Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model

Siem Jan Koopman and Michel van der Wel ()

International Journal of Forecasting, 2013, vol. 29, issue 4, 676-694

Abstract: We extend the class of dynamic factor yield curve models in order to include macroeconomic factors. Our work benefits from recent developments in the dynamic factor literature related to the extraction of the common factors from a large panel of macroeconomic series and the estimation of the parameters in the model. We include these factors in a dynamic factor model for the yield curve, in which we model the salient structure of the yield curve by imposing smoothness restrictions on the yield factor loadings via cubic spline functions. We carry out a likelihood-based analysis in which we jointly consider a factor model for the yield curve, a factor model for the macroeconomic series, and their dynamic interactions with the latent dynamic factors. We illustrate the methodology by forecasting the U.S. term structure of interest rates. For this empirical study, we use a monthly time series panel of unsmoothed Fama–Bliss zero yields for treasuries of different maturities between 1970 and 2009, which we combine with a macro panel of 110 series over the same sample period. We show that the relationship between the macroeconomic factors and the yield curve data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Finally, we perform an extensive out-of-sample forecasting study. Our main conclusion is that macroeconomic variables can lead to more accurate yield curve forecasts.

Keywords: Fama–Bliss data set; Kalman filter; Maximum likelihood; Yield curve (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (12)

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Related works:
Working Paper: Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:29:y:2013:i:4:p:676-694

DOI: 10.1016/j.ijforecast.2012.12.004

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