When does the yield curve contain predictive power? Evidence from a data-rich environment

Jari Hännikäinen

No 1603, Working Papers from Tampere University, Faculty of Management and Business, Economics

Abstract: This paper analyzes the predictive content of the level, slope and curvature of the yield curve for U.S. real activity in a data-rich environment. We find that the slope contains predictive power, but the level and curvature are not successful leading indicators. The predictive power of each of the yield curve factors fluctuates over time. The results show that economic conditions matter for the predictive ability of the slope. In particular, inflation persistence emerges as a key variable that affects the predictive content of the slope. The slope tends to forecast output growth better when inflation is highly persistent.

Keywords: yield curve; factor model; data-rich environment; forecasting; macroeconomic regimes; conditional predictive ability (search for similar items in EconPapers)
JEL-codes: C53 C55 E43 E44 E47 E52 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2016-04
New Economics Papers: this item is included in nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://urn.fi/URN:ISBN:978-952-03-0108-8 First version, 2016 (application/pdf)

Related works:
Journal Article: When does the yield curve contain predictive power? Evidence from a data-rich environment (2017)
Working Paper: When does the yield curve contain predictive power? Evidence from a data-rich environment (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:tam:wpaper:1603

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