Treatment assignment and balance

Treatment assignment

Treatment assignment
sarpanchgendercaste_combination N Percent
bharti kamble 599 25.32
bharti marathe 589 24.89
rohit kamble 570 24.09
rohit marathe 608 25.70

Balance

bharti kamble (N=599) bharti marathe (N=589) rohit kamble (N=570) rohit marathe (N=608)
Proportions across treatment groups, each pre-specified covariate
Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.
rural 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
age 35.9 10.3 35.6 10.4 36.8 11.1 36.2 10.3
gender 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
knowledge_local_politics 0.9 0.3 0.9 0.3 0.9 0.3 0.9 0.3
gender_norms 89.1 17.2 87.7 17.7 87.9 18.2 88.3 18.2
N Pct. N Pct. N Pct. N Pct.
religion Adivasi/Sarna 19 3.2 31 5.3 23 4.0 33 5.4
Buddhist 72 12.0 80 13.6 62 10.9 79 13.0
Christian 2 0.3 0 0.0 2 0.4 0 0.0
Hindu 360 60.1 321 54.5 342 60.0 338 55.6
Jain 1 0.2 0 0.0 2 0.4 0 0.0
Muslim 145 24.2 157 26.7 139 24.4 158 26.0
caste Maratha 69 11.5 49 8.3 48 8.4 52 8.6
OBC 215 35.9 214 36.3 208 36.5 230 37.8
Other General Caste 86 14.4 85 14.4 89 15.6 83 13.7
Scheduled Caste (Dalit) 103 17.2 111 18.8 101 17.7 105 17.3
Scheduled Tribe (Adivasi) 121 20.2 125 21.2 120 21.1 133 21.9
VJNT (Bhatke Vimukt) 5 0.8 5 0.8 4 0.7 5 0.8
education Primary school or less 92 15.4 72 12.2 92 16.1 86 14.1
Secondary school 326 54.4 339 57.6 309 54.2 351 57.7
Undergraduate and above 181 30.2 178 30.2 169 29.6 171 28.1
prior_vote No 103 17.2 115 19.5 90 15.8 100 16.4
Yes 496 82.8 474 80.5 480 84.2 508 83.6
Balance test
Bharti Kamble Bharti Marathe Rohit Kamble Rohit Marathe
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Each model is a linear regression of each treatment group indicator on covariates. All regressions use robust standard errors.
Rural 0.019 −0.031 −0.004 0.017
(0.021) (0.021) (0.021) (0.021)
Age −0.001 −0.000 0.001 0.000
(0.001) (0.001) (0.001) (0.001)
Gender 0.020 −0.030+ −0.039* 0.049**
(0.018) (0.018) (0.018) (0.019)
religionBuddhist 0.084 −0.021 −0.050 −0.014
(0.063) (0.066) (0.064) (0.066)
religionChristian 0.338 −0.282*** 0.237 −0.293***
(0.282) (0.058) (0.287) (0.057)
religionHindu 0.079+ −0.042 0.037 −0.074
(0.044) (0.049) (0.046) (0.050)
religionJain 0.189 −0.309*** 0.416 −0.296***
(0.342) (0.058) (0.354) (0.057)
religionMuslim 0.065 −0.016 −0.003 −0.046
(0.049) (0.054) (0.051) (0.055)
casteOBC −0.066+ 0.021 0.029 0.016
(0.036) (0.033) (0.033) (0.033)
casteOther General Caste −0.039 −0.011 0.066 −0.017
(0.045) (0.042) (0.043) (0.044)
casteScheduled Caste (Dalit) −0.076 0.035 0.075 −0.035
(0.050) (0.047) (0.049) (0.047)
casteScheduled Tribe (Adivasi) −0.069+ 0.039 0.026 0.003
(0.041) (0.038) (0.037) (0.038)
casteVJNT (Bhatke Vimukt) −0.042 0.014 0.003 0.024
(0.110) (0.108) (0.098) (0.104)
educationSecondary school −0.036 0.048+ −0.040 0.028
(0.029) (0.028) (0.029) (0.029)
educationUndergraduate and above −0.033 0.042 −0.027 0.017
(0.035) (0.034) (0.034) (0.034)
prior_voteYes 0.010 −0.036 0.015 0.011
(0.026) (0.026) (0.025) (0.025)
Knowledge of local politics 0.001 0.007 0.004 −0.012
(0.029) (0.029) (0.028) (0.030)
Gender norms 0.001 −0.001 −0.000 −0.000
(0.001) (0.001) (0.001) (0.001)
Num.Obs. 2359 2359 2359 2359
R2 0.007 0.008 0.009 0.007
F.statistic 0.917 12.792 1.039 20.059
F.p.value 0.558 0 0.411 0

Pre-registered main and secondary hypotheses.

  • M1: The male advantage in authority. I expect that relative to female presidents, hypothetical male presidents will be more likely to be perceived to possess authority (Outcome 1).
  • M2: The dominant caste advantage in authority. I expect that relative to Dalit presidents, hypothetical Maratha presidents will be more likely to be perceived to possess authority (Outcome 1).
  • M3: The male advantage in pliability. I expect that relative to female presidents, hypothetical male presidents will be less likely to be perceived to be willing to resign (Outcome 2).
  • M4: The dominant caste advantage in pliability. I expect that relative to Dalit presidents, hypothetical Maratha presidents will likely to be perceived to be willing to resign (Outcome 2).
  • S1: The dominant caste advantage in backlash. I expect that relative to Dalit presidents, hypothetical Maratha presidents will be less likely to be perceived to face backlash (Outcome 3).
  • S2: The male advantage in backlash? Relative to female presidents, it is unclear whether hypothetical male presidents will be less likely to be perceived to face backlash (Outcome 3). On one hand, it could be negative, if regardless of community, women who gain power are perceived as a threat to dominance. On the otherhand, it could be zero, if women who gain power within the dominant caste group are not perceived as a threat to dominance. I expect a potential gender effect to be weaker than the caste effect for this outcome, as political violence in this context often occurs among community lines.
M1: Male advantage in authority M2: Dominant caste advantage in authority M3: Male advantage in pliability M4: Dominant caste advantage in pliability S1: Male advantage in backlash? S2: Dominant caste advantage in backlash
Pre-registered main and secondary hypotheses
Unadjusted Covariate-adjusted Unadjusted Covariate-adjusted Unadjusted Covariate-adjusted Unadjusted Covariate-adjusted Unadjusted Covariate-adjusted Unadjusted Covariate-adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Each model is a linear regression of each treatment indicator (either male or Maratha) on each outcome, corresponding to each hypothesis. For each hypothesis, unadjusted and covariate-adjusted estimates are presented. All regressions use robust standard errors.
Male 0.044* 0.049** −0.038+ −0.042* −0.004 −0.007
(0.019) (0.019) (0.020) (0.019) (0.021) (0.020)
Maratha 0.148*** 0.139*** −0.100*** −0.099*** −0.113*** −0.114***
(0.019) (0.019) (0.020) (0.019) (0.020) (0.020)
rural 0.029 0.031 0.030 0.028 0.106*** 0.104***
(0.023) (0.023) (0.023) (0.023) (0.024) (0.023)
age −0.002 −0.002 0.005*** 0.005*** 0.003** 0.003**
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
gender 0.019 0.016 0.043* 0.045* 0.008 0.011
(0.020) (0.019) (0.020) (0.020) (0.021) (0.021)
religionBuddhist −0.154* −0.151* −0.041 −0.041 0.010 0.006
(0.065) (0.065) (0.069) (0.068) (0.074) (0.074)
religionChristian −0.036 0.041 −0.134 −0.187 0.272 0.207
(0.254) (0.259) (0.222) (0.226) (0.309) (0.309)
religionHindu −0.116* −0.102* 0.036 0.027 0.008 −0.004
(0.049) (0.047) (0.050) (0.049) (0.055) (0.054)
religionJain 0.202*** 0.292*** −0.340*** −0.394*** −0.033 −0.103
(0.056) (0.059) (0.074) (0.064) (0.324) (0.324)
religionMuslim 0.080 0.086+ −0.031 −0.033 0.225*** 0.218***
(0.051) (0.050) (0.055) (0.054) (0.060) (0.060)
casteOBC −0.035 −0.037 0.081* 0.082* −0.091* −0.087*
(0.038) (0.038) (0.038) (0.037) (0.039) (0.039)
casteOther General Caste 0.013 0.019 0.133** 0.128** −0.033 −0.035
(0.045) (0.045) (0.048) (0.048) (0.050) (0.050)
casteScheduled Caste (Dalit) 0.130* 0.132* 0.035 0.034 −0.112* −0.111*
(0.051) (0.052) (0.053) (0.053) (0.055) (0.055)
casteScheduled Tribe (Adivasi) −0.002 −0.005 −0.031 −0.029 −0.128** −0.124**
(0.044) (0.043) (0.042) (0.042) (0.044) (0.044)
casteVJNT (Bhatke Vimukt) 0.098 0.095 0.284* 0.286* −0.095 −0.091
(0.099) (0.100) (0.124) (0.124) (0.115) (0.116)
educationSecondary school 0.118*** 0.107*** 0.026 0.034 −0.064* −0.056+
(0.031) (0.031) (0.031) (0.031) (0.032) (0.032)
educationUndergraduate and above 0.094* 0.085* 0.022 0.029 −0.046 −0.040
(0.037) (0.036) (0.037) (0.037) (0.039) (0.039)
knowledge_local_politics 0.011 0.011 −0.071* −0.071* 0.036 0.036
(0.029) (0.029) (0.033) (0.033) (0.033) (0.033)
gender_norms −0.002** −0.002** 0.003*** 0.002*** −0.001* −0.001*
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Num.Obs. 2347 2341 2347 2341 2347 2341 2347 2341 2346 2340 2346 2340
R2 0.002 0.057 0.025 0.076 0.002 0.038 0.011 0.047 0.000 0.048 0.013 0.061

Exploratory analyses.

Means by intersectional identity.

Qualitative responses to questions 1, 2, and 3.

## TableGrob (2 x 1) "arrange": 2 grobs
##   z     cells    name           grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (2-2,1-1) arrange gtable[layout]

## TableGrob (2 x 1) "arrange": 2 grobs
##   z     cells    name           grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (2-2,1-1) arrange gtable[layout]

## TableGrob (2 x 1) "arrange": 2 grobs
##   z     cells    name           grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (2-2,1-1) arrange gtable[layout]