A forecasting system in aircraft autopilot that can accurately forecast when the plane hits the mountain is always wrong.
Forecasting when the forecast depends on the actions of agents that can be informed by the forecast changes the game. If the Fed model forecasts recession and the Fed takes action to prevent it from happening, it changes everything.
Only a forecasting model that is not observed/believed by policy makers can predict without intervention.
Layman's idea of forecasting: Predict what happens in the future.
Economic forecasting: Forecast is input for actions. Predict what happens in the future, using this model, these variables, and everything else stay the same. You can check afterward if the model is an accurate forecaster by removing the changes caused by variables outside the model.
It is always harder to accurately forecast actual recession, than it is to forecast the predictions of the Fed model. You don't need an information edge there, just information parity.
When the Fed takes action, it is usually a very rational action, with a clear-defined goal of long-term economic health. This makes their actions easier to predict than other market participants.
So you went the hard route, forecasting the highly complex system directly, but then "variables outside the model" caused the "accurate" model to not perform well? You don't buy anything with that, since you live in a world with outside variables which mess up your predictions. The solution is to make your model actually accurate, by incorporating these "variables outside the model": Predict what others will predict.
Forecasting when the forecast depends on the actions of agents that can be informed by the forecast changes the game. If the Fed model forecasts recession and the Fed takes action to prevent it from happening, it changes everything. Only a forecasting model that is not observed/believed by policy makers can predict without intervention.
Layman's idea of forecasting: Predict what happens in the future.
Economic forecasting: Forecast is input for actions. Predict what happens in the future, using this model, these variables, and everything else stay the same. You can check afterward if the model is an accurate forecaster by removing the changes caused by variables outside the model.