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

mentioned above, that it is impossible to identify all the individuals that suffer from a particular
illness, if purchase or intake of medicine is used to determine the illness the for the purpose of an
analysis. <strong>An</strong>d finally, an obstacle with these observational data is the endogeneity of treatment,
since the patients that are the most effected by the illness are more likely to get treated. 47
Despite these drawbacks, this is the approach taken, due to the nature of the data. There are also
some advantages to this approach. Observational data avoid the self-reporting bias that occurs in
interviews. Self-reported measures of health have the weakness that people are likely to understate
their condition of health because this for instance can influence their eligibility for an early
retirement pension or because not working can be legitimized by ill health. 48 On the other hand
individuals can also be inclined to overstate their condition of health, especially in the case of
mental illness which still is attached with social stigma. 49
In the medicine dataset the population of MTX users is identified by the individuals who buy
MTX 50 on prescription in a pharmacy in Denmark between 1995 and 2003. MTX comes in tablet
and liquid form, and the inclusion of individuals taking MTX in liquid form gave rise to a problem,
since the liquid form of MTX cannot be measured in defined daily dosages. The consumption of
MTX for these individuals had the value zero, which is not really the case. It was decided to include
individuals using the liquid form anyway, since it gives a more true view of the sample population,
and it was a question of only about 1 % of the population. Instead of having some individuals with a
value of 0 of MTX consumption, their consumption was coded to the mean value of the MTX
consumption, since this variable otherwise would be downward biased.
If an individual buys MTX in a given year, the individual is part of the sample population that year,
otherwise not. This implies that the sample population is not constant from year to year. I am
dealing with an unbalanced panel, which is the case when some time periods are missing for some
individuals. 51
In this case it is the way that the sample population is defined that is causing the panel to be
unbalanced, since it is not sure that individuals are in need of MTX in consecutive years. When
rotation in and out of the panel is random, it is not a problem for the validity of the estimations. But
whether individuals buy MTX or not, is certainly not decided upon randomly, but instead it is to a
high degree related to the state of their health, which is an unobservable in this analysis.
47
Duggan and Evans (2005)
48
<strong>An</strong>derson and Burkhauser (1985), Ruhm (1992).
49
Savoca (1992)
50
ATC-code L04AX03 or L01BA01
51
Wooldridge (2002)
31