Term structure and real-time learning
Pablo Aguilar () and
No 1803, Working Papers from Banco de España, Working Papers Homepage
This paper introduces the term structure of interest rates into a medium-scale DSGE model. This extension results in a multi-period forecasting model that is estimated under both adaptive learning and rational expectations. Term structure information enables us to characterize agents’ expectations in real time, which addresses an imperfect information issue mostly neglected in the adaptive learning literature. Relative to the rational expectations version, our estimated DSGE model under adaptive learning largely improves the model fit to the data, which include not just macroeconomic data but also the yield curve and the consumption growth and inflation forecasts reported in the Survey of Professional Forecasters. Moreover, the estimation results show that most endogenous sources of aggregate persistence are dramatically undercut when adaptive learning based on multi-period forecasting is incorporated through the term structure of interest rates.
Keywords: real-time adaptive learning; term spread; multi-period forecasting; short-versus long-sighted agents; SPF forecasts; medium-scale DSGE model (search for similar items in EconPapers)
JEL-codes: C53 D84 E30 E44 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-for and nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:bde:wpaper:1803
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