Financial analysts are professional forecasters. But why study the economy, a traditional lagging indicator, if you want to forecast investment measures? The investment record of this process is only rarely better than random and when you take account of the expenses of achieving these results, they come out a little bit less than chance. Why do it at all with that unconvincing record of success? Economic forecasts are supposed to be meaningful. But if you believe that asset prices reflect a forecast of future outcomes, it would seem quite difficult to use a technique that reaches back into the past to get an idea of the future. But that is what economic forecasting does. It is teased for forecasting three recessions for every one hat actually happens. No wonder it is called the dismal science.
Financial Times economics columnist Sir Samuel Brittan makes a pointed reflection on the practice of forecasting: ''The golden rule for economic forecasters is: forecast what has already happened and stay at the cautious end. Forecasts tell us more about the present and the recent past than about the future."
Poor methods, bad models and inaccurate data are all blamed for the recurrence of serious forecast errors. But according to Oxford economics professor David Hendry, these are not the primary cause of systematic mistakes. Rather, unanticipated large changes within the forecast period are the culprit. The primary fault of economic forecasting is in not rapidly adjusting the forecasts once they go wrong.
Hendry uses an analogy from rocket science: a rocket to the moon is forecast to reach there at a precise time and location, and usually does so. But if it is hit by a meteor and knocked off course or destroyed the forecast is systematically badly wrong. That outcome need not suggest poor engineering or bad forecasting models and certainly does not suggest that Newtonian gravitation theory is incorrect.
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