  It is hard to exaggerate the role of economic aggregators -- functions that
summarize numerous and / or heterogeneous data -- in economic models since the
early XX$^{th}$ century. In many cases, as witnessed by the pioneering works of
Cobb and Douglas, these functions were information quantities tailored to
economic theories, i.e. they were built to fit economic phenomena. In this
paper, we look at these functions from the complementary side: information. We
use a recent toolbox built on top of a vast class of distortions coined by
Bregman, whose application field rivals metrics' in various subfields of
mathematics. This toolbox makes it possible to find the quality of an
aggregator (for consumptions, prices, labor, capital, wages, etc.), from the
standpoint of the information it carries. We prove a rather striking result.
  From the informational standpoint, well-known economic aggregators do belong
to the \textit{optimal} set. As common economic assumptions enter the analysis,
this large set shrinks, and it essentially ends up \textit{exactly fitting}
either CES, or Cobb-Douglas, or both. To summarize, in the relevant economic
contexts, one could not have crafted better some aggregator from the
information standpoint. We also discuss global economic behaviors of optimal
information aggregators in general, and present a brief panorama of the links
between economic and information aggregators.
  Keywords: Economic Aggregators, CES, Cobb-Douglas, Bregman divergences
