Descriptives, treatment assignment, compliance and balance

Descriptives

Sample descriptives, France
Mean SD N Percent
age 18-24 years old 174 8.61
25-34 years old 320 15.83
35-44 years old 380 18.80
45-54 years old 437 21.62
55-64 years old 400 19.79
65-74 years old 253 12.52
75+ years old 57 2.82
ambivalent_sexism_index 3.34 0.63 2021 100.00
pro_sociality_index 3.34 0.72 2021 100.00
climate_beliefs A great deal 396 19.59
A little 250 12.37
A lot 632 31.27
Don't know 46 2.28
Moderately 604 29.89
Not at all 93 4.60
trust_government Don't know 190 9.40
Just about always 135 6.68
Most of the time 508 25.14
Only some of the time 1188 58.78
male 0 1014 50.17
1 1006 49.78
has_children 0 673 33.30
1 1348 66.70
religiosity 0 854 42.26
1 540 26.72
2 378 18.70
3 104 5.15
4 114 5.64
5 31 1.53
owner_domicile 0 741 36.67
1 1229 60.81
participated_protest_last_12_months 0 1618 80.06
1 403 19.94
demanded_action_last_12_months 0 1613 79.81
1 408 20.19
employment A homemaker or stay-at-home parent 61 3.02
Other: 24 1.19
Retired 381 18.85
Student 69 3.41
Unemployed and looking for work 86 4.26
Working full-time 1231 60.91
Working part-time 169 8.36
education Informal education only (including Koranic school) 34 1.68
No formal education 30 1.48
Post-university 135 6.68
Primary school 42 2.08
Secondary school 867 42.90
University 913 45.18
nationality East Asia 6 0.30
Eastern Europe (outside France) 36 1.78
France 1809 89.51
Latin America 7 0.35
North Africa 65 3.22
North America 3 0.15
Oceania 3 0.15
South Asia 5 0.25
Sub-Saharan Africa 21 1.04
Western Europe (outside France) 66 3.27
Sample descriptives, Ivory Coast
Mean SD N Percent
age 18-24 years old 541 31.64
25-34 years old 665 38.89
35-44 years old 329 19.24
45-54 years old 142 8.30
55-64 years old 32 1.87
75+ years old 1 0.06
ambivalent_sexism_index 3.62 0.67 1710 100.00
pro_sociality_index 3.90 0.69 1710 100.00
climate_beliefs A great deal 407 23.80
A little 284 16.61
A lot 584 34.15
Don't know 45 2.63
Moderately 311 18.19
Not at all 79 4.62
trust_government Don't know 328 19.18
Just about always 248 14.50
Most of the time 542 31.70
Only some of the time 592 34.62
male 0 687 40.18
1 1007 58.89
has_children 0 904 52.87
1 806 47.13
religiosity 0 116 6.78
1 262 15.32
2 311 18.19
3 272 15.91
4 443 25.91
5 306 17.89
owner_domicile 0 1196 69.94
1 307 17.95
participated_protest_last_12_months 0 1267 74.09
1 443 25.91
demanded_action_last_12_months 0 1314 76.84
1 396 23.16
employment A homemaker or stay-at-home parent 33 1.93
Other: 28 1.64
Retired 9 0.53
Student 376 21.99
Unemployed and looking for work 235 13.74
Working full-time 710 41.52
Working part-time 319 18.65
education Informal education only (including Koranic school) 9 0.53
No formal education 24 1.40
Post-university 87 5.09
Primary school 33 1.93
Secondary school 407 23.80
University 1150 67.25
ethnicity Abbey 59 3.45
Abron 43 2.51
Adjoukrou 72 4.21
Agni 169 9.88
Attié 95 5.56
Avikam 14 0.82
Bambara 39 2.28
Baoulé 415 24.27
Bété 123 7.19
Dida 39 2.28
Dioula 86 5.03
Don't know 42 2.46
Godié 11 0.64
Gouro 48 2.81
Guéré 58 3.39
Koulango 25 1.46
Kroumen 14 0.82
Lobi 4 0.23
Malinké/Maninka 62 3.63
Only Ivoirian (do not identify in these terms) 106 6.20
Senoufo 124 7.25
Yacouba 62 3.63

Treatment assignment and compliance

Treatment assignment
treatment N Percent
Man_agent 937 25.11
Man_victim 933 25.01
Woman_agent 924 24.77
Woman_victim 937 25.11
photo_recall gender_photo victim_agent_photo
Treatment received
treatment Man holding bucket Man holding sign Woman holding bucket Woman holding sign Don’t know Man There was no person in the photo Woman Don’t know The person was a victim of climate change The person was mobilizing to combat climate change
Man_agent 36.00 839.00 14.00 48.00 12.00 867.00 3.00 55.00 35.00 453.00 449.00
Man_victim 702.00 40.00 166.00 25.00 6.00 743.00 3.00 181.00 35.00 796.00 102.00
Woman_agent 7.00 82.00 28.00 807.00 3.00 79.00 3.00 839.00 20.00 319.00 585.00
Woman_victim 20.00 20.00 849.00 48.00 4.00 30.00 4.00 899.00 44.00 791.00 102.00

Balance

Man_agent (N=937) Man_victim (N=933) Woman_agent (N=924) Woman_victim (N=937)
Proportions across treatment groups, each pre-specified covariate
Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.
male 0.6 0.5 0.5 0.5 0.5 0.5 0.5 0.5
has_children 0.6 0.5 0.6 0.5 0.6 0.5 0.6 0.5
religiosity 2.0 1.6 1.9 1.6 2.0 1.7 1.9 1.7
owner_domicile 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5
ambivalent_sexism_index 3.5 0.6 3.4 0.7 3.5 0.7 3.5 0.7
pro_sociality_index 3.6 0.8 3.6 0.8 3.6 0.8 3.6 0.8
participated_protest_last_12_months 0.2 0.4 0.2 0.4 0.2 0.4 0.2 0.4
demanded_action_last_12_months 0.2 0.4 0.2 0.4 0.2 0.4 0.2 0.4
N Pct. N Pct. N Pct. N Pct.
age 18-24 years old 183 19.5 179 19.2 191 20.7 162 17.3
25-34 years old 256 27.3 237 25.4 237 25.6 255 27.2
35-44 years old 177 18.9 180 19.3 178 19.3 174 18.6
45-54 years old 141 15.0 142 15.2 133 14.4 163 17.4
55-64 years old 108 11.5 109 11.7 108 11.7 107 11.4
65-74 years old 66 7.0 65 7.0 65 7.0 57 6.1
75+ years old 6 0.6 21 2.3 12 1.3 19 2.0
employment A homemaker or stay-at-home parent 21 2.2 26 2.8 20 2.2 27 2.9
Other: 12 1.3 14 1.5 11 1.2 15 1.6
Retired 92 9.8 111 11.9 92 10.0 95 10.1
Student 121 12.9 100 10.7 115 12.4 109 11.6
Unemployed and looking for work 78 8.3 80 8.6 91 9.8 72 7.7
Working full-time 492 52.5 488 52.3 483 52.3 478 51.0
Working part-time 121 12.9 114 12.2 112 12.1 141 15.0
education Informal education only (including Koranic school) 13 1.4 10 1.1 9 1.0 11 1.2
No formal education 14 1.5 10 1.1 12 1.3 18 1.9
Post-university 66 7.0 45 4.8 61 6.6 50 5.3
Primary school 20 2.1 21 2.3 15 1.6 19 2.0
Secondary school 326 34.8 315 33.8 301 32.6 332 35.4
University 498 53.1 532 57.0 526 56.9 507 54.1
nationality East Asia 1 0.1 1 0.1 3 0.3 1 0.1
Eastern Europe (outside France) 5 0.5 13 1.4 8 0.9 10 1.1
France 451 48.1 460 49.3 442 47.8 456 48.7
Latin America 3 0.3 1 0.1 1 0.1 2 0.2
North Africa 22 2.3 12 1.3 15 1.6 16 1.7
North America 1 0.1 1 0.1 0 0.0 1 0.1
Oceania 0 0.0 0 0.0 1 0.1 2 0.2
South Asia 2 0.2 2 0.2 1 0.1 0 0.0
Sub-Saharan Africa 8 0.9 6 0.6 3 0.3 4 0.4
Western Europe (outside France) 14 1.5 15 1.6 20 2.2 17 1.8
NA 430 45.9 422 45.2 430 46.5 428 45.7
ethnicity Abbey 12 1.3 12 1.3 14 1.5 21 2.2
Abron 12 1.3 12 1.3 7 0.8 12 1.3
Adjoukrou 15 1.6 22 2.4 23 2.5 12 1.3
Agni 47 5.0 40 4.3 45 4.9 37 3.9
Attié 28 3.0 28 3.0 18 1.9 21 2.2
Avikam 4 0.4 3 0.3 7 0.8 0 0.0
Bambara 10 1.1 8 0.9 14 1.5 7 0.7
Baoulé 105 11.2 94 10.1 107 11.6 109 11.6
Bété 24 2.6 33 3.5 28 3.0 38 4.1
Dida 7 0.7 9 1.0 12 1.3 11 1.2
Dioula 24 2.6 16 1.7 24 2.6 22 2.3
Don't know 6 0.6 13 1.4 11 1.2 12 1.3
Godié 3 0.3 1 0.1 1 0.1 6 0.6
Gouro 6 0.6 17 1.8 11 1.2 14 1.5
Guéré 16 1.7 12 1.3 14 1.5 16 1.7
Koulango 6 0.6 12 1.3 4 0.4 3 0.3
Kroumen 4 0.4 3 0.3 4 0.4 3 0.3
Lobi 3 0.3 1 0.1 0 0.0 0 0.0
Malinké/Maninka 14 1.5 16 1.7 14 1.5 18 1.9
Only Ivoirian (do not identify in these terms) 30 3.2 24 2.6 24 2.6 28 3.0
Senoufo 37 3.9 30 3.2 36 3.9 21 2.2
Yacouba 17 1.8 16 1.7 12 1.3 17 1.8
NA 507 54.1 511 54.8 494 53.5 509 54.3
climate_beliefs A great deal 187 20.0 192 20.6 201 21.8 223 23.8
A little 127 13.6 141 15.1 140 15.2 126 13.4
A lot 321 34.3 317 34.0 296 32.0 282 30.1
Don't know 28 3.0 24 2.6 20 2.2 19 2.0
Moderately 230 24.5 223 23.9 224 24.2 238 25.4
Not at all 44 4.7 36 3.9 43 4.7 49 5.2
trust_government Don't know 124 13.2 123 13.2 143 15.5 128 13.7
Just about always 85 9.1 94 10.1 102 11.0 102 10.9
Most of the time 269 28.7 256 27.4 269 29.1 256 27.3
Only some of the time 459 49.0 460 49.3 410 44.4 451 48.1
Balance test
Man victim Man agent Woman victim Woman agent
+ 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.
(Intercept) 0.406*** 0.089 0.294** 0.211*
(0.097) (0.099) (0.103) (0.100)
male 0.002 0.011 −0.022 0.009
(0.015) (0.015) (0.015) (0.015)
age25-34 years old −0.040 0.036 0.038 −0.035
(0.027) (0.027) (0.027) (0.027)
age35-44 years old −0.030 0.016 0.035 −0.021
(0.030) (0.029) (0.029) (0.030)
age45-54 years old −0.043 0.010 0.069* −0.036
(0.032) (0.031) (0.032) (0.031)
age55-64 years old −0.051 0.017 0.034 −0.001
(0.035) (0.035) (0.035) (0.035)
age65-74 years old −0.076 0.020 0.021 0.036
(0.053) (0.055) (0.054) (0.051)
age75+ years old 0.028 −0.147* 0.134+ −0.015
(0.079) (0.066) (0.079) (0.069)
employmentOther × 0.048 −0.021 −0.005 −0.021
(0.082) (0.075) (0.083) (0.075)
employmentRetired 0.051 0.018 −0.042 −0.028
(0.062) (0.062) (0.065) (0.059)
employmentStudent −0.062 0.049 −0.007 0.019
(0.055) (0.055) (0.058) (0.056)
employmentUnemployed and looking for work 0.003 0.011 −0.076 0.062
(0.054) (0.053) (0.056) (0.054)
employmentWorking full-time 0.002 0.017 −0.036 0.017
(0.048) (0.047) (0.051) (0.047)
employmentWorking part-time −0.014 0.016 −0.000 −0.002
(0.051) (0.050) (0.054) (0.050)
educationNo formal education −0.068 0.006 0.036 0.026
(0.088) (0.094) (0.097) (0.089)
educationPost-university −0.030 0.005 −0.065 0.091
(0.075) (0.079) (0.080) (0.072)
educationPrimary school 0.032 −0.001 −0.040 0.009
(0.088) (0.089) (0.091) (0.082)
educationSecondary school 0.005 −0.020 −0.028 0.043
(0.071) (0.074) (0.076) (0.067)
educationUniversity 0.027 −0.048 −0.042 0.063
(0.071) (0.073) (0.075) (0.066)
has_children −0.010 −0.002 0.002 0.010
(0.018) (0.017) (0.018) (0.018)
religiosity −0.005 0.001 −0.000 0.004
(0.005) (0.005) (0.005) (0.005)
owner_domicile −0.008 0.014 −0.013 0.007
(0.017) (0.017) (0.017) (0.017)
ambivalent_sexism_index −0.030* 0.025* −0.002 0.007
(0.012) (0.012) (0.012) (0.012)
climate_beliefsA little 0.002 0.011 −0.033 0.019
(0.026) (0.025) (0.026) (0.026)
climate_beliefsA lot 0.016 0.034+ −0.041* −0.009
(0.021) (0.020) (0.021) (0.020)
climate_beliefsDon't know −0.016 0.094+ −0.045 −0.032
(0.053) (0.056) (0.051) (0.051)
climate_beliefsModerately −0.014 0.023 −0.007 −0.002
(0.022) (0.022) (0.023) (0.022)
climate_beliefsNot at all −0.048 0.018 0.010 0.019
(0.037) (0.039) (0.041) (0.039)
pro_sociality_index −0.010 0.008 0.009 −0.007
(0.011) (0.011) (0.011) (0.011)
trust_governmentJust about always 0.015 −0.025 0.029 −0.018
(0.031) (0.031) (0.032) (0.033)
trust_governmentMost of the time 0.006 0.022 −0.000 −0.028
(0.025) (0.026) (0.026) (0.026)
trust_governmentOnly some of the time 0.026 0.019 0.007 −0.052*
(0.023) (0.024) (0.024) (0.024)
participated_protest_last_12_months 0.026 0.007 −0.026 −0.007
(0.020) (0.020) (0.020) (0.020)
demanded_action_last_12_months −0.000 −0.012 −0.002 0.014
(0.020) (0.020) (0.020) (0.020)
Num.Obs. 3459 3459 3459 3459
R2 0.010 0.009 0.009 0.007
F.statistic 1.126 1.066 0.936 0.698
F.p.value 0.285 0.367 0.572 0.901

Main hypothesis 1 (M1).

Feminization of climate change communication will politically demobilize Ivorian citizens. We expect that this will have no effect or a positive effect on French citizens. We present country-wise regressions in the main paper and pooled regressions across the sample in the appendix.

CDI, unadjusted CDI, adjusted FR, unadjusted FR, adjusted Pooled, unadjusted Pooled, adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Outcome is a PCA index of the three political mobilization outcomes. Robust SEs.
(Intercept) −0.406*** 3.357*** 0.326*** 1.978*** −0.009 3.314***
(0.048) (0.597) (0.044) (0.541) (0.034) (0.291)
treatment_female 0.020 0.062 0.024 0.007 0.019 0.027
(0.067) (0.066) (0.063) (0.056) (0.047) (0.043)
male −0.170* 0.027 −0.031
(0.076) (0.060) (0.045)
age25-34 years old −0.352*** −0.089 −0.278***
(0.103) (0.137) (0.081)
age35-44 years old −0.389** −0.144 −0.196*
(0.122) (0.139) (0.088)
age45-54 years old −0.484** −0.113 −0.113
(0.162) (0.141) (0.094)
age55-64 years old −0.185 −0.394** −0.230*
(0.345) (0.144) (0.105)
age75+ years old 0.345 −0.291 −0.026
(0.343) (0.223) (0.204)
employmentOther × −0.145 0.295 −0.083
(0.322) (0.237) (0.194)
employmentRetired 0.310 0.316 0.092
(0.634) (0.197) (0.175)
employmentStudent 0.159 0.035 0.181
(0.256) (0.238) (0.160)
employmentUnemployed and looking for work 0.060 0.412+ 0.193
(0.253) (0.222) (0.158)
employmentWorking full-time 0.020 0.389* 0.200
(0.240) (0.166) (0.136)
employmentWorking part-time −0.036 0.484** 0.124
(0.243) (0.184) (0.143)
educationNo formal education −0.520 −0.373 −0.429
(0.616) (0.328) (0.278)
educationPost-university −1.169* −0.477* −0.703**
(0.572) (0.241) (0.220)
educationPrimary school −0.777 −0.576+ −0.650*
(0.614) (0.313) (0.268)
educationSecondary school −0.960+ −0.419+ −0.579**
(0.558) (0.222) (0.205)
educationUniversity −1.097* −0.391+ −0.651**
(0.558) (0.219) (0.203)
has_children −0.161+ 0.001 −0.108*
(0.086) (0.066) (0.052)
religiosity −0.002 −0.062* −0.063***
(0.024) (0.026) (0.016)
ethnicityAbron 0.192
(0.200)
ethnicityAdjoukrou 0.108
(0.171)
ethnicityAgni 0.317+
(0.162)
ethnicityAttié 0.258
(0.182)
ethnicityAvikam 0.307
(0.421)
ethnicityBambara 0.218
(0.254)
ethnicityBaoulé 0.165
(0.137)
ethnicityBété 0.308+
(0.173)
ethnicityDida 0.062
(0.250)
ethnicityDioula 0.366+
(0.187)
ethnicityDon't know −0.011
(0.277)
ethnicityGodié −0.268
(0.457)
ethnicityGouro −0.135
(0.202)
ethnicityGuéré 0.011
(0.221)
ethnicityKoulango 0.074
(0.346)
ethnicityKroumen 0.200
(0.363)
ethnicityLobi 0.535*
(0.247)
ethnicityMalinké/Maninka 0.404+
(0.221)
ethnicityOnly Ivoirian (do not identify in these terms) 0.339+
(0.184)
ethnicitySenoufo 0.246
(0.173)
ethnicityYacouba 0.178
(0.218)
owner_domicile −0.367*** 0.083 0.071
(0.093) (0.061) (0.049)
ambivalent_sexism_index −0.323*** −0.123* −0.212***
(0.057) (0.053) (0.039)
climate_beliefsA little 0.226+ 0.797*** 0.462***
(0.116) (0.109) (0.080)
climate_beliefsA lot 0.144 0.151+ 0.121*
(0.090) (0.084) (0.061)
climate_beliefsDon't know 0.628* 0.330+ 0.391*
(0.250) (0.179) (0.157)
climate_beliefsModerately 0.293** 0.517*** 0.407***
(0.104) (0.087) (0.066)
climate_beliefsNot at all 0.713*** 1.290*** 0.955***
(0.194) (0.183) (0.132)
pro_sociality_index −0.325*** −0.546*** −0.515***
(0.058) (0.048) (0.037)
trust_governmentJust about always −0.249+ 0.093 −0.127
(0.132) (0.160) (0.103)
trust_governmentMost of the time −0.178+ −0.125 −0.144+
(0.105) (0.112) (0.076)
trust_governmentOnly some of the time −0.160 0.031 −0.017
(0.101) (0.103) (0.072)
participated_protest_last_12_months −0.157+ −0.539*** −0.416***
(0.086) (0.081) (0.059)
demanded_action_last_12_months −0.225* −0.202** −0.275***
(0.089) (0.076) (0.057)
age65-74 years old −0.303+ −0.125
(0.180) (0.154)
nationalityEastern Europe (outside France) 1.067*
(0.451)
nationalityFrance 0.625
(0.389)
nationalityLatin America 0.443
(0.521)
nationalityNorth Africa 0.423
(0.425)
nationalityNorth America −0.171
(1.064)
nationalityOceania −0.994+
(0.539)
nationalitySouth Asia 0.236
(0.863)
nationalitySub-Saharan Africa 0.581
(0.508)
nationalityWestern Europe (outside France) 0.746+
(0.422)
R2 0.00 0.21 0.00 0.27 0.00 0.25
Num. obs. 1710 1490 2004 1952 3714 3442

Main hypothesis 2 (M2).

Victimization of climate change communication will politically demobilize Global South citizens. We expect that this will have no effect or a positive effect on French citizens. We present country-wise regressions in the main paper and pooled regressions across the sample in the appendix.

CDI, unadjusted CDI, adjusted FR, unadjusted FR, adjusted Pooled, unadjusted Pooled, adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Outcome is a PCA index of the three political mobilization outcomes. Robust SEs.
(Intercept) −0.396*** 3.357 0.316*** 1.963*** −0.015 3.321***
(0.048) (0.043) (0.539) (0.033) (0.292)
treatment_victim 0.001 0.040 0.043 0.030 0.029 0.011
(0.067) (0.063) (0.056) (0.047) (0.043)
male −0.170 0.028 −0.031
(0.060) (0.045)
age25-34 years old −0.351 −0.088 −0.278***
(0.137) (0.081)
age35-44 years old −0.390 −0.143 −0.196*
(0.139) (0.088)
age45-54 years old −0.486 −0.113 −0.112
(0.141) (0.094)
age55-64 years old −0.191 −0.392** −0.228*
(0.144) (0.105)
age75+ years old 0.356 −0.295 −0.024
(0.223) (0.204)
employmentOther × −0.137 0.295 −0.084
(0.236) (0.194)
employmentRetired 0.313 0.315 0.091
(0.196) (0.175)
employmentStudent 0.169 0.035 0.182
(0.238) (0.160)
employmentUnemployed and looking for work 0.067 0.415+ 0.194
(0.222) (0.158)
employmentWorking full-time 0.027 0.388* 0.200
(0.166) (0.136)
employmentWorking part-time −0.030 0.485** 0.125
(0.184) (0.143)
educationNo formal education −0.516 −0.368 −0.427
(0.329) (0.278)
educationPost-university −1.160 −0.473+ −0.702**
(0.242) (0.219)
educationPrimary school −0.769 −0.578+ −0.651*
(0.313) (0.267)
educationSecondary school −0.952 −0.418+ −0.578**
(0.222) (0.205)
educationUniversity −1.091 −0.390+ −0.651**
(0.219) (0.202)
has_children −0.161 0.001 −0.108*
(0.066) (0.052)
religiosity −0.001 −0.062* −0.063***
(0.026) (0.016)
ethnicityAbron 0.180
ethnicityAdjoukrou 0.105
ethnicityAgni 0.312
ethnicityAttié 0.246
ethnicityAvikam 0.312
ethnicityBambara 0.220
ethnicityBaoulé 0.162
ethnicityBété 0.303
ethnicityDida 0.060
ethnicityDioula 0.367
ethnicityDon't know −0.017
ethnicityGodié −0.268
ethnicityGouro −0.143
ethnicityGuéré 0.007
ethnicityKoulango 0.048
ethnicityKroumen 0.199
ethnicityLobi 0.512
ethnicityMalinké/Maninka 0.396
ethnicityOnly Ivoirian (do not identify in these terms) 0.333
ethnicitySenoufo 0.241
ethnicityYacouba 0.167
owner_domicile −0.370 0.084 0.071
(0.061) (0.049)
ambivalent_sexism_index −0.322 −0.122* −0.212***
(0.053) (0.039)
climate_beliefsA little 0.223 0.800*** 0.462***
(0.109) (0.080)
climate_beliefsA lot 0.141 0.153+ 0.120+
(0.084) (0.061)
climate_beliefsDon't know 0.618 0.336+ 0.389*
(0.179) (0.158)
climate_beliefsModerately 0.292 0.519*** 0.407***
(0.088) (0.066)
climate_beliefsNot at all 0.714 1.293*** 0.956***
(0.182) (0.132)
pro_sociality_index −0.325 −0.546*** −0.515***
(0.048) (0.037)
trust_governmentJust about always −0.249 0.090 −0.127
(0.160) (0.103)
trust_governmentMost of the time −0.180 −0.126 −0.144+
(0.112) (0.076)
trust_governmentOnly some of the time −0.166 0.030 −0.018
(0.103) (0.072)
participated_protest_last_12_months −0.156 −0.540*** −0.417***
(0.081) (0.059)
demanded_action_last_12_months −0.225 −0.201** −0.274***
(0.076) (0.057)
age65-74 years old −0.301+ −0.123
(0.180) (0.154)
nationalityEastern Europe (outside France) 1.058*
(0.447)
nationalityFrance 0.620
(0.384)
nationalityLatin America 0.439
(0.516)
nationalityNorth Africa 0.420
(0.421)
nationalityNorth America −0.182
(1.063)
nationalityOceania −0.994+
(0.543)
nationalitySouth Asia 0.231
(0.861)
nationalitySub-Saharan Africa 0.576
(0.504)
nationalityWestern Europe (outside France) 0.742+
(0.417)
R2 0.00 0.21 0.00 0.27 0.00 0.25
Num. obs. 1710 1490 2004 1952 3714 3442

Main hypothesis 3 (M3).

Feminization of climate change communication will increase support for Global South climate financing among Global North citizens (for all outcomes). We expect the same among Global South citizens but only for 5/6 outcomes. For Global South citizens, we expect the last outcome (willingness to pay) to move in the opposite direction. We present country-wise regressions in the main paper and pooled regressions across the sample in the appendix.

Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, Ivorian sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adpatation outcomes. Run on Ivorian sample. Robust SEs.
(Intercept) 0.842*** 0.559* 0.445*** 0.447* 0.331*** −0.166 0.838*** 0.496* 0.103*** 0.068 0.786*** 0.532***
(0.013) (0.238) (0.017) (0.218) (0.016) (0.270) (0.013) (0.200) (0.010) (0.088) (0.014) (0.121)
treatment_female −0.015 −0.015 −0.004 −0.005 0.136*** 0.148*** −0.029 −0.043* 0.011 0.006 0.024 0.023
(0.018) (0.019) (0.024) (0.026) (0.023) (0.024) (0.018) (0.019) (0.015) (0.016) (0.019) (0.020)
male 0.025 0.044 −0.058* 0.075*** 0.037* 0.013
(0.021) (0.029) (0.027) (0.023) (0.018) (0.023)
age25-34 years old 0.021 0.035 0.005 0.014 −0.004 0.043
(0.028) (0.039) (0.037) (0.030) (0.025) (0.029)
age35-44 years old 0.013 0.058 0.043 0.019 0.047 0.000
(0.034) (0.047) (0.044) (0.033) (0.031) (0.035)
age45-54 years old −0.002 0.058 0.074 0.037 0.098* −0.027
(0.043) (0.060) (0.056) (0.041) (0.045) (0.046)
age55-64 years old −0.072 0.147 −0.080 −0.088 0.088 −0.050
(0.100) (0.102) (0.096) (0.093) (0.084) (0.088)
age75+ years old 0.566*** −0.647*** 0.289* 0.168+ 0.015 −1.017***
(0.111) (0.131) (0.133) (0.089) (0.052) (0.062)
employmentOther × 0.122 0.224 −0.012 −0.004 −0.042 0.187
(0.101) (0.137) (0.125) (0.086) (0.100) (0.125)
employmentRetired −0.149 0.109 0.001 −0.102 −0.015 0.375**
(0.236) (0.202) (0.204) (0.163) (0.163) (0.117)
employmentStudent 0.160+ 0.055 −0.054 −0.159* −0.083 0.221*
(0.087) (0.104) (0.095) (0.074) (0.070) (0.094)
employmentUnemployed and looking for work 0.145+ −0.001 −0.067 −0.074 −0.048 0.256**
(0.086) (0.103) (0.095) (0.073) (0.069) (0.093)
employmentWorking full-time 0.090 0.091 −0.053 −0.100 −0.076 0.254**
(0.083) (0.099) (0.090) (0.069) (0.065) (0.091)
employmentWorking part-time 0.068 0.066 0.008 −0.079 −0.052 0.238*
(0.085) (0.100) (0.092) (0.070) (0.066) (0.092)
educationNo formal education −0.208 0.249 0.285 0.205 0.023 −0.095
(0.240) (0.213) (0.248) (0.177) (0.041) (0.069)
educationPost-university −0.045 0.211 0.199 0.171 0.136* −0.342***
(0.228) (0.195) (0.230) (0.167) (0.055) (0.081)
educationPrimary school 0.063 0.088 0.295 0.155 0.057 −0.248*
(0.229) (0.205) (0.240) (0.175) (0.058) (0.101)
educationSecondary school −0.004 0.116 0.195 0.139 0.099* −0.255***
(0.225) (0.189) (0.224) (0.164) (0.040) (0.068)
educationUniversity −0.032 0.176 0.195 0.148 0.111** −0.298***
(0.225) (0.187) (0.223) (0.163) (0.038) (0.066)
has_children 0.024 0.015 0.097** 0.064** −0.005 0.047+
(0.024) (0.033) (0.032) (0.024) (0.021) (0.025)
religiosity −0.002 0.006 −0.013 −0.004 −0.000 0.006
(0.006) (0.009) (0.008) (0.007) (0.006) (0.007)
ethnicityAbron 0.004 −0.161 0.106 0.036 −0.005 −0.006
(0.059) (0.106) (0.099) (0.065) (0.063) (0.075)
ethnicityAdjoukrou −0.176** −0.214* 0.103 0.041 −0.051 0.085
(0.066) (0.089) (0.090) (0.058) (0.051) (0.059)
ethnicityAgni −0.113* −0.158+ 0.065 0.009 −0.012 0.052
(0.051) (0.083) (0.083) (0.060) (0.050) (0.060)
ethnicityAttié −0.030 −0.121 0.164+ −0.014 −0.024 0.098
(0.053) (0.090) (0.090) (0.065) (0.056) (0.064)
ethnicityAvikam −0.123 −0.051 0.090 0.212** 0.133 0.235***
(0.131) (0.157) (0.149) (0.065) (0.125) (0.065)
ethnicityBambara −0.166* −0.007 0.281* −0.030 −0.035 −0.003
(0.083) (0.111) (0.113) (0.079) (0.067) (0.086)
ethnicityBaoulé −0.085+ −0.067 0.166* 0.034 −0.028 0.055
(0.045) (0.077) (0.078) (0.055) (0.047) (0.056)
ethnicityBété −0.152** −0.103 0.203* 0.001 −0.058 0.082
(0.057) (0.087) (0.088) (0.062) (0.052) (0.063)
ethnicityDida −0.057 −0.065 0.269* −0.076 −0.057 0.044
(0.067) (0.110) (0.109) (0.085) (0.063) (0.081)
ethnicityDioula −0.095+ −0.117 0.187* 0.033 −0.064 −0.006
(0.057) (0.092) (0.091) (0.065) (0.054) (0.070)
ethnicityDon't know −0.066 −0.123 0.047 0.061 −0.009 0.105
(0.076) (0.109) (0.108) (0.081) (0.068) (0.085)
ethnicityGodié −0.161 0.035 0.230 −0.018 −0.084+ −0.034
(0.159) (0.185) (0.168) (0.123) (0.047) (0.136)
ethnicityGouro −0.166* −0.037 −0.029 0.032 −0.039 0.055
(0.075) (0.104) (0.095) (0.076) (0.062) (0.074)
ethnicityGuéré −0.125+ 0.007 0.231* 0.079 −0.033 0.071
(0.067) (0.099) (0.101) (0.066) (0.062) (0.073)
ethnicityKoulango −0.047 −0.218+ 0.258* 0.156* −0.051 0.178**
(0.091) (0.132) (0.121) (0.067) (0.065) (0.066)
ethnicityKroumen −0.011 0.155 0.261+ 0.095 −0.115* −0.050
(0.099) (0.164) (0.156) (0.099) (0.046) (0.128)
ethnicityLobi 0.122 0.271 −0.058 0.110 −0.142+ 0.071
(0.076) (0.272) (0.200) (0.085) (0.076) (0.218)
ethnicityMalinké/Maninka −0.052 −0.119 0.215* 0.025 0.019 −0.036
(0.062) (0.101) (0.097) (0.073) (0.071) (0.079)
ethnicityOnly Ivoirian (do not identify in these terms) −0.043 −0.040 0.009 −0.015 −0.042 0.018
(0.053) (0.089) (0.087) (0.063) (0.053) (0.066)
ethnicitySenoufo −0.082 −0.179* 0.130 0.030 0.015 0.019
(0.053) (0.087) (0.087) (0.061) (0.056) (0.063)
ethnicityYacouba −0.022 −0.054 0.211* 0.035 −0.054 0.061
(0.060) (0.098) (0.097) (0.064) (0.060) (0.070)
owner_domicile −0.021 −0.082* 0.041 0.037 −0.021 0.020
(0.029) (0.037) (0.035) (0.027) (0.024) (0.030)
ambivalent_sexism_index 0.061*** −0.052* 0.046* 0.024 0.015 0.008
(0.016) (0.021) (0.020) (0.016) (0.013) (0.016)
climate_beliefsA little 0.009 −0.071 0.142*** −0.005 −0.082** −0.028
(0.029) (0.043) (0.041) (0.030) (0.029) (0.034)
climate_beliefsA lot −0.020 −0.019 −0.023 −0.053* −0.068** 0.007
(0.024) (0.035) (0.032) (0.025) (0.025) (0.026)
climate_beliefsDon't know −0.181* −0.004 0.096 −0.246** −0.118** −0.187*
(0.075) (0.090) (0.089) (0.083) (0.038) (0.083)
climate_beliefsModerately −0.060* −0.069+ 0.046 −0.036 −0.102*** 0.002
(0.030) (0.041) (0.040) (0.030) (0.026) (0.030)
climate_beliefsNot at all −0.104+ −0.121+ 0.133+ −0.041 −0.110** 0.035
(0.058) (0.068) (0.069) (0.053) (0.035) (0.050)
pro_sociality_index 0.029+ −0.000 −0.017 0.013 −0.008 0.034*
(0.016) (0.021) (0.020) (0.015) (0.012) (0.016)
trust_governmentJust about always −0.081* 0.015 0.039 0.117*** 0.035 0.093**
(0.035) (0.048) (0.046) (0.035) (0.028) (0.034)
trust_governmentMost of the time −0.035 0.004 0.059 0.106** 0.059* 0.052
(0.029) (0.041) (0.038) (0.032) (0.024) (0.032)
trust_governmentOnly some of the time −0.054* 0.023 −0.020 0.081* 0.030 −0.002
(0.027) (0.039) (0.036) (0.032) (0.024) (0.032)
participated_protest_last_12_months 0.000 0.077* 0.082* 0.022 0.013 0.029
(0.024) (0.034) (0.032) (0.024) (0.023) (0.025)
demanded_action_last_12_months 0.023 −0.042 0.114*** 0.068** −0.010 0.059*
(0.025) (0.035) (0.033) (0.023) (0.023) (0.025)
R2 0.00 0.08 0.00 0.06 0.02 0.13 0.00 0.10 0.00 0.06 0.00 0.08
Num. obs. 1710 1490 1710 1490 1710 1490 1710 1490 1710 1490 1710 1490
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, French sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adaptation outcomes. Run on French sample. Robust SEs.
(Intercept) 0.434*** 0.446 0.497*** 0.424 0.278*** 0.093 0.519*** 0.371 0.037*** −0.122** 0.496*** 0.319
(0.016) (0.294) (0.016) (0.275) (0.014) (0.302) (0.016) (0.290) (0.006) (0.045) (0.016) (0.266)
treatment_female −0.020 −0.025 0.005 0.010 0.085*** 0.090*** −0.027 −0.020 −0.004 −0.005 0.009 0.015
(0.022) (0.022) (0.022) (0.023) (0.021) (0.021) (0.022) (0.021) (0.008) (0.008) (0.022) (0.021)
male −0.035 0.029 −0.028 −0.026 0.001 −0.006
(0.023) (0.024) (0.022) (0.022) (0.009) (0.023)
age25-34 years old −0.101+ 0.132* 0.037 0.036 −0.003 −0.116*
(0.055) (0.052) (0.053) (0.054) (0.016) (0.054)
age35-44 years old −0.109+ 0.172** 0.059 0.032 −0.001 −0.081
(0.056) (0.053) (0.054) (0.055) (0.016) (0.054)
age45-54 years old −0.156** 0.187*** 0.038 0.031 0.021 −0.133*
(0.055) (0.053) (0.053) (0.055) (0.018) (0.054)
age55-64 years old −0.104+ 0.242*** 0.009 0.029 0.033+ −0.041
(0.058) (0.054) (0.054) (0.057) (0.020) (0.056)
age65-74 years old −0.076 0.213** −0.000 0.019 0.000 0.020
(0.074) (0.072) (0.068) (0.071) (0.029) (0.073)
age75+ years old 0.025 0.360*** −0.073 0.019 −0.018 0.109
(0.098) (0.094) (0.082) (0.095) (0.033) (0.095)
employmentOther × −0.201+ −0.028 0.162 −0.014 0.020 0.009
(0.114) (0.126) (0.123) (0.117) (0.047) (0.108)
employmentRetired −0.101 −0.092 0.031 −0.145+ 0.030 −0.032
(0.082) (0.080) (0.072) (0.075) (0.029) (0.073)
employmentStudent −0.092 −0.053 0.060 −0.151 0.006 −0.023
(0.104) (0.103) (0.098) (0.099) (0.028) (0.093)
employmentUnemployed and looking for work −0.067 −0.119 −0.009 −0.142+ 0.062+ −0.021
(0.088) (0.086) (0.079) (0.084) (0.035) (0.080)
employmentWorking full-time −0.071 −0.058 0.009 −0.165* 0.005 0.022
(0.069) (0.066) (0.061) (0.064) (0.019) (0.059)
employmentWorking part-time −0.045 −0.055 0.080 −0.104 0.003 0.009
(0.078) (0.075) (0.070) (0.072) (0.021) (0.068)
educationNo formal education −0.069 −0.108 −0.022 −0.016 0.003 −0.175
(0.131) (0.126) (0.126) (0.120) (0.009) (0.124)
educationPost-university −0.059 0.072 −0.150 −0.145 0.031 −0.183+
(0.100) (0.096) (0.098) (0.091) (0.020) (0.095)
educationPrimary school −0.079 −0.039 0.073 0.047 0.024 −0.231*
(0.121) (0.120) (0.118) (0.113) (0.025) (0.116)
educationSecondary school −0.050 −0.071 −0.150+ −0.131 0.019* −0.238**
(0.091) (0.088) (0.091) (0.084) (0.010) (0.087)
educationUniversity −0.048 −0.031 −0.167+ −0.160+ 0.021* −0.201*
(0.091) (0.087) (0.090) (0.083) (0.009) (0.086)
has_children −0.005 −0.051+ 0.027 0.029 0.005 0.018
(0.026) (0.026) (0.024) (0.025) (0.009) (0.025)
religiosity 0.004 −0.017+ 0.007 0.019* −0.001 0.025*
(0.010) (0.010) (0.010) (0.010) (0.004) (0.010)
nationalityEastern Europe (outside France) 0.108 −0.036 −0.073 −0.098 0.044 −0.015
(0.265) (0.249) (0.274) (0.269) (0.031) (0.246)
nationalityFrance 0.126 0.071 −0.009 −0.160 0.048** −0.032
(0.251) (0.233) (0.264) (0.254) (0.015) (0.231)
nationalityLatin America 0.134 −0.029 0.020 −0.157 0.024 −0.271
(0.316) (0.294) (0.315) (0.314) (0.019) (0.280)
nationalityNorth Africa 0.230 0.007 0.002 −0.123 0.061* 0.095
(0.258) (0.241) (0.269) (0.262) (0.031) (0.241)
nationalityNorth America 0.051 0.252 0.095 −0.273 0.020 0.571*
(0.442) (0.387) (0.376) (0.385) (0.024) (0.234)
nationalityOceania 0.047 0.752* −0.364 −0.187 0.029 −0.035
(0.609) (0.295) (0.290) (0.451) (0.033) (0.399)
nationalitySouth Asia 0.093 0.339 −0.112 0.104 0.021 0.277
(0.352) (0.309) (0.333) (0.312) (0.020) (0.303)
nationalitySub-Saharan Africa 0.253 −0.010 −0.075 0.105 0.071 −0.104
(0.276) (0.260) (0.282) (0.263) (0.057) (0.258)
nationalityWestern Europe (outside France) 0.086 0.054 −0.160 −0.122 0.046 0.018
(0.259) (0.241) (0.268) (0.261) (0.028) (0.240)
owner_domicile −0.056* 0.076** −0.049* −0.064** 0.012 −0.011
(0.025) (0.025) (0.023) (0.024) (0.009) (0.024)
ambivalent_sexism_index −0.006 −0.032+ 0.100*** 0.024 0.000 0.002
(0.019) (0.019) (0.017) (0.018) (0.008) (0.019)
climate_beliefsA little −0.128** −0.011 −0.070+ −0.133*** −0.009 −0.148***
(0.042) (0.043) (0.040) (0.040) (0.013) (0.040)
climate_beliefsA lot −0.055+ 0.009 −0.010 −0.024 0.011 −0.044
(0.033) (0.033) (0.031) (0.031) (0.013) (0.031)
climate_beliefsDon't know −0.010 −0.015 0.148+ −0.090 0.024 −0.097
(0.085) (0.085) (0.080) (0.074) (0.034) (0.079)
climate_beliefsModerately −0.111*** −0.007 −0.061+ −0.076* 0.001 −0.083*
(0.034) (0.034) (0.032) (0.033) (0.012) (0.033)
climate_beliefsNot at all −0.055 0.050 −0.019 −0.095+ −0.013 −0.234***
(0.060) (0.061) (0.054) (0.055) (0.016) (0.048)
pro_sociality_index 0.072*** −0.017 −0.004 0.116*** 0.010+ 0.094***
(0.018) (0.018) (0.016) (0.017) (0.006) (0.017)
trust_governmentJust about always 0.020 0.092 0.025 0.147** 0.032 0.282***
(0.060) (0.059) (0.057) (0.054) (0.023) (0.054)
trust_governmentMost of the time −0.010 0.113* 0.054 0.153*** 0.019 0.230***
(0.046) (0.045) (0.042) (0.043) (0.014) (0.042)
trust_governmentOnly some of the time −0.057 0.059 −0.021 0.078* 0.014 0.136***
(0.041) (0.041) (0.038) (0.039) (0.013) (0.037)
participated_protest_last_12_months 0.072* 0.077* 0.056+ 0.214*** 0.004 0.116***
(0.032) (0.032) (0.031) (0.029) (0.012) (0.031)
demanded_action_last_12_months 0.008 0.005 0.044 0.073* 0.027* 0.066*
(0.031) (0.031) (0.029) (0.029) (0.013) (0.030)
R2 0.00 0.06 0.00 0.05 0.01 0.07 0.00 0.15 0.00 0.02 0.00 0.13
Num. obs. 1991 1939 1992 1940 1994 1942 1994 1942 1987 1935 1994 1942
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, pooled sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adaptation outcomes. Run on pooled sample. Robust SEs.
(Intercept) 0.621*** 0.306** 0.473*** 0.548*** 0.302*** 0.047 0.666*** 0.292** 0.067*** −0.055 0.629*** 0.240*
(0.011) (0.112) (0.012) (0.115) (0.011) (0.113) (0.011) (0.104) (0.006) (0.041) (0.011) (0.097)
treatment_female −0.016 −0.024 0.000 0.007 0.109*** 0.112*** −0.027+ −0.034* 0.004 −0.000 0.017 0.017
(0.016) (0.015) (0.016) (0.017) (0.016) (0.016) (0.016) (0.015) (0.008) (0.008) (0.016) (0.015)
male 0.007 0.048** −0.046** 0.029+ 0.026** 0.023
(0.016) (0.017) (0.016) (0.016) (0.009) (0.016)
age25-34 years old −0.020 0.078* 0.022 0.007 −0.007 −0.030
(0.026) (0.031) (0.030) (0.027) (0.017) (0.027)
age35-44 years old −0.074* 0.122*** 0.038 −0.031 0.013 −0.079**
(0.030) (0.034) (0.033) (0.029) (0.018) (0.030)
age45-54 years old −0.151*** 0.137*** 0.019 −0.068* 0.033+ −0.160***
(0.033) (0.036) (0.034) (0.032) (0.019) (0.032)
age55-64 years old −0.155*** 0.191*** −0.038 −0.115** 0.030 −0.113**
(0.038) (0.040) (0.037) (0.037) (0.021) (0.036)
age65-74 years old −0.119* 0.162** −0.046 −0.121* −0.009 −0.072
(0.059) (0.061) (0.055) (0.054) (0.029) (0.058)
age75+ years old −0.026 0.291*** −0.124+ −0.129 −0.026 −0.005
(0.087) (0.086) (0.071) (0.082) (0.033) (0.086)
employmentOther × 0.003 0.061 0.118 0.037 0.022 0.117
(0.082) (0.090) (0.085) (0.070) (0.052) (0.080)
employmentRetired −0.050 −0.049 0.034 −0.114+ 0.016 0.078
(0.071) (0.071) (0.064) (0.062) (0.034) (0.066)
employmentStudent 0.085 −0.036 0.008 −0.131* −0.006 0.094
(0.061) (0.063) (0.060) (0.056) (0.032) (0.058)
employmentUnemployed and looking for work 0.069 −0.089 −0.013 −0.078 0.033 0.131*
(0.059) (0.061) (0.058) (0.054) (0.032) (0.056)
employmentWorking full-time −0.019 −0.027 0.005 −0.133** −0.018 0.105*
(0.055) (0.054) (0.051) (0.048) (0.026) (0.050)
employmentWorking part-time 0.033 −0.022 0.068 −0.056 0.014 0.125*
(0.057) (0.058) (0.055) (0.050) (0.028) (0.053)
educationNo formal education −0.057 −0.017 0.063 0.076 0.002 −0.023
(0.108) (0.106) (0.107) (0.094) (0.011) (0.090)
educationPost-university 0.004 0.096 −0.088 −0.038 0.066** −0.142+
(0.089) (0.088) (0.089) (0.081) (0.022) (0.074)
educationPrimary school 0.061 −0.034 0.093 0.073 0.027 −0.128
(0.100) (0.101) (0.101) (0.092) (0.024) (0.086)
educationSecondary school 0.019 −0.029 −0.079 −0.052 0.043*** −0.159*
(0.084) (0.082) (0.084) (0.077) (0.012) (0.068)
educationUniversity 0.042 0.024 −0.089 −0.048 0.058*** −0.126+
(0.084) (0.081) (0.083) (0.077) (0.011) (0.067)
has_children 0.021 −0.023 0.060** 0.059** 0.006 0.049**
(0.019) (0.020) (0.019) (0.018) (0.010) (0.018)
religiosity 0.032*** 0.001 −0.003 0.028*** 0.011** 0.036***
(0.005) (0.006) (0.006) (0.005) (0.003) (0.005)
owner_domicile −0.108*** 0.017 −0.030 −0.086*** −0.024* −0.043*
(0.018) (0.020) (0.018) (0.018) (0.010) (0.018)
ambivalent_sexism_index 0.031* −0.044** 0.076*** 0.025* 0.007 0.004
(0.013) (0.014) (0.013) (0.012) (0.007) (0.012)
climate_beliefsA little −0.029 −0.051+ 0.045 −0.058* −0.040* −0.064*
(0.026) (0.030) (0.028) (0.025) (0.015) (0.027)
climate_beliefsA lot −0.037+ −0.011 −0.011 −0.031 −0.027* −0.015
(0.021) (0.024) (0.022) (0.020) (0.014) (0.021)
climate_beliefsDon't know −0.059 −0.016 0.135* −0.143* −0.041 −0.117*
(0.056) (0.060) (0.058) (0.057) (0.025) (0.056)
climate_beliefsModerately −0.094*** −0.043+ −0.012 −0.072** −0.048*** −0.052*
(0.023) (0.026) (0.024) (0.023) (0.013) (0.023)
climate_beliefsNot at all −0.030 −0.024 0.053 −0.030 −0.052** −0.063+
(0.041) (0.045) (0.043) (0.040) (0.018) (0.038)
pro_sociality_index 0.084*** −0.010 −0.000 0.095*** 0.008 0.091***
(0.012) (0.013) (0.012) (0.011) (0.006) (0.012)
trust_governmentJust about always −0.045 0.035 0.052 0.124*** 0.019 0.158***
(0.032) (0.036) (0.035) (0.030) (0.019) (0.030)
trust_governmentMost of the time −0.042 0.038 0.065* 0.111*** 0.030* 0.112***
(0.026) (0.029) (0.028) (0.026) (0.015) (0.026)
trust_governmentOnly some of the time −0.092*** 0.023 −0.025 0.046+ 0.010 0.025
(0.024) (0.027) (0.025) (0.025) (0.013) (0.025)
participated_protest_last_12_months 0.047* 0.057* 0.091*** 0.140*** 0.004 0.087***
(0.020) (0.023) (0.022) (0.019) (0.012) (0.020)
demanded_action_last_12_months 0.024 −0.028 0.081*** 0.081*** 0.010 0.066***
(0.021) (0.023) (0.022) (0.019) (0.012) (0.020)
R2 0.00 0.17 0.00 0.03 0.01 0.07 0.00 0.18 0.00 0.04 0.00 0.16
Num. obs. 3701 3429 3702 3430 3704 3432 3704 3432 3697 3425 3704 3432

Main hypothesis 4 (M4).

Victimization of climate change communication will increase support for Global South climate financing among Global North citizens (for all five outcomes). We expect the same among Global South citizens but only for 5/6 outcomes. For Global South citizens, we expect the willingness to pay outcome to move in the opposite direction. We present country-wise regressions in the main paper and pooled regressions across the sample in the appendix.

Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, Ivorian sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adpatation outcomes. Run on Ivorian sample. Robust SEs.
(Intercept) 0.833*** 0.544 0.451*** 0.457 0.410*** −0.077 0.816*** 0.465 0.106*** 0.063 0.820*** 0.566
(0.013) (0.017) (0.017) (0.013) (0.010) (0.013)
treatment_victim 0.003 0.013 −0.017 −0.018 −0.022 −0.040 0.014 0.020 0.006 0.011 −0.043* −0.037
(0.018) (0.024) (0.024) (0.018) (0.015) (0.019)
male 0.025 0.044 −0.059 0.076 0.037 0.012
age25-34 years old 0.020 0.035 0.009 0.013 −0.004 0.044
age35-44 years old 0.013 0.058 0.046 0.018 0.046 0.002
age45-54 years old −0.004 0.060 0.083 0.033 0.098 −0.023
age55-64 years old −0.071 0.148 −0.094 −0.084 0.087 −0.052
age75+ years old 0.553 −0.640 0.382 0.138 0.013 −0.987
employmentOther × 0.119 0.224 0.015 −0.012 −0.042 0.193
employmentRetired −0.155 0.112 0.038 −0.114 −0.016 0.387
employmentStudent 0.161 0.052 −0.051 −0.159 −0.081 0.217
employmentUnemployed and looking for work 0.146 −0.003 −0.064 −0.074 −0.046 0.253
employmentWorking full-time 0.091 0.088 −0.054 −0.099 −0.075 0.250
employmentWorking part-time 0.068 0.064 0.013 −0.080 −0.051 0.236
educationNo formal education −0.212 0.251 0.312 0.196 0.022 −0.086
educationPost-university −0.048 0.210 0.223 0.165 0.136 −0.338
educationPrimary school 0.062 0.087 0.308 0.152 0.058 −0.247
educationSecondary school −0.007 0.116 0.220 0.132 0.100 −0.250
educationUniversity −0.036 0.176 0.221 0.139 0.111 −0.291
has_children 0.024 0.015 0.096 0.064 −0.005 0.046
religiosity −0.002 0.006 −0.012 −0.005 −0.000 0.006
ethnicityAbron 0.006 −0.160 0.083 0.043 −0.006 −0.008
ethnicityAdjoukrou −0.174 −0.215 0.086 0.046 −0.051 0.081
ethnicityAgni −0.110 −0.159 0.039 0.017 −0.012 0.045
ethnicityAttié −0.027 −0.120 0.133 −0.005 −0.025 0.093
ethnicityAvikam −0.118 −0.056 0.062 0.223 0.136 0.221
ethnicityBambara −0.163 −0.009 0.266 −0.025 −0.034 −0.009
ethnicityBaoulé −0.083 −0.068 0.153 0.038 −0.028 0.052
ethnicityBété −0.151 −0.103 0.192 0.004 −0.058 0.080
ethnicityDida −0.056 −0.065 0.262 −0.074 −0.058 0.042
ethnicityDioula −0.092 −0.119 0.171 0.038 −0.063 −0.013
ethnicityDon't know −0.066 −0.121 0.043 0.061 −0.010 0.106
ethnicityGodié −0.164 0.037 0.252 −0.026 −0.085 −0.026
ethnicityGouro −0.166 −0.036 −0.038 0.034 −0.041 0.056
ethnicityGuéré −0.122 0.006 0.212 0.085 −0.032 0.065
ethnicityKoulango −0.043 −0.215 0.208 0.170 −0.055 0.173
ethnicityKroumen −0.007 0.153 0.237 0.103 −0.114 −0.058
ethnicityLobi 0.136 0.268 −0.166 0.144 −0.142 0.043
ethnicityMalinké/Maninka −0.050 −0.118 0.195 0.031 0.018 −0.039
ethnicityOnly Ivoirian (do not identify in these terms) −0.040 −0.041 −0.015 −0.008 −0.042 0.012
ethnicitySenoufo −0.078 −0.180 0.102 0.039 0.015 0.011
ethnicityYacouba −0.019 −0.053 0.184 0.044 −0.055 0.056
owner_domicile −0.021 −0.081 0.037 0.038 −0.021 0.020
ambivalent_sexism_index 0.062 −0.052 0.046 0.024 0.015 0.008
climate_beliefsA little 0.009 −0.070 0.140 −0.005 −0.082 −0.027
climate_beliefsA lot −0.020 −0.018 −0.027 −0.052 −0.069 0.008
climate_beliefsDon't know −0.180 −0.002 0.080 −0.242 −0.119 −0.187
climate_beliefsModerately −0.059 −0.069 0.040 −0.034 −0.102 0.001
climate_beliefsNot at all −0.105 −0.121 0.141 −0.044 −0.110 0.037
pro_sociality_index 0.029 −0.000 −0.018 0.013 −0.008 0.034
trust_governmentJust about always −0.082 0.016 0.045 0.115 0.034 0.095
trust_governmentMost of the time −0.035 0.004 0.056 0.106 0.059 0.051
trust_governmentOnly some of the time −0.053 0.025 −0.028 0.083 0.029 −0.002
participated_protest_last_12_months 0.001 0.077 0.077 0.023 0.013 0.027
demanded_action_last_12_months 0.023 −0.042 0.116 0.067 −0.010 0.059
R2 0.00 0.08 0.00 0.06 0.00 0.11 0.00 0.10 0.00 0.06 0.00 0.08
Num. obs. 1710 1490 1710 1490 1710 1490 1710 1490 1710 1490 1710 1490
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, French sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adpatation outcomes. Run on French sample. Robust SEs.
(Intercept) 0.438*** 0.450 0.512*** 0.447 0.310*** 0.135 0.511*** 0.366 0.037*** −0.125** 0.506*** 0.339
(0.016) (0.297) (0.016) (0.274) (0.015) (0.297) (0.016) (0.293) (0.006) (0.044) (0.016) (0.265)
treatment_victim −0.030 −0.032 −0.026 −0.024 0.019 0.034 −0.010 −0.014 −0.004 −0.001 −0.010 −0.013
(0.022) (0.022) (0.022) (0.023) (0.021) (0.021) (0.022) (0.021) (0.008) (0.008) (0.022) (0.022)
male −0.036 0.029 −0.029 −0.026 0.001 −0.007
(0.023) (0.024) (0.022) (0.022) (0.009) (0.023)
age25-34 years old −0.102+ 0.131* 0.036 0.036 −0.003 −0.117*
(0.055) (0.052) (0.053) (0.054) (0.016) (0.054)
age35-44 years old −0.110* 0.171** 0.061 0.031 −0.001 −0.081
(0.056) (0.053) (0.054) (0.055) (0.016) (0.054)
age45-54 years old −0.156** 0.187*** 0.040 0.031 0.021 −0.133*
(0.055) (0.053) (0.053) (0.055) (0.018) (0.054)
age55-64 years old −0.106+ 0.242*** 0.014 0.028 0.032 −0.041
(0.058) (0.054) (0.055) (0.057) (0.020) (0.056)
age65-74 years old −0.079 0.212** 0.007 0.017 −0.000 0.020
(0.074) (0.072) (0.068) (0.070) (0.029) (0.073)
age75+ years old 0.027 0.364*** −0.070 0.019 −0.018 0.112
(0.098) (0.094) (0.084) (0.095) (0.033) (0.095)
employmentOther × −0.198+ −0.032 0.147 −0.011 0.021 0.005
(0.113) (0.126) (0.124) (0.117) (0.048) (0.108)
employmentRetired −0.098 −0.093 0.021 −0.142+ 0.030 −0.034
(0.082) (0.080) (0.072) (0.075) (0.029) (0.073)
employmentStudent −0.093 −0.053 0.062 −0.152 0.006 −0.023
(0.104) (0.103) (0.097) (0.100) (0.028) (0.094)
employmentUnemployed and looking for work −0.068 −0.122 −0.015 −0.141+ 0.063+ −0.024
(0.089) (0.086) (0.080) (0.085) (0.035) (0.080)
employmentWorking full-time −0.070 −0.059 0.004 −0.164* 0.005 0.021
(0.069) (0.066) (0.061) (0.064) (0.019) (0.059)
employmentWorking part-time −0.045 −0.056 0.077 −0.104 0.003 0.007
(0.078) (0.075) (0.070) (0.072) (0.021) (0.068)
educationNo formal education −0.076 −0.111 −0.011 −0.020 0.002 −0.177
(0.131) (0.126) (0.129) (0.120) (0.009) (0.124)
educationPost-university −0.063 0.069 −0.146 −0.147 0.030 −0.185+
(0.099) (0.096) (0.099) (0.091) (0.020) (0.095)
educationPrimary school −0.074 −0.038 0.064 0.049 0.024 −0.232*
(0.120) (0.121) (0.120) (0.113) (0.025) (0.116)
educationSecondary school −0.051 −0.072 −0.151+ −0.131 0.019* −0.239**
(0.091) (0.088) (0.092) (0.084) (0.010) (0.087)
educationUniversity −0.049 −0.032 −0.167+ −0.160+ 0.021* −0.202*
(0.091) (0.087) (0.091) (0.083) (0.009) (0.086)
has_children −0.006 −0.051+ 0.029 0.029 0.005 0.018
(0.026) (0.026) (0.024) (0.025) (0.009) (0.025)
religiosity 0.004 −0.017+ 0.007 0.019* −0.001 0.024*
(0.010) (0.010) (0.010) (0.010) (0.004) (0.010)
nationalityEastern Europe (outside France) 0.121 −0.031 −0.096 −0.091 0.045 −0.014
(0.267) (0.249) (0.269) (0.272) (0.031) (0.244)
nationalityFrance 0.135 0.072 −0.029 −0.155 0.049*** −0.032
(0.254) (0.233) (0.258) (0.257) (0.015) (0.229)
nationalityLatin America 0.143 −0.030 −0.007 −0.151 0.025 −0.274
(0.316) (0.295) (0.314) (0.317) (0.019) (0.277)
nationalityNorth Africa 0.237 0.008 −0.015 −0.119 0.062* 0.094
(0.260) (0.241) (0.264) (0.265) (0.031) (0.239)
nationalityNorth America 0.069 0.255 0.053 −0.262 0.022 0.570*
(0.440) (0.385) (0.355) (0.392) (0.023) (0.232)
nationalityOceania 0.042 0.756** −0.341 −0.192 0.028 −0.030
(0.600) (0.290) (0.281) (0.457) (0.033) (0.402)
nationalitySouth Asia 0.106 0.336 −0.155 0.115 0.023 0.271
(0.357) (0.307) (0.323) (0.317) (0.019) (0.300)
nationalitySub-Saharan Africa 0.262 −0.011 −0.106 0.112 0.073 −0.107
(0.279) (0.259) (0.278) (0.266) (0.056) (0.256)
nationalityWestern Europe (outside France) 0.093 0.056 −0.173 −0.118 0.047+ 0.018
(0.261) (0.241) (0.263) (0.264) (0.028) (0.238)
owner_domicile −0.057* 0.075** −0.048* −0.065** 0.012 −0.011
(0.025) (0.025) (0.024) (0.024) (0.009) (0.024)
ambivalent_sexism_index −0.007 −0.033+ 0.101*** 0.024 0.000 0.002
(0.019) (0.019) (0.017) (0.018) (0.008) (0.019)
climate_beliefsA little −0.131** −0.013 −0.066+ −0.134*** −0.009 −0.149***
(0.042) (0.043) (0.040) (0.040) (0.013) (0.040)
climate_beliefsA lot −0.055+ 0.006 −0.013 −0.024 0.012 −0.046
(0.033) (0.033) (0.031) (0.031) (0.013) (0.031)
climate_beliefsDon't know −0.016 −0.019 0.154+ −0.092 0.024 −0.099
(0.085) (0.086) (0.081) (0.074) (0.034) (0.080)
climate_beliefsModerately −0.112*** −0.008 −0.060+ −0.077* 0.001 −0.083*
(0.034) (0.034) (0.032) (0.033) (0.012) (0.033)
climate_beliefsNot at all −0.059 0.048 −0.013 −0.097+ −0.013 −0.235***
(0.060) (0.061) (0.055) (0.055) (0.015) (0.049)
pro_sociality_index 0.072*** −0.017 −0.002 0.116*** 0.010+ 0.094***
(0.018) (0.018) (0.016) (0.017) (0.006) (0.017)
trust_governmentJust about always 0.022 0.094 0.022 0.148** 0.032 0.283***
(0.060) (0.059) (0.057) (0.054) (0.023) (0.054)
trust_governmentMost of the time −0.009 0.113* 0.051 0.153*** 0.020 0.230***
(0.046) (0.045) (0.042) (0.043) (0.014) (0.042)
trust_governmentOnly some of the time −0.055 0.059 −0.025 0.080* 0.014 0.137***
(0.041) (0.041) (0.038) (0.039) (0.013) (0.037)
participated_protest_last_12_months 0.073* 0.077* 0.054+ 0.214*** 0.004 0.116***
(0.032) (0.032) (0.031) (0.029) (0.012) (0.031)
demanded_action_last_12_months 0.007 0.005 0.046 0.073* 0.027* 0.066*
(0.031) (0.031) (0.029) (0.029) (0.013) (0.030)
R2 0.00 0.06 0.00 0.05 0.00 0.06 0.00 0.15 0.00 0.02 0.00 0.13
Num. obs. 1991 1939 1992 1940 1994 1942 1994 1942 1987 1935 1994 1942
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, pooled sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adpatation outcomes. Run on pooled sample. Robust SEs.
(Intercept) 0.622*** 0.299** 0.484*** 0.567*** 0.357*** 0.101 0.653*** 0.272** 0.069*** −0.058 0.652*** 0.261**
(0.011) (0.112) (0.012) (0.116) (0.011) (0.116) (0.011) (0.104) (0.006) (0.041) (0.011) (0.097)
treatment_victim −0.017 −0.008 −0.022 −0.022 −0.001 0.004 −0.001 0.005 −0.000 0.004 −0.027+ −0.017
(0.016) (0.015) (0.016) (0.017) (0.016) (0.016) (0.016) (0.015) (0.008) (0.009) (0.016) (0.015)
male 0.007 0.047** −0.048** 0.030+ 0.026** 0.022
(0.016) (0.017) (0.016) (0.016) (0.009) (0.016)
age25-34 years old −0.020 0.078* 0.022 0.007 −0.007 −0.029
(0.026) (0.031) (0.030) (0.027) (0.017) (0.027)
age35-44 years old −0.074* 0.123*** 0.039 −0.032 0.013 −0.079**
(0.030) (0.034) (0.033) (0.029) (0.018) (0.030)
age45-54 years old −0.152*** 0.138*** 0.022 −0.070* 0.033+ −0.159***
(0.033) (0.036) (0.035) (0.032) (0.019) (0.032)
age55-64 years old −0.156*** 0.191*** −0.034 −0.116** 0.030 −0.112**
(0.038) (0.040) (0.038) (0.037) (0.021) (0.036)
age65-74 years old −0.121* 0.161** −0.040 −0.123* −0.008 −0.072
(0.059) (0.061) (0.055) (0.054) (0.029) (0.058)
age75+ years old −0.028 0.295*** −0.113 −0.133 −0.026 −0.001
(0.087) (0.086) (0.073) (0.082) (0.033) (0.086)
employmentOther × 0.004 0.061 0.116 0.038 0.022 0.118
(0.082) (0.090) (0.087) (0.070) (0.052) (0.080)
employmentRetired −0.049 −0.049 0.026 −0.112+ 0.016 0.077
(0.071) (0.070) (0.064) (0.062) (0.034) (0.066)
employmentStudent 0.084 −0.037 0.010 −0.131* −0.005 0.093
(0.061) (0.063) (0.060) (0.056) (0.032) (0.058)
employmentUnemployed and looking for work 0.068 −0.091 −0.014 −0.078 0.034 0.130*
(0.059) (0.061) (0.059) (0.054) (0.032) (0.056)
employmentWorking full-time −0.019 −0.028 0.003 −0.132** −0.018 0.104*
(0.055) (0.054) (0.051) (0.048) (0.025) (0.050)
employmentWorking part-time 0.033 −0.022 0.068 −0.056 0.014 0.125*
(0.057) (0.057) (0.055) (0.050) (0.028) (0.053)
educationNo formal education −0.059 −0.018 0.070 0.074 0.002 −0.022
(0.108) (0.106) (0.110) (0.094) (0.011) (0.090)
educationPost-university 0.002 0.094 −0.084 −0.038 0.067** −0.144+
(0.089) (0.088) (0.091) (0.082) (0.022) (0.074)
educationPrimary school 0.061 −0.034 0.090 0.074 0.027 −0.129
(0.099) (0.101) (0.104) (0.092) (0.024) (0.086)
educationSecondary school 0.018 −0.030 −0.077 −0.053 0.043*** −0.159*
(0.083) (0.082) (0.086) (0.078) (0.012) (0.067)
educationUniversity 0.041 0.024 −0.086 −0.048 0.058*** −0.126+
(0.083) (0.081) (0.086) (0.077) (0.011) (0.067)
has_children 0.021 −0.023 0.062** 0.059** 0.006 0.049**
(0.019) (0.020) (0.019) (0.018) (0.010) (0.018)
religiosity 0.032*** 0.001 −0.003 0.028*** 0.011** 0.036***
(0.005) (0.006) (0.006) (0.005) (0.003) (0.005)
owner_domicile −0.107*** 0.016 −0.031+ −0.086*** −0.024* −0.043*
(0.018) (0.019) (0.018) (0.018) (0.010) (0.018)
ambivalent_sexism_index 0.031* −0.045** 0.076*** 0.025* 0.007 0.004
(0.013) (0.014) (0.013) (0.012) (0.007) (0.012)
climate_beliefsA little −0.029 −0.051+ 0.044 −0.057* −0.040* −0.065*
(0.026) (0.030) (0.029) (0.025) (0.015) (0.027)
climate_beliefsA lot −0.036+ −0.012 −0.017 −0.029 −0.027* −0.016
(0.021) (0.024) (0.023) (0.020) (0.014) (0.021)
climate_beliefsDon't know −0.058 −0.018 0.126* −0.140* −0.041 −0.119*
(0.057) (0.060) (0.059) (0.057) (0.025) (0.056)
climate_beliefsModerately −0.094*** −0.044+ −0.013 −0.071** −0.048*** −0.053*
(0.023) (0.026) (0.024) (0.023) (0.013) (0.023)
climate_beliefsNot at all −0.031 −0.024 0.056 −0.031 −0.052** −0.063+
(0.041) (0.045) (0.043) (0.040) (0.018) (0.038)
pro_sociality_index 0.084*** −0.010 −0.000 0.095*** 0.008 0.091***
(0.012) (0.013) (0.013) (0.011) (0.006) (0.012)
trust_governmentJust about always −0.045 0.036 0.053 0.123*** 0.019 0.159***
(0.032) (0.036) (0.035) (0.030) (0.019) (0.030)
trust_governmentMost of the time −0.041 0.038 0.063* 0.112*** 0.030* 0.112***
(0.026) (0.029) (0.028) (0.026) (0.015) (0.026)
trust_governmentOnly some of the time −0.091*** 0.023 −0.030 0.047+ 0.010 0.025
(0.024) (0.027) (0.026) (0.025) (0.013) (0.025)
participated_protest_last_12_months 0.048* 0.057* 0.088*** 0.141*** 0.004 0.087***
(0.020) (0.023) (0.022) (0.019) (0.012) (0.020)
demanded_action_last_12_months 0.024 −0.027 0.082*** 0.081*** 0.010 0.066***
(0.021) (0.023) (0.022) (0.019) (0.012) (0.020)
R2 0.00 0.17 0.00 0.03 0.00 0.06 0.00 0.18 0.00 0.04 0.00 0.16
Num. obs. 3701 3429 3702 3430 3704 3432 3704 3432 3697 3425 3704 3432

Secondary hypothesis 1 (S1).

Victimization of climate change communication will differentially demobilize Global South citizens when the victim is also a woman. We expect that this will have no effect or a positive effect on French citizens. We present country-wise regressions in the main paper and pooled regressions across the sample in the appendix

CDI, unadjusted CDI, adjusted FR, unadjusted FR, adjusted Pooled, unadjusted Pooled, adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Outcome is a PCA index of the three political mobilization outcomes. Robust SEs.
(Intercept) −0.378*** 3.351*** 0.268*** 1.915*** −0.030 3.303***
(0.068) (0.595) (0.061) (0.547) (0.047) (0.294)
treatment_female −0.036 0.008 0.099 0.065 0.032 0.034
(0.095) (0.094) (0.087) (0.078) (0.066) (0.061)
treatment_victim −0.055 −0.015 0.116 0.088 0.042 0.018
(0.096) (0.095) (0.089) (0.079) (0.067) (0.061)
treatment_female × treatment_victim 0.111 0.111 −0.148 −0.115 −0.026 −0.014
(0.134) (0.135) (0.126) (0.111) (0.095) (0.087)
male −0.165* 0.029 −0.031
(0.076) (0.060) (0.045)
age25-34 years old −0.359*** −0.088 −0.277***
(0.104) (0.137) (0.081)
age35-44 years old −0.397** −0.144 −0.196*
(0.123) (0.139) (0.088)
age45-54 years old −0.497** −0.113 −0.113
(0.163) (0.141) (0.094)
age55-64 years old −0.184 −0.393** −0.229*
(0.345) (0.144) (0.105)
age75+ years old 0.295 −0.300 −0.027
(0.349) (0.223) (0.204)
employmentOther × −0.154 0.289 −0.084
(0.320) (0.236) (0.194)
employmentRetired 0.284 0.311 0.092
(0.629) (0.196) (0.175)
employmentStudent 0.157 0.037 0.182
(0.255) (0.237) (0.160)
employmentUnemployed and looking for work 0.062 0.407+ 0.194
(0.251) (0.222) (0.158)
employmentWorking full-time 0.020 0.385* 0.200
(0.238) (0.166) (0.136)
employmentWorking part-time −0.039 0.484** 0.125
(0.241) (0.183) (0.143)
educationNo formal education −0.516 −0.363 −0.429
(0.620) (0.329) (0.278)
educationPost-university −1.153* −0.472+ −0.703**
(0.577) (0.242) (0.220)
educationPrimary school −0.768 −0.582+ −0.650*
(0.616) (0.314) (0.268)
educationSecondary school −0.949+ −0.418+ −0.579**
(0.562) (0.222) (0.205)
educationUniversity −1.086+ −0.393+ −0.652**
(0.562) (0.219) (0.203)
has_children −0.158+ 0.003 −0.108*
(0.087) (0.066) (0.052)
religiosity −0.001 −0.062* −0.063***
(0.024) (0.026) (0.016)
ethnicityAbron 0.190
(0.202)
ethnicityAdjoukrou 0.121
(0.172)
ethnicityAgni 0.326*
(0.162)
ethnicityAttié 0.263
(0.182)
ethnicityAvikam 0.335
(0.420)
ethnicityBambara 0.230
(0.255)
ethnicityBaoulé 0.169
(0.138)
ethnicityBété 0.309+
(0.174)
ethnicityDida 0.068
(0.250)
ethnicityDioula 0.372*
(0.188)
ethnicityDon't know −0.006
(0.279)
ethnicityGodié −0.290
(0.455)
ethnicityGouro −0.131
(0.202)
ethnicityGuéré 0.017
(0.221)
ethnicityKoulango 0.082
(0.347)
ethnicityKroumen 0.214
(0.363)
ethnicityLobi 0.540*
(0.250)
ethnicityMalinké/Maninka 0.406+
(0.222)
ethnicityOnly Ivoirian (do not identify in these terms) 0.344+
(0.185)
ethnicitySenoufo 0.254
(0.173)
ethnicityYacouba 0.178
(0.219)
owner_domicile −0.365*** 0.086 0.071
(0.093) (0.061) (0.049)
ambivalent_sexism_index −0.324*** −0.121* −0.212***
(0.057) (0.053) (0.039)
climate_beliefsA little 0.229* 0.801*** 0.462***
(0.116) (0.109) (0.080)
climate_beliefsA lot 0.143 0.152+ 0.121*
(0.090) (0.084) (0.061)
climate_beliefsDon't know 0.624* 0.341+ 0.392*
(0.250) (0.179) (0.157)
climate_beliefsModerately 0.293** 0.520*** 0.407***
(0.104) (0.088) (0.066)
climate_beliefsNot at all 0.709*** 1.293*** 0.956***
(0.194) (0.182) (0.132)
pro_sociality_index −0.325*** −0.545*** −0.515***
(0.058) (0.048) (0.037)
trust_governmentJust about always −0.250+ 0.090 −0.127
(0.132) (0.160) (0.103)
trust_governmentMost of the time −0.179+ −0.123 −0.144+
(0.105) (0.112) (0.076)
trust_governmentOnly some of the time −0.162 0.032 −0.017
(0.101) (0.103) (0.072)
participated_protest_last_12_months −0.151+ −0.537*** −0.416***
(0.087) (0.081) (0.059)
demanded_action_last_12_months −0.227* −0.203** −0.275***
(0.089) (0.076) (0.057)
age65-74 years old −0.302+ −0.124
(0.180) (0.154)
nationalityEastern Europe (outside France) 1.061*
(0.453)
nationalityFrance 0.629
(0.391)
nationalityLatin America 0.458
(0.518)
nationalityNorth Africa 0.433
(0.428)
nationalityNorth America −0.161
(1.061)
nationalityOceania −0.992+
(0.531)
nationalitySouth Asia 0.235
(0.860)
nationalitySub-Saharan Africa 0.592
(0.509)
nationalityWestern Europe (outside France) 0.751+
(0.424)
R2 0.00 0.21 0.00 0.27 0.00 0.25
Num. obs. 1710 1490 2004 1952 3714 3442

Secondary hypothesis 2 (S2).

Victimization of climate change communication will differentially increase support for Global South climate financing when the victim is also a woman, among Global North citizens (for all five outcomes). We expect the same among Global South citizens but only for the first four outcomes. For Global South citizens, we expect the last outcome to move in the opposite direction.

Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, Ivorian sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adpatation outcomes. Run on Ivorian sample. Robust SEs.
(Intercept) 0.844*** 0.556* 0.442*** 0.447* 0.340*** −0.143 0.833*** 0.488* 0.098*** 0.058 0.826*** 0.575***
(0.018) (0.238) (0.024) (0.219) (0.023) (0.270) (0.018) (0.199) (0.014) (0.088) (0.018) (0.120)
treatment_female −0.023 −0.030 0.019 0.026 0.142*** 0.154*** −0.033 −0.055* 0.016 0.013 −0.012 −0.026
(0.025) (0.027) (0.034) (0.036) (0.033) (0.035) (0.026) (0.027) (0.021) (0.022) (0.026) (0.027)
treatment_victim −0.005 −0.002 0.006 0.013 −0.017 −0.033 0.011 0.007 0.011 0.018 −0.079** −0.088**
(0.025) (0.027) (0.034) (0.037) (0.032) (0.034) (0.025) (0.026) (0.021) (0.023) (0.028) (0.028)
treatment_female × treatment_victim 0.016 0.030 −0.046 −0.063 −0.011 −0.013 0.007 0.026 −0.011 −0.013 0.071+ 0.101*
(0.036) (0.038) (0.048) (0.052) (0.047) (0.049) (0.037) (0.038) (0.030) (0.033) (0.039) (0.040)
male 0.026 0.042 −0.059* 0.077*** 0.036* 0.016
(0.021) (0.029) (0.027) (0.023) (0.018) (0.022)
age25-34 years old 0.019 0.039 0.007 0.012 −0.003 0.038
(0.028) (0.039) (0.037) (0.029) (0.025) (0.029)
age35-44 years old 0.011 0.062 0.045 0.017 0.047 −0.004
(0.034) (0.047) (0.045) (0.033) (0.031) (0.035)
age45-54 years old −0.006 0.065 0.079 0.033 0.098* −0.032
(0.043) (0.060) (0.056) (0.042) (0.045) (0.046)
age55-64 years old −0.072 0.147 −0.080 −0.088 0.087 −0.049
(0.100) (0.102) (0.096) (0.093) (0.084) (0.088)
age75+ years old 0.552*** −0.620*** 0.312* 0.152+ 0.014 −1.027***
(0.111) (0.131) (0.134) (0.089) (0.053) (0.065)
employmentOther × 0.119 0.229+ −0.009 −0.007 −0.042 0.183
(0.101) (0.137) (0.125) (0.086) (0.100) (0.124)
employmentRetired −0.156 0.123 0.011 −0.110 −0.015 0.367**
(0.235) (0.201) (0.207) (0.164) (0.165) (0.117)
employmentStudent 0.159+ 0.057 −0.059 −0.158* −0.081 0.208*
(0.087) (0.104) (0.096) (0.075) (0.069) (0.094)
employmentUnemployed and looking for work 0.146+ −0.001 −0.071 −0.073 −0.046 0.250**
(0.086) (0.103) (0.096) (0.073) (0.068) (0.093)
employmentWorking full-time 0.090 0.091 −0.058 −0.099 −0.074 0.244**
(0.083) (0.098) (0.091) (0.069) (0.065) (0.090)
employmentWorking part-time 0.067 0.068 0.006 −0.079 −0.051 0.229*
(0.085) (0.100) (0.093) (0.070) (0.066) (0.092)
educationNo formal education −0.207 0.247 0.289 0.205 0.020 −0.082
(0.240) (0.212) (0.248) (0.174) (0.041) (0.068)
educationPost-university −0.041 0.201 0.198 0.175 0.133* −0.326***
(0.228) (0.194) (0.231) (0.164) (0.055) (0.079)
educationPrimary school 0.065 0.083 0.292 0.158 0.056 −0.243*
(0.229) (0.205) (0.241) (0.173) (0.058) (0.100)
educationSecondary school −0.002 0.110 0.195 0.141 0.097* −0.242***
(0.225) (0.188) (0.225) (0.161) (0.040) (0.065)
educationUniversity −0.029 0.169 0.196 0.150 0.109** −0.281***
(0.225) (0.187) (0.224) (0.160) (0.039) (0.064)
has_children 0.024 0.013 0.096** 0.064** −0.005 0.049*
(0.024) (0.033) (0.032) (0.024) (0.021) (0.025)
religiosity −0.002 0.006 −0.013 −0.004 −0.000 0.006
(0.006) (0.009) (0.008) (0.007) (0.006) (0.007)
ethnicityAbron 0.004 −0.160 0.107 0.036 −0.005 −0.005
(0.059) (0.106) (0.099) (0.065) (0.063) (0.074)
ethnicityAdjoukrou −0.172** −0.221* 0.099 0.044 −0.052 0.092
(0.066) (0.089) (0.090) (0.059) (0.050) (0.059)
ethnicityAgni −0.111* −0.162+ 0.060 0.012 −0.011 0.053
(0.052) (0.083) (0.082) (0.060) (0.050) (0.060)
ethnicityAttié −0.029 −0.124 0.163+ −0.013 −0.024 0.102
(0.053) (0.090) (0.089) (0.065) (0.056) (0.063)
ethnicityAvikam −0.115 −0.065 0.076 0.222*** 0.135 0.238***
(0.131) (0.158) (0.149) (0.066) (0.125) (0.066)
ethnicityBambara −0.162+ −0.013 0.275* −0.026 −0.034 −0.002
(0.083) (0.111) (0.112) (0.079) (0.066) (0.085)
ethnicityBaoulé −0.083+ −0.070 0.164* 0.036 −0.028 0.056
(0.045) (0.077) (0.078) (0.055) (0.047) (0.056)
ethnicityBété −0.152** −0.104 0.202* 0.002 −0.058 0.083
(0.057) (0.087) (0.087) (0.062) (0.052) (0.062)
ethnicityDida −0.055 −0.069 0.268* −0.074 −0.058 0.048
(0.067) (0.110) (0.108) (0.085) (0.063) (0.081)
ethnicityDioula −0.093 −0.120 0.182* 0.036 −0.062 −0.010
(0.058) (0.092) (0.090) (0.065) (0.054) (0.070)
ethnicityDon't know −0.065 −0.126 0.049 0.061 −0.011 0.115
(0.077) (0.108) (0.108) (0.082) (0.068) (0.084)
ethnicityGodié −0.167 0.047 0.238 −0.025 −0.084+ −0.042
(0.159) (0.185) (0.166) (0.124) (0.047) (0.135)
ethnicityGouro −0.165* −0.040 −0.027 0.032 −0.041 0.065
(0.075) (0.104) (0.095) (0.076) (0.062) (0.074)
ethnicityGuéré −0.123+ 0.004 0.227* 0.081 −0.032 0.071
(0.067) (0.099) (0.101) (0.066) (0.062) (0.072)
ethnicityKoulango −0.045 −0.223+ 0.260* 0.157* −0.054 0.193**
(0.092) (0.132) (0.120) (0.066) (0.065) (0.066)
ethnicityKroumen −0.007 0.148 0.254 0.100 −0.114* −0.048
(0.099) (0.166) (0.156) (0.100) (0.045) (0.129)
ethnicityLobi 0.124 0.270 −0.072 0.115 −0.137+ 0.048
(0.076) (0.269) (0.198) (0.086) (0.074) (0.225)
ethnicityMalinké/Maninka −0.051 −0.120 0.214* 0.026 0.018 −0.034
(0.063) (0.101) (0.097) (0.073) (0.071) (0.078)
ethnicityOnly Ivoirian (do not identify in these terms) −0.041 −0.043 0.006 −0.013 −0.042 0.017
(0.053) (0.089) (0.087) (0.064) (0.053) (0.066)
ethnicitySenoufo −0.079 −0.183* 0.124 0.033 0.015 0.018
(0.053) (0.087) (0.087) (0.061) (0.056) (0.063)
ethnicityYacouba −0.022 −0.054 0.211* 0.035 −0.053 0.060
(0.060) (0.098) (0.097) (0.064) (0.060) (0.069)
owner_domicile −0.021 −0.083* 0.042 0.037 −0.021 0.023
(0.029) (0.037) (0.035) (0.027) (0.024) (0.030)
ambivalent_sexism_index 0.061*** −0.051* 0.045* 0.024 0.015 0.006
(0.016) (0.021) (0.020) (0.016) (0.013) (0.016)
climate_beliefsA little 0.010 −0.072+ 0.143*** −0.005 −0.082** −0.023
(0.030) (0.043) (0.041) (0.030) (0.029) (0.034)
climate_beliefsA lot −0.021 −0.018 −0.022 −0.054* −0.069** 0.009
(0.024) (0.035) (0.033) (0.025) (0.025) (0.026)
climate_beliefsDon't know −0.182* −0.002 0.099 −0.248** −0.118** −0.186*
(0.075) (0.090) (0.089) (0.083) (0.039) (0.083)
climate_beliefsModerately −0.060* −0.069+ 0.045 −0.035 −0.101*** 0.001
(0.030) (0.041) (0.040) (0.030) (0.026) (0.030)
climate_beliefsNot at all −0.105+ −0.119+ 0.135+ −0.042 −0.110** 0.034
(0.058) (0.068) (0.069) (0.054) (0.034) (0.050)
pro_sociality_index 0.029+ −0.000 −0.018 0.013 −0.008 0.034*
(0.016) (0.021) (0.020) (0.015) (0.012) (0.016)
trust_governmentJust about always −0.081* 0.016 0.041 0.117** 0.034 0.095**
(0.035) (0.048) (0.046) (0.036) (0.028) (0.034)
trust_governmentMost of the time −0.035 0.004 0.060 0.105** 0.059* 0.051
(0.029) (0.041) (0.038) (0.032) (0.024) (0.032)
trust_governmentOnly some of the time −0.054* 0.024 −0.018 0.080* 0.030 −0.000
(0.027) (0.039) (0.036) (0.032) (0.024) (0.031)
participated_protest_last_12_months 0.002 0.074* 0.080* 0.023 0.013 0.031
(0.024) (0.034) (0.032) (0.024) (0.023) (0.025)
demanded_action_last_12_months 0.023 −0.042 0.115*** 0.067** −0.010 0.058*
(0.025) (0.035) (0.033) (0.023) (0.023) (0.025)
R2 0.00 0.08 0.00 0.06 0.02 0.13 0.00 0.10 0.00 0.06 0.01 0.09
Num. obs. 1710 1490 1710 1490 1710 1490 1710 1490 1710 1490 1710 1490
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
Climate adaptation outcomes, French sample
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: 6 climate adpatation outcomes. Run on French sample. Robust SEs.
(Intercept) 0.473*** 0.506+ 0.485*** 0.403 0.270*** 0.070 0.522*** 0.372 0.032*** −0.131** 0.491*** 0.314
(0.022) (0.300) (0.022) (0.281) (0.020) (0.300) (0.022) (0.293) (0.008) (0.046) (0.022) (0.266)
treatment_female −0.070* −0.077* 0.055+ 0.061+ 0.082** 0.090** −0.022 −0.008 0.011 0.008 0.029 0.034
(0.031) (0.031) (0.032) (0.032) (0.029) (0.029) (0.032) (0.030) (0.012) (0.013) (0.032) (0.031)
treatment_victim −0.079* −0.084** 0.023 0.026 0.015 0.034 −0.005 −0.002 0.010 0.012 0.010 0.005
(0.031) (0.032) (0.032) (0.032) (0.028) (0.029) (0.032) (0.030) (0.012) (0.012) (0.032) (0.030)
treatment_female × treatment_victim 0.099* 0.104* −0.099* −0.101* 0.006 −0.002 −0.010 −0.024 −0.029+ −0.026 −0.040 −0.037
(0.044) (0.044) (0.045) (0.045) (0.042) (0.042) (0.045) (0.042) (0.017) (0.017) (0.045) (0.043)
male −0.037 0.029 −0.027 −0.026 0.002 −0.006
(0.023) (0.024) (0.022) (0.022) (0.009) (0.023)
age25-34 years old −0.102+ 0.132* 0.037 0.036 −0.003 −0.117*
(0.055) (0.052) (0.053) (0.054) (0.016) (0.054)
age35-44 years old −0.108+ 0.170** 0.060 0.031 −0.001 −0.082
(0.056) (0.053) (0.054) (0.055) (0.016) (0.054)
age45-54 years old −0.156** 0.187*** 0.038 0.031 0.021 −0.133*
(0.055) (0.053) (0.053) (0.055) (0.018) (0.054)
age55-64 years old −0.105+ 0.242*** 0.010 0.028 0.033+ −0.041
(0.057) (0.054) (0.054) (0.057) (0.020) (0.056)
age65-74 years old −0.077 0.211** 0.002 0.018 −0.000 0.019
(0.074) (0.073) (0.068) (0.070) (0.029) (0.073)
age75+ years old 0.034 0.359*** −0.078 0.020 −0.019 0.109
(0.097) (0.094) (0.083) (0.095) (0.033) (0.095)
employmentOther × −0.197+ −0.035 0.164 −0.017 0.018 0.006
(0.114) (0.127) (0.122) (0.117) (0.048) (0.109)
employmentRetired −0.097 −0.095 0.031 −0.145+ 0.029 −0.033
(0.081) (0.079) (0.072) (0.075) (0.029) (0.073)
employmentStudent −0.094 −0.051 0.061 −0.151 0.006 −0.022
(0.103) (0.102) (0.097) (0.100) (0.029) (0.093)
employmentUnemployed and looking for work −0.063 −0.128 −0.006 −0.145+ 0.060+ −0.025
(0.088) (0.085) (0.079) (0.085) (0.035) (0.080)
employmentWorking full-time −0.068 −0.061 0.009 −0.166** 0.004 0.021
(0.069) (0.065) (0.061) (0.064) (0.019) (0.059)
employmentWorking part-time −0.046 −0.056 0.082 −0.105 0.003 0.008
(0.077) (0.074) (0.070) (0.072) (0.021) (0.068)
educationNo formal education −0.079 −0.108 −0.016 −0.017 0.004 −0.176
(0.130) (0.126) (0.126) (0.120) (0.009) (0.124)
educationPost-university −0.063 0.069 −0.146 −0.147 0.031 −0.185+
(0.100) (0.096) (0.098) (0.090) (0.020) (0.095)
educationPrimary school −0.072 −0.042 0.071 0.047 0.023 −0.232*
(0.121) (0.120) (0.118) (0.112) (0.025) (0.116)
educationSecondary school −0.051 −0.072 −0.149+ −0.131 0.019* −0.239**
(0.092) (0.088) (0.090) (0.084) (0.009) (0.087)
educationUniversity −0.047 −0.035 −0.166+ −0.161+ 0.021* −0.203*
(0.092) (0.087) (0.090) (0.083) (0.009) (0.086)
has_children −0.007 −0.050+ 0.027 0.029 0.005 0.018
(0.026) (0.026) (0.024) (0.025) (0.009) (0.025)
religiosity 0.004 −0.017+ 0.007 0.019* −0.001 0.024*
(0.010) (0.010) (0.010) (0.010) (0.004) (0.010)
nationalityEastern Europe (outside France) 0.114 −0.026 −0.082 −0.093 0.045 −0.010
(0.271) (0.256) (0.273) (0.271) (0.031) (0.245)
nationalityFrance 0.124 0.081 −0.013 −0.157 0.050** −0.027
(0.257) (0.240) (0.262) (0.256) (0.016) (0.230)
nationalityLatin America 0.121 −0.012 0.018 −0.153 0.028 −0.264
(0.319) (0.302) (0.315) (0.316) (0.020) (0.277)
nationalityNorth Africa 0.222 0.020 −0.001 −0.119 0.064* 0.100
(0.264) (0.248) (0.267) (0.264) (0.031) (0.239)
nationalityNorth America 0.044 0.274 0.086 −0.265 0.024 0.581*
(0.442) (0.402) (0.371) (0.386) (0.025) (0.232)
nationalityOceania 0.045 0.757** −0.366 −0.185 0.030 −0.033
(0.623) (0.284) (0.284) (0.462) (0.030) (0.409)
nationalitySouth Asia 0.094 0.341 −0.115 0.106 0.021 0.278
(0.357) (0.316) (0.328) (0.316) (0.019) (0.304)
nationalitySub-Saharan Africa 0.240 0.006 −0.078 0.109 0.075 −0.098
(0.282) (0.267) (0.280) (0.265) (0.057) (0.257)
nationalityWestern Europe (outside France) 0.083 0.064 −0.164 −0.118 0.048+ 0.022
(0.265) (0.249) (0.266) (0.264) (0.029) (0.238)
owner_domicile −0.058* 0.076** −0.048* −0.064** 0.012 −0.011
(0.025) (0.026) (0.023) (0.024) (0.009) (0.024)
ambivalent_sexism_index −0.008 −0.032+ 0.101*** 0.024 0.000 0.002
(0.019) (0.019) (0.017) (0.018) (0.008) (0.019)
climate_beliefsA little −0.132** −0.012 −0.067+ −0.134*** −0.009 −0.148***
(0.042) (0.043) (0.040) (0.040) (0.013) (0.040)
climate_beliefsA lot −0.056+ 0.006 −0.007 −0.026 0.011 −0.045
(0.033) (0.033) (0.031) (0.031) (0.013) (0.031)
climate_beliefsDon't know −0.020 −0.015 0.154+ −0.092 0.025 −0.098
(0.084) (0.085) (0.080) (0.074) (0.034) (0.080)
climate_beliefsModerately −0.113*** −0.008 −0.060+ −0.077* 0.001 −0.083*
(0.034) (0.034) (0.032) (0.033) (0.012) (0.033)
climate_beliefsNot at all −0.058 0.048 −0.015 −0.097+ −0.013 −0.236***
(0.060) (0.061) (0.054) (0.055) (0.016) (0.048)
pro_sociality_index 0.071*** −0.016 −0.003 0.117*** 0.010+ 0.094***
(0.018) (0.018) (0.016) (0.017) (0.006) (0.017)
trust_governmentJust about always 0.022 0.094 0.022 0.148** 0.032 0.283***
(0.060) (0.059) (0.057) (0.054) (0.023) (0.054)
trust_governmentMost of the time −0.012 0.115* 0.053 0.153*** 0.020 0.231***
(0.045) (0.045) (0.042) (0.043) (0.014) (0.042)
trust_governmentOnly some of the time −0.058 0.061 −0.023 0.079* 0.014 0.138***
(0.041) (0.041) (0.038) (0.039) (0.013) (0.037)
participated_protest_last_12_months 0.070* 0.079* 0.055+ 0.214*** 0.005 0.117***
(0.032) (0.032) (0.031) (0.029) (0.012) (0.031)
demanded_action_last_12_months 0.009 0.003 0.045 0.073* 0.026* 0.065*
(0.031) (0.031) (0.029) (0.029) (0.013) (0.030)
R2 0.00 0.06 0.00 0.05 0.01 0.07 0.00 0.15 0.00 0.02 0.00 0.13
Num. obs. 1991 1939 1992 1940 1994 1942 1994 1942 1987 1935 1994 1942 

## willingness to pay

library(estimatr)
library(broom)

# make sure Currency_label is a factor with the correct order
df <- df %>%
  mutate(Currency_label = factor(Currency_label,
                                 levels = c("€1","€5","€25","€50","€100",
                                            "500 CFA","2000 CFA","10000 CFA","20000 CFA","40000 CFA")))

# function: run regression for a given treatment var
get_effects <- function(data, sample_label, treat_var, treat_label) {
  data %>%
    group_by(Currency_label) %>%
    do({
      f <- as.formula(paste("willingness_to_pay ~", treat_var))
      mod <- lm_robust(f, data = .)
      tidy(mod, conf.int = TRUE) %>%
        filter(term == treat_var) %>%
        mutate(N = n())
    }) %>%
    ungroup() %>%
    mutate(sample = sample_label,
           treatment = treat_label)
}

# France (euros only)
res_fr_female <- get_effects(df %>% filter(fr_sample == 1 & grepl("€", Currency_label)),
                             "France", "treatment_female", "Female treatment")
res_fr_victim <- get_effects(df %>% filter(fr_sample == 1 & grepl("€", Currency_label)),
                             "France", "treatment_victim", "Victim treatment")

# Côte d’Ivoire (CFA only)
res_cdi_female <- get_effects(df %>% filter(cdi_sample == 1 & grepl("CFA", Currency_label)),
                              "Côte d’Ivoire", "treatment_female", "Female treatment")
res_cdi_victim <- get_effects(df %>% filter(cdi_sample == 1 & grepl("CFA", Currency_label)),
                              "Côte d’Ivoire", "treatment_victim", "Victim treatment")

# Combine all
results <- bind_rows(res_fr_female, res_fr_victim,
                     res_cdi_female, res_cdi_victim)

# Plot
p <- ggplot(results,
       aes(x = Currency_label, y = estimate,
           ymin = conf.low, ymax = conf.high,
           color = treatment, shape = treatment,
           group = treatment)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_pointrange(position = position_dodge(width = 0.5)) +
  labs(x = "Randomized contribution amount",
       y = "Treatment effect",
       title = "Impact of treatments by contribution amount") +
  facet_wrap(~sample, scales = "free_x", ncol = 2) +
  theme_classic(base_size = 14) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))


ggsave("treatment_effects_wtp.png", plot = p,
       width = 10, height = 6, dpi = 300)

Exploratory hypotheses.

Mechanism outcomes

First, in order to probe potential mechanisms underlying our main and secondary hypotheses, we preregister a group of exploratory analyses where we investigate the impact of our treatments (and their interactions) on several psychological and attitudinal outcomes, as well as an open text response on how the treatment made the respondent feel.

Gender paternalism Global south paternalism People in some parts of the world face more climate consequences Ivory Coast more affected by climate change than France Likelihood of climate migration Extent to which migration to my country should be decreased Anger/resentment response Empathetic response Helplessness response Deserving victimhood Send message to rep. concerning what I just saw
Mechanism outcomes, French sample
Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Mechanism outcomes. Run on French sample. Robust SEs.
(Intercept) 0.751*** 0.771*** 0.772*** 0.822*** 0.808*** 0.813*** 0.577*** 0.561*** 0.562*** 0.681*** 0.671*** 0.668*** 3.761*** 3.782*** 3.675*** 3.311*** 3.368*** 3.398*** 0.074*** 0.083*** 0.063*** 0.790*** 0.799*** 0.817*** 0.137*** 0.118*** 0.120*** 0.615*** 0.606*** 0.625*** 0.526*** 0.527*** 0.533***
(0.014) (0.013) (0.019) (0.012) (0.013) (0.017) (0.016) (0.016) (0.022) (0.015) (0.015) (0.021) (0.035) (0.035) (0.051) (0.041) (0.042) (0.058) (0.008) (0.009) (0.011) (0.013) (0.013) (0.017) (0.011) (0.010) (0.014) (0.015) (0.015) (0.022) (0.016) (0.016) (0.022)
treatment_female 0.022 −0.001 −0.015 −0.010 −0.006 −0.002 0.001 0.007 0.072 0.217** −0.018 −0.060 0.026* 0.040* −0.018 −0.035 −0.008 −0.005 −0.031 −0.038 −0.039+ −0.010
(0.019) (0.027) (0.017) (0.025) (0.022) (0.032) (0.021) (0.030) (0.049) (0.069) (0.059) (0.083) (0.013) (0.017) (0.018) (0.025) (0.015) (0.020) (0.022) (0.031) (0.022) (0.032)
treatment_victim −0.018 −0.041 0.013 0.018 0.026 0.030 0.020 0.026 0.031 0.172* −0.131* −0.174* 0.007 0.021 −0.036* −0.053* 0.029+ 0.032 −0.013 −0.021 −0.042+ −0.014
(0.019) (0.027) (0.017) (0.024) (0.022) (0.031) (0.021) (0.030) (0.049) (0.069) (0.059) (0.082) (0.013) (0.016) (0.018) (0.026) (0.015) (0.022) (0.022) (0.031) (0.022) (0.031)
treatment_victim × treatment_female 0.046 −0.010 −0.008 −0.012 −0.287** 0.087 −0.028 0.034 −0.006 0.015 −0.056
(0.038) (0.035) (0.045) (0.042) (0.098) (0.118) (0.025) (0.037) (0.030) (0.044) (0.044)
R2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Num. obs. 1981 1981 1981 1975 1975 1975 1973 1973 1973 1969 1969 1969 1965 1965 1965 1963 1963 1963 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021
Gender paternalism Global south paternalism People in some parts of the world face more climate consequences Ivory Coast more affected by climate change than France Likelihood of climate migration Extent to which migration to my country should be decreased Anger/resentment response Empathetic response Helplessness response Deserving victimhood Send message to rep. concerning what I just saw
Mechanism outcomes, Ivorian sample
Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction Feminization Victimization Interaction
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Mechanism outcomes. Run on Ivorian sample. Robust SEs.
(Intercept) 0.896*** 0.899*** 0.898*** 0.917*** 0.917*** 0.921*** 0.581*** 0.593*** 0.570*** 0.783*** 0.772*** 0.786*** 3.521*** 3.488*** 3.474*** 2.877*** 2.931*** 2.856*** 0.042*** 0.052*** 0.053*** 0.919*** 0.891*** 0.895*** 0.039*** 0.057*** 0.051*** 0.901*** 0.894*** 0.891*** 0.852*** 0.821*** 0.842***
(0.010) (0.010) (0.015) (0.009) (0.009) (0.013) (0.017) (0.017) (0.024) (0.014) (0.014) (0.020) (0.044) (0.044) (0.064) (0.046) (0.046) (0.065) (0.007) (0.008) (0.011) (0.009) (0.011) (0.015) (0.007) (0.008) (0.011) (0.010) (0.010) (0.015) (0.012) (0.013) (0.018)
treatment_female 0.011 0.002 0.008 −0.007 0.033 0.047 −0.007 −0.028 0.005 0.028 0.112+ 0.151+ 0.008 −0.002 −0.017 −0.009 0.009 0.012 0.015 0.007 −0.042* −0.042
(0.014) (0.021) (0.013) (0.019) (0.024) (0.034) (0.020) (0.029) (0.062) (0.088) (0.065) (0.092) (0.010) (0.015) (0.014) (0.021) (0.010) (0.016) (0.014) (0.021) (0.018) (0.026)
treatment_victim 0.005 −0.004 0.006 −0.009 0.009 0.023 0.015 −0.006 0.070 0.094 0.003 0.042 −0.012 −0.023+ 0.040** 0.048* −0.028** −0.025+ 0.029* 0.022 0.020 0.021
(0.014) (0.021) (0.013) (0.019) (0.024) (0.034) (0.020) (0.028) (0.062) (0.089) (0.065) (0.092) (0.010) (0.014) (0.014) (0.019) (0.010) (0.013) (0.014) (0.020) (0.018) (0.024)
treatment_victim × treatment_female 0.018 0.029 −0.027 0.043 −0.048 −0.080 0.021 −0.016 −0.005 0.015 −0.001
(0.029) (0.026) (0.047) (0.040) (0.124) (0.130) (0.020) (0.028) (0.020) (0.028) (0.036)
R2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710 1710

Heterogeneous treatment effects

Second, we probe heterogeneity of treatment effects by conducting subgroup analysis and interaction analyses (between treatment and covariates of interest) with the following covariates: gender, baseline climate beliefs, age, whether or not has children, socioeconomic status, and ambivalent sexism.

Gender

Main outcomes, feminization x gender heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.391*** 0.833*** 0.417*** 0.384*** 0.804*** 0.071*** 0.780***
(0.075) (0.020) (0.027) (0.027) (0.022) (0.014) (0.023)
treatment_female 0.105 -0.013 -0.009 0.129*** -0.017 0.005 0.027
(0.104) (0.029) (0.038) (0.038) (0.031) (0.020) (0.031)
male -0.027 0.013 0.052 -0.086* 0.058* 0.055** 0.021
(0.098) (0.026) (0.035) (0.033) (0.027) (0.020) (0.029)
treatment_female × male -0.138 -0.003 0.004 0.008 -0.016 0.006 -0.011
(0.137) (0.037) (0.049) (0.048) (0.038) (0.029) (0.040)
R2 0.00 0.00 0.00 0.03 0.01 0.01 0.00
Num. obs. 1694 1694 1694 1694 1694 1694 1694
(Intercept) 0.290*** 0.453*** 0.467*** 0.294*** 0.540*** 0.037*** 0.494***
(0.060) (0.023) (0.023) (0.021) (0.023) (0.009) (0.023)
treatment_female 0.016 -0.004 0.007 0.086** -0.036 -0.005 -0.004
(0.085) (0.032) (0.032) (0.030) (0.032) (0.012) (0.032)
male 0.070 -0.038 0.057+ -0.032 -0.040 0.001 0.004
(0.089) (0.031) (0.032) (0.028) (0.032) (0.012) (0.032)
treatment_female × male 0.020 -0.037 -0.002 -0.004 0.017 0.003 0.027
(0.126) (0.044) (0.045) (0.042) (0.045) (0.017) (0.045)
R2 0.00 0.00 0.00 0.01 0.00 0.00 0.00
Num. obs. 2003 1990 1991 1993 1993 1986 1993
Main outcomes, victimization x gender heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.348*** 0.838*** 0.434*** 0.448*** 0.779*** 0.065*** 0.826***
(0.073) (0.020) (0.027) (0.027) (0.023) (0.013) (0.021)
treatment_victim 0.020 -0.022 -0.043 0.003 0.032 0.018 -0.064*
(0.104) (0.029) (0.038) (0.038) (0.031) (0.020) (0.031)
male -0.084 -0.008 0.030 -0.063+ 0.065* 0.068*** -0.002
(0.097) (0.026) (0.035) (0.035) (0.028) (0.020) (0.027)
treatment_victim × male -0.027 0.039 0.047 -0.042 -0.028 -0.020 0.033
(0.137) (0.037) (0.049) (0.049) (0.038) (0.029) (0.040)
R2 0.00 0.00 0.00 0.01 0.00 0.01 0.00
Num. obs. 1694 1694 1694 1694 1694 1694 1694
(Intercept) 0.295*** 0.460*** 0.469*** 0.323*** 0.491*** 0.040*** 0.484***
(0.059) (0.023) (0.023) (0.021) (0.023) (0.009) (0.023)
treatment_victim 0.006 -0.018 0.004 0.028 0.060+ -0.010 0.015
(0.084) (0.032) (0.032) (0.030) (0.032) (0.012) (0.032)
male 0.042 -0.044 0.083** -0.026 0.041 -0.004 0.042
(0.087) (0.032) (0.032) (0.029) (0.032) (0.012) (0.032)
treatment_victim × male 0.077 -0.026 -0.056 -0.018 -0.142** 0.012 -0.049
(0.126) (0.044) (0.045) (0.042) (0.045) (0.017) (0.045)
R2 0.00 0.00 0.00 0.00 0.01 0.00 0.00
Num. obs. 2003 1990 1991 1993 1993 1986 1993

Baseline climate beliefs

For the HTEs, we operationalize this as \(climate\_beliefs\_binary = 1\) if the respondent says “Moderately”, “A lot”, or “A great deal” to the following question. Other responses are coded as 0. - To what extent do you think climate change already affects or will affect your personal life negatively? Some ways climate change could affect you include irregular rains, more frequent floods, and worsening harvests that make life more expensive and more difficult.

Main outcomes, feminization x climate beliefs heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) 0.005 0.850*** 0.352*** 0.432*** 0.845*** 0.075*** 0.779***
(0.106) (0.025) (0.033) (0.034) (0.025) (0.018) (0.028)
treatment_female -0.068 -0.060 0.084+ 0.132** -0.086* -0.003 -0.005
(0.153) (0.038) (0.048) (0.049) (0.040) (0.026) (0.041)
climate_beliefs_binary -0.547*** -0.011 0.124** -0.135*** -0.009 0.038+ 0.009
(0.118) (0.029) (0.038) (0.039) (0.029) (0.022) (0.033)
treatment_female × climate_beliefs_binary 0.130 0.058 -0.118* 0.009 0.074+ 0.017 0.037
(0.169) (0.043) (0.056) (0.056) (0.045) (0.032) (0.047)
R2 0.02 0.00 0.01 0.03 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 1.108*** 0.377*** 0.514*** 0.251*** 0.366*** 0.022* 0.328***
(0.103) (0.036) (0.037) (0.032) (0.036) (0.011) (0.035)
treatment_female -0.072 -0.015 -0.001 0.094* 0.006 0.003 0.052
(0.138) (0.050) (0.051) (0.047) (0.050) (0.016) (0.049)
climate_beliefs_binary -0.956*** 0.069+ -0.021 0.032 0.188*** 0.019 0.206***
(0.114) (0.040) (0.041) (0.036) (0.040) (0.013) (0.039)
treatment_female × climate_beliefs_binary 0.096 -0.005 0.007 -0.010 -0.037 -0.008 -0.049
(0.154) (0.055) (0.057) (0.052) (0.055) (0.018) (0.055)
R2 0.06 0.00 0.00 0.01 0.02 0.00 0.02
Num. obs. 2004 1991 1992 1994 1994 1987 1994
Main outcomes, victimization x climate beliefs heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.100 0.835*** 0.376*** 0.500*** 0.825*** 0.057*** 0.804***
(0.113) (0.027) (0.035) (0.036) (0.027) (0.017) (0.029)
treatment_victim 0.138 -0.027 0.030 -0.009 -0.040 0.032 -0.052
(0.153) (0.038) (0.048) (0.050) (0.039) (0.026) (0.041)
climate_beliefs_binary -0.382** -0.003 0.097* -0.116** -0.011 0.063** 0.020
(0.124) (0.030) (0.040) (0.041) (0.031) (0.021) (0.032)
treatment_victim × climate_beliefs_binary -0.197 0.039 -0.060 -0.021 0.072 -0.033 0.012
(0.170) (0.043) (0.056) (0.056) (0.044) (0.031) (0.047)
R2 0.02 0.00 0.00 0.01 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 1.004*** 0.373*** 0.471*** 0.275*** 0.353*** 0.039** 0.358***
(0.092) (0.034) (0.035) (0.031) (0.034) (0.014) (0.034)
treatment_victim 0.143 -0.007 0.091+ 0.055 0.035 -0.034* -0.006
(0.138) (0.050) (0.051) (0.047) (0.050) (0.015) (0.049)
climate_beliefs_binary -0.867*** 0.083* 0.052 0.045 0.199*** -0.002 0.186***
(0.104) (0.038) (0.039) (0.035) (0.038) (0.015) (0.038)
treatment_victim × climate_beliefs_binary -0.090 -0.030 -0.144* -0.046 -0.061 0.036* -0.011
(0.154) (0.055) (0.057) (0.053) (0.056) (0.018) (0.055)
R2 0.06 0.00 0.00 0.00 0.02 0.00 0.02
Num. obs. 2004 1991 1992 1994 1994 1987 1994

Age

For the HTEs, we operationalize this as \(above\_median\_age = 1\) if the respondent’s age is above the median age category. Other responses are coded as 0.

Main outcomes, feminization x age heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.392*** 0.842*** 0.428*** 0.333*** 0.836*** 0.095*** 0.786***
(0.050) (0.013) (0.018) (0.017) (0.013) (0.011) (0.015)
treatment_female 0.069 -0.014 0.007 0.125*** -0.037+ 0.005 0.024
(0.071) (0.019) (0.025) (0.025) (0.020) (0.015) (0.020)
above_median_age -0.139 -0.005 0.165** -0.019 0.025 0.079+ 0.005
(0.167) (0.042) (0.056) (0.053) (0.040) (0.043) (0.047)
treatment_female × above_median_age -0.469* -0.015 -0.117 0.112 0.075 0.057 -0.006
(0.217) (0.061) (0.079) (0.077) (0.053) (0.063) (0.064)
R2 0.01 0.00 0.01 0.02 0.00 0.01 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 0.246*** 0.483*** 0.485*** 0.324*** 0.596*** 0.027*** 0.543***
(0.065) (0.024) (0.024) (0.022) (0.023) (0.008) (0.024)
treatment_female -0.060 -0.002 -0.051 0.059+ -0.062+ -0.006 0.010
(0.094) (0.034) (0.034) (0.032) (0.034) (0.010) (0.034)
above_median_age 0.143 -0.088** 0.020 -0.082** -0.137*** 0.018 -0.084**
(0.089) (0.032) (0.032) (0.029) (0.031) (0.012) (0.032)
treatment_female × above_median_age 0.144 -0.031 0.098* 0.047 0.064 0.004 0.000
(0.126) (0.045) (0.045) (0.042) (0.045) (0.016) (0.045)
R2 0.01 0.01 0.01 0.01 0.01 0.00 0.01
Num. obs. 2004 1991 1992 1994 1994 1987 1994
Main outcomes, victimization x age heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.367*** 0.835*** 0.438*** 0.405*** 0.812*** 0.092*** 0.819***
(0.050) (0.013) (0.018) (0.018) (0.014) (0.010) (0.014)
treatment_victim 0.019 0.001 -0.013 -0.020 0.011 0.011 -0.043*
(0.071) (0.019) (0.025) (0.025) (0.020) (0.015) (0.021)
above_median_age -0.316+ -0.022 0.137* 0.057 0.051 0.145** 0.006
(0.167) (0.046) (0.058) (0.059) (0.041) (0.049) (0.045)
treatment_victim × above_median_age -0.115 0.018 -0.056 -0.032 0.021 -0.070 -0.003
(0.220) (0.061) (0.080) (0.080) (0.054) (0.064) (0.064)
R2 0.01 0.00 0.00 0.00 0.00 0.01 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 0.243*** 0.516*** 0.461*** 0.345*** 0.569*** 0.030*** 0.547***
(0.062) (0.024) (0.024) (0.023) (0.024) (0.008) (0.024)
treatment_victim -0.054 -0.069* -0.002 0.014 -0.007 -0.011 0.002
(0.094) (0.034) (0.034) (0.032) (0.034) (0.010) (0.034)
above_median_age 0.132 -0.140*** 0.091** -0.063* -0.105*** 0.014 -0.074*
(0.086) (0.032) (0.032) (0.030) (0.032) (0.012) (0.032)
treatment_victim × above_median_age 0.163 0.072 -0.044 0.010 -0.001 0.011 -0.019
(0.126) (0.045) (0.045) (0.042) (0.045) (0.016) (0.045)
R2 0.01 0.01 0.01 0.00 0.01 0.00 0.01
Num. obs. 2004 1991 1992 1994 1994 1987 1994

Has children

Main outcomes, feminization x has children heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.103 0.844*** 0.385*** 0.269*** 0.806*** 0.094*** 0.728***
(0.065) (0.017) (0.023) (0.021) (0.019) (0.014) (0.021)
treatment_female -0.022 -0.033 0.037 0.126*** -0.081** 0.014 0.041
(0.091) (0.025) (0.033) (0.031) (0.028) (0.020) (0.029)
has_children -0.641*** -0.005 0.126*** 0.130*** 0.067** 0.021 0.123***
(0.093) (0.025) (0.034) (0.032) (0.025) (0.021) (0.028)
treatment_female × has_children 0.084 0.038 -0.086+ 0.023 0.111** -0.007 -0.036
(0.131) (0.036) (0.048) (0.047) (0.036) (0.030) (0.038)
R2 0.05 0.00 0.01 0.04 0.03 0.00 0.02
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 0.390*** 0.441*** 0.524*** 0.265*** 0.497*** 0.032*** 0.465***
(0.076) (0.027) (0.027) (0.024) (0.027) (0.010) (0.027)
treatment_female 0.051 0.017 -0.051 0.088* -0.039 -0.008 0.012
(0.109) (0.039) (0.039) (0.036) (0.039) (0.013) (0.039)
has_children -0.097 -0.012 -0.041 0.020 0.034 0.007 0.047
(0.094) (0.033) (0.033) (0.030) (0.033) (0.012) (0.033)
treatment_female × has_children -0.038 -0.055 0.084+ -0.005 0.017 0.006 -0.005
(0.134) (0.047) (0.048) (0.044) (0.048) (0.017) (0.048)
R2 0.00 0.00 0.00 0.01 0.00 0.00 0.00
Num. obs. 2004 1991 1992 1994 1994 1987 1994
Main outcomes, victimization x has children heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.084 0.832*** 0.410*** 0.339*** 0.769*** 0.108*** 0.788***
(0.064) (0.017) (0.023) (0.022) (0.020) (0.014) (0.019)
treatment_victim -0.061 -0.008 -0.014 -0.013 -0.007 -0.015 -0.081**
(0.091) (0.025) (0.033) (0.031) (0.028) (0.020) (0.029)
has_children -0.677*** 0.002 0.088** 0.155*** 0.103*** -0.005 0.068**
(0.093) (0.026) (0.034) (0.033) (0.026) (0.021) (0.026)
treatment_victim × has_children 0.157 0.023 -0.011 -0.026 0.040 0.044 0.075*
(0.131) (0.036) (0.048) (0.047) (0.036) (0.030) (0.038)
R2 0.05 0.00 0.01 0.02 0.03 0.00 0.02
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 0.411*** 0.454*** 0.491*** 0.319*** 0.466*** 0.031** 0.454***
(0.076) (0.028) (0.028) (0.026) (0.028) (0.010) (0.028)
treatment_victim 0.009 -0.009 0.015 -0.022 0.023 -0.004 0.033
(0.109) (0.039) (0.039) (0.036) (0.039) (0.013) (0.039)
has_children -0.140 -0.023 0.032 -0.013 0.067* 0.010 0.077*
(0.092) (0.034) (0.034) (0.031) (0.034) (0.012) (0.034)
treatment_victim × has_children 0.049 -0.032 -0.062 0.062 -0.050 -0.001 -0.064
(0.134) (0.047) (0.048) (0.044) (0.048) (0.017) (0.048)
R2 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Num. obs. 2004 1991 1992 1994 1994 1987 1994

Socioeconomic status

For the HTEs, we operationalize this as \(above\_median\_edu = 1\) if the respondent’s education is above the median level, 0 otherwise.

##                                                     
##                                                         0    1
##   Informal education only (including Koranic school)   43    0
##   No formal education                                  54    0
##   Post-university                                       0  222
##   Primary school                                       75    0
##   Secondary school                                   1274    0
##   University                                         2063    0
Main outcomes, feminization x SES heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.402*** 0.839*** 0.446*** 0.326*** 0.837*** 0.101*** 0.791***
(0.049) (0.013) (0.017) (0.016) (0.013) (0.011) (0.014)
treatment_female 0.033 -0.010 -0.015 0.147*** -0.032+ 0.012 0.018
(0.069) (0.018) (0.025) (0.024) (0.019) (0.015) (0.020)
above_median_edu -0.074 0.044 -0.028 0.092 0.024 0.038 -0.093
(0.205) (0.051) (0.078) (0.078) (0.055) (0.055) (0.072)
treatment_female × above_median_edu -0.259 -0.101 0.210+ -0.202+ 0.058 -0.015 0.102
(0.306) (0.083) (0.109) (0.108) (0.075) (0.076) (0.094)
R2 0.00 0.00 0.00 0.02 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 0.347*** 0.429*** 0.488*** 0.277*** 0.511*** 0.035*** 0.484***
(0.046) (0.016) (0.016) (0.015) (0.016) (0.006) (0.016)
treatment_female 0.019 -0.014 0.003 0.084*** -0.019 -0.002 0.018
(0.065) (0.023) (0.023) (0.022) (0.023) (0.008) (0.023)
above_median_edu -0.318+ 0.063 0.124* 0.006 0.121* 0.024 0.172**
(0.185) (0.064) (0.062) (0.057) (0.061) (0.030) (0.061)
treatment_female × above_median_edu 0.075 -0.090 0.027 0.005 -0.121 -0.028 -0.138
(0.266) (0.089) (0.087) (0.084) (0.088) (0.037) (0.088)
R2 0.00 0.00 0.00 0.01 0.00 0.00 0.00
Num. obs. 2004 1991 1992 1994 1994 1987 1994
Main outcomes, victimization x SES heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) -0.383*** 0.829*** 0.447*** 0.413*** 0.812*** 0.105*** 0.819***
(0.049) (0.013) (0.017) (0.017) (0.014) (0.011) (0.014)
treatment_victim -0.004 0.011 -0.017 -0.025 0.018 0.005 -0.037+
(0.069) (0.018) (0.025) (0.024) (0.019) (0.015) (0.020)
above_median_edu -0.229 0.067 0.074 -0.038 0.084+ 0.020 0.014
(0.200) (0.046) (0.075) (0.073) (0.047) (0.049) (0.056)
treatment_victim × above_median_edu 0.052 -0.163+ 0.009 0.061 -0.068 0.024 -0.129
(0.312) (0.086) (0.112) (0.109) (0.076) (0.077) (0.096)
R2 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 0.342*** 0.434*** 0.501*** 0.305*** 0.503*** 0.036*** 0.498***
(0.045) (0.016) (0.017) (0.015) (0.017) (0.006) (0.017)
treatment_victim 0.029 -0.024 -0.022 0.028 -0.002 -0.003 -0.009
(0.065) (0.023) (0.023) (0.022) (0.023) (0.008) (0.023)
above_median_edu -0.320* 0.053 0.140* 0.067 0.105+ 0.015 0.091
(0.158) (0.059) (0.057) (0.057) (0.058) (0.026) (0.058)
treatment_victim × above_median_edu 0.101 -0.089 -0.012 -0.132 -0.106 -0.012 0.027
(0.280) (0.090) (0.089) (0.084) (0.090) (0.036) (0.090)
R2 0.00 0.00 0.01 0.00 0.00 0.00 0.00
Num. obs. 2004 1991 1992 1994 1994 1987 1994

Ambivalent sexism

For the HTEs, we use the \(ambivalent\_sexism\_index\).

Main outcomes, feminization x ambivalent sexism heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) 1.162*** 0.491*** 0.787*** 0.298** 0.787*** -0.015 0.591***
(0.289) (0.080) (0.097) (0.094) (0.068) (0.056) (0.078)
treatment_female 0.181 0.076 -0.370** -0.026 -0.106 0.073 0.224*
(0.399) (0.111) (0.133) (0.133) (0.104) (0.078) (0.104)
ambivalent_sexism_index -0.434*** 0.097*** -0.095*** 0.009 0.014 0.033* 0.054**
(0.079) (0.021) (0.026) (0.026) (0.018) (0.016) (0.021)
treatment_female × ambivalent_sexism_index -0.042 -0.026 0.101** 0.045 0.021 -0.017 -0.055*
(0.108) (0.029) (0.036) (0.036) (0.028) (0.022) (0.028)
R2 0.05 0.02 0.01 0.02 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 1.462*** 0.345*** 0.664*** 0.019 0.225** 0.038 0.308***
(0.252) (0.086) (0.085) (0.075) (0.086) (0.035) (0.085)
treatment_female 0.067 0.019 -0.003 -0.087 0.058 -0.036 0.096
(0.370) (0.122) (0.122) (0.111) (0.122) (0.048) (0.121)
ambivalent_sexism_index -0.339*** 0.026 -0.050* 0.077*** 0.088*** -0.000 0.056*
(0.075) (0.025) (0.025) (0.023) (0.025) (0.010) (0.025)
treatment_female × ambivalent_sexism_index -0.013 -0.012 0.002 0.052 -0.025 0.010 -0.026
(0.110) (0.036) (0.036) (0.033) (0.036) (0.014) (0.036)
R2 0.02 0.00 0.00 0.03 0.01 0.00 0.00
Num. obs. 2004 1991 1992 1994 1994 1987 1994
Main outcomes, victimization x ambivalent sexism heterogeneous effects
Political mobilization index Preference: poor countries vs. France Preference: adaptation vs. emergency relief Preference: gender-based vs. general Willingness to sign petition Clicks: adaptation and mitigation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Note: Robust SEs.
(Intercept) 1.289*** 0.495*** 0.586*** 0.265** 0.782*** 0.048 0.720***
(0.273) (0.076) (0.092) (0.094) (0.074) (0.052) (0.067)
treatment_victim -0.069 0.074 0.020 0.029 -0.103 -0.053 -0.021
(0.399) (0.112) (0.133) (0.134) (0.105) (0.078) (0.105)
ambivalent_sexism_index -0.464*** 0.093*** -0.037 0.040 0.009 0.016 0.027
(0.074) (0.020) (0.025) (0.025) (0.020) (0.014) (0.018)
treatment_victim × ambivalent_sexism_index 0.015 -0.019 -0.011 -0.014 0.033 0.016 -0.006
(0.108) (0.029) (0.036) (0.036) (0.028) (0.022) (0.028)
R2 0.05 0.02 0.00 0.00 0.00 0.00 0.00
Num. obs. 1710 1710 1710 1710 1710 1710 1710
(Intercept) 1.143*** 0.389*** 0.607*** -0.091 0.138 0.025 0.295**
(0.271) (0.092) (0.091) (0.081) (0.091) (0.029) (0.090)
treatment_victim 0.637+ -0.059 0.103 0.121 0.211+ -0.009 0.111
(0.370) (0.123) (0.122) (0.112) (0.123) (0.047) (0.122)
ambivalent_sexism_index -0.245** 0.015 -0.028 0.119*** 0.111*** 0.004 0.062*
(0.080) (0.027) (0.027) (0.024) (0.026) (0.009) (0.026)
treatment_victim × ambivalent_sexism_index -0.183+ 0.009 -0.039 -0.029 -0.065+ 0.001 -0.035
(0.110) (0.036) (0.036) (0.033) (0.036) (0.014) (0.036)
R2 0.03 0.00 0.01 0.02 0.01 0.00 0.00
Num. obs. 2004 1991 1992 1994 1994 1987 1994

Analysis of open text outcomes

We will come back to this after soliciting feedback on how to analyze the responses. For now, we randomly select 50 responses from each treatment category and compare them.

Comparing female to male treatments

Random Emotional Responses by Sample and Treatment
French - Male treatment French - Female treatment Ivorian - Male treatment Ivorian - Female treatment
Tristesse Poignant De la pitié J’ai ressenti en voyant cette image de la peine, de la pitié et de la révolte qui m’a sensibilisé sur l’importance de prendre soin de notre environnement pour éviter les catastrophes naturelles subies dans le monde entier.
Du fait du changement climatique le continent africain est première victime et acteur de solutions au problème majeur du 21 ème siècle Me fait pitié inquiétude face au changement climatique J’ai eu de la peine
le désespoir De l’injustice et de l’inégalité Je compatis à là douleur de cette personne Je senti une tristesse inimaginable. C’est triste d’avoir une femme souffre sans que quelqu’un lui vienne en aide.
De la tristesse Une enième expression du wokisme debilitant. Empathie et inquiétude De la pitié et de la compassion pour cette femme
Empathie face au courage de cette personne de la tristesse Sorrow and regret une femme victime du danger du réchaufement climatique (inondation)qui n’est pas secourue et qui se sauve seule. je ressens vraiment les dangers du rechaufement climatique, donc il va falloir que chaque personne y comprenne et participe à la sensibilisation de retablisement de la faune et faure
La réalité frappante. Que l’Afrique est concerné et surtout les pays pauvres Rien Le changement climatique est pour la plupart du temps plus fréquent dans les pays moins démuni car ils ont besoin d’aide La tristesse et désolation
un peu de tristesse face au regard de cette personne qui a tout perdu qu’il faut agir pour le climat J’ai ressenti de la détresse en voyant les yeux de cet homme et de l’impuissance car n’étant pas à mesure de l’aider immédiatement si la situation était vraie. De la pitié, de la compassion et une forte volonté de la tirer de cet endroit
Déboussolée, l’Afrique est connue pour manque d’eau et sur l’image il y en avait énormément Solidarité, compréhension De la peine Touchée
un sentiment de malaise Je suis sensible à cette personne J’ai ressentir de la peine pour lui et même temps pour nous autre parents De la pitié
J’ai ressenti de la peine et de la tristesse LA FEMME EST VICTIME AVANT TOUT DE LA PAUVRETE ET DES INEGALITES. LE CHANGEMENT CLIMATIQUE SUPPOSE NE FAIT QU’AJOUTER A SES DIFFICULTES QUOTIDIENNES. DANS LA REGION DU SAHEL LES EFFETS DE CE CHANGEMENT CLIMATIQUE RESTENT ASSEZ PEU PERCEPTIBLES. Découragement mais en agissant maintenant je pense que l’on peux changer les choses Il est important de sensibiliser sur le changement climatique et je trouve ça brave que les femmes rentre au coeur de ça
C’est triste de voir ça Colère face à des conditions de vie indignes C’est un phénomène à combattre pour protéger la génération future Je me suis sentie un peu triste
Malheureusement, ce genre de situation va se multiplier Que les femmes sont plus touchées par le changement climatique de la peine J’ai vu que la lutte contre le changement climatique est un sujet à prendre au sérieux si l’on ne veut pas être victime
PAS GRAND CHOSE Qu’il faut se mobilisé pour aider les autres dans nos geste quotidien J’ai ressenti la tristesse la pitié. La maltraitance des personnes De la tristesse
Rire UNE FEMME QUI LEVE UNE PANCARTE POUR LUTTER EVTER QUE NOTRE PLANE EXPLOSE EN PLUS CETTE PERSONNE VIE DANS UN PAYS PAUVRE De la compassion, en voyant mon frère africain souffrir à cause du réchauffement climatique de la tristesse et de l’empathie
de la tristesse de la fierté pour cette femme qui se bat pour une cause noble De la tristesse j ai senti la stupeur la déception
Tristesse Empathie De la tristesse J’ai ressenti du chagrin pour tout ceux qui subissent les effets du réchauffement climatique
Très triste De la tristesse et un cliché J’ai ressenti de la compassion mêlée à de la tristesse quand j’ai vu l’homme et les animaux en proie à l’inondation. Douleur et regret
Pauvreté L’envie de l’aider La compassion De la peine
De la peine, de la peur aussi car c’est ce qui peut arriver chez nous. De la peine pour cette femme Bizarre De la peine
Qu ils faut réagir pour le climat De la compassion. Le peur Désolé
Qu’il faut du changement rapidement Une personne triste portant un seau sur la tête TRISTE ET DECOURAGE ET JE ME SUIS SENTIR COUPABLE AUSSI Ça m’a vraiment rendu triste de voir la femme africaine, être victime de l’ignorance humaine en général.
De la tristesse et un sentiment d’impuissance. De la compassion J’ai ressenti sur cette image un ouff de soulagement et un motivations à participer au action pour lutter contre le réchauffement climatique. Douleur et regret
De la tristesse et de la révolte Que tous les pays sont touchés par le changement climatique et qu’il est temps d’agir. Une grande tristesse et un grand désarroi De la pène
De la peur et de la tristesse Inpeu pauvre je me suis sentie blessé La tristesse
Très bien Injustice J’ai ressenti la pitié De la tristesse car nous devons nous bouger afin que les choses changent
De la pauvreté De la peine A bit nervous as if it wants to rain Conscious
Du mal être de la tristesse et de la compassion de la sympathie J’ai vu que la femme vous que les catastrophes climatique saisse
gêne et suprise Je n ai rien ressenti Un regret Plutôt triste de voir de si belles femmes souffrir
Pas plus cvomp De l’espoir Une rage et une tristesse pour cette personne
Tristesse De la tristesse La Tristesse De l’empathie
Questionnement Rien L’image que j’ai vue étais véritablement un message de sensibilisation contre la lutte du changements climatiques nous devons prendre soin de notre planète pour protéger touts les habitants qui y vivent J’ai éprouvé de la compassion
de la tristesse Rien de particulier Une tristesse Un choque
De la pitié de la peine De la peine car j’en ai été victime aussi et cela m’a rappelé mon cas. De la compassion pour la personne, et en même de l’envie de participer à la lutte contre le changement climatique
Le changement climatique est une réalité Triste et qu’il faut se mobiliser rapidement contre ce phénomène Le besoin d’aide Un besoin d’aide
De la tristesse et l’envie d’aider cette pauvre personne qui se trouvait dans une situation précaire Ça m’a fait réfléchir à ceux qui ont soutenu la manifestation triste La tristesse et le fait que l’on doit se mobiliser afin de lutter contre ce fléau
de la compassion Nnnn la tristesse de voir une personne victime du changement climatique. J’ai ressenti de la peine pour ceux qui souffrent contre le changement climatique
De la pitié Rien Une profonde tristesse et un désir de changement It made me feel sad
Rien de particulier Aucune idée la tristesse Attristée
Pas grand chose De la compassion La compation Une empathie
La tristesse De la pitié J’ai un compassion L’urgence de la dit
De la peine de la peine Empathie et inquiétude J’ai ressenti de la tristesse. Beaucoup de douleurs au niveau de la gente féminine
Rien de spécial Que cette femme cherche a aidé pour le changement climatique De l’empathie, de la tristesse et l’envie de vouloir aider Une tristesse marquante
de la peur La difficulté d’être sur un sol ferme à cause des inondations lutter pour avancer Tristesse et besoin d’aider J’étais un peu triste car je ne trouve pas normal que nous souffrons de cette manière
ce n’ai pas un problème de réchauffement climatique ,c’est la nature qui se transforme peut être il y a des millions d’année c’était la mer !! Intéressant Tristesse homme La lutte contre le changement climatique nous concerne tous. Je me sens donc engagée dans ce combat.
De la tristesse De la tristesse j’avais de la peine pour la personne Une image désolante, empreinte de tristesse — le reflet d’une douleur que nul être humain sur cette terre ne devrait endurer, quelle que soit sa couleur, sa religion ou son origine.
Qu’il faut aider la personne il faut agir pour arreter cela J’ai senti qu’il fallait absolument faire quelque chose au plus vite sinon, nous courrons à notre perte. Douleur et regret
Envie de changer les choses Une femme très triste J’ai ressenti une peine pour cette personne cela m’a rappelé les inondations pendant la saison pluvieuse dans mon pays. De la compassion de la solidarité de l’empathie
De la compassion De l’envie d’aider la difficile vie d’une victime du changement climatique De la compassion
Il avait l’air malheureux De l’empathie La lutte constante contre le changement climatique J’ai ressenti de la peine même si c’était une image
Ras L’IMAGE MET LA FEMME AFRICAINE EN PROMOTION POUR LUTTER CONTRE LE CHANGEMENT CLIMATIQUE. OU SONT LES HOMMES? Tristesse J’ai ressenti de la peine pour la femme qui a été victime des conséquences du changement climatique

Comparing victim to agent treatments

Random Emotional Responses by Sample and Treatment
French - Agent treatment French - Victim treatment Ivorian - Agent treatment Ivorian - Victim treatment
Personne démuni face aux problémes liés au changement climatique alors qu’il n’en ai pas responsable De la peine De La Peine De la peur
De la peine de voir que certains sont en danger acause des activités humaines Triste de voir les difficultés rencontrées Motiver à lutter contre le changement climatique Une grande colère un désespoir et une impuissance de ma part a aider mon frère africain
Choquer Tristesse Tristesse Veut l’aider
De la colère face au changement climatique principalement du à l’être humain. De la tristesse et de sa se voit qu’il ont pris l’habitude de faire leur travail tous les jours dans ses conditions De la tristesse LA DESOLATION
De la joie, de ’a haine et beaucoup de quiétude car cet homme est engagé Rien de bien particulier De la peine pour cette dernière qui à cause de l’inondation se retrouve presqu’emporter par l’eau Triste 😥
Pour le climat It s strange De la compassion De la compassion.
La pauvreté Beaucoup de tristesse. Ça devrait plus exister à notre époque. Je suis outré. Une conscience et grande sensibilisation à engager pour sauver notre planète Ce que j’ai vue , une femme souffrent et l’eau l’enveillir. Il faut qu’ont vienne on son secours a cause de la situation climatique
une image réaliste Beaucoup de tristesse et de compassion j’ai ressentis de la sensibilité Se sentir très pathétique
Rien Tristesse J’ai vu la souffrance Une tristesse
cela me desespert cat personne en prend consciance Que c’est une femme avec pleins de courage qui va cherche de l’eau sans l’aide de personne UN PINCEMENT AU COEUR Empathie et inquiétude
Émouvant la peine PAS GRANDE CHOSE Je me suis senti indigné qu’une tel chose arrive encore dans nos pays
Compassion its feel ike women tired from un fair rules and holding everything by her self J’ai ressenti que le changement climatique est un danger à venir donc il est temps pour d’agir. Jai ressentis de la peine
C’est les pays et les communites pauvres qui souffrent des effets de changement climatique alors que les plus riches et qui sont là cause de ce changement n’assument pas leurs responsabilités La faute du changement climatique et la responsabilité des pays les plus polluants comme les États-Unis. Triste vraiment j’ai ressenti un mal
De l inquiétude Cela. Est grave que les politiques du monde ce mobilise pas contre le changement climatique La pitié pour ces gens Une empathie me donne un sentiment de pitié
De la tristesse et de l’impuissance face a la situation. De la pitié Enthousiaste De la pitié pour cette dame, comme pour toutes celles qui traversent seules des moments difficiles
De la compassion pour cet homme qui à l’air si triste. Aucune idée J’avais mal au coeur de voir cet homme Beaucoup de réflexion
De la peine de la tristesse rien J’ai ressentis une empathie pour cette dame
Triste et remonté It made me feel kinda sad. That we take a lot of things granted in life. We are lucky that we are in our warm blankets. And that we should rise the voice for them and support them. We should raise awareness about it and help them. In rural areas, floods wash away farmland, reducing food production and threatening livelihoods. While Africa contributes the least to global greenhouse gas emissions, it suffers some of the most damaging effects. And thats so sad. Urgent international support and investment in adaptation strategies are essential to help African nations build resilience against climate-related floods. Helping African countries adapt is not just fair—it’s necessary for global climate justice. De la détermination à m’investir pour la sauvegarde du climat De la pitié, de la compassion et une forte volonté de la tirer de cet endroit
Une inquiétude pour le climat La misère Je me suis senti triste en voyant la femme tenant une pancarte pour la lutte contre le changement climatique. Les gaz à effet de serre provoque aussi ces changement climatiques Tristesse
Rien De la tristesse et de la compation J’ai eu mal au cœur de voir le homme dans eau qui à arrivée à son cour Mal au cœur
Beaucoup de desolation l impuissance J’ai juste ressenti une tristesse, en voyant les choses changées de manière brusque. Le changé climatique est un phénomène très néfaste pour l’humanité tout entière Sa me rend triste
Il faut préserver la nature Rien en particulier j’ai ressenti une profonde tristesse en voyant l’image car les paysans, les désoeuvrés sont les personnes les plus touchées par les effets du changement climatique. les zones rurales ne peuvent lutter contre la nature Je sens que il souffre sa femme ne prend pas soin de lui
Desastte De l’ampatie L’image transmet un puissant message d’urgence climatique et de solidarité. Elle met en lumière le rôle essentiel des femmes des pays pauvres dans la lutte contre le changement climatique, tout en suscitant de l’admiration pour leur courage et un appel à l’action. Cela suscite de la pitié et un certain découragement envers les populations, car les autorités déploient peu d’efforts pour leur venir en aide. Il est essentiel d’anticiper les actions d’assistance afin de mieux soutenir les populations en difficulté.
Impressionnant De la tristesse Une envie de lutter contre la détérioration du climat Rien du tout
De la tristesse Il avait besoin d’aide Détresse La compassion
La peine Tristesse Douleur et regret Douleur et regret
Rien Les africains avec beaucoup de ressources naturelles et vivent dans la misère Une joie J’ai retenu que le changement climatique peut être dangereux pour des personnes pauvres
De l’empathie Il est vraiment nécessaire de faire attention à notre planete J’ai vu un homme engagé dans la lutte De la pitié
Le changement climatique est une réalité de la tristesse, de la peine pour cette personne qui à tout perdu De la tristesse Oui
De la compassion du soutien La realité du changement climatique qui n’est pas une vue de l’esprit Émue De la tristesse
rien du tout sur le sujet De la tristesse Bizarre choc
Une certaine émotion et compation pour cette femme Empathie La peine pour l’Afrique J’ai ressenti de la pitié et de la désolation.
les femmes ont le pouvoir contre le changement climatique de la compassion Inquiète Du chagrin de la compassion
La misere De la peine De la tristesse pour toute ces femmes qui luttent pour un lendemain meilleur Triste
DE LA TRISTESSE De la compassion pour cette personne J’ai ressenti de la peine et de la tristesse en voyant que les actions de chacun de nous impact négativement les personnes déjà en difficultées. UUNE TRISTESSE, CAR CE QUI ARRIVE EST UN PHENOMENE MONDIAL, QUI DOIT ETRE PRIS EN COMPTE PAR TOUT LE MONDE AFIN D’ERADIQUER CE FLEAU.
Une femme tenant une pancarte pour sauver le climat Je ressent un changement de vision du monde Un état de choc…une tristesse et un sursaut I feel sad
L’urgence de lutter conte les changements climatiques pour les pays pauvres Agréable et génial Une véritable motivation étant prouver comme une expérience positive Rien du tout
un combattant Dans certains pays les femmes souffrent beaucoup R Une femme vulnérable du fait du changement climatique
Les pays pauvres subissent le plus et se battent le plus contre le changement climatique De la pauvreté Un sentiment de tristesse De la.compation pour l’humanité
Bizarre un africain inondé ça interpelle tristesse et empathie J’ai retenu qu’on doit protéger l’environnement pour ne pas affecter le climat De la pitié et de la compassion
Beaucoup de peine, impossible de venir en aide ,c’est triste De la tristesse Empathie et inquiétude La comparaison
Envie de l aider Ce sont toujours les pauvres qui trinquent et qui sont les premiers victimes du dérèglement climatique It’s make me feel sad to know the gravity of the climat situation caused by human actions. That mean we all need to take position for that and look for a real solution that will involve everybody without restrictions. Sad
de la tristesse La tristesses L’empathie Aider les femmes victimes du changement climatique
Questionnement ? Jai été plus attiré par comment était placé les différents éléments sur l’image , apparaît être de L’IA De la tristesse le changement climatique a un effet negatif sur la vie de l’homme J’ai eu de la peine pour la dame qui apparemment cherchait à sauvé sa vie
L’urgence de prendre en compte les problématiques du changement climatique et d’aider ceux qui le subissent par des actions positives et responsables Tristesse J’ai eu l’envie d’être parmi ceux qui veulent lutter contre le changement climatique dans de nombreux pays pauvre Je ne pense pas que ça soit les femmes pauvres qui sont plus touchées pendant le changement climatique
De la peine agréable Tristesse De la compassion
Du courage Rien Rien de spécial De la compassion et de la pitié
je pense qu il faut en faire plus pour les années a venir pour le changement climatique et proteger nos agricultures Uncomfortable and angry Compassion à la communauté La destruction des biens et personnes L’abandon et le manque de solidarité RIEN
Les problèmes liés aux changements climatiques. Tristesse Belle image pour lutter contre le changement climatique Une grande tristesse parce le changement climatique a plusieurs effets néfaste sur l’environnement
Plus grand-chose avec le gouvernement qu’on a n’a pu n’a plus grand-chose à es Tristesse J’étais bouleversé Blessé

Complier average causal effects.

M1.

Ivorian sample French sample Pooled sample
M1, CACEs
(1) (2) (3)
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Each model is an instrumental variables regression of the political mobilization index outcome, with the instrument being an indicator for being assigned to the female condition and the endogenous variable being whether or not the respondent identified the person in the image as female. Unadjusted models presented.
(Intercept) -0.412*** 0.321*** -0.015
(0.053) (0.055) (0.039)
fit_gender_compliance_identified_as_woman 0.024 0.031 0.024
(0.080) (0.081) (0.059)
Num.Obs. 1702 1988 3690
R2 -0.000 -0.000 0.000
Log.Lik. -2968.794 -3506.293 -6598.199
Wald (x_endo_1) 4123.415 3213.004 7082.283

M2.

Ivorian sample French sample Pooled sample
M2, CACEs
(1) (2) (3)
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Each model is an instrumental variables regression of the political mobilization index outcome, with the instrument being an indicator for being assigned to the victim condition and the endogenous variable being whether or not the respondent identified the person in the image as a victim. Unadjusted models presented.
(Intercept) -0.395*** 0.238* -0.057
(0.092) (0.109) (0.073)
fit_victim_compliance_identified_as_victim -0.028 0.114 0.048
(0.131) (0.158) (0.105)
Num.Obs. 1670 1911 3581
R2 0.001 -0.000 -0.001
Log.Lik. -2908.524 -3363.505 -6390.662
Wald (x_endo_1) 691.601 435.895 1087.295

M3.

Ivorian sample French sample Pooled sample
M3, CACEs
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Each model is an instrumental variables regression of the support for climate adaptation outcomes, with the instrument being an indicator for being assigned to the female condition and the endogenous variable being whether or not the respondent identified the person in the image as a woman. Unadjusted models presented.
(Intercept) 0.843*** -0.412*** 0.315*** 0.841*** 0.103*** 0.784*** 0.435*** 0.321*** 0.258*** 0.525*** 0.038*** 0.495*** 0.623*** -0.015 0.283*** 0.670*** 0.068*** 0.627***
(0.014) (0.053) (0.019) (0.015) (0.012) (0.015) (0.019) (0.055) (0.018) (0.019) (0.007) (0.019) (0.013) (0.039) (0.013) (0.013) (0.007) (0.013)
fit_gender_compliance_identified_as_woman -0.017 0.024 0.163*** -0.035 0.012 0.028 -0.023 0.031 0.112*** -0.035 -0.005 0.012 -0.018 0.024 0.137*** -0.033+ 0.004 0.021
(0.021) (0.080) (0.028) (0.022) (0.018) (0.023) (0.028) (0.081) (0.027) (0.029) (0.011) (0.029) (0.020) (0.059) (0.019) (0.019) (0.010) (0.020)
Num.Obs. 1702 1702 1702 1702 1702 1702 1975 1988 1978 1978 1971 1978 3677 3690 3680 3680 3673 3680
R2 -0.000 -0.000 0.009 0.001 0.001 -0.001 0.001 -0.000 0.013 0.001 0.000 -0.000 0.001 0.000 0.010 0.002 0.000 -0.001
Log.Lik. -731.197 -2968.794 -1192.432 -774.017 -432.061 -862.883 -1408.425 -3506.293 -1285.063 -1434.579 528.376 -1435.771 -2570.480 -6598.199 -2493.405 -2487.935 -187.364 -2526.168
Wald (x_endo_1) 4123.415 4123.415 4123.415 4123.415 4123.415 4123.415 3229.841 3213.004 3240.902 3241.846 3214.639 3241.379 7108.622 7082.283 7121.717 7122.438 7090.811 7122.081

M4.

Ivorian sample French sample Pooled sample
M4, CACEs
Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay Prefers adaptation finance in poor countries vs. France Prefers adaptation finance vs. emergency relief Prefers gender-based adaptation finance vs. general programming Willingness to sign petition Clicks to learn more about climate adaptation Willingness to pay
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
Each model is an instrumental variables regression of the support for climate adaptation outcomes, with the instrument being an indicator for being assigned to the victim condition and the endogenous variable being whether or not the respondent identified the person in the image as a victim. Unadjusted models presented.
(Intercept) 0.837*** -0.395*** 0.428*** 0.805*** 0.103*** 0.854*** 0.480*** 0.238* 0.297*** 0.526*** 0.042** 0.520*** 0.646*** -0.057 0.362*** 0.657*** 0.071*** 0.681***
(0.025) (0.092) (0.033) (0.025) (0.021) (0.027) (0.038) (0.109) (0.036) (0.039) (0.014) (0.039) (0.025) (0.073) (0.024) (0.024) (0.013) (0.024)
fit_victim_compliance_identified_as_victim -0.001 -0.028 -0.041 0.031 0.009 -0.087* -0.081 0.114 0.037 -0.013 -0.010 -0.010 -0.042 0.048 -0.004 0.008 -0.001 -0.053
(0.035) (0.131) (0.047) (0.036) (0.030) (0.038) (0.056) (0.158) (0.052) (0.056) (0.021) (0.056) (0.035) (0.105) (0.035) (0.034) (0.019) (0.035)
Num.Obs. 1670 1670 1670 1670 1670 1670 1900 1911 1902 1902 1896 1902 3570 3581 3572 3572 3566 3572
R2 -0.000 0.001 0.001 -0.002 -0.001 -0.006 -0.004 -0.000 -0.005 0.000 -0.001 0.000 -0.001 -0.001 0.000 -0.000 0.000 -0.001
Log.Lik. -710.796 -2908.524 -1178.035 -754.588 -423.015 -851.660 -1362.166 -3363.505 -1255.514 -1378.771 498.058 -1379.702 -2491.018 -6390.662 -2443.789 -2396.285 -191.556 -2434.355
Wald (x_endo_1) 691.601 691.601 691.601 691.601 691.601 691.601 436.287 435.895 442.011 443.324 442.149 442.84 1088.548 1087.295 1095.612 1097.292 1096.165 1096.765