There are a bunch of datasets, e.g. world values survey, alcohol usage report etc which present good amounts of data over long periods of time.
However, these aren't really panel datasets (In some cases, they can't be, e.g. many ageing reports) - i.e. the entities surveyed aren't the same over the various "waves".
So typical longitudinal models such as fixed effects don't make sense.
In such cases, are pooled cross sections the best way to analyze the data in terms of relationship between variables, and if so, what sort of causality can be claimed, assuming each wave grabbed random, representative samples....
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