An Analysis on Danish Micro Data - School of Economics and ...

labour force participants only, as was done in section 6.3. Table 10 displays the marginal effects
from the random effects estimation, using a binary indicator of the use of antidepressants.
Table 10 Marginal effects - random effects Tobit estimation with a binary indicator of antidepressant use
dy/dx s.e.
ad_dummy† 7.6434 10.0590
mtx -0.0202 0.0232
wageinc 0.0002*** 0.0000
age 2.6441 1.9329
ab02† 8.1471 14.4090
ab36† -8.6103 10.1580
ab79† -6.9359 9.4423
ab1014† 9.8960 7.5546
single† -9.3879 6.6687
ieland1† 68.6304** 26.4660
ieland2† 59.0027 36.7330
short† 3.4717 6.5382
higher† 5.5635 7.8422
agesq -0.0155 0.0225
useofmedicin 0.0003 0.0047
u 0.7096 1.3033
No. of obs
No. of groups
Note: † For dummy variables dy/dx is for discrete change from 0 to 1
The reference categories are less developed county of origin, and basic level of education.
The significance levels are indicated as follows: 10 % - *, 5 % - **, 1 % - ***.
As can be seen from table 10, the use of antidepressants has a positive marginal effect on the
number of days a person is employed, but the result is not significant. In general the marginal
effects from estimation on employment days are numerically larger compared to the results from the
estimations performed in chapter 6. The tests of endogeneity and sample selection are not
performed here, as this estimation is only thought as tentatively.
The results should be interpreted with great caution, as these results are based on a small sample
size, only 1388 observations consisting of 573 individuals. In addition all the drawbacks mentioned
in section 6.6 also apply here.
The results from table 10 show that the marginal effects become much larger when employing a
continuous outcome variable, but because of the above-mentioned reasons it should be emphasized
once more that the results displayed in table 10 are only tentatively and meant as an inspirational
basis for further research.
1388
573
67