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3.2
Data and descriptive statistics
The outcomes of interest in this study are the occurrence of sickness absence,
unemployment, and receiving DB up to 15 months after the experiment was conducted.
In the analysis, we use data from the SIA that combine information from several data
sources. First of all, data from the caseworker administration system, containing
information of when and if Sassam and AM were performed, are linked to the benefit
payment register (both disability and sickness benefits). Spell information on
unemployment from the public employment services were then merged to these data.
The registers also include basic individual information on gender, age, and educational
level.
Descriptive statistics on the experimental population is presented in Table 1. From this
table we can see that the share of individuals born on an even day (S-treated) and the
share born on an even day in an even month (A-treated) is 48.1 and 49.5 percent,
respectively. This is almost exactly the same shares as for the total population (see
Appendix A) and close to what is theoretically expected (179/365.25 = 0.490 and 89/179
= 0.497). This provides some evidence that caseworkers have not intentionally made the
screening to the experiment population on the date of birth. The mean differences
between treated and controls are overall very small. There are, however, some
statistically significant differences worth discussing.
The share of women among the S-treated is higher than among the S-controls, and the
S-treated are also younger on average. Perhaps the most problematic difference is the
fact that the S-treated have on average more historic days on sickness absence than the
S-controls. No significant differences are found between A-treated and A-controls.
