supplementary information - university of california, san...

Supplementary Information:

Figure SA1. Based upon the groupings uncovered through the hierarchical clustering algorithm, we categorized the name generators. We then selected one name generator from within each group in order to create a subset of name generators that would maintain the greatest proportion of the total network using a smaller number of name generators.

Regression models used to derive homophily values shown in figures below (Tables SA3-SA16): We used regression models to test whether trait similarity between ego and alter significantly predicted the chance that ego would name alter as a social contact. We quantified the association between social ties and similarity for each trait across the 12 name generators using a dataset composed of all possible nominations within each village (n = 4,197,904)34. Of these, there were a total of 80,838 observed nominations across all of the name generators in the dataset. Statistical analyses consisted of a logit form of a general estimating equation in which separate regression models were run for each of 16 traits of interest in order to predict ties for each of the 12 separate name generators. The dependent variable for the name generators was 1 if person i named person j as a social contact in that name generator (for instance if i names j as someone to whom they go for advice), and 0 otherwise. The main independent variables in these basic models included a measure for the trait of interest for the person i (the “ego”), a measure for the trait of interest for person j (the “alter”), and a measure of the similarity of their traits (this is the homophily measure). For example, for gender, we ran 12 different regressions: one for each name generator. Each regression included a variable for ego’s gender, a variable for alter’s gender, and a variable indicating whether or not they had the same gender. These three variables allow us to measure how much a trait predicts the sending of nominations (do women name more social contacts than men?), the receiving of nominations (are women named more often than men?), and the extent to which homophily on the trait plays a role (are same-gender social ties more frequent than opposite-gender?). To measure similarity for continuous traits we took the absolute value of the difference between ego’s and alter’s measures and then coded each dyad as 1 if it was below the median difference in values and 0 if it was above. Because each ego was represented in the dataset multiple times, we adjusted the standard errors by using a general estimating equation, clustering on the ego. Finally, all models included a binary control variable for “same household or not” for each dyadic observation to adjust for the fact that certain traits such as latrine ownership will be the same for those in the same household, while others traits such as education may be very different.

Figure SA1. Regression analyses in Tables SA3-SA19 provide estimates of the odds that an alter was nominated in any name generator, conditional on specific characteristics of the alter (shown below each plot). Most plots show that higher status alters are more likely to be named than lower status alters (Ball & Newman, 2013).

0 2 4 6 8

Male versus female

go to temple with

give rice to

borrow rice from

give advice to

lend $ to

invite home

visit their home

talk to

take advice from

med emergencyborrow $ from

related to

0.5 1.0 1.5 2.0

High caste versus scheduled

give rice to

lend $ to

related to

invite home

give advice to

talk to

visit their home

borrow rice from

med emergencygo to temple with

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take advice from

0.8 0.9 1.0 1.1 1.2 1.3 1.4

Owns latrine versus not

give rice to

lend $ to

give advice to

invite home

go to temple with

borrow rice from

visit their home

related to

talk to


take advice from

0.85 0.90 0.95 1.00 1.05 1.10 1.15

One SD (4.7) increase in educ yrs

give rice to

borrow rice from

related to

invite home

lend $ to

visit their home

take advice from

give advice to

med emergencytalk to

go to temple with

borrow $ from

0.8 1.0 1.2 1.4 1.6 1.8

One SD (12.8) increase in age yrs

go to temple with

give advice to

lend $ to

talk to

give rice to

invite home

borrow rice from


visit their home

take advice from

related to

1 2 3 4 5

Has election card versus not

go to temple with

give advice to

talk to

lend $ to

invite home

visit their home

give rice to


borrow rice from

take advice from

related to

0.5 1.0 1.5 2.0 2.5

Savings group member versus not

related to

take advice from

med emergencygive advice to

visit their home

borrow $ from

talk to

invite home

go to temple with

lend $ to

borrow rice from

give rice to

1.0 1.2 1.4 1.6

Above poverty level versus below

go to temple with

give rice to

lend $ to

give advice to

invite home

talk to

related to

borrow rice from

visit their home

med emergencytake advice from

borrow $ from

Odds of alter being named conditional on alter's characteristics

Figure SA 2. Regression analyses in Tables SA3-SA19 provide estimates of the odds that an alter was nominated in any name generator, conditional on specific characteristics of the alter (shown below each plot). Most plots show that lower status egos are more likely to name social contacts than higher status egos (Ball & Newman, 2013)

0.6 0.8 1.0 1.2 1.4

Male versus female

borrow $ from

go to temple with

talk to

med emergencyvisit their home

related to

invite home

take advice from

lend $ to

borrow rice from

give advice to

give rice to

0.6 0.8 1.0 1.2

High caste versus scheduled

take advice from

borrow $ from

borrow rice from


talk to

invite home

give advice to

go to temple with

related to

lend $ to

give rice to

0.7 0.8 0.9 1.0 1.1

Owns latrine versus not

take advice from

go to temple with

borrow $ from

give advice to

talk to

med emergencyborrow rice from

visit their home

invite home

lend $ to

give rice to

related to

0.90 0.95 1.00 1.05 1.10 1.15

One SD (4.7) increase in educ yrs

borrow $ from

give advice to

take advice from

talk to


borrow rice from

lend $ to

invite home

give rice to

related to

go to temple with

0.85 0.95 1.05 1.15

One SD (12.8) increase in age yrs

go to temple with

take advice from

related to

borrow rice from

give rice to

visit their home

invite home


talk to

lend $ to

give advice to

0.5 0.6 0.7 0.8 0.9

Has election card versus not

take advice from

visit their home

borrow $ from

talk to

invite home


go to temple with

lend $ to

give rice to

give advice to

related to

1.1 1.2 1.3 1.4 1.5 1.6 1.7

Savings group member versus not

give rice to

borrow rice from

visit their home

talk to

invite home

lend $ to


give advice to

related to

take advice from

go to temple with

0.8 0.9 1.0 1.1 1.2 1.3

Above poverty level versus below

take advice from

borrow $ from

give advice to

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talk to


borrow rice from

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related to

Odds of ego naming an alter conditional on ego's characteristics

Figure SA3. There is an increasing relationship between mean social network status (measured by differences between inward and outward nominations and out-degree) and mean demographic status (measured by differences in income, age, and gender) for the social ties generated by each name generator.

1.0 1.5 2.0 2.5 3.0

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Mean difference between ego and alter in-degree

Mea

n di

ffer

ence

bet

wee

n eg

o an

d al

ter

pove

rty

go to temple with

give advice to

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take advice from

R2 = 0.27

1.0 1.5 2.0 2.5 3.0

-0.1

0.0

0.1

0.2

0.3


Mea

n di

ffer

ence

bet

wee

n eg

o an

d al

ter

age

go to temple with

give advice to

lend $ to

give rice to

talk to

borrow $ frominvite home

visit their home borrow rice frommedical emergency

related to

take advice fromR2 = 0.74

1.0 1.5 2.0 2.5 3.0

0.0

0.5

1.0


Mea

n di

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ence

bet

wee

n eg

o an

d al

ter

gend

er

go to temple with

give advice to

lend $ toinvite home

med emergency

visit their home

borrow rice from

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related to

R2 = 0.36

Heirarchical vs Peer Nominations

Figure SA4. Homophily measures for seven individual characteristics for all twelve name generators from Tables SA3-SA19. The higher the measure, the greater the likelihood that egos name alters who are similar on that characteristic.

0 2 4 6 8 10

Gender

Homophily measure

go to temple with

related to

take advice from

give advice to

give rice to

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med emergency

invite home

visit their home

borrow $ from

lend $ to

talk to*

*homophily over 10 not shown1 2 3 4 5 6 7 8

Religion

Homophily measure

go to temple with

talk to

borrow $ from

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lend $ to

visit their home

invite home

give rice to

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related to*

*homophily over 10 not shown1 2 3 4 5 6 7

Caste

Homophily measure

go to temple with

talk to

take advice from

give advice to

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lend $ to

visit their home

invite home

med emergency

give rice to

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related to*

*homophily over 10 not shown

1.0 1.5 2.0 2.5 3.0 3.5 4.0

Lang

Homophily measure

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1.0 1.5 2.0 2.5

Age

Homophily measure

related to

give rice to

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invite home

visit their home

borrow $ from

lend $ to

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1.0 1.2 1.4 1.6 1.8

Poverty Level

Homophily measure

talk to

take advice from

lend $ to

give advice to

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invite home

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1.0 1.1 1.2 1.3 1.4 1.5 1.6

Education

Homophily measure

take advice from

give rice to

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related to

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med emergency

visit their home

lend $ to

invite home

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give advice to

go to temple with

Homophily on individual characteristics

Figure SA5. Homophily measures for three household characteristics for all twelve name generators from Tables SA3-SA19. The higher the measure, the greater the likelihood that egos name alters who are similar on that characteristic.

1.0 1.2 1.4 1.6 1.8

HH Electricity

Homophily measure

talk to

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1.0 1.1 1.2 1.3 1.4 1.5 1.6

HH Bed #

Homophily measure

take advice from

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med emergency

1.0 1.1 1.2 1.3 1.4 1.5

HH Room #

Homophily measure

take advice from

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invite home

give rice to

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go to temple with

Homophily on household characteristics

Figure SA6. Homophily measures for six behavioral characteristics for all twelve name generators from Tables SA3-SA19. The higher the measure, the greater the likelihood that egos name alters who are similar on that characteristic.

1.0 1.2 1.4 1.6 1.8 2.0 2.2

Savings Group

Homophily measure

related to

go to temple with

take advice from

give rice to

give advice to

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med emergencyinvite home

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lend $ to

1.0 1.2 1.4 1.6 1.8 2.0 2.2

Election Card

Homophily measure

related to

go to temple with

give rice to

borrow rice from

med emergencygive advice to

invite home

borrow $ from

lend $ to

visit their home

take advice from

talk to

1.0 1.2 1.4 1.6 1.8

HH Latrine

Homophily measure

take advice from

give advice to

talk to

borrow $ from

lend $ to

visit their home

invite home

med emergencygive rice to

borrow rice from

related to

go to temple with

1.0 1.1 1.2 1.3 1.4 1.5 1.6

Work Out of Village

Homophily measure

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1.0 1.1 1.2 1.3 1.4 1.5 1.6

Micro-finance Participant

Homophily measure

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visit their home

lend $ to

related to

give rice to

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1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35

Have Savings Account

Homophily measure

related to

take advice from

give advice to

go to temple with

give rice to

talk to

invite home

visit their home

borrow $ from

lend $ to


Homophily on behavioral characteristics

Figure SA7. Network measures averaged across all 75 villages for each name generator. Of note are the high network betweenness and closeness centralization scores for the visit and invite home questions. These suggest XXX.

0.05 0.10 0.15 0.20

Mean network transitivity

give advice to

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talk to

borrow $ from

med emergencylend $ to

invite home

visit their home

go to temple with

give rice to

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related to

0.005 0.006 0.007 0.008 0.009 0.010

Mean network density

give advice to

take advice from


borrow $ from

talk to

give rice to

borrow rice from

invite home

go to temple with

visit their home

related to

0.0000 0.0005 0.0010 0.0015 0.0020

Mean network centralization: closeness

go to temple with

take advice from

related to

give advice to

borrow $ from


give rice to

borrow rice from

talk to

visit their home

invite home

0.010 0.015 0.020 0.025 0.030 0.035 0.040

Mean network centralization: degree

go to temple with

give advice to

lend $ to


borrow rice from

give rice to

visit their home

talk to

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related to

take advice from

0.00 0.01 0.02 0.03 0.04 0.05 0.06

Mean network centralization: betweenness

go to temple with

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related to

take advice from

lend $ to


give rice to

borrow rice from

talk to

visit their home

invite home

0.1 0.2 0.3 0.4 0.5

Mean network reciprocity

talk to

borrow $ from

lend $ to

med emergencygive rice to

invite home

related to

visit their home

take advice from

borrow rice from

give advice to

go to temple with

Network characteristics averaged across villages

Socialize

with

Visit their

home

Invite home

Borrow rice from

Give rice to

Get medical advice from

Borrow $ from

Lend money

to

Give advice

to

Take advice from

Go to temple

with

Related to

Socialize with 20929 9915 9102 5894 6270 5741 7004 6285 3911 3861 574 104

Visit their home 9915 25821 18423 10304 11664 9337 10050 8872 5399 5731 864 3587

Invite home 9102 18423 24675 10615 10991 8658 9136 8842 5182 5119 834 3403 Borrow rice

from 5894 10304 10615 21109 15253 8088 7966 8314 4563 4399 881 3248

Give rice to 6270 11664 10991 15253 21683 9268 9296 7943 4847 5114 876 3996 Get medical advice from 5741 9337 8658 8088 9268 17548 9186 7366 4643 5687 1359 4059

Borrow $ from 7004 10050 9136 7966 9296 9186 18679 10829 5469 6886 985 2625

Lend money to 6285 8872 8842 8314 7943 7366 10829 16316 5577 4978 860 2060

Give advice to 3911 5399 5182 4563 4847 4643 5469 5577 14698 7486 2542 1442

Take advice from 3861 5731 5119 4399 5114 5687 6886 4978 7486 18229 2637 2629

Go to temple with 574 864 834 881 876 1359 985 860 2542 2637 7530 169

Related to 104 3587 3403 3248 3996 4059 2625 2060 1442 2629 169 14862

Table SA1. Matrix showing total count of nominations shared between two name generators (for example, did person i name person j as someone they lend money to and also as someone they give advice to?). Diagonal values show the total number of nominations for each name generator.

Socialize

with

Visit their

home

Invite home

Borrow rice from

Give rice to

Get medical advice from

Borrow $ from

Lend money

to

Give advice

to

Take advice from

Go to temple

with

Related to

Socialize with 1.00 0.42 0.40 0.28 0.29 0.30 0.35 0.34 0.22 0.19 0.04 0.00

Visit their home 1.00 0.73 0.44 0.49 0.44 0.45 0.43 0.27 0.26 0.06 0.18

Invite home 1.00 0.46 0.47 0.41 0.42 0.44 0.27 0.24 0.06 0.17

Borrow rice from 1.00 0.71 0.42 0.40 0.45 0.26 0.22 0.07 0.18

Give rice to 1.00 0.47 0.46 0.42 0.27 0.25 0.07 0.22 Get medical advice

from 1.00 0.51 0.43 0.29 0.32 0.12 0.25

Borrow $ from 1.00 0.62 0.33 0.37 0.08 0.15

Lend money to 1.00 0.36 0.29 0.08 0.13

Give advice to 1.00 0.46 0.24 0.09

Take advice from 1.00 0.22 0.16

Go to temple with 1.00 0.01

Related to 1.00

Table SA2. Matrix showing simple Pearson correlation between each pair of name generators.

Table SA3 - Logistic regression model showing likeihood of a tie between ego and alter conditional on ego gender, alter gender, and a binary measure of ego-alter gender homophily across 12 different name generators. All gender models show female compared to male (reference).

Name Generator Socialize with

Visit their home

Invite home

Borrow rice from

Give rice to

Emergency help

Borrow $

Lend money

to

Give advice

to

Take advice from

Go to temple

with

Related to

Ego female beta 0.57 0.46 0.22 -0.28 -0.02 0.53 0.65 0.13 -0.01 0.19 0.59 0.31 (se) (-0.03) (-0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) Alter female -0.09 -0.08 -0.48 0.29 -0.13 -1.03 -1.08 -0.42 -0.28 -1.01 0.64 -1.96 (se) (0.04) (0.03) (0.02) (0.02) (0.02) (0.03) (0.03) (0.03) (0.02) (0.02) (0.03) (0.03) Ego gender = alter ego 2.66 2.16 2.09 1.41 1.54 1.81 2.24 2.32 1.07 0.98 -0.24 0.54 (se) (0.04) (0.03) (0.02) (0.02) (0.02) (0.03) (0.03) (0.03) (0.02) (0.02) (0.03) (0.03) Same household -1.28 -1.37 -1.19 -0.08 -0.86 2.36 1.42 0.76 4.53 4.72 6.4 0.3 (se) (8.18) (0.16) (0.15) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.09)

Table SA4 - Logistics regression model showing likeihood of a tie between ego and alter conditional on ego education in years, alter education in years, and a binary measure of ego-alter education in years similarity across 12 different name generators.


Visit their home

Invite Home

Borrow rice from

Give rice to

Emergency help

Borrow $

Lend money

to

Give advice

to

Take advice from

Go to temple

with

Related to

Ego education -0.01 0 0 0 0 -0.01 0.01 0 -0.01 -0.01 0.02 0.01 (se) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Alter education 0.02 0 -0.01 -0.03 -0.02 0.01 0.03 -0.01 0.01 0.01 0.02 -0.02 (se) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Ego education = alter education 0.39 0.36 0.38 0.3 0.3 0.32 0.32 0.37 0.39 0.26 0.4 0.32 (se) (0.02) (0.01) (0.01) (0.02) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) Same household -1.28 -1.37 -1.19 -0.08 -0.86 2.36 1.42 0.76 4.53 4.72 6.4 0.3 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.03) (0.06) (0.07) (0.02) (0.02) (0.03) (0.08) *For homophily on education we took the absolute value of the difference between egos and alters education and then coded each dyad as 1 if it was below the median difference in values and 0 if it was above.

Table SA5 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego age in years, alter ego in years, and a binary measures of ego-alter age in years similarity across 12 different name generators.


Visit their home

Invite home

Borrow rice from

Give rice to

Emergency help

Borrow $

Lend money

to

Give advice

to

Take advice from

Go to temple

with

Related to

Ego age 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 (se) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Alter age 0.01 0.02 0.01 0.01 0.01 0.01 0.02 0.01 0.00 0.04 -0.01 0.05 (se) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Close to = alter age 0.69 0.56 0.55 0.38 0.43 0.53 0.57 0.61 0.75 0.65 0.97 0.29 (se) (0.01) (0.01) (0.01) (0.01) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) Same household -1.72 -1.75 -1.58 -1.08 -1.18 2.01 1.03 0.33 4.27 4.48 4.43 0.20 (se) (0.01) (0.06) (0.15) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.09) *For homophily on education we took the absolute value of the difference between egos and alters age and then coded each dyad as 1 if it was below the median difference in values and 0 if it was above.

Table SA6 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego caste, alter caste, and a binary measures of ego-alter caste across 12 different name generators. All caste categories compared to scheduled caste (reference).


Visit their home

Invite Home

Borrow rice from

Give rice to

Emergency help

Borrow $

Lend money

to

Give advice

to

Take advice from

Go to temple

with

Related to

Ego scheduled tribe 0.28 0.29 0.29 0.36 0.3 0.26 0.21 0.29 0.20 0.12 0.10 0.34 (se) (0.03) (0.03) (0.03) (0.04) (0.04) (0.04) (0.04) (0.04) (0.05) (0.04) (0.11) (0.07) Ego other backwards caste -0.3 -0.31 -0.28 -0.27 -0.34 -0.34 -0.46 -0.24 -0.20 -0.41 -0.13 -0.20 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (0.05) (0.04) Ego general caste -0.1 -0.14 -0.05 0.15 -0.23 -0.2 -0.43 0.06 -0.02 -0.5 -0.02 -0.01 (se) (0.03) (0.0)3 (0.03) (0.03) (0.04) (0.04) (0.03) (0.04) (0.04) (0.04) (0.08) (0.07) Alter scheduled tribe 0.40 0.41 0.38 0.31 0.4 0.39 0.43 0.29 0.16 0.21 0.11 0.35 (se) (0.04) (0.04) (0.04) (0.04) (0.04) (0.05) (0.04) (0.04) (0.06) (0.05) (0.11) (0.07) Alter other backwards caste -0.07 -0.15 -0.22 -0.29 -0.2 -0.13 0.06 -0.27 -0.13 0.17 -0.04 -0.36 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (0.03) (0.03) (0.03) (-0.05) (0.04) Alter general caste 0.28 0.31 0.15 -0.16 0.34 0.38 0.6 -0.06 0.15 0.65 0.45 0.03 (se) (0.03) (0.03) (0.03) (0.04) (0.01) (0.04) (0.03) (0.04) (0.05) (0.04) (-0.08) (0.07) Ego caste = alter caste 1.14 1.57 1.6 1.77 1.85 1.75 1.5 1.56 1.46 1.36 1.13 2.79 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (-0.06) (0.04) Same household -2.16 -2.34 -2.2 -1.74 -1.86 1.41 0.49 -0.23 3.76 3.99 5.98 -0.51 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (-0.04) (0.09)

Table SA7 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego religion, alter religion, and a binary measures of ego-alter similarity on religion across 12 different name generators. All religion categories compared to Hindu (reference).


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Ego Muslim 0.72 0.86 0.85 0.81 0.89 0.79 0.49 0.69 0.49 0.62 -0.68 0.95 (se) (0.05) (0.05) (0.05) (0.06) (0.06) (0.06) (0.07) (0.06) (0.07) (0.07) (0.24) (0.12) Ego Chrisitan 1.15 1.41 1.53 1.7 1.71 1.48 0.89 1.57 0.89 1.07 0.66 2.46 (se) (0.17) (0.16) (0.18) (0.17) (0.19) ( 0.23) (0.35) (0.18) (0.35) (0.27) (1.10) (0.59) Alter Muslim 0.17 0.23 0.23 0.29 0.20 0.27 0.11 0.31 0.11 0.02 -0.47 0.44 (se) (0.06) (0.05) (0.06) (0.06) (0.06) (0.07) (0.08) (0.06) (0.08) (0.08) (0.24) (0.12) Alter Christian 1.24 1.3 1.38 1.46 1.5 1.18 0.51 1.24 0.51 0.43 -0.4 1.59 (se) (0.24) (0.21) (0.21) (0.21) (0.22) (0.31) (0.45) (0.24) (0.45) (0.40) (1.13) (0.70) Ego religion = alter religion 1.46 1.69 1.83 1.85 1.9 1.92 1.55 1.65 1.55 1.62 1.40 3.45 (se) (0.06) (0.05) (0.05) (0.06) (0.06) (0.07) (0.08) (0.06) (0.08) (0.08) (0.26) (0.14) Same household -1.79 -1.85 -1.68 -1.19 -1.29 1.92 4.20 0.24 4.2 4.39 6.36 0.06 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.04) (0.02) (0.08) (0.02) (0.02) (0.03) (0.09)

Table SA8 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego mother tongue, alter mother tongue, and a binary measure of ego-alter similarity on mother tongue across 12 different name generators. All language categories compared to speaking Kannada (reference).


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Ego Tamil 0.37 0.39 0.41 0.23 0.35 0.27 0.34 0.31 0.27 0.23 0.04 0.29 (se) (0.04) (0.04) (0.04) (0.05) (0.04) (0.05) (0.05) (0.05) (0.05) (0.05) (0.10) (0.06) Ego Teiugu 0.15 0.19 0.20 0.15 0.23 0.20 0.26 0.15 0.05 0.25 -0.03 0.03 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (0.03) (0.03) (0.03) (0.05) (0.04) Ego Urdu 0.27 0.43 0.4 0.37 0.44 0.4 0.38 0.29 0.15 0.29 -0.86 0.41 (se) (0.04) (0.03) (0.03) (0.04) (0.03) (0.04) (0.04) (0.04) (0.04) (0.04) (0.11) (0.04) Ego Other 0.33 0.67 0.65 0.65 0.40 0.67 0.64 0.54 0.49 0.6 0.11 0.54 (se) (0.17) (0.13) (0.15) (0.16) (0.19) (0.16) (0.17) (0.19) (0.17) (0.15) (0.47) (0.26) Alter Tamil 0.23 0.20 0.21 0.34 0.18 0.12 0.10 0.27 0.17 0.01 -0.15 0.50 (se) (0.05) (0.05) (0.05) (0.05) (0.05) (0.06) (0.05) (0.06) (0.06) (0.06) (0.10) (0.07) Alter Telugu 0.02 0.06 0.08 0.18 0.06 -0.03 -0.09 0.12 0.04 -0.25 -0.14 0.10 (se) (0.02) (0.02) (0.02) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.05) (0.04) Alter Urdu -0.08 0.06 0.07 0.16 0.05 0.10 -0.10 0.08 0.01 -0.07 -0.62 .036 (se) (0.05) (0.04) (0.04) (0.04) (0.04) (0.05) (0.05) (0.05) (0.05) (0.05) (0.10) (0.05) Alter Other -0.18 0.20 0.07 0.13 0.10 -1.01 -0.04 0.15 0.16 0.11 -0.16 0.71 (se) (0.21) (0.17) (0.19) (0.20) (0.20) (0.21) (0.22) (0.23) (0.21) (0.19) (0.47) (0.21) Ego language = alter language 0.60 0.81 0.80 0.96 0.94 0.92 .0.77 0.79 0.60 0.67 0.46 1.26 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (0.03) (0.03) (0.03) (0.05) (0.03) Same household -1.82 -1.90 -1.72 -1.25 -1.34 1.86 0.90 0.19 4.15 4.34 6.31 0.02 (se) (0.18) (0.16) (0.15) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.842)

Table SA9 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego household room number, alter household room number, and a binary measures of ego-alter household room number similarity across 12 different name generators.


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Ego room # 0.01 0.01 0.01 0.02 0.00 0.00 -0.02 0.01 -0.03 -0.08 -0.05 0.02 (se) (0.01) (0.00) (0.00) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.02) (0.01) Alter room # 0.03 0.02 0.00 -0.05 0.00 0.01 0.06 -0.03 -0.03 0.05 -0.04 -0.01 (se) (0.01) (0.00) (0.00) (0.01) (0.01) (0.01) (0.00) (0.01) (0.01) (0.01) (0.02) (0.01) Ego room # = alter room # 0.15 0.20 0.23 0.23 0.24 0.19 0.17 0.17 0.13 0.05 0.32 0.26 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.06) (0.02) Same household -1.78 -1.83 -1.65 -1.13 -1.25 1.95 0.96 0.29 4.24 4.46 6.33 0.14 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.03) (0.05) (0.08) (0.02) (0.02) (0.03) (0.08)

*For homophily on household room number we took the absolute value of the difference between egos and alters household room number and then coded each dyad as 1 if it was below the median difference in values and 0 if it was above.

Table SA10 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego household bed number, alter household bed number, and a binary measure of ego-alter household bed number similarity across 12 different name generators.


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Ego bed # 0.01 0.01 0.01 0.02 0.00 0.01 -0.01 0.02 -0.02 -0.07 0.00 0.02 (se) (0.00) (0.00) (0.00) (0.00) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) Alter bed # 0.01 0.00 -0.02 -0.05 -0.01 0.02 0.04 -0.03 -0.04 0.03 -0.03 0.01 (se) (0.00) (0.00) (0.01) (0.01) (0.01) (0.01) (0.00) (0.01) (0.01) (0.01) (0.01) (0.01) Ego bed # = alter bed # 0.20 0.30 0.30 0.29 0.32 0.40 0.25 0.30 0.15 0.07 0.37 0.31 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.06) (0.02) Same household -1.78 -1.83 1.65 1.13 1.25 1.90 0.96 0.27 4.24 4.46 6.32 0.14 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.03) (0.05) (0.08) (0.02) (0.02) (0.03) (0.08) *For homophily on household bed number we took the absolute value of the difference between egos and alter household bed number and then coded each dyad as 1 if it was below the median difference in values and 0 if it was above.

Table SA11 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego household latrine ownership, alter household latrine ownership, and a binary measure of ego-alter household latrine ownership similarity across 12 different name generators. Latrine measures compared to those with no latrine (reference).


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Ego latrine -0.04 -0.03 0.00 0.06 -0.03 -0.04 -0.13 0.05 -0.07 -0.27 -0.17 0.08 (se) (0.02) (0.01) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.05) (0.02) Alter latrine 0.12 0.08 0.02 -0.11 0.06 0.14 0.29 -0.06 -0.04 0.31 0.03 0.10 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.05) (0.02) Ego latrine = alter latrine 0.30 0.36 0.38 0.42 0.43 0.39 0.33 0.36 0.29 0.25 0.49 0.47 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.06) (0.02) Same household -1.82 -1.91 -1.73 -1.21 -1.34 1.87 0.91 0.21 4.16 4.37 6.24 0.05 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.04) (0.09)

Table SA12 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego saving group membership (SGM), alter saving group membership (SGM) , and a binary measure of ego-alter saving group membership (SGM) across 12 different name generators. Savings group measure compared to those who do not participate in a savings group (reference).


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Ego SGM 0.28 0.28 0.28 0.17 0.22 0.29 0.31 0.29 0.32 0.35 0.45 0.33 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.04) (0.03) Alter SGM 0.60 0.55 0.61 0.85 0.74 0.42 0.57 0.67 0.54 0.19 0.61 -0.74 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.04) (0.03) Ego SGM = alter SGM 0.75 0.70 0.69 0.58 0.65 0.66 0.77 0.78 0.60 0.47 0.29 0.27 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.04) 0.03 Same household -1.68 -1.71 -1.54 -1.03 -1.13 22.05 1.07 0.38 4.30 4.48 6.45 0.23 (se) (0.18) (0.16) (0.15) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.09)

Table SA13 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego election card ownership (EC), alter election card ownership (EC), and a binary measure of ego-alter election card ownership (EC) across 12 different name generators. Election card measures are compared to those without an election card (reference).


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Ego EC -0.41 -0.44 -0.41 -0.28 -0.35 -0.40 -0.42 -0.32 -0.22 -0.56 -0.35 -0.22 (se) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.04) (0.05) (0.07) Alter EC 0.09 0.09 0.28 0.40 0.53 0.48 0.49 0.10 -0.01 0.76 -0.17 1.53 (se) (0.03) (0.35) (0.03) (0.03) (0.03) (0.04) (0.04) (0.04) (0.04) (0.04) (0.05) (0.07) Ego EC = alter EC 0.73 0.73 0.61 0.38 0.44 0.55 0.62 0.64 0.58 0.69 0.37 0.28 (se) (0.03) 0.65 (0.03) (0.03) (0.03) (0.04) (0.04) (0.04) (0.04) (0.04) (0.05) (0.07) Same household -1.71 -1.74 -1.57 -1.07 -1.16 2.03 1.05 0.35 4.27 4.48 6.39 0.25 (se) (0.18) (0.16) (0.15) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.09)

Table SA14 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego savings account ownership (SA), alter savings account ownership (SA) , and a binary measure of ego-alter savings account ownership (SA) across 12 different name generators. Savings group measures are compared to those who do not participate in a savings group.


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Ego SA 0.07 0.07 0.11 0.08 0.05 0.05 0.05 0.16 0.17 0.06 0.20 0.11 (se) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.02) (0.01) (0.03) (0.02) Alter SA 0.43 0.43 0.41 0.39 0.45 0.43 0.57 0.40 0.38 0.56 0.30 0.14 (se) (0.02) (0.01) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) Ego SA = alter SA 0.23 0.24 0.24 0.22 0.26 0.25 0.24 0.25 0.19 0.14 0.2 0.11 (se) (0.02) (0.01) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) Same household -1.70 -1.73 -1.58 -1.08 -1.18 2.03 1.04 0.34 4.28 4.49 6.41 0.23 (se) (0.18) (0.18) (0.16) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.09)

Table SA15 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego working outside the village, alter working outside the village, and a binary measure of ego-alter similarity on working outside the village across 12 different name generators. Working outside the village compared to those who work but not outside the village (reference).


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Ego work 0.17 0.16 0.15 0.15 0.17 0.14 0.18 0.14 0.12 0.15 0.13 0.13 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.03) (0.05) (0.03) Alter work -0.01 -0.03 0.03 -0.04 -0.07 0.03 -0.09 0.06 0.04 -0.12 -0.01 0.13 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.03) (0.05) 0.03 Ego work = alter work 0.32 0.38 0.36 0.39 0.37 0.35 0.32 0.34 0.22 0.22 0.18 0.29 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.03) (0.05) (0.03) Same household -1.96 -2.25 -1.85 -1.09 -1.24 1.89 0.62 -0.25 4.18 4.27 6.34 0.26 (se) (0.30) (0.32) (0.27) (0.20) (0.21) (0.05) (0.09) (0.15) (0.03) (0.03) (0.05) (0.12)

Table SA16 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego micro-finance participation (MF), alter saving group membership (SGM) , and a binary measure of ego-alter similarity on micro-finance participation (MF) across 12 different name generators. Micro-finance participation (MF) compared to thoes who did not participate within villages where micro-finance was available (reference).


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Ego MF 0.20 0.21 0.21 0.24 0.25 0.18 0.22 0.21 0.08 0.15 0.05 0.27 (se) (0.03) (0.02) (0.02) (0.02) (0.02) (0.03) (0.03) (0.03) (0.03) (0.03) (0.07) (0.03) Alter MF 0.13 0.19 0.24 0.31 0.24 0.16 0.10 0.28 0.11 -0.05 -0.14 0.23 (se) (0.03) (0.02) (0.02) (0.02) (0.02) (0.03) (0.03) (0.03) (0.03) (0.03) (0.07) (0.03) Ego MF = alter MF 0.28 0.34 0.34 0.41 0.41 0.33 0.32 0.36 0.25 0.24 0.23 0.37 (se) (0.03) (0.02) (0.02) (0.02) (0.02) (0.03) (0.03) (0.03) (0.03) (0.03) (0.08) (0.03) Same household -1.61 -1.78 -1.65 -1.25 -1.16 2.23 1.04 0.24 4.24 4.42 6.53 0.31 (se) (0.21) (0.21) (0.20) (0.17) (0.16) (0.04) (0.06) (0.10) (0.03) (0.02) (0.04) (0.10)

Table SA17 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego household electricity status, and a binary measure of ego-alter similarity on electricity status across 12 different name generators. All electricity categories compared to having private electricity (reference).


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Ego Govt. Electric 0.12 0.15 0.14 0.13 0.18 0.17 0.22 0.11 0.11 0.28 0.09 0.17 (se) (0.02) (0.01) (0.01) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.05) (0.02) Ego No Electric 0.31 0.33 0.30 0.26 0.35 0.34 0.39 0.25 0.23 0.46 0.23 0.24 (se) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.04) (0.03) (0.09) (0.04) Alter Govt. Electric -0.02 0.06 0.11 0.22 0.09 0.03 -0.13 0.17 0.09 -0.21 -0.06 0.12 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.05) (0.02) Alter No Electric -0.06 0.06 0.15 0.30 0.13 0.07 -0.15 0.26 0.12 -0.21 0.08 0.20 (se) (0.04) (0.03) (0.03) (0.03) (0.03) (0.04) (0.04) (0.04) (0.04) (0.04) (0.09) (0.04) Ego electricity = alter electricity 0.30 0.37 0.38 0.38 0.41 0.41 0.35 0.35 0.36 0.38 0.31 0.52 (se) (0.02) (0.02) (0.05) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.06) (0.02) Same household -1.83 -1.89 -1.72 -1.23 -1.33 1.86 0.91 0.20 4.12 4.31 6.27 0.03 (se) (0.18) (0.16) (0.15) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.04) (0.09)

Table SA18 - Logistic regression model showing likelihood of a tie between ego and alter conditional on ego poverty card status, and a binary measure of ego-alter similarity on poverty card status across 12 different name generators. All poverty status categories compared to above level (reference).


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to

Take advice from

Go to temple

with

Related to

Ego below proverty -0.08 -0.13 -0.15 -0.19 -0.15 -0.10 -0.01 -0.17 -0.05 0.12 -0.06 -0.20 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) Ego no card -0.04 0.01 -0.01 -0.03 0.02 0.00 0.03 -0.08 -0.03 0.11 -0.06 0.02 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (0.03) (0.03) (0.03) (0.05) (0.03) Alter below proverty -0.24 -0.29 -0.22 -0.09 -0.29 -0.34 -0.47 -0.12 -0.16 -0.45 -0.04 -0.24 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) (0.05) (0.02) Alter no card -0.26 -0.36 -0.30 -0.21 -0.39 -0.39 -0.46 -0.22 -0.22 -0.55 -0.08 -0.51 (se) (0.03) (0.02) (0.02) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.05) (0.03) Ego poverty = alter poverty 0.31 0.42 0.43 0.43 0.49 0.43 0.39 0.37 0.38 0.33 0.47 0.52 (se) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.03) (0.02) Same household -1.80 -1.88 -1.70 -1.20 -1.34 1.89 0.90 0.23 4.16 4.37 6.28 0.07 (se) (0.18) (0.17) (0.16) (0.13) (0.14) (0.04) (0.06) (0.08) (0.02) (0.02) (0.03) (0.09)

supplementary information - university of california, san...

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