It is common for a majority of people to rank themselves as better than average on simple tasks and worse than average on difficult tasks. The literature takes for granted that this apparent misconfidence is problematic. We argue, however, that this behavior is consistent with purely rational Bayesian updaters. In fact, better-than-average data alone cannot be used to show overconfidence; we indicate which type of data can be used. Our theory is consistent with empirical patterns found in the literature.

We provide an example that shows that in the Alesina and Angeletos (2005) model one can obtain multiplicity even if luck plays no role in the economy. Thus, it is not critical that the noise to signal ratio be increasing in taxes, or that desired taxes are increasing in the noise to signal ratio.