Climate Attitudes and State Climate Policies in the United States

Author

Jillian W. Reynolds

Published

June 10, 2025

1 Sample for Analysis

1.1 Attitudes

Variable n
WARMUS 6,311  
WARMIMP 6,312  
WARMDO 6,272  
REGGREEN 6,308  
FSENV 6,310  

1.2 States

State no_SD_vars removed final_n
CA 644 66 578
TX 521 44 477
FL 432 44 388
NY 348 38 310
PA 304 28 276
IL 294 21 273
OH 280 24 256
MI 254 28 226
NC 234 21 213
GA 204 25 179
WI 175 13 162
IN 177 16 161
VA 172 12 160
WA 182 22 160
MA 171 18 153
NJ 167 14 153
MN 157 11 146
AZ 151 10 141
MD 160 20 140
CO 153 14 139
TN 151 17 134
MO 142 11 131
SC 116 13 103
KY 111 13 98
AL 101 6 95
OR 98 11 87
OK 93 8 85
KS 92 9 83
LA 86 6 80
UT 74 6 68
CT 73 7 66
MS 68 6 62
ID 64 8 56
AR 55 4 51
IA 57 6 51
NE 46 1 45
NV 52 7 45
NM 48 5 43
WV 42 3 39
NH 41 6 35
ME 29 2 27
HI 27 3 24
ND 26 4 22
MT 20 0 20
RI 19 1 18
SD 18 1 17
VT 21 6 15
DE 13 2 11
WY 12 1 11
AK 6 1 5
min — 6 0 5
max — 644 66 578
sum — 6981 663 6318

2 Policies

Enacted and Partially Enacted Policies

2.1 Counts

Figure 1
rank state enacted partially_enacted total in_progress not_enacted
1 CA 47 3 50 0 12
2 CO 46 4 50 0 12
3 MA 45 3 48 2 12
4 NY 44 3 47 0 15
5 MD 38 3 41 3 18
6 WA 38 2 40 0 22
7 OR 36 4 40 1 21
8 MN 34 4 38 1 23
9 NJ 32 3 35 1 26
10 RI 31 4 35 1 26
11 CT 28 4 32 2 28
12 ME 26 5 31 0 31
13 VT 26 4 30 2 30
14 NM 25 4 29 1 32
15 DE 23 5 28 1 33
16 NC 23 5 28 0 34
17 IL 22 5 27 0 35
18 PA 21 5 26 0 36
19 HI 20 4 24 2 36
20 VA 20 4 24 1 37
21 MI 21 2 23 1 38
22 NV 18 5 23 0 39
23 NH 16 3 19 0 43
24 WI 13 4 17 3 42
25 LA 10 3 13 0 49
26 IA 9 4 13 0 49
27 TX 10 2 12 0 50
28 UT 8 4 12 0 50
29 AZ 7 4 11 0 51
30 MT 6 4 10 0 52
31 OH 6 4 10 0 52
32 OK 6 4 10 0 52
33 MO 5 5 10 0 52
34 FL 6 3 9 0 53
35 SC 6 3 9 0 53
36 IN 5 4 9 0 53
37 KY 5 4 9 0 53
38 AR 5 3 8 0 54
39 AK 4 4 8 0 54
40 GA 4 4 8 0 54
41 NE 4 4 8 0 54
42 TN 4 3 7 0 55
43 WV 3 4 7 0 55
44 AL 4 2 6 0 56
45 ND 2 4 6 0 56
46 SD 3 2 5 0 57
47 ID 2 3 5 1 56
48 KS 1 4 5 0 57
49 MS 1 4 5 0 57
50 WY 1 4 5 0 57
Summary Statistics
stat enacted partially_enacted total in_progress not_enacted
min  1     2      5     0     12   
max 47     5     50     3     57   
median 10     4     13     0     49   
mean 16.4   3.7   20.1   0.46  41.44
sd 14.055 0.839 14.047 0.813 14.41

2.2 Distributions

quantiles_q25 quantiles_q50 quantiles_q75
10 23 40

2.3 Means

variable mean sd
enacted 16.4  14.055
in_progress  0.46  0.813
partially_enacted  3.7   0.839
not_enacted 41.44 14.41 
policies 20.1  14.047

3 Attitudes

3.1 Distributions

3.1.1 Individuals’ Attitudes

variable quantile_q25 quantile_q50 quantile_q75
WARMUS 3   4    5  
WARMIMP 2   3    5  
WARMDO 3       4.333 5  
REGGREEN 3       4.333 5  
FSENV 3   4    5  

3.1.2 States’ Attitudes

3.2 Means

3.2.1 Individuals’ Attitudes

variable mean mean_se mean_low mean_upp sd
WARMUS 3.526 0.027 3.472 3.58  1.331
WARMIMP 3.313 0.029 3.256 3.37  1.334
WARMDO 3.841 0.024 3.795 3.888 1.146
REGGREEN 3.763 0.026 3.712 3.814 1.225
FSENV 3.913 0.023 3.868 3.958 1.112

3.2.2 States’ Attitudes

3.2.2.1 Maps

3.2.2.2 Tables

state WARMUS_mean WARMIMP_mean WARMDO_mean REGGREEN_mean FSENV_mean
AK 2.722 3.155 3.809 2.846 3.789
AL 3.04  2.895 3.67  3.294 3.64 
AR 3.157 3.067 3.548 3.675 3.697
AZ 3.245 3.097 3.522 3.526 3.736
CA 3.869 3.661 4.048 4.027 4.145
CO 3.653 3.634 4.013 4.025 4.045
CT 3.542 3.335 3.803 4.02  3.821
DE 3.968 3.98  4.535 4.566 4.467
FL 3.398 3.253 3.614 3.748 3.893
GA 3.448 3.141 3.758 3.561 3.662
HI 3.988 3.664 3.891 4.305 4.056
IA 3.641 3.3   4.013 3.814 4.008
ID 2.808 2.877 3.462 3.367 3.617
IL 3.755 3.377 3.922 3.837 4.071
IN 3.34  3.234 3.777 3.626 3.833
KS 3.426 3.114 3.839 3.719 3.686
KY 3.294 3.014 3.339 3.405 3.48 
LA 3.14  2.816 3.533 3.394 3.743
MA 3.885 3.634 4.089 4.2   4.148
MD 3.889 3.704 4.181 4.04  4.188
ME 3.715 3.548 3.868 4.111 3.827
MI 3.257 3.245 3.753 3.595 3.973
MN 3.448 3.221 3.904 3.864 3.938
MO 3.408 3.193 3.803 3.693 3.858
MS 3.572 3.145 3.616 3.501 3.824
MT 2.523 2.22  2.765 2.651 2.681
NC 3.198 3.003 3.558 3.566 3.686
ND 2.879 2.905 3.404 3.567 3.249
NE 3.248 2.75  3.583 3.724 3.621
NH 3.744 3.492 3.99  4.082 4.309
NJ 3.681 3.509 4.083 3.752 4.011
NM 3.765 3.534 3.996 3.767 3.995
NV 4.05  3.718 4.242 3.94  4.234
NY 3.829 3.593 4.052 3.978 4.057
OH 3.321 2.993 3.604 3.632 3.608
OK 3.235 3.091 3.447 3.519 3.739
OR 3.937 3.808 4.097 4.07  4.024
PA 3.612 3.413 3.963 3.766 3.955
RI 2.805 2.502 3.554 3.231 3.546
SC 3.749 3.524 3.906 3.91  4.127
SD 3.271 3.432 3.241 3.332 3.684
TN 3.272 3.077 3.672 3.613 3.692
TX 3.495 3.253 3.856 3.637 3.947
UT 3.439 3.25  3.949 3.896 3.754
VA 3.485 3.205 3.883 3.674 3.921
VT 4.432 3.387 4.294 3.826 4.255
WA 3.765 3.597 4.33  4.091 4.143
WI 3.051 2.788 3.598 3.521 3.729
WV 2.656 2.553 3.096 3.082 3.353
WY 2.735 3.011 3.283 3.601 3.302
min — 2.523 2.22  2.765 2.651 2.681
max — 4.432 3.98  4.535 4.566 4.467
median — 3.443 3.24  3.806 3.706 3.83 
mean — 3.436 3.238 3.775 3.704 3.835
sd — 0.406 0.355 0.33  0.349 0.307
state WARMUS_mean WARMIMP_mean WARMDO_mean REGGREEN_mean FSENV_mean
AK 2.722 3.155 3.809 2.846 3.789
AL 3.04  2.895 3.67  3.294 3.64 
ID 2.808 2.877 3.462 3.367 3.617
LA 3.14  2.816 3.533 3.394 3.743
MT 2.523 2.22  2.765 2.651 2.681
ND 2.879 2.905 3.404 3.567 3.249
NE 3.248 2.75  3.583 3.724 3.621
OH 3.321 2.993 3.604 3.632 3.608
RI 2.805 2.502 3.554 3.231 3.546
WI 3.051 2.788 3.598 3.521 3.729
WV 2.656 2.553 3.096 3.082 3.353
WY 2.735 3.011 3.283 3.601 3.302
rank WARMUS_mean WARMIMP_mean WARMDO_mean REGGREEN_mean FSENV_mean
1   VT DE DE DE DE
2   NV OR WA HI NH
3   HI NV VT MA VT
4   DE MD NV ME NV
5   OR HI MD WA MD
rank WARMUS_mean WARMIMP_mean WARMDO_mean REGGREEN_mean FSENV_mean
 1   VT DE DE DE DE
 2   NV OR WA HI NH
 3   HI NV VT MA VT
 4   DE MD NV ME NV
 5   OR HI MD WA MD
 6   MD CA OR NH MA
 7   MA CO MA OR CA
 8   CA MA NJ MD WA
 9   NY WA NY CA SC
10   WA NY CA CO IL

4 Correlations

4.1 Individuals’ Attitudes

variable corr corr_se corr_low corr_upp
WARMUS 0.154 0.017 0.121 0.187
WARMIMP 0.157 0.017 0.124 0.19 
WARMDO 0.149 0.018 0.114 0.185
REGGREEN 0.145 0.017 0.113 0.178
FSENV 0.128 0.016 0.096 0.159
variable WARMUS WARMIMP WARMDO REGGREEN FSENV
WARMUS 1     0.802 0.634 0.619 0.552
WARMIMP 0.802 1     0.624 0.622 0.576
WARMDO 0.634 0.624 1     0.599 0.63 
REGGREEN 0.619 0.622 0.599 1     0.521
FSENV 0.552 0.576 0.63  0.521 1    

4.2 States’ Attitudes

variable corr
WARMUS_mean 0.59 
WARMIMP_mean 0.583
WARMDO_mean 0.626
REGGREEN_mean 0.583
FSENV_mean 0.562
variable WARMUS_mean WARMIMP_mean WARMDO_mean REGGREEN_mean FSENV_mean
WARMUS_mean 1        0.861     0.849     0.831     0.857
WARMIMP_mean     0.861 1        0.837     0.836     0.863
WARMDO_mean     0.849     0.837 1        0.795     0.911
REGGREEN_mean     0.831     0.836     0.795 1        0.781
FSENV_mean     0.857     0.863     0.911     0.781 1   

5 Regression Models

5.1 Models

model_combined_IN model_FSENV_IN model_REGGREEN_IN model_WARMDO_IN model_WARMIMP_IN model_WARMUS_IN
(Intercept) 22.275**** 24.511**** 24.500**** 24.388**** 24.233**** 24.320****
WARMUS 0.240 0.610**
WARMIMP 0.300 0.649**
WARMDO 0.165 0.613*
REGGREEN 0.248 0.599**
FSENV 0.104 0.538*
PTYID_CV -0.660**** -0.814**** -0.805**** -0.762**** -0.757**** -0.762****
LRSELF_CV -0.344*** -0.389*** -0.375*** -0.398*** -0.364*** -0.373***
age_CV 0.005 0.009 0.007 0.005 0.007 0.006
education_CV2 -2.347 -2.396 -2.368 -2.374 -2.371 -2.309
education_CV3 -1.138 -1.142 -1.185 -1.158 -1.151 -1.098
education_CV4 -0.002 -0.016 -0.040 -0.030 -0.054 0.038
education_CV5 0.442 0.452 0.396 0.461 0.390 0.458
income_CV 0.251**** 0.262**** 0.252**** 0.252**** 0.261**** 0.259****
race_CV2 -2.283** -2.525** -2.307** -2.510** -2.404** -2.414**
race_CV3 3.718*** 3.728*** 3.829**** 3.804**** 3.646*** 3.699***
race_CV4 7.596**** 7.680**** 7.619**** 7.731**** 7.639**** 7.635****
race_CV5 -0.791 -0.909 -0.920 -0.801 -0.863 -0.768
race_CV6 1.693 1.764 1.677 1.716 1.713 1.727
sex_CV2 -0.677 -0.602 -0.624 -0.597 -0.623 -0.652
Num.Obs. 6252 6310 6308 6272 6312 6311
R2 0.080 0.078 0.078 0.078 0.079 0.079
R2 Adj. -178.788 -160.656 -160.561 -159.534 -160.484 -160.491
AIC 51916.0 52389.5 52318.2 52059.1 52353.0 52345.2
BIC 60166.5 60215.8 60219.0 59833.5 60277.7 60250.0
RMSE 15.13 15.13 15.13 15.14 15.12 15.13
* p < 0.1, ** p < 0.05, *** p < 0.01, **** p < 0.001
model_combined_ST model_FSENV_ST model_REGGREEN_ST model_WARMDO_ST model_WARMIMP_ST model_WARMUS_ST
(Intercept) -74.004*** -78.534**** -66.794**** -80.368**** -54.668**** -50.023****
WARMUS_mean 4.333 20.410****
WARMIMP_mean 4.873 23.089****
WARMDO_mean 21.373 26.613****
REGGREEN_mean 6.348 23.461****
FSENV_mean -10.629 25.717****
Num.Obs. 50 50 50 50 50 50
R2 0.421 0.316 0.340 0.392 0.340 0.348
R2 Adj. 0.356 0.302 0.326 0.379 0.326 0.334
AIC 391.8 392.1 390.4 386.3 390.4 389.7
BIC 405.1 397.9 396.1 392.0 396.1 395.5
RMSE 10.58 11.50 11.30 10.85 11.30 11.23
* p < 0.1, ** p < 0.05, *** p < 0.01, **** p < 0.001

5.2 Details

5.2.1 Individuals’ Attitudes and Policies

Stratified 1 - level Cluster Sampling design (with replacement)
With (101) clusters.
Called via srvyr
Sampling variables:
  - ids: wgts_psu 
  - strata: wgts_ST_norata 
  - weights: Weight 

Call:  svyglm(formula = policies ~ WARMUS + PTYID_CV + LRSELF_CV + age_CV + 
    education_CV + income_CV + race_CV + sex_CV, design = .)

Coefficients:
  (Intercept)         WARMUS       PTYID_CV      LRSELF_CV         age_CV  
    24.320376       0.610431      -0.762057      -0.372751       0.005705  
education_CV2  education_CV3  education_CV4  education_CV5      income_CV  
    -2.308514      -1.097786       0.038422       0.457755       0.259235  
     race_CV2       race_CV3       race_CV4       race_CV5       race_CV6  
    -2.413570       3.699071       7.634935      -0.768305       1.726738  
      sex_CV2  
    -0.651886  

Degrees of Freedom: 6310 Total (i.e. Null);  36 Residual
  (7 observations deleted due to missingness)
Null Deviance:      1588000 
Residual Deviance: 1464000  AIC: 54790
MODEL INFO:
Observations: 6311
Dependent Variable: policies
Type: Survey-weighted linear regression 

MODEL FIT:
R² = 0.08
Adj. R² = -0.31 

Standard errors: Robust
--------------------------------------------------
                       Est.   S.E.   t val.      p
------------------- ------- ------ -------- ------
(Intercept)           24.32   2.09    11.63   0.00
WARMUS                 0.61   0.26     2.35   0.02
PTYID_CV              -0.76   0.16    -4.63   0.00
LRSELF_CV             -0.37   0.12    -3.03   0.00
age_CV                 0.01   0.02     0.37   0.72
education_CV2         -2.31   1.57    -1.47   0.15
education_CV3         -1.10   1.52    -0.72   0.48
education_CV4          0.04   1.58     0.02   0.98
education_CV5          0.46   1.75     0.26   0.79
income_CV              0.26   0.05     4.76   0.00
race_CV2              -2.41   1.09    -2.21   0.03
race_CV3               3.70   1.05     3.53   0.00
race_CV4               7.63   1.27     6.03   0.00
race_CV5              -0.77   1.69    -0.46   0.65
race_CV6               1.73   1.62     1.07   0.29
sex_CV2               -0.65   0.50    -1.30   0.20
--------------------------------------------------

Estimated dispersion parameter = 231.94 
Stratified 1 - level Cluster Sampling design (with replacement)
With (101) clusters.
Called via srvyr
Sampling variables:
  - ids: wgts_psu 
  - strata: wgts_ST_norata 
  - weights: Weight 

Call:  svyglm(formula = policies ~ WARMIMP + PTYID_CV + LRSELF_CV + 
    age_CV + education_CV + income_CV + race_CV + sex_CV, design = .)

Coefficients:
  (Intercept)        WARMIMP       PTYID_CV      LRSELF_CV         age_CV  
     24.23301        0.64868       -0.75734       -0.36399        0.00679  
education_CV2  education_CV3  education_CV4  education_CV5      income_CV  
     -2.37056       -1.15054       -0.05372        0.39017        0.26144  
     race_CV2       race_CV3       race_CV4       race_CV5       race_CV6  
     -2.40448        3.64607        7.63852       -0.86297        1.71269  
      sex_CV2  
     -0.62259  

Degrees of Freedom: 6311 Total (i.e. Null);  36 Residual
  (6 observations deleted due to missingness)
Null Deviance:      1589000 
Residual Deviance: 1464000  AIC: 54800
MODEL INFO:
Observations: 6312
Dependent Variable: policies
Type: Survey-weighted linear regression 

MODEL FIT:
R² = 0.08
Adj. R² = -0.30 

Standard errors: Robust
--------------------------------------------------
                       Est.   S.E.   t val.      p
------------------- ------- ------ -------- ------
(Intercept)           24.23   2.06    11.78   0.00
WARMIMP                0.65   0.25     2.57   0.01
PTYID_CV              -0.76   0.16    -4.65   0.00
LRSELF_CV             -0.36   0.13    -2.90   0.01
age_CV                 0.01   0.02     0.43   0.67
education_CV2         -2.37   1.57    -1.51   0.14
education_CV3         -1.15   1.53    -0.75   0.46
education_CV4         -0.05   1.59    -0.03   0.97
education_CV5          0.39   1.76     0.22   0.83
income_CV              0.26   0.05     4.82   0.00
race_CV2              -2.40   1.09    -2.21   0.03
race_CV3               3.65   1.04     3.51   0.00
race_CV4               7.64   1.27     6.03   0.00
race_CV5              -0.86   1.68    -0.51   0.61
race_CV6               1.71   1.61     1.06   0.30
sex_CV2               -0.62   0.49    -1.26   0.22
--------------------------------------------------

Estimated dispersion parameter = 231.96 
Stratified 1 - level Cluster Sampling design (with replacement)
With (101) clusters.
Called via srvyr
Sampling variables:
  - ids: wgts_psu 
  - strata: wgts_ST_norata 
  - weights: Weight 

Call:  svyglm(formula = policies ~ WARMDO + PTYID_CV + LRSELF_CV + age_CV + 
    education_CV + income_CV + race_CV + sex_CV, design = .)

Coefficients:
  (Intercept)         WARMDO       PTYID_CV      LRSELF_CV         age_CV  
    24.387588       0.613332      -0.762034      -0.397736       0.005111  
education_CV2  education_CV3  education_CV4  education_CV5      income_CV  
    -2.373521      -1.157976      -0.030008       0.461218       0.252483  
     race_CV2       race_CV3       race_CV4       race_CV5       race_CV6  
    -2.509603       3.803914       7.730878      -0.801208       1.715920  
      sex_CV2  
    -0.597005  

Degrees of Freedom: 6271 Total (i.e. Null);  36 Residual
  (46 observations deleted due to missingness)
Null Deviance:      1580000 
Residual Deviance: 1456000  AIC: 54450
MODEL INFO:
Observations: 6272
Dependent Variable: policies
Type: Survey-weighted linear regression 

MODEL FIT:
R² = 0.08
Adj. R² = -0.31 

Standard errors: Robust
--------------------------------------------------
                       Est.   S.E.   t val.      p
------------------- ------- ------ -------- ------
(Intercept)           24.39   2.32    10.50   0.00
WARMDO                 0.61   0.34     1.79   0.08
PTYID_CV              -0.76   0.16    -4.62   0.00
LRSELF_CV             -0.40   0.13    -3.18   0.00
age_CV                 0.01   0.02     0.32   0.75
education_CV2         -2.37   1.58    -1.51   0.14
education_CV3         -1.16   1.52    -0.76   0.45
education_CV4         -0.03   1.59    -0.02   0.99
education_CV5          0.46   1.75     0.26   0.79
income_CV              0.25   0.05     4.64   0.00
race_CV2              -2.51   1.10    -2.28   0.03
race_CV3               3.80   1.03     3.71   0.00
race_CV4               7.73   1.24     6.24   0.00
race_CV5              -0.80   1.70    -0.47   0.64
race_CV6               1.72   1.63     1.05   0.30
sex_CV2               -0.60   0.50    -1.19   0.24
--------------------------------------------------

Estimated dispersion parameter = 232.21 
Stratified 1 - level Cluster Sampling design (with replacement)
With (101) clusters.
Called via srvyr
Sampling variables:
  - ids: wgts_psu 
  - strata: wgts_ST_norata 
  - weights: Weight 

Call:  svyglm(formula = policies ~ REGGREEN + PTYID_CV + LRSELF_CV + 
    age_CV + education_CV + income_CV + race_CV + sex_CV, design = .)

Coefficients:
  (Intercept)       REGGREEN       PTYID_CV      LRSELF_CV         age_CV  
    24.499913       0.599117      -0.805170      -0.374780       0.006537  
education_CV2  education_CV3  education_CV4  education_CV5      income_CV  
    -2.368465      -1.185032      -0.039608       0.396069       0.252474  
     race_CV2       race_CV3       race_CV4       race_CV5       race_CV6  
    -2.306654       3.829304       7.619329      -0.919903       1.677453  
      sex_CV2  
    -0.623599  

Degrees of Freedom: 6307 Total (i.e. Null);  36 Residual
  (10 observations deleted due to missingness)
Null Deviance:      1588000 
Residual Deviance: 1465000  AIC: 54770
MODEL INFO:
Observations: 6308
Dependent Variable: policies
Type: Survey-weighted linear regression 

MODEL FIT:
R² = 0.08
Adj. R² = -0.31 

Standard errors: Robust
--------------------------------------------------
                       Est.   S.E.   t val.      p
------------------- ------- ------ -------- ------
(Intercept)           24.50   1.99    12.34   0.00
REGGREEN               0.60   0.26     2.28   0.03
PTYID_CV              -0.81   0.16    -4.93   0.00
LRSELF_CV             -0.37   0.12    -3.12   0.00
age_CV                 0.01   0.02     0.41   0.68
education_CV2         -2.37   1.57    -1.51   0.14
education_CV3         -1.19   1.54    -0.77   0.45
education_CV4         -0.04   1.59    -0.02   0.98
education_CV5          0.40   1.76     0.22   0.82
income_CV              0.25   0.05     4.59   0.00
race_CV2              -2.31   1.10    -2.09   0.04
race_CV3               3.83   1.02     3.74   0.00
race_CV4               7.62   1.23     6.19   0.00
race_CV5              -0.92   1.70    -0.54   0.59
race_CV6               1.68   1.62     1.04   0.31
sex_CV2               -0.62   0.50    -1.25   0.22
--------------------------------------------------

Estimated dispersion parameter = 232.22 
Stratified 1 - level Cluster Sampling design (with replacement)
With (101) clusters.
Called via srvyr
Sampling variables:
  - ids: wgts_psu 
  - strata: wgts_ST_norata 
  - weights: Weight 

Call:  svyglm(formula = policies ~ FSENV + PTYID_CV + LRSELF_CV + age_CV + 
    education_CV + income_CV + race_CV + sex_CV, design = .)

Coefficients:
  (Intercept)          FSENV       PTYID_CV      LRSELF_CV         age_CV  
    24.510559       0.537903      -0.813615      -0.388721       0.008728  
education_CV2  education_CV3  education_CV4  education_CV5      income_CV  
    -2.395933      -1.141873      -0.016450       0.451946       0.262369  
     race_CV2       race_CV3       race_CV4       race_CV5       race_CV6  
    -2.524851       3.727995       7.680157      -0.908957       1.763738  
      sex_CV2  
    -0.601715  

Degrees of Freedom: 6309 Total (i.e. Null);  36 Residual
  (8 observations deleted due to missingness)
Null Deviance:      1590000 
Residual Deviance: 1466000  AIC: 54780
MODEL INFO:
Observations: 6310
Dependent Variable: policies
Type: Survey-weighted linear regression 

MODEL FIT:
R² = 0.08
Adj. R² = -0.31 

Standard errors: Robust
--------------------------------------------------
                       Est.   S.E.   t val.      p
------------------- ------- ------ -------- ------
(Intercept)           24.51   2.26    10.85   0.00
FSENV                  0.54   0.31     1.73   0.09
PTYID_CV              -0.81   0.16    -5.12   0.00
LRSELF_CV             -0.39   0.13    -3.03   0.00
age_CV                 0.01   0.02     0.56   0.58
education_CV2         -2.40   1.55    -1.55   0.13
education_CV3         -1.14   1.51    -0.75   0.46
education_CV4         -0.02   1.57    -0.01   0.99
education_CV5          0.45   1.74     0.26   0.80
income_CV              0.26   0.05     4.83   0.00
race_CV2              -2.52   1.08    -2.33   0.03
race_CV3               3.73   1.04     3.58   0.00
race_CV4               7.68   1.26     6.11   0.00
race_CV5              -0.91   1.70    -0.53   0.60
race_CV6               1.76   1.61     1.10   0.28
sex_CV2               -0.60   0.50    -1.21   0.23
--------------------------------------------------

Estimated dispersion parameter = 232.42 
Stratified 1 - level Cluster Sampling design (with replacement)
With (101) clusters.
Called via srvyr
Sampling variables:
  - ids: wgts_psu 
  - strata: wgts_ST_norata 
  - weights: Weight 

Call:  svyglm(formula = policies ~ WARMUS + WARMIMP + WARMDO + REGGREEN + 
    FSENV + PTYID_CV + LRSELF_CV + age_CV + education_CV + income_CV + 
    race_CV + sex_CV, design = .)

Coefficients:
  (Intercept)         WARMUS        WARMIMP         WARMDO       REGGREEN  
    22.275271       0.239654       0.300151       0.164910       0.248054  
        FSENV       PTYID_CV      LRSELF_CV         age_CV  education_CV2  
     0.103897      -0.659772      -0.343578       0.004912      -2.346703  
education_CV3  education_CV4  education_CV5      income_CV       race_CV2  
    -1.137960      -0.001628       0.441770       0.251386      -2.283109  
     race_CV3       race_CV4       race_CV5       race_CV6        sex_CV2  
     3.718413       7.596191      -0.791075       1.693250      -0.677234  

Degrees of Freedom: 6251 Total (i.e. Null);  32 Residual
  (66 observations deleted due to missingness)
Null Deviance:      1576000 
Residual Deviance: 1450000  AIC: 54270
MODEL INFO:
Observations: 6252
Dependent Variable: policies
Type: Survey-weighted linear regression 

MODEL FIT:
R² = 0.08
Adj. R² = -0.47 

Standard errors: Robust
--------------------------------------------------
                       Est.   S.E.   t val.      p
------------------- ------- ------ -------- ------
(Intercept)           22.28   2.50     8.91   0.00
WARMUS                 0.24   0.38     0.64   0.53
WARMIMP                0.30   0.34     0.89   0.38
WARMDO                 0.16   0.44     0.38   0.71
REGGREEN               0.25   0.39     0.63   0.53
FSENV                  0.10   0.37     0.28   0.78
PTYID_CV              -0.66   0.17    -3.85   0.00
LRSELF_CV             -0.34   0.12    -2.77   0.01
age_CV                 0.00   0.02     0.31   0.76
education_CV2         -2.35   1.60    -1.47   0.15
education_CV3         -1.14   1.54    -0.74   0.47
education_CV4         -0.00   1.60    -0.00   1.00
education_CV5          0.44   1.77     0.25   0.80
income_CV              0.25   0.05     4.60   0.00
race_CV2              -2.28   1.11    -2.06   0.05
race_CV3               3.72   1.04     3.59   0.00
race_CV4               7.60   1.24     6.12   0.00
race_CV5              -0.79   1.69    -0.47   0.64
race_CV6               1.69   1.64     1.03   0.31
sex_CV2               -0.68   0.50    -1.34   0.19
--------------------------------------------------

Estimated dispersion parameter = 232.01

5.2.2 States’ Attitudes and Policies


Call:
lm(formula = policies ~ WARMUS_mean, data = .)

Coefficients:
(Intercept)  WARMUS_mean  
     -50.02        20.41  
MODEL INFO:
Observations: 50
Dependent Variable: policies
Type: OLS linear regression 

MODEL FIT:
F(1,48) = 25.62, p = 0.00
R² = 0.35
Adj. R² = 0.33 

Standard errors:OLS
--------------------------------------------------
                      Est.    S.E.   t val.      p
----------------- -------- ------- -------- ------
(Intercept)         -50.02   13.95    -3.59   0.00
WARMUS_mean          20.41    4.03     5.06   0.00
--------------------------------------------------

Call:
lm(formula = policies ~ WARMIMP_mean, data = .)

Coefficients:
 (Intercept)  WARMIMP_mean  
      -54.67         23.09  
MODEL INFO:
Observations: 50
Dependent Variable: policies
Type: OLS linear regression 

MODEL FIT:
F(1,48) = 24.71, p = 0.00
R² = 0.34
Adj. R² = 0.33 

Standard errors:OLS
---------------------------------------------------
                       Est.    S.E.   t val.      p
------------------ -------- ------- -------- ------
(Intercept)          -54.67   15.13    -3.61   0.00
WARMIMP_mean          23.09    4.65     4.97   0.00
---------------------------------------------------

Call:
lm(formula = policies ~ WARMDO_mean, data = .)

Coefficients:
(Intercept)  WARMDO_mean  
     -80.37        26.61  
MODEL INFO:
Observations: 50
Dependent Variable: policies
Type: OLS linear regression 

MODEL FIT:
F(1,48) = 30.89, p = 0.00
R² = 0.39
Adj. R² = 0.38 

Standard errors:OLS
--------------------------------------------------
                      Est.    S.E.   t val.      p
----------------- -------- ------- -------- ------
(Intercept)         -80.37   18.14    -4.43   0.00
WARMDO_mean          26.61    4.79     5.56   0.00
--------------------------------------------------

Call:
lm(formula = policies ~ REGGREEN_mean, data = .)

Coefficients:
  (Intercept)  REGGREEN_mean  
       -66.79          23.46  
MODEL INFO:
Observations: 50
Dependent Variable: policies
Type: OLS linear regression 

MODEL FIT:
F(1,48) = 24.68, p = 0.00
R² = 0.34
Adj. R² = 0.33 

Standard errors:OLS
----------------------------------------------------
                        Est.    S.E.   t val.      p
------------------- -------- ------- -------- ------
(Intercept)           -66.79   17.57    -3.80   0.00
REGGREEN_mean          23.46    4.72     4.97   0.00
----------------------------------------------------

Call:
lm(formula = policies ~ FSENV_mean, data = .)

Coefficients:
(Intercept)   FSENV_mean  
     -78.53        25.72  
MODEL INFO:
Observations: 50
Dependent Variable: policies
Type: OLS linear regression 

MODEL FIT:
F(1,48) = 22.16, p = 0.00
R² = 0.32
Adj. R² = 0.30 

Standard errors:OLS
--------------------------------------------------
                      Est.    S.E.   t val.      p
----------------- -------- ------- -------- ------
(Intercept)         -78.53   21.02    -3.74   0.00
FSENV_mean           25.72    5.46     4.71   0.00
--------------------------------------------------

Call:
lm(formula = policies ~ WARMUS_mean + WARMIMP_mean + WARMDO_mean + 
    REGGREEN_mean + FSENV_mean, data = .)

Coefficients:
  (Intercept)    WARMUS_mean   WARMIMP_mean    WARMDO_mean  REGGREEN_mean  
      -74.004          4.333          4.873         21.373          6.348  
   FSENV_mean  
      -10.629  
MODEL INFO:
Observations: 50
Dependent Variable: policies
Type: OLS linear regression 

MODEL FIT:
F(5,44) = 6.41, p = 0.00
R² = 0.42
Adj. R² = 0.36 

Standard errors:OLS
----------------------------------------------------
                        Est.    S.E.   t val.      p
------------------- -------- ------- -------- ------
(Intercept)           -74.00   22.97    -3.22   0.00
WARMUS_mean             4.33    9.42     0.46   0.65
WARMIMP_mean            4.87   10.93     0.45   0.66
WARMDO_mean            21.37   12.73     1.68   0.10
REGGREEN_mean           6.35    9.32     0.68   0.50
FSENV_mean            -10.63   14.49    -0.73   0.47
----------------------------------------------------

Differences between observations between models for individuals’ attitudes with and without sociodemographic control variables

Combined: 636

WARMUS: 660

WARMIMP: 661

WARMDO: 643

REGGREEN: 654

FSENV: 657