A Pure Test for the Elasticity of Yield Spreads



Table 7
Regressions of Changes in Real Yield Spreads of SCM Long-Term Corporate Bond Indices on Changes
in Selected Real Determinants -
AR-GARCH Estimation

Table 7 reports the results of the AR-GARCH estimation of regression model (4) in which the dependent
variable is the monthly change in the real yield spread. This regression model is of the following form:

S = β0 + β1Ylt + β2(Yltr )2 + β3Slope + β4I + ε,

where S is the monthly change in the real yield spread, Yl,t,r is the monthly change in the real yield on the
constant maturity long-term Government of Canada index, (
Yltr)2 is a convexity term, Slope is the
monthly change in the real spread between the constant maturity long-term Government of Canada index and
the three-month Treasury bill yield, and
I is the monthly real return on the Toronto Stock Exchange 300
index.
t-values are in parentheses, m gives the degree of the autoregressive process as determined by the
stepwise autoregression method,
p and q are the GARCH(p,q) parameters, Norm. Test gives the p-value for
the normality test for detecting misspecification of the GARCH model, and finally LM gives the
p-value for
the Lagrange multiplier test. Panel A reports the estimates for the entire sample, covering the 08:1976-
07:2001 25-year period. Data during this sample period are dominated by corporate bonds carrying a
standard call provision. Panel B outlines the results for the 01:1995-07:2001 sub-period, in which bonds
carrying the doomsday call are expected to dominate all indices.

Panel A: 09:1976-07:2001

Regression Coefficients    AR and GARCH Parameters

Index

β 0

β1

β 2

β 3

β 4

m

p

q

Norm. Test

R2

LM

AAA

-0.0041

(-0.55)

0.0019
(0.13)

0.0002
(0.02)

-0.0418

(-3.06)

-0.0005

(-0.31)

1, 2

1

1

<0.0001

0.15

<.0001

AA

-0.0040

(-0.71)

-0.0178

(-1.36)

0.0052
(0.66)

-0.0706

(-5.91)

-0.0040

(-2.90)

1, 2, 4

1

1

<.0001

0.19

0.0005

A

-0.0032

(-0.52)

0.0005
(0.04)

0.0044
(0.58)

-0.0571

(-4.28)

-0.0034

(-2.81)

1, 2

1

1

0.0012

0.15

<.0001

BBB

-0.0022

(-0.15)

-0.0029

(-0.21)

0.0208
(1.38)

-0.0818

(-3.10)

-0.0078

(-2.38)

-

1

1

<0.0001

0.11

-

Panel

B: 01:1995-07:2001

Regression Coefficients

AR and GARCH Parameters

Goodness of Fit

Index

β 0

β1

β 2

β 3

β 4

m

p

q

Norm. Test

R2

LM

AAA

N/A

AA

-0.0180

(-1.15)

-0.0104

(-0.29)

0.1060
(2.19)

-0.0453

(-0.98)

-0.0044

(-1.49)

-

-

-

-

0.16

-

A

-0.0115

(-0.64)

-0.0130
(-0.37)

0.0927
(1.89)

-0.0503

(-1.05)

-0.0042

(-1.45)

-

-

-

-

0.10

-

BBB

-0.0185

(-0.68)

0.0465
(0.86)

0.0997
(1.33)

-0.0131

(-0.18)

-0.0122

(-2.77)

-

-

-

-

0.13

-

41



More intriguing information

1. If our brains were simple, we would be too simple to understand them.
2. Apprenticeships in the UK: from the industrial-relation via market-led and social inclusion models
3. Life is an Adventure! An agent-based reconciliation of narrative and scientific worldviews
4. The name is absent
5. Bridging Micro- and Macro-Analyses of the EU Sugar Program: Methods and Insights
6. The name is absent
7. DISCUSSION: POLICY CONSIDERATIONS OF EMERGING INFORMATION TECHNOLOGIES
8. The name is absent
9. Valuing Farm Financial Information
10. The name is absent
11. The name is absent
12. Dendritic Inhibition Enhances Neural Coding Properties
13. Weak and strong sustainability indicators, and regional environmental resources
14. TOWARD CULTURAL ONCOLOGY: THE EVOLUTIONARY INFORMATION DYNAMICS OF CANCER
15. Trade Openness and Volatility
16. Konjunkturprognostiker unter Panik: Kommentar
17. The Impact of Cognitive versus Affective Aspects on Consumer Usage of Financial Service Delivery Channels
18. The Determinants of Individual Trade Policy Preferences: International Survey Evidence
19. The name is absent
20. The bank lending channel of monetary policy: identification and estimation using Portuguese micro bank data