Missing data plagues all surveys, and to a degree the New Zealand Census suffers from the same malaise.
While it is not a high level of missingness, it is present. If not correctly dealt with; just deleting cases
with missing data will lead to biased conclusions, particularly if the missingness mechanism is NMAR.
Some missing data may be inevitable; sometimes a respondent may be incapable of answering a question.
This is usually MAR. If however the respondent refuses to answer a question because of say having a
high income, then the results of the income question will be biased. Over time there have been a growing
number of people employing avoidance tactics so as not to be classified as a refusal, but to make
enumeration just too difficult. Anecdotal evidence among enumerators shows that this accounts for about
5% of respondents.
Scheffer, J. (2001), Issues in data collection: missing data and the 2001 New Zealand census, Research Letters in the Information and Mathematical Sciences, 2, 55-61