  I congratulate all the authors for their insightful papers with wide-ranging
contributions. The articles demonstrate the power and elegance of the Bayesian
inference paradigm. In particular, it allows to incorporate prior knowledge as
well as hierarchical model building in a convincing way. Regarding the latter,
the contribution by Raftery, Alkema and German is a very fascinating piece, as
it addresses a set of problems of great public interest and presents
predictions for the world populations and other interesting quantities with
uncertainty regions. Their approach is based on a hierarchical model, taking
various characteristics into account (e.g., fertility projections). It would
have been very difficult to come up with a "better" solution which would be as
clear in terms of interpretation (in contrast to a "black-box machine") and
which would provide (model-based) uncertainties for the predictions into the
future.
