  We compute the Bayesian evidences for one- and two-parameter models of
evolving dark energy, and compare them to the evidence for a cosmological
constant, using current data from Type Ia supernova, baryon acoustic
oscillations, and the cosmic microwave background. We use only distance
information, ignoring dark energy perturbations. We find that, under various
priors on the dark energy parameters, LambdaCDM is currently favoured as
compared to the dark energy models. We consider the parameter constraints that
arise under Bayesian model averaging, and discuss the implication of our
results for future dark energy projects seeking to detect dark energy
evolution. The model selection approach complements and extends the
figure-of-merit approach of the Dark Energy Task Force in assessing future
experiments, and suggests a significantly-modified interpretation of that
statistic.
