Maybe. When you construct an unbalanced panel of responding persons, you take all of the responding persons from each wave and stack them into a long file that has one record per person per wave.
The weight that could be used to weight this sample is the cross-sectional responding person weight from each wave. That is, in their Wave 1 observation, the person would be weighted by their Wave 1 cross-sectional responding person weight, their Wave 2 observation would be weighted by their Wave 2 cross-sectional responding person weight, and so on.
Similarly, if you are constructing an unbalanced panel of enumerated persons, then you could use the cross-sectional enumerated person weight.
If you pool, say, five waves of data together, the sum of the weights will be around 100 million (that is, five times the average population size between 2001 and 2005). Therefore, you may wish to rescale the weights by dividing the total by the number of waves you have included in the unbalanced panel.
The decision to weight the sample in this way depends on the type of analysis you are undertaking on the unbalanced panel. For example:
- If your analysis is of uncommon events and you are effectively taking a pooled sample, then the weighting strategy suggested above should be fine.
- Alternatively, if your analysis requires at least two observations on the same individual, then you will be dropping those people who are only interviewed once. The cross-sectional weights, therefore, will not be appropriate (nor will the longitudinal weights).