In his 1995 paper, Hill points out that random samples from random samples will usually give rise to data that satisfy Benford's law. He mentions a newspaper frontpage as an example where data may come from economics, sports, or weather forecast; their mixed aggregate will follow Benford's law whereas individual distributions may not.
Durtschi et al. (2004), however, put the emphasis on individual variables being the outcome of several variables, e.g. accounts being a product of quantity sold and prices, for Benford's law to hold (among other conditions).
In the literature on Benford's law, the choice for analysing either all variables together (Hill) or variables separately (Durtschi) is rarely justified. Often, the two are combined. This extends to the treatment of longitudinal data where observations are sometimes analysed by period (e.g. a survey wave) and sometimes lumped together, effectively ignoring their longitudinal character.
My data contain several variables (communions, marriages, baptisms) from twenty parishes for ten successive years. Is it acceptable to
lump the data together across parishes and years
analyse all variables together instead of analysing them separately?