Using the Yield Curve in Forecasting Output Growth and In?flation
AbstractFollowing Diebold and Li (2006), we use the Nelson-Siegel (NS, 1987) yield curve factors. However the NS yield curve factors are not supervised for a specifi?c forecast target in the sense that the same factors are used for forecasting different variables, e.g., output growth or infl?ation. We propose a modifed NS factor model, where the new NS yield curve factors are supervised for a specifi?c variable to forecast. We show it outperforms the conventional (non-supervised) NS factor model in out-of-sample forecasting of monthly US output growth and infl?ation. The original NS yield factor model is to combine information (CI) of predictors and uses factors of predictors (yield curve). The new supervised NS factor model is to combine forecasts (CF) and uses factors of forecasts of output growth or infl?ation conditional on the yield curve. We formalize the concept of supervision, and demonstrate analytically and numerically how supervision works. For both CF and CI schemes, principal components (PC) may be used in place of the NS factors. In out-of-sample forecasting of U.S. monthly output growth and infl?ation, we fi?nd that supervised CF-factor models (CF-NS, CF-PC) are substantially better than unsupervised CI-factor models (CI-NS, CI-PC), especially at longer forecast horizons.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2012-17.
Date of creation: 12 2011
Date of revision:
Contact details of provider:
Web page: http://www.econ.au.dk/afn/
Level; slope; and curvature of the yield curve; Nelson-Siegel factors; Supervised factor models; Combining forecasts; Principal components.;
Find related papers by JEL classification:
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
- G1 - Financial Economics - - General Financial Markets
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Daniela Osterrieder, 2013. "Interest Rates with Long Memory: A Generalized Affine Term-Structure Model," CREATES Research Papers 2013-17, School of Economics and Management, University of Aarhus.
- Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," CREATES Research Papers 2012-18, School of Economics and Management, University of Aarhus.
- Abdymomunov, Azamat, 2013. "Predicting output using the entire yield curve," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 333-344.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.