The level of detail in the presentation of a numerical forecast, usually thought of as the number of significant digits reported. The believability of forecasts can be influenced by how precisely they are reported. Teigen (1990) showed that more precise reporting can make a forecast more acceptable (unless such precision seems unreasonable). Teigen calls this the preciseness paradox. That is, under a wide variety of circumstances, the more precise the forecast, the more confident we are about the forecast. But the more precise the forecast, the less likely it is to turn out correct. When forecasters provide detail, they imply that they have much expertise about the topic. Thus, the preciseness paradox should be stronger for statements about the past than for predictions. It is. Consider one of Teigen’s studies. He asked subjects how much confidence they would have in different informants if they visited Iceland and received the following answers to this question:

“Owing to various price regulation measures, this year’s inflation rate was down to 5%. Was it higher last year?”


Which of these answers would you be most confident about? Teigen says that Olafur’s statement is the most general, and Larus’s the most exact. If Larus was right, so are Olafur and Jon. On the other hand, Olafur could have been right, while Larus and Jon were wrong (if inflation were to be 14%, for example). However, most of the subjects (16) were most confident in Larus and eight subjects were most confident in Jon, while only seven subjects were most confident in Olafur. When the statements about inflation were converted from the past to represent a forecast about next year’s inflation, the confidence in the most precise forecast (by Larus) decreased (to 6 of 34 subjects) but did not disappear. Teigen suggests that this occurs because people do not expect forecasters to be able to provide precise forecasts of inflation. When people expect that experts can make good forecasts, added detail and preciseness are likely to lead them to have more confidence in the forecasts. To avoid misplaced confidence, forecasters should ensure that there is no false precision in their reports.