Effect of Neighborhood Racial and Socioeconomic Composition on Urban Residents' Evaluations of Their Neighborhoods

Effect of Neighborhood Racial and Socioeconomic Composition on Urban Residents'Evaluations of Their NeighborhoodsAuthor(s): Brian Stipak and Carl HenslerSource: Social Indicators Research, Vol. 12, No. 3 (Apr., 1983), pp. 311-320Published by: SpringerStable URL: http://www.jstor.org/stable/27521104 .

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BRIAN STIPAK AND CARL HENSLER

EFFECT OF NEIGHBORHOOD RACIAL AND SOCIO

ECONOMIC COMPOSITION ON URBAN RESIDENTS'

EVALUATIONS OF THEIR NEIGHBORHOODS*

(Received 18 October, 1982)

ABSTRACT. Using merged survey and census data from Los Angeles and Detroit, this

study investigates the effect of neighborhood racial and socioeconomic composition on

urban residents' evaluations of their neighborhoods. The findings show that all types of residents - both black and white, low income and high income - evaluate lower

income and higher minority areas more negatively. Aversion to low income and high

minority areas does not appear to result from class and racial prejudice, but rather

from undesirable neighborhood characteristics.

How people react to living in different types of sociodemographic neighbor hoods is an important question for urban policy and public housing policy. Political discussions commonly assume that racial prejudice plays an important role in determining locational preferences and promoting white flight to the

suburbs. On the other hand, since the racial and the socioeconomic composi tion of neighborhoods are usually related, what appears as a reaction to racial

composition might actually result from socioeconomic preferences. This

paper examines the effect of neighborhood racial and socioeconomic composi tion on people's reactions to their neighborhoods.

Findings from some existing research do warn against overemphasizing the role of racial prejudice in determining neighborhood satisfaction. Survey results show, for example, that most blacks say they prefer integrated neigh borhoods to all black neighborhoods (Farley et al., 1979, p. 104; Pettigrew,

1973, p. 44), and Little (1976) found an important independent effect on

housing preferences due to neighborhood income. On the other hand, Camp bell (1981, p. 155) ascribed an important role to racial preferences by specu

lating that satisfaction blacks derive from living in black areas counteracts

the effect of living in low income neighborhoods. This research addresses these issues by attempting to estimate the separate

effects on urban residents' evaluations of their neighborhoods attributable

to (1) neighborhood racial composition, (2) neighborhood socioeconomic

composition, and (3) the race and socioeconomic characteristics of the in

dividual resident} Naturally, it is necessary to include individual-level variables

Social Indicators Research 12 (1983) 311-320. 0303-8300/83/0123-0311$01.00

Copyright ? 1983 by D. Reidel Publishing Co., Dordrecht, Holland, and Boston, U.S.A.



312 BRIAN STIPAK AND CARL HENSLER

in the analysis, since different types of respondents tend to provide different

neighborhood evaluations, ceteris paribus, because of different expectations,

standards, preferences, or general evaluative predispositions. For example, the

tendency for blacks to express less satisfaction than whites with their neigh

borhoods, communities, and local services (Campbell et al., 1976, Ch. 7;

Marans and Rodgers, 1975; Schuman and Gruenberg, 1972) could result from

differences in black evaluative proclivities, as well as from differences between

blacks and whites in their neighborhoods, communities, and services. Also, this research examines for possible interactions between the individual-level

and neighborhood-level characteristics, since racial prejudice would make

blacks and whites respond in opposite ways to neighborhood racial composi tion. Similarly, class prejudice would make low-income and high-income residents respond in opposite ways to neighborhood income level.

In order to make possible a rigorous analysis of the separate neighborhood and individual effects, this study uses two unusual dataseis of survey data

merged with independent contextual data from the U.S. Census. This contrasts

with most analyses of survey data, which rely on the survey data alone and

therefore have at best only respondents' reports about their neighborhoods.

Using these dataseis for the Los Angeles and Detroit metropolitan areas, the

analysis investigates two primary research questions:

(1) Do people of different races and socioeconomic levels evaluate neigh borhoods differently, or are differences in evaluations given by people of

different races and socioeconomic levels the result of the different kinds of

neighborhoods in which they live?

(2) Do people evaluate neighborhoods of different racial and socioeconomic

composition differently, and if so, does the effect of neighborhood racial and

socioeconomic composition depend on the race and socioeconomic level of

the individual?

DATA

The survey data for Los Angeles are from the Los Angeles Metropolitan Area

Survey, conducted by the UCLA Institute for Social Science Research in

1972. The survey data for Detroit are from a University of Michigan Institute

for Social Research survey conducted in 1974. The sample size for Los

Angeles is 1017, and for Detroit 1194. Census data from the 1970 Census of

Population and Housing were merged with each of these survey dataseis.



NEIGHBORHOOD EVALUATION 313

Thus, for each case (respondent), the datasets contain both survey data about

the respondent and census data about the respondent's census tract.

NEIGHBORHOOD EVALUATION SCALES

A four-item neighborhood evaluation scale is used as the dependent variable

in the Los Angeles analysis. A factor analysis of a large set of survey ques

tions, all concerning the respondent's neighborhood, showed that four neigh borhood evaluation items were strongly associated with one principal com

ponent. The four items obtained evaluations of the respondent's neighbor hood in terms of (1) safety for the respondent and the respondent's family,

(2) available recreational facilities, (3) quality of the local public schools, and (4) an overall evaluation of the neighborhood as a place to live.2 Because

these four items empirically define a single dimension, and because they measure different aspects of perceived neighborhood quality, they were

summed into a single, general neighborhood evaluation scale. The estimated

scale reliability (Cronbach's alpha) is 0.65, indicating that about thirty five percent of the scale variance results from random error. This scale, like

the scales used in the Detroit analysis, was transformed to a standard devia

tion often.

Two different neighborhood evaluation scales were used in the Detroit

analysis. The first scale is a five-item scale constructed on the basis of cor

relational and factor analytic results, as well as face validity. Four of the

items asked the respondents to rate their neighborhood on seven-point scales

according to different characteristics: (1) friendly people ?

unfriendly

people, (2) very good place to live ? very poor place to live, (3) pleasant

? unpleasant, and (4) good neighbors ?bad neighbors. The fifth item was a

seven-point rating of the respondents' general satisfaction with their neigh borhoods. The estimated reliability for the summated scale is 0.87.

A second neighborhood evaluation scale was used in the Detroit analysis in

order to match as closely as possible the content of the Los Angeles scale.

Since an item on public schools was not included in the Detroit dataset, a

three-item scale was constructed using seven-point ratings of (1) personal

safety in the neighborhood, (2) satisfaction with recreational facilities, and

(3) the same general neigborhood satisfaction item used in the first scale.

The estimated reliability for the second scale is 0.65. The correlation between

the two scales is 0.70, indicating they share about half of their scale variance.




On the basis of face validity, the first scale appears to have a larger component

concerning people in the neighborhood, whereas the second scale, like the

Los Angeles scale, has a larger component of concern with safety and local

services.

RESULTS

Table I presents the results for the Los Angeles analysis, and Tables II and III

present the results for the Detroit analyses for scales one and two, respective

ly. Each of the three tables presents the estimated regression coefficients, with their standard errors in parentheses,3 for three different multiple regres sion equations. First, the scale is regressed on the individual-level respondent characteristics. Second, the scale is regressed on the contextual census tract

characteristics. Third, the scale is regressed on both the individual-level and

contextual variables.

The individual-level variables include the logarithm (base two) of the

respondent's family income,4 the respondent's number of years of education, and a dummy variable for black respondents. Because of the large Mexican

TABLE I

Los Angeles results: regression of neighborhood evaluation scale on (1) individual-level

variables only, (2) tract-level variables only, (3) both individual-level and

tract-level variables

Independent variables (1) (2) (3)

Log income 1.4 (0.3)b -

0.2(0.3) Education 0.3 (0.1)b

- 0.1(1.1)

Black dummy -5.8 (1.0)b -

2.4(1.7) Spanish dummy -2.1 (1.0)a

- 1.7(1.0)

Log median income - 7.1 (0.9)b 6.8 (1.0)b Median education - -0.1 (0.4) -0.2 (0.4)

Proportion black - -5.6 (1.3)b -8.2 (2.2)b Proportion Spanish

- -8.6 (2.3)b -10.2 (2.6)b

R 0.33 0.49 0.49

a Statistically significant, 0.05 level, 2-tail test.

b Statistically significant, 0.01 level, 2-tail test.

Note: Table entries are the estimated unstandardized partial regression coefficients, with their associated standard errors in parentheses.




TABLE II

Detroit results: regression of first neighborhood evaluation scale on (1) individual-level

variables only, (2) tract-level variables only, (3) both individual-level and



Log income

Education

Black dummy

Log median income

Median education

Proportion black

1.3 (0.3)b -0.1 (0.1) -4.1 (0.7)b

9.4(1.5)b -0.4 (1.0)

-1.6(1.0)

0.4 (0.3) -0.2 (0.1)

0.1(1.3)

8.8(1.6)b -0.2 (0.5)

-1.7(1.7)

R 0.24 0.35 0.36



Note: Table entries are the estimated unstandardized partial regression coefficients, with

their associated standard errors in parentheses.

TABLE III

Detroit results: regression of second neighborhood evaluation scale on (1) individual

level variables only, (2) tract-level variables only, (3) both individual-level and



Log income

Education

Black dummy

Log median income

Median education

Proportion black

R

1.8(0.3)b 0.0 (0.1)

-6.6 (0.7)b

0.37

10.5 (1.5)b -0.5 (0.5) -5.1 (1.0)b

0.47

0.7 (0.3)a -0.1 (0.1)

-0.2(1.4)

9.5 (1.5)b -0.4 (0.5)

-4.9(1.8)b

0.48



Note: Table entries are the estimated unstandardized partial regression coefficients, with

their associated standard errors in parentheses.




American population in Los Angeles, a dummy variable for Spanish-surname

respondents is included in the Los Angeles analysis. The contextual variables

include the logarithm (base two) of the median family income in the re

spondent's census tract, the medium number of school years completed by adults twenty-five years of age or older, the proportion of the tract popula tion that was black, and, for the Los Angeles analysis, the proportion of the

tract population Spanish-surname. Since the evaluation scales have a standard

deviation of ten, the regression coefficients indicate the estimated effect

in tenths of standard deviations of doubling individual or median tract in

come, of increasing individual or median tract education one year, of a re

spondent being black or Spanish surname compared to white, and of the

respondent's area being all-black or all Spanish-surname, compared to all

white.

All three tables show remarkably similar results. Individual-level socio

economic and race variables appear to have an effect when the contextual

variables are not included, but their observed effects largely disappear when

the contextual variables are included. In all tables, significant individual

level coefficients in regression (1) diminish greatly in absolute value when

re-estimated in regression (2), and in only one case in regression (3) is a coef

ficient for an individual-level variable statistically significant. In addition, the

multiple correlations show that the individual-level variables add almost no

additional explanatory power to the contextual variables. Therefore, the

answer to the first research question is that people of different races and

socioeconomic levels do not evaluate neighborhoods differently. Observed

differences between different racial and socioeconomic groups result from the

different kinds of neighborhoods in which those people tend to reside.

The answer to the second research question is that people do evaluate

neighborhoods of different racial and socioeconomic composition differently. Tables I and III show strong effects for the contextual race and income

variables, and Table II shows a strong effect for the contextual income

variable. Living in lower income and higher minority areas leads to more

negative neighborhood evaluations. These observed effects do not diminish

when the individual-level variables are controlled. The coefficient estimates

do not decline in absolute value, and the coefficients remain statistically

significant. Although multiple correlations increase considerably when the

contextual variables are added to the individual-level only regressions, the

individual-level variables add almost nothing to the explanatory power of




the contextual variables. In short, the results unambiguously show strong

contextual, not individual-level, effects.

The strong contextual effects do not depend on the sociodemographic traits of the individual. Multiplicative interactive terms for the race and in

come variables were included in each of the combined individual-level and

tract-level regression equations, and none of the terms was statistically

significant. In addition, the Detroit analyses were done separately for low and

high income respondents, and separately for blacks and whites, and little

change was observed in the coefficient estimates for the contextual variables.5

This is consistent with the findings of this and other Detroit surveys (Farley et al.9 1979, p. 104), as well as national surveys (Pettigrew, 1973, p. 44), that most blacks say they prefer integrated rather than all black neighbor

hoods. In short, people of different races and socioeconomic levels react

about the same to living in various types of neighborhoods.6

INTERPRETATIONS AND CONCLUSIONS

All types of residents ? whether black or white, low income or high income ? tend to evaluate lower income and higher minority areas more negatively than higher income and lower minority areas. Residents' reactions to neigh borhoods of different socioeconomic and racial composition do not appear to result from racial or class prejudice, since all types of people react to

neighborhoods in the same way.7 Past speculation (e.g. Campbell, 1981, p. 155) that satisfaction blacks derive from living in black areas counteracts

the effect of living in low income neighborhoods seems to have been in error. Rather, undesirable characteristics associated with both lower income

and higher minority areas decrease neighborhood satisfaction for everyone alike ? rich and poor, white and black.

The strong, positive effect of neighborhood income level found in this

research is consistent with Little's (1976) finding that neighborhood income

has an important independent effect on housing preferences. The contrasting results for neighborhood education level indicate that the important ex

planatory variable is not the broad sociological concept of class, but simply the level of poverty, as measured by income. Similarly, the negative effect observed for high minority areas supports the argument of Schuman and

Gruenberg (1972) that urban black dissatisfaction stems from undesirable

objective characteristics of minority neighborhoods.8 However, since neigh




borhood income level and racial composition are only moderately associated

and have independent effects,9 they should not be viewed, as do Schuman

and Gruenberg (1972, p. 386), as constituting a single status dimension, but

rather as constituting distinct and separate sources of neighborhood dissatis

faction.

If living in minority neighborhoods creates greater dissatisfaction, in

dependent of the neighborhood's economic level, what objective character

istics of minority areas cause that dissatisfaction? Schuman and Gruenberg

(1972) emphasized the importance of poor local services. Taylor (1979, p.

35) argued that the social disorganization found in black neighborhoods lowers neighborhood satisfaction. Other possibilities include housing quality,

density, and local amenities. Further contextual research should be under

taken ? by appending data for measures of local services, social disorganiza

tion (e.g., crime rates), housing quality,and other characteristics hypothesized to be important

? to identify the true sources of dissatisfaction with minori

ty areas.10

Fortunately, information elicited directly from survey respondents and

from interviewer observations can help in identifying important sources of

dissatisfaction. Newman and Duncan (1979, p. 163) found that blacks suf

fered more than any other demographic group, according to respondent

reports, from neighborhood problems of cleanliness, congestion, and crime.

Other research has shown that respondent and interviewer ratings of neigh borhood maintenance levels are strong predictors of neighborhood satisfac

tion (Campbell et al., 1976, Ch. 7; Lansing and Marans, 1969; Marans and

Rodgers, 1975; Zehner, 1971, 1977). Thus, at least a substantial component of the dissatisfaction generated by living in minority areas results from the

greater physical deterioration and unattractiveness of those neighborhoods. Dissatisfaction created by social disorganization and poor local services per se may be less important, although social disorganization (e.g. widespread

arson) and poor services can themselves cause physical deterioration and un

attractiveness. Since the statistical results of this study demonstrate the

importance that undesirable characteristics of lower income and minority areas have in creating urban dissatisfaction, the sources of that dissatisfaction

merit the attention of policy makers concerned with the quality of urban

life and potential urban unrest.

The results of this study also have policy implications for housing integra tion. If opposition to integration results primarily from pure racial prejudice,




rather than from realistic perceptions of conditions in higher minority areas,

Pettigrew's (1973) argument that integrated housing will erode such opposi tion may be plausible. However, this study has shown that people of all types see higher minority areas as less desirable places to live. Characteristics of

minority areas, as well as lower income areas, make people ? both black and

white, low income and high income - averse to living there. Therefore, public

policy must attack the problems making those areas undesirable in order to

decrease negative perceptions of higher minority areas that foster white

opposition to housing integration.

Portland State University, and Delphi Communications Corporation

NOTES

* The authors wish to thank Robert Marans and Willard Rodgers for generously allowing the use of data from their Detroit Quality of Life Study. 1

See Stipak and Hensler (1982) for a discussion of the statistical problems involved in

this type of research. 2

Readers interested in the exact working of the survey items can write the authors for

copies of the interview schedules. 3

The estimated standard errors in Tables I-III are only approximations, since they assume simple random sampling. However, judging from FrankeFs (1971) findings about

design effects for partial regression coefficients, these approximations are reasonable. 4

Using a logarithmic transformation, rather than a linear term, implies that equal proportional changes in income, rather than equal dollar changes, have equal effects on

evaluations. A logarithmic representation of income instead of a linear representation is generally preferable, since for a number of reasons income has a diminishing marginal effect on behavior and attitudes. First, economic well-being increases non-linearly with income because of assistance programs and progressive taxation. Second, utility is usual

ly a non-linear function of income (e.g. see Hamblin et al., 1975). Finally, in our own

empirical investigations we have found that relationships of income to attitude scales, controlling for other variables, are approximately logarithmic. In contrast, relation

ships for respondent education are typically linear. 5

For the scale two results, the proportion black variable showed a somewhat larger effect for whites than blacks. 6

Stipak (1980) showed that asking respondents about their preferences for the racial

composition of their neighborhood identified subsets of both blacks and whites which differ in the strength of the effect that neighborhood racial composition has on neighbor hood satisfaction. However, the point here is that there are no large overall differences between the reactions of people of different races and economic levels. 7

Racial prejudice would increase the negative effect of the contextual black variable

for whites, and decrease the effect for blacks. Class prejudice would produce a similar interaction between the individual and contextual SES variables. However, no such interactions were detected, as discussed above. 8

Note that the proportion black variable shows a strong effect on the evaluation scales (Tables I and III) having a large component of concern with safety and local




services, but not on the scale (Table II) with a larger component concerning people in the neighborhood. This is consistent with the interpretation that dissatisfaction with

minority areas stems not from reactions to neighborhood residents, but rather to neigh borhood problems. 9

For Detroit the correlation between the log median income and proportion black variables is -0.48. For Los Angeles the correlation between the log median income and

proportion black variables is -0.46, and the correlation between the log median income

and proportion Spanish-surname variables is -0.40. 10

However, problems of data availability, measurement, and high collinearity may make this research approach difficult and expensive.

BIBLIOGRAPHY

Campbell, Angus: 1981, The Sense of Well-Being in America (McGraw-Hill, New York).

Campbell, Angus, Philip E. Converse, and Willard L. Rodgers: 1976, The Quality of

American Life (Russell Sage, New York).

Farley, Reynolds, Suzanne Bianchi, and Diane Colasanto: 1979, 'Barriers to the racial

integration of neighborhoods: The Detroit case', Annals of the American Academy of Political and Social Science 441, pp. 97-113.

Frankel, Martin R.: 1971, Inference from Survey Samples: An Empirical Investigation (Institute for Social Research, University of Michigan, Ann Arbor).

Hamblin, Robert L., Donald H. Clairmont, and Bruce A. Chadwick: 1975, 'Utility and

gambling decisions: experiments and equations', Social Science Research 4, pp. 1-15.

Lansing, John B., and Robert W. Marans: 1969., 'Evaluation of neighborhood quality', Journal of American Institute of Planners 35, pp. 195-199.

Little, James T.: 1976, 'Residential preferences, neighborhood filtering, and neighbor hood change', Journal of Urban Economics 3, pp. 68?81.

Marans, Robert W., and Willard Rodgers: 1975, 'Toward an understanding of community satisfaction', in Amos H. Hawley and Vincent P. Rock (eds.), Metropolitan America

in Contemporary Perspective (Wiley, New York), pp. 299-352.

Newman, Sandra J., and Greg J. Duncan: 1979, 'Residential problems, dissatisfaction, and mobility', Journal of the American Planning Association 45, pp. 154-166.

Pettigrew, Thomas F.: 1973, 'Attitudes on race and housing: a social-phychological view', in Amos H. Hawley and Vincent P. Rock (eds.), Segregation in Residential Areas (National Academy of Sciences, Washington), pp. 21-84.

Schuman, Howard, and Barry Gruenberg: 1972, 'Dissatisfaction with city services: is race an important factor?', in Harlan Hahn (ed.), People and Politics in Urban

Society (Sage, Beverly Hills), pp. 369-392.

Stipak, Brian: 1980, 'Analysis of policy issues concerning social integration', Policy Sciences 12, pp. 41-60.

Stipak, Brian and Carl Hensler: 1982, 'Statistical inference in contextual analysis', American Journal of Political Science 26, pp. 151-175.

Taylor, D. Garth: 1979, 'Housing, neighborhoods, and race relations: recent survey evidence', Annals of the American Academy of Political and Social Science 441, pp. 26-40.

Zehner, Robert B.: 1971, 'Neighborhood and community satisfaction in new towns and less planned suburbs', Journal of the American Institute of Planners 37, pp. 379-385.

Zehner, Robert B.: 1977, Indicators of the Quality of Life in New Communities (Bal linger, Cambridge).



Documents

Effect of Neighborhood Racial and Socioeconomic Composition on Urban Residents' Evaluations of Their Neighborhoods