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

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.

Economic policy uncertainty effects for forecasting future real economic activity

“…This is a clearly economically significant relationship. In most of the previous papers, the slope of the yield curve has also been noted to be positively connected to the future real economic activity, even though recent studies have also revealed that the predictive power of the yield curve slope fluctuates over time (see Stock and Watson, 2003, Estrella et al, 2003, Mody and Taylor, 2003, Rossi and Sekhposyan, 2011, and Hännikäinen, 2016. These results indicate that also in our analysis, the presumption is that everything should be analyzed allowing for the time-variation in the regression coefficients of the models.…”

Predictive ability of financial variables in changing economic circumstances

“…In addition, evidence suggests that the term spread, stock returns and short-term interest rate have different informational content for GDP growth during normal growth periods than during recessions and economic turbulence in the Nordic countries (Kuosmanen et al, 2015). In contrast, Hännikäinen (2017) does not find any difference in the predictive content of the term spread during recessions or normal growth periods in the U.S. However, the existing literature does not identify an economic cause for the varying predictive content of financial variables over the business cycle (e.g., Wheelock & Wohar, 2009).…”

“…However, we lack systematic evidence regarding the economic circumstances under which financial variables tend to have more or less useful predictive content for GDP growth. The existing evidence has thus far focused on the U.S. economy and explained the changes in the predictive content of term spreads (Bordo & Haubrich, 2004;Benati & Goodhart, 2008;Ng & Wrigth, 2013;Hännikäinen, 2017). The aim of this paper is to broaden the analysis to cover the three most focal predictive financial variables, several economic conditions and a large set of countries.…”

The predictive power of the yield spread for future economic expansions: Evidence from a new approach

“…13 Examples of research incorporating the level and curvature of the yield curve include: Moneta (2005), Chinn and Kucko (2015), Stock and Watson (2003), Benati and Goodhard (2008), Ang, Piazzesi, and Wei (2006), Hännikäinen (2017). Overall, the spread appears to have stronger predictive power that the level or the curvature factor (Hännikäinen, 2017). (2006) and Afonso and Martins (2012); the former is computed as (y(3) + y(36) + y(120)) / 3, with y(k) denoting the yield of a bond with maturity of k months, whereas the latter is calculated as 2*y(36) -y(120) -y(3).…”