Modelling Structural Breaks
A key aspect of the financial crisis was the lack of fore-knowledge, so analyses of forecasting in the face of breaks, during breaks and of breaks themselves remain a central focus. In a world where breaks are unanticipated and occur intermittently, it is easy to understand why economic forecasting has a poor track record of missing major changes, and being systematically wrong for prolonged periods. We are developing improved forecasting methods; approaches to try and forecast breaks, or failing that, forecasting during breaks; and building robust forecasting devices. Importantly, if agents were to use such devices, a new basis for both economics and empirical models must be forged. New data sources, such as Google Trends, provide disaggregated high-frequency information on a vast scale, both allowing the possibility of improved ‘nowcasts’ for flash estimates of GNP, inflation etc., and providing incipient information on agents’ reactions to changes to help predict breaks and during breaks.
Project Leader / Primary Investigator
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