Manuscript NIH-PA Author Manuscript7. EXAMPLESStated Residential Preferences in MCSUI Data We illustrate the analysis of stated preference data using the MCSUI data for Los Angeles. For illustrative purposes, we only analyze the “ranked attractiveness” and “would move in” data. The ranked-attractiveness data were only collected for non-white respondents. Table 2 shows the percentage of T0901317 web neighborhoods that were ranked first or second by black, Asian, and Hispanic respondents who were asked about neighbors of different race/ethnicities. Among black respondents asked about white, Asian, or Hispanic neighbors, the most attractive neighborhoods were those with a minority of other-group neighbors. However, a nontrivial proportion of black respondents identified the entirely other-group neighborhood (e.g., 100 white) as the most attractive neighborhood. Asian respondents were also most likely to rank neighborhoods with a minority of other-group neighbors as most attractive, although they find Hispanic and black neighbors less attractive than white neighbors. Similarly, Hispanic respondents find white neighbors more attractive than black or Asian neighbors, but are most likely to rank neighbors with a strong Hispanic presence most attractive. Table 3 shows the percent of white, black, Hispanic, and Asian respondents willing to move into a neighborhood based on its neighborhood proportion other (where the other-group may be white, black, Asian, or Hispanic). The first column of the table, which shows how white, Asian, and Hispanic respondents evaluate black neighbors, indicates that all groups avoid majority black neighborhoods. These descriptive tables show the distribution of responses over categories of neighborhood proportion other, but they do not provide a succinct way of showing the relationship between neighborhood preferences and neighborhood characteristics.Sociol Methodol. Author manuscript; available in PMC 2013 March 08.Bruch and MarePageModels–We analyze the “ranked attractiveness” data by treating the five responses (one for each vignette neighborhood) as a full ranking of the alternatives. In contrast, we treat the five responses to the “would you move in/out” question as a partial ranking of the alternative vignette neighborhoods, and use these rankings to estimate rank-ordered logit models with ties. In Table 1 each respondent has five lines of data, one for each neighborhood ethnic composition vignette and the respondent’s rank of the vignette. The vignette rank is the dependent variable and is modeled as a function of the percent other-group in the neighborhood.12 Separate parameters are estimated for each combination of respondent’s own race and the race of the other group in the vignette neighborhood. The nonlinear continuous model adequately describes residential preferences for these simple data. The coefficients from these models are shown in Table 4. The predicted probabilities from the models for two of the ethnic groups, blacks and Hispanics, are presented in Figures 2 and 3. The top panel of Figure 2 shows the probability that black respondents rank a vignette neighborhood most attractive. Separate panels are shown for Thonzonium (bromide) web black-white, black-Hispanic, and black-Asian neighborhoods. Black respondents tend to rank as most attractive those neighborhoods where their own ethnic group is heavily represented most. However, when asked which neighborhoods they would be willing to move into, blacks display a strong preference fo.Manuscript NIH-PA Author Manuscript7. EXAMPLESStated Residential Preferences in MCSUI Data We illustrate the analysis of stated preference data using the MCSUI data for Los Angeles. For illustrative purposes, we only analyze the “ranked attractiveness” and “would move in” data. The ranked-attractiveness data were only collected for non-white respondents. Table 2 shows the percentage of neighborhoods that were ranked first or second by black, Asian, and Hispanic respondents who were asked about neighbors of different race/ethnicities. Among black respondents asked about white, Asian, or Hispanic neighbors, the most attractive neighborhoods were those with a minority of other-group neighbors. However, a nontrivial proportion of black respondents identified the entirely other-group neighborhood (e.g., 100 white) as the most attractive neighborhood. Asian respondents were also most likely to rank neighborhoods with a minority of other-group neighbors as most attractive, although they find Hispanic and black neighbors less attractive than white neighbors. Similarly, Hispanic respondents find white neighbors more attractive than black or Asian neighbors, but are most likely to rank neighbors with a strong Hispanic presence most attractive. Table 3 shows the percent of white, black, Hispanic, and Asian respondents willing to move into a neighborhood based on its neighborhood proportion other (where the other-group may be white, black, Asian, or Hispanic). The first column of the table, which shows how white, Asian, and Hispanic respondents evaluate black neighbors, indicates that all groups avoid majority black neighborhoods. These descriptive tables show the distribution of responses over categories of neighborhood proportion other, but they do not provide a succinct way of showing the relationship between neighborhood preferences and neighborhood characteristics.Sociol Methodol. Author manuscript; available in PMC 2013 March 08.Bruch and MarePageModels–We analyze the “ranked attractiveness” data by treating the five responses (one for each vignette neighborhood) as a full ranking of the alternatives. In contrast, we treat the five responses to the “would you move in/out” question as a partial ranking of the alternative vignette neighborhoods, and use these rankings to estimate rank-ordered logit models with ties. In Table 1 each respondent has five lines of data, one for each neighborhood ethnic composition vignette and the respondent’s rank of the vignette. The vignette rank is the dependent variable and is modeled as a function of the percent other-group in the neighborhood.12 Separate parameters are estimated for each combination of respondent’s own race and the race of the other group in the vignette neighborhood. The nonlinear continuous model adequately describes residential preferences for these simple data. The coefficients from these models are shown in Table 4. The predicted probabilities from the models for two of the ethnic groups, blacks and Hispanics, are presented in Figures 2 and 3. The top panel of Figure 2 shows the probability that black respondents rank a vignette neighborhood most attractive. Separate panels are shown for black-white, black-Hispanic, and black-Asian neighborhoods. Black respondents tend to rank as most attractive those neighborhoods where their own ethnic group is heavily represented most. However, when asked which neighborhoods they would be willing to move into, blacks display a strong preference fo.