Appendix

Exposure and Preferences: Evidence from Indian Slums

March 12, 2019

List of Tables

A1 Correlation between k-nearest score calculated for random sample of 60 in-

dividuals from each neighborhood, versus the same metric calculated for the

entire neighborhood. The reported means and standard deviations of the cor-

relations are for 1000 random samples of 60 individuals from each neighborhood. 4

A2 Correlations over 1000 iterations between k-nearest score calculated for ran-

dom sample of 60 individuals from each neighborhood, versus contact with

individuals from another religion. . . . . . . . . . . . . . . . . . . . . . . . . 5

A3 Relationship between proportion of the 10 nearest neighbors of another reli-

gion, and proportion who have any contacts with members of another religion. 6

A4 Results for co-ethnicity attribute in candidate experiment compared between

high- and low-exposure subsamples, based on religious exposure. . . . . . . . 7

A5 Balance Table, High vs. Low Exposure . . . . . . . . . . . . . . . . . . . . . 8

A6 Balance Table, High vs. Low Exposure (De-Medianed) . . . . . . . . . . . . 8

A7 Results for co-ethnicity attribute in candidate experiment compared between

high- and low-exposure subsamples, based on religious exposure. . . . . . . . 16

A8 Balance Table, High vs. Low Exposure, Network Survey . . . . . . . . . . . 17

A9 Results for co-ethnicity attribute in neighbor experiment compared between

high- and low-exposure subsamples, based on religious exposure. . . . . . . . 24

List of Figures

A1 Empirical distribution of k-nearest neighbors metric for religion, k = 10. . . . 1

A2 Empirical distribution of k-nearest neighbors metric for religion, k = 10. . . . 2

A3 Histogram of correlation between sample version of religious k-nearest-neighbor

score and contact for 1000 random samples, K = 10. These results from ran-

dom samples are similar to those calculated for the full neighborhood census. 5

A4 Difference in coethnic coefficients between low- and high-exposure subsam-

ples, based on religious exposure, including results for de-medianed k-nearest-

neighbors metric. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

A5 Coethnic coefficients for low- and high-exposure subsamples of Hindus, based

on religious exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

A6 Coethnic coefficients for low- and high-exposure subsamples of Muslims, based

on religious exposure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

A7 Coethnic coefficients for low- and high-exposure subsamples of individuals

with higher than average asset score, based on religious exposure. . . . . . . 12

A8 Coethnic coefficients for low- and high-exposure subsamples of high-caste in-

dividuals, based on religious exposure. . . . . . . . . . . . . . . . . . . . . . 13

A9 Coethnic coefficients for low- and high-exposure subsamples of respondents

from Jaipur only, based on religious exposure. . . . . . . . . . . . . . . . . . 14

A10 Coethnic coefficients for low- and high-exposure subsamples of respondents

from Patna only, based on religious exposure. . . . . . . . . . . . . . . . . . 15

A11 Coethnic coefficients for low- and high-exposure subsamples of high-income

respondents only, based on religious exposure, in network census survey. . . . 17

A12 Coethnic coefficients for low- and high-exposure subsamples of Patna respon-

dents only, based on religious exposure, in network census survey. . . . . . . 18

A13 Coethnic coefficients for low- and high-exposure subsamples of female respon-

dents only, based on religious exposure, in network census survey. . . . . . . 19

A14 Coethnic coefficients for low- and high-exposure subsamples of migrant re-

spondents only, based on religious exposure, in network census survey. . . . . 20

A15 Coethnic coefficients for low- and high-exposure subsamples of high-caste re-

spondents only, based on religious exposure, in network census survey. . . . . 21

A16 Coethnic coefficients for low- and high-exposure subsamples of Muslim re-

spondents only, based on religious exposure, in network census survey. . . . . 22

A17 Coethnic coefficients for low- and high-exposure subsamples of Hindu respon-

dents only, based on religious exposure, in network census survey. . . . . . . 23

A18 Non-coethnicity coefficients for in neighbor comparison conjoint between low-

and high-exposure subsamples for de-medianed k-nearest-neighbors metric. . 25

1 Measurement

1.1 Empirical distributions of k-nearest-neighbors metrics

Figure A1: Empirical distribution of k-nearest neighbors metric for religion, k = 10.

1

Figure A2: Empirical distribution of k-nearest neighbors metric for religion, k = 10.

2

1.2 Subsample properties of k-nearest-neighbors metric

The main text establishes that the k-nearest-neighbors score is highly correlated to social

contact when the locations and ascriptive characteristics of every household in the neigh-

borhood are known. Here I establish that the same holds when the locations and ascriptive

characteristics are only known for a random subset of of the neighborhood’s households, as

is the case for most empirical settings. This is to rule out the possibility that when only a

fraction of the households are sampled, the resulting map of the neighborhood could be too

sparse to allow the patterns of social contact in the neighborhood to be accurately inferred.

To confirm that the k-nearest-neighbors metric can capture social contact when only a por-

tion of the neighborhood’s residents are sampled, I test it on randomly chosen subsets of the

neighborhood census data set.

To do this, I take a random sample of 60 residents from each of the neighborhoods from

which census data was collected. I then calculate the value of the k-nearest-neighbors metric

using only the households in the random sample. The resulting value corresponds to the

result that would have been calculated, had only a sample of the neighborhood’s residents

been interviewed and geocoded. This value can then be compared to the “real” value of the

metric, which I calculated using the entire population of the neighborhood. By comparing

the value of the k-nearest-neighbors metric that is calculated from the neighborhood census

to the value that is calculated from a randomized subset of the same data, I can check whether

the metric is useful when calculated from data that is generated by randomized sampling,

including the household surveys that comprise the main dataset used in the present study.

In Table A1, I show the results of this comparison. For each neighborhood, I generated

1000 randomly chosen subsets of 60 individuals from each neighborhood. For each randomly

chosen subset, I calculated the k-nearest-neighbors metric, and checked the correlation be-

tween this and the value of the metric for the same individuals, but calculated using the entire

neighborhood sample. The results in Table A1 show that the correlation between the census

3

and subset versions of k-nearest-neighbors metric is quite high: for example, for k = 10, the

average correlation between the subset and census versions (over the 1000 randomly chosen

subsets) is 0.85, with a standard deviation of 0.020. Similar results hold for other values of

k. These results allow us to be confident that, even if I am working with sampled data, the

value of the k-nearest-neighbors metric that I calculate will be close the value that I would

have found had I had access to census data. This demonstrates the validity of using the

k-nearest-neighbors metric to proxy social contact in the household survey data, which was

administered to random samples from each neighborhood.

k Correlation Mean Correlation SD

5 0.77 0.02610 0.85 0.02015 0.87 0.018

Table A1: Correlation between k-nearest score calculated for random sample of 60 individualsfrom each neighborhood, versus the same metric calculated for the entire neighborhood. Thereported means and standard deviations of the correlations are for 1000 random samples of60 individuals from each neighborhood.

Table A2 shows that the subsample version of the k-nearest-neighbors metric, in addition

to being highly correlated with the census version, is similarly effective in picking up variation

in social contact. Comparing Table 2, in the main text, to Table A2 below, we find that,

similar to the census version shown in the former, the sample version shown in the latter

picks up more than 40% of the variation in outgroup contact. This result further confirms my

premise that physical proximity, as measured by the k-nearest-neighbors metric calculated

for a randomly sampled subset of residents of a neighborhood, is an effective proxy for social

contact. The same results are shown in Figure A3, which is a histogram of the observed

correlations between the k-nearest-neighbors scores calculated from 1000 random subsamples

of the census data and outgroup contact.

Table A3 shows the relationship between the 10-nearest-neighbors score and the proba-

4

k Mean Correlation SD of Correlation

5 0.418 0.05110 0.431 0.04715 0.438 0.045

Table A2: Correlations over 1000 iterations between k-nearest score calculated for randomsample of 60 individuals from each neighborhood, versus contact with individuals from an-other religion.

Figure A3: Histogram of correlation between sample version of religious k-nearest-neighborscore and contact for 1000 random samples, K = 10. These results from random samplesare similar to those calculated for the full neighborhood census.

5

bility of having at least one network link with a member of the religious outgroup. Of the

respondents whose 10-nearest-neighbors score is 10, indicating that all 10 of their closest

neighbors are of the same religion, only 1% have any network links with a member of the

outgroup. Individuals with a score of 10 are totally separated, both physically and socially,

from individuals of other religions. Meanwhile more than a quarter of individuals whose

10-nearest-neighbors score is 9 or below have at least one network link with a member of

another religion.

10-Nearest-Neighbors score Proportion with some outgroup contacts N

10 1% 1159≤ 9 26% 1422≤ 8 30% 1134≤ 7 33% 909≤ 6 37% 734≤ 5 38% 539≤ 4 41% 378≤ 3 46% 240≤ 2 54% 135≤ 1 66% 680 75% 28

Table A3: Relationship between proportion of the 10 nearest neighbors of another religion,and proportion who have any contacts with members of another religion.

6

2 Household sample conjoint: Candidate comparisons

Table A4: Results for co-ethnicity attribute in candidate experiment compared betweenhigh- and low-exposure subsamples, based on religious exposure.

k Coef HiExp SD HiExp Coef LoExp SD LoExp p

1 0.045 0.023 -0.041 0.009 0.0012 0.038 0.020 -0.046 0.010 03 0.029 0.019 -0.048 0.010 04 0.011 0.017 -0.046 0.010 0.0045 0.005 0.017 -0.045 0.010 0.0106 0.002 0.017 -0.045 0.010 0.0177 -0.006 0.017 -0.043 0.010 0.0558 -0.005 0.016 -0.045 0.010 0.0409 -0.003 0.016 -0.047 0.011 0.02210 -0.008 0.015 -0.045 0.011 0.04511 -0.007 0.015 -0.046 0.011 0.03812 -0.004 0.015 -0.049 0.011 0.01313 -0.002 0.014 -0.052 0.011 0.00514 -0.002 0.014 -0.053 0.011 0.00515 -0.005 0.014 -0.051 0.011 0.01116 -0.007 0.014 -0.050 0.011 0.01717 -0.008 0.014 -0.050 0.011 0.01818 -0.010 0.014 -0.049 0.011 0.02719 -0.013 0.013 -0.047 0.012 0.05320 -0.014 0.013 -0.047 0.011 0.05821 -0.014 0.013 -0.047 0.012 0.06522 -0.013 0.013 -0.049 0.011 0.04023 -0.018 0.013 -0.044 0.011 0.12824 -0.021 0.013 -0.041 0.012 0.25125 -0.019 0.013 -0.043 0.012 0.17126 -0.020 0.013 -0.042 0.012 0.21127 -0.018 0.013 -0.045 0.012 0.12928 -0.012 0.012 -0.044 0.012 0.06129 -0.014 0.012 -0.044 0.012 0.07230 -0.016 0.013 -0.046 0.012 0.105

7

Table A5: Balance Table, High vs. Low Exposure

Low Exp. High Exp. p

Asset Index 9.49 9.95 0Low Caste 0.55 0.42 0

Muslim 0.09 0.32 0Male 0.51 0.51 0.69Age 39 38.81 0.63

Migrant 0.33 0.33 0.83Jaipur 0.48 0.55 0Patna 0.48 0.22 0

n 3, 173 1, 991

Table A6: Balance Table, High vs. Low Exposure (De-Medianed)

Low Exp. High Exp. p

Asset Index 9.61 9.87 0.07Low Caste 0.52 0.41 0

Muslim 0.16 0.29 0Male 0.51 0.50 0.57Age 39 38.62 0.4

Migrant 0.32 0.36 0.01Jaipur 0.49 0.55 0Patna 0.40 0.30 0

n 4, 136 1, 028

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Figure A4: Difference in coethnic coefficients between low- and high-exposure subsamples,based on religious exposure, including results for de-medianed k-nearest-neighbors metric.

9

Figure A5: Coethnic coefficients for low- and high-exposure subsamples of Hindus, based onreligious exposure.

10

Figure A6: Coethnic coefficients for low- and high-exposure subsamples of Muslims, basedon religious exposure.

11

Figure A7: Coethnic coefficients for low- and high-exposure subsamples of individuals withhigher than average asset score, based on religious exposure.

12

Figure A8: Coethnic coefficients for low- and high-exposure subsamples of high-caste indi-viduals, based on religious exposure.

13

Figure A9: Coethnic coefficients for low- and high-exposure subsamples of respondents fromJaipur only, based on religious exposure.

14

Figure A10: Coethnic coefficients for low- and high-exposure subsamples of respondents fromPatna only, based on religious exposure.

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3 Network census conjoint: Candidate comparisons

Table A7: Results for co-ethnicity attribute in candidate experiment compared betweenhigh- and low-exposure subsamples, based on religious exposure.

k Coef HiExp SD HiExp Coef LoExp SD LoExp p

1 0.103 0.007 0.048 0.029 0.0692 0.111 0.014 0.036 0.031 0.0293 0.100 0.014 0.035 0.035 0.0824 0.097 0.015 0.032 0.036 0.0955 0.107 0.018 0.020 0.034 0.0256 0.100 0.017 0.021 0.035 0.0427 0.103 0.014 0.015 0.035 0.0198 0.105 0.014 0.010 0.033 0.0089 0.102 0.014 0.009 0.033 0.01010 0.104 0.015 0.003 0.032 0.00411 0.103 0.012 0.002 0.032 0.00312 0.103 0.014 -0.002 0.029 0.00113 0.106 0.013 -0.008 0.028 014 0.104 0.014 -0.009 0.029 015 0.104 0.013 -0.010 0.029 016 0.103 0.013 -0.011 0.029 017 0.101 0.010 0.016 0.033 0.01518 0.101 0.010 0.015 0.033 0.01319 0.101 0.011 0.014 0.033 0.01220 0.101 0.009 0.012 0.034 0.01221 0.100 0.011 0.011 0.034 0.01222 0.098 0.013 0.013 0.033 0.01823 0.098 0.014 0.011 0.033 0.01624 0.098 0.013 0.011 0.034 0.01625 0.092 0.011 0.025 0.037 0.08726 0.093 0.010 0.023 0.037 0.07427 0.093 0.010 0.022 0.037 0.06828 0.097 0.010 0.017 0.036 0.03129 0.098 0.013 0.014 0.033 0.01830 0.101 0.014 0.009 0.031 0.007

16

Table A8: Balance Table, High vs. Low Exposure, Network Survey

Low Exp. High Exp. p

Income (k INR/mo.) 12.26 11.47 0.01Low Caste 0.48 0.27 0

Muslim 0.02 0.39 0Male 0.48 0.52 0.04Age 35.83 36.15 0.51

Migrant 0.40 0.45 0Jaipur 0.46 0.74 0

n 1, 159 1, 422

Figure A11: Coethnic coefficients for low- and high-exposure subsamples of high-incomerespondents only, based on religious exposure, in network census survey.

17

Figure A12: Coethnic coefficients for low- and high-exposure subsamples of Patna respon-dents only, based on religious exposure, in network census survey.

18

Figure A13: Coethnic coefficients for low- and high-exposure subsamples of female respon-dents only, based on religious exposure, in network census survey.

19

Figure A14: Coethnic coefficients for low- and high-exposure subsamples of migrant respon-dents only, based on religious exposure, in network census survey.

20

Figure A15: Coethnic coefficients for low- and high-exposure subsamples of high-caste re-spondents only, based on religious exposure, in network census survey.

21

Figure A16: Coethnic coefficients for low- and high-exposure subsamples of Muslim respon-dents only, based on religious exposure, in network census survey.

22

Figure A17: Coethnic coefficients for low- and high-exposure subsamples of Hindu respon-dents only, based on religious exposure, in network census survey.

23

4 Household sample conjoint: Neighbor comparisons

Table A9: Results for co-ethnicity attribute in neighbor experiment compared between high-and low-exposure subsamples, based on religious exposure.

k Coef HiExp SD HiExp Coef LowExp SD LowExp p

1 -0.055 0.031 -0.029 0.017 0.4512 -0.020 0.027 -0.040 0.019 0.5503 -0.008 0.023 -0.048 0.020 0.1944 -0.017 0.021 -0.044 0.021 0.3675 -0.019 0.021 -0.047 0.021 0.3556 -0.014 0.021 -0.053 0.022 0.1917 -0.016 0.020 -0.052 0.022 0.2178 -0.017 0.019 -0.052 0.023 0.2539 -0.016 0.019 -0.057 0.024 0.17610 -0.014 0.019 -0.061 0.023 0.11211 -0.016 0.018 -0.059 0.024 0.14612 -0.013 0.018 -0.064 0.024 0.09113 -0.017 0.018 -0.060 0.025 0.16314 -0.028 0.021 -0.037 0.023 0.78915 -0.028 0.021 -0.037 0.023 0.76016 -0.028 0.021 -0.037 0.023 0.76617 -0.029 0.020 -0.037 0.024 0.79118 -0.030 0.020 -0.036 0.024 0.84319 -0.030 0.019 -0.036 0.024 0.84320 -0.027 0.019 -0.039 0.024 0.69621 -0.031 0.019 -0.035 0.025 0.91122 -0.033 0.019 -0.033 0.025 123 -0.026 0.021 -0.039 0.022 0.68624 -0.030 0.020 -0.035 0.023 0.88925 -0.032 0.020 -0.033 0.023 0.99026 -0.036 0.020 -0.029 0.023 0.83827 -0.035 0.020 -0.030 0.024 0.86428 -0.043 0.019 -0.029 0.024 0.65029 -0.041 0.019 -0.032 0.023 0.77130 -0.041 0.019 -0.033 0.023 0.796

24

Figure A18: Non-coethnicity coefficients for in neighbor comparison conjoint between low-and high-exposure subsamples for de-medianed k-nearest-neighbors metric.

25