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Garcia Alvarado, Fernando <1991>

Use this identifier to cite or link to this document:
http://hdl.handle.net/10579/10810

Publisher:
Università Ca' Foscari Venezia

Date:
2017-07-06

Copyright:
© Fernando Garcia Alvarado, 2017

openAccess

openAccess

The term structure defined as the spread between a long-term (10 years) and a short-
term (3 months to 2 years) government yield rate accounts for a non negligible predictive
power for both output and ination under most circumstances. Despite the fundamental
drawback that no standard theory model explains this relationship Estrella (2005) de-
rived a rational expectations model which can be analytically solved. Estrella and Trubin
(2006) proposed a probit model which is extended in this thesis to the Bayesian Regression
Framework and the Gibbs Sampling technique to a collection of thirty countries.
The general topic of interest covers the econometric measures to assess the interconnection be-
tween Government Yield Rates and the Gross Domestic Product output. Estrella and Hardou-
velis (1991) formulate a probabilistic model using the US Government Yield Rates to forecast
possible recessions in the US Economy. There exists an associated relationship between a
positive slope in the yield curve with a future increase in the (real) economic activity level.
According to the authors, this measure (yield curve slope) historically gives a predictive power
that is independent of monetary policy and outperforms indicators such as surveys and lagged
growth in economic activity. The attening phenomenon predicts a drop in the future interest
rates which is associated with a lower level of real GDP. The next step that I will introduce is
to extend this model to include a diversity of countries to study the connections between GDP
output and government yield rates among different nations.
Historic Example: In the case of the US, the flattening of the curve predicted the imminent
recessions of the early 90s, early 2000s and the 2007-2008 crisis. Moreover, a considerable set
of countries suffered the same yield curve flattening prior to the latter crisis.
One of the most recurred explanations about the reason why yield spreads have a predictive
power over the future output is given by the notion that yield curves tend to `flatten' whenever
there is a monetary policy tightening, which is itself related to a slowdown in the future levels
of economic activity and ination.
Recall the IS model as the downward slopping curve which considers the Gross Domestic Prod-
uct as the dependent variable and the interest rate as an independent term. Remind as well of
the Phillips curve as an inverse relation between inflation rate and unemployment.
There seems to be, therefore, a predictive role contained in the spread between the long-term
and the short-term yields. The effect of the yield, however, is affected by all three parameters
of monetary policy: gy, g_pi and gr.
Let us take a closer look to the last equations derived in the model above. In the extreme
positive scenario, where gr = 1 and g_pi = 0, the yield spread would thereby become the solely
remnant predictor1. In the other sense, a very negative scenario would develop if both g_pi and gy
are positive and very large, yet gp/gy tends to a constant value. In such case the coeffcient on
the yield spread would become diluted. Apart from both extreme scenarios, the model suggests
a predictive role of the yield spread in the expectations of output and ination.
As a final remark, the model denotes that the role of the yield spread is not structural and may
vary along time in case of changes in the monetary policy. We will see in the next section how
the coeffcient for the yield spread in the probit models has structural changes after economic
recessions occur and new monetary policies are enforced.