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| Author | Carlo A. Favero, Linlin Niu, Luca Sala |
| Content | This paper addresses the issue of forecasting the term structure.We provide a unified state-space modeling framework that encompasses different existing discrete-time yield curve models. Within such framework we analyze the impact of two modeling choices, namely the imposition of no-arbitrage restrictions and the size of the information set used to extract factors, on the forecasting performance. Using US yield curve data, we find that both no-arbitrage and large information help in forecasting but no model uniformly dominates the other. No-arbitrage models are more useful at shorter horizon for shorter maturities. Large information sets are more useful atlonger horizons and longer maturities. We also find evidence for a significant feedback from yield curve models to macroeconomic variables that could be exploited for macroeconomic forecasting. |
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| Keywords | Yield curve, terms tructure of interest rates, forecasting, large data set, factor models |
