Counterfactual Predictions

The difficulties in properly anticipating key economic variables may encourage decision makers to rely on experts' forecasts. The experts' forecasts, however, may not be accurate. So, their forecasts must be empirically tested. This may induce experts to forecast strategically to pass the test. A test can be ignorantly passed if a false expert, with no knowledge of the data generating process, can pass the test. Standard tests, if they are unlikely to reject correct forecasts, can be ignorantly passed. Tests that cannot be ignorantly passed must necessarily make use of future predictions (i.e., predictions based on data not yet realized at the time the forecasts are rejected). Such tests cannot be run if, as it is customary, forecasters only report the probability of next period's events given the observed data. This result shows that it is difficult to dismiss false, but strategic, experts. This result also suggests an important role of counterfactual predictions in the empirical testing of forecasts.