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International Funding Cost, Mortgage Rates and Cash Rate Cycle Relationship: Evidence in the
Context of Australia
Quynh Chau PhamBenjamin LiuEduardo Roca
Griffith Business SchoolDepartment of Accounting Finance and Economics
November 11, 2014
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Contents:
• Introduction• Related Literature & Hypotheses• Data & Econometric Methods• Result discussion• Conclusion
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Source: Retrieved from Steward, Robertson and Heath (2013)
1. Introduction
Banks’ wholesale DebtShare of total funding, 2011
Source: Retrieved from Leon Berkelmans and Andrew Duong (2014)
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1. IntroductionGap in the Literature• In Australia, numerous studies on cash rate pass-through on
mortgage rates (Karamujic, 2011; Lim, 2001; Smales, 2012; Valadkhani, 2013, 2014; Valadkhani & Anwar, 2012).
• Recently, several authors have analysed the trends in the funding and lending behaviour of Australian banks (Bailey et al. (2012), Deans & Stewart (2012), Stewart, Robertson & Heath (2013) and Berkelman & Duong (2014)).
• None of them has attempted to incorporate the impact of offshore funding costs on mortgage rates
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1• Lenders’ funding cycle differs from the cash rate cycle
2• Proliferated attention of policymakers, publicity towards the cash rate
cycle; and lenders’ pricing behaviour,
3• The heavy reliance of Australian lenders on international financial
markets,
4• The limitation in the scarce literature on influence of offshore funding
costs on mortgage rates in Australian market.
1. Introduction
Aim of the StudyIn particular, this study aims to answer two key questions:
• Whether international funding costs have affected mortgage rates? • Has the effect of the cash-rate cycle on mortgage rates reduced by the
increasing presence of offshore funding?
Motivations of the study
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Contributions
Contributions of the study
1- the offshore funding cost influence on
mortgage rate
2. Using both nominal & effective
mortgage rates
3-ARDL approach
application
1. Introduction
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2. Related Literature
Cash rate pass-through •An incomplete pass-through of base rate on mortgage rate in UK (Hofmann and Mizen (2004)), in Hong Kong and Singapore (Chong, 2010; Chong, Liu, & Shrestha, 2006), in NZ (Liu et al., 2008)• In U.S, both complete and incomplete pass-through of FFR ((Payne, 2006a; Payne, 2006b, 2007)
Cash rate pass-through
• Lowe (1995) find incomplete pass-through on mortgage rates
• Valadkhani & Anwar (2012), Valadkhani (2013) & (2014); Valadkhani & Bollen (2013) show complete make-up from cash rate to mortgage rates.
Offshore funding cost impact •Concerns on the increasing trend of offshore funding: e.g. Herald Sun, 2014). Bailey et al. (2012), Deans & Stewart (2012), Stewart, Robertson & Heath (2013) and Berkelman & Duong (2014)
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2. Research Hypotheses
H01: •The changes in cash rate still directly affect our sampled rates of the standard adjusted mortgages in both the short-term and the long term.
H02: •There are positive responses of the mortgage rates of the banks to changes in international funding costs
H03: •The effect of the cash-rate cycle on mortgage rates has been reduced by the increasing presence of offshore funding.
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3. Data and Econometric Methods3.1 Sample and Data
Sample No. of Obs.
Observations of standard adjustable mortgages 6,850
No. of groups: 1. Whole banking sector 2. Major group 3. Foreign group 4. Regional group
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Types of Variables Sources
Dependent variables:Mortgage interest rates: 1. Nominal rate (WRATE) 2. Effective rate (WAAPR)
Cannex’s survey of Australian lenders
Independent variables:1. Cash rate (CR) Table F01 of RBA database
2. International funding costs (AUDLIBOR)Australian spot exchange rate
DataStream
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3 Data and Econometric Methods3.2 Estimation methods– Unit root tests: ADF, PP and KPSS – The Autoregressive Distributed Lag (ARDL) model
developed by Pesaran et al. (2001)– The Granger causality tests carried out under the
VECM & VAR– The impulse response analysis (IRA) of VAR – The Dynamic Conditional Correlation (DCC) model
developed by Engle (2002)
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3. Data and Econometric Methods3.3 Empirical Models
Δyt = γ0 + Σγ1i(L)Δyt + Σ∂1j(L)Δx1t + Σδ1k(L)Δx2t + φECTt-1 + μjt (3)
Δyt = α0 + Σγ2i(L)Δyt + Σ∂2j(L)Δx1t + Σδ2k(L)Δx2t + ɛjt (4)
Δy1t = β0 + Σ βiΔyt-i + ΣγjΔx1t-j + ΣδkΔx2t-k + θ0yt-1 + θ1x1t-1 + θ2x2t-1 + e1t (1)
Δy2t = β0 + Σ βiΔyt-i + ΣγjΔx1t-j + ΣδkΔx2t-k + ω0yt-1 + ω1x1t-1 + ω2x2t-1 + e2t (2)
Notes: Y1t is nominal mortgage rate (WRATE)Y2t is effective mortgage rate (WAAPR)X1 is cash rate (CR)X2 is offshore funding costs (AUDLIBOR)
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3. Data and Econometric MethodsTable 2: Unconditional Correlations
Variables 1 2 3
Panel A: Whole sector 1 WAAPR 1.00
2 CR 0.57 1.00 3 AUDLIBOR 0.19 0.67 1.00
Panel B: Major group
1 WAAPR 1.00 2 CR 0.38 1.00 3 AUDLIBOR 0.10 0.68 1.00
Panel C: Foreign group
1 WAAPR 1.00 2 CR 0.42 1.00 3 AUDLIBOR 0.15 0.68 1.00
Panel D: Regional group 1 WAAPR 1.00 2 CR 0.56 1.00 3 AUDLIBOR 0.18 0.67 1.00
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3. Data and Econometric MethodsTable 3: Unit Root Test Result
Description ADF PP KPSS on level 1st diff on level 1st diff on level 1st diff
Panel A: Independent series AUDLIBOR -1.20 -16.98*** -1.08 -17.13*** 1.18*** 0.19 CR -2.91** -5.34*** -2.11 -31.58*** 0.33 0.08 Panel B: Weekly mortgage series Major Group WAAPR -3.72*** -4.68*** -2.75 -26.32*** 0.464** 0.12 Foreign Group WAAPR -2.35 -27.80*** -2.50 -27.61*** 0.53** 0.14 Regional Group WAAPR -3.21** -22.76*** -3.41** -26.39*** 0.44* 0.09 The whole sector WAAPR -2.86* -10.04*** -3.38** -28.21*** 0.58** 0.10
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4. Empirical results4.1. Long-term relationship
Table 4: The ARDL test for Cointegration under bivariate systemDependent Variables
Forcing variable
F-stat.
Conclusion (H0)
Panel A: Whole sector
WAAPR CR 16.007a Rejected
AUDLIBOR 13.254a Rejected
Panel B: Major group
WAAPR CR 8.522a Rejected
AUDLIBOR 8.685a Rejected
Panel C: Foreign group
WAAPR CR 6.708a Rejected
AUDLIBOR 6.847a Rejected
Panel D: Regional group
WAAPR CR 2.558c Fail to reject
AUDLIBOR 10.028a Rejected
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4. Empirical results4.1. Long-term relationship
Table 5: Granger noncausality test for a long-term relationship
Long-run causality ECM
Long-run adj. speed
Long-run causality decision
Long-run coefficients
Equations t-statistic X1 X2
Panel A: Whole sector
Y -5.660** 0.078** Y ← X1 0.661***
Y -5.148** 0.060** Y← X2
0.159***
Panel B: Major group
Y -4.117** 0.070** Y ← X1 0.695***
Y -4.163** 0.064** Y← X2
0.186***
Panel C: Foreign group
Y -3.656** 0.063** Y ← X1 0.639***
Y -3.692** 0.059** Y← X2
0.164***
Panel D: Regional group
Y
No
Y -4.462** 0.063** Y← X2
0.172***
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4. Empirical results4.2. Short-term relationshipTable 6: Granger noncausality test for a short-term relationship
Equations
Short-run causality (F-statistic)
Causality decision
X1 X2
Panel A: Whole sector
Y 18.018*** Y ← X1
Y 6.061*** Y← X2
Panel B: Major group
Y 2.648** Y← X1
Y 3.009*** Y← X2
Panel C: Foreign group
Y 3.899*** Y← X1
Y 0.244 No
Panel D: Regional group
Y 19.336*** Y← X1
Y 6.111*** Y← X2
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4. Empirical results4.3. Time Varying RelationshipsFigure 2. Dynamic Conditional Correlations of the whole banking sector
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5. ConclusionThe ADRL, VEC & VAR granger causality, IRA test results determine:• The cash rate still continues to drive mortgage
rates (Hypothesis 1);• International funding costs significantly affect
mortgage rates both in long & short term (Hypothesis 2);
• The DCC test result confirms hypothesis 3: the linkage between the cash rate and mortgage rates has indeed weakened since 2006