The point of this discussion is that prediction markets should be well-calibrated, but this is not a sufficient condition for their usefulness. They must also provide accurate predictions, with relatively tight distributions. The maximum allowable dispersion of the distribution will depend on the materiality of the forecast error. That is, the prediction should be accurate enough, such that the maximum allowable error would not cause the decision-maker to alter his or her decision had the true value been known in advance.
Where the distribution of the prediction market is not tight, the market may still have some use, but not so much for being able to predict the outcome. Instead, the market will be providing information about the degree of uncertainty surrounding the outcome. This may indicate the need for greater care in assessing risks and the need for more extensive contingency planning. A flatter distribution may indicate that the market is not functioning properly (lack of information completeness, perhaps). Alternatively, a flat distribution may indicate that the variable being predicted is, simply, not predictable.
