Avances Multinivel LAPOP

Preparación de la base

#2008-2018
lapop2004_2018$democracia7 <- lapop2004_2018$ing4
lapop2004_2018$democracia_ord <- lapop2004_2018$pn4
lapop2004_2018$reduc_desigualdad <- lapop2004_2018$ros4

lapop2004_2018$country_f <- factor(lapop2004_2018$country, 
                                   labels = c("México", "Colombia", "Perú", 
                                              "Chile", "Uruguay", "Brasil", "Argentina"))

lapop2004_2018$sexo <- factor(lapop2004_2018$q1, labels = c("Varón", "Mujer"))

lapop2004_2018 <- lapop2004_2018 %>% 
  mutate(categoria_ocup = case_when((colocup4a <= 2 | ocup4a <= 2) & ocup1a == 3 ~ 1,
                                  (colocup4a <= 2 | ocup4a <= 2) & ocup1a == 1 ~ 2,
                                  (colocup4a <= 2 | ocup4a <= 2) & ocup1a == 2 ~ 3,
                                  (colocup4a <= 2 | ocup4a <= 2) & ocup1a == 4 ~ 4,
                                  (colocup4a == 3 |ocup4a == 3) | ocup1a == 5 ~ 5,
                                  colocup4a >= 4 |ocup4a >= 4 ~ 6),
         categoria_ocup_f = factor(categoria_ocup, labels = c("Patrón", "Asalariado público",
                                                          "Asalariado privado",
                                                          "Cuenta propia", "Desocupado",
                                                          "Inactivo")),
         ing_decil = case_when(wave == 2008 | wave == 2010 ~ q10,
                               wave == 2012 ~ q10new_12,
                               wave == 2014 ~ q10new_14,
                               wave == 2016 ~ q10new_16,
                               wave == 2018 ~ q10new_18),
         ideologia = car::recode(l1, "1=10; 2=9; 3=8; 4=7; 5=6; 6=5; 7=4; 8=3; 9=2; 10=1"))

#2018
lapop2004_2018$desempleados <- lapop2004_2018$redist3
lapop2004_2018$desempleados <- car::recode(lapop2004_2018$desempleados,
                                           "7=1;6=2;5=3;4=4;3=5;2=6;1=7")

lapop2004_2018$ayuda_pobres <- lapop2004_2018$redist1

lapop2004_2018 <- lapop2004_2018 %>% 
  mutate(redist2_inv = car::recode(redist2, "1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1"),
         impuestos_ricos = case_when(country == 8 ~ redist2_inv,
                                     TRUE ~ redist2a),
         urbano = factor(ur, labels = c("Urbano", "Rural")),
         informal = car::recode(formal, "1=0; 2=1"),
         formal_f = factor(formal, labels = c("formal", "informal")),
         formal_estado = case_when(formal == 1 ~ 1,
                                   formal == 2 ~ 2,
                                   categoria_ocup >= 5 ~ 3,
                                   TRUE ~ NA_real_),
         formal_estado = factor(formal_estado, labels = c("Formal", "Informal",
                                                          "No ocupados")),
         estatus_ocup = case_when(ocupoit <= 2 ~ 1,
                                  ocupoit > 2 & ocupoit < 4 ~ 2,
                                  ocupoit %in% c(5, 7, 8, 10) ~ 3,
                                  ocupoit %in% c(6, 9) ~ 4,
                                  categoria_ocup >= 5 ~ 5,
                                  TRUE ~ NA_real_),
         estatus_ocup_f = factor(estatus_ocup, labels = c("Directivos-Profesionales",
                                                          "Técnicos-administrativos-vendedores",
                                                          "Trabajadores manuales calificados",
                                                          "Trabajadores manuales no calificados",
                                                          "No ocupados")))

#Pegado bases

lapop2004_2018 <- lapop2004_2018 %>% 
  left_join(agregados, by = c("country_f", "wave"))

rm(paises_brecha, paises_desempleo, paises_empleopub, paises_informalidad)

Casos perdidos variables objetivo

Data Frame Summary

lapop2004_2018

Dimensions: 66771 x 2
Duplicates: 66707

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	democracia7 [numeric]	Mean (sd) : 5.2 (1.7) min ≤ med ≤ max: 1 ≤ 5 ≤ 7 IQR (CV) : 3 (0.3)	1 : 2556 ( 4.0% ) 2 : 2328 ( 3.6% ) 3 : 5070 ( 7.9% ) 4 : 10045 ( 15.7% ) 5 : 12021 ( 18.8% ) 6 : 11202 ( 17.5% ) 7 : 20796 ( 32.5% )		2753 (4.1%)
2	reduc_desigualdad [numeric]	Mean (sd) : 5.7 (1.6) min ≤ med ≤ max: 1 ≤ 6 ≤ 7 IQR (CV) : 2 (0.3)	1 : 1931 ( 3.0% ) 2 : 1659 ( 2.5% ) 3 : 2978 ( 4.6% ) 4 : 6419 ( 9.8% ) 5 : 9795 ( 15.0% ) 6 : 12511 ( 19.2% ) 7 : 29897 ( 45.9% )		1581 (2.4%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-09-06

Democracia 7 categorías x onda

	2008	2010	2012	2014	2016	2018	NA
1	3.08	3.31	2.74	3.27	5.74	4.61	NaN
2	3.06	3.26	2.94	2.96	4.92	3.61	NaN
3	6.20	6.58	7.31	7.31	9.52	8.47	NaN
4	12.52	13.05	13.31	13.52	18.58	18.93	NaN
5	15.59	16.29	16.97	17.98	19.62	21.45	NaN
6	19.58	17.81	18.66	15.75	14.37	14.75	NaN
7	34.71	34.26	34.30	34.90	24.27	25.13	NaN
NA	5.25	5.43	3.77	4.28	2.98	3.05	NaN

Democracia 7 categorías x educación

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	NA
1	5.14	6.81	4.44	4.20	3.72	4.81	3.92	4.27	4.39	4.47	3.96	4.03	3.20	3.11	2.85	2.67	2.62	2.26	2.94	10.34
2	4.64	5.40	5.00	4.35	4.00	4.50	3.07	3.91	3.73	3.47	2.98	4.23	2.70	3.38	3.02	2.18	2.45	2.17	2.88	7.13
3	7.30	8.10	8.39	8.07	8.40	8.28	7.44	7.59	7.72	8.23	7.27	9.47	6.79	7.15	6.94	4.64	6.78	4.11	5.28	10.57
4	12.69	11.97	12.82	13.38	12.53	14.77	14.32	13.00	15.79	17.25	14.10	18.23	15.30	14.70	15.93	11.87	13.12	10.99	13.18	17.93
5	15.26	15.73	15.32	17.15	18.03	17.86	16.36	17.01	19.46	20.10	16.63	20.35	18.45	19.01	18.65	15.41	15.95	14.41	15.38	19.08
6	12.11	13.38	16.85	16.67	18.39	17.24	17.05	16.10	16.92	15.27	15.43	16.74	17.38	17.06	18.82	16.72	18.93	18.94	14.25	11.49
7	26.78	25.00	25.24	26.71	26.84	24.53	31.73	33.08	27.34	27.60	36.15	24.63	33.32	33.72	32.69	45.52	39.19	46.33	45.22	14.94
NA	16.09	13.62	11.94	9.46	8.08	8.00	6.12	5.04	4.65	3.62	3.47	2.32	2.86	1.87	1.10	0.99	0.94	0.79	0.87	8.51

Democracia 7 categorías x ocupación

	Patrón	Asalariado público	Asalariado privado	Cuenta propia	Desocupado	Inactivo	NA
1	4.40	2.71	3.26	4.22	4.95	3.82	5.33
2	3.60	2.81	2.85	3.92	4.09	3.59	3.13
3	7.45	6.35	6.75	8.15	9.10	7.61	9.72
4	13.37	12.84	14.84	15.84	18.21	14.52	15.52
5	15.37	16.41	17.58	18.45	20.37	17.89	18.81
6	16.41	17.15	17.48	16.57	15.12	16.92	12.07
7	37.47	40.01	34.63	28.87	24.39	30.11	26.02
NA	1.92	1.73	2.62	3.99	3.77	5.54	9.40

Democracia 7 categorías x ingresos (decil)

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	NA
1	8.25	5.75	4.96	4.06	3.99	3.76	3.46	3.43	3.20	2.73	2.87	3.48	3.36	4.01	3.42	3.35	3.43	3.24
2	6.53	4.29	3.73	4.13	3.99	3.39	3.60	3.43	3.31	2.95	3.09	2.73	2.83	2.82	2.99	3.01	3.02	3.19
3	9.11	9.15	8.66	8.57	7.91	7.91	8.37	7.87	6.65	7.53	6.66	8.52	7.52	7.12	5.75	6.30	6.16	6.17
4	17.86	16.26	15.25	15.13	15.11	16.84	15.13	15.57	15.12	15.47	14.22	15.87	16.99	16.53	15.01	13.29	10.71	13.41
5	16.38	17.51	19.42	18.46	17.85	18.55	18.68	18.07	18.46	17.92	18.81	19.73	19.78	17.53	19.48	16.35	14.07	16.49
6	12.07	14.38	15.74	16.29	17.79	18.36	18.64	17.71	17.16	17.45	17.88	15.35	16.26	16.77	16.20	17.89	16.87	16.32
7	22.29	24.58	26.15	27.83	29.51	28.22	29.24	31.18	33.37	33.40	34.33	31.97	31.19	33.35	35.96	38.39	44.97	33.99
NA	7.51	8.07	6.08	5.52	3.85	2.98	2.88	2.74	2.74	2.54	2.14	2.35	2.06	1.86	1.19	1.42	0.77	7.19

Reducción de la desigualdad x onda

	2008	2010	2012	2014	2016	2018	NA
1	2.01	1.64	1.58	2.98	4.39	4.63	NaN
2	1.74	1.76	1.41	2.92	3.64	3.35	NaN
3	3.16	3.19	2.98	4.72	5.74	6.88	NaN
4	7.01	7.16	8.54	9.88	11.54	13.46	NaN
5	12.40	12.96	14.83	14.89	15.68	17.23	NaN
6	20.15	20.02	20.50	17.25	17.71	16.85	NaN
7	49.80	50.26	47.97	44.63	39.78	36.50	NaN
NA	3.74	3.01	2.18	2.73	1.53	1.10	NaN

Reducción desigualdad x educación

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	NA
1	5.31	5.16	4.03	3.73	3.27	3.16	3.12	3.36	2.84	3.10	2.58	2.53	2.24	2.27	2.46	2.38	2.42	2.36	4.15	8.28
2	2.57	3.52	3.71	3.20	2.82	2.89	2.62	2.04	2.31	2.56	2.69	2.46	1.83	2.27	2.26	2.47	2.51	1.62	2.88	7.59
3	4.56	5.05	5.08	4.49	4.50	4.43	4.17	4.02	4.28	4.34	3.63	5.02	3.92	4.58	4.58	4.35	5.19	4.11	5.35	5.52
4	7.30	6.34	7.34	9.99	8.58	8.86	8.41	9.16	7.72	9.74	8.54	10.59	9.89	9.37	11.52	9.65	10.29	10.25	13.44	14.94
5	13.10	12.68	12.98	12.04	11.90	13.47	13.40	13.87	13.90	14.78	13.75	16.51	16.04	15.37	16.30	14.13	15.07	13.58	14.38	14.25
6	14.59	16.78	18.79	18.06	17.21	18.83	17.21	17.38	18.52	17.48	17.85	20.19	19.00	20.97	20.88	19.80	20.85	18.66	17.06	12.87
7	42.04	42.14	41.53	42.90	46.50	45.04	48.18	47.06	48.17	46.16	48.63	41.33	45.36	44.47	41.45	46.01	42.94	48.50	41.54	30.34
NA	10.53	8.33	6.53	5.59	5.22	3.33	2.89	3.10	2.26	1.86	2.33	1.38	1.72	0.71	0.56	1.19	0.74	0.92	1.20	6.21

Reducción desigualdad x ocupación

	Patrón	Asalariado público	Asalariado privado	Cuenta propia	Desocupado	Inactivo	NA
1	4.16	2.36	2.38	3.16	3.05	2.96	5.17
2	2.72	1.91	2.16	2.89	2.39	2.54	2.35
3	5.44	3.74	4.13	4.58	4.60	4.60	5.80
4	10.89	8.69	9.30	10.16	9.04	9.66	10.97
5	14.97	14.11	15.10	14.67	14.27	14.63	13.95
6	20.26	20.11	18.92	18.77	18.04	18.51	15.67
7	40.91	47.69	46.62	43.66	46.94	43.72	40.44
NA	0.64	1.40	1.40	2.12	1.67	3.38	5.64

Reducción desigualdad x ingresos (decil)

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	NA
1	4.56	3.98	2.43	3.09	2.54	2.63	2.45	2.19	2.33	2.01	3.22	2.45	2.47	2.91	2.66	3.29	4.56	3.34
2	4.80	3.31	2.64	2.15	2.19	2.59	2.26	2.36	2.36	2.64	2.26	2.97	2.35	2.48	2.52	2.44	2.92	2.10
3	5.91	4.16	4.19	3.89	4.07	4.19	4.12	4.25	4.64	4.49	5.39	3.86	4.98	4.25	4.89	4.32	5.36	4.97
4	11.45	8.88	8.01	8.31	8.74	9.19	9.41	8.99	10.42	10.45	9.60	10.69	11.17	9.89	10.40	11.98	11.59	10.26
5	12.44	12.17	13.40	14.35	14.06	14.79	15.92	14.40	14.60	15.13	14.50	15.11	16.18	17.20	17.10	16.41	15.60	14.64
6	14.78	16.10	18.85	18.91	19.17	20.75	19.64	20.48	19.61	20.09	20.62	18.27	19.78	19.35	18.76	17.49	17.42	16.54
7	41.75	47.17	47.05	46.73	47.19	44.10	44.54	45.32	44.34	44.22	43.29	45.53	42.03	42.76	42.61	43.50	41.95	43.30
NA	4.31	4.23	3.42	2.57	2.04	1.76	1.64	2.00	1.70	0.97	1.12	1.13	1.05	1.15	1.05	0.57	0.62	4.85

Data Frame Summary

lapop2018

Dimensions: 11009 x 3
Duplicates: 10569

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	desempleados [numeric]	Mean (sd) : 3.4 (2) min ≤ med ≤ max: 1 ≤ 3 ≤ 7 IQR (CV) : 3 (0.6)	1 : 2549 ( 23.3% ) 2 : 1612 ( 14.7% ) 3 : 1897 ( 17.3% ) 4 : 1579 ( 14.4% ) 5 : 1167 ( 10.7% ) 6 : 908 ( 8.3% ) 7 : 1222 ( 11.2% )		75 (0.7%)
2	impuestos_ricos [numeric]	Mean (sd) : 4.3 (1.9) min ≤ med ≤ max: 1 ≤ 4 ≤ 7 IQR (CV) : 3 (0.4)	1 : 1268 ( 11.8% ) 2 : 861 ( 8.0% ) 3 : 1306 ( 12.2% ) 4 : 2252 ( 21.0% ) 5 : 1962 ( 18.3% ) 6 : 1253 ( 11.7% ) 7 : 1838 ( 17.1% )		269 (2.4%)
3	ayuda_pobres [numeric]	Mean (sd) : 5.5 (1.8) min ≤ med ≤ max: 1 ≤ 6 ≤ 7 IQR (CV) : 3 (0.3)	1 : 505 ( 4.6% ) 2 : 379 ( 3.5% ) 3 : 640 ( 5.8% ) 4 : 1294 ( 11.8% ) 5 : 1501 ( 13.7% ) 6 : 1734 ( 15.8% ) 7 : 4893 ( 44.7% )		63 (0.6%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-09-06

Desempleados x educación

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	NA
1	26.92	29.41	21.48	26.55	28.33	27.59	25.54	26.10	28.64	28.10	23.86	21.17	24.90	18.55	18.33	17.15	15.38	18.82	17.16	19.78
2	15.38	13.73	17.45	18.18	14.68	17.00	17.63	14.09	15.08	16.94	14.39	13.96	13.03	12.53	15.68	12.47	14.17	12.47	12.19	19.78
3	13.85	12.75	18.12	14.91	13.99	18.47	19.42	15.24	15.93	19.42	14.96	18.42	18.26	18.55	20.77	14.70	16.60	12.02	14.00	14.29
4	10.77	9.80	10.07	12.36	11.95	9.61	11.39	12.24	12.37	11.98	16.10	14.95	16.06	15.66	17.72	16.93	15.38	16.55	18.06	17.58
5	8.46	8.82	10.74	10.55	10.92	10.59	7.55	9.70	9.15	7.85	8.90	11.21	10.58	11.57	11.81	15.14	14.17	14.29	11.29	8.79
6	6.15	6.86	8.05	6.55	6.83	5.91	6.83	8.55	6.10	7.23	8.90	7.73	7.74	8.19	7.94	8.69	11.74	14.51	13.54	9.89
7	15.38	16.67	10.74	8.73	11.95	9.85	11.03	13.63	12.37	7.54	11.93	12.04	8.90	14.70	7.54	14.92	11.94	11.11	13.32	8.79
NA	3.08	1.96	3.36	2.18	1.37	0.99	0.60	0.46	0.34	0.93	0.95	0.52	0.52	0.24	0.20	0.00	0.61	0.23	0.45	1.10

Desempleados x ocupación

	Patrón	Asalariado público	Asalariado privado	Cuenta propia	Desocupado	Inactivo	NA
1	28.08	22.09	23.30	24.52	22.16	22.42	25.93
2	16.54	12.29	14.57	14.83	13.23	15.15	19.26
3	16.15	15.95	17.88	18.43	14.85	17.32	14.81
4	15.38	15.95	15.48	14.06	13.15	13.96	13.33
5	10.77	11.24	10.83	9.34	9.33	11.46	9.63
6	5.77	11.24	8.01	7.72	8.12	8.29	8.89
7	7.31	11.11	9.78	10.37	18.34	10.41	6.67
NA	0.00	0.13	0.14	0.73	0.81	1.00	1.48

Desempleados x ingresos (decil)

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	NA
1	27.35	27.35	25.75	25.76	26.87	20.29	23.71	19.06	21.72	24.47	24.80	21.12	22.51	19.59	20.62	22.84	20.24	22.76
2	12.56	15.15	15.45	13.96	13.67	14.17	17.26	13.81	13.10	16.18	15.76	14.15	15.01	13.86	16.32	13.53	13.38	14.53
3	13.45	16.18	17.34	15.40	14.94	19.48	17.58	19.41	18.74	17.53	16.38	19.57	19.70	19.96	16.49	15.96	15.09	16.45
4	8.52	11.91	12.06	12.81	11.13	15.94	13.23	18.36	16.75	16.96	17.16	15.31	14.26	14.97	13.23	15.08	15.95	13.70
5	10.31	8.82	9.67	10.50	10.17	11.43	10.32	10.14	10.28	8.48	9.83	11.43	14.07	13.68	10.48	9.09	13.21	10.05
6	9.42	7.65	7.54	8.06	6.36	8.53	6.94	9.27	7.46	7.32	6.55	8.91	6.57	8.32	11.17	10.64	10.46	8.72
7	15.25	11.91	11.81	12.95	15.90	8.70	10.48	9.79	11.61	9.06	9.20	8.72	7.69	9.43	11.34	11.97	11.49	12.29
NA	3.14	1.03	0.38	0.58	0.95	1.45	0.48	0.17	0.33	0.00	0.31	0.78	0.19	0.18	0.34	0.89	0.17	1.50

Ayuda pobres x educación

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	NA
1	11.54	5.88	5.37	3.64	3.75	3.20	5.04	3.93	4.24	4.55	7.58	2.65	4.26	3.13	3.87	6.01	5.47	7.71	7.67	3.30
2	2.31	5.88	1.34	0.73	1.71	1.48	3.84	2.08	2.88	2.79	3.98	2.54	3.68	3.13	4.07	6.90	6.28	5.44	4.51	4.40
3	3.08	7.84	3.36	5.09	2.73	2.22	3.60	5.31	4.07	4.55	5.68	4.26	6.52	8.67	8.15	9.80	7.49	9.98	12.19	3.30
4	9.23	6.86	8.72	8.00	4.10	3.69	7.91	6.24	6.95	9.50	13.64	8.72	16.00	16.39	16.50	18.04	16.80	20.18	20.09	8.79
5	9.23	3.92	8.05	9.82	9.90	10.84	11.87	11.55	11.02	11.16	10.23	14.17	14.52	15.90	14.66	18.04	19.64	20.18	17.83	16.48
6	13.08	9.80	15.44	13.82	15.70	14.78	17.51	15.47	14.41	16.63	13.26	16.81	15.29	16.63	18.74	13.81	18.02	12.47	15.58	15.38
7	50.00	58.82	57.05	57.82	61.43	63.55	48.80	55.20	56.10	50.41	45.27	50.34	39.29	35.90	33.81	26.50	25.71	23.13	21.90	47.25
NA	1.54	0.98	0.67	1.09	0.68	0.25	1.44	0.23	0.34	0.41	0.38	0.52	0.45	0.24	0.20	0.89	0.61	0.91	0.23	1.10

Ayuda pobres x ocupación

	Patrón	Asalariado público	Asalariado privado	Cuenta propia	Desocupado	Inactivo	NA
1	4.62	5.36	5.80	4.59	3.81	4.05	5.19
2	3.85	5.49	3.98	3.34	3.08	2.98	2.22
3	7.69	7.32	7.09	5.49	4.22	5.48	4.44
4	11.92	14.77	14.09	10.93	10.15	11.01	10.37
5	16.92	17.12	14.09	13.80	11.85	12.96	14.81
6	15.38	13.99	14.81	15.65	14.69	17.03	12.59
7	39.23	35.42	39.98	45.48	51.87	45.76	48.15
NA	0.38	0.52	0.14	0.73	0.32	0.74	2.22

Ayuda pobres x ingresos (decil)

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	NA
1	7.17	2.94	3.52	3.17	4.77	4.35	3.55	4.55	4.31	4.24	5.15	4.84	3.94	4.81	6.70	5.54	6.00	5.15
2	2.24	2.35	2.51	2.30	1.91	2.74	2.42	3.50	3.98	3.66	3.28	3.49	3.19	4.81	3.61	5.99	6.69	3.82
3	2.69	3.68	2.89	6.33	4.29	4.51	4.52	5.77	5.14	6.17	6.55	5.43	7.69	7.58	7.90	8.65	9.61	5.81
4	6.73	6.18	8.17	8.92	8.11	10.47	12.26	11.71	11.28	14.07	11.86	13.37	14.26	14.05	14.26	19.96	17.50	11.46
5	8.52	7.94	10.93	10.07	13.83	14.17	14.84	12.59	10.78	14.07	15.44	16.28	16.70	16.64	16.15	14.19	19.55	13.29
6	12.11	15.59	16.71	17.70	15.26	16.43	17.58	14.86	15.75	17.53	14.98	16.09	17.45	15.90	15.98	17.29	11.15	14.37
7	60.09	60.44	54.90	50.94	51.35	46.22	44.19	46.50	47.76	40.27	42.75	40.50	36.40	35.86	35.40	27.94	28.64	44.85
NA	0.45	0.88	0.38	0.58	0.48	1.13	0.65	0.52	1.00	0.00	0.00	0.00	0.38	0.37	0.00	0.44	0.86	1.25

Impuestos ricos x educación

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	NA
1	16.15	17.65	12.75	13.09	13.99	14.78	10.55	13.16	12.20	11.57	12.69	13.03	9.03	9.16	8.35	10.47	9.92	11.11	11.74	10.99
2	11.54	5.88	8.05	8.36	8.53	9.36	7.31	6.00	7.63	6.10	8.71	10.07	5.55	5.30	7.94	6.90	9.72	7.48	9.93	8.79
3	5.38	11.76	14.09	13.45	10.58	12.56	10.79	9.93	9.15	9.92	13.45	14.32	10.00	12.05	13.65	11.80	10.73	12.24	16.03	15.38
4	15.38	11.76	17.45	18.91	14.68	15.52	15.35	18.01	19.15	20.87	19.70	19.93	23.68	23.37	24.64	22.72	25.71	19.95	24.83	16.48
5	16.92	9.80	13.42	11.27	15.02	14.53	20.02	17.32	15.93	18.90	16.48	16.71	20.71	23.13	17.31	18.04	17.61	21.54	14.90	18.68
6	9.23	9.80	10.74	12.00	10.58	11.82	12.83	12.93	13.90	12.09	8.71	10.33	12.71	11.08	13.85	9.80	9.11	10.88	9.48	6.59
7	20.00	24.51	18.12	18.55	20.14	18.23	19.30	21.02	20.17	18.18	17.42	14.06	15.81	13.73	13.44	18.93	15.18	15.19	11.96	19.78
NA	5.38	8.82	5.37	4.36	6.48	3.20	3.84	1.62	1.86	2.38	2.84	1.56	2.52	2.17	0.81	1.34	2.02	1.59	1.13	3.30

Impuestos ricos x ocupación

	Patrón	Asalariado público	Asalariado privado	Cuenta propia	Desocupado	Inactivo	NA
1	9.23	11.24	10.64	12.39	13.31	11.05	14.07
2	8.85	6.80	6.71	8.02	8.04	8.34	7.41
3	13.46	11.50	11.98	11.40	11.69	12.17	8.89
4	23.46	21.96	21.52	21.30	19.89	19.34	14.81
5	20.00	18.30	19.32	16.89	17.37	17.53	17.04
6	7.31	11.63	11.89	10.89	9.82	12.01	13.33
7	17.31	16.99	16.78	17.36	17.53	15.84	20.00
NA	0.38	1.57	1.15	1.76	2.35	3.72	4.44

Impuestos ricos x ingresos (decil)

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	NA
1	17.49	15.44	11.56	11.08	13.67	9.98	10.00	9.27	8.96	11.75	11.70	8.91	7.88	11.09	13.92	12.42	13.21	11.63
2	13.45	8.24	7.29	9.35	9.06	7.41	6.45	5.94	6.80	5.59	8.11	9.11	6.57	7.02	9.79	8.87	9.61	6.64
3	8.52	11.62	12.81	11.22	11.61	11.59	11.13	12.06	10.28	11.95	11.08	10.47	12.76	13.49	11.51	14.19	14.41	11.63
4	15.70	15.00	18.47	20.00	17.17	18.36	21.94	24.30	21.56	22.35	21.68	25.97	20.83	22.00	20.79	24.83	23.50	17.69
5	8.52	15.74	16.33	16.26	14.94	21.58	17.74	20.10	21.23	19.65	17.63	18.02	22.33	19.04	17.35	17.52	17.50	16.61
6	14.35	10.29	11.31	11.37	12.08	13.20	13.23	10.84	12.77	11.37	11.70	10.47	13.32	10.91	12.03	7.32	9.09	10.71
7	17.94	20.15	19.72	17.55	19.24	15.94	17.26	16.43	15.75	15.99	17.32	15.70	14.45	14.60	13.06	13.30	11.49	19.27
NA	4.04	3.53	2.51	3.17	2.23	1.93	2.26	1.05	2.65	1.35	0.78	1.36	1.88	1.85	1.55	1.55	1.20	5.81

Se observa que para las variables objetivo de impuestos, ayuda a la pobreza y desempleo no existiría un sesgo importante por parte de los grupos más desfavorecidos en educación, ingresos y trabajo. Por tal motivo, esos casos perdidos pueden ser no considerados en el análisis.

Se realiza un análisis de correspondencias múltiples para observar el vínculo entre la variable de democracia y reducción de la desigualdad. De este surge que los grupos más desfavorecidos son los que menos reponden a dichas preguntas.

Se opta entonces por imputar a los casos sin respuesta en las variables de democracia y reducción de la desigualdad, utilizando la técnica de hot deck. Esta realiza una imputación aleatoria, brindándole un valor válido a un caso con valor faltante. Para ello, la imputación se hará al interior de los grupos de ingresos y posteriormente, en el caso los grupos con ingresos faltantes, se utilizará el nivel educativo.

Imputación variables objetivo

#1) Random Hot Deck para la variable democracia7 -----

lapop2004_2018$democracia7_imp <- lapop2004_2018$democracia7

set.seed(971986)
lapop2004_2018 <- lapop2004_2018 %>%
  hotdeck(variable = "democracia7_imp",
          domain_var = "ing_decil",
          imp_suffix = "check")

print(lapop2004_2018 %>% 
  select(democracia7, democracia7_imp) %>% 
  summarytools::dfSummary(plain.ascii  = FALSE, 
          style        = "grid", 
          graph.magnif = 0.75, 
          valid.col    = FALSE),
  method = "render")

Data Frame Summary

lapop2004_2018

Dimensions: 66771 x 2
Duplicates: 66757

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	democracia7 [numeric]	Mean (sd) : 5.2 (1.7) min ≤ med ≤ max: 1 ≤ 5 ≤ 7 IQR (CV) : 3 (0.3)	1 : 2556 ( 4.0% ) 2 : 2328 ( 3.6% ) 3 : 5070 ( 7.9% ) 4 : 10045 ( 15.7% ) 5 : 12021 ( 18.8% ) 6 : 11202 ( 17.5% ) 7 : 20796 ( 32.5% )		2753 (4.1%)
2	democracia7_imp [numeric]	Mean (sd) : 5.2 (1.7) min ≤ med ≤ max: 1 ≤ 5 ≤ 7 IQR (CV) : 3 (0.3)	1 : 2677 ( 4.0% ) 2 : 2427 ( 3.6% ) 3 : 5305 ( 7.9% ) 4 : 10497 ( 15.7% ) 5 : 12569 ( 18.8% ) 6 : 11666 ( 17.5% ) 7 : 21630 ( 32.4% )		0 (0.0%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-09-06

#2) Random Hot Deck para la variable reduc_desigualdad -----
lapop2004_2018$reduc_desigualdad_imp <- lapop2004_2018$reduc_desigualdad

set.seed(971986)
lapop2004_2018 <- lapop2004_2018 %>%
  hotdeck(variable = "reduc_desigualdad_imp",
          domain_var = "ing_decil",
          imp_suffix = "check")

print(lapop2004_2018 %>% 
  select(reduc_desigualdad, reduc_desigualdad_imp) %>% 
  summarytools::dfSummary(plain.ascii  = FALSE, 
          style        = "grid", 
          graph.magnif = 0.75, 
          valid.col    = FALSE),
  method = "render")

Data Frame Summary

lapop2004_2018

Dimensions: 66771 x 2
Duplicates: 66757

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reduc_desigualdad [numeric]	Mean (sd) : 5.7 (1.6) min ≤ med ≤ max: 1 ≤ 6 ≤ 7 IQR (CV) : 2 (0.3)	1 : 1931 ( 3.0% ) 2 : 1659 ( 2.5% ) 3 : 2978 ( 4.6% ) 4 : 6419 ( 9.8% ) 5 : 9795 ( 15.0% ) 6 : 12511 ( 19.2% ) 7 : 29897 ( 45.9% )		1581 (2.4%)
2	reduc_desigualdad_imp [numeric]	Mean (sd) : 5.7 (1.6) min ≤ med ≤ max: 1 ≤ 6 ≤ 7 IQR (CV) : 2 (0.3)	1 : 1975 ( 3.0% ) 2 : 1698 ( 2.5% ) 3 : 3048 ( 4.6% ) 4 : 6553 ( 9.8% ) 5 : 10030 ( 15.0% ) 6 : 12816 ( 19.2% ) 7 : 30651 ( 45.9% )		0 (0.0%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-09-06

Casos perdidos variables predictoras

print(lapop2004_2018 %>% 
  select(ideologia) %>% 
  summarytools::dfSummary(plain.ascii  = FALSE, 
          style        = "grid", 
          graph.magnif = 0.75, 
          valid.col    = FALSE),
  method = "render")

Data Frame Summary

lapop2004_2018

Dimensions: 66771 x 1
Duplicates: 66760

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ideologia [numeric]	Mean (sd) : 5.5 (2.5) min ≤ med ≤ max: 1 ≤ 6 ≤ 10 IQR (CV) : 3 (0.4)	1 : 4863 ( 8.6% ) 2 : 2363 ( 4.2% ) 3 : 5310 ( 9.3% ) 4 : 4844 ( 8.5% ) 5 : 7295 ( 12.8% ) 6 : 14855 ( 26.1% ) 7 : 5318 ( 9.4% ) 8 : 4989 ( 8.8% ) 9 : 2380 ( 4.2% ) 10 : 4594 ( 8.1% )		9960 (14.9%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-09-06

kable(round(prop.table(table(lapop2004_2018$ideologia, lapop2004_2018$wave, 
                 useNA = "always"), margin = 2)*100, digits = 2),
      format = "html", caption = "Ideología x onda") %>% 
  kable_styling()

Ideología x onda

	2008	2010	2012	2014	2016	2018	NA
1	6.25	5.88	7.18	7.23	7.82	9.37	NaN
2	3.99	3.50	3.50	3.60	3.26	3.43	NaN
3	8.71	8.13	7.68	7.40	7.54	8.28	NaN
4	8.18	8.02	6.96	6.32	6.56	7.48	NaN
5	14.95	12.26	11.60	8.84	9.10	8.97	NaN
6	20.57	20.28	22.14	22.05	24.05	24.33	NaN
7	7.60	7.79	7.52	7.55	8.85	8.37	NaN
8	6.93	6.80	6.68	7.33	8.77	8.20	NaN
9	2.93	3.31	3.12	3.16	4.59	4.15	NaN
10	4.55	5.24	6.26	6.93	9.33	8.78	NaN
NA	15.32	18.79	17.36	19.59	10.14	8.64	NaN

kable(round(prop.table(table(lapop2004_2018$ideologia, lapop2004_2018$ing_decil, 
                 useNA = "always"), margin = 2)*100, digits = 2),
      format = "html", caption = "Ideología x ingreso") %>% 
  kable_styling()

Ideología x ingreso

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	NA
1	9.98	9.93	7.67	7.70	7.82	6.80	6.79	6.88	7.34	6.43	6.63	7.77	6.03	6.35	5.99	7.38	7.51	6.64
2	4.80	4.09	3.54	4.10	3.61	3.87	3.67	3.78	3.51	3.74	3.38	3.44	3.80	2.58	2.66	3.07	2.99	3.04
3	7.51	7.78	8.11	7.79	7.65	8.19	8.22	8.53	7.95	7.88	8.19	8.29	7.73	8.31	8.79	8.63	8.75	7.00
4	4.68	6.46	6.93	7.17	7.87	7.89	7.05	7.27	7.66	7.63	6.95	6.17	7.12	8.22	7.46	8.35	8.16	6.88
5	7.64	9.77	11.05	11.31	11.59	12.12	11.92	11.68	11.69	9.98	11.28	10.31	10.19	9.89	12.11	10.45	10.82	9.98
6	19.58	17.07	20.25	20.25	22.37	22.40	22.95	22.73	22.66	23.89	24.10	24.11	26.17	24.94	25.70	26.52	23.36	21.49
7	6.40	6.98	7.27	7.70	7.05	8.56	8.63	8.75	7.83	8.88	9.44	8.90	8.82	8.79	9.79	7.27	9.04	6.76
8	6.53	7.09	6.72	7.32	7.62	6.78	7.27	7.65	8.49	8.47	8.61	8.29	7.32	8.70	8.12	8.23	11.15	5.56
9	5.17	4.20	3.21	3.99	3.57	3.52	3.12	3.51	3.02	4.52	4.11	3.30	3.64	3.92	3.47	3.80	4.34	2.66
10	10.84	7.85	6.65	5.69	6.20	6.45	7.05	6.80	8.47	7.28	6.89	7.44	8.25	7.41	6.60	8.35	8.16	5.47
NA	16.87	18.77	18.61	16.97	14.65	13.43	13.32	12.42	11.37	11.30	10.42	12.01	10.92	10.89	9.31	7.95	5.72	24.52

kable(round(prop.table(table(lapop2004_2018$ideologia, lapop2004_2018$ed, 
                 useNA = "always"), margin = 2)*100, digits = 2),
      format = "html", caption = "Ideología x educacion") %>% 
  kable_styling()

Ideología x educacion

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	NA
1	16.00	14.91	14.19	13.14	11.63	12.54	8.78	7.48	6.96	7.32	6.27	6.50	4.94	4.53	4.48	4.44	4.22	4.94	5.35	10.57
2	4.31	5.40	5.48	5.73	4.90	5.22	4.08	3.83	3.65	3.73	2.82	3.47	2.47	3.38	2.06	3.00	2.92	3.23	2.54	3.22
3	8.04	7.51	7.58	8.27	8.76	9.62	8.22	7.78	7.72	8.56	6.81	8.18	6.80	6.97	8.16	7.89	8.46	7.76	9.16	6.90
4	5.89	6.22	5.56	6.74	6.72	7.01	6.32	7.59	5.73	7.00	7.21	7.54	7.02	8.26	8.53	8.05	9.17	8.36	8.03	6.90
5	7.46	7.28	9.60	8.27	8.63	9.28	9.79	9.68	9.61	9.42	10.69	11.90	11.80	12.17	13.84	12.53	14.10	12.79	11.17	9.89
6	11.77	14.20	13.47	16.44	15.08	14.91	19.14	20.01	20.49	21.43	23.35	23.53	26.91	28.57	27.38	25.80	25.80	24.53	25.28	16.09
7	2.49	3.29	4.52	5.40	6.86	6.25	7.48	7.37	7.43	8.05	8.54	8.53	8.22	8.17	8.66	8.96	9.79	10.81	11.77	7.59
8	3.57	4.11	5.16	4.49	5.99	5.19	7.44	6.90	7.75	8.47	7.92	7.46	7.54	7.42	8.70	8.75	8.67	9.10	11.64	5.06
9	3.32	3.52	3.47	2.63	2.32	3.19	3.90	3.10	3.65	3.92	3.55	4.02	3.24	3.20	3.75	3.78	3.83	3.09	4.01	3.45
10	7.88	6.34	5.89	6.12	6.99	6.01	7.98	7.16	7.96	8.32	7.16	6.80	6.37	6.13	5.01	6.61	6.43	6.70	5.69	9.20
NA	29.27	27.23	25.08	22.79	22.12	20.78	16.88	19.09	19.04	13.76	15.68	12.06	14.67	11.20	9.43	10.19	6.61	8.68	5.35	21.15

#MCA
lapop2004_2018$ed_f <- factor(lapop2004_2018$ed, labels = c(0:18))
lapop2004_2018$ing_decil_f <- factor(lapop2004_2018$ing_decil, labels = c(0:16))
lapop2004_2018$ideologia_f <- factor(lapop2004_2018$ideologia, labels = c(1:10))

variables_mca <- lapop2004_2018 %>% 
  select(ideologia_f, ed_f, categoria_ocup_f, ing_decil_f)

mca2 <- MCA(variables_mca, ncp = 2, graph = F)

ggcloud_variables(mca2, vlab = F, shapes = T, shapesize = 2, points = "besth")

Los casos perdidos en la variable ideología se encuentran muy asociaciados al nivel educativo bajo y a los ingresos bajos. Nuevamente, como en el caso de las variables objetivo, lo mejor sería imputarlas según nivel económico, ya que está relacionada y no formará parte del modelo de regresión.

Data Frame Summary

lapop2004_2018

Dimensions: 66771 x 2
Duplicates: 66751

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ideologia [numeric]	Mean (sd) : 5.5 (2.5) min ≤ med ≤ max: 1 ≤ 6 ≤ 10 IQR (CV) : 3 (0.4)	1 : 4863 ( 8.6% ) 2 : 2363 ( 4.2% ) 3 : 5310 ( 9.3% ) 4 : 4844 ( 8.5% ) 5 : 7295 ( 12.8% ) 6 : 14855 ( 26.1% ) 7 : 5318 ( 9.4% ) 8 : 4989 ( 8.8% ) 9 : 2380 ( 4.2% ) 10 : 4594 ( 8.1% )		9960 (14.9%)
2	ideologia_imp [numeric]	Mean (sd) : 5.5 (2.5) min ≤ med ≤ max: 1 ≤ 6 ≤ 10 IQR (CV) : 3 (0.4)	1 : 5750 ( 8.6% ) 2 : 2791 ( 4.2% ) 3 : 6201 ( 9.3% ) 4 : 5663 ( 8.5% ) 5 : 8572 ( 12.8% ) 6 : 17539 ( 26.3% ) 7 : 6271 ( 9.4% ) 8 : 5780 ( 8.7% ) 9 : 2795 ( 4.2% ) 10 : 5409 ( 8.1% )		0 (0.0%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-09-06

Problema variable Tranferencias Condicionadas

Ayuda gobierno x Transferencias condicionadas. Chile 2016.

wf1	1	2	NA	Total
1	35.5%	8.7%	25.0%	11.7%
2	64.5%	91.0%	59.1%	87.7%
NA		0.2%	15.9%	0.6%
Total	100.0%	100.0%	100.0%	100.0%

Ayuda gobierno x Transferencias condicionadas. Todos los países 2016.

wf1	1	2	NA	Total
1	36.4%	5.5%	19.2%	12.0%
2	63.1%	94.3%	68.0%	87.6%
NA	0.6%	0.2%	12.8%	0.4%
Total	100.0%	100.0%	100.0%	100.0%

Las variables de Ayuda económica del gobierno y Transferencias condicionadas parecieran no apuntar a lo mismo. Del total de familias que recibió transferencias condicionadas, solo un 35,5% indicó declarar que recibió ayuda económica del gobierno.

Descriptivos

Tablas resumen

Característica	Total1	2008, N = 10,5731	2010, N = 11,9251	2012, N = 10,6661	2014, N = 10,6261	2016, N = 11,9721	2018, N = 11,0091
Acuerdo con democracia	5.24 (1.69)	5.45 (1.64)	5.39 (1.66)	5.41 (1.62)	5.37 (1.66)	4.87 (1.77)	5.00 (1.68)
Acuerdo con políticas de reducción de desigualdad	5.72 (1.58)	5.97 (1.43)	5.98 (1.40)	5.93 (1.38)	5.68 (1.61)	5.46 (1.73)	5.34 (1.73)
Desempleo como fenómeno voluntario	3.44 (2.00)	NA (NA)	NA (NA)	NA (NA)	NA (NA)	NA (NA)	3.44 (2.00)
Los gobiernos deben invertir en ayudar a los pobres	5.53 (1.75)	NA (NA)	NA (NA)	NA (NA)	NA (NA)	NA (NA)	5.53 (1.75)
Injusto que los ricos paguen altos impuestos	4.29 (1.90)	NA (NA)	NA (NA)	NA (NA)	NA (NA)	NA (NA)	4.29 (1.90)
Categoría ocupacional
Patrón	1,249 (1.9%)	216 (2.1%)	201 (1.7%)	165 (1.6%)	149 (1.4%)	258 (2.2%)	260 (2.4%)
Asalariado público	4,869 (7.4%)	801 (7.7%)	878 (7.4%)	815 (7.7%)	732 (6.9%)	878 (7.4%)	765 (7.0%)
Asalariado privado	14,047 (21.2%)	2,394 (22.9%)	2,514 (21.3%)	2,490 (23.5%)	2,407 (22.8%)	2,156 (18.2%)	2,086 (19.2%)
Cuenta propia	15,148 (22.9%)	2,192 (21.0%)	2,765 (23.4%)	2,513 (23.7%)	2,509 (23.8%)	2,836 (23.9%)	2,333 (21.5%)
Desocupado	5,277 (8.0%)	640 (6.1%)	943 (8.0%)	619 (5.8%)	504 (4.8%)	1,339 (11.3%)	1,232 (11.3%)
Inactivo	25,543 (38.6%)	4,199 (40.2%)	4,509 (38.2%)	3,981 (37.6%)	4,258 (40.3%)	4,398 (37.1%)	4,198 (38.6%)
Formalidad
Formal	2,954 (8.1%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	2,954 (27.0%)
Informal	2,649 (7.3%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	2,649 (24.2%)
No ocupados	30,720 (84.6%)	4,839 (100.0%)	5,452 (100.0%)	4,600 (100.0%)	4,762 (100.0%)	5,737 (100.0%)	5,330 (48.8%)
Estatus ocupacional
Directivos-Profesionales	471 (1.3%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	471 (4.5%)
Técnicos-administrativos-vendedores	631 (1.8%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	631 (6.0%)
Trabajadores manuales calificados	2,678 (7.5%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	2,678 (25.7%)
Trabajadores manuales no calificados	1,316 (3.7%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	1,316 (12.6%)
No ocupados	30,727 (85.8%)	4,839 (100.0%)	5,452 (100.0%)	4,600 (100.0%)	4,762 (100.0%)	5,737 (100.0%)	5,337 (51.2%)
Ideología (der-izq)	5.54 (2.46)	5.36 (2.32)	5.45 (2.36)	5.50 (2.42)	5.58 (2.49)	5.76 (2.54)	5.60 (2.57)
Sexo
Varón	32,090 (48.1%)	5,008 (47.4%)	5,610 (47.0%)	5,097 (47.8%)	4,975 (46.8%)	5,945 (49.7%)	5,455 (49.6%)
Mujer	34,678 (51.9%)	5,565 (52.6%)	6,315 (53.0%)	5,569 (52.2%)	5,651 (53.2%)	6,026 (50.3%)	5,552 (50.4%)
Edad	41 (17)	41 (16)	40 (17)	41 (16)	42 (17)	41 (16)	42 (17)
Años educativos	9.9 (4.2)	9.3 (4.3)	9.6 (4.2)	9.8 (4.1)	9.8 (4.1)	10.2 (4.0)	10.4 (4.1)
Región
Urbano	55,226 (82.7%)	8,540 (80.8%)	9,967 (83.6%)	8,919 (83.6%)	8,962 (84.3%)	9,547 (79.7%)	9,291 (84.4%)
Rural	11,545 (17.3%)	2,033 (19.2%)	1,958 (16.4%)	1,747 (16.4%)	1,664 (15.7%)	2,425 (20.3%)	1,718 (15.6%)
Nivel de desempleo	7.03 (2.12)	7.14 (1.80)	7.56 (2.03)	6.32 (1.48)	6.32 (1.34)	6.98 (2.35)	7.77 (2.85)
Nivel de informalidad	44 (14)	46 (14)	45 (13)	43 (14)	43 (14)	45 (14)	43 (13)
Nivel de empleo público	11.3 (3.9)	11.1 (3.4)	11.4 (3.5)	11.5 (4.0)	11.4 (4.0)	11.2 (4.2)	11.4 (4.4)
Brecha informales / asalariados reg.	50.5 (6.6)	50.3 (6.7)	51.6 (7.7)	50.6 (7.2)	50.6 (6.4)	50.0 (5.3)	49.9 (5.9)
País
Argentina	8,976 (13.4%)	1,486 (14.1%)	1,410 (11.8%)	1,512 (14.2%)	1,512 (14.2%)	1,528 (12.8%)	1,528 (13.9%)
Brasil	10,008 (15.0%)	1,497 (14.2%)	2,482 (20.8%)	1,499 (14.1%)	1,500 (14.1%)	1,532 (12.8%)	1,498 (13.6%)
Chile	9,897 (14.8%)	1,527 (14.4%)	1,965 (16.5%)	1,571 (14.7%)	1,571 (14.8%)	1,625 (13.6%)	1,638 (14.9%)
Colombia	9,243 (13.8%)	1,503 (14.2%)	1,506 (12.6%)	1,512 (14.2%)	1,496 (14.1%)	1,563 (13.1%)	1,663 (15.1%)
México	9,360 (14.0%)	1,560 (14.8%)	1,562 (13.1%)	1,560 (14.6%)	1,535 (14.4%)	1,563 (13.1%)	1,580 (14.4%)
Perú	10,168 (15.2%)	1,500 (14.2%)	1,500 (12.6%)	1,500 (14.1%)	1,500 (14.1%)	2,647 (22.1%)	1,521 (13.8%)
Uruguay	9,119 (13.7%)	1,500 (14.2%)	1,500 (12.6%)	1,512 (14.2%)	1,512 (14.2%)	1,514 (12.6%)	1,581 (14.4%)
1 Media (DE); n (%)

Boxplot (año y país)

Boxplot 2018

Descriptivos variables independientes

Cruces variable laboral y variables objetivo 2008-2018

Cruces variable laboral / informal y variables objetivo 2018

Modelos Multinivel 2008-2018

El ICC para la variable objetivo de acuerdo con la democracia es de 0.095.

El ICC para la variable objetivo de reducción de la desigualdad es de 0.04.

Democracia

	Ind	Ind+grup	Random_apub	Random_apri	Random_cuent
(Intercept)	5.26***	5.25***	5.25***	5.25***	5.25***
	(0.08)	(0.06)	(0.06)	(0.06)	(0.06)
patron_cwc	0.00	0.00	0.00	0.00	0.00
	(0.05)	(0.05)	(0.05)	(0.05)	(0.05)
asal_pub_cwc	0.06*	0.06*	0.06	0.06*	0.06*
	(0.03)	(0.03)	(0.04)	(0.03)	(0.03)
asal_pri_cwc	0.05**	0.05**	0.05**	0.05*	0.05**
	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)
cuenta_prop_cwc	-0.01	-0.01	-0.01	-0.01	-0.01
	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)
desocupado_cwc	-0.11***	-0.11***	-0.11***	-0.11***	-0.11***
	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)
ideologia_cwc	-0.02***	-0.02***	-0.02***	-0.02***	-0.02***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
sexo_cwc	0.07***	0.07***	0.07***	0.07***	0.07***
	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
edad_cwc	0.01***	0.01***	0.01***	0.01***	0.01***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
educ_cwc	0.06***	0.06***	0.06***	0.06***	0.06***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
desempleo_cgm		-0.02	-0.01	-0.02	-0.04
		(0.03)	(0.03)	(0.03)	(0.03)
informalidad_cgm		-0.03***	-0.04***	-0.03***	-0.03***
		(0.01)	(0.01)	(0.01)	(0.01)
empleo_pub_cgm		0.04	0.05**	0.05*	0.05*
		(0.02)	(0.02)	(0.02)	(0.02)
brecha_remun_cgm		-0.05***	-0.06***	-0.05***	-0.06***
		(0.01)	(0.01)	(0.01)	(0.01)
AIC	233260.64	233261.74	233246.23	233257.02	233260.78
BIC	233369.07	233406.31	233408.87	233419.67	233423.42
Log Likelihood	-116618.32	-116614.87	-116605.11	-116610.51	-116612.39
Num. obs.	62060	62060	62060	62060	62060
Num. groups: pais_anio	42	42	42	42	42
Var: pais_anio (Intercept)	0.27	0.13	0.13	0.13	0.13
Var: Residual	2.50	2.50	2.50	2.50	2.50
Var: pais_anio asal_pub_cwc			0.02
Cov: pais_anio (Intercept) asal_pub_cwc			-0.04
Var: pais_anio asal_pri_cwc				0.01
Cov: pais_anio (Intercept) asal_pri_cwc				-0.01
Var: pais_anio cuenta_prop_cwc					0.00
Cov: pais_anio (Intercept) cuenta_prop_cwc					0.01
***p < 0.001; **p < 0.01; *p < 0.05

## Data: base_ml
## Models:
## democracia_null: democracia7 ~ 1 + (1 | pais_anio)
## democracia_ind: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
##                 npar    AIC    BIC  logLik deviance  Chisq Df Pr(>Chisq)    
## democracia_null    3 234949 234976 -117472   234943                         
## democracia_ind    12 233188 233296 -116582   233164 1779.5  9  < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## democracia_ind: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## democracia_ind_grup: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
##                     npar    AIC    BIC  logLik deviance  Chisq Df Pr(>Chisq)
## democracia_ind        12 233188 233296 -116582   233164                     
## democracia_ind_grup   16 233161 233305 -116564   233129 34.879  4   4.92e-07
##                        
## democracia_ind         
## democracia_ind_grup ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## democracia_ind_grup: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## democracia_random_apub: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 + asal_pub_cwc | pais_anio)
##                        npar    AIC    BIC  logLik deviance  Chisq Df Pr(>Chisq)
## democracia_ind_grup      16 233161 233305 -116564   233129                     
## democracia_random_apub   18 233145 233308 -116554   233109 19.778  2  5.073e-05
##                           
## democracia_ind_grup       
## democracia_random_apub ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## democracia_ind_grup: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## democracia_random_apri: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 + asal_pri_cwc | pais_anio)
##                        npar    AIC    BIC  logLik deviance  Chisq Df Pr(>Chisq)
## democracia_ind_grup      16 233161 233305 -116564   233129                     
## democracia_random_apri   18 233156 233319 -116560   233120 8.5113  2    0.01418
##                         
## democracia_ind_grup     
## democracia_random_apri *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## democracia_ind_grup: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## democracia_random_cuent: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 + cuenta_prop_cwc | pais_anio)
##                         npar    AIC    BIC  logLik deviance  Chisq Df
## democracia_ind_grup       16 233161 233305 -116564   233129          
## democracia_random_cuent   18 233160 233322 -116562   233124 5.0993  2
##                         Pr(>Chisq)  
## democracia_ind_grup                 
## democracia_random_cuent    0.07811 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Reducción de la desigualdad

	Ind	Ind+grup	Random_apub	Random_apri	Random_cuent
(Intercept)	5.73***	5.73***	5.73***	5.73***	5.73***
	(0.05)	(0.05)	(0.05)	(0.05)	(0.05)
patron_cwc	-0.09	-0.09	-0.09	-0.09	-0.09
	(0.05)	(0.05)	(0.05)	(0.05)	(0.05)
asal_pub_cwc	0.14***	0.14***	0.14***	0.14***	0.14***
	(0.03)	(0.03)	(0.03)	(0.03)	(0.03)
asal_pri_cwc	0.05**	0.05**	0.05**	0.05*	0.05**
	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)
cuenta_prop_cwc	0.02	0.02	0.02	0.02	0.01
	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)
desocupado_cwc	0.13***	0.13***	0.13***	0.13***	0.13***
	(0.02)	(0.02)	(0.02)	(0.02)	(0.02)
ideologia_cwc	0.02***	0.02***	0.02***	0.02***	0.02***
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
sexo_cwc	-0.00	-0.00	-0.00	-0.00	-0.00
	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
edad_cwc	0.00	0.00	0.00	0.00	0.00
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
educ_cwc	0.00**	0.00**	0.00**	0.00**	0.00**
	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
desempleo_cgm		0.01	0.01	0.00	0.01
		(0.03)	(0.03)	(0.03)	(0.03)
informalidad_cgm		-0.01	-0.01	-0.01	-0.01
		(0.01)	(0.01)	(0.01)	(0.01)
empleo_pub_cgm		-0.01	-0.00	-0.01	-0.01
		(0.02)	(0.02)	(0.02)	(0.02)
brecha_remun_cgm		0.00	-0.00	-0.00	0.00
		(0.01)	(0.01)	(0.01)	(0.01)
AIC	229750.90	229779.99	229778.97	229775.90	229771.49
BIC	229859.33	229924.56	229941.61	229938.55	229934.14
Log Likelihood	-114863.45	-114873.99	-114871.48	-114869.95	-114867.74
Num. obs.	62060	62060	62060	62060	62060
Num. groups: pais_anio	42	42	42	42	42
Var: pais_anio (Intercept)	0.10	0.09	0.09	0.09	0.09
Var: Residual	2.36	2.36	2.36	2.36	2.36
Var: pais_anio asal_pub_cwc			0.01
Cov: pais_anio (Intercept) asal_pub_cwc			-0.01
Var: pais_anio asal_pri_cwc				0.01
Cov: pais_anio (Intercept) asal_pri_cwc				-0.01
Var: pais_anio cuenta_prop_cwc					0.01
Cov: pais_anio (Intercept) cuenta_prop_cwc					-0.00
***p < 0.001; **p < 0.01; *p < 0.05

## Data: base_ml
## Models:
## reduc_desigualdad_null: reduc_desigualdad ~ 1 + (1 | pais_anio)
## reduc_desigualdad_ind: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
##                        npar    AIC    BIC  logLik deviance  Chisq Df Pr(>Chisq)
## reduc_desigualdad_null    3 229809 229836 -114902   229803                     
## reduc_desigualdad_ind    12 229676 229785 -114826   229652 150.72  9  < 2.2e-16
##                           
## reduc_desigualdad_null    
## reduc_desigualdad_ind  ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## reduc_desigualdad_ind: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## reduc_desigualdad_ind_grup: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
##                            npar    AIC    BIC  logLik deviance  Chisq Df
## reduc_desigualdad_ind        12 229676 229785 -114826   229652          
## reduc_desigualdad_ind_grup   16 229677 229821 -114822   229645 7.6622  4
##                            Pr(>Chisq)
## reduc_desigualdad_ind                
## reduc_desigualdad_ind_grup     0.1048

## Data: base_ml
## Models:
## reduc_desigualdad_ind_grup: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## reduc_desigualdad_random_apub: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 + asal_pub_cwc | pais_anio)
##                               npar    AIC    BIC  logLik deviance  Chisq Df
## reduc_desigualdad_ind_grup      16 229677 229821 -114822   229645          
## reduc_desigualdad_random_apub   18 229676 229839 -114820   229640 4.8387  2
##                               Pr(>Chisq)  
## reduc_desigualdad_ind_grup                
## reduc_desigualdad_random_apub    0.08898 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## reduc_desigualdad_ind_grup: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## reduc_desigualdad_random_apri: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 + asal_pri_cwc | pais_anio)
##                               npar    AIC    BIC  logLik deviance Chisq Df
## reduc_desigualdad_ind_grup      16 229677 229821 -114822   229645         
## reduc_desigualdad_random_apri   18 229673 229836 -114818   229637 7.849  2
##                               Pr(>Chisq)  
## reduc_desigualdad_ind_grup                
## reduc_desigualdad_random_apri    0.01975 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Data: base_ml
## Models:
## reduc_desigualdad_ind_grup: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## reduc_desigualdad_random_cuent: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 + cuenta_prop_cwc | pais_anio)
##                                npar    AIC    BIC  logLik deviance  Chisq Df
## reduc_desigualdad_ind_grup       16 229677 229821 -114822   229645          
## reduc_desigualdad_random_cuent   18 229669 229832 -114816   229633 11.848  2
##                                Pr(>Chisq)   
## reduc_desigualdad_ind_grup                  
## reduc_desigualdad_random_cuent   0.002674 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1