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International Shocks on Australia - The Japanese Effect∗
Mardi DungeyResearch School of Pacific and Asian Studies
The Australian National UniversityCanberra, ACT, 0200
Renée FryDepartment of Economics and Finance,Queensland University of Technology,
Brisbane, QLD, [email protected]
December 2001
Abstract
Although Australia has an equivalently large trading relationship with Japan and the US,current macro models often incorporate only US variables in the external sector of Australia. Thispaper explores the consequences of including both US and Japanese effects in the internationalsector of an SVAR model of Australia. The results indicate the significance of the Japanese effects.Excluding Japan results in an overstatement of the impact of US based shocks on the Australianeconomy. When Japan is included, US based shocks remain dominant in explaining Australianoutcomes, but the responses are moderated compared with a model incorporating only a US basedexternal sector. This has important implications for domestic policy responses to internationalshocks. Without the influence of Japan, domestic monetary policy will over-react to a US basedshock.
Keywords: Structural VAR, unified framework, monetary policy.
JEL Classifications: C51, F41.
∗We would like to thank Ron Bewley, Stan Hurn, Warwick McKibbin, Vance Martin and
Adrian Pagan for their helpful comments.
1
1 Introduction
Although Australia has an equivalently large trading relationship with Japan and the US, current
macro models often incorporate only US variables in the external sector of Australia; for example
Gruen and Sheutrim (1994), Brischetto and Voss (1999), Summers (1999) and Beechey et al (2000).
There are some exceptions to this, but these generally impose the international sectors exogenously.1
This paper explores the consequences of including Japanese effects in the international sector, by
extending the Dungey and Pagan (2000) SVAR model of the US and Australia.
Three main results are evident from this model. First, the Japanese effects, whilst small in mag-
nitude, should be included to avoid model misspecification. The exclusion of Japan results in an
overstatement of the impact of US shocks on Australia. This implies that models with US only based
external sectors may lead to over compensating policy decisions. Second, international shocks have a
larger impact on Australia than similarly sized domestic shocks. Third, the inclusion of Japan in the
model is important for Australia, as the impact of the US sourced shocks are amplified by the impact
of the US shocks on Japanese variables, which has subsequent indirect effects on Australian variables.
The literature on international VAR models is relatively small. Some examples include Pesaran,
Schuermann and Weiner (2001), Monticelli and Tristani (1999), and the Minneapolis World VAR
of Litterman and Sims (1988). The Minneapolis World VAR attempts to link three regional blocks
consisting of the US, Japan and Europe, where Europe is proxied by aggregating Germany, France
and the United Kingdom. Each equation in this system is estimated separately. In contrast to the
Minneapolis World VAR and Pesaran et al, the approach adopted here is to estimate a SVAR of
interdependent economies simultaneously. Monticelli and Tristani examine interactions between the
countries involved in the EMU currency block. Germany anchors the system whereas Austria, Belgium,
France, Germany, Italy, the Netherlands and Spain are aggregated into a single region. Analysis of
this system proceeds as in a two country model. The main problem with this approach is that the
effects of shocks to Germany on the individual small economies cannot be determined, thereby making
appropriate policy responses on a country basis difficult.
The rest of this paper proceeds as follows. Section 2 presents the model specification for the
SVAR, including an outline of the contemporaneous and dynamic structures of the model, as well
as an overview of the key equations. This section also includes a discussion of a multicollinearity
correction adopted to circumvent problems arising from the simultaneous inclusion of the US and
Japanese output variables in the Australian output equation. Section 3 contains the empirical results
for shocks to both the domestic and international economies. Although the emphasis of this paper
is on the impact of international shocks on Australia, the section begins with an overview of the1See Adams, Dixon, McDonald, Meagher, and Parmenter (1994), Commonwealth Treasury (1996) and Powell and
Murphy (1997). An important exception is the suite of models maintained by McKibbin, where there are multiple linksto interdependent country models, see McKibbin and Wilcoxen (1998) for example.
2
Table 1: Key variables in the international SVAR.
Variable Definition(a) Abbreviation
Commodity Prices World commodity price index, logs PCUSOutput GDP (SA), logs GDPUInflation Inflation (SA), percent INFUInterest Rate Federal funds rate, percent RUJapanOutput Industrial production (SA), logs IPJInflation Inflation, percent INFJInterest Rate Call rate, percent RJExchange Rate USD/Yen exchange rate, logs EJAustraliaDemand GNE, SA, logs GNEAOutput (SA) GDP, SA, logs GDPAInflation Inflation, percent INFAInterest Rate Cash rate, percent RAExchange Rate Nominal trade weighted index EA
(a)All variables are detrended.
dynamics of the Australian module to ensure that sensible results are obtained. International policy
shocks to output and foreign monetary policy are then analysed, along with the impact of commodity
price shocks. Section 4 provides an insight into the conduct of monetary policy in Australia. Some
concluding comments appear in Section 5.
2 SVAR Model Specification
The selection of variables for the SVAR model is motivated by policy interest and a need for a
parsimonious specification. Each of the US, Japan and Australia includes domestic variables consisting
of output, inflation and the interest rate. Additional variables in the Australian module include the
exchange rate and a measure of demand, whilst for Japan the exchange rate is also included. No
exchange rate variable is included in the US module as the US is the numeraire. Commodity prices
also enter the system. Table 1 presents a summary of the key variables, their filters and abbreviations.
The measure of output chosen is real GDP for both the US (GDPU) and Australia (GDPA), and
industrial production for Japan(IPJ).2 Dungey and Pagan (2000) find that the inclusion of both GNE
(GNEA) and GDP in an Australian SVAR improves its performance, and this is also the case in this
paper. GDP is interpreted as an output variable and GNE as domestic demand.
Inflation (INFU, INFJ, INFA) is used to represent prices in the model, as this is the target of2The use of GDP initially results in instability in the Japanese component of the SVAR model. An examination
of the industrial production index and GDP for Japan suggests that GDP exhibits little cyclical fluctuation. Horiye,
Naniwa and Ishihara (1987) find that the lack of cyclical variation in Japanese GNP is due to the negative correlation
between Government expenditure and domestic demand.
3
monetary policy conducted by the RBA. The use of inflation is increasing in the VAR literature; see
Dungey and Pagan (2000), and Garratt, Lee, Pesaran and Shin (2001). This is in contrast to the use
of the price level, as in Sims (1992). The interest rate (RU, RJ, RA) represents the monetary policy
instrument in each national VAR model. Although the monetary aggregate M1 is included as an
additional monetary policy instrument in the Sims (1992) model, it is not included here to preserve
degrees of freedom. The exclusion of the monetary aggregate from such models is a contentious area of
the literature; see the debate between Sims (1998) and Rudebusch (1998a,b), and also Leeper and Zha
(2001), Sack (2000), McCallum (1999), and Brischetto and Voss (1999). The exchange rate for Japan
is given by the Yen per USD rate (EJ), and the nominal trade weighted index is chosen for Australia
(EA). Existing Australian VARs use either the nominal or real trade weighted index, although the
choice between the two produces little difference in the results; see Dungey (1997) and Eichenbaum
and Evans (1995).
The commodity price index (PC) traditionally enters VAR and SVAR models to capture inflation-
ary expectations. It also represents the terms of trade effect when used in models of Australia; see
Sims (1992), Gruen and Wilkinson (1994) and Brischetto and Voss (1999). Sims (1992) also finds that
the inclusion of commodity prices helps to alleviate problems in estimating closed economy VARs. In
particular, the incorporation of the commodity price index into Sims’ national VARs solves the price
puzzle, where prices rise in response to an exogenous increase in the interest rate.
The key variables in the model, Yt are
Yt =hPCt YU,t YJ,t YA,t
i, (1)
where
YU,t =hGDPU,t INFU,t RU,t
i, (2)
YJ,t =hIPJ,t INFJ,t RJ,t EJ,t
i, (3)
YA,t =hGNEA,t GDPA,t INFA,t RA,t EA,t
i. (4)
The level of each variable is expressed in natural logarithms with the exceptions of the interest rates
and the inflation rates for each country, which are expressed in percentage terms. Data sources and
codes are contained in Appendix A. All variables are detrended against a constant and a time trend
and thus represent deviations around deterministic trends. An alternative approach follows Garratt,
Lee, Pesaran and Shin (2001) where stochastic long run relationships in the form of cointegration
are embedded in a SVAR model of the UK. Two dummy variables are included in the equation for
the Australian exchange rate to allow for outliers.3 The international SVAR model is estimated with
p = 2 lags.4 The sample period begins in Quarter 3, 1979 and ends in Quarter 2, 1999. The starting
date is chosen to avoid structural breaks in the Australian economy.3The first occurs in Quarter 2, 1985 when the cash rate jumped 300 basis points. The second occurs in Quarter
3, 1986 to account for the effects of the Banana Republic statement made by the then Treasurer of Australia, PaulKeating; see Dungey and Pagan (2000).
4Given the degrees of freedom limitations here, a lag length of 2 quarters is considered optimal.
4
Table 2: Contemporaneous structure of the international SVAR.
Dep. Explanatory VariablesVar.
US Japan Australia
PC GDPU INFU RU IPJ INFJ RJ EJ GNEA GDPA INFA RA EA
PC
GDPU *
INFU * *
RU * *
IPJ * *
INFJ * *
RJ * *
EJ * * * * * * *
GNEA
GDPA * * *
INFA *
RA * *
EA * * * * * * * * * * * *
A * represents the inclusion of an explanatory variable.
2.1 Contemporaneous and Dynamic Structures
The inclusion of both the US and Japanese economies requires the imposition of restrictions on
the contemporaneous and dynamic structures of the model due to degrees of freedom limitations. To
alleviate this problem, block exogeneity between economies in both the contemporaneous and dynamic
structures of the model is imposed. The US as a large economy, is an ‘anchor’ for the system, making
it block exogenous to both Japan and Australia. The Japanese economy is influenced by the US
economy, but is block exogenous to the Australian economy, while Australia as a small open economy,
does not feedback into either the US or Japanese economies. This structure is supported in existing
empirical literature. The placement of Japan in the centre of the system is consistent with evidence
that US shocks are transmitted to Japan and Japanese shocks are transmitted to Australia, but that
Japanese shocks do not transmit to the US, and Australian shocks do not transmit to Japan; see
Selover and Round (1996), Selover (1997) and Horiye, Naniwa and Ishihara (1987). These block
exogeneity restriction have become relatively common in two country open economy SVAR models
recently, following the work of Cushman and Zha (1997) and Zha (1999).
The variables entering into each equation are summarised in Tables 2 and 3, where Table 2 high-
lights the contemporaneous structure whilst Table 3 highlights the lag structure of the model. The
rows correspond to the dependent variable of each equation, whilst the inclusion of explanatory vari-
5
Table 3: Lag structure of the international SVAR.
Dep. Explanatory VariablesVar.
US Japan Australia
PC GDPU INFU RU IPJ INFJ RJ EJ GNEA GDPA INFA RA EA
PC *
GDPU * * * **
INFU * * * **
RU * * * *
IPJ * * * * ** *
INFJ * * * ** *
RJ * * *
EJ * * * * * * * *
GNEA * * * ** *
GDPA * * * * * ** *
INFA * * ** *
RA * * * *
EA * * * * * * * * * * * * *
A * represents the inclusion of lags 1 and 2, while a ** represents the inclusion of just lag 2.
ables in each equation are indicated by a *. In Table 3, a blank corresponds to a variable not entering
an equation, if all lags of a variable enter an equation, a * is recorded. In some equations only the
second lag of a variable enters, this is denoted by **; the reasons for this are given in our discussion
of the key equations below.
2.2 The Commodity Price Equation
Commodity prices (PCt) are exogenous to each of the three economies and are specified as an AR(2)
process
PCt = f1(PCt−1, PCt−2). (5)
2.3 Output and Demand Equations
The US output equation is specified as
GDPU,t = f2(PCt, PCt−1, PCt−2, GDPU,t−1, GDPU,t−2,
INFU,t−1, INFU,t−2, RU,t−2). (6)
6
US output is a function of lagged values of US output, inflation, the second lag of the interest rate
and contemporaneous and lagged commodity prices. Interest rate effects are delayed to reflect the
gap between the implementation and impact of domestic monetary policy; see Gruen and Shuetrim
(1994) and Dungey and Pagan (2000).
The Japanese output equation is as follows
IPJ,t = f3(PCt, PCt−1, PCt−2, GDPU,t,GDPU,t−1, GDPU,t−2,
IPJ,t−1,IPJ,t−2, INFJ,t−1, INFJ,t−2, RJ,t−2, EJ,t−1, EJ,t−2), (7)
and has a similar structure to that of the US GDP equation with the addition of some international
variables. Included are contemporaneous and lagged effects from US output and commodity prices, as
well as the Japanese variables of lagged industrial production, inflation, the second lag of the interest
rate and all lags of the exchange rate.
Both demand and output are included in the Australian module of the SVAR. Australian demand
depends only on lagged Australian domestic variables, including lags of demand, output, inflation,
the second lag of the interest rate, and all lags of the exchange rate as specified below
GNEA,t = f5(GNEA,t−1, GNEA,t−2,GDPA,t−1, GDPA,t−2,
INFA,t−1, INFA,t−2, RA,t−2, EA,t−1, EA,t−2). (8)
The Australian output equation is specified as
GDPA,t = f4(GDPU,t, GDPU,t−1, GDPU,t−2, IPJ,t,IPJ,t−1,IPJ,t−2,
GNEA,t, GNEA,t−1, GNEA,t−2, GDPA,t−1, GDPA,t−2,
INFA,t−1, INFA,t−2, RA,t, EA,t−1, EA,t−2). (9)
and contains contemporaneous and lagged US and Japanese outputs, and Australian demand, as well
as lagged Australian output, inflation, the second lag of the interest rate, and all lags of the exchange
rate. The inclusion of Australian demand and output in the model introduces a balance of payments
type relationship into the Australian module. However, analytical and policy interest clearly lies with
demand and output shocks and responses, which is why both are retained in the model.
Shocks from the US filter through to Japan and Australia via the relationship between output
variables. The total impact of a US shock on Australia will be composed of a direct impact from
the US and an indirect impact from the effect of the US shock on the Japanese economy and its
subsequent transmission to Australia.
2.3.1 Multicollinearity Correction
Models estimating Australian output, such as in Gruen and Sheutrim (1994), generally contain some
measure of total international output as an independent variable. The inclusion of output for both
Japan and the US in (9) raises the possibility of multicollinearity due to some form of common
international business cycle. This is solved by placing a further constraint on the system. A weighted
7
sum of an index of US and Japanese outputs is constructed to replace the individual variables in the
Australian component of the model,
GDPTOT,t = w1GDPU,t + w2IPJ,t, (10)
where the weights represent the relative common currency values of US and Japanese GDP in 1990.
Here, w1 = 0.729 and w2 = 0.271. GDPTOT,t is scaled to take the value 100 in the base year, 1990.5
The effect of this constraint on the system is to alter the form of the resulting impulse response
functions. The impulse response function representing the change in Australian output to a shock to
US output (εUS,t), in the original system can be expressed as
∂GDPA,t∂εUS,t
=∂GDPU,t∂εUS,t
+∂IPJ,t∂εUS,t
, (11)
whilst in the newly restricted system accounting for multicollinearity, this change is
∂GDPA,t∂εUS,t
=∂GDPA,t
∂GDPTOT ,t
µw1∂GDPU,t
∂εUS,t+w2∂IPJ,t∂εUS,t
¶. (12)
In the instance where multicollinearity is non-existent, these two expressions will give the same result.
It is not necessary to consider this issue between other variables such as US and Japanese interest
rates, as in no instance do they simultaneously enter an equation as independent variables in the
SVAR.
2.4 The Inflation Rate Equations
US inflation is modelled as dependent on the contemporaneous and lagged impact of commodity prices
and domestic output, and lagged inflation,
INFU,t = f6(PCt, PCt−1, PCt−2, GDPU,t,GDPU,t−1, GDPU,t−2,
INFU,t−1, INFU,t−2, RU,t−2). (13)
The restriction on the timing of the impact of interest rate changes also applies, as it does in the
output equations.
The Japanese inflation rate is specified as
INFJ,t = f7(PCt, PCt−1, PCt−2, IPJ,t, IPJ,t−1, IPJ,t−2, INFJ,t−1, INFJ,t−2,
RJ,t−2, EJ,t−1, EJ,t−2), (14)
and is a function of contemporaneous and lagged commodity prices and Japanese output, as well
as the domestic variables of lagged inflation, the second lag of the interest rate, and all lags of the
exchange rate.5To implement this restriction the identity GDPTOT = w1GDPU +w2IPJ is constructed and the SVAR estimated
with GDPA dependent on GDPTOT with loading β, say. Hence a shock to GDPU is transmitted through GDPTOTwith weight w1. To assess the impact of this shock on GDPA requires the replacement of the coefficient on GDPU asshown in Tables 2 and 3 with the coefficient βw1. Similarly the coefficient for IPJ in the GDPA equation is replacedwith βw2 in calculating impulse response functions. This is a manipulation to produce impulse response functions, notthe method of estimation.
8
For Australia, the inflation rate equation is
INFA,t = f8(GNEA,t, GNEA,t−1, GNEA,t−2, INFA,t−1, INFA,t−2,
RA,t−2, EA,t−1, EA,t−2), (15)
which is a function of contemporaneous and lagged demand, lagged inflation and the exchange rate,
as well as the second lag of the Australian interest rate.
The inclusion of lagged exchange rates in the inflation equation for Australia and Japan represent
the impact of import prices; see Dungey and Pitchford (2000) and Beechey et al (2000) for recent
Australian examples. Commodity prices are restricted to enter the Japanese inflation equation but
not the Australian inflation equation. This restriction is motivated by the fact that commodity prices
represent import prices to Japan and export prices to Australia, and export price inflation is generally
not found to be empirically important for Australia; see de Brouwer and Ericsson (1998).
2.5 The Interest Rate Equations
Here, the interest rate represents the monetary policy instrument. This is a contentious area of the
literature; see the debate between Sims (1998) and Rudebusch (1998a,b) for example. A common
world interest rate is not imposed on the model directly, although there remain linkages between
international interest rates via the links between output in each economy.
The interest rate equation for each economy in (16) to (18) is generally determined by domestic
economic conditions. The interest rate in each case depends on contemporaneous and lagged domestic
output (demand for Australia) and inflation, and lagged domestic interest rates. For the US and
Australia, commodity prices enter into this equation as a lag, as monetary policy adjusts to the effects
of export prices on output after a lag.
RU,t = f9(PCt−1, PCt−2, GDPU,t,GDPU,t−1, GDPU,t−2,
INFU,t, INFU,t−1, INFU,t−2, RU,t−1, RU,t−2), (16)
RJ,t = f10(IPJ,t, IPJ,t−1, IPJ,t−2, INFJ,t, INFJ,t−1, INFJ,t−2,
RJ,t−1, RJ,t−2), (17)
RA,t = f11(PCt−1, PCt−2, GNEA,t,GNEA,t−1,GNEA,t−2,
INFA,t, INFA,t−1, INFA,t−2, RA,t−1, RA,t−2). (18)
2.6 The Exchange Rate Equations
Each of the exchange rates is modelled to include all available information in the system. The Yen
exchange rate equation includes all US and Japanese variables in the model as well as commodity
9
prices as follows
EJ,t = f12(PCt, PCt−1, PCt−2, GDPU,t,GDPU,t−1, GDPU,t−2,
INFU,t, INFU,t−1, INFU,t−2, RU,t, RU,t−1, RU,t−2,
IPJ,t, IPJ,t−1, IPJ,t−2, INFJ,t, INFJ,t−1, INFJ,t−2,
RJ,t, RJ,t−1, RJ,t−2, EJ,t−1, EJ,t−2). (19)
All foreign and domestic variables also enter into the Australian exchange rate equation,
EA,t = f13(PCt, PCt−1, PCt−2,GDPU,t, GDPU,t−1,GDPU,t−2,
INFU,t, INFU,t−1, INFU,t−2, RU,t, RU,t−1, RU,t−2,
IPJ,t, IPJ,t−1, IPJ,t−2, INFJ,t, INFJ,t−1, INFJ,t−2,
RJ,t, RJ,t−1, RJ,t−2, EJ,t, EJ,t−1, EJ,t−2,
GNEA,t, GNEA,t−1,GNEA,t−2, GDPA,t,GDPA,t−1, GDPA,t−2,
INFA,t, INFA,t−1, INFA,t−2, RA,t, RA,t−1, RA,t−2, EA,t−1, EA,t−2), (20)
as the Australian exchange rate is assumed to be responsive to all information in the system.
3 Empirical Results
The set of equations for the variables in (1) of Section 2 can be conveniently combined into the
following SVAR system
B0Yt = B1Yt−1 +B2Yt−2 + εt, (21)
where εt is a multivariate white noise process with zero mean and constant diagonal variance-
covariance matrix, D. The parameter matrix B0, has unit diagonal elements and off diagonal terms
given in Table 2. The parameter matrices B1 and B2 correspond to the lag variables and are sum-
marised in Table 3.
The parameters of the SVAR are estimated in two parts. The first part consists of deriving the
corresponding VAR model associated with (21)
Yt = Φ1Yt−1 +Φ2Yt−2 + vt, (22)
where
Φi = B−10 Bi, i = 1, 2, (23)
vt = B−10 εt. (24)
Each equation of the VAR is estimated by OLS, and the VAR residuals vt, extracted. Single equation
estimation of the VAR in (22) yields consistent, but asymptotically inefficient parameter estimates.
The loss in efficiency arises from the zero restrictions given in Table 3.
10
Table 4: Standard deviations of the international SVAR.
US Japan Australia
GNEA,t 0.011GDPU,t 0.004 IPJ,t 0.004 GDPA,t 0.005INFU,t 0.546 INFJ,t 0.676 INFA,t 0.589RU,t 0.876 RJ,t 0.555 RA,t 1.120
EJ,t 0.040 EA,t 0.032
PCt 0.038
The second part of the estimation consists of choosing B0 andD to maximise the likelihood function
conditional on the parameter estimates of the VAR in the previous step. Formally, this amounts to
defining the following likelihood function at the tth observation
lnLt = −12ln (2π)− 1
2ln¯̄B−10 DB−100
¯̄− 12v0t¡B−10 DB−100
¢−1vt, (25)
where vt is taken as the residuals from the VAR in the first step. The log of the likelihood function
for a sample of t = 1, 2, ...T observations, is given by
lnL =TXt=1
lnLt, (26)
which is maximised using the procedure MAXLIK in GAUSS. The BFGS iterative gradient algorithm
is used with derivatives computed numerically.
A selection of the key impulse response functions obtained from shocking the SVAR model are
discussed in this section.6 The size of the shocks are given by the standard deviations of the errors
which are presented in Table 4. As in most VAR applications, the confidence intervals for the impulse
response functions are wide. A selection are presented in an earlier working paper; see Dungey and
Fry (2001).
3.1 Australian Domestic Economy Shocks
Although the focus of this paper is on the effect of the international shocks on Australia, an analysis
of the Australian module of the SVAR model ensures that the dynamics of the Australian sub-system
are sensible. Overall, the behaviour of the SVAR model in response to Australian domestic shocks is
very similar to the results reported in Dungey and Pagan (2000). Some specific examples follow.
Figure 1 shows the impact of shocks to Australian output (GDPA) and aggregate demand (GNEA)
on inflation (INFA) and interest rates (RA). The qualitative impact of the shocks on inflation and the
interest rate are as anticipated, with both shocks resulting in increases in inflation and higher interest
rates within the first year.6The full set of responses are available from the authors on request.
11
Figure 1: Response of Australian inflation and the interest rate to shocks in Australian output and
aggregate demand. Shock in GDPA (solid line), shock in GNEA (dashed line).
Monetary policy shocks are represented by interest rate shocks in this model. A monetary policy
shock has the expected contractionary effect on domestic output and inflation although there is some
brief evidence of the price puzzle as inflation initially rises, but this is quickly reversed; see Figure 2.
Alternative specifications based on the inclusion of commodity prices and a money supply variable
did not solve the price puzzle; for contrary empirical results see Cochrane (1998) and McCallum
(1999). A similar short-lived price puzzle is found by Dungey and Pagan (2000) who are able to
overcome the problem by including international capital markets in the form of deflated share market
prices. However, Brooks and Henry (2000) show that equity market links between the three countries
considered are not causal. This line of investigation is not pursued here due to degrees of freedom
constraints.
3.2 International Output Shocks
Output shocks originating in the US and Japan demonstrate the anticipated responses in terms of own
economy impacts and impacts from cross country transmissions. Figure 3 shows that a US output
shock leads to expansions in US, Japanese and Australian outputs. The expansion in outputs, in turn,
results in higher inflation in all economies. Monetary policy responds in each case by contracting. The
rise in US output increases the inflation rate in Australia, primarily through import prices, proxied
by exchange rate effects as outlined in Section 2.4. Figure 3d also shows that aggregate demand in
Australia (GNEA) increases in response to the US output shock.
Similarly, a Japanese output shock results in theoretically correct responses in both Japan and
12
Figure 2: Response of Australian output and inflation to a shock in the Australian interest rate.
Australia. Figure 4 presents the expansionary effects of a Japanese output shock on Australian output
(GDPA) and Australian demand (GNEA). Inflation rates in each economy subsequently rise, although
the response in Japan is quite volatile. This is followed by contractionary monetary policy in each
economy in reaction to the Japanese output expansion.
The Australian responses to US output shocks are augmented by their transmission through the
Japanese economy. To decompose the effect of a US output shock on Australia into the direct effect
from the US and the indirect effect from Japan, the following procedure is adopted. First, the full
model is shocked to yield the total effect of the US shocks on Australia. Second, the causal linkages
from Japan to Australia are set to zero whilst the remaining parameter estimates are based on the
full system results. The system is then shocked to yield the direct effect of a US sourced shock on
Australia. The indirect effect of the shock is given as the difference between the total and direct
effects.7
The results of this decomposition are shown in Figure 5 for the effects of a shock to US output on
Australian output. It is evident that the direct effect of the US shock is dominant, with about two
thirds of the magnitude of the shock at the time of the peak being the result of the direct linkage,
and the remaining one third arising from the indirect transmission mechanisms through the Japanese
economy. Selover and Round (1996) obtain a similar result.
An alternative approach for uncovering the contribution of Japan to model outcomes is to reesti-
mate the model as a two country model between the US and Australia, and to then perform impulse
analysis based on the reestimated parameter estimates. This experiment provides insights into po-7The same results are obtained if the model is decomposed into direct and indirect effects by imposing zero restrictions
on the US parameter estimates in the Australian impulse response functions, to obtain the indirect effect of the US onAustralia via Japan.
13
Figure 3: US, Japanese and Australian responses to a US output shock. US responses (solid line),
Japanese responses (dashed line), Australian responses (dotted line).
14
Figure 4: Responses of Japanese and Australian variables to a Japanese output shock. Response of
Japanese variables (solid line), response of Australian variables (dashed line).
15
Figure 5: Decomposition of the response of Australian output to a US output shock. Total effect
(solid line), direct effect of US output on Australian output (dashed line), indirect effect of US output
on Australian output via Japanese output (dotted line).
tential misspecification problems from the exclusion of Japan in constructing an international SVAR
model for Australia.
The results of this experiment are contained in Figure 6 which compares the US output shock on
Australian output for both the two country SVAR and the full SVAR. These results show that the
inclusion of the Japanese economy reduces the amplitude of the responses of Australian output and
aggregate demand and inflation to a US output shock; see Figures 6a to 6d. Figure 6b shows that the
longer term inflationary effect of an international shock is overstated if the Japanese economy is not
included. Consequently, the amplitude of the monetary policy response is lower in a model including
Japan than a model which does not; see Figure 6c.
As a further test of the relative importance of Japan in the model, a likelihood ratio test of the
joint hypothesis that the Japanese variables in the Australian component of the model are significant
is given in Table 5. The test amounts to a joint test of 15 zero restrictions. The null hypothesis is
rejected at the 5% level of significance, and is nearly rejected at the 1% level. Thus, the inclusion of
Japan is significant.
Further evidence on the relative importance of Japanese shocks on the Australia economy is ob-
tained by comparing the relative effect of a Japanese output shock on Australian variables, to a direct
Australian output shock of the same magnitude. The result in Figure 7 shows that the Japanese out-
put shock has a relatively greater impact on Australian inflation than does an equivalent Australian
output shock.
16
Figure 6: Comparison of models of Australian responses to a US output shock. International SVAR
model (solid line), two country model (dashed line).
17
Table 5: Likelihood ratio test that Japan is jointly significant in Australia.
Statistic p-value
Joint significance of 29. 822 0. 012*Japan in Australia(15 restrictions)
* denotes significance at the 0.05 level** denotes significance at the 0.01 level
Figure 7: Response of Australian inflation to equivalent sized shocks in Japanese (solid line) and
Australian outputs (dashed line).
18
3.3 International Monetary Policy Shocks
Inspection of Figure 8 reveals that a contractionary shock to US monetary policy induces a reduction
in US inflation and a contraction in US output. The contraction in the US economy subsequently
results in lower output in Japan and Australia; see Figure 8a. This is followed by eventual falls in
Australian demand (GNEA) and inflation (INFA).
The price puzzle is evident for Japan in response to a Japanese monetary policy shock, as shown
in Figure 9b. Despite this, the remainder of the Japanese and Australian responses to the Japanese
interest rate shock are as anticipated. Japanese and Australian outputs (IPJ and GDPA) contract,
followed by falling inflation, and eventually a reduction in aggregate demand (GNEA) in Australia,
along with a reduction in interest rates (RJ and RA). Shioji (1997) finds some reduction in the Japanese
price puzzle using oil prices in place of commodity prices. The results suggest that commodity prices
do not consistently solve the price puzzle; see also Hanson (2000).
In general, the model has difficulty in capturing the behaviour of Japanese inflation. The inflation
series for Japan is very noisy, making sensible estimation difficult.8 McCallum (1999) argues that the
money base needs to be included in macroeconomic models for Japan to provide a better indication
of the overall status of Japan’s economy. This proved not to be the case here.
Figure 10 compares the two country model of the US and Australia with the international SVAR
model for a US interest rate shock. Again inclusion of the Japanese economy reduces the amplitude
of the Australian responses; see Figures 10a and d. Inflation has a deeper and longer response to the
interest rate shock in the model which includes Japan. A similar result is observed for US output
shocks. The policy implications of these result are explored further in Section 4.
3.4 Commodity Price Shocks
Figure 11 presents the responses of selected variables in the system to a shock in commodity prices. An
increase in commodity prices causes an initial increase in US output and subsequently US inflation.
This results in an increase in Japanese and Australian output, but given that commodities are an
important import for Japan, the initial inflationary effect is greater for Japan. Japanese inflation
continues above trend for between 5 and 6 years, compared with about 4 years for the US. The
Australian exchange rate appreciates strongly in response to the higher commodity prices. This is
consistent with the existing literature; see de Brouwer and O’Reagan (1997) and Gruen and Wilkinson
(1994).
One unexpected result from this model as shown in Figure 11 is that higher commodity prices are
not reflected in higher Australian inflation. This may reflect that commodity prices are not a good
indicator of inflationary expectations in Australia. Further, although Australia is a large commodity
exporter, it is also generally a price taker on international markets, where contracts are primarily
written in USD or Yen terms. Thus in this instance, the addition of commodity prices has not solved
the price puzzle, but has instead transferred it to another segment of the model.8 Several experiments with different data sources were conducted with no improvement over the current version.
19
Figure 8: US, Japanese and Australian responses to a US interest rate shock. US responses (solid
line), Japanese responses (dashed line), Australian responses (dotted line).
20
Figure 9: Response of Japanese and Australian variables to a Japanese interest rate shock. Japanese
responses (solid line), Australian responses (dashed line).
21
Figure 10: Comparison of models of Australian responses to a US interest rate shock. International
SVAR model (solid line), two country model (dashed line).
22
Figure 11: Responses to a commodity price shock. Figure (a) commodity price response. For Figures
(b), (c) and (d), the representation is: US responses (solid line), Japanese responses (dashed line),
Australian responses (dotted line).
23
Figure 12: Comparison of models of Australian responses to a commodity price shock. Multi-country
model (solid line), two country model (dashed line).
24
Figure 13: Response of Australian interest rate to output shocks. Response of Australian interest rate
to a US output shock (solid line), response of Australian interest rate to an equivalent sized Australian
output shock (dashed line).
The inclusion of Japan in the model with the US also moderates impulse response functions for
Australia in response to a shock in commodity prices. Figure 12 shows that the inclusion of Japan
in the system mutes the effect of a commodity price shock compared with the results from the US-
Australia only system. These results may help explain the better than expected inflationary outcomes
from such shocks as commodity price shocks in the late 1990s. An implication of this result is that
monetary policy reactions may be overstated if the effect of the Japanese economy is not considered
in conjunction with the US in an Australian SVAR model.
4 Understanding Australian Monetary Policy
At various times speculation has arisen that Australian monetary policy is mainly reactive to US
monetary policy, see for example discussion in the Australian popular press in May and June 2000,
but this model shows clearly that this is not the case. Figures 3c and 9c present the response of
the Australian interest rate to US and Japanese interest rate shocks respectively. Figures 4c and 8c
present the same comparison for output shocks. These results suggest that the RBA places greater
weight on international output movements than it does on interest rate movements in the US and
Japan whilst conducting monetary policy.
The RBA states that monetary policy is formed in light of domestic economic conditions; see
Fraser (1995). Figure 13 compares the response of Australian monetary policy to an international
output shock with an Australian output shock. For comparative purposes, the size of the shock
to Australian output is scaled to be the same size as the initial impact of a US output shock on
25
Australian output. The difference in the responses is indicative of the contemporaneous and feedback
effects of the international shocks in the model, and can be interpreted as the impact of international
conditions on monetary policy. This is not the same as stating that the international economy directly
increases Australian interest rates. Instead, the decomposition gives a taste of the relative importance
of the flow on effects of the international conditions to the domestic economy and hence to domestic
monetary policy.
5 Conclusions
The strong influence of the US on Australia is recognized in empirical models of the Australian
economy. However, despite Japan’s status as an equal trading partner, it is usually excluded. This
paper has constructed and estimated a SVARmodel of the Australian economy, where the international
sector is represented by both the US and Japan. This represents both an extension to the general
VAR literature, which concentrates on two region models, and complements analysis of the nature of
international shocks on the Australian economy.
The model comprises three inter-related modules, representing the US, Japan and Australia aug-
mented by commodity price effects. The US represents an ‘anchor’ for the system and is exogenous
to the other economies. Japan is placed in the center reflecting evidence that US based shocks are
transmitted to Japan and Japanese shocks transmitted to Australia but not vice versa. A small open
economy assumption is applied to Australia, excluding it from influencing the other economies.
The Japanese economy makes a statistically significant contribution to the results of the model.
Excluding Japan results in a model misspecification. In total the US based shocks are dominant in
explaining impulse responses in the model. However, although the impact of the Japanese effects
are relatively small in magnitude, they have an important role in amplifying the effects of US based
shocks, through indirect transmission via Japan.
The importance of these results are highlighted by comparison with a two country model. If Japan
is not included in the model, the impulse responses to US based shocks will be overstated. Monetary
policy responses in Australia will overcompensate if the magnitude of the impulse responses is smaller.
This means that correct model specification is important in formulating appropriate policy responses.
26
A Data Sources and Codes
Table 6: Data sources, codes and abbreviations.
Variable Source Code Abbreviation
Commodity Price Index Datastream WDI76AXDF PCUSAReal GDP (SA) Datastream USGDP...D GDPUInflation (SA) Datastream USI64...F PUFederal Funds Rate Datastream USI60B.. RUJapanIndustrial Production (SA) Datastream JPI66..IF IPJInflation dX IOEJPCPI PJCall Rate Datastream JPI60..B RJUSD/YEN dX EJAustraliaGNE (SA) Datastream AUGNE...D GNEAReal GDP (SA) Datastream AUGDP...D GDPAInflation dX GCPIAGU PACash Rate Datastream AUCASH11F RANominal Trade Weighted Index dX A8.119aH EA
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