Giacomini, R;
Altavilla, C;
Ragusa, G;
(2017)
Anchoring the yield curve using survey expectations.
Journal of Applied Econometrics
, 32
(6)
pp. 1055-1068.
10.1002/jae.2588.
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Abstract
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 can accurately predict yields, but they are typically not available for all maturities and/or forecast horizons. We show how survey expectations can be exploited to improve the accuracy of yield curve forecasts given by a base model. We do so by employing a flexible exponential tilting method that anchors the model forecasts to the survey expectations, and we develop a test to guide the choice of the anchoring points. The method implicitly incorporates into yield curve forecasts any information that survey participants have access to—such as information about the current state of the economy or forward-looking information contained in monetary policy announcements—without the need to explicitly model it. We document that anchoring delivers large and significant gains in forecast accuracy relative to the class of models that are widely adopted by financial and policy institutions for forecasting the term structure of interest rates.
Type: | Article |
---|---|
Title: | Anchoring the yield curve using survey expectations |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/jae.2588 |
Publisher version: | http://dx.doi.org/10.1002/jae.2588 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
URI: | https://discovery.ucl.ac.uk/id/eprint/1570204 |
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