey, an undergraduate student in Social Ecology, assisted with address verification and mapping associated with the project. The respondents to the survey deserve particular appreciation for spending time to complete the questionnaire. In addition, a number of voucher holders attended a focus group prior to survey implementation and graciously pretested a draft of the questionnaire. Finally, the U.S. Department of Housing and Urban Development (HUD) provided the major funding for the study. The research team is grateful for this support. It is important to note that the findings and interpretations within this report are solely the author s and do not necessarily represent the views of HUD. Any questions about the study or the contents of this report should be directed to: Professor Victoria Basolo Department of Planning, Policy, & Design School of Social Ecology University of California Irvine, CA basolo@uci.edu Phone:

3 TABLE OF CONTENTS I. Introduction.. 1 II. Methodology. 4 III. Study Context, Results, and Discussion The Study Area Results Socio-demographics Housing and Neighborhoods Residential Mobility Discussion. 25 IV. Summary & Conclusion.. 28 V. References.. 31 Appendix

4 LIST OF TABLES Table 1. Race and Ethnicity of Voucher Holders and the Wider Community. 8 Table 2. Gender, Marital Status, and the Presence of Children. 9 Table 3. Age by Employment Status. 11 Table 4. Annual Income by Employment Status Table 5. Housing Alternatives Without Section 8 Assistance.. 12 Table 6. Size of Household, Number of Bedrooms, and Contract Rent Table 7. Housing Satisfaction Table 8. Satisfaction with Selected Housing Characteristics.. 14 Table 9. Neighborhood Satisfaction 14 Table 10. Satisfaction with Selected Neighborhood Characteristics.. 15 Table 11. Use and Type of Daycare.. 16 Table 12. Distance to Daycare from Home. 16 Table 13. Distance to Daycare from Place of Employment 17 Table 14. Number of Moves in the Last 3 Years 17 Table 15. Mover and Non-Mover Satisfaction with Home.. 19 Table 16. Mover and Non-Mover Satisfaction with Neighborhood.. 19 Table 17. Main Reason for Planning to Move Table 18. Obstacles to Mobility Table A-1 Selected Characteristics of Concentrated Census Tracts Table A-2 Census Tract Changes for Movers Currently Living in Concentrated Tracts.. 35

5 LIST OF FIGURES Figure 1: Location of the City of Santa Ana... 6 Figure 2. Education Completed.. 10 Figure 3: Proximate Location of Section 8 Voucher Holders Figure 4: Proximate Location of Movers, Before Move Figure 5: Proximate Location of Movers, After Move.. 22

6 I. INTRODUCTION The Section 8 voucher program is the primary program for housing assistance to renters in the City of Santa Ana. It helps over 2,000 of the city s residents secure decent, affordable housing. Section 8 is a federal program operated through local housing authorities. Therefore, the funding originates, and the rules are designed by, the federal government and administered at the local level. For this reason, it is important to understand the goals of federal housing policy and the needs and constraints of local agencies and their clients. In terms of federal housing policy, significant change has occurred over the last three decades. For the Section 8 tenant-based program, major modifications have been made to the program rules in an effort to increase residential choice for recipients of housing vouchers. For example, under the Housing Choice Voucher Program 1 (Section 8), recipients now can pay more than fair market rent for a dwelling unit. The tenant, however, must pay the difference between the housing subsidy and the unit s rent. Second, the program removed barriers to interjurisdictional moves by voucher holders. Recipients now may move anywhere in the country with a local housing authority and retain their voucher assistance. 2 The voucher program, therefore, has the potential for lower-income persons receiving this assistance to improve their living conditions and experience higher levels of residential satisfaction. National policy continues to favor the Section 8 approach to housing assistance. As a market-oriented, demand-side approach to housing assistance, the program works within the private rental market and, as a result, overcomes several 1 2 Public Law merged the Section 8 certificate and voucher programs and administrative rules passed in 1999 provided clarification for program elements of the merged program, renamed the Housing Choice Voucher Program. Portability because a permanent feature of the voucher program in 1987 and later was extended to the certificate program (U.S. Department of Housing and Urban Development, 2000).

7 obstacles to the provision of housing for lower-income people. For example, this approach requires no public production of housing units and therefore, avoids the resistance to the placement of lower-income housing developments in communities. Furthermore, it removes government s responsibilities to manage and maintain public housing units. Finally, it is claimed that the Section 8 program increases residential choice, residential satisfaction, and the potential for economic advancement for recipients of this housing assistance. Related to these claims, the program is thought to help deconcentrate the poor, as well as minorities, receiving Section 8 assistance. For all these reasons, the program has garnered substantial support across the political spectrum. Administrative relief from site selection and management of public housing developments clearly is an advantage to the public agencies charged with providing lower-income housing assistance. However, the Section 8 program presents administrative burdens and also faces substantial obstacles in many housing markets. The administrative problems associated with Section 8 portability have been well documented, but complete solutions to these problems have not been included in the program s design (Basolo, 2003; Feins, et al., 1996). Furthermore, the supply of suitable Section 8 rentals in some housing markets, especially in higher cost areas, is simply too low to meet program needs. Moreover, since landlords do not have to accept Section 8, it is even more difficult in tight markets to find enough housing for lease to voucher holders (See Finkel and Buron, 2001). The Section 8 program has been shaped by many claims about the benefits associated with enhanced choice. Most of these claims remain unsubstantiated by research. Although recent studies have been conducted on mobility and vouchers, most of this research focuses on vouchering out of public housing tenants such as

8 the Moving to Opportunity Program 3 and the desegregation effort in Chicago initiated by the court rulings in the Gautreaux case. 4 A few recent studies have considered the regular voucher program. Findings from this research suggest that from a national perspective deconcentration occurs, but results vary according to region (Pendall, 2000; U.S. HUD, 2000). The limited research on the Section 8 program, especially in the western region of the U.S., as well as the questions about the benefits of mobility, present an opportunity to conduct valuable research on the Section 8 program. This report offers results from a study on the residential satisfaction and mobility of voucher holders within the jurisdiction of the Santa Ana Housing Authority in California. The remainder of the report is organized into four sections. The first section describes the study methodology. The second section describes the context of the study and presents the data results with accompanying discussion. The third section qualitatively interprets these results in the context of the claims made about Section 8 policy, as well as their import for the Section 8 clients and administering agency. Finally, the report concludes with a summary of the findings from the study. 3 4 The MTO program focuses on poverty deconcentration and involves tracking housing voucher holders moving from high poverty to low poverty neighborhoods over a 10-year period. The program operates in five cities and research on this program uses an experimental design using treatment and control groups. To date, research indicates mobility to higher income neighborhoods has some benefits, however, overall the results are mixed and it is too soon to evaluate long term effects (see Goering et al., 2002 for a summary of findings thus far). In 1966, public housing residents in Chicago filed a class action lawsuit against the Chicago Public Housing Authority and HUD charging racial discrimination in Chicago s public housing. Eventually, the case was heard in the U.S. Supreme Court, which found in favor of the public housing residents and ordered a remediation plan to promote racial desegregation of this population. The plan allowed volitional moves for poor, African-American, central city public housing residents to predominantly white, affluent suburbs. Researchers found that movers to the suburbs had higher levels of employment and their children had higher rates of high school graduation compared to households remaining in the central city (Rosenbaum, 1995; Rubinowitz and Rosenbaum, 2000).

9 II. METHODOLOGY The research is a cross-sectional study of residential satisfaction and mobility within the voucher population under the administrative jurisdiction of the Santa Ana Housing Authority (SAHA). The data come from three sources, including a mail survey of voucher holders, the SAHA database, and the U.S. Census Bureau. The survey design was guided by recommendations from Dillman (1978) and included five major elements aimed at optimization of the response rate. First, a draft questionnaire was reviewed by housing authority staff and pretested on voucher holders from two housing authority jurisdictions. This step provided feedback on the effectiveness of questions and reasonableness of response time. Using suggestions received from this process, we modified a few questions and response categories to increase clarity. The questionnaire included queries about actual and planned moves, individual socio-demographics, and perceptions and attitudes about living environments. 5 Second, the survey introduction letter was co-developed and cosigned by the researcher and a housing authority manager. Third, due to the known ethnic mix in the population, the letter included a description of the study and instructions in three languages: English, Spanish, and Vietnamese. The questionnaire was translated into Spanish and Vietnamese for respondents requesting it in these languages. Fourth, the housing authority client database served as the sampling frame and the sample was drawn directly from this source. 6 Fifth, non-respondents received multiple follow-ups encouraging their participation in the study. The study population consisted of 2,558 voucher holders within the jurisdiction of the Santa Ana Housing Authority. A random sample of 830 voucher holders was 5 6 A copy of the questionnaire is available from the author. The database contained the names and addresses of Section 8 voucher holders. To gain access to the list, the researcher agreed to procedures to maintain anonymity of respondents and to ensure security of the data.

10 selected from the population. The mail survey was conducted in Spring Completed questionnaires were received over a four-month period. Each questionnaire was logged by a tracking number and then responses were input into a data base by trained research assistants. Data input was checked using two methods. Research assistants verified the data input through a spot check of the data base against original questionnaires and the lead investigator ran descriptive analyses to check for any values inconsistent with the questions and response categories. Four hundred and sixty-seven (56.3%) of the voucher holders returned a completed questionnaire. While this response is good for a mail survey, it could be non-representative of the population as the respondents could differ from non-respondents in a systematic manner. To assess this possibility, we compared respondents to non-respondents. Movers were over represented in the final sample and response was more likely as age and contract rent increased and less likely with increases in income. 7 Therefore, the results may not be representative of the voucher holder population in Santa Ana. The client database contained information on residential location, race and ethnicity, gender, age, contract rent, and income. Using the addresses provided by the housing authority, corresponding neighborhood data was extracted at the census tract level from Summary Files 1 and 3 of Census These two secondary sources of data were joined to the survey data. 7 The response bias test, a logistic regression with response (yes=1, no=0), produced non statistically significant coefficients for ethnicity (Hispanic or not), race (black, Asian, white or not), children under 18 present in the home, and gender.

11 III. STUDY CONTEXT, RESULTS, & DISCUSSION The context of the study, particularly the housing market and population dynamics in the study area, is important to understanding the results from the research. For this reason, this section begins with a brief demographic overview of the study area, followed by the key survey results and a discussion of the findings. 3.1 The Study Area The voucher holders fall within the jurisdiction of the City of Santa Ana Housing Authority. The City is located in the northern section of Orange County, California, a relatively low-density suburban county located directly south of Los Angeles County (see Figure 1). Figure 1. Location of the City of Santa Ana

12 The regional housing market is a major contextual element that must be acknowledged in this study. Orange County is among the most expensive areas in the country for ownership (National Association of Home Builders, 2002) and rental housing. HUD recognizes the high rental costs in the area through its determination of Fair Market Rent (FMR), which is set at the 50 th percentile in Orange County, instead of the typical 40 th percentile 8 (U.S. Department of Housing and Urban Development, 2002). Furthermore, according to a report by the National Low Income Housing Coalition (2002), Orange County ranked in the top ten least affordable metropolitan statistical areas for rental housing. This report concludes that a worker in Orange County must make $22.21 an hour to afford the FMR on a two-bedroom housing unit. 9 Santa Ana is the most populous city in Orange County and the ninth largest in population in the State. In 2000, Santa Ana had a total of 337,977 persons, an increase of 15.1% since 1990, and a population density of 12,451.9 persons per square mile of land area (U.S. Bureau of the Census, 2002). The increase in population was accompanied by significant demographic change, which resulted in a very different demographic profile compared to Orange County as a whole. For example, the Hispanic population grew by 34.3% in the 1990s 10 and now comprise over three-quarters of the population in the City. However, this ethnic group represents less than one-third of the County s population. The racial/ethnic composition of the study s voucher sample does not mirror either the City or County. Although the total number is small, African-Americans constitute a larger proportion of Only 39 areas in the country have FMR set at the 50 th percentile. The study found, that for the nation as a whole, the median wage would need to be $14.66 an hour to afford a two-bedroom home at FMR. Note that California s minimum wage is $6.75 an hour, making it one of nine states with minimum wage set above the federal level ($5.15/hr.). This figure was computed using 1990 and 2000 Census data. It is important to note that, in 2000, the U.S. Census Bureau modified its question on Hispanic/Latino ethnicity from the earlier Census. Therefore, the numbers are not directly comparable between the two years and should be considered only a rough estimate of the change in the percentage of Latinos in the community.

13 the sample than found in the City and County, and Hispanics represent only one-third of the sample (see Table 1). 11 Table 1. Race and Ethnicity of Voucher Holders and the Wider Community Race/Ethnicity # % Santa Ana 1 Orange County 1 African-American % 1.7% 1.7% Asian % 8.8% 13.6% White % 42.7% 64.8% Other % 46.8% 19.9% Total % 100.0% 100.0% Ethnicity Hispanic % 76.1% 30.8% Non-Hispanic % 23.9% 69.2% Total % 100.0% 100.0% 1. U.S. Census Bureau, Census 2000, SF The race and ethnicity data come from the housing authority's client database. These categories are slightly different than the selections offered in Census For example, other categories, such as more than two races, could be selected in Census The population of Santa Ana is also much poorer, on average, than Orange County as a whole. In 1999, the median household income in Santa Ana was $43,412, over $15,000 less than the County s figure for that year. In addition, Santa Ana s poverty rate at 19.8% in 1999 exceeded the County rate of 10.3% by more than nine percentage points Unless otherwise noted, all the results in this report reflect responses from the full 467-person response sample. Santa Ana s residents, on average, are also worse off economically compared to the State as a whole. The City s median household income in 1999 was about $4,000 less than the State s figure, and Santa Ana s poverty rate exceeded the State s rate by more than five percentage points (U.S. Bureau of the Census, 2002).

14 3.2 Results The data include a wide range of information including socio-demographic characteristics of the sample, objective and subjective indicators about the respondents housing and neighborhoods, and respondents recent and planned residential mobility. The results are presented using these general topic areas Socio-demographics The first set of results concern the composition of the study s response sample. A majority of the respondents (73.7%) are immigrants (foreign-born). Asians comprise nearly 50% of the voucher holder population in Santa Ana, followed by Whites (44.5%), and African-Americans (6%). Hispanic ethnicity was reported by 33% of the survey respondents (see Table 1 in the previous section). Table 2. Gender, Marital Status, and the Presence of Children Gender # % Females Males Total Marital Status # % Married Unmarried Total Presence of Children # % Children present No children present Total Table 2 displays the distribution of respondents by gender, marital status, and the presence of children in the household. A majority of the respondents were women

15 (58.7%) and over half of the respondents were married (50.3%). Children were present in 50.1% of the respondents households. 13 Two hundred and thirty-one of the respondents (49.5%) had a high school degree 14 or at least some college. However, a relatively large proportion of the survey respondents (18.4%) had less than a 6 th grade education. Another 32.1% had completed at least 6 th grade, but had not received a high school diploma or its equivalent (See Figure 2). Figure 2. Education Completed 24.0% 2.8% 0.6% 18.4% 32.1% 22.1% < 6th grade 6th grade but < high school High school Some college 4 yr college degree Master's degree or higher The respondents ranged in age from 23 to 90 years old. The mean age of the sample was 55 with a standard deviation (s.d.) of Table 3 indicates that 27.6% of the respondents were age 65 years or older. Table 3 also shows employment status by age. One hundred and eighty-eight of the voucher holders in the sample (40.3%) were employed; however, the percentage of employed respondents under 65 is considerably higher (53.3%) In the housing authority files, voucher holders claim the number of dependents in the household. This information is used as a proxy for the presence of children. This figure includes high school equivalence (e.g., the GED).

16 Table 3. Age by Employment Status Employed Unemployed Total Age # Row % # Row % # Row % Under 65 years of age years and over Total Table 4 displays the descriptive statistics for annual income of respondents. The mean income of all respondents was $16, (s.d.=$8,944.41). Employed respondents as a group had a higher average income (mean=$19,871.78; s.d.= $9,585.55) than unemployed respondents (mean=$13,656.17; s.d.=$7,529.28). The distribution of the income data was skewed positively. That is, many values appear at the lower end of the distribution, while a few, relatively extreme values appear at the upper end. Therefore, while the mean is an important measure of central tendency, the median may be a better measure for characterizing these income data. For this reason, the median is also included in Table 4. Table 4. Annual Income by Employment Status Income Employed Unemployed Total sample Mean $19, $13, $16, Standard deviation $9, $7, $8, Median $18, $11, $15, In addition to the typical socioeconomic statistics, this study gathered information on the relatively recent housing circumstances of the Section 8 voucher holders and their likely living circumstances without housing assistance. Clearly, all voucher holders are currently housed, however, the survey asked if a respondent had been homeless in the last five years. Eighteen (3.9%) of the voucher holders responded affirmatively to this question (n=456). However, when asked their likely

17 housing circumstances if they were to lose their Section 8 vouchers, over 17% of the respondents (n=426) thought they would be homeless (see Table 5). The modal response to this question was move to less expensive housing in Orange County (31.7%). Another 5.9% of the respondents said they would move to less expensive housing outside of Orange County. Moving into someone else s house was a common response and included moving in with family (20%), friends (4%), and others who are not family or friends (12.4%). Table 5. Housing Alternatives Without Section 8 Assistance Housing Alternatives # % Move to less expensive housing in Orange County Move in with family Become homeless Move in with others, not family or friends Move to less expensive housing outside Orange County Move in with friends Other Total * *Does not sum to 100% due to rounding Housing and Neighborhoods The second set of results includes objective data about the respondents housing, as well as the respondents attitudes about their housing and neighborhood. Respondents households included about three persons, on average. The mean number of bedrooms in respondents homes was about two, while the mean contract rent was approximately $974 (see Table 6). Table 6. Size of Household, Number of Bedrooms, and Contract Rent Characteristics Mean s.d. Number living in home Number of bedrooms Contract rent $ $253.09

18 Next, the report presents the results from attitudinal questions about the home and respondents subjective assessments about a number of neighborhood qualities. The survey asked respondents to identify their level of satisfaction with their housing using a seven-point scale ranging from very dissatisfied to very satisfied. As shown in Table 7, the voucher holders in the sample tended to have high levels of housing satisfaction. Almost 49% of the respondents reported being very satisfied with their housing and another 36.6% responded they were somewhat satisfied with their housing. Only 6.7% of the respondents experienced any housing dissatisfaction. Table 7. Housing Satisfaction Satisfaction level # % Very satisfied Somewhat satisfied Neither satisfied or dissatisfied Somewhat dissatisfied Very dissatisfied Total The voucher holders in the sample rated four housing characteristics on a scale from one to ten with one being very dissatisfied and ten being very satisfied. Table 8 presents the mean of responses for satisfaction with the size of the home, the physical condition of the dwelling unit, the affordability of the unit, and relations with the landlord. 15 The mean for each characteristic exceeds seven, which is well above the midpoint on the satisfaction response scale (midpoint=5.5). Therefore, respondents, on average, were relatively satisfied with all four characteristics of their home. 15 The relationship with the landlord is included as a characteristic of the dwelling unit because, for renters, the landlord is attached to the house and may influence the renter s feelings toward the home.

19 Table 8. Satisfaction with Selected Housing Characteristics Characteristics Mean s.d. Size Physical condition Affordability Relations with landlord Respondents were slightly less satisfied with their neighborhoods compared to their housing. About 82% of the respondents were either very satisfied or somewhat satisfied with their neighborhoods, while 7.5% of the respondents reported some level of dissatisfaction (see Table 9). Table 9. Neighborhood Satisfaction Satisfaction level # % Very satisfied Somewhat satisfied Neither satisfied or dissatisfied Somewhat dissatisfied Very dissatisfied Total The questionnaire asked respondents to evaluate 11 neighborhood characteristics on a scale from one to ten with one being very dissatisfied and ten being very satisfied. The responses are shown in Table 10. Proximity to friends had the lowest mean value (6.68 with a s.d. of 2.29) of the 11 characteristics. 16 Access to public transportation was rated the highest among the characteristics with a mean of 16 Note that this value most likely means that respondents would be more satisfied if their friends were closer in proximity to their current neighborhood. However, it also could mean that friends are close by, and respondents desire more distance from them.

20 8.24 (s.d.=1.91). 17 Overall, respondents appear to be more satisfied than dissatisfied with their neighborhoods. Table 10. Satisfaction with Selected Neighborhood Characteristics Characteristics Mean s.d. Physical conditions of homes Cleanliness Safety Relations with neighbors Quality of public schools Access to shopping Access to public transportation Access to parks Proximity of job Proximity to family Proximity to friends Only 321 respondents answered this question. Some households have other circumstances that may affect their residential satisfaction and location decision. The need for daycare, for example, is important for many families with young children. Ninety-eight respondents (21%) reported the use of daycare. Of these respondents, the majority relied on social networks, a friend/neighbor (21.4%) or family (35.7%), for their daycare (see Table 11). 17 Ironically, however, only 4.1% of the respondents (with 197 responding) reported using public transportation to travel to work and 15% of the voucher holders (with 467 responding) responded that they used public transportation for shopping trips (full results for the transportation mode to work and shopping questions are not included in this report, but are available from the author).

21 Table 11. Use and Type of Daycare Type # % Licensed facility Unlicensed facility Nanny Friend/Neighbor Relative Other Total In general, most daycare locations were near the respondents homes. In fact, 53.1% of the respondents reported that their daycare was less than one mile from their residence. Another 33.7% of the respondents used daycare within one to five miles of their homes (see Table 12). Of the respondents who were working and used daycare, 14.5% said their daycare was within one mile of their place of employment, while another 33.9% used daycare within one to five miles of their job (see Table 13). Only three respondents used daycare that was ten or more miles from both their homes and jobs (not shown in tables). These three voucher holders used a relative for daycare. Table 12. Distance to Daycare from Home Distance # % <1 mile miles >5 but <10 miles or more miles Total * *Does not sum to 100% due to rounding.

22 Table 13. Distance to Daycare from Place of Employment Distance # % <1 mile miles >5 but <10 miles or more miles Total Residential Mobility As mentioned in the introduction to this report, voucher holders have the option to live outside the jurisdiction of the housing authority issuing the voucher. The data from the survey reveal that 66% of the voucher holders in the response sample live within the City of Santa Ana and 100% live in Orange County (see Figure 3). They also show that nearly all the mobility in the last three years (>99% of the response sample) occurred within the County. The moving behavior of respondents was a key area of interest for this study. As shown in Table 14, almost 44% of the response sample moved in the last three years. About 24.5% of respondents who had moved had done so more than once. In other words, 44 respondents in the response sample reported multiple moves over the last three years ( ). 18 Table 14. Number of Moves in the Last 3 Years Number of moves # % Zero One Two Three or more Total Recall that movers were over represented in the response sample.

23 Figure 3. Proximate Location of Section 8 Voucher Holders 19 Movers and non-movers experienced varying levels of housing and neighborhood satisfaction. 20 As shown in Table 15, more movers were very satisfied with their homes (51.2%) compared to non-movers (46.9%); however, dissatisfaction levels (combined somewhat dissatisfied and very dissatisfied responses) were similar between the two groups (6.4% and 6.9% respectively). The same general pattern emerges from the data on neighborhood satisfaction (see Table 16). Almost All figures concerning voucher holders residences show proximate locations; the scale of the dots purposely masks exact locations of voucher holders for confidentiality purposes. In addition, all dots are not totally revealed due to voucher holders proximities to each other i.e. some of the dots overlap. For voucher holders reporting multiple moves in the last three years, the responses for previous residence in the remainder of this section pertain to the last residence prior to the current home.

24 48% of the movers were very satisfied with their neighborhood, while the very satisfied category was chosen by 40.5% of non-movers. Nearly 8% of the movers experienced some level of dissatisfaction, as did 7.2% of the non-movers. Table 15. Mover and Non-Mover Satisfaction with Home Mover Non- Mover Satisfaction level # % # % Very satisfied Somewhat satisfied Neither satisfied or dissatisfied Somewhat dissatisfied Very dissatisfied Total Table 16. Mover and Non-Mover Satisfaction with Neighborhood Mover Non- Mover Satisfaction level # % # % Very satisfied Somewhat satisfied Neither satisfied or dissatisfied Somewhat dissatisfied Very dissatisfied Total Does not sum to 100% due to rounding error. When only considering movers, the results of changes in satisfaction levels reveal an improvement in general housing and neighborhood satisfaction pre-move versus post-move. The satisfaction questions are a subjective assessment by the respondents and are important for capturing their perceptions about their living environments. However, it is also worthwhile to consider more objective indicators of the effects of moving. While data on individual housing units of the respondents are unavailable from this study, neighborhood indicators from the Census 2000 offer some

25 interesting results. Basolo and Nguyen (2003) analyzed the survey data from this study in conjunction with neighborhood data from Census Their analysis reveals that movers experienced significant improvements between their previous and current neighborhoods. 22 Their results show that, on average, current neighborhoods compared to previous neighborhoods had the following: Lower densities (persons per square mile of land area) Lower unemployment rates Higher median household incomes Lower poverty rates Higher housing values Lower percentage of overcrowded units Lower percentage of dwelling units lacking complete plumbing It should be noted that voucher holders median contract rent and their neighborhood conditions are related. That is, the research described above found that voucher holders living in better conditions paid more in rent. At the same time, while Basolo and Nguyen (2003) found that movers paid more in rent than non-movers, on average, and movers paid more for their new housing units compared to their previous units, these differences were not statistically significant. 23 In addition to considering the perceptions of movers and the neighborhood indicators, this research examined the geographic distribution of movers, pre-move and post-move, to determine if moves by voucher holders resulted in their spatial deconcentration. 24 Figures 4 and 5 show the proximate locations of voucher holders, The neighborhood is defined as the census tract in their analysis. Their analysis consists of a series of difference of means tests (t-tests) with a p-value of.05 as the criterion for statistical significance. The authors also consider the difference in neighborhood conditions by race and ethnicity. These results are available from the authors. These results are based on difference of means tests (t-tests) with a p-value of.05 as the criterion for statistical significance. This analysis considers only movers. It is possible that movers located in a neighborhood with a high number of non-moving voucher holders and thus, remain spatially concentrated with other voucher holders. However, the improvements shown in the neighborhood indicators suggest otherwise.

26 before and after their moves. A comparison of these two figures clearly suggests that moving resulted in deconcentration of this subset of the sample. In other words, movers tended to be less clumped together spatially after their moves. The Appendix includes additional data and analyses about movers currently living in neighborhoods with comparatively higher proportions of voucher holders. Figure 4. Proximate Location of Movers, Before Move

27 Figure 5. Proximate Location of Movers, After Move Respondents also reported on their plans to move. Ninety-eight respondents (21%) planned to move within a year; only four of the voucher holders planned moves outside of Orange County. Respondents identified a number of reasons for planning to move; however, when asked the main reason for their moving plans, the modal response, selected by 23 of the 83 voucher holders answering this question (27.7%), was want a bigger home. Other relatively common reasons for planning a move included wanting a home in better physical condition (13.3%), wanting a more affordable home (9.6%), wanting a safer neighborhood (7.2%), wanting to live closer to family members (7.2%), and experiencing a problem with the landlord (6.0%). The

28 number of respondents citing another reason was relatively low with the next largest category chosen by less than 4% of the voucher holders responding to this question (see Table 17, wherein all other reasons are collapsed into the other category). Table 17. Main Reason for Planning to Move Reasons # % Want a bigger home Want a home in better condition Want a more affordable home Want to live closer to family Want to live in a safer neighborhood Experiencing problems with the landlord Other Total * *Does not sum to 100% due to rounding. Mobility and the desire for mobility are fairly prevalent among the voucher holders in the response sample. However, moving may be inhibited by the conditions within the regional housing market and also by a mover s personal circumstances. The Orange County region is known for its high housing costs as discussed previously in this report. These costs are a reflection of several factors including: 1) the region s desirability (e.g., good year round weather, employment opportunities, nearby amenities such as recreation and entertainment venues); 2) a severe undersupply of housing (see Landis et al., 2000); and 3) a low vacancy rate (3.5%). In addition to market conditions, a potential mover s personal circumstances may affect mobility decisions. A residential move, for example, can be difficult or undesirable due to an individual s budget constraint, as well as her stage in the life cycle (age, marital status, children etc.).

29 The respondents in this study are special, because, by definition, they are lower-income individuals and therefore, have substantial budget constraints. In addition, the Section 8 program requires the completion and processing of much paperwork, as well as standards concerning the reasonableness of rent costs and the physical conditions of the unit. Furthermore, a landlord is not required to rent to a Section 8 voucher holder. Given these various influences on residential (re)location decisions for the population under study, the voucher holders may perceive barriers to mobility that are not typically considered in studies of the general population. Therefore, the survey asked respondents about several potential obstacles to their residential mobility. The biggest obstacle to moving appeared to be the lack of housing units available for rent. Sixty-two percent of the respondents identified this problem. Over 46% of the respondents perceived that landlords did not want to rent to Section 8 voucher holders (n=442). It is possible that respondents conflated these two questions such that a lack of available housing units was due to the unwillingness of landlords to rent to Section 8 program clients. However, a chi-square analysis indicates that there is no association between these two responses (X 2 =0.003, p=0.95). Table 18. Obstacles to Mobility Obstacle #* %* Too few homes to rent Landlords won't rent to Section Too much paper work Paper work is confusing *Number and percentage responding yes (n=442).

30 In addition to the problems mentioned above, some respondents found the administrative paperwork overwhelming. Slightly more than 17% of the respondents thought there would be too much paperwork in making a move, while 10.6% thought the paperwork would be too confusing (see Table 18). 3.3 Discussion The study results show that the voucher holder sample is very diverse in terms of age, gender, marital status, race, and ethnicity. A majority of the respondents under 65 years of age were working and the median income for this group was slightly higher than the median for the group of voucher holders as a whole. However, the common denominator for the respondents is their low-income status, and therefore, their need for publicly assisted rental housing. As the data reveal, without the housing subsidy, over half of the respondents thought they would be homeless or have to double up with others. Clearly, the Section 8 program is important in reducing social problems such as homelessness and overcrowding, as well as enhancing the voucher holders quality of life. Voucher holders expressed fairly high levels of housing and neighborhood satisfaction in general. On all specific satisfaction indicators, respondents, on average, exceeded the mid-value on the satisfaction scale by a full point (on a 10- point scale) and most values were more than two points above the mid-value. This result indicates that, for the most part, voucher holders in the sample have secured housing in neighborhoods that meet their needs. Despite high levels of residential satisfaction, over one-fifth of the respondents were planning a move within a year. The most often cited reason for the proposed move was a desire for a bigger home. While the sample, on average, was satisfied with the size of their home, this result reveals that a number of the voucher holders are dissatisfied with the size of their

31 current home and will be pursuing a larger home in the near future. This finding suggests an unmet demand for larger rental units in the regional housing market. A substantial portion of the response sample had moved in the three years prior to the survey. Voucher holders who had moved in the last three years were more satisfied overall with their housing and neighborhoods than voucher holders who had not moved. Moreover, movers generally were more satisfied with their current living environments compared to their previous ones. This finding is important because it suggests that the first element of residential choice policy, mobility, provides voucher holders with an opportunity to improve their living environments. However, at least two issues must be considered before concluding that mobility is the ultimate answer. First, the data from this study show that voucher holders living in better housing and neighborhoods tended to pay more in contract rent for their dwelling unit. Given the lower incomes of Section 8 recipients and the concomitant constraints on their housing budgets, the price for better conditions may be a substantial burden for these households and may result in many Section 8 recipients foregoing other needs in order to divert a larger proportion of their income to rent. Second, even if voucher holders choose to spend more of their income on housing, the data show that the better housing in more desirable neighborhoods may not be available for rent due to a lack of rental housing supply overall, as well as the unwillingness of landlords to rent to Section 8 voucher holders. The survey results reflect only the respondents perceptions of obstacles to mobility. However, during the course of the study, the research team found some evidence, albeit anecdotal, that landlords are reluctant to rent to Section 8 households. Moreover, this propensity to refuse renting to Section 8 program participants may be unevenly distributed across the region. The perception of a

32 limited housing supply is consistent with the objective indicators presented in this report. That is, Orange County has a relatively low housing vacancy rate and therefo re, there is strong competition for available rental units. If respondents have accurately perceived the added difficulty of landlords tending to reject Section 8 for their properties, then voucher holders can be expected to have substantial problems finding and securing rental units in more desirable neighborhoods. This finding clearly indicates major obstacles to mobility for this population. Overall, the data show that the Section 8 program in Santa Ana is effectively meeting the housing needs of many lower-income households. However, budget limitations within this population and the housing supply constraints within the Orange County regional market do not bode well for continuing success of this program. Additional housing construction, particularly rental units, is needed to meet the housing needs of voucher holders. Construction of housing units has not been a function of the Santa Ana Housing Authority and it is unlikely that housing development will be pursued in the near future by this agency. However, the City of Santa Ana and its housing authority should continue, and strengthen, their relationships with for profit and nonprofit housing developers, as well as other local governments in Orange County. In the former case, the City can help developers in many ways, including regulatory relief and subsidies to leverage existing sources of funding such as the Low Income Housing Tax Credit program, and the recently recapitalized, State managed Multi-family Housing Program. 25 For the latter, local governments need to cooperate on housing issues for two reasons. First, the housing market is regional and good planning that works towards multiple housing opportunities across jurisdictions acknowledges the market s operating environment. 25 The passage of a ballot measure in 2002 provides substantial funding for housing programs, particularly affordable multi-family development.

33 Second, HUD, the funding agency for Section 8, favors deconcentration of voucher holders, especially if they are living in poor neighborhoods, through mobility of the benefit, and also encourages cooperation among local housing authorities. In fact, when evaluating local housing authorities, HUD considers deconcentration of lowerincome households, as well as regional cooperation among housing authorities. Many other reasons exist for local jurisdictions to address the undersupply of rental housing. For example, lack of decent rental opportunities could lead to (more) overcrowding and homelessness in the region. These conditions undermine the chances of individuals to provide adequately for themselves and their dependents. In addition, increased homelessness creates additional demand on social service providers, and a higher level of overcrowding places additional stress on the physical infrastructure. In sum, federal (and many local) policies continue to favor rent subsidies such as Section 8 over many other strategies. In addition, federal policy encourages deconcentration to improve living environments for lower-income people, as well as to ameliorate certain social problems. In Santa Ana, this study shows that mobility appears to reduce voucher concentration and result in an improvement in housing and neighborhood satisfaction for voucher holders. However, undersupply of rental units in the regional housing market suggests that improved residential satisfaction through intra-regional mobility has some very real limits. IV. SUMMARY & CONCLUSION This study examined a sample of voucher holders under the administrative jurisdiction of the Santa Ana Housing Authority. The primary data from the study were collected via a mail survey, and then combined with existing data from the Authority s client files and tract level data from Census The final dataset

34 contains socio-demographics on the voucher holders, objective and subjective assessments of the voucher holders living environments, including residential conditions and satisfaction levels, and information on voucher holders planned and actual mobility. Descriptive analyses of the data reveal a racially/ethnically diverse voucher population. The sample had more women than men and the average age of respondents was 55 years. Married respondents comprised about one-half of the sample, as did individuals reporting the presence of a child in the household. Slightly less than half the sample had completed high school. Voucher holders, on average, had relatively high levels of housing and neighborhood satisfaction, in general, as well as on individual indicators. Respondents who had moved within the last three years tended to have higher levels of satisfaction than non movers and were more satisfied with their current housing and neighborhoods than their previous living environments. Considering both subjective responses and objective indicators from Census 2000, voucher holders generally lived in better neighborhoods after a move. The study shows that mobility assisted in the deconcentration of voucher holders in neighborhoods. That is, the geographic pattern, before and after mobility, exhibits less spatial clustering among voucher holders. However, despite moving, some Section 8 households continue to live in disadvantaged neighborhoods as measured by a number of indicators including unemployment, income, and poverty. Voucher holders perceived two major obstacles to mobility. First, a lack of available dwelling units for rent was identified most frequently as an obstacle to mobility. Second, voucher holders reported that landlords tend to be unwilling to rent to Section 8 households. The perception of an undersupply of rental housing in the