|
The effect of age on cultural consumption in table 5 is relative to the age group 50-54. All younger cohorts prefer movies and only the oldest (70-74) seem to go less often to the cinema than the reference group. The indirect marginal effect of age on highbrow art is negative for each younger age group. The direct marginal effects of cohorts are not significant. The results indicate that age is not a relevant variable to classify highbrow art consumption into active and inactive groups. Education seems to be very important to classify culture consumption structures. When the reference level is elementary school (edu2), citizens with any other education level are significantly more active in culture consumption, in both directions: highbrow art and movies. The highest marginal (direct + indirect) effect is for those that have the best education (edu9 = master’s degree): 0.160 = 0.195 – 0.035. However, those with a bachelor’s degree (edu8) have the largest direct and largest (negative) indirect effect: 0.150 = 0.250 – 0.100. They seem to be the most omnivore group. They are most active in highbrow art consumption as well as in movies at the cinema consumption. Consumers with college level education (edu6) are third most active group. The results confirm the well-known hypothesis that omnivores have higher levels of education (Chan and Goldthorpe 2005, Alderson, Junisbai and Heacock 2007). Spouse’s education in some cases is relevant to explain consumption of movies at the cinema. If the spouse has either a master’s degree or upper secondary diploma, the person is more active to go to the cinema and that indirectly reduces highbrow art participation.
The effect of domicile on culture consumption is selective. In Southern and Western Finland (Area1 or Area2) people are more active in both highbrow art and movies at the cinema consumption. In Eastern Finland (Area3) people are less active in highbrow art consumption but significantly more active in movie attendance than in Northern Finland or in the Ahvenanmaa archipelago (reference areas). Household’s size matters only indirectly to highbrow art consumption since bigger families seem to favour movies. The number of small children (less than 7) or older children (7-17) significantly reduces both culture consumption segments. Household incomes (or personal incomes – not reported here) are not significant. The survey article by Seaman (2006, 441) shows that there is mixed evidence whether education outweights incomes in explaining performing art consumption. The lack of the relation between incomes and participation might be due to positive relation between participation and wealth, not household incomes.
Table 5-6 presents the results of bivariate probit model explaining simultaneously highbrow art (art1234_5) and movie (mov1234_5) consumption when age-cohort 40-45 and upper secondary school level education (edu5) are the reference values. The gender effect is similar than in table 5. Females are more omnivore. Married citizens are more active in highbrow art consumption, but the dummy variable ‘common-law marriage’ is not significant. In the previous estimation (table 5) when the reference was age-cohort 50-54 and elementary school education that variable was significant. This indicates that the effect of ‘common-law marriage’ is related to age or educational level. Age-cohorts younger than 40 are significantly more active in movie consumption but there are no differences in highbrow art consumption.
Table 5 : Bivariate probit analysis ,
|
Art1234_5
|
Art1234_5: marginal effect
|
Art1234_5: direct marginal effect
|
Art1234_5: indirect marginal effect
|
Mov1234_5
|
gender (male=1, female=2)
|
0.422
(0.092)***
|
0.063
(0.016)***
|
0.074
(0.016)***
|
-0.011
(0.005)*
|
0.196
(0.095)*
|
Marital status: single
|
0.032
(0.182)
|
0.013
(0.030)
|
0.006
(0.032)
|
0.008
(0.010)
|
-0.141
(0.185)
|
Marital status: married
|
0.409
(0.224)(*)
|
0.058
(0.038)
|
0.071
(0.039)(*)
|
-0.014
(0.014)
|
0.249
(0.255)
|
MS: common-law marriage
|
0.286
(0.239)
|
0.043
(0.040)
|
0.050
(0.042)
|
-0.007
(0.015)
|
0.125
(0.269)
|
age15_19
|
-0.014
(0.293)
|
-0.046
(0.050)
|
-0.002
(0.051)
|
-0.044
(0.025)(*)
|
0.782
(0.425)(*)
|
age20_24
|
-0.172
(0.260)
|
-0.064
(0.043)
|
-0.030
(0.045)
|
-0.034
(0.018)(*)
|
0.612
(0.324)(*)
|
age25_29
|
0.061
(0.252)
|
-0.019
(0.042)
|
0.011
(0.044)
|
-0.030
(0.014)*
|
0.534
(0.252)*
|
age30_34
|
0.109
(0.278)
|
-0.038
(0.046)
|
0.019
(0.049)
|
-0.057
(0.021)**
|
1.015
(0.361)**
|
age35_39
|
0.335
(0.238)
|
0.027
(0.039)
|
0.058
(0.042)
|
-0.031
(0.014)*
|
0.561
(0.254)*
|
age40_44 = C
|
--
|
--
|
--
|
--
|
--
|
age45_49
|
0.123
(0.195)
|
0.002
(0.033)
|
0.021
(0.034)
|
-0.019
(0.012)
|
0.342
(0.220)
|
age50_54
|
0.011
(0.214)
|
0.012
(0.035)
|
0.002
(0.037)
|
0.010
(0.011)
|
-0.174
(0.189)
|
age55_59
|
0.026
(0.207)
|
0.007
(0.034)
|
0.005
(0.036)
|
0.003
(0.010)
|
-0.046
(0.187)
|
age60_64
|
0.009
(0.196)
|
0.001
(0.033)
|
0.002
(0.034)
|
-0.001
(0.011)
|
0.014
(0.189)
|
age65_69
|
0.012
(0.242)
|
-0.002
(0.039)
|
0.002
(0.042)
|
-0.005
(0.013)
|
0.083
(0.234)
|
age70_74
|
-0.253
(0.236)
|
-0.009
(0.039)
|
-0.044
(0.041)
|
0.035
(0.013)**
|
-0.627
(0.218)**
|
edu1
|
0.020
(0.279)
|
-0.003
(0.047)
|
0.036
(0.049)
|
-0.007
(0.022)
|
0.119
(0.398)
|
edu2
|
-0.646
(0.208)***
|
-0.077
(0.036)*
|
-0.113
(0.037)**
|
0.035
(0.013)**
|
-0.636
(0.224)**
|
edu3
|
-0.198
(0.225)
|
-0.025
(0.038)
|
-0.035
(0.039)
|
0.010
(0.013)
|
-0.172
(0.235)
|
edu4
|
-0.065
(0.178)
|
-0.002
(0.031)
|
-0.011
(0.031)
|
0.009
(0.011)
|
-0.169
(0.201)
|
edu5
|
ccc
|
|
ccc
|
ccc
|
ccc
|
edu6
|
0.428
(0.198)*
|
0.067
(0.034)*
|
0.075
(0.035)*
|
-0.007
(0.012)
|
0.132
(0.209)
|
edu7
|
0.229
(0.253)
|
0.023
(0.042)
|
0.040
(0.044)
|
-0.017
(0.017)
|
0.308
(0.297)
|
edu8
|
0.806
(0.465)(*)
|
0.071
(0.081)
|
0.141
(0.081)(*)
|
-0.070
(0.038)(*)
|
1.256
(0.681)(*)
|
edu9
|
0.492
(0.348)
|
0.080
(0.059)
|
0.086
(0.062)
|
-0.006
(0.014)
|
0.103
(0.258)
|
spouse-edu1
|
-0.273
(1.375)
|
-0.029
(0.347)
|
-0.048
(0.241)
|
0.019
(0.116)
|
-0.341
(2.088)
|
spouse-edu2
|
0.044
(0.242)
|
0.038
(0.041)
|
0.008
(0.042)
|
0.030
(0.015)*
|
-0.540
(0.256)*
|
spouse-edu3
|
-0.156
(0.270)
|
-0.013
(0.046)
|
-0.027
(0.047)
|
0.014
(0.016)
|
-0.250
(0.294)
|
spouse-edu4
|
-0.270
(0.200)
|
-0.021
(0.035)
|
-0.047
(0.035)
|
0.027
(0.014)(*)
|
-0.476
(0.235)*
|
spouse-edu5
|
ccc
|
|
ccc
|
ccc
|
ccc
|
spouse-edu6
|
-0.012
(0.245)
|
0.009
(0.043)
|
-0.002
(0.043)
|
0.011
(0.014)
|
-0.200
(0.254)
|
spouse-edu7
|
0.072
(0.326)
|
0.017
(0.055)
|
0.013
(0.057)
|
0.004
(0.020)
|
-0.079
(0.360)
|
spouse-edu8
|
-0.374
(0.384)
|
-0.036
(0.073)
|
-0.065
(0.067)
|
0.029
(0.025)
|
-0.526
(0.436)
|
spouse-edu9
|
0.575
(0.469)
|
0.091
(0.081)
|
0.100
(0.080)
|
-0.009
(0.019)
|
0.170
(0.337)
|
Area1
|
0.359
(0.146)*
|
0.030
(0.025)
|
0.063
(0.026)*
|
-0.033
(0.009)***
|
0.593
(0.141)***
|
Area2
|
0.368
(0.164)*
|
0.026
(0.027)
|
0.064
(0.029)*
|
-0.038
(0.010)***
|
0.678
(0.161)***
|
Area3
|
0.203
(0.179)
|
0.004
(0.030)
|
0.035
(0.031)
|
-0.031
(0.010)**
|
0.556
(0.174)**
|
Household’s size
|
0.035
(0.060)
|
-0.002
(0.011)
|
0.006
(0.011)
|
-0.009
(0.004)*
|
0.153
(0.076)*
|
Children <7
|
-0.217
(0.094)*
|
-0.033
(0.016)*
|
-0.038
(0.016)*
|
0.005
(0.006)
|
-0.087
(0.104)
|
Children 7-17
|
-0.295
(0.130)*
|
-0.034
(0.021)(*)
|
-0.051
(0.023)*
|
0.018
(0.008)*
|
-0.317
(0.150)*
|
Household Incomes
|
0.278D-5
(0.563D-5)
|
-0.234D-6
(0.906D-6)
|
0.486D-6
(0.989D-6)
|
-0.720D-6
(0.499D-6
|
0.129D-4
(0.900D-5)
|
Constant
|
-0.186
(0.271)
|
|
|
|
-0.280
(0.301)
|
ρ = 0.631 (0.047)***
|
|
|
|
|
|
(standard error in parenthesis.). Art1234_5: 0 =’ Never in the last twelve months’, 1 = ‘Less often’ or ‘Several times per month’ or ‘Several times per week’ or ‘Every day’ - Mov1234_5 classified in the same way.
Log Likelihood = - 985.15, AIC = 1.633, BIC = 1.953, HQIC = 1.754, (*), *, **, *** = significance level 10%,5%,1%,0,1% .
|
Elementary education (edu2) in relation to upper secondary (graduate) level education (edu5) lowers significantly both highbrow art and movies at the cinema consumption. College (edu6) or bachelor’s degree (edu8) educated are more active in highbrow art participation. The results in tables 5 and 6 indicate that the most omnivore citizens are those with a bachelor’s degree. They go to see art exhibition, opera or theatrical performances and also movies at the cinema. Spouse’s education in relation to upper secondary level education is significantly lowering cinema activity if the spouse has either elementary school (edu2) or vocational school or course (edu4) education. The effects of the area as well as the family size or the number of children are similar in table 6 and in table 5.
The marginal effects of age-cohorts in tables 5-5 and 5-6 are different since the reference value is different: the age-cohort 50-54 in table 5-5 and the age-cohort 40-44 in table 5-6, but only the level is different. Otherwise they reveal the same information. In figure 1 there are direct (DirME5 and DirME6) and indirect (IndME5 and IndME6) marginal effects of age-cohorts in tables 5 and 6. The values are highly correlated: ρDirME5, DirME6, age = 0.958, ρIndME5, IndME6,age = 0.981. The direct and indirect marginal effects of age-cohorts are not significantly correlated. The marginal effects in tables 5-5 and 5-6 are not all significantly different from zero, but still it is worth noticing that age-cohort 20-24 has the most negative attitude towards highbrow arts and they favour movies at the cinema. Figure 1 reveals that the largest amplitudes from the negative indirect marginal effect to the positive direct marginal effect is by the age-cohorts 30-34 and 35-39. The amplitude for the cohort 30-34 is (-0.073, 0.023) ↔ 0.096 and for the cohort 35-39 (-0.045, 0.058) ↔ 1.003.
Figure 5 : Direct and indirect marginal effect of age-cohorts on highbrow art consumption
The age-cohorts 30-34 and 35-39 are most omnivore but this indication is unreliable to some extent. The marginal effects of education (Figure 2) are more reliable since mainly they are significantly different from zero.
Figure 5 : Direct and indirect marginal effects of education on highbrow art consumption
The marginal effects of education in tables 5 and 6 are highly correlated: ρDirME5, DirME6, edu = 0.977, ρIndME5, IndME6, edu = 0.993. The direct and indirect marginal effects are highly negatively correlated (ρDirME5, IndME5, edu = -0.859 and ρDirME6, IndME6, edu = -0.884) indicating that those active in highbrow art consumption are active also in cinema consumption.
The results with the Finnish data are in harmony with the results of Kracman (1996), Bihagen and Katz-Gerro (2000) or Vander Stichele and Laermans (2006) who show that educational level, gender and age are related with performing arts consumption. However, the effect of education is not linear. It is true that better and longer education leads to higher probability of consuming performing arts, but those with master’s level education are not necessarily more active than people with a bachelor’s degree (obtained from university). If the bachelor’s degree is obtained from a university of applied sciences (polytechnic), the marginal effect is positive but less positive than for those with a university level bachelor’s degree. Incomes do not seem to explain cultural participation but the number of children significantly reduces cultural participation, both performing arts and movies.
For the purpose of analyzing cultural participation using bivariate probit analysis, the original data was recoded and reclassified into two categories: yes vs. no. However, about 5 percent of the respondents in the sample could be classified to the category ‘often’ (‘every day’ + ‘several times per week’ + ‘several times per month’) in participating in performing arts events. With multinomial logit analysis, the three groups can be studied but the indirect effects (between performing arts and movies) that could be evaluated by using bivariate probit model could not be obtained. Still, this classification into three groups is reasonable. The results of the MNL analysis to explain performing arts consumption are presented in tables 5-7 and 5-8. In table 5-7 the reference values of the age-cohort and educational levels are 50-54 years old and elementary school (edu2).
Table 5 : Multinomial logit (MNL) analysis
|
y = 1
|
y = 2
|
marginal effects: y = 0
|
marginal effects: y = 1
|
marginal effects: y = 2
|
Marginal effects averaged over individuals:
y = 0
|
Marginal effects averaged over individuals:
y = 1
|
Marginal effects averaged over individuals:
y = 2
|
Averages of Individual Elasticities of Probabilities:
y = 0
|
Averages of Individual Elasticities of Probabilities:
y = 1
|
Averages of Individual Elasticities of Probabilities:
y = 2
|
Gender (male=1, female=2)
|
0.771
(0.159)***
|
1.156
(0.313)***
|
-0.090
(0.018)***
|
0.078
(0.019)***
|
0.013
(0.008)(*)
|
-0.098
|
0.076
|
0.023
|
-1.042
|
0.153
|
0.750
|
Marital status: single
|
-0.075
(0.311)
|
0.497
(0.572)
|
0.007
(0.036)
|
-0.021
(0.038)
|
0.015
(0.014)
|
0.006
|
-0.032
|
0.026
|
0.005
|
-0.011
|
0.112
|
Marital status: married
|
0.562
(0.343)(*)
|
-0.499
(0.746)
|
-0.061
(0.040)
|
0.087
(0.043)*
|
-0.026
(0.018)
|
-0.063
|
0.109
|
-0.045
|
-0.211
|
0.062
|
-0.454
|
MS: common-law marriage
|
0.275
(0.380)
|
0.108
(0.789)
|
-0.031
(0.044)
|
0.035
(0.047)
|
-0.003
(0.019)
|
-0.033
|
0.039
|
-0.006
|
-0.037
|
0.009
|
-0.019
|
age15_19
|
-0.056
(0.522)
|
-0.505
(1.093)
|
0.008
(0.060)
|
0.004
(0.065)
|
-0.012
(0.027)
|
0.010
|
0.011
|
-0.021
|
0.004
|
0.000
|
-0.028
|
age20_24
|
-0.443
(0.432)
|
-0.615
(0.797)
|
0.052
(0.050)
|
-0.046
(0.052)
|
-0.006
(0.019)
|
0.056
|
-0.046
|
-0.011
|
0.020
|
-0.005
|
-0.014
|
age25_29
|
0.166
(0.427)
|
-2.048
(1.201)(*)
|
-0.011
(0.049)
|
0.069
(0.055)
|
-0.058
(0.030)(*)
|
-0.007
|
0.108
|
-0.101
|
-0.009
|
0.003
|
-0.161
|
age30_34
|
0.244
(0.467)
|
0.321
(0.887)
|
-0.028
(0.054)
|
0.026
(0.056)
|
0.003
(0.021)
|
-0.031
|
0.026
|
0.005
|
-0.013
|
0.002
|
0.007
|
age35_39
|
0.602
(0.437)
|
0.544
(0.817)
|
-0.069
(0.050)
|
0.069
(0.052)
|
0.001
(0.019)
|
-0.075
|
0.073
|
0.001
|
-0.043
|
0.005
|
0.000
|
age40_44
|
0.029
(0.385)
|
-0.902
(0.942)
|
0.329D-4
(0.044)
|
0.024
(0.048)
|
-0.024
(0.023)
|
0.002
|
0.040
|
-0.043
|
-0.001
|
0.002
|
-0.080
|
age45_49
|
0.192
(0.359)
|
0.427
(0.690)
|
-0.023
(0.041)
|
0.016
(0.043)
|
0.007
(0.016)
|
-0.025
|
0.013
|
0.012
|
-0.018
|
0.001
|
0.025
|
age50_54,C
|
---
|
|
|
|
|
|
|
|
|
|
|
age55_59
|
-0.016
(0.333)
|
1.037
(0.632)(*)
|
-0.002
(0.038)
|
-0.026
(0.040)
|
0.028
(0.015)(*)
|
-0.005
|
-0.044
|
0.048
|
-0.008
|
-0.009
|
0.107
|
age60_64
|
-0.049
(0.329)
|
1.221
(0.623)*
|
0.001
(0.038)
|
-0.034
(0.040)
|
0.033
(0.015)*
|
-0.002
|
-0.056
|
0.058
|
-0.009
|
-0.014
|
0.128
|
age65_69
|
-0.015
(0.395)
|
0.476
(0.845)
|
-0.870D-4
(0.045)
|
-0.013
(0.049)
|
0.013
(0.020)
|
-0.001
|
-0.021
|
0.022
|
-0.000
|
-0.001
|
0.030
|
age70_74
|
-0.412
(0.385)
|
1.648
(0.698)*
|
0.040
(0.044)
|
-0.093
(0.047)*
|
0.053
(0.018)**
|
0.038
|
-0.130
|
0.092
|
0.003
|
-0.023
|
0.104
|
edu1
|
1.155
(0.493)*
|
1.730
(1.225)
|
-0.136
(0.057)*
|
0.116
(0.064)(*)
|
0.019
(0.030)
|
-0.147
|
0.114
|
0.034
|
-0.046
|
0.016
|
0.046
|
edu2
|
C
|
|
|
|
|
|
|
|
|
|
|
edu3
|
0.667
(0.331)*
|
0.733
(0.866)
|
-0.077
(0.038)*
|
0.073
(0.044)(*)
|
0.004
(0.022)
|
-0.083
|
0.076
|
0.007
|
-0.040
|
0.013
|
0.018
|
edu4
|
0.869
(0.269)***
|
1.678
(0.665)**
|
-0.103
(0.031)***
|
0.079
(0.035)*
|
0.024
(0.017)
|
-0.113
|
0.071
|
0.043
|
-0.155
|
0.034
|
0.210
|
edu5
|
1.376
(0.410)***
|
3.184
(0.779)***
|
-0.166
(0.048)***
|
0.113
(0.051)*
|
0.053
(0.020)**
|
-0.182
|
0.091
|
0.092
|
-0.098
|
0.001
|
0.132
|
edu6
|
1.805
(0.321)***
|
2.551
(0.689)***
|
-0.211
(0.037)***
|
0.185
(0.040)***
|
0.026
(0.017)
|
-0.229
|
0.184
|
0.046
|
-0.400
|
0.028
|
0.205
|
edu7
|
1.392
(0.418)***
|
3.063
(0.862)***
|
-0.167
(0.049)***
|
0.118
(0.052)*
|
0.049
(0.022)*
|
-0.184
|
0.098
|
0.085
|
-0.106
|
0.008
|
0.145
|
edu8
|
2.478
(0.796)***
|
4.609
(1.066)***
|
-0.294
(0.090)***
|
0.229
(0.090)**
|
0.065
(0.022)**
|
-0.321
|
0.208
|
0.113
|
-0.100
|
-0.008
|
0.071
|
edu9
|
1.921
(0.518)****
|
3.733
(0.839)***
|
-0.229
(0.059)***
|
0.174
(0.061)**
|
0.055
(0.020)**
|
-0.250
|
0.155
|
0.095
|
-0.196
|
-0.010
|
0.166
|
spouse-edu1
|
-0.549
(0.987)
|
2.398
(1.516)
|
0.053
(0.113)
|
-0.128
(0.120)
|
0.076
(0.036)*
|
0.050
|
-0.182
|
0.132
|
0.000
|
-0.003
|
0.015
|
spouse-edu2
|
C
|
|
|
|
|
|
|
|
|
|
|
spouse-edu3
|
-0.259
(0.433)
|
0.694
(0.926)
|
0.026
(0.050)
|
-0.051
(0.054)
|
0.024
(0.023)
|
0.026
|
-0.069
|
0.042
|
0.007
|
-0.005
|
0.039
|
spouse-edu4
|
-0.363
(0.324)
|
0.378
(0.738)
|
0.039
(0.037)
|
-0.057
(0.041)
|
0.018
(0.018)
|
0.041
|
-0.072
|
0.032
|
0.047
|
-0.018
|
0.116
|
spouse-edu5
|
0.393
(0.539)
|
1.268
(1.083)
|
-0.049
(0.062)
|
0.024
(0.066)
|
0.024
(0.026)
|
-0.054
|
0.012
|
0.043
|
-0.015
|
0.001
|
0.035
|
spouse-edu6
|
0.119
(0.391)
|
0.613
(0.791)
|
-0.015
(0.045)
|
0.002
(0.048)
|
0.013
(0.019)
|
-0.018
|
-0.006
|
0.023
|
-0.018
|
-0.002
|
0.069
|
spouse-edu7
|
0.164
(0.516)
|
0.909
(0.993)
|
-0.022
(0.059)
|
0.001
(0.062)
|
0.020
(0.023)
|
-0.025
|
-0.010
|
0.035
|
-0.010
|
-0.001
|
0.041
|
spouse-edu8
|
-0.514
(0.562)
|
-1.171
(1.345)
|
0.062
(0.065)
|
-0.043
(0.070)
|
-0.019
(0.033)
|
0.068
|
-0.035
|
-0.033
|
0.013
|
-0.002
|
-0.021
|
spouse-edu9
|
1.152
(0.690)(*)
|
2.539
(0.967)**
|
-0.138
(0.078)(*)
|
0.097
(0.078)
|
0.041
(0.020)*
|
-0.152
|
0.081
|
0.071
|
-0.101
|
-0.010
|
0.099
|
Area1
|
0.533
(0.248)*
|
1.402
(0.609)*
|
-0.065
(0.029)*
|
0.040
(0.032)
|
0.025
(0.015)(*)
|
-0.072
|
0.029
|
0.043
|
-0.256
|
0.011
|
0.447
|
Area2
|
0.583
(0.273)*
|
1.288
(0.649)*
|
-0.070
(0.031)*
|
0.049
(0.034)
|
0.021
(0.016)
|
-0.077
|
0.041
|
0.036
|
-0.134
|
0.015
|
0.195
|
Area3
|
0.280
(0.299)
|
0.588
(0.739)
|
-0.033
(0.035)
|
0.024
(0.038)
|
0.009
(0.018)
|
-0.037
|
0.021
|
0.016
|
-0.029
|
0.007
|
0.046
|
Household’s size
|
0.062
(0.104)
|
0.157
(0.233)
|
-0.008
(0.012)
|
0.005
(0.013)
|
0.003
(0.006)
|
-0.008
|
0.004
|
0.005
|
-0.130
|
0.015
|
0.238
|
Children <7
|
-0.423
(0.147)**
|
-0.334
(0.350)
|
0.049
(0.017)**
|
-0.049
(0.019)**
|
0.001
(0.001)
|
0.052
|
-0.054
|
0.002
|
0.138
|
-0.039
|
-0.002
|
Children 7-17
|
-0.488
(0.213)*
|
-2.359
(1.038)*
|
0.063
(0.025)**
|
-0.012
(0.031)
|
-0.051
(0.022)*
|
0.072
|
0.017
|
-0.089
|
0.068
|
-0.014
|
-0.324
|
Household Incomes
|
0.129D-4
(0.173D-4)
|
-0.431D-4
(0.517D-4)
|
-0.128D-5
(0.025)
|
0.271D-5
(0.226D-5)
|
-0.142D-5
(0.128D-5)
|
0.000
|
0.000
|
0.000
|
-0.034
|
0.015
|
-0.199
|
Constant
|
-1.339
(0.428)***
|
-6.840
(1.107)***
|
0.175
(0.050)***
|
-0.025
(0.059)
|
-0.150
(0.035)***
|
|
|
|
|
|
|
Explanatory variable: y = “How many times in the last twelve months have you seen an art exhibition, opera or theatrical performance?” = 0 (never), 1 (less often) or 2 (daily, several times per week or several times per month).
McFadden pseudo R2 = 0.146, χ2 = 246.006***, AIC = 1.261, BIC = 1.569, HQIC = 1.371
(*), *, **, *** = significance level 10%,5%,1%,0,1% .
Partial derivatives of probabilities with respect to the vector of characteristics are computed at the means of the Xs. Probabilities at the mean vector are Prob(y=0) = 0.133, Prob(y=1) = 0.840, Prob(y=2) = 0.027
|
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