ZS Anti-Establishment: World Values Survey

Background

Wave 6 of the World Values Survey was conducted in 2010-2014. Among many measures, the survey included two measures of interest to this project:

1. Economic Zero-Sum. Respondents were asked to indicate their attitude about wealth accumulation from People can only get rich at the expense of others (1) to Wealth can grow so there´s enough for everyone (10). I reverse-scored this to get an economic zero-sum measure.
2. Confidence in Institutions. Respondents indicated their confidence in a variety of institutions on a scale of 1 (A great deal) to 4 (None at all). I reverse-scored these to get a confidence score. The institutions are: Church, armed forces, press, television, labor unions, police, courts, national government, political parties, parliament, civil services, universities, major companies, banks.
3. Voting in national elections. Respondents indicated their voting behavior: Always, Usually, Never.
4. Control variables. We have individual-level controls and country-level controls. On the individual level, we control for participants’ ideology (left to right scale), sex, age, education, and income (on a within-country income scale). On the country-level, we control for GDP per capita and gini.

Descriptives

Total N and total missing values for each country

Economic zero-sum variable

country	total_N	missing
Algeria	1200	83
Argentina	1030	77
Armenia	1100	92
Australia	1477	28
Azerbaijan	1002	1
Belarus	1535	32
Brazil	1486	52
Chile	1000	34
China	2300	355
Colombia	1512	26
Cyprus	1000	12
Ecuador	1202	7
Egypt	1523	0
Estonia	1533	49
Georgia	1202	44
Germany	2046	57
Ghana	1552	0
Haiti	1996	46
Hong Kong	1000	7
India	4078	659
Iraq	1200	37
Japan	2443	535
Jordan	1200	22
Kazakhstan	1500	0
Kuwait	1303	56
Kyrgyzstan	1500	8
Lebanon	1200	38
Libya	2131	165
Malaysia	1300	0
Mexico	2000	17
Morocco	1200	329
Netherlands	1902	183
New Zealand	841	67
Nigeria	1759	0
Pakistan	1200	0
Palestine	1000	36
Peru	1210	67
Philippines	1200	0
Poland	966	55
Qatar	1060	11
Romania	1503	56
Russia	2500	291
Rwanda	1527	0
Singapore	1972	2
Slovenia	1069	58
South Africa	3531	87
South Korea	1200	8
Spain	1189	50
Sweden	1206	74
Taiwan	1238	64
Thailand	1200	13
Trinidad & Tobago	999	25
Tunisia	1205	99
Turkey	1605	39
Ukraine	1500	0
United States	2232	57
Uruguay	1000	114
Uzbekistan	1500	131
Yemen	1000	147
Zimbabwe	1500	0

Confidence in institutions

The numbers in the institution columns represent the total missing values per institution in that country.

country	total_N	armedforces	banks	church	civilservices	court	gov	laborunions	majorcompanies	parl	police	polparties	press	tv	univ
Algeria	1200	71	199	79	165	132	150	261	182	242	63	215	100	74	135
Argentina	1030	38	33	12	40	17	20	49	39	46	13	36	43	18	34
Armenia	1100	8	69	19	80	51	41	306	185	48	39	52	34	10	85
Australia	1477	28	29	27	36	37	29	39	43	38	25	31	34	33	32
Azerbaijan	1002	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Belarus	1535	3	16	7	15	7	8	18	14	17	6	14	5	5	12
Brazil	1486	83	9	14	12	5	15	86	42	35	6	16	19	9	43
Chile	1000	8	20	11	30	15	15	84	20	22	11	14	15	11	26
China	2300	223	325	740	367	274	203	867	466	265	226	295	337	261	328
Colombia	1512	8	16	5	14	23	12	38	17	26	5	18	8	8	20
Cyprus	1000	8	10	9	10	17	18	58	30	13	4	14	13	3	24
Ecuador	1202	3	1	0	3	3	3	6	4	2	0	2	0	1	1
Egypt	1523	1523	13	4	22	4	3	53	17	16	3	22	6	1	12
Estonia	1533	60	27	128	45	54	21	237	126	41	14	60	16	10	126
Georgia	1202	17	54	10	54	111	53	274	133	58	40	58	24	15	99
Germany	2046	63	35	51	44	53	45	173	88	68	21	64	23	21	176
Ghana	1552	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Haiti	1996	52	53	51	53	50	49	55	53	57	47	50	49	54	51
Hong Kong	1000	9	4	6	12	8	5	11	10	11	3	7	10	4	7
India	4078	243	293	30	639	205	377	557	680	483	162	338	332	258	558
Iraq	1200	8	110	11	60	59	47	218	141	86	12	49	53	9	72
Japan	2443	286	285	313	338	254	277	700	490	322	144	333	105	107	498
Jordan	1200	7	65	21	42	16	30	220	89	80	8	185	21	5	43
Kazakhstan	1500	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Kuwait	1303	68	82	61	63	66	50	1303	104	87	60	1303	68	65	84
Kyrgyzstan	1500	6	7	14	6	6	7	7	4	10	5	7	9	2	9
Lebanon	1200	33	56	51	53	57	221	88	68	85	43	80	48	44	62
Libya	2131	119	154	177	226	144	159	389	240	280	114	241	131	98	163
Malaysia	1300	1	1	1	1	1	2	4	1	1	1	2	1	1	1
Mexico	2000	9	7	1	29	20	5	25	9	25	1	3	8	2	12
Morocco	1200	71	122	6	104	70	84	368	153	106	70	120	133	93	215
Netherlands	1902	213	106	147	132	78	89	203	174	133	63	102	73	80	170
New Zealand	841	63	60	86	111	55	81	152	128	76	39	73	55	57	111
Nigeria	1759	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Pakistan	1200	13	52	11	54	32	40	53	53	45	23	43	30	31	49
Palestine	1000	45	74	33	65	85	88	150	109	107	56	93	52	28	62
Peru	1210	23	46	7	22	17	22	60	39	14	7	29	14	14	24
Philippines	1200	2	0	1	1	2	2	2	3	1	1	0	3	0	1
Poland	966	71	72	21	73	80	38	257	180	56	50	60	39	27	147
Qatar	1060	8	15	6	1060	11	7	1060	29	16	7	1060	7	6	12
Romania	1503	50	75	17	57	91	50	120	135	62	27	65	36	22	131
Russia	2500	127	171	163	205	188	138	514	369	276	108	184	60	45	313
Rwanda	1527	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Singapore	1972	0	1	0	3	1	0	0	1	0	1	0	0	0	1
Slovenia	1069	34	28	23	32	50	29	83	61	26	22	31	10	9	85
South Africa	3531	154	188	36	193	129	112	249	195	132	99	128	94	60	185
South Korea	1200	3	3	4	4	4	3	6	6	6	4	6	3	4	4
Spain	1189	31	27	19	42	24	18	42	40	55	17	25	21	14	47
Sweden	1206	39	21	34	220	34	21	74	54	32	7	34	7	13	71
Taiwan	1238	76	80	77	69	87	68	148	108	96	50	90	83	49	86
Thailand	1200	44	39	42	63	61	58	166	96	90	51	73	48	42	61
Trinidad & Tobago	999	49	37	26	106	75	48	115	117	69	24	56	23	21	81
Tunisia	1205	63	179	93	165	82	92	197	238	129	57	112	91	85	222
Turkey	1605	35	65	39	64	47	41	129	89	62	21	52	38	24	71
Ukraine	1500	0	0	0	0	0	0	0	0	0	0	0	0	0	0
United States	2232	38	55	37	50	44	45	45	54	62	37	44	36	37	56
Uruguay	1000	40	89	30	96	57	33	65	125	64	18	53	28	21	74
Uzbekistan	1500	36	102	88	62	93	30	297	201	151	42	179	30	15	86
Yemen	1000	84	343	28	143	152	76	489	416	167	101	132	257	93	294
Zimbabwe	1500	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Variables of interest

Confidence in institutions

Economic Zero-Sum

Analysis

EZS -> Confidence in institutions

Entire data set

Just the US

Linear model: EZS -> Confidence in the Church

Whole sample

(#tab:unnamed-chunk-7)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.10	[-0.50, 0.69]	0.32	59,360	.751
ScaleEZS	-0.03	[-0.04, -0.02]	-7.64	59,360	< .001
Scaleideo	0.08	[0.08, 0.09]	22.64	59,360	< .001
Sexmale	-0.11	[-0.12, -0.09]	-15.15	59,360	< .001
Age	0.00	[0.00, 0.00]	18.10	59,360	< .001
Edu	-0.02	[-0.02, -0.02]	-10.60	59,360	< .001
Income	0.00	[0.00, 0.00]	-0.34	59,360	.733
Gdppc	0.00	[0.00, 0.00]	-4.59	47	< .001
Gini	0.01	[-0.01, 0.02]	0.81	47	.423

Just the US

(#tab:unnamed-chunk-8)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.21	[-0.50, 0.07]	-1.47	2076	.141
ScaleEZS	-0.07	[-0.12, -0.03]	-3.40	2076	.001
Scaleideo	0.27	[0.23, 0.32]	12.72	2076	< .001
Sexmale	-0.10	[-0.18, -0.02]	-2.36	2076	.018
Age	0.01	[0.00, 0.01]	4.87	2076	< .001
Edu	-0.01	[-0.04, 0.02]	-0.64	2076	.524
Income	0.01	[-0.01, 0.03]	0.82	2076	.410

Linear model: EZS -> Confidence in the Armed Forces

Whole sample

(#tab:unnamed-chunk-9)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.17	[-0.39, 0.72]	0.59	57,714	.557
ScaleEZS	-0.04	[-0.05, -0.03]	-10.24	57,714	< .001
Scaleideo	0.09	[0.09, 0.10]	23.55	57,714	< .001
Sexmale	0.05	[0.04, 0.07]	7.06	57,714	< .001
Age	0.00	[0.00, 0.00]	16.11	57,714	< .001
Edu	0.00	[-0.01, 0.00]	-1.60	57,714	.109
Income	0.01	[0.00, 0.01]	3.25	57,714	.001
Gdppc	0.00	[0.00, 0.00]	-0.46	46	.651
Gini	-0.01	[-0.02, 0.00]	-1.45	46	.155

Just the US

(#tab:unnamed-chunk-10)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.82	[-1.10, -0.54]	-5.67	2074	< .001
ScaleEZS	-0.05	[-0.10, -0.01]	-2.54	2074	.011
Scaleideo	0.23	[0.19, 0.27]	10.72	2074	< .001
Sexmale	0.05	[-0.03, 0.13]	1.12	2074	.265
Age	0.01	[0.01, 0.01]	7.69	2074	< .001
Edu	0.04	[0.01, 0.07]	2.26	2074	.024
Income	0.01	[-0.01, 0.03]	1.09	2074	.276

Linear model: EZS -> Confidence in the press

Whole sample

(#tab:unnamed-chunk-11)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.23	[-0.69, 0.22]	-1.00	59,411	.319
ScaleEZS	-0.02	[-0.02, -0.01]	-3.68	59,411	< .001
Scaleideo	0.04	[0.04, 0.05]	10.58	59,411	< .001
Sexmale	0.01	[-0.01, 0.02]	0.75	59,411	.455
Age	0.00	[0.00, 0.00]	10.48	59,411	< .001
Edu	0.00	[0.00, 0.01]	2.01	59,411	.044
Income	0.02	[0.01, 0.02]	8.70	59,411	< .001
Gdppc	0.00	[0.00, 0.00]	-1.51	47	.138
Gini	0.00	[-0.01, 0.01]	0.28	47	.780

Just the US

(#tab:unnamed-chunk-12)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.11	[-0.18, 0.41]	0.75	2077	.453
ScaleEZS	-0.01	[-0.05, 0.04]	-0.26	2077	.797
Scaleideo	-0.19	[-0.23, -0.14]	-8.39	2077	< .001
Sexmale	-0.06	[-0.14, 0.03]	-1.30	2077	.193
Age	0.00	[0.00, 0.00]	0.30	2077	.766
Edu	-0.05	[-0.09, -0.02]	-3.03	2077	.002
Income	0.06	[0.04, 0.08]	5.15	2077	< .001

Linear model: EZS -> Confidence in television

Whole sample

(#tab:unnamed-chunk-13)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.15	[-0.33, 0.64]	0.63	59,552	.532
ScaleEZS	-0.01	[-0.02, 0.00]	-2.49	59,552	.013
Scaleideo	0.04	[0.04, 0.05]	10.94	59,552	< .001
Sexmale	-0.02	[-0.04, -0.01]	-2.89	59,552	.004
Age	0.00	[0.00, 0.00]	7.75	59,552	< .001
Edu	-0.02	[-0.02, -0.01]	-7.88	59,552	< .001
Income	0.02	[0.01, 0.02]	7.79	59,552	< .001
Gdppc	0.00	[0.00, 0.00]	-1.90	47	.064
Gini	0.00	[-0.02, 0.01]	-0.67	47	.507

Just the US

(#tab:unnamed-chunk-14)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.92	[0.62, 1.21]	6.08	2074	< .001
ScaleEZS	-0.02	[-0.06, 0.03]	-0.74	2074	.462
Scaleideo	-0.07	[-0.12, -0.03]	-3.32	2074	.001
Sexmale	-0.10	[-0.19, -0.02]	-2.41	2074	.016
Age	0.00	[0.00, 0.00]	0.69	2074	.492
Edu	-0.14	[-0.18, -0.11]	-8.11	2074	< .001
Income	0.04	[0.01, 0.06]	3.22	2074	.001

Linear model: EZS -> Confidence in labor unions

Whole sample

(#tab:unnamed-chunk-15)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.04	[-0.52, 0.44]	-0.16	57,149	.876
ScaleEZS	-0.03	[-0.03, -0.02]	-6.13	57,149	< .001
Scaleideo	0.01	[0.00, 0.02]	1.79	57,149	.074
Sexmale	0.00	[-0.02, 0.01]	-0.27	57,149	.790
Age	0.00	[0.00, 0.00]	1.06	57,149	.291
Edu	0.00	[0.00, 0.01]	0.79	57,149	.432
Income	0.02	[0.01, 0.02]	7.45	57,149	< .001
Gdppc	0.00	[0.00, 0.00]	-0.61	47	.546
Gini	0.00	[-0.01, 0.01]	-0.30	47	.768

Just the US

(#tab:unnamed-chunk-16)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.58	[0.29, 0.87]	3.96	2070	< .001
ScaleEZS	0.05	[0.01, 0.10]	2.44	2070	.015
Scaleideo	-0.27	[-0.32, -0.23]	-12.53	2070	< .001
Sexmale	-0.14	[-0.22, -0.06]	-3.38	2070	.001
Age	-0.01	[-0.01, 0.00]	-4.27	2070	< .001
Edu	-0.05	[-0.08, -0.01]	-2.76	2070	.006
Income	0.02	[0.00, 0.05]	2.03	2070	.043

Linear model: EZS -> Confidence in police

Whole sample

(#tab:unnamed-chunk-17)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.29	[-0.78, 0.19]	-1.18	59,547	.238
ScaleEZS	-0.04	[-0.05, -0.03]	-10.40	59,547	< .001
Scaleideo	0.08	[0.07, 0.09]	20.50	59,547	< .001
Sexmale	-0.04	[-0.06, -0.03]	-5.42	59,547	< .001
Age	0.00	[0.00, 0.00]	8.86	59,547	< .001
Edu	-0.01	[-0.01, 0.00]	-4.42	59,547	< .001
Income	0.02	[0.02, 0.03]	12.32	59,547	< .001
Gdppc	0.00	[0.00, 0.00]	2.99	47	.004
Gini	0.00	[-0.01, 0.01]	-0.17	47	.865

Just the US

(#tab:unnamed-chunk-18)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-1.24	[-1.53, -0.95]	-8.39	2076	< .001
ScaleEZS	-0.09	[-0.13, -0.05]	-4.02	2076	< .001
Scaleideo	0.11	[0.06, 0.15]	4.81	2076	< .001
Sexmale	-0.12	[-0.20, -0.04]	-2.90	2076	.004
Age	0.01	[0.00, 0.01]	5.41	2076	< .001
Edu	0.09	[0.06, 0.13]	5.37	2076	< .001
Income	0.05	[0.03, 0.07]	4.41	2076	< .001

Linear model: EZS -> Confidence in the courts

Whole sample

(#tab:unnamed-chunk-19)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.16	[-0.68, 0.37]	-0.58	59,082	.560
ScaleEZS	-0.05	[-0.06, -0.04]	-11.68	59,082	< .001
Scaleideo	0.05	[0.04, 0.06]	11.98	59,082	< .001
Sexmale	-0.03	[-0.05, -0.02]	-4.42	59,082	< .001
Age	0.00	[0.00, 0.00]	0.72	59,082	.473
Edu	0.00	[0.00, 0.00]	0.10	59,082	.918
Income	0.03	[0.03, 0.03]	14.66	59,082	< .001
Gdppc	0.00	[0.00, 0.00]	1.66	47	.104
Gini	0.00	[-0.02, 0.01]	-0.51	47	.610

Just the US

(#tab:unnamed-chunk-20)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-1.00	[-1.29, -0.70]	-6.60	2071	< .001
ScaleEZS	-0.07	[-0.11, -0.02]	-2.95	2071	.003
Scaleideo	0.00	[-0.05, 0.04]	-0.21	2071	.833
Sexmale	-0.03	[-0.11, 0.05]	-0.71	2071	.477
Age	0.00	[0.00, 0.01]	2.08	2071	.038
Edu	0.06	[0.02, 0.09]	3.37	2071	.001
Income	0.08	[0.06, 0.11]	6.94	2071	< .001

Linear model: EZS -> Confidence in the national government

Whole sample

(#tab:unnamed-chunk-21)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.16	[-0.71, 0.39]	-0.58	59,135	.565
ScaleEZS	-0.05	[-0.05, -0.04]	-11.45	59,135	< .001
Scaleideo	0.08	[0.08, 0.09]	20.70	59,135	< .001
Sexmale	-0.04	[-0.05, -0.02]	-4.62	59,135	< .001
Age	0.00	[0.00, 0.00]	9.33	59,135	< .001
Edu	0.00	[-0.01, 0.00]	-2.53	59,135	.011
Income	0.02	[0.02, 0.03]	12.25	59,135	< .001
Gdppc	0.00	[0.00, 0.00]	-0.84	47	.406
Gini	0.00	[-0.01, 0.01]	0.12	47	.901

Just the US

(#tab:unnamed-chunk-22)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.12	[-0.17, 0.42]	0.82	2073	.414
ScaleEZS	-0.06	[-0.10, -0.01]	-2.47	2073	.014
Scaleideo	-0.16	[-0.21, -0.12]	-7.24	2073	< .001
Sexmale	-0.14	[-0.23, -0.06]	-3.36	2073	.001
Age	0.00	[-0.01, 0.00]	-3.24	2073	.001
Edu	-0.03	[-0.06, 0.01]	-1.48	2073	.140
Income	0.07	[0.05, 0.09]	5.77	2073	< .001

Linear model: EZS -> Confidence in political parties

Whole sample

(#tab:unnamed-chunk-23)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.08	[-0.62, 0.45]	-0.30	58,989	.765
ScaleEZS	-0.03	[-0.04, -0.02]	-6.72	58,989	< .001
Scaleideo	0.07	[0.06, 0.08]	16.80	58,989	< .001
Sexmale	0.00	[-0.02, 0.01]	-0.07	58,989	.945
Age	0.00	[0.00, 0.00]	7.48	58,989	< .001
Edu	-0.01	[-0.01, -0.01]	-4.79	58,989	< .001
Income	0.03	[0.03, 0.04]	16.48	58,989	< .001
Gdppc	0.00	[0.00, 0.00]	-0.78	47	.440
Gini	0.00	[-0.02, 0.01]	-0.33	47	.745

Just the US

(#tab:unnamed-chunk-24)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.02	[-0.28, 0.32]	0.12	2071	.906
ScaleEZS	-0.08	[-0.13, -0.04]	-3.66	2071	< .001
Scaleideo	-0.01	[-0.06, 0.03]	-0.59	2071	.554
Sexmale	-0.13	[-0.22, -0.05]	-3.02	2071	.003
Age	0.00	[0.00, 0.00]	-1.32	2071	.188
Edu	-0.02	[-0.06, 0.01]	-1.20	2071	.229
Income	0.06	[0.04, 0.08]	4.90	2071	< .001

Linear model: EZS -> Confidence in parliament

Whole sample

(#tab:unnamed-chunk-25)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.16	[-0.75, 0.43]	-0.53	58,763	.599
ScaleEZS	-0.04	[-0.05, -0.03]	-9.22	58,763	< .001
Scaleideo	0.07	[0.06, 0.08]	16.93	58,763	< .001
Sexmale	-0.01	[-0.03, 0.00]	-1.42	58,763	.155
Age	0.00	[0.00, 0.00]	7.12	58,763	< .001
Edu	0.00	[0.00, 0.00]	-0.02	58,763	.984
Income	0.03	[0.03, 0.03]	14.74	58,763	< .001
Gdppc	0.00	[0.00, 0.00]	-0.37	47	.714
Gini	0.00	[-0.02, 0.01]	-0.24	47	.815

Just the US

(#tab:unnamed-chunk-26)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.51	[0.21, 0.81]	3.34	2056	.001
ScaleEZS	-0.08	[-0.12, -0.04]	-3.50	2056	< .001
Scaleideo	-0.09	[-0.14, -0.05]	-4.10	2056	< .001
Sexmale	-0.17	[-0.26, -0.09]	-4.05	2056	< .001
Age	-0.01	[-0.01, 0.00]	-5.42	2056	< .001
Edu	-0.04	[-0.08, -0.01]	-2.49	2056	.013
Income	0.05	[0.03, 0.07]	4.31	2056	< .001

Linear model: EZS -> Confidence in civil services

Whole sample

(#tab:unnamed-chunk-27)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.03	[-0.60, 0.55]	-0.09	58,540	.927
ScaleEZS	-0.04	[-0.05, -0.03]	-9.49	58,540	< .001
Scaleideo	0.06	[0.05, 0.06]	13.99	58,540	< .001
Sexmale	-0.02	[-0.03, 0.00]	-2.52	58,540	.012
Age	0.00	[0.00, 0.00]	7.91	58,540	< .001
Edu	0.01	[0.00, 0.01]	2.93	58,540	.003
Income	0.02	[0.02, 0.03]	11.13	58,540	< .001
Gdppc	0.00	[0.00, 0.00]	-0.13	47	.894
Gini	-0.01	[-0.02, 0.01]	-0.82	47	.417

Just the US

(#tab:unnamed-chunk-28)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.62	[-0.92, -0.33]	-4.09	2072	< .001
ScaleEZS	-0.05	[-0.10, -0.01]	-2.31	2072	.021
Scaleideo	-0.12	[-0.16, -0.08]	-5.31	2072	< .001
Sexmale	-0.08	[-0.17, 0.00]	-1.93	2072	.054
Age	0.00	[0.00, 0.01]	2.15	2072	.032
Edu	0.04	[0.00, 0.07]	2.20	2072	.028
Income	0.05	[0.02, 0.07]	3.85	2072	< .001

Linear model: EZS -> Confidence in universities

Whole sample

(#tab:unnamed-chunk-29)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.61	[-1.00, -0.21]	-2.97	58,203	.003
ScaleEZS	-0.04	[-0.05, -0.04]	-10.42	58,203	< .001
Scaleideo	0.03	[0.02, 0.04]	6.92	58,203	< .001
Sexmale	0.01	[-0.01, 0.02]	0.95	58,203	.341
Age	0.00	[0.00, 0.00]	4.99	58,203	< .001
Edu	0.03	[0.02, 0.03]	12.97	58,203	< .001
Income	0.02	[0.01, 0.02]	7.32	58,203	< .001
Gdppc	0.00	[0.00, 0.00]	0.78	47	.441
Gini	0.01	[0.00, 0.02]	1.53	47	.132

Just the US

(#tab:unnamed-chunk-30)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.41	[-0.71, -0.12]	-2.77	2065	.006
ScaleEZS	-0.01	[-0.05, 0.03]	-0.46	2065	.648
Scaleideo	-0.20	[-0.25, -0.16]	-9.25	2065	< .001
Sexmale	-0.11	[-0.19, -0.03]	-2.60	2065	.009
Age	0.00	[-0.01, 0.00]	-3.06	2065	.002
Edu	0.03	[0.00, 0.07]	1.86	2065	.063
Income	0.08	[0.06, 0.10]	6.94	2065	< .001

Linear model: EZS -> Confidence in major companies

Whole sample

(#tab:unnamed-chunk-31)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.39	[-0.75, -0.02]	-2.07	58,025	.038
ScaleEZS	-0.04	[-0.05, -0.03]	-9.76	58,025	< .001
Scaleideo	0.07	[0.07, 0.08]	17.59	58,025	< .001
Sexmale	0.00	[-0.01, 0.02]	0.16	58,025	.870
Age	0.00	[0.00, 0.00]	-0.24	58,025	.813
Edu	0.01	[0.00, 0.01]	3.49	58,025	< .001
Income	0.03	[0.03, 0.04]	15.20	58,025	< .001
Gdppc	0.00	[0.00, 0.00]	-1.19	47	.238
Gini	0.01	[0.00, 0.02]	1.41	47	.164

Just the US

(#tab:unnamed-chunk-32)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	-0.06	[-0.35, 0.22]	-0.44	2066	.663
ScaleEZS	-0.12	[-0.16, -0.07]	-5.32	2066	< .001
Scaleideo	0.19	[0.15, 0.24]	8.98	2066	< .001
Sexmale	-0.04	[-0.12, 0.04]	-0.88	2066	.379
Age	0.00	[0.00, 0.00]	0.70	2066	.482
Edu	-0.06	[-0.09, -0.02]	-3.31	2066	.001
Income	0.09	[0.07, 0.12]	8.09	2066	< .001

Linear model: EZS -> Confidence in banks

Whole sample

(#tab:unnamed-chunk-33)

**

Term	\(\hat{\beta}\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.10	[-0.39, 0.58]	0.39	58,980	.696
ScaleEZS	-0.05	[-0.06, -0.04]	-11.81	58,980	< .001
Scaleideo	0.06	[0.05, 0.07]	15.74	58,980	< .001
Sexmale	-0.04	[-0.05, -0.02]	-5.04	58,980	< .001
Age	0.00	[0.00, 0.00]	-5.11	58,980	< .001
Edu	0.00	[-0.01, 0.00]	-0.98	58,980	.329
Income	0.03	[0.03, 0.03]	14.76	58,980	< .001
Gdppc	0.00	[0.00, 0.00]	-2.58	47	.013
Gini	0.00	[-0.01, 0.01]	-0.11	47	.912

Just the US

(#tab:unnamed-chunk-34)

**

Predictor	\(b\)	95% CI	\(t\)	\(\mathit{df}\)	\(p\)
Intercept	0.26	[-0.03, 0.56]	1.75	2065	.080
ScaleEZS	-0.09	[-0.13, -0.04]	-3.93	2065	< .001
Scaleideo	0.16	[0.12, 0.21]	7.39	2065	< .001
Sexmale	-0.20	[-0.29, -0.12]	-4.80	2065	< .001
Age	0.00	[0.00, 0.00]	-0.46	2065	.644
Edu	-0.05	[-0.08, -0.01]	-2.80	2065	.005
Income	0.05	[0.03, 0.07]	4.25	2065	< .001