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Anchoring the yield curve using survey expectations

  • Carlo Altavilla
  • Raffaella Giacomini

    ()

    (Institute for Fiscal Studies and UCL)

  • Giuseppe Ragusa

The dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations are accurate predictors of yields, but only for very short maturities. We argue that this is partly due to the ability of survey participants to incorporate information about the current state of the economy as well as forward-looking information such as that contained in monetary policy announcements. We show how the informational advantage of survey expectations about short yields can be exploited to improve the accuracy of yield curve forecasts given by a base model. We do so by employing a flexible projection method that anchors the model forecasts to the survey expectations in segments of the yield curve where the informational advantage exists and transmits the superior forecasting ability to all remaining yields. The method implicitly incorporates into yield curve forecasts any information that survey participants have access to, without the need to explicitly model it. We document that anchoring delivers large and significant gains in forecast accuracy for the whole yield curve, with improvements of up to 52% over the years 2000-2012 relative to the class of models that are widely adopted by financial and policy institutions for forecasting the term structure of interest rates.

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File URL: http://www.cemmap.ac.uk/wps/cwp521313.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP52/13.

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Date of creation: Oct 2013
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Handle: RePEc:ifs:cemmap:52/13
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  1. Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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