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Ination Expectations Spillovers between the
United States and Euro Area
Aleksei Net²unajev
Lars Winkelmann
School of Business and Economics
Freie Universität Berlin
CRC 649 Economic Risk
Introduction 1-1
Ination expectations and monetary policy
Anchoring of ination expectations → macro stability.
Bomn and Rudebusch (2000), Orphanides and Williams (2005)
Ination Expectations spillover
Introduction 1-1
Ination expectations and monetary policy
Anchoring of ination expectations → macro stability.
Bomn and Rudebusch (2000), Orphanides and Williams (2005)
FED press release December 12, 2012:
... the Committee [...] anticipates that the federal funds rate will
be appropriate at least as long as [...]
ination between one and two years ahead is projected to be
no more than a half percentage point above the Committee's 2
percent longer-run goal,
and longer-term ination expectations continue to be well
anchored.
Ination Expectations spillover
Introduction 1-2
Empirical literature on ination expectations
Anchoring criteria: Long run expectations are ...
... insensitive to macroeconomic news. Gürkaynak et al. (2010)
... uncorrelated with shorter term expectations. Jochmann et
al. (2010), Gefang et al. (2011), Lemke, Strohsal (2013)
∆πe
t (long) = α0 + α1∆πe
t (short) + ut
Ination Expectations spillover
Introduction 1-2
Empirical literature on ination expectations
Anchoring criteria: Long run expectations are ...
... insensitive to macroeconomic news. Gürkaynak et al. (2010)
... uncorrelated with shorter term expectations. Jochmann et
al. (2010), Gefang et al. (2011), Lemke, Strohsal (2013)
∆πe
t (long) = α0 + α1∆πe
t (short) + ut
→ cross countries spillovers are neglected!
Ination Expectations spillover
Introduction 1-2
Empirical literature on ination expectations
Anchoring criteria: Long run expectations are ...
... insensitive to macroeconomic news. Gürkaynak et al. (2010)
... uncorrelated with shorter term expectations. Jochmann et
al. (2010), Gefang et al. (2011), Lemke, Strohsal (2013)
∆πe
t (long) = α0 + α1∆πe
t (short) + ut
→ cross countries spillovers are neglected!
However: Evidence about a global ination factor. Ciccarelli,
Mojonit (2010), Mumtaz, Surico (2012), Bataa et al. (2013)
Ination Expectations spillover
Introduction 1-3
This paper
Extension of the conventional pass through model.
Focus on ination expectations spillovers between US and EA.
Study structural ination expectations shocks.
Allow for time-varying spillovers. Diebold, Yilmaz (2009)
Ination Expectations spillover
Introduction 1-3
This paper
Extension of the conventional pass through model.
Focus on ination expectations spillovers between US and EA.
Study structural ination expectations shocks.
Allow for time-varying spillovers. Diebold, Yilmaz (2009)
Model: Markov switching SVAR.
Lanne, Lütkepohl, Maciejowska (2010), Lütkepohl, Net²unajev (2013).
Identication through heteroscedasticity.
Test over identifying restrictions. Avoid ad hoc restrictions.
Ination Expectations spillover
Introduction 1-4
Outline
1. Introduction
2. Data: Break even ination rates
3. Methodology: The MS- SVAR model
4. Results: Ination expectations spillovers
5. Conclusion
Ination Expectations spillover
Data: Break even ination rates 2-1
US and EA data
Measure of ination expectations: Break even ination (BEI)
Fisher (1930), Christensen et al. (2010), Joyce et al. (2010)
BEIt(τ) ≡
nominal yield
y
N
t (τ) −
real yield
y
R
t (τ) =
expectations
πe
t (τ) +
risk premium
φt(τ)
Weekly data from 2004 -2011 (372 obs.).
BEIt(τ): One year (implied) forward with τ = 5, 10.
φt: VIX volatility index.
Söderlind (2011) and Christensen and Gillan (2012)
Ination Expectations spillover
Data: Break even ination rates 2-2
Figure 1: Weekly 5- and 10-year BEI rates
2004 2005 2006 2007 2008 2009 2010 2011
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
3
3.2
BEI (US 5Y)
BEI (EA 5Y)
2004 2005 2006 2007 2008 2009 2010 2011
1.5
2
2.5
3
3.5
4
BEI (US 10Y)
BEI (EA 10Y)
Ination Expectations spillover
Data: Break even ination rates 2-3
Figure 2: Weekly VIX and V-STOXX
2004 2005 2006 2007 2008 2009 2010 2011
10
20
30
40
50
60
70
80
VIX
VSTOXX
Correlation VIX  V-STOXX: 0.98.
US and EA BEI rates are aected by the common
Risk premium shocks.
Ination Expectations spillover
Methodology: The MS- SVAR model 3-1
Markov Switching Structural VAR
Lanne, Lütkepohl, Maciejowska (2010)
K = 5- dimensional VAR(p)
Yt = ν + A1Yt−1 + · · · + ApYt−p + Ut,
Orthogonal structural shocks: εt = B
−1Ut or Ut = Bεt.
Ut follows a Markov process with states st = 1, 2, .., M:
Ut|st ∼ N(0, Σst ), Σst = BΛst B , and Λ1 = IK.
If volatility changes of structural shocks are pairwise distinct,
B can be uniquely determined without any restrictions.
Ination Expectations spillover
Methodology: The MS- SVAR model 3-2
Model selection
Table 1: MS-VAR model selectionTable 1: Markov switching- VAR model selection.
Model log LT AIC SC
VAR(3) without MS 783.79 -1377.59 -1006.07
MS(2)-VAR(3) 1163.39 -2106.78 -1676.59
MS(3)-VAR(3) 1252.51 -2255.03 -1766.18∗
MS(4)-VAR(3) 1290.15 -2300.30∗ -1752.78
Notes: LT is the value of the likelihood function, AIC = −2 log LT +
2×no of free parameters, SC = −2 log LT +log T×no of free parameters.
Full sample Jan. 2004 - Jan. 2011 (T = 372 obs.).
representation, see further discussion in Appendix X. Note that a likelihood ratio test
with the corresponding MS(3)-SVAR(3) does not reject the hypothesis of a state-invariant
Ination Expectations spillover
Methodology: The MS- SVAR model 3-3
Markov states
Figure 3: State probabilities MS(3)-VAR(3).Figure 2: State probabilities of unrestricted MS(3)-VAR(3) model.
2004 2005 2006 2007 2008 2009 2010 2011
0
0.5
1
State 1
2004 2005 2006 2007 2008 2009 2010 2011
0
0.5
1
State 2
2004 2005 2006 2007 2008 2009 2010 2011
0
0.5
1
State 3
Notes: The states are characterized by three different volatility regimes. State 1 the lowest,
State 3 the highest volatility.
Volatility increasing in states.
Labeling: 1 non-crisis, 2 crisis, 3 outbreak.
Ination Expectations spillover
Methodology: The MS- SVAR model 3-4
Identication I
Table 2: LR-Tests of pairwise variancesTable 3: Tests for Equality of variances across states.
H0 LR statistic p-value
λ21 = λ22, λ31 = λ32 5.46 0.06
λ21 = λ23, λ31 = λ33 10.25 0.00
λ21 = λ24, λ31 = λ34 4.23 0.12
λ21 = λ25, λ31 = λ35 7.84 0.01
λ22 = λ23, λ32 = λ33 10.27 0.00
λ22 = λ24, λ32 = λ34 7.73 0.02
λ22 = λ25, λ32 = λ35 4.13 0.13
λ23 = λ24, λ33 = λ34 4.99 0.08
λ23 = λ25, λ33 = λ35 10.29 0.00
λ24 = λ25, λ34 = λ35 4.23 0.12
Notes: Tests for Equality of λijs of MS(3)-VAR(3). Model
with State-invariant and unrestricted B.
Table 4: Contemporaneous transmission (Tests of zero restrictions on B).
No. H0 LR df p-value
R0 state-invariant B 9.98 10 0.44
R1 R0 + 10Y shocks exogenous 4.60 4 0.33
Ination Expectations spillover
Methodology: The MS- SVAR model 3-4
Identication I
Table 2: LR-Tests of pairwise variancesTable 3: Tests for Equality of variances across states.
H0 LR statistic p-value
λ21 = λ22, λ31 = λ32 5.46 0.06
λ21 = λ23, λ31 = λ33 10.25 0.00
λ21 = λ24, λ31 = λ34 4.23 0.12
λ21 = λ25, λ31 = λ35 7.84 0.01
λ22 = λ23, λ32 = λ33 10.27 0.00
λ22 = λ24, λ32 = λ34 7.73 0.02
λ22 = λ25, λ32 = λ35 4.13 0.13
λ23 = λ24, λ33 = λ34 4.99 0.08
λ23 = λ25, λ33 = λ35 10.29 0.00
λ24 = λ25, λ34 = λ35 4.23 0.12
Notes: Tests for Equality of λijs of MS(3)-VAR(3). Model
with State-invariant and unrestricted B.
Table 4: Contemporaneous transmission (Tests of zero restrictions on B).
No. H0 LR df p-value
R0 state-invariant B 9.98 10 0.44
R1 R0 + 10Y shocks exogenous 4.60 4 0.33
i) distinct variances, ii) state invariant B (p-value 0.44)
= the MS(3)-SVAR(3) is (statistically) identied.
Ination Expectations spillover
Methodology: The MS- SVAR model 3-5
Identication II
Assumptions proposed by the literature:
1. Long horizon BEI rates are exogenous. Jochmann et al. (2010)
2. Spillovers across countries are neglected.Gürkaynak et al. (2010)
3. No immediate responses of BEI risk premia to ination
expectations shocks. Beechey et al. (2011)
Ination Expectations spillover
Methodology: The MS- SVAR model 3-5
Identication II
Assumptions proposed by the literature:
1. Long horizon BEI rates are exogenous. Jochmann et al. (2010)
2. Spillovers across countries are neglected.Gürkaynak et al. (2010)
3. No immediate responses of BEI risk premia to ination
expectations shocks. Beechey et al. (2011)
B =






b11 0 0 0 b15
0 b22 0 0 b25
b31 0 b33 b34 b35
0 b42 b43 b44 b35
0 0 0 0 b55






, εt =







ε
πe(US 5Y)
t
ε
πe(EA 5Y)
t
ε
πe(US 10Y)
t
ε
πe(EA 10Y)
t
ε Risk
t







Ination Expectations spillover
Methodology: The MS- SVAR model 3-6
Testing
Table 3: Testing of identifying restrictions.Table 2: Contemporaneous transmissions (Tests of zero restrictions on B).
No. H0 LR df p-value
R1 10Y IE shocks no effect on 5Y BEI 4.60 4 0.33
R2 R1 + 5Y IE shocks no effect on foreign BEI 11.67 8 0.17
R3 R2 + 5Y10Y IE shocks no effect on VIX 19.71 12 0.00
Note: Likelihood ratio tests are based on the MS(3)-SVAR(3) model. H1 of all tests:
state-invariant B. LR = 2(log LT − log Lr
T ), where Lr
T denotes the maximum likelihood
under H0 and LT denotes the maximum likelihood for the model under H1. T = 372
obs.
• Restriction 4: Immediate responses of BEI risk premia to inflation expectation shocks
are zero (e.g. Beechey et al., 2011). Inflation expectations shocks originating at
the medium (5Y) and long (10Y) horizon have no instantaneous effect on the VIX.
Ination Expectations spillover
Results: Ination expectations spillovers 4-1
Impulse responses
Figure 4: Transmission of structural shocks.
0 10 20
−0.5
0
0.5
1
1.5
BEI
(US5Y)
US 5Y shock
0 10 20
−0.5
0
0.5
EA 5Y shock
0 10 20
−0.5
0
0.5
US 10Y shock
0 10 20
−0.5
0
0.5
EA 10Y shock
0 10 20
−0.04
−0.02
0
Risk shock
0 10 20
−0.5
0
0.5
BEI
(EA5Y)
0 10 20
0
0.5
1
1.5
0 10 20
−0.5
0
0.5
0 10 20
−0.5
0
0.5
0 10 20
−0.04
−0.02
0
0.02
0 10 20
−1
0
1
BEI
(US10Y)
0 10 20
−0.5
0
0.5
0 10 20
−0.5
0
0.5
1
1.5
0 10 20
−1
0
1
0 10 20
−0.04
−0.02
0
0.02
0 10 20
−0.5
0
0.5
BEI
(EA10Y)
0 10 20
−0.5
0
0.5
0 10 20
−0.5
0
0.5
0 10 20
0
0.5
1
1.5
0 10 20
−0.02
−0.01
0
0.01
0 10 20
−10
0
10
20
VIX
0 10 20
0
10
20
0 10 20
−5
0
5
10
0 10 20
−10
0
10
20
0 10 20
−0.5
0
0.5
1
1.5
Ination Expectations spillover
Results: Ination expectations spillovers 4-2
Variance spillovers
Figure 5: Variance decomposition.
US
EA
Risk
US US
EAEA
Risk
Risk
State 1 State 2 State 3
BEI(US 10Y)
EA10Y
US
Risk
EA
EA
Risk
US
EA
Risk
USBEI(EA 10Y)
Changes in risk are dominating.
Up to 30% of variance is explained by the risk premium shock!
Ination Expectations spillover
Results: Ination expectations spillovers 4-3
Risk adjusted spillovers
Table 4: Ination expectations spillovers.
R3 R1 + 5Y EA shocks no effect on US 8.44 6 0.21
R4 R3 + R2 + 5Y10Y no effect on risk 19.71 12 0.00
Note: MS(3)-VAR(3) model. H1 of R1-R4: state-invariant B, H1 of R0: fully unre-
stricted. LR = 2(log LT − log Lr
T ), where Lr
T denotes the maximum likelihood under H0
and LT denotes the maximum likelihood for the model under H1. T = 372 obs.
Table 5: Inflation expectations spillovers.
US 10Y EA 10Y
State 1 2 3 1 2 3
επe(US 5Y) 18.2 28.3 34.7 2.9 3.1 3.7
επe(EA 5Y) 3.3 7.1 5.6 5.7 8.8 8.5
επe(US 10Y) 64.5 45.1 44.2 3.6 1.8 2.2
επe(EA 10Y) 14.0 19.4 15.5 87.8 86.3 84.6
Note: Percentage of risk adjusted BEI variance explained by the
structural inflation expectations shocks (επe
) in states 1 (lowest
volatility) to state 3 (highest volatility). Calculated from forecast
error variance decomposition at 100 weeks horizon.
12
Spillovers EA → US: 17.3%, 10ppt increase in crisis state.
Spillovers US → EA: 6.5% rather stable across states.
Weaker anchoring during crisis times.
Ination Expectations spillover
Conclusion 5-1
Conclusion
Main results about spillovers:
Cross country spillovers increase during crisis times.
US expectations stronger aected than EA expectations.
Elevated market uncertainty reduces the anchoring of ination
expectations.
Policy conclusion:
Results speak in favor of ...
discussion and advice between policy makers about appropriate
policy measures.
coordinated policy actions at an international level.
Ination Expectations spillover

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Inflation Expectations Spillovers between the United States and Euro Area

  • 1. Ination Expectations Spillovers between the United States and Euro Area Aleksei Net²unajev Lars Winkelmann School of Business and Economics Freie Universität Berlin CRC 649 Economic Risk
  • 2. Introduction 1-1 Ination expectations and monetary policy Anchoring of ination expectations → macro stability. Bomn and Rudebusch (2000), Orphanides and Williams (2005) Ination Expectations spillover
  • 3. Introduction 1-1 Ination expectations and monetary policy Anchoring of ination expectations → macro stability. Bomn and Rudebusch (2000), Orphanides and Williams (2005) FED press release December 12, 2012: ... the Committee [...] anticipates that the federal funds rate will be appropriate at least as long as [...] ination between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term ination expectations continue to be well anchored. Ination Expectations spillover
  • 4. Introduction 1-2 Empirical literature on ination expectations Anchoring criteria: Long run expectations are ... ... insensitive to macroeconomic news. Gürkaynak et al. (2010) ... uncorrelated with shorter term expectations. Jochmann et al. (2010), Gefang et al. (2011), Lemke, Strohsal (2013) ∆πe t (long) = α0 + α1∆πe t (short) + ut Ination Expectations spillover
  • 5. Introduction 1-2 Empirical literature on ination expectations Anchoring criteria: Long run expectations are ... ... insensitive to macroeconomic news. Gürkaynak et al. (2010) ... uncorrelated with shorter term expectations. Jochmann et al. (2010), Gefang et al. (2011), Lemke, Strohsal (2013) ∆πe t (long) = α0 + α1∆πe t (short) + ut → cross countries spillovers are neglected! Ination Expectations spillover
  • 6. Introduction 1-2 Empirical literature on ination expectations Anchoring criteria: Long run expectations are ... ... insensitive to macroeconomic news. Gürkaynak et al. (2010) ... uncorrelated with shorter term expectations. Jochmann et al. (2010), Gefang et al. (2011), Lemke, Strohsal (2013) ∆πe t (long) = α0 + α1∆πe t (short) + ut → cross countries spillovers are neglected! However: Evidence about a global ination factor. Ciccarelli, Mojonit (2010), Mumtaz, Surico (2012), Bataa et al. (2013) Ination Expectations spillover
  • 7. Introduction 1-3 This paper Extension of the conventional pass through model. Focus on ination expectations spillovers between US and EA. Study structural ination expectations shocks. Allow for time-varying spillovers. Diebold, Yilmaz (2009) Ination Expectations spillover
  • 8. Introduction 1-3 This paper Extension of the conventional pass through model. Focus on ination expectations spillovers between US and EA. Study structural ination expectations shocks. Allow for time-varying spillovers. Diebold, Yilmaz (2009) Model: Markov switching SVAR. Lanne, Lütkepohl, Maciejowska (2010), Lütkepohl, Net²unajev (2013). Identication through heteroscedasticity. Test over identifying restrictions. Avoid ad hoc restrictions. Ination Expectations spillover
  • 9. Introduction 1-4 Outline 1. Introduction 2. Data: Break even ination rates 3. Methodology: The MS- SVAR model 4. Results: Ination expectations spillovers 5. Conclusion Ination Expectations spillover
  • 10. Data: Break even ination rates 2-1 US and EA data Measure of ination expectations: Break even ination (BEI) Fisher (1930), Christensen et al. (2010), Joyce et al. (2010) BEIt(τ) ≡ nominal yield y N t (τ) − real yield y R t (τ) = expectations πe t (τ) + risk premium φt(τ) Weekly data from 2004 -2011 (372 obs.). BEIt(τ): One year (implied) forward with τ = 5, 10. φt: VIX volatility index. Söderlind (2011) and Christensen and Gillan (2012) Ination Expectations spillover
  • 11. Data: Break even ination rates 2-2 Figure 1: Weekly 5- and 10-year BEI rates 2004 2005 2006 2007 2008 2009 2010 2011 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 BEI (US 5Y) BEI (EA 5Y) 2004 2005 2006 2007 2008 2009 2010 2011 1.5 2 2.5 3 3.5 4 BEI (US 10Y) BEI (EA 10Y) Ination Expectations spillover
  • 12. Data: Break even ination rates 2-3 Figure 2: Weekly VIX and V-STOXX 2004 2005 2006 2007 2008 2009 2010 2011 10 20 30 40 50 60 70 80 VIX VSTOXX Correlation VIX V-STOXX: 0.98. US and EA BEI rates are aected by the common Risk premium shocks. Ination Expectations spillover
  • 13. Methodology: The MS- SVAR model 3-1 Markov Switching Structural VAR Lanne, Lütkepohl, Maciejowska (2010) K = 5- dimensional VAR(p) Yt = ν + A1Yt−1 + · · · + ApYt−p + Ut, Orthogonal structural shocks: εt = B −1Ut or Ut = Bεt. Ut follows a Markov process with states st = 1, 2, .., M: Ut|st ∼ N(0, Σst ), Σst = BΛst B , and Λ1 = IK. If volatility changes of structural shocks are pairwise distinct, B can be uniquely determined without any restrictions. Ination Expectations spillover
  • 14. Methodology: The MS- SVAR model 3-2 Model selection Table 1: MS-VAR model selectionTable 1: Markov switching- VAR model selection. Model log LT AIC SC VAR(3) without MS 783.79 -1377.59 -1006.07 MS(2)-VAR(3) 1163.39 -2106.78 -1676.59 MS(3)-VAR(3) 1252.51 -2255.03 -1766.18∗ MS(4)-VAR(3) 1290.15 -2300.30∗ -1752.78 Notes: LT is the value of the likelihood function, AIC = −2 log LT + 2×no of free parameters, SC = −2 log LT +log T×no of free parameters. Full sample Jan. 2004 - Jan. 2011 (T = 372 obs.). representation, see further discussion in Appendix X. Note that a likelihood ratio test with the corresponding MS(3)-SVAR(3) does not reject the hypothesis of a state-invariant Ination Expectations spillover
  • 15. Methodology: The MS- SVAR model 3-3 Markov states Figure 3: State probabilities MS(3)-VAR(3).Figure 2: State probabilities of unrestricted MS(3)-VAR(3) model. 2004 2005 2006 2007 2008 2009 2010 2011 0 0.5 1 State 1 2004 2005 2006 2007 2008 2009 2010 2011 0 0.5 1 State 2 2004 2005 2006 2007 2008 2009 2010 2011 0 0.5 1 State 3 Notes: The states are characterized by three different volatility regimes. State 1 the lowest, State 3 the highest volatility. Volatility increasing in states. Labeling: 1 non-crisis, 2 crisis, 3 outbreak. Ination Expectations spillover
  • 16. Methodology: The MS- SVAR model 3-4 Identication I Table 2: LR-Tests of pairwise variancesTable 3: Tests for Equality of variances across states. H0 LR statistic p-value λ21 = λ22, λ31 = λ32 5.46 0.06 λ21 = λ23, λ31 = λ33 10.25 0.00 λ21 = λ24, λ31 = λ34 4.23 0.12 λ21 = λ25, λ31 = λ35 7.84 0.01 λ22 = λ23, λ32 = λ33 10.27 0.00 λ22 = λ24, λ32 = λ34 7.73 0.02 λ22 = λ25, λ32 = λ35 4.13 0.13 λ23 = λ24, λ33 = λ34 4.99 0.08 λ23 = λ25, λ33 = λ35 10.29 0.00 λ24 = λ25, λ34 = λ35 4.23 0.12 Notes: Tests for Equality of λijs of MS(3)-VAR(3). Model with State-invariant and unrestricted B. Table 4: Contemporaneous transmission (Tests of zero restrictions on B). No. H0 LR df p-value R0 state-invariant B 9.98 10 0.44 R1 R0 + 10Y shocks exogenous 4.60 4 0.33 Ination Expectations spillover
  • 17. Methodology: The MS- SVAR model 3-4 Identication I Table 2: LR-Tests of pairwise variancesTable 3: Tests for Equality of variances across states. H0 LR statistic p-value λ21 = λ22, λ31 = λ32 5.46 0.06 λ21 = λ23, λ31 = λ33 10.25 0.00 λ21 = λ24, λ31 = λ34 4.23 0.12 λ21 = λ25, λ31 = λ35 7.84 0.01 λ22 = λ23, λ32 = λ33 10.27 0.00 λ22 = λ24, λ32 = λ34 7.73 0.02 λ22 = λ25, λ32 = λ35 4.13 0.13 λ23 = λ24, λ33 = λ34 4.99 0.08 λ23 = λ25, λ33 = λ35 10.29 0.00 λ24 = λ25, λ34 = λ35 4.23 0.12 Notes: Tests for Equality of λijs of MS(3)-VAR(3). Model with State-invariant and unrestricted B. Table 4: Contemporaneous transmission (Tests of zero restrictions on B). No. H0 LR df p-value R0 state-invariant B 9.98 10 0.44 R1 R0 + 10Y shocks exogenous 4.60 4 0.33 i) distinct variances, ii) state invariant B (p-value 0.44) = the MS(3)-SVAR(3) is (statistically) identied. Ination Expectations spillover
  • 18. Methodology: The MS- SVAR model 3-5 Identication II Assumptions proposed by the literature: 1. Long horizon BEI rates are exogenous. Jochmann et al. (2010) 2. Spillovers across countries are neglected.Gürkaynak et al. (2010) 3. No immediate responses of BEI risk premia to ination expectations shocks. Beechey et al. (2011) Ination Expectations spillover
  • 19. Methodology: The MS- SVAR model 3-5 Identication II Assumptions proposed by the literature: 1. Long horizon BEI rates are exogenous. Jochmann et al. (2010) 2. Spillovers across countries are neglected.Gürkaynak et al. (2010) 3. No immediate responses of BEI risk premia to ination expectations shocks. Beechey et al. (2011) B =       b11 0 0 0 b15 0 b22 0 0 b25 b31 0 b33 b34 b35 0 b42 b43 b44 b35 0 0 0 0 b55       , εt =        ε πe(US 5Y) t ε πe(EA 5Y) t ε πe(US 10Y) t ε πe(EA 10Y) t ε Risk t        Ination Expectations spillover
  • 20. Methodology: The MS- SVAR model 3-6 Testing Table 3: Testing of identifying restrictions.Table 2: Contemporaneous transmissions (Tests of zero restrictions on B). No. H0 LR df p-value R1 10Y IE shocks no effect on 5Y BEI 4.60 4 0.33 R2 R1 + 5Y IE shocks no effect on foreign BEI 11.67 8 0.17 R3 R2 + 5Y10Y IE shocks no effect on VIX 19.71 12 0.00 Note: Likelihood ratio tests are based on the MS(3)-SVAR(3) model. H1 of all tests: state-invariant B. LR = 2(log LT − log Lr T ), where Lr T denotes the maximum likelihood under H0 and LT denotes the maximum likelihood for the model under H1. T = 372 obs. • Restriction 4: Immediate responses of BEI risk premia to inflation expectation shocks are zero (e.g. Beechey et al., 2011). Inflation expectations shocks originating at the medium (5Y) and long (10Y) horizon have no instantaneous effect on the VIX. Ination Expectations spillover
  • 21. Results: Ination expectations spillovers 4-1 Impulse responses Figure 4: Transmission of structural shocks. 0 10 20 −0.5 0 0.5 1 1.5 BEI (US5Y) US 5Y shock 0 10 20 −0.5 0 0.5 EA 5Y shock 0 10 20 −0.5 0 0.5 US 10Y shock 0 10 20 −0.5 0 0.5 EA 10Y shock 0 10 20 −0.04 −0.02 0 Risk shock 0 10 20 −0.5 0 0.5 BEI (EA5Y) 0 10 20 0 0.5 1 1.5 0 10 20 −0.5 0 0.5 0 10 20 −0.5 0 0.5 0 10 20 −0.04 −0.02 0 0.02 0 10 20 −1 0 1 BEI (US10Y) 0 10 20 −0.5 0 0.5 0 10 20 −0.5 0 0.5 1 1.5 0 10 20 −1 0 1 0 10 20 −0.04 −0.02 0 0.02 0 10 20 −0.5 0 0.5 BEI (EA10Y) 0 10 20 −0.5 0 0.5 0 10 20 −0.5 0 0.5 0 10 20 0 0.5 1 1.5 0 10 20 −0.02 −0.01 0 0.01 0 10 20 −10 0 10 20 VIX 0 10 20 0 10 20 0 10 20 −5 0 5 10 0 10 20 −10 0 10 20 0 10 20 −0.5 0 0.5 1 1.5 Ination Expectations spillover
  • 22. Results: Ination expectations spillovers 4-2 Variance spillovers Figure 5: Variance decomposition. US EA Risk US US EAEA Risk Risk State 1 State 2 State 3 BEI(US 10Y) EA10Y US Risk EA EA Risk US EA Risk USBEI(EA 10Y) Changes in risk are dominating. Up to 30% of variance is explained by the risk premium shock! Ination Expectations spillover
  • 23. Results: Ination expectations spillovers 4-3 Risk adjusted spillovers Table 4: Ination expectations spillovers. R3 R1 + 5Y EA shocks no effect on US 8.44 6 0.21 R4 R3 + R2 + 5Y10Y no effect on risk 19.71 12 0.00 Note: MS(3)-VAR(3) model. H1 of R1-R4: state-invariant B, H1 of R0: fully unre- stricted. LR = 2(log LT − log Lr T ), where Lr T denotes the maximum likelihood under H0 and LT denotes the maximum likelihood for the model under H1. T = 372 obs. Table 5: Inflation expectations spillovers. US 10Y EA 10Y State 1 2 3 1 2 3 επe(US 5Y) 18.2 28.3 34.7 2.9 3.1 3.7 επe(EA 5Y) 3.3 7.1 5.6 5.7 8.8 8.5 επe(US 10Y) 64.5 45.1 44.2 3.6 1.8 2.2 επe(EA 10Y) 14.0 19.4 15.5 87.8 86.3 84.6 Note: Percentage of risk adjusted BEI variance explained by the structural inflation expectations shocks (επe ) in states 1 (lowest volatility) to state 3 (highest volatility). Calculated from forecast error variance decomposition at 100 weeks horizon. 12 Spillovers EA → US: 17.3%, 10ppt increase in crisis state. Spillovers US → EA: 6.5% rather stable across states. Weaker anchoring during crisis times. Ination Expectations spillover
  • 24. Conclusion 5-1 Conclusion Main results about spillovers: Cross country spillovers increase during crisis times. US expectations stronger aected than EA expectations. Elevated market uncertainty reduces the anchoring of ination expectations. Policy conclusion: Results speak in favor of ... discussion and advice between policy makers about appropriate policy measures. coordinated policy actions at an international level. Ination Expectations spillover