Comparing Predictions and Outcomes: Theory and Application to Income Changes

Abstract

Household surveys often elicit respondents' intentions or predictions of future outcomes. The survey questions may ask respondents to choose among a selection of (ordered) response categories. If panel data or repeated cross-sections are available, predictions may be compared with realized outcomes. The categorical nature of the predictions data, however, complicates this comparison. Generalizing previous findings on binary intentions data, we derive bounds on features of the empirical distribution of realized outcomes under the "best-case" hypothesis that respondents have rational expectations and that reported expectations are best predictions of future outcomes. These bounds are shown to depend on the assumed model of how respondents form their "best prediction" when forced to choose among (ordered) categories. An application to data on income change expectations and realized income changes illustrates how alternative response models may be used to test the best-case hypothesis.predictions;categorical data;loss function;income growth