  We investigate whether experts possess differential expertise when making
predictions. We note that this would make it possible to aggregate multiple
predictions into a result that is more accurate than their consensus average,
and that the improvement prospects grow with the amount of differentiation.
Turning this argument on its head, we show how differentiation can be measured
by how much weighted aggregation improves on simple averaging. Taking
stock-market analysts as experts in their domain, we do a retrospective study
using historical quarterly earnings forecasts and actual results for large
publicly traded companies. We use it to shed new light on the Sinha et al.
(1997) result, showing that analysts indeed possess individual expertise, but
that their differentiation is modest. On the other hand, they have significant
individual bias. Together, these enable a 20%-30% accuracy improvement over
consensus average.
