LA ÉTICA PÚBLICA APLICADA A LOS GOBIERNOS
3.1 El compromiso ético en el ámbito internacional
Table A1: Descriptive Statistics by Gender
MALES FEMALES
mean s.d. mean s.d.
public transport accessibility (pta) 3.182 1.116 3.222 1.130
cars = 0 0.180 0.384 0.198 0.399
cars = 1 0.534 0.499 0.533 0.499
cars ≥ 2 0.285 0.452 0.269 0.443
employed 0.889 0.314 0.586 0.492
job-education mismatch (years) -0.070 3.104 0.095 3.026
overeducation (schooling > occupation-average + s.d.) 0.162 0.368 0.167 0.373
age 38.31 11.93 40.33 11.98
no education 0.062 0.242 0.087 0.281
primary education 0.179 0.383 0.195 0.396
lower secondary education 0.311 0.463 0.301 0.459
upper secondary education 0.129 0.336 0.121 0.326
vocational education - low grade 0.080 0.272 0.069 0.253
vocational education - high grade 0.082 0.275 0.063 0.242
tertiary education 0.156 0.363 0.165 0.372
field of tertiary education = social sciences 0.058 0.234 0.082 0.274
field of tertiary education = humanities 0.014 0.119 0.025 0.155
field of tertiary education = health studies 0.015 0.120 0.034 0.181
field of tertiary education = hard science 0.016 0.126 0.013 0.115
field of tertiary education = technical studies 0.052 0.223 0.011 0.106
born in Spain 0.944 0.230 0.954 0.210
born in EU15 countries 0.008 0.091 0.007 0.086
born in Africa 0.020 0.140 0.010 0.098
born in America 0.018 0.132 0.023 0.151
born in other countries 0.010 0.099 0.006 0.079
marital status = single 0.388 0.487 0.264 0.441
marital status = married 0.560 0.496 0.650 0.477
marital status = others 0.053 0.224 0.086 0.280
local unemployment rate 0.111 0.035 0.110 0.034
resident in Barcelona 0.305 0.460 0.326 0.469
# children aged 0-4 0.142 0.405 0.155 0.421
# children aged 5-9 0.133 0.386 0.147 0.403
# children aged 10-15 0.177 0.440 0.194 0.460
# children aged 16-19 0.209 0.471 0.210 0.468
number of adults in the household 2.706 1.199 2.630 1.149
car park in the house building 0.170 0.376 0.177 0.382
usable housing space (in m2/100) 84.85 35.81 86.56 37.81
40 Table A2a: Variables Correlation Matrix by Gender, Males
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1 job-education mismatch* 1.00
2 employment -- 1.00
3 cars 0.06 0.11 1.00
4 public transport accessibility 0.06 -0.03 -0.27 1.00
5 age -0.23 0.06 0.01 0.07 1.00
6 no education -0.49 -0.04 -0.08 -0.03 0.17 1.00 7 primary education -0.31 -0.04 -0.06 -0.08 0.11 -0.12 1.00 8 lower secondary education -0.15 -0.02 -0.01 -0.08 -0.07 -0.17 -0.31 1.00 9 upper secondary education -0.03 0.01 0.00 0.06 -0.03 -0.10 -0.18 -0.26 1.00 10 vocational education - low grade 0.27 0.01 0.03 -0.02 -0.10 -0.08 -0.14 -0.20 -0.11 1.00 11 vocational education - high grade 0.36 0.03 0.05 0.02 -0.09 -0.08 -0.14 -0.20 -0.12 -0.09 1.00 12 tertiary education 0.38 0.05 0.07 0.15 0.03 -0.11 -0.20 -0.29 -0.17 -0.13 -0.13 1.00 13 field of tertiary education = social sciences 0.25 0.03 0.04 0.09 0.00 -0.06 -0.12 -0.17 -0.10 -0.07 -0.07 0.58 1.00 14 field of tertiary education = humanities 0.13 0.00 -0.02 0.05 0.01 -0.03 -0.06 -0.08 -0.05 -0.04 -0.04 0.28 -0.03 1.00 15 field of tertiary education = health studies 0.06 0.03 0.03 0.05 0.04 -0.03 -0.06 -0.08 -0.05 -0.04 -0.04 0.28 -0.03 -0.01 1.00 16 field of tertiary education = hard science 0.14 0.02 0.02 0.05 0.01 -0.03 -0.06 -0.09 -0.05 -0.04 -0.04 0.30 -0.03 -0.02 -0.02 1.00 17 field of tertiary education = technical studies 0.18 0.03 0.05 0.07 0.02 -0.06 -0.11 -0.16 -0.09 -0.07 -0.07 0.55 -0.06 -0.03 -0.03 -0.03 1.00 18 born in Spain 0.02 0.06 0.20 -0.06 0.09 -0.13 0.00 0.05 -0.03 0.04 0.03 0.00 0.00 -0.02 0.01 0.00 0.00 19 born in EU15 countries 0.04 -0.01 -0.03 0.02 -0.01 -0.02 -0.03 -0.04 0.01 0.00 0.01 0.08 0.04 0.04 0.01 0.02 0.04 20 born in Africa -0.09 -0.04 -0.09 -0.04 -0.06 0.18 0.03 -0.03 -0.02 -0.03 -0.04 -0.05 -0.02 -0.01 -0.01 -0.02 -0.03 21 born in America 0.04 -0.03 -0.14 0.07 -0.06 0.00 -0.02 -0.01 0.06 -0.02 -0.01 0.01 0.00 0.00 -0.01 0.00 0.01 22 born in other countries 0.00 -0.02 -0.11 0.08 -0.04 0.04 0.00 -0.01 0.01 -0.02 -0.01 0.00 0.00 0.01 0.00 -0.01 0.00 23 marital status = single 0.12 -0.13 -0.10 0.04 -0.61 -0.07 -0.05 0.02 0.01 0.04 0.05 -0.01 0.00 0.03 -0.03 0.00 -0.01 24 marital status = married -0.12 0.14 0.12 -0.05 0.54 0.07 0.05 -0.02 -0.02 -0.03 -0.04 0.01 0.00 -0.03 0.02 0.00 0.01 25 marital status = others -0.01 -0.04 -0.07 0.01 0.12 0.00 0.01 -0.01 0.02 -0.01 -0.02 0.00 0.00 0.00 0.01 0.00 0.00 26 local unemployment rate -0.07 -0.12 -0.17 0.10 -0.05 0.07 0.10 0.07 -0.06 0.00 -0.04 -0.15 -0.09 -0.04 -0.06 -0.05 -0.08 27 resident in Barcelona 0.08 -0.02 -0.22 0.77 0.07 -0.05 -0.09 -0.09 0.08 -0.02 0.02 0.18 0.11 0.06 0.06 0.06 0.08 28 # children aged 0-4 0.05 0.04 0.02 -0.03 -0.09 -0.03 -0.05 -0.02 0.02 0.02 0.02 0.05 0.03 0.01 0.01 0.02 0.02 29 # children aged 5-9 0.03 0.05 0.02 -0.03 0.00 -0.03 -0.03 0.00 0.02 0.01 0.00 0.03 0.02 0.00 0.02 0.02 0.01 30 # children aged 10-15 -0.03 0.03 0.04 -0.05 0.07 -0.01 0.03 0.03 0.00 -0.02 -0.03 -0.02 -0.01 -0.02 0.02 0.00 -0.02 31 # children aged 16-19 -0.06 -0.02 0.06 -0.04 0.00 0.00 0.05 0.06 -0.03 -0.02 -0.04 -0.05 -0.03 -0.03 0.00 -0.02 -0.03 32 number of adults in the household -0.04 -0.05 0.11 0.01 -0.06 0.07 0.03 0.01 -0.04 -0.02 0.00 -0.05 -0.04 -0.02 -0.02 -0.02 -0.01 33 car park in the house building 0.04 0.03 0.18 -0.23 0.03 -0.04 -0.04 -0.03 0.02 0.00 0.02 0.07 0.04 0.01 0.03 0.02 0.04 34 usable housing space (in m2/100) 0.07 0.05 0.26 -0.22 0.06 -0.07 -0.08 -0.07 0.04 -0.02 0.01 0.20 0.12 0.04 0.07 0.06 0.11 Note: * The correlation between job-education mismatch and other variables has been computed for the subsample of employed individuals.
41 Table A2a: Variables Correlation Matrix by Gender, Males (continued)
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
18 born in Spain 1.00
19 born in EU15 countries -0.38 1.00
20 born in Africa -0.58 -0.01 1.00
21 born in America -0.55 -0.01 -0.02 1.00 22 born in other countries -0.41 0.00 -0.01 -0.01 1.00 23 marital status = single -0.03 0.01 0.02 0.02 0.01 1.00 24 marital status = married 0.03 -0.02 -0.01 -0.03 -0.01 -0.90 1.00 25 marital status = others 0.01 0.01 -0.02 0.01 -0.01 -0.19 -0.27 1.00 26 local unemployment rate -0.05 -0.02 0.05 0.02 0.06 0.07 -0.07 0.01 1.00 27 resident in Barcelona -0.05 0.03 -0.05 0.06 0.07 0.04 -0.05 0.02 0.00 1.00 28 # children aged 0-4 -0.04 0.02 0.05 0.00 0.00 -0.20 0.22 -0.04 -0.02 -0.02 1.00 29 # children aged 5-9 0.01 0.00 0.00 0.00 -0.02 -0.21 0.22 -0.04 -0.02 -0.02 0.12 1.00 30 # children aged 10-15 0.03 -0.02 -0.01 -0.02 -0.01 -0.18 0.20 -0.05 -0.01 -0.04 -0.04 0.12 1.00 31 # children aged 16-19 0.06 -0.03 -0.03 -0.03 -0.02 -0.03 0.06 -0.05 0.01 -0.04 -0.11 -0.03 0.28 1.00 32 number of adults in the household -0.18 -0.04 0.13 0.10 0.13 0.20 -0.14 -0.12 0.04 -0.01 -0.17 -0.16 -0.17 -0.08 1.00 33 car park in the house building 0.06 0.01 -0.05 -0.03 -0.04 -0.06 0.06 -0.01 -0.21 -0.12 0.03 0.04 0.03 0.03 -0.02 1.00 34 usable housing space (in m2/100) 0.08 0.01 -0.06 -0.05 -0.05 -0.07 0.08 -0.03 -0.24 -0.11 0.02 0.06 0.07 0.06 0.05 0.30 1.00 Note: * The correlation between job-education mismatch and other variables has been computed for the subsample of employed individuals
42 Table A2b: Variables Correlation Matrix by Gender, Females
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
1 job-education mismatch* 1.00
2 employment -- 1.00
3 cars 0.04 0.05 1.00
4 Public transport accessibility 0.05 0.02 -0.31 1.00
5 age -0.25 0.01 -0.03 0.12 1.00
6 no education -0.44 -0.04 -0.06 -0.03 0.19 1.00 7 primary education -0.29 -0.05 -0.06 -0.06 0.18 -0.09 1.00 8 lower secondary education -0.25 -0.06 -0.01 -0.07 0.01 -0.14 -0.26 1.00 9 upper secondary education -0.07 0.03 0.00 0.04 -0.06 -0.09 -0.16 -0.26 1.00 10 vocational education - low grade 0.19 -0.01 0.02 -0.03 -0.09 -0.07 -0.12 -0.19 -0.12 1.00 11 vocational education - high grade 0.30 0.02 0.03 -0.01 -0.16 -0.07 -0.12 -0.19 -0.12 -0.09 1.00 12 tertiary education 0.45 0.10 0.07 0.13 -0.04 -0.12 -0.21 -0.34 -0.21 -0.16 -0.16 1.00 13 field of tertiary education = social sciences 0.32 0.06 0.05 0.08 -0.05 -0.08 -0.14 -0.22 -0.14 -0.10 -0.10 0.66 1.00 14 field of tertiary education = humanities 0.18 0.03 0.00 0.07 0.01 -0.04 -0.07 -0.12 -0.07 -0.05 -0.05 0.35 -0.06 1.00 15 field of tertiary education = health studies 0.10 0.06 0.05 0.05 0.02 -0.05 -0.09 -0.14 -0.09 -0.06 -0.06 0.41 -0.08 -0.04 1.00 16 field of tertiary education = hard science 0.13 0.03 0.03 0.02 -0.02 -0.03 -0.06 -0.09 -0.06 -0.04 -0.04 0.26 -0.05 -0.03 -0.03 1.00 17 field of tertiary education = technical studies 0.11 0.02 0.02 0.03 -0.04 -0.03 -0.05 -0.08 -0.05 -0.04 -0.04 0.23 -0.04 -0.02 -0.03 -0.02 1.00 18 born in Spain -0.05 0.01 0.18 -0.08 0.07 -0.05 0.00 0.03 -0.05 0.03 0.02 0.00 0.00 -0.01 0.02 0.00 -0.03 19 born in EU15 countries 0.04 -0.01 -0.02 0.02 -0.01 -0.01 -0.02 -0.03 0.01 -0.01 0.01 0.06 0.04 0.06 -0.01 0.01 0.02 20 born in Africa -0.04 -0.02 -0.06 -0.01 -0.05 0.10 0.02 -0.01 -0.01 -0.01 -0.02 -0.03 -0.02 -0.01 -0.02 -0.01 -0.01 21 born in America 0.06 0.00 -0.16 0.09 -0.04 0.01 -0.01 -0.01 0.06 -0.03 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 0.02 22 born in other countries 0.01 0.00 -0.07 0.04 -0.03 0.02 0.01 -0.01 0.02 -0.01 -0.01 -0.01 -0.01 0.01 -0.01 0.00 0.01 23 marital status = single 0.14 0.00 -0.12 0.06 -0.51 -0.09 -0.09 -0.04 0.03 0.02 0.09 0.07 0.05 0.02 0.01 0.02 0.04 24 marital status = married -0.09 -0.01 0.22 -0.08 0.34 0.06 0.05 0.03 -0.03 -0.01 -0.06 -0.03 -0.02 -0.02 0.00 -0.01 -0.02 25 marital status = others -0.08 0.02 -0.17 0.03 0.23 0.04 0.06 0.02 0.00 -0.01 -0.05 -0.06 -0.04 -0.01 -0.01 -0.02 -0.02 26 local unemployment rate -0.06 -0.10 -0.16 0.10 -0.06 0.07 0.09 0.06 -0.04 0.01 -0.02 -0.15 -0.09 -0.04 -0.07 -0.04 -0.03 27 resident in Barcelona 0.06 0.02 -0.26 0.79 0.13 -0.03 -0.07 -0.08 0.05 -0.03 -0.01 0.15 0.10 0.08 0.06 0.03 0.03 28 # children aged 0-4 0.07 -0.04 0.07 -0.04 -0.14 -0.05 -0.07 -0.03 0.02 0.02 0.03 0.07 0.04 0.03 0.02 0.03 0.02 29 # children aged 5-9 0.02 -0.02 0.05 -0.04 -0.02 -0.03 -0.03 0.00 0.02 0.02 -0.01 0.02 0.01 0.01 0.02 0.01 -0.01 30 # children aged 10-15 -0.06 -0.01 0.03 -0.05 0.07 0.00 0.03 0.05 0.00 0.01 -0.05 -0.05 -0.04 -0.02 0.00 -0.01 -0.02 31 # children aged 16-19 -0.10 -0.02 0.05 -0.04 0.03 0.02 0.07 0.08 -0.03 -0.02 -0.06 -0.08 -0.07 -0.03 -0.01 -0.03 -0.02 32 number of adults in the household 0.00 -0.02 0.13 0.01 -0.08 0.04 0.03 0.01 -0.03 -0.01 0.02 -0.04 -0.02 -0.03 -0.02 0.00 0.01 33 car park in the house building 0.02 0.02 0.19 -0.24 0.02 -0.04 -0.04 -0.02 0.02 -0.01 0.01 0.06 0.04 0.01 0.04 0.03 0.01 34 usable housing space (in m2/100) 0.04 0.04 0.28 -0.20 0.07 -0.06 -0.07 -0.06 0.02 -0.02 -0.02 0.16 0.10 0.06 0.08 0.04 0.03 Note: * The correlation between job-education mismatch and other variables has been computed for the subsample of employed individuals
43 Table A2b: Variables Correlation Matrix by Gender, Females (continued)
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
18 born in Spain 1.00
19 born in EU15 countries -0.39 1.00
20 born in Africa -0.39 -0.01 1.00
21 born in America -0.73 -0.01 -0.01 1.00 22 born in other countries -0.36 0.02 -0.01 -0.01 1.00 23 marital status = single -0.05 0.03 0.01 0.04 0.00 1.00 24 marital status = married 0.05 -0.02 -0.01 -0.05 0.00 -0.81 1.00 25 marital status = others 0.00 0.00 0.00 0.01 0.00 -0.26 -0.37 1.00 26 local unemployment rate -0.04 -0.02 0.04 0.03 0.03 0.07 -0.07 0.01 1.00 27 resident in Barcelona -0.07 0.03 -0.02 0.07 0.04 0.04 -0.06 0.03 0.01 1.00 28 # children aged 0-4 0.00 0.00 0.03 -0.02 0.00 -0.19 0.22 -0.06 -0.03 -0.03 1.00 29 # children aged 5-9 0.02 0.00 0.00 -0.01 -0.02 -0.20 0.20 -0.01 -0.03 -0.02 0.10 1.00 30 # children aged 10-15 0.02 -0.01 0.01 -0.03 -0.01 -0.18 0.15 0.03 0.00 -0.04 -0.07 0.09 1.00 31 # children aged 16-19 0.04 -0.02 0.01 -0.04 -0.01 -0.06 0.05 0.02 0.02 -0.05 -0.13 -0.04 0.27 1.00 32 number of adults in the household -0.15 -0.02 0.07 0.13 0.08 0.23 -0.12 -0.16 0.03 -0.01 -0.16 -0.16 -0.18 -0.07 1.00 33 car park in the house building 0.05 0.01 -0.03 -0.04 -0.02 -0.07 0.08 -0.03 -0.21 -0.14 0.03 0.04 0.03 0.02 -0.01 1.00 34 usable housing space (in m2/100) 0.06 0.02 -0.04 -0.05 -0.03 -0.07 0.10 -0.05 -0.24 -0.11 0.03 0.06 0.07 0.07 0.08 0.30 1.00 Note: * The correlation between job-education mismatch and other variables has been computed for the subsample of employed individuals
44 Table A3: Average Elasticity of Public Transport Accessibility and Car Ownership (Independent Equations)
OUTCOME %Δ[years of
overeducation] %ΔPr[employed] %ΔPr[cars = 0] %ΔPr[cars = 1] %ΔPr[cars ≥ 2]
MALES
%Δ(public transport accessibility) -0.057 0.002 0.908 0.035 -0.838
Δ 0 to 1 car -0.026 0.067
Δ 1 to 2 cars -0.018 0.016
FEMALES
%Δ(public transport accessibility) -0.047 0.059 0.978 0.000 -0.977
Δ 0 to 1 car -0.047 0.024
Δ 1 to 2 cars -0.027 0.079
Note: the marginal effect of public transport accessibility is computed as the changes in predicted outcomes after a 10% change in public transport accessibility (elasticity). The marginal effect of car ownership is the changes in predicted outcomes after switching from 0 to 1 car and from 1 to 2 cars respectively. The elasticity of the years of overeducation has been computed considering individuals to be overeducated when they have more years of schooling than the average in their respective occupation plus one standard deviation point (i.e. mismatch greater than the standard deviation of years of schooling in each occupation). Numbers in bold type indicate that the corresponding coefficient is significant at a 5% significance level.
Table A4: Sensitivity Analysis
OUTCOME %Δ[years of overeducation]
baseline sample
MALES (n = 44077) FEMALES (n = 48961)
%Δ(public transport accessibility) -0.086 -0.081
Δ 0 to 1 car -0.076 -0.141
Δ 1 to 2 cars -0.084 -0.120
only individuals residing in the same place for more than 10 years
MALES (n = 22765) FEMALES (n = 25871)
%Δ(public transport accessibility) -0.097 -0.096
Δ 0 to 1 car -0.059 -0.120
Δ 1 to 2 cars -0.068 -0.093
only individuals residing with their parents
MALES (n = 11116)
FEMALES (n = 7416)
%Δ(public transport accessibility) -0.083 -0.057
Δ 0 to 1 car -0.060 -0.038
Δ 1 to 2 cars -0.053 -0.035
only head of household
45
%Δ(public transport accessibility) -0.115 -0.027
Δ 0 to 1 car -0.139 -0.074
Δ 1 to 2 cars -0.157 -0.075
Note: the marginal effect of public transport accessibility is computed as the changes in predicted outcomes after a 10% change in public transport accessibility (elasticity). The marginal effect of car ownership is the changes in predicted outcomes after switching from 0 to 1 car and from 1 to 2 cars respectively. The elasticity of the years of overeducation has been computed considering individuals to be overeducated when they have more years of schooling than the average in their respective occupation plus one standard deviation point (i.e. mismatch greater than the standard deviation of years of schooling in each occupation). Numbers in bold type indicate that the corresponding coefficient is significant at a 5% significance level.
46 Table A5: Descriptive Statistics for Selected Subsamples for Sensitivity Analysis
(a) (b) (c)
MALES FEMALES MALES FEMALES MALES FEMALES
mean s.d. mean s.d. mean s.d. mean s.d. mean s.d. mean s.d.
public transport accessibility (pta) 3.312 1.076 3.365 1.086 3.182 1.079 3.252 1.096 3.166 1.123 3.310 1.166
cars = 0 0.174 0.379 0.200 0.400 0.201 0.401 0.220 0.414 0.162 0.368 0.269 0.444
cars = 1 0.528 0.499 0.533 0.499 0.438 0.496 0.465 0.499 0.584 0.493 0.515 0.500
cars ≥ 2 0.298 0.457 0.267 0.443 0.361 0.480 0.315 0.465 0.254 0.435 0.216 0.411
employed 0.878 0.328 0.534 0.499 0.827 0.379 0.806 0.396 0.937 0.244 0.817 0.387
job-education mismatch (years) -0.305 3.090 -0.219 3.021 0.551 2.966 0.717 2.968 -0.162 3.158 0.342 3.099
overeducation (schooling > occupation-average + s.d.) 0.145 0.353 0.145 0.352 0.207 0.405 0.221 0.415 0.160 0.367 0.195 0.396
age 40.34 13.20 43.81 12.46 26.72 7.18 26.73 7.43 43.73 10.43 41.42 10.61
no education 0.071 0.256 0.112 0.316 0.027 0.161 0.019 0.135 0.073 0.261 0.065 0.247
primary education 0.203 0.402 0.236 0.425 0.152 0.359 0.093 0.290 0.184 0.387 0.148 0.355
lower secondary education 0.321 0.467 0.309 0.462 0.350 0.477 0.284 0.451 0.289 0.453 0.247 0.432
upper secondary education 0.115 0.319 0.103 0.304 0.126 0.332 0.145 0.353 0.119 0.324 0.134 0.340
vocational education - low grade 0.074 0.262 0.056 0.230 0.102 0.303 0.093 0.291 0.074 0.263 0.083 0.275
vocational education - high grade 0.077 0.266 0.050 0.217 0.108 0.311 0.129 0.335 0.078 0.269 0.074 0.262
tertiary education 0.139 0.346 0.134 0.341 0.135 0.342 0.237 0.425 0.182 0.386 0.249 0.432
field of tertiary education = social sciences 0.050 0.217 0.066 0.248 0.052 0.223 0.125 0.330 0.066 0.249 0.121 0.326
field of tertiary education = humanities 0.013 0.113 0.020 0.140 0.013 0.113 0.027 0.163 0.016 0.127 0.040 0.196
field of tertiary education = health studies 0.013 0.114 0.029 0.167 0.008 0.091 0.043 0.203 0.019 0.136 0.054 0.225
field of tertiary education = hard science 0.014 0.118 0.010 0.102 0.013 0.113 0.021 0.144 0.020 0.139 0.020 0.140
field of tertiary education = technical studies 0.049 0.216 0.010 0.097 0.048 0.214 0.021 0.143 0.061 0.239 0.013 0.115
born in Spain 0.990 0.098 0.989 0.106 0.989 0.105 0.988 0.111 0.952 0.213 0.952 0.213
born in EU15 countries 0.003 0.051 0.003 0.059 0.002 0.040 0.002 0.040 0.010 0.100 0.010 0.101
born in Africa 0.003 0.052 0.002 0.040 0.004 0.061 0.003 0.059 0.017 0.130 0.008 0.088
born in America 0.003 0.054 0.005 0.070 0.004 0.063 0.006 0.077 0.013 0.111 0.024 0.154
born in other countries 0.001 0.039 0.001 0.038 0.002 0.041 0.001 0.038 0.008 0.088 0.005 0.073
marital status = single 0.443 0.497 0.276 0.447 1.000 0.000 1.000 0.000 0.158 0.364 0.210 0.407
marital status = married 0.512 0.500 0.640 0.480 0.000 0.000 0.000 0.000 0.775 0.418 0.565 0.496
marital status = others 0.045 0.207 0.084 0.277 0.000 0.000 0.000 0.000 0.068 0.251 0.225 0.418
Number of observations 22,765 25,871 11,116 7,416 23,545 15,007
47 Table A5: Descriptive Statistics for Selected Subsamples for Sensitivity Analysis (continued)
(a) (b) (c)
MALES FEMALES MALES FEMALES MALES FEMALES
mean s.d. mean s.d. mean s.d. mean s.d. mean s.d. mean s.d.
local unemployment rate 0.114 0.035 0.113 0.034 0.114 0.037 0.113 0.036 0.111 0.034 0.109 0.034
resident in Barcelona 0.343 0.475 0.369 0.482 0.294 0.455 0.324 0.468 0.300 0.458 0.376 0.484
# children aged 0-4 0.037 0.207 0.042 0.217 0.009 0.106 0.009 0.109 0.182 0.452 0.175 0.437
# children aged 5-9 0.091 0.322 0.097 0.330 0.026 0.177 0.029 0.194 0.169 0.428 0.156 0.412
# children aged 10-15 0.188 0.442 0.197 0.455 0.102 0.329 0.099 0.334 0.212 0.477 0.201 0.473
# children aged 16-19 0.261 0.508 0.254 0.499 0.281 0.543 0.269 0.530 0.200 0.457 0.184 0.441
number of adults in the household 2.961 1.101 2.861 1.082 3.401 1.035 3.458 1.016 2.337 0.984 2.100 0.959
car park in the house building 0.130 0.336 0.136 0.343 0.155 0.362 0.155 0.362 0.177 0.382 0.169 0.375
usable housing space (in m2/100) 82.65
32.93 83.94 35.07 85.14 37.13 87.04 38.82 84.72 35.06 83.81 34.90
Number of observations 22,765 25,871 11,116 7,416 23,545 15,007
48 Table A6: Accounting for Private Transport Accessibility (Selected Estimates)
MALES FEMALES
mismatch
public transport accessibility (pta) -0.128a -0.147a -0.115a -0.136a
(-6.966) (-6.911) (-4.413) (-4.677)
cars = 0 reference category
cars = 1 -0.411a -0.411a -0.793a -0.790a
(-4.351) (-4.351) (-5.729) (-5.713)
cars ≥ 2 -0.829a -0.829a -1.374a -1.367a
(-4.673) (-4.673) (-5.168) (-5.150)
private transport accessibility 0.015c 0.016
(1.806) (1.570) employment
public transport accessibility (pta) 0.011 -0.011 0.052a 0.065a
(0.624) (-0.552) (4.066) (4.450)
cars = 0 reference category
cars = 1 0.346a 0.356a 0.218a 0.212a
(3.316) (3.380) (3.164) (3.062)
cars ≥ 2 0.497b 0.517b 0.520a 0.507a
(2.436) (2.508) (3.909) (3.796)
private transport accessibility 0.017b -0.010b
(2.529) (-2.033)
Number of observations 44,077 44,077 48,961 48,961 Note: a significant at 1% level, b significant at 5% level, c significant at 10%
level; t-Statistics in parenthesis, standard errors clustered at the census tract level. Private transport accessibility has been computed in the same fashion than public transport job accessibility (see section 3.2) but using private transport time. All the equations contain the same set of covariates than in the baseline estimations of table 2.