10
Continued Table 2
Religion:
Catholic |
Reference | ||||
Protestant |
0.04 |
0.14 |
0.14 | ||
Orthodox |
-0.02 |
0.14 |
0.15 | ||
Other |
-0.10 |
0.18 |
0.19 | ||
Non believer |
0.08 |
0.16 |
0.16 | ||
No answer |
0.15 |
0.25 |
0.26 | ||
Cut values | |||||
Cut 1 |
-3.69 |
-3.58 | |||
Cut 2 |
-0.55 |
-0.46 | |||
No of cases |
5592 |
5592 | |||
Log likelihood |
-4834.1 |
-4852.4 | |||
Chi2-test |
Chi2(38) = 904** |
Chi2(18) = 872** | |||
Pseudo R2 |
0.086 |
0.083 | |||
Test for excluding variables |
Chi2(20) = 31.4 |
Notes: **(*) indicates statistical significance at a 1 (5) percent level. SE denotes normal standard errors, HCSE
lists White’s (1980) heteroscedasticity consistent standard errors.
The actual coefficients of ordered logit models do not give a very good idea about the effects
of changes in the explanatory variables on the predicted probabilities of falling under one of
the categories of the dependent variable (Greene 1991, 703ff). In particular, the coefficients in
Table 2 do not imply sign restrictions on the effects of changes in the explanatory variables on
the middle category, i.e. “not very satisfied”. It is therefore useful to compute marginal effects
of explanatory variables, here evaluated at the sample mean of the other variables. For
dummy variables, this is not truly a marginal effect but rather the change from zero to one.
Table 3 reports marginal effects for the variables within the reduced model of Table 2 for all
categories of life-satisfaction. Actual and predicted frequencies of the dependent variable are
given in the last line of the table. It is apparent that the model somewhat over-predicts the
number of cases falling into the middle category, a typical outcome of this class of models.
Applying the results on marginal effects to country dummies, we find that although all
countries show lower happiness levels than the Czech Republic, being non-Czech has varying
implications with respect to the probability of answering “not very satisfied”, the middle
category of happiness. In addition, the probabilities of falling into the top or bottom categories