Tag Archives: statistical models

Forecasting GDP in the presence of breaks: when is the past a good guide to the future?

George Kapetanios, Simon Price and Sophie Stone.

Structural breaks are a major source of forecast errors, and few come larger than the recent financial crisis and subsequent recession.  After a break, formerly good models stop working.  One way to cope is to discount the past in a data driven way.  We try that, and find that shortly after the crash it was best to ignore almost all data older than three years – but now it is again time to take a longer view.
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Filed under Macroeconomics, New Methodologies