Evaluation of the Australian Wage Subsidy Special Youth ...

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interview date, those who ever entered full-time education, or for whom responses were
missing in 1984, 1985 or 1986 (Richardson (1998): 5). The first of these restrictions is
not dealt with here, as it prescribes the eligible set, but is returned to subsequently. The
latter of these has been dealt with in part, with reference to the natural attrition, which
caused missing values. Apart from natural attrition, the set discarded for whom responses
were missing in 1984, 1985 or 1986 also includes those cases for whom data on some of
the regressor variables is missing. In particular, when information about the family
background is missing, or when the proportion of time in unemployment is missing, these
cases are dropped from the analysis set. Statisticians usually term this form of missing
data ‘item non-response’.
Greene (1991) points out there are two main scenarios to consider, depending on why the
data on the regressors is missing. Imputation or discarding the cases is the usual approach
to this type of missing data. Using the terminology of Griliches (1986) this type of
incomplete data is described as the ignorable case if when using the complete
observations the data are not missing for self-selection reasons 98 . In the ignorable case,
using only the complete observations is not problematic if efficiency related to the
variance is not important. The non-ignorable case, where the missing information is
systematically related to the variable being modelled, is another case of the sample
selection problem.
98 Ignorable non-response means the same as selection on observables.