Description
The purpose of this paper is to assess the level of the real effective exchange rate in
Australia and New Zealand
Journal of Financial Economic Policy
Exchange rate assessments for Australia and New Zealand
Hali Edison Francis Vitek
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Hali Edison Francis Vitek, (2009),"Exchange rate assessments for Australia and New Zealand", J ournal of
Financial Economic Policy, Vol. 1 Iss 2 pp. 155 - 176
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Exchange rate assessments for
Australia and New Zealand
Hali Edison and Francis Vitek
International Monetary Fund, Washington, DC, USA
Abstract
Purpose – The purpose of this paper is to assess the level of the real effective exchange rate in
Australia and New Zealand.
Design/methodology/approach – The paper describes three empirical models commonly used to
conduct exchange rate assessments and applies them to data for Australia and New Zealand.
Findings – The baseline results using data and medium-term projections, available as of October
2008, suggest that the Australian and New Zealand dollar were broadly in line with fundamentals, but
with a wide variation across models. A battery of sensitivity tests illustrates that altering the
underlying assumptions can yield substantially different assessments. The results are particularly
sensitive to the choice of assessment horizon, the set of economies included in the sample, medium-term
forecasts, and the exchange rate reference period.
Originality/value – The paper provides an assessment of the exchange rates in Australia and
New Zealand.
Keywords Exchange rates, Macroeconomics, Australia, New Zealand
Paper type Research paper
I. Introduction
An integral part of the Fund’s mandate is the close monitoring and careful evaluation of
exchange rates of its members. As a result, the Fund has developed a framework for
assessing exchange rates. As part of this mandate, the International Monetary Fund
(IMF) Consultative Group on Exchange Rate Issues (CGER) has developed models and
provided assessments for a number of advanced and emerging market economies with
the aim to inform country-speci?c surveillance[1].
Australia and New Zealand are both small commodity-exporting economies with
reasonably long histories of independently ?oating exchange rates. From 2001 to
mid-2008, the currencies of both countries experienced large appreciations in nominal
and real effective terms. This together with persistent current account de?cits raised
concerns in some corners that strong currencies were adversely affecting their external
price competitiveness.
Against this background, the paper seeks to assess the level of the real effective
exchange rate in Australia and New Zealand. Several related papers have been written
that have used these methods that speci?cally focused on Australia and New Zealand,
including Brooks and Hargreaves (2000), MacDonald (2001), Dvornak et al. (2003), and
Wren-Lewis (2004). The contribution this paper makes is that it uses the latest
econometric techniques, modestly improving upon those used by the IMF CGER group.
In particular, three modi?cations to the conventional methods are introduced and
then tested. First, each model is estimated as both a standard unrestricted panel
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – F31, F32
Exchange rate
assessments
155
Journal of Financial Economic Policy
Vol. 1 No. 2, 2009
pp. 155-176
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576380911010263
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regression using ordinary least squares (OLS) and as a restricted panel regression
using the generalized method of moments (GMM). Second, each model is estimated
using a large sample of economies and then a narrower panel of economically similar
economies. Third, the exchange rate assessments are conducted at two time horizons:
the current time (within sample) and the medium-term (out of sample). In addition, a
battery of robustness tests are used to gather some insights into the sensitivity of the
results to changes in various assumptions.
Several useful lessons can be drawn from this study. Econometric models used for
exchange rate assessments offer some guidance in systematically analyzing the data.
However, the models tend to offer con?icting results and are highly uncertain,
requiring further investigation[2]. The results suggest that these models, while useful
as a diagnostic tool, must be complemented with more standard country surveillance in
the context of the Article IV and cannot substitute for such surveillance.
The organization of this paper is as follows. The next section provides background
information on exchange rate developments for Australia and New Zealand. Section III
presents the estimation results for the three empirical models. Section IV applies these
results to exchange rate assessments for Australia and New Zealand and considers a
battery of robustness tests. Section V concludes.
II. Stylized facts on real exchange rate trends
In recent years up until the middle of 2008, the Australian and New Zealand currencies
had appreciated signi?cantly in nominal and real effective terms (Figures 1 and 2,
panel (a)). From 2001 to mid-2008, the Australian dollar in nominal effective terms
appreciated by more than 30 percent, while the New Zealand dollar appreciated by
about 35 percent. In real effective terms, both currencies appreciated by over 30
percent. The difference between nominal and real effective exchanges rates re?ect
accumulated in?ation rate differentials relative to trading partners. Since mid-2008,
both the Australian and New Zealand dollars have depreciated signi?cantly[3].
These real effective exchange rate movements have been driven in part by
movements in real effective interest rate differentials (Figures 1 and 2, panel (b)). This
relationship recently appears stronger at shorter horizons than at longer horizons,
which likely re?ects the emergence of the carry trade. This global search for yield has
targeted Australian and New Zealand dollar assets not only because of high interest
rate spreads, but also because these spreads seemed likely to persist.
The strength of these currencies has also been supported by higher terms of trade as
both countries are relatively large exporters of primary commodities (Figures 1 and 2,
panel (c)). Australia has seen a sharp increase in its terms of trade as a result of
increasing coal, iron ore, and other mineral prices, while New Zealand has experienced
an increase in dairy prices. The relationship between the terms of trade and the
exchange rate broke down around 1999 for a couple of years, but has resumed with the
run up of commodity prices. Since mid-2008, global commodity prices have declined.
The balance of payments for Australia and New Zealand have widened as their
exchange rates strengthened. The trade balances of Australia and New Zealand have
declined, reducing their current account balances (Figures 1 and 2, panel (d)). Since
2001, the trade balance of New Zealand has deteriorated from a surplus and its current
account de?cit has widened considerably.
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In assessing the appropriate level of the real effective exchange rate, a common ?rst step
is to compare the prevailing level of the real effective exchange rate to some historical
average. Such a comparison assumes that the real exchange rate should remain
relatively constant over time, and that the nominal effective exchange rate should move
in line with relative price levels, which is consistent with purchasing power parity (PPP)
(Rogoff, 1996). This is a useful point of departure for studying the appropriate level of
the exchange rate. As of October 2008, both countries’ real effective exchange rate is
above its historical level (Figures 1 and 2, panel (e)). This result emerges using either the
IMF or the central bank’s measure of the real effective exchange rate.
Figure 1.
Australia: real
exchange rate trends
Real and nominal effective exchange rate trends
Real exchange rate and current account and trade balance
80
100
120
140
(a)
(b)
(c)
(d)
(e)
(f )
80
100
120
140
Nominal effective exchange rate
Real effective exchange rate
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–8
–6
–4
–2
0
2
4
6
Real effective exchange rate (lhs)
Ratio of trade balance to GDP (rhs)
Ratio of current account balance to GDP (rhs)
Real exchange rate and real interest differentials
Real exchange rates and historical average
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–4
–2
0
2
4
6
8
10
Real exchange rate, 2,000 = 100 (lhs)
Short-term real interest rate differential (rhs)
Long-term real interest rate differential (rhs)
80
100
120
140
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
80
100
120
140
TWI (RBA)
IMF
Average
Real exchange rate and terms of trade
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
40
60
80
100
120
140
Real exchange rate, 2,000 = 100 (lhs)
Terms of trade for goods and services (rhs)
Terms of trade for goods (rhs)
10
20
30
40
50
60
70
80
90
Jul-07 Oct-07 Jan-08 Apr-08 Jul-08 Oct-08
0.6
0.7
0.8
0.9
1.0
1.1
Vix volatility index (lhs)
Nominal AUD/USD exchange rate (rhs)
Source: IMF staff estimates
Recent movements in the exchange rate and the VIX
Exchange rate
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However, most exchange rate assessments tend to be geared toward evaluating the
consistency of the exchange rate with economic fundamentals over the medium to
longer run. Those factors that have the most in?uence on exchange rates over the short
run are not necessarily the same ones that will exercise the most in?uence over the long
term. Nevertheless, the starting point for the assessment is important. In the past few
months with the global ?nancial turmoil, there has been considerable movement in
exchange rates, as illustrated by the movements in US dollar bilateral exchange
rates for Australia and New Zealand and the VIX, a measure of market volatility
Figure 2.
New Zealand: real
exchange rate trends
Real and nominal effective exchange rate trends Real exchange rate and current account and trade balance
80
100
120
140
1985 1987 1989 1991 1993 1995 1997
(a) (d)
(b) (e)
(c) (f)
1999 2001 2003 2005 2007
80
100
120
140
Nominal effective exchange rate
Real effective exchange rate
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–10
–8
–6
–4
–2
0
2
4
6
8
Real effective exchange rate (lhs)
Ratio of trade balance to GDP (rhs)
Ratio current account balance to GDP (rhs)
Real exchange rate and real interest differentials Real exchange rates and historical average
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–4
–2
0
2
4
6
8
Real exchange rate, 2,000 = 100 (lhs)
Short-term real interest rate differential (rhs)
Long-term real interest rate differential (rhs)
80
100
120
140
160
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
80
100
120
140
160
TWI-5 (RBNZ)
IMF
Average
Real exchange rate and terms of trade Recent movements in the exchange rate and the VIX
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
80
90
100
110
120
130
140
Real exchange rate, 2,000 = 100 (lhs)
Terms of trade for goods and services (rhs)
Terms of trade for goods (rhs)
10
20
30
40
50
60
70
80
90
Jul-07 Oct-07 Jan-08 Apr-08 Jul-08 Oct-08
0.5
0.6
0.7
0.8
0.9
1.0
Vix Volatility Index (lhs)
Nominal NZL/US exchange rate (rhs)
Source: IMF staff estimates
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(Figures 1 and 2, panel (f)). This large increase in volatility has made it more dif?cult to
conduct exchange rate assessments.
III. The empirical models[4]
Country coverage and econometric methodology
The estimation dataset consists of 55 industrial and emerging market economies and
covers the period 1973-2007. For each empirical model, two country groupings are
considered: a 55-country sample (wide panel) and a nine-country sample (narrow
panel). (A detailed description of this panel data set is provided in Appendix 1 and the
theoretical foundation of the three approaches can be found in Appendix 2.) The wide
panel spans economies that contribute signi?cantly to global trade, because an
economy with a large global presence will have greater effects on the exchange rates of
other countries. This wide country coverage allows one to exploit the substantial
cross-country variation among the advanced and emerging market economies in the
sample. However, the wide panel also poses possible estimation problems related to
imposing cross-economy equality restrictions on slope coef?cients[5]. In recognition of
this problem, a narrow panel of nine structurally similar economies is also
considered[6]. The countries are all relatively small and open economies that are
relatively large exporters of primary commodities.
A common econometric methodology has been applied to derive the most suitable
speci?cation. The models are ?rst estimated by OLS and then by the GMM, using
lagged explanatory variables as instruments, where appropriate. For the GMM model,
a general to speci?c model speci?cation strategy is used to derive a parsimonious
speci?cation. Both estimation techniques correct for cross-section speci?c
unconditional heteroskedasticity and contemporaneous correlation of unknown form.
A. The macroeconomic balance approach
The macroeconomic balance (MB) approach focuses on the requirement for achieving
internal and external balance. In practice, it involves assessing the change in the real
effective exchange rate that is needed to close the gap between the “underlying”
current account balance of a country and its “equilibrium” level. This approach
comprises three steps:
(1) Estimating the equilibrium current account balance (current account norm).
(2) Determining the “cyclically adjusted” or underlying current account balance[7].
(3) Calculating the exchange rate adjustment that is required to close the gap
between the underlying and equilibrium current account balances, based on the
estimated elasticity of the current account with respect to the real effective
exchange rate.
The discussion below focuses on the estimation and interpretation of the equilibrium
current account balance.
The estimated medium-run equilibrium value of the current account balance is
derived from a panel regression model:
ca
i;t
¼ b
0;i
þb
T
x
i;t
þ 1
i;t
; ð1Þ
where b
0;i
denotes an economy speci?c ?xed effect, and 1
i;t
, Nð0; s
2
i
Þ. The variable
ca
i;t
denotes the ratio of the current account balance to gross national product (GDP),
Exchange rate
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while x
i;t
denotes a vector of explanatory variables. These variables include the ratio
of the retirement age population to the working age population, the growth rate of the
population, the logarithm of income per capita expressed in terms of purchasing power,
the growth rate of income per capita expressed in terms of purchasing power, the ratio
of the oil trade balance to GDP, the ratio of the ?scal balance to GDP, and the lagged
ratio of the net foreign assets (NFA) position to GDP.
The estimates of equation (1) are broadly similar across econometric techniques and
country coverage (Table I). The estimated coef?cients are statistically signi?cant and
have the expected sign and plausible magnitudes:
.
The coef?cient on the dependency ratio is negative, indicating that a higher
dependency ratio reduces the current account balance. A 1 percent point increase
in the dependency ratio relative to trading partners would lower the current
account norm by about 0.5 percent of GDP.
.
The coef?cient on population growth is negative, but the size varies widely
depending on the estimation method. A 1 percent point increase in population
growth relative to trading partners would lead to a worsening of the current
account norm by 1-4 percent of GDP[8].
.
The coef?cient on higher relative income growth is negative. A 1 percent point
increase in relative income growth would reduce the current account norm by 0.4
percent of GDP.
.
The coef?cient on the oil trade balance is positive. For Australia and New
Zealand, which are net oil importers, this suggests that a widening of the oil
trade de?cit would imply a decrease in the current account norm.
.
The coef?cient on the initial NFA position is positive and quite small. An
increase in NFA of 10 percent of GDP would increase the current account norm
by about 0.01 percent of GDP.
The point estimates are decomposed into time-varying contributions of each of the
explanatory variables, allowing one to give a country-speci?c interpretation to the
equation (Figure 3). Using the wide panel GMM results, we see that the equilibrium
current account de?cits have been driven by a set of common factors[9]. In both
Wide panel Narrow panel
OLS GMM OLS GMM
Relative old-age dependency 20.62
* * *
20.58
* * *
20.66
* * *
20.74
* * *
Relative population growth 20.79
* *
24.26
* *
0.49 21.14
Relative income 20.09
* * *
– 0.07 0.06
Relative income growth 20.02
* * *
20.38
* *
0.38
* * *
–
Oil trade balance 0.73
* * *
0.88
* * *
1.26
* * *
1.31
* * *
Relative ?scal balance 0.17
* * *
0.08
* * *
0.18
* *
0.15
* *
Initial net foreign assets 0.001
* *
0.001
* *
20.002 0.001
Observations 735 714 174 169
R
2
0.73 0.67 0.76 0.78
Notes: Statistical signi?cant at the
*
10%,
* *
5%, and
* * *
1% levels; dependent variable: ratio of
current account balance to output
Table I.
Estimation results for the
MB approach
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countries, high relative population growth has contributed to their large current
account de?cits. Both countries have relatively low dependency ratios that have
supported their current account de?cits. In addition, relatively low income growth has
reduced private investment, which has reduced their equilibrium current account
de?cits. Finally, oil trade de?cits have exacerbated their equilibrium current account
de?cits.
B. The equilibrium real exchange rate approach
The equilibrium real exchange rate (ERER) approach models the real effective
exchange rate as a function of factors that cause temporary but persistent deviations
from long-run PPP. As discussed in a survey paper by Froot and Rogoff (1995), a
variety of theoretical models predict the existence of such factors. The model takes the
form:
ln
Q
i;t
¼ b
0;i
þb
T
x
i;t
þ 1
i;t
; ð2Þ
where b
0;i
denotes an economy speci?c ?xed effect, and 1
i;t
, Nð0; s
2
i
Þ. The dependent
variable denoted as
Q
i;t
is the real effective exchange rate, while x
i;t
denotes a vector of
explanatory variables. These variables include the logarithm of the terms of trade, the
logarithm of output per worker expressed in terms of purchasing power, the ratio of
government consumption to GDP, and the ratio of the NFA position to GDP.
The ?rst column in Table II reports the estimated equilibrium long-run
relationship between the real exchange and the above mentioned set of explanatory
variables. The speci?cation in column 2 provides a parsimonious set of coef?cients,
which have been estimated using GMM. The coef?cients on all three explanatory
Figure 3.
MB approach: estimated
contribution – level and
change in percent of GDP
Australia - level
–8
–6
–4
–2
0
2
1997 1999 2001 2003 2005 2007
Fixed effect Relative old age dependency
Relative population growth Relative income growth
Oil trade balance Initial net foreign assets
Fiscal balance Actual current account
Predicted current account
New Zealand - level
–12
–8
–4
0
4
1997 1999 2001 2003 2005 2007
Fixed effect Relative old age dependency
Relative population growth Relative income growth
Oil trade balance Initial net foreign assets
Fiscal balance Actual current account
Predicted current account
Australia - change
–3
–2
–1
0
1
2
3
1997 1999 2001 2003 2005 2007
New Zealand - change
–6
–4
–2
0
2
4
1997 1999 2001 2003 2005 2007
Relative old age dependency Relative population growth
Relative income growth Oil trade balance
Initial net foreign assets Fiscal balance
Actual current account Predicted current account
Source: IMF staff estimates
Relative old age dependency Relative population growth
Relative income growth Oil trade balance
Initial net foreign assets Fiscal balance
Actual current account Predicted current account
Exchange rate
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variables are positive, so that an increase relative to trading partners of each variable
would tend to lead to an appreciation of a country’s equilibrium exchange rate.
Looking more closely at the decomposition of the model for Australia and New
Zealand highlights the positive effect from the terms of trade in the recent period
(Figure 4). The improvement in the terms of trade contributed positively to the
appreciation of the Australian dollar since 1999. In addition, high relative productivity
and government consumption also contributed to the strength of the Australian dollar.
In contrast, for New Zealand, low relative productivity has contributed negatively to
the equilibrium real effective exchange rate.
Wide panel Narrow panel
OLS GMM OLS GMM
Terms of trade 0.33
* * *
0.41
* * *
0.34
* * *
20.39
* * *
Relative productivity 0.15 0.26
* * *
20.42
* *
–
Relative government consumption 0.38
* * *
1.76
* * *
3.54 –
Initial net foreign assets 0.00
* *
– 20.03
* * *
–
Observations 724 1,006 165 238
R
2
0.52 0.67 0.48 0.19
Notes: Statistical signi?cant at the
*
10%,
* *
5%, and
* * *
10% levels; dependent variable: real
effective exchange rate
Table II.
Estimation results for the
ERER approach
Figure 4.
ERER approach:
estimated contribution –
level and change
Australia - level
–0.2
0.0
0.2
0.4
1997 1999 2001 2003 2005 2007
Fixed effect Relative government consumption
Relative productivity Terms of trade
Predicted real effective exchange rate Actual real effective exchange rate
New Zealand - level
–0.2
0.0
0.2
0.4
1997 1999 2001 2003 2005 2007
Terms of trade
Relative productivity
Relative government consumption
Fixed effect
Actual real effective exchange
rate
Predicted real effective exchange rate
Australia - change
–0.10
–0.05
0.00
0.05
0.10
0.15
1997 1999 2001 2003 2005 2007
Relative government consumption Relative productivity
Terms of trade Predicted real effective exchange
rate Actual real effective exchange rate
New Zealand - change
–0.15
–0.10
–0.05
0.00
0.05
0.10
0.15
1997 1999 2001 2003 2005 2007
Terms of trade
Relative productivity
Relative government consumption
Actual real effective exchange rate
Predicted real effective exchange rate
Source: IMF staff estimates
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C. The external sustainability approach
The third approach, the external sustainability approach (ES), focuses on the
relationship between the sustainability of a country’s external stock and its current
account ?ow, and the real effective exchange rate. Like the MB approach, it involves
three steps:
(1) Estimating the ratio of the current account balance to GDP that would stabilize
the NFA position at a given benchmark value.
(2) Determining the level of the current account balance expected to prevail over
the medium term.
(3) Assessing the adjustment in the real effective exchange rate that is needed to
close the gap between the medium-term current account and the
NFA-stabilizing current account balance.
The medium-run equilibrium value of the ratio of the NFA position to GDP is modeled
from an intertemporal perspective.
The benchmark level of the NFAposition is the key element in the ES approach. It is
common to calibrate this benchmark level to match the most recently observed value of
the NFA position, or some measure of the central tendency of its recently observed
values. Alternatively, the medium-run equilibrium value of the NFA position is
modeled in a panel regression taking the form:
nfa
i;t
¼ b
0;i
þb
T
x
i;t
þ 1
i;t
ð3Þ
where b
0;i
denotes an economy speci?c ?xed effect, and 1
i;t
, Nð0; s
2
i
Þ. As speci?ed,
nfa
i;t
denotes the ratio of the NFA position to GDP, while x
i;t
denotes a vector of
explanatory variables. These include the logarithm of output per worker expressed in
terms of purchasing power, the ratio of the retirement age population to the working
age population, and the ratio of the government net asset position to GDP.
Table III reports the estimation results for the ratio of the NFAposition to GDP. The
results for the wide panel suggest that higher relative productivity would reduce the
NFA position, while a higher dependency ratio and government net asset position
would increase the NFA position. The results for the narrow panel are mixed; only the
coef?cient on the government net asset position is signi?cant.
Looking more closely at the results for Australia and New Zealand, reveals that
?xed effects account for the majority of the estimated equilibrium net foreign debt
Wide panel Narrow panel
OLS GMM OLS GMM
Relative productivity 20.34
* * *
20.39
* * *
20.12 –
Relative old-age dependency 0.69
* *
– 20.95 –
Government net assets 20.21
* * *
0.17
* * *
0.53
* * *
0.58
* * *
Observations 527 514 159 198
R
2
0.90 0.67 0.71 0.69
Notes: Statistical signi?cant at the
*
10%,
* *
5%, and
* * *
1% levels; dependent variable: ratio of net
foreign assets to output
Table III.
Estimation results
for the ES approach
Exchange rate
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positions (Figure 5). This result suggests that relevant explanatory variables that vary
signi?cantly across economies but not over time have been omitted from the panel
regression model.
IV. Exchange rate assessments
A. Baseline results
For the purposes of comparability, we develop a baseline where each approach is
applied to Australian and New Zealand data. Because exchange rates are notoriously
dif?cult to forecast in the short run, the medium-run horizon (2013) was deemed the
best for the construction of the baseline benchmark. Also, to construct the baseline we
use the GMM model estimates for the sample of 55 countries. To complete this exercise,
the medium-term forecast of the explanatory variables is based on the October 2008
World Economic Outlook (WEO), unless otherwise indicated.
For the MB and ES approach, the assessments are based on the required real
exchange rate adjustment that would close the gap between the estimated current
account norm and the underlying (projected) current account based on the WEO
forecasts. The magnitude of the exchange rate adjustment is derived by dividing the
current account gap by the semi-elasticity of the current account with respect to the real
effective exchange rate. The notion is that a country more open to trade will be able to
close its current account gap with less real exchange rate adjustment. For the ERER
approach, the magnitude of the exchange rate adjustment is calculated directly as the
difference between the country’s real effective exchange rate and its estimated
equilibrium value.
Figure 5.
ES approach:
estimated contribution –
level and change
Australia - level
–70
–60
–50
–40
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–20
–10
0
10
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Fixed effect Relative productivity
Government net foreign assets Actual net foreign assets
Predicted net foreign assets
New Zealand - level
–100
–80
–60
–40
–20
0
20
1997 1999 2001 2003 2005 2007
Fixed effect Relative productivity
Government net foreign assets Actual net foreign assets
Predicted net foreign assets
Australia - change
–4
–2
0
2
4
6
1997 1999 2001 2003 2005 2007
Relative productivity
Actual net foreign assets
Government net foreign assets
Predicted net foreign assets
New Zealand - change
–4
–2
0
2
4
1997 1999 2001 2003 2005 2007
–30
–20
–10
0
10
20
Relative productivity
Predicted net foreign assets
Government net foreign assets
Actual net foreign assets (rhs)
Source: IMF staff estimates
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The baseline estimates for the level of the exchange rate are wide-ranging, varying
considerably across models. For Australia, the ERER model indicates the dollar is 18
percent undervalued while the ES model produces estimates that suggest the dollar to
be overvalued by 17 percent[10]. The estimates from the MB model fall in the middle, at
3 percent overvalued. For the New Zealand dollar the baseline estimates are similarly
spread, going from 7 percent undervalued (ERER) to 11 percent overvalued (ES)
(Table IV). These results are based on the assumption that the underlying current
account de?cit for Australia is 5.0 percent of GDP and 5.6 percent of GDP for New
Zealand (i.e. the WEO forecast for 2013). For the MB and ES approaches, the elasticities
are taken from the IMF CGER methodology (Lee et al., 2008).
Not only are these point estimates wide ranging across models, but there is also a
great deal of uncertainty for each model. Figure 6 shows both the point estimate
(depicted with bars) and the 90 percent con?dence intervals, which capture model
uncertainty[11]. For Australia, the estimate ranges from 30 percent undervalued to
Current account
balance
Norm Forecast Real effective exchange rate
Australia
a
Macroeconomic balance 24.5 25.0 2.8
Equilibrium real exchange – – 217.8
External sustainability rate 22.4 25.0 16.7
New Zealand
b
Macroeconomic balance 25.2 25.6 1.6
Equilibrium real exchange rate – – 27.0
External sustainability 23.3 25.6 11.1
Notes: All ?gures are based on ?ve year conditional forecasts, and are expressed in percent;
a
estimates are based on a medium-run semi-elasticity of the ratio of the current account balance to
output with respect to the real effective exchange rate of 20.16, a net foreign asset-to-GDP norm of
249.5, and a medium-run equilibrium output growth rate of 5.3 percent;
b
estimates are based on a
medium-run semi-elasticity of the ratio of the current account balance to output with respect to the real
effective exchange rate of 20.21, a net foreign asset to GDP norm of 271.2, and a medium-run
equilibrium output growth rate of 4.8 percent
Source: IMF staff estimates
Table IV.
Baseline result:
quantitative exchange
rate assessment
Figure 6.
Con?dence intervals
The model yields wide confidence bands for Australia... ...and bands are even wider for some models for New Zealand
Australia: 90 percent confidence intervals
–35
–30
–25
–20
–15
–10
–5
0
5
10
15
20
25
30
MB ERER ES
–35
–30
–25
–20
–15
–10
–5
0
5
10
15
20
25
30
–25
–20
–15
–10
–5
5
0
10
15
20
25
30
35
New Zealand: 90 pecent confidence intervals
–25
–20
–15
–10
–5
0
5
10
15
20
25
30
35
MB ERER ES
Source: IMF staff estimates
Exchange rate
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25 percent overvalued. For New Zealand, the range is almost as wide, spanning
from 222 percent undervalued to 20 percent overvalued. Note that these con?dence
intervals may overstate the uncertainty surrounding the exchange rate overvaluation
estimates, as they are in?ated by model misspeci?cation[12].
B. Robustness tests
Given the large differences in the baseline results and the model uncertainty, there are
serious questions regarding the robustness of estimates of overvaluation. While the
baseline construction appears somewhat arbitrary, it was chosen because it broadly
re?ected the assumptions made when these models are applied at the IMF. To gain a
better understanding of what lies behind these results, we consider a battery of
robustness tests. The remainder of this section considers alternative speci?cations by
changing the underlying WEO forecasts and reference exchange rate, auxiliary
parameters, assessment horizon, country sample, and estimation method.
Reference period. The medium-term forecast used to derive the explanatory
variables and the reference period for the exchange rate may have a large impact on the
assessment, especially during turbulent times. Since June 2008, there has been a
considerable downgrading of the global outlook and large changes in the WEO
forecasts. Over this period, the Australian and New Zealand dollars have come under
substantial downward pressure as commodity prices eased and interest rate
differentials narrowed. At the end of October, the Australian dollar was more than 30
percent off its mid-year peak in nominal effective terms and the New Zealand dollar
was nearly 20 percent lower than mid-year. These large moves make an exchange rate
assessment ephemeral.
Against this background, we illustrate how rapidly the exchange rate assessment
can change over a short period of time and how the different models tend to re?ect
these changes. Three different WEO forecasts (June, August, and October) with
corresponding reference exchange rates are used to compute the degree of
overvaluation (Table V). For example, for Australia the June MB approach indicated
that the dollar was overvalued by 8 percent, while in October the gap was 3 percent.
Over the same period, the ERER model showed a large swing, moving from being
Assessment date MB 2013 ERER 2013 ES 2013
Australia
June 2008
a
8.1 8 18.4
August 2008
b
5.0 3.3 21.4
October 2008
c
2.8 217.8 16.7
New Zealand
June 2008
a
13.9 12.2 19.1
August 2008
b
6.7 1.5 19.0
October 2008
c
1.6 27.0 11.1
Notes: Results reported are estimated for the sample of 55 countries using GMM;
a
based on Spring
2008 WEO and reference period for exchange rate is average for 2007;
b
Based on Spring 2008 WEO
and reference period for exchange rate is end August 2008;
c
based on October 2008 WEOand reference
period for exchange rate is end October 2008
Source: Fund staff estimates
Table V.
Sensitivity: reference data
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overvalued by 8 percent in June to being undervalued by 18 percent in October. The
results for New Zealand also show a narrowing overvaluation or a move to being
undervalued depending on which model is being used. In contrast, the ES model seems
to be less affected by these changes and furthermore consistently projects a greater
overvaluation than the other models.
Auxiliary parameters. The degree of overvaluation also depends on the auxiliary
parameter assumptions. Below we consider the impact of key parameters for the MB
approach and ES approach.
MB approach: current account norms and trade elasticities. Two key parameters for
the MB approach are: the underlying current account projection and the medium-run
semi-elasticity of the ratio of the current account balance to GDP with respect to the
real effective exchange rate (trade elasticity). A larger current account de?cit creates a
large gap between the projection and the norm, which requires a larger exchange rate
adjustment. For a given current account gap, a larger trade elasticity reduces the
exchange rate overvaluation.
Using the baseline as a point of departure, plausible sensitivity analysis suggests
that the Australian exchange rate assessment ranges between an undervaluation of 5
percent to an overvaluation of 13 percent. For New Zealand, the range is from an
undervaluation of 4 percent to an overvaluation of 8 percent (Table VI). These results
underscore the uncertainty surrounding the equilibrium level of the real effective
exchange rate[13].
ES approach: NFA norms and nominal growth assumption. The ES approach relies
on an intertemporal budget constraint that requires the present value of future trade
surpluses be suf?cient to pay for the country’s outstanding external liabilities. Two
key parameters in this approach are the NFA norm and the rate of growth of the
economy. The current account norm consistent with stabilizing NFAs at a given level
is approximately proportional to this growth rate. Thus, for net debtor countries,
higher growth rates are associated with higher equilibrium current account de?cits.
Taking this one step further, this will tend to reduce the current account gap, which
will lead to a smaller overvaluation of the exchange rate.
The benchmark level of the NFA position is the key in the ES approach. It is
common to calibrate this benchmark level to the most recently observed value of
the NFA position, or to some measure of the central tendency of its recently
Elasticity CA/GDP projection
a
Australia 24.0 25.0 26.0
20.11 25.2 3.9 13.0
20.16 23.6 2.8 8.9
20.21 22.7 2.0 6.8
New Zealand 24.6 25.6 26.6
20.16 24.1 2.1 8.4
20.21 23.1 1.6 6.4
20.26 22.5 1.3 5.2
Notes: REER overvaluation is expressed in percent;
a
projection of the underlying CA/GDP in 2013
Source: IMF staff estimates
Table VI.
Sensitivity analysis: MB
Approach – CA/GDP
projection and trade
elasticity
Exchange rate
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observed values. The baseline estimates use model derived NFA estimates. For
comparison, we also compute the degree of overvaluation using the end-2007 NFA to
GDP ratio. For both Australia and New Zealand, the model estimates produce
relatively low NFA positions, therefore replacing those values with end-2007 lifts the
NFA norms and as a consequence raises the current account norm. This in turn
reduces the estimates of overvaluation (Table VII).
To illustrate the sensitivity of the assessment to growth rates, we use the baseline as
the point of departure and recomputed the degree of overvaluation assuming a 1
percent point higher and lower growth rate. The degree of overvaluation clearly
changes as we vary the growth rate of the economy. For both countries, a 1 percent
point change in the growth rate alters the estimate of overvaluation by nearly 3 percent
points (Table VIII).
Assessment horizon. The time horizon that is used to evaluate the consistency of the
exchange rate with economic fundamentals is also another important factor. For the
baseline, the adjustment was calculated based on medium-term fundamentals ?ve
years hence. It is assumed that at this point in time, the economy is operating at its
potential and therefore one is able to abstract from cyclical and short-term in?uences
Baseline – estimated Alternative – observed 2007
Australia
a
NFA norm 247.4 261.9
Current account norm 22.4 23.1
Degree of misalignment 16.7 12.0
New Zealand
b
NFA norm 271.2 287.2
Current account norm 23.3 24.0
Degree of misalignment 11.1 7.6
Notes: Results reported are at time t þ 5, using GMM estimator, 55 countries;
a
for Australia, the
baseline NFA is estimated from the model (Table III), the alternative NFA measure is observed at end
2007, the growth rate is 5.3;
b
for NewZealand, the baseline NFAis estimated fromthe model (Table III),
the alternative NFA measure is observed at end 2007, the growth rate is 4.8
Source: IMF staff estimates
Table VII.
Sensitivity: external
sustanability – NFA
norms
Lower growth Baseline higher growth
Australia
a
Current account norm 22.0 22.4 22.8
Degree of misalignment 19.5 16.7 13.9
New Zealand
b
Current account norm 22.6 23.3 23.9
Degree of misalignment 14.3 11.1 8.0
Notes: Results reported are at time t þ 5, using GMM estimator, 55 countries;
a
For Australia, the
baseline growth is 5.3 percent, low growth is 4.3 percent, and high growth is 6.3 percent;
b
for New
Zealand, the baseline growth is 4.8 percent, low growth is 3.8 percent, and high growth is 5.8 percent
Source: IMF staff estimates
Table VIII.
Sensitivity: external
sustanability – growth
rates
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on the exchange rate. However, some argue that the assessment should also be made
based on the current value of fundamentals.
In the cases of Australia and New Zealand, exchange rate assessments taken at the
current horizon (2008) tend to suggest larger overvaluation, but this result varies
across models and by country (Table IX). The MB model for Australia suggests the
size of overvaluation is broadly similar across the two horizons. In contrast, the ERER
model suggests that the exchange rate is relatively close to its equilibrium level in the
short run, but in the medium-term baseline estimates suggested the exchange rate was
nearly 18 percent undervalued. For New Zealand, the size of overvaluation is larger for
all models for the current period. Once again, for both countries, the ES model appears
to be less sensitive to changes in the time horizon and tends to register the largest
overvaluation.
Country coverage. The set of economies that are included in the sample also
in?uences the assessment. Two panel estimates for each model are considered, varying
the country coverage. In contrast to the baseline, which uses the wider sample, the
narrow sample tends to produce smaller overvaluation estimates for Australia.
The results are mixed for NewZealand (Table X). The difference re?ects the changes in
the selected model speci?cations and coef?cient estimates. Consistent with earlier
robustness tests, the ES model tends to report large overvaluations.
Estimation method. For comparison to other results, the models were also estimated
by OLS. In general, the OLS estimates tend to be higher than those based on GMM
2008 2013
Australia
Macroeconomic balance 7.8 2.8
Equilibrium real exchange rate 0.5 217.8
External sustainability 24.2 16.7
New Zealand
Macroeconomic balance 16.8 1.6
Equilibrium real exchange rate 10.7 27.0
External sustainability 23.4 11.1
Source: IMF staff estimates
Table IX.
Sensitivity:
assessment period
Wide sample
a
Narrow sample
b
Australia
Macroeconomic balance 2.8 0.0
Equilibrium real exchange rate 217.8 226.9
External sustainability 16.7 14.8
New Zealand
Macroeconomic balance 1.6 21.4
Equilibrium real exchange rate 27.0 28.4
External sustainability 11.1 12.9
Notes: Results reported are at time t þ 5;
a
sample 55 countries;
b
sample nine countries
Source: IMF staff estimates
Table X.
Sensitivity:
country coverage
Exchange rate
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estimates (Table XI). For example, for the MB model, the OLS estimate for Australia
suggests a 9 percent point adjustment where as the GMM estimates suggest a
2.8 percent point adjustment. However, the size of the difference varies considerably by
model.
In sum, the quantitative assessments are sensitive to variations in assumptions. For
Australia and New Zealand, small changes in the baseline can lead to substantial
differences in exchange rate overvaluation estimates (Figure 7).
V. Concluding remarks
Drawing on existing literature, this paper has estimated three commonly used
equilibrium exchange rate models and applied them to Australia and New Zealand.
The baseline results used data as of October 2008 and suggest that the Australian and
New Zealand dollars may be misaligned, but the direction of that misalignment is
unclear. The ERER model suggests undervaluation for both currencies, while the MB
model results imply the currencies are broadly in line with fundamentals. In contrast,
the ES model results indicate that both currencies are overvalued.
As a result, numerical exchange rate assessments need to be treated with caution as
the size of overvaluation, even under the baseline, can give very imprecise answers.
There are a number of potential factors that can create this uncertainty, which
we investigated. For example, the empirical relationships of the different models were
estimated for a large pool of heterogeneous countries and there could be large
OLS GMM
Australia
Macroeconomic balance 9.0 2.8
Equilibrium real exchange rate 26.2 27.0
External sustainability 16.4 16.7
New Zealand
Macroeconomic balance 3.7 1.6
Equilibrium real exchange rate 26.2 27.0
External sustainability 11.0 11.1
Note:
a
Results reported are at time t þ 5 and estimated for the sample of 55 countries
Source: IMF staff estimates
Table XI.
Sensitivity: estimation
method
a
Figure 7.
Quantitative exchange
rate assessment: summary
Australia
–30
–20
–10
0
10
20
30
MB ERER ES
P
e
r
c
e
n
t
Baseline Reference period Assessment horizon
Country coverage Estimation method
Baseline Reference period Assessment horizon
Country coverage Estimation method
New Zealand
–20
–10
0
10
20
30
MB ERER ES
P
e
r
c
e
n
t
Source: IMF staff estimates
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differences between the resulting “average” country and Australia or New Zealand.
This was partially addressed in the paper by reestimating the model over a narrow
more homogenous panel of countries, but this too has its shortcomings.
The lesson drawn from this exercise is simple: there is a great deal of weakness to
numerical exchange rate assessments and they should be viewed as a diagnostic tool
and not as the golden yardstick from which to judge the appropriate level of the
exchange rate.
Notes
1. Several papers have been written in this area by Lee et al. (2008) and Isard (2007) containing
summaries of the methodologies that underpin the analysis and references to earlier IMF
literature.
2. Similar conclusions emerged in Dunaway et al. (2006).
3. The 2008 data included in these ?gures are mostly based on data from October.
4. See Appendix 2 for the theoretical foundations of these models.
5. The imposition of cross-economy equality restrictions on slope coef?cients generally yields
asymptotic variance reductions at the cost of asymptotic bias increases. It is ambiguous
whether conditioning estimation on a wide panel of structurally dissimilar economies or a
narrowpanel of structurally similar economies is optimal fromthe perspective of minimizing
asymptotic mean-squared error (Davidson and MacKinnon, 2004).
6. The economies considered are: Australia, Canada, Chile, Denmark, Finland, New Zealand,
Norway, South Africa, and Sweden.
7. In practice, the underlying current account is de?ned as the value of the current account that
would be observed at the prevailing real effective exchange rate if all countries were
operating at potential output (internal balance) and if the effects of past exchange rate
changes had been completely realized.
8. The size of the coef?cient is robust to changes in the estimation sample period.
9. The results for the narrow panel are broadly similar with some variation in the size of
coef?cient estimates, partly re?ecting lower degrees of freedom.
10. The ERER model uses a terms of trade projection that may not re?ect market expectations.
11. Projections for the ERER model are based on Table XII.
12. Modeling observed levels as a function only of the determinants of unobserved trend
components adds unobserved cyclical components to the residuals, increasing their
variances. If cyclical and trend components were jointly modeled within an unobserved
Terms of trade Relative productivity Relative government consumption
Australia
2008 1.21 1.25 1.00
2013 1.15 1.19 1.00
New Zealand
2008 1.19 0.80 1.01
2013 1.24 0.77 1.02
Note: ERER model: forecast of explanatory variables
Table XII.
Exchange rate
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components framework, then the variances of estimates of medium-run equilibrium values
would be reduced. Moreover, deviations of observed levels from estimated medium-run
equilibrium values could be explained in terms of cyclical factors.
13. These speci?c results need to be interpreted with caution because they have not been derived
by statistical methods and therefore it is not possible to assign any level of con?dence to
them.
14. Where appropriate, the explanatory variables for each approach are expressed as deviations
from trade-weighted averages across trading partners.
15. The derivation of this result assumes that the real effective exchange rate is GDP-based.
16. This bypasses separate measurement of tradables productivity and nontradables
productivity, expressed as deviations from trade-weighted average across trading partners.
This is desirable in practice, as the sectoral output and employment data required to construct
these explanatory variables are released with long delays for many economies, while the
distinction between tradables and nontradables sectors is somewhat arbitrary.
References
Balassa, B. (1964), “The purchasing power parity doctrine: a reappraisal”, Journal of Political
Economy, Vol. 72, pp. 584-96.
Barro, R. and Sala-i-Martin, X. (1999), Economic Growth, MIT Press, Cambridge, MA.
Brooks, A. and Hargreaves, D. (2000), “A macroeconomic balance measure of New Zealand’s
equilibrium exchange rate”, Discussion Paper No. 2000/09, Reserve Bank of New Zealand,
Wellington, available at:http://EconPapers.repec.org/RePEc:nzb:nzbdps:2000/09
Campa, J. and Goldberg, L. (2002), “Exchange rate pass-through into import prices: a macro or
micro phenomenon?”, Working Paper No. 9834, National Bureau of Economic Research,
Cambridge, MA.
Davidson, R. and MacKinnon, J. (2004), Econometric Theory and Methods, Oxford University
Press, New York, NY.
Dunaway, S., Leigh, L. and Li, Z. (2006), “How robust are estimates of equilibrium exchange
rates? The case of China”, Working Paper No. 06/220, International Monetary Fund,
Washington, DC.
Dvornak, N., Kohler, M. and Menzies, G. (2003), “Australia’s medium-run exchange rate:
a macroeconomic balance approach”, Discussion Paper No. 2003-03, Reserve Bank of
Australia, Sydney.
Froot, K. and Rogoff, K. (1995), “Perspectives on PPP and long-run real exchange rates”,
Handbook of International Economics, Vol. 3, pp. 1647-88.
Isard, P. (2007), “Equilibrium exchange rates: assessment methodologies”, Working Paper
No. 07/296, International Monetary Fund, Washington, DC.
Lee, J., Milesi-Ferretti, G.M., Ostry, J.D., Prati, A. and Ricci, L. (2008), “Exchange rate
assessments: CGER methodologies”, Occasional Paper No. 261, International Monetary
Fund, Washington, DC.
MacDonald, R. (2001), “Modelling the long-run real effective exchange rate of the New Zealand
dollar”, Discussion Paper No. 2002/02, Reserve Bank of New Zealand, Wellington.
Obstfeld, M. and Rogoff, K. (1995), “The intertemporal approach to the current account”,
Handbook of International Economics, Vol. 3, pp. 1731-99.
Rogoff, K. (1996), “The purchasing power parity puzzle”, Journal of Economic Literature, Vol. 34,
pp. 647-68.
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Samuelson, P. (1964), “Theoretical notes on trade problems”, Review of Economics and Statistics,
Vol. 46, pp. 145-64.
Wren-Lewis, S. (2004), “A model of equilibrium exchange rates for New Zealand and Australian
dollars”, Discussion Paper No. 2004/07, Reserve Bank of New Zealand, Wellington.
Further reading
International Monetary Fund (2008), World Economic Outlook, International Monetary Fund,
Washington, DC, October.
Appendix 1. Dataset description
Country coverage
Wide panel sample. Algeria, Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, China,
Colombia, Croatia, the Czech Republic, Denmark, Egypt, Finland, France, Germany, Greece,
Hong Kong SAR, Hungary, India, Indonesia, Ireland, Israel, Italy, Japan, Korea, Luxembourg,
Malaysia, Mexico, Morocco, The Netherlands, New Zealand, Norway, Pakistan, Peru, the
Philippines, Poland, Portugal, Russia, Saudi Arabia, Singapore, the Slovak Republic, Slovenia,
South Africa, Spain, Sweden, Switzerland, Taiwan POC, Thailand, Tunisia, Turkey, the UK, the
USA, and Venezuela.
Narrow panel sample. Australia, Canada, Chile, Denmark, Finland, New Zealand, Norway,
South Africa, and Sweden.
Dataset
The dataset consists of annual observations on several macroeconomic variables over the period
1973-2007. In addition, for the medium-term analysis it uses forecasts from the WEO over the
period 2008-2013. This panel is unbalanced, in the sense that the number of observations varies
across macroeconomic variables along both the cross-sectional and time-series dimensions.
Variables[14]
Macroeconomic balance approach. Dependent variable: the ratio of the current account balance
to GDP.
Explanatory variables:
.
the ratio of the retirement age population to the working age population;
.
the growth rate of the population;
.
the logarithm of income per capita expressed in terms of purchasing power;
.
the growth rate of income per capita expressed in terms of purchasing power;
.
the ratio of the oil trade balance to GDP;
.
the ratio of the ?scal balance to GDP; and
.
the lagged ratio of the NFA position to GDP.
Equilibrium real exchange rate approach. Dependent variable: the logarithm of the real effective
exchange rate.
Explanatory variables:
.
the logarithm of the terms of trade;
.
the logarithm of output per worker expressed in terms of purchasing power;
.
the ratio of government consumption to GDP; and
.
the ratio of the NFA position to GDP.
External sustainability approach. Dependent variable: the ratio of the NFA position to GDP.
Exchange rate
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Explanatory variables:
.
the logarithm of output per worker expressed in terms of purchasing power;
.
the ratio of the retirement age population to the working age population, and
.
the ratio of the government net asset position to GDP.
Data sources
Data and forecasts, where possible, are from the October 2008 vintage of the World Economic
Outlook database maintained by the international monetary fund. These forecasts are
conditional on a constant consumer price index-based real effective exchange rate. Other data
were retrieved from other databases maintained by the International Monetary Fund or the
World Bank Group, and conditional forecasts were generated. In particular, effective exchange
rate data were obtained from the information notice system database, NFA position data
were retrieved from the international investment position database, and population share
data were extracted from the world development indicators database.
Appendix 2. The theoretical framework
This Appendix discusses the theoretical foundation of the three approaches.
MB approach
Under the MB approach, the medium-run equilibrium value of the ratio of the current account
balance to GDP is jointly modeled from intertemporal and intratemporal perspectives. The
medium-run equilibrium value of the real effective exchange rate is then inferred as that value of
the real effective exchange rate that reconciles these intertemporal and intratemporal current
account balance estimates.
As discussed in a survey paper by Obstfeld and Rogoff (1995), intertemporal models of the
current account balance are based on the saving and investment behavior of domestic economic
agents. Private saving is typically modeled within the framework of household utility
maximization, while private investment is typically modeled within the framework of ?rm value
maximization. Public saving and investment are typically treated as exogenous.
Within the framework of overlapping generations models, household utility maximization
predicts temporary but persistent deviations of the private saving rate from its long-run
equilibrium value in response to demographic change. The pro?le of household disposable
income over the life cycle is typically hump-shaped. Given this household disposable income
pro?le, consumption smoothing behavior implies a reduction in the private saving rate in
response to an increase in the economically inactive share of the population. It is common to
proxy for this effect of demographic change with the ratio of the retirement age population to the
working age population, and the growth rate of the population, both of which are expected to be
negatively associated with the private saving rate, and by implication with the ratio of the
current account balance to output.
Within the framework of neoclassical growth models, ?rm value maximization predicts
temporary but persistent deviations of the private investment rate from its long-run equilibrium
value in response to unbalanced economic growth. Under the conditional convergence
hypothesis discussed in Barro and Sala-i-Martin (1999), technological diffusion across economies
having similar saving rates and population growth rates implies a negative association of the
private capital investment rate with the level of income per capita, and a positive association
with the growth rate of income per capita. This implies a positive association of the ratio of the
current account balance to output with the level of income per capita, and a negative association
with its growth rate.
Under Ricardian equivalence, households fully internalize the intertemporal budget
constraint of the government, implying invariance of the current account balance to the ?scal
balance. A variety of theoretical models predict departures from Ricardian equivalence, in which
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case the ratio of the current account balance to output is typically positively associated with the
?scal balance. Departures from Ricardian equivalence are well documented empirically.
Equilibrium real exchange rate approach
Let
S
i;t
denote the nominal effective exchange rate, de?ned as a geometric trade-weighted
average of nominal bilateral exchange rates S
i;t
, each of which measures the price of the domestic
currency in terms of foreign currency. Also, let
Q
i;t
denote the real effective exchange rate,
de?ned as a geometric trade-weighted average of real bilateral exchange rates Q
i;t
, each of which
measures the price of a basket of domestic goods and services in terms of a basket of foreign
goods and services. If P
i;t
denotes the price of this basket of domestic goods and services, then
the real effective exchange rate satis?es:
ln
Q
i;t
¼ ln
S
i;t
þ ln P
i;t
2ln
P
i;t
ðA1Þ
where
P
i;t
denotes a geometric trade-weighted average of the prices of these baskets of foreign
goods and services. Suppose that P
i;t
may be expressed as a geometric trade-weighted average
of the prices of tradables P
T
i;t
and nontradables P
N
i;t
:
ln P
i;t
¼ u ln P
T
i;t
þ ð1 2uÞln P
N
i;t
ðA2Þ
where 0 # u # 1. Combination of this de?nition with result (A1) yields the following
decomposition of deviations from long-run PPP into deviations from the law of one price for
tradables, and deviations of the price of nontradables in terms of tradables from a geometric
trade-weighted average of this relative price across trading partners:
ln
Q
i;t
¼ ln
S
i;t
P
T
i;t
P
T
i;t
þ ð1 2uÞ ln
P
N
i;t
P
T
i;t
2ln
P
N
i;t
P
T
i;t
2
4
3
5
ðA3Þ
This decomposition is useful for classifying theoretical models which predict temporary but
persistent deviations of the real effective exchange rate from its long-run equilibrium value.
Let T
i;t
denote the terms of trade, de?ned as the price of exports of goods and services in
terms of imports of goods and services. If exchange rate pass through is complete, then the
domestic currency price of imports equals the foreign currency price of exports converted into
domestic currency, and decomposition (A3) may be expressed as:
ln
Q
i;t
¼ ln T
i;t
þ ð1 2uÞ ln
P
N
i;t
P
T
i;t
2ln
P
N
i;t
P
T
i;t
2
4
3
5
: ðA4Þ
In an empirical investigation of the degree of exchange rate pass through among developed
economies, Campa and Goldberg (2002) ?nd that exchange rate pass through is incomplete in the
short run, but complete in the long run[15]. This empirical evidence suggests a positive
association between the real effective exchange rate and the terms of trade.
The existence of deviations from long-run PPP attributable to the existence of nontradables is
rationalized by the model due to Balassa (1964) and Samuelson (1964). They consider a small
open economy which produces tradable and nontradable outputs with capital and labor inputs.
Consistent with a medium-run interpretation, they assume that capital is freely mobile both
internationally and across sectors domestically, while labor is only freely mobile across sectors
domestically. Within this theoretical framework, if productivity growth in the tradables sector
exceeds that in the nontradables sector, then in competitive equilibrium, wage equalization
across sectors implies that the price of nontradables in terms of tradables will increase over time.
If the relative price of nontradables rises faster domestically than among trading partners, then
Exchange rate
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appreciation of the domestic currency in real effective terms is induced. As emphasized by Froot
and Rogoff (1995), this mechanism remains operative even in the absence of a productivity
growth differential across the tradables and nontradables sectors, provided that tradables are
relatively capital intensive, as is generally observed. Following Balassa (1964), it is common to
assume that tradables productivity bias is pronounced in relatively productive economies,
implying a positive association between the real effective exchange rate and output per worker,
expressed as a deviation from a trade-weighted average across trading partners[16].
Under the model associated with Balassa (1964) and Samuelson (1964), the real effective
exchange rate depends only on supply factors. However, if the strong assumptions underlying
this theoretical framework are relaxed, then the real effective exchange rate can also depend on
demand factors. It is common to assume that government consumption is biased toward
nontradables, implying a positive association between the real effective exchange rate and the
ratio of government consumption to output, expressed as a deviation from a trade-weighted
average across trading partners.
In medium-run equilibrium, intertemporal budget balance implies that net creditor economies
will tend to run trade de?cits, while net debtor economies will tend to run trade surpluses. To
induce the necessary expenditure switching, economies running trade de?cits will tend to have
relatively overvalued currencies in real effective terms, while economies running trade surpluses
will tend to have relatively undervalued currencies. This suggests a positive association between
the real effective exchange rate and the ratio of the NFA position to output.
External sustainability approach
Whether an economy is a net foreign creditor or debtor depends on accumulated net capital
?ows. Private net capital ?ows have a tendency to equalize the marginal product of capital
across economies, while public net capital ?ows may arise independently of such rate of return
considerations.
Within the framework of neoclassical growth models, the marginal product of capital is
increasing in the productivity with which inputs are combined to produce output, and is
decreasing in the abundance of capital relative to other inputs. This suggests a negative
association of the ratio of the NFA position to output with output per worker, and a positive
association with the ratio of the retirement age population to the working age population.
Corresponding author
Hali Edison can be contacted at: [email protected]
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doc_613664950.pdf
The purpose of this paper is to assess the level of the real effective exchange rate in
Australia and New Zealand
Journal of Financial Economic Policy
Exchange rate assessments for Australia and New Zealand
Hali Edison Francis Vitek
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To cite this document:
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Financial Economic Policy, Vol. 1 Iss 2 pp. 155 - 176
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Exchange rate assessments for
Australia and New Zealand
Hali Edison and Francis Vitek
International Monetary Fund, Washington, DC, USA
Abstract
Purpose – The purpose of this paper is to assess the level of the real effective exchange rate in
Australia and New Zealand.
Design/methodology/approach – The paper describes three empirical models commonly used to
conduct exchange rate assessments and applies them to data for Australia and New Zealand.
Findings – The baseline results using data and medium-term projections, available as of October
2008, suggest that the Australian and New Zealand dollar were broadly in line with fundamentals, but
with a wide variation across models. A battery of sensitivity tests illustrates that altering the
underlying assumptions can yield substantially different assessments. The results are particularly
sensitive to the choice of assessment horizon, the set of economies included in the sample, medium-term
forecasts, and the exchange rate reference period.
Originality/value – The paper provides an assessment of the exchange rates in Australia and
New Zealand.
Keywords Exchange rates, Macroeconomics, Australia, New Zealand
Paper type Research paper
I. Introduction
An integral part of the Fund’s mandate is the close monitoring and careful evaluation of
exchange rates of its members. As a result, the Fund has developed a framework for
assessing exchange rates. As part of this mandate, the International Monetary Fund
(IMF) Consultative Group on Exchange Rate Issues (CGER) has developed models and
provided assessments for a number of advanced and emerging market economies with
the aim to inform country-speci?c surveillance[1].
Australia and New Zealand are both small commodity-exporting economies with
reasonably long histories of independently ?oating exchange rates. From 2001 to
mid-2008, the currencies of both countries experienced large appreciations in nominal
and real effective terms. This together with persistent current account de?cits raised
concerns in some corners that strong currencies were adversely affecting their external
price competitiveness.
Against this background, the paper seeks to assess the level of the real effective
exchange rate in Australia and New Zealand. Several related papers have been written
that have used these methods that speci?cally focused on Australia and New Zealand,
including Brooks and Hargreaves (2000), MacDonald (2001), Dvornak et al. (2003), and
Wren-Lewis (2004). The contribution this paper makes is that it uses the latest
econometric techniques, modestly improving upon those used by the IMF CGER group.
In particular, three modi?cations to the conventional methods are introduced and
then tested. First, each model is estimated as both a standard unrestricted panel
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – F31, F32
Exchange rate
assessments
155
Journal of Financial Economic Policy
Vol. 1 No. 2, 2009
pp. 155-176
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576380911010263
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regression using ordinary least squares (OLS) and as a restricted panel regression
using the generalized method of moments (GMM). Second, each model is estimated
using a large sample of economies and then a narrower panel of economically similar
economies. Third, the exchange rate assessments are conducted at two time horizons:
the current time (within sample) and the medium-term (out of sample). In addition, a
battery of robustness tests are used to gather some insights into the sensitivity of the
results to changes in various assumptions.
Several useful lessons can be drawn from this study. Econometric models used for
exchange rate assessments offer some guidance in systematically analyzing the data.
However, the models tend to offer con?icting results and are highly uncertain,
requiring further investigation[2]. The results suggest that these models, while useful
as a diagnostic tool, must be complemented with more standard country surveillance in
the context of the Article IV and cannot substitute for such surveillance.
The organization of this paper is as follows. The next section provides background
information on exchange rate developments for Australia and New Zealand. Section III
presents the estimation results for the three empirical models. Section IV applies these
results to exchange rate assessments for Australia and New Zealand and considers a
battery of robustness tests. Section V concludes.
II. Stylized facts on real exchange rate trends
In recent years up until the middle of 2008, the Australian and New Zealand currencies
had appreciated signi?cantly in nominal and real effective terms (Figures 1 and 2,
panel (a)). From 2001 to mid-2008, the Australian dollar in nominal effective terms
appreciated by more than 30 percent, while the New Zealand dollar appreciated by
about 35 percent. In real effective terms, both currencies appreciated by over 30
percent. The difference between nominal and real effective exchanges rates re?ect
accumulated in?ation rate differentials relative to trading partners. Since mid-2008,
both the Australian and New Zealand dollars have depreciated signi?cantly[3].
These real effective exchange rate movements have been driven in part by
movements in real effective interest rate differentials (Figures 1 and 2, panel (b)). This
relationship recently appears stronger at shorter horizons than at longer horizons,
which likely re?ects the emergence of the carry trade. This global search for yield has
targeted Australian and New Zealand dollar assets not only because of high interest
rate spreads, but also because these spreads seemed likely to persist.
The strength of these currencies has also been supported by higher terms of trade as
both countries are relatively large exporters of primary commodities (Figures 1 and 2,
panel (c)). Australia has seen a sharp increase in its terms of trade as a result of
increasing coal, iron ore, and other mineral prices, while New Zealand has experienced
an increase in dairy prices. The relationship between the terms of trade and the
exchange rate broke down around 1999 for a couple of years, but has resumed with the
run up of commodity prices. Since mid-2008, global commodity prices have declined.
The balance of payments for Australia and New Zealand have widened as their
exchange rates strengthened. The trade balances of Australia and New Zealand have
declined, reducing their current account balances (Figures 1 and 2, panel (d)). Since
2001, the trade balance of New Zealand has deteriorated from a surplus and its current
account de?cit has widened considerably.
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In assessing the appropriate level of the real effective exchange rate, a common ?rst step
is to compare the prevailing level of the real effective exchange rate to some historical
average. Such a comparison assumes that the real exchange rate should remain
relatively constant over time, and that the nominal effective exchange rate should move
in line with relative price levels, which is consistent with purchasing power parity (PPP)
(Rogoff, 1996). This is a useful point of departure for studying the appropriate level of
the exchange rate. As of October 2008, both countries’ real effective exchange rate is
above its historical level (Figures 1 and 2, panel (e)). This result emerges using either the
IMF or the central bank’s measure of the real effective exchange rate.
Figure 1.
Australia: real
exchange rate trends
Real and nominal effective exchange rate trends
Real exchange rate and current account and trade balance
80
100
120
140
(a)
(b)
(c)
(d)
(e)
(f )
80
100
120
140
Nominal effective exchange rate
Real effective exchange rate
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–8
–6
–4
–2
0
2
4
6
Real effective exchange rate (lhs)
Ratio of trade balance to GDP (rhs)
Ratio of current account balance to GDP (rhs)
Real exchange rate and real interest differentials
Real exchange rates and historical average
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–4
–2
0
2
4
6
8
10
Real exchange rate, 2,000 = 100 (lhs)
Short-term real interest rate differential (rhs)
Long-term real interest rate differential (rhs)
80
100
120
140
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
80
100
120
140
TWI (RBA)
IMF
Average
Real exchange rate and terms of trade
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
40
60
80
100
120
140
Real exchange rate, 2,000 = 100 (lhs)
Terms of trade for goods and services (rhs)
Terms of trade for goods (rhs)
10
20
30
40
50
60
70
80
90
Jul-07 Oct-07 Jan-08 Apr-08 Jul-08 Oct-08
0.6
0.7
0.8
0.9
1.0
1.1
Vix volatility index (lhs)
Nominal AUD/USD exchange rate (rhs)
Source: IMF staff estimates
Recent movements in the exchange rate and the VIX
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However, most exchange rate assessments tend to be geared toward evaluating the
consistency of the exchange rate with economic fundamentals over the medium to
longer run. Those factors that have the most in?uence on exchange rates over the short
run are not necessarily the same ones that will exercise the most in?uence over the long
term. Nevertheless, the starting point for the assessment is important. In the past few
months with the global ?nancial turmoil, there has been considerable movement in
exchange rates, as illustrated by the movements in US dollar bilateral exchange
rates for Australia and New Zealand and the VIX, a measure of market volatility
Figure 2.
New Zealand: real
exchange rate trends
Real and nominal effective exchange rate trends Real exchange rate and current account and trade balance
80
100
120
140
1985 1987 1989 1991 1993 1995 1997
(a) (d)
(b) (e)
(c) (f)
1999 2001 2003 2005 2007
80
100
120
140
Nominal effective exchange rate
Real effective exchange rate
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–10
–8
–6
–4
–2
0
2
4
6
8
Real effective exchange rate (lhs)
Ratio of trade balance to GDP (rhs)
Ratio current account balance to GDP (rhs)
Real exchange rate and real interest differentials Real exchange rates and historical average
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
–4
–2
0
2
4
6
8
Real exchange rate, 2,000 = 100 (lhs)
Short-term real interest rate differential (rhs)
Long-term real interest rate differential (rhs)
80
100
120
140
160
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
80
100
120
140
160
TWI-5 (RBNZ)
IMF
Average
Real exchange rate and terms of trade Recent movements in the exchange rate and the VIX
80
100
120
140
160
1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007
80
90
100
110
120
130
140
Real exchange rate, 2,000 = 100 (lhs)
Terms of trade for goods and services (rhs)
Terms of trade for goods (rhs)
10
20
30
40
50
60
70
80
90
Jul-07 Oct-07 Jan-08 Apr-08 Jul-08 Oct-08
0.5
0.6
0.7
0.8
0.9
1.0
Vix Volatility Index (lhs)
Nominal NZL/US exchange rate (rhs)
Source: IMF staff estimates
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(Figures 1 and 2, panel (f)). This large increase in volatility has made it more dif?cult to
conduct exchange rate assessments.
III. The empirical models[4]
Country coverage and econometric methodology
The estimation dataset consists of 55 industrial and emerging market economies and
covers the period 1973-2007. For each empirical model, two country groupings are
considered: a 55-country sample (wide panel) and a nine-country sample (narrow
panel). (A detailed description of this panel data set is provided in Appendix 1 and the
theoretical foundation of the three approaches can be found in Appendix 2.) The wide
panel spans economies that contribute signi?cantly to global trade, because an
economy with a large global presence will have greater effects on the exchange rates of
other countries. This wide country coverage allows one to exploit the substantial
cross-country variation among the advanced and emerging market economies in the
sample. However, the wide panel also poses possible estimation problems related to
imposing cross-economy equality restrictions on slope coef?cients[5]. In recognition of
this problem, a narrow panel of nine structurally similar economies is also
considered[6]. The countries are all relatively small and open economies that are
relatively large exporters of primary commodities.
A common econometric methodology has been applied to derive the most suitable
speci?cation. The models are ?rst estimated by OLS and then by the GMM, using
lagged explanatory variables as instruments, where appropriate. For the GMM model,
a general to speci?c model speci?cation strategy is used to derive a parsimonious
speci?cation. Both estimation techniques correct for cross-section speci?c
unconditional heteroskedasticity and contemporaneous correlation of unknown form.
A. The macroeconomic balance approach
The macroeconomic balance (MB) approach focuses on the requirement for achieving
internal and external balance. In practice, it involves assessing the change in the real
effective exchange rate that is needed to close the gap between the “underlying”
current account balance of a country and its “equilibrium” level. This approach
comprises three steps:
(1) Estimating the equilibrium current account balance (current account norm).
(2) Determining the “cyclically adjusted” or underlying current account balance[7].
(3) Calculating the exchange rate adjustment that is required to close the gap
between the underlying and equilibrium current account balances, based on the
estimated elasticity of the current account with respect to the real effective
exchange rate.
The discussion below focuses on the estimation and interpretation of the equilibrium
current account balance.
The estimated medium-run equilibrium value of the current account balance is
derived from a panel regression model:
ca
i;t
¼ b
0;i
þb
T
x
i;t
þ 1
i;t
; ð1Þ
where b
0;i
denotes an economy speci?c ?xed effect, and 1
i;t
, Nð0; s
2
i
Þ. The variable
ca
i;t
denotes the ratio of the current account balance to gross national product (GDP),
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while x
i;t
denotes a vector of explanatory variables. These variables include the ratio
of the retirement age population to the working age population, the growth rate of the
population, the logarithm of income per capita expressed in terms of purchasing power,
the growth rate of income per capita expressed in terms of purchasing power, the ratio
of the oil trade balance to GDP, the ratio of the ?scal balance to GDP, and the lagged
ratio of the net foreign assets (NFA) position to GDP.
The estimates of equation (1) are broadly similar across econometric techniques and
country coverage (Table I). The estimated coef?cients are statistically signi?cant and
have the expected sign and plausible magnitudes:
.
The coef?cient on the dependency ratio is negative, indicating that a higher
dependency ratio reduces the current account balance. A 1 percent point increase
in the dependency ratio relative to trading partners would lower the current
account norm by about 0.5 percent of GDP.
.
The coef?cient on population growth is negative, but the size varies widely
depending on the estimation method. A 1 percent point increase in population
growth relative to trading partners would lead to a worsening of the current
account norm by 1-4 percent of GDP[8].
.
The coef?cient on higher relative income growth is negative. A 1 percent point
increase in relative income growth would reduce the current account norm by 0.4
percent of GDP.
.
The coef?cient on the oil trade balance is positive. For Australia and New
Zealand, which are net oil importers, this suggests that a widening of the oil
trade de?cit would imply a decrease in the current account norm.
.
The coef?cient on the initial NFA position is positive and quite small. An
increase in NFA of 10 percent of GDP would increase the current account norm
by about 0.01 percent of GDP.
The point estimates are decomposed into time-varying contributions of each of the
explanatory variables, allowing one to give a country-speci?c interpretation to the
equation (Figure 3). Using the wide panel GMM results, we see that the equilibrium
current account de?cits have been driven by a set of common factors[9]. In both
Wide panel Narrow panel
OLS GMM OLS GMM
Relative old-age dependency 20.62
* * *
20.58
* * *
20.66
* * *
20.74
* * *
Relative population growth 20.79
* *
24.26
* *
0.49 21.14
Relative income 20.09
* * *
– 0.07 0.06
Relative income growth 20.02
* * *
20.38
* *
0.38
* * *
–
Oil trade balance 0.73
* * *
0.88
* * *
1.26
* * *
1.31
* * *
Relative ?scal balance 0.17
* * *
0.08
* * *
0.18
* *
0.15
* *
Initial net foreign assets 0.001
* *
0.001
* *
20.002 0.001
Observations 735 714 174 169
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0.73 0.67 0.76 0.78
Notes: Statistical signi?cant at the
*
10%,
* *
5%, and
* * *
1% levels; dependent variable: ratio of
current account balance to output
Table I.
Estimation results for the
MB approach
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countries, high relative population growth has contributed to their large current
account de?cits. Both countries have relatively low dependency ratios that have
supported their current account de?cits. In addition, relatively low income growth has
reduced private investment, which has reduced their equilibrium current account
de?cits. Finally, oil trade de?cits have exacerbated their equilibrium current account
de?cits.
B. The equilibrium real exchange rate approach
The equilibrium real exchange rate (ERER) approach models the real effective
exchange rate as a function of factors that cause temporary but persistent deviations
from long-run PPP. As discussed in a survey paper by Froot and Rogoff (1995), a
variety of theoretical models predict the existence of such factors. The model takes the
form:
ln
Q
i;t
¼ b
0;i
þb
T
x
i;t
þ 1
i;t
; ð2Þ
where b
0;i
denotes an economy speci?c ?xed effect, and 1
i;t
, Nð0; s
2
i
Þ. The dependent
variable denoted as
Q
i;t
is the real effective exchange rate, while x
i;t
denotes a vector of
explanatory variables. These variables include the logarithm of the terms of trade, the
logarithm of output per worker expressed in terms of purchasing power, the ratio of
government consumption to GDP, and the ratio of the NFA position to GDP.
The ?rst column in Table II reports the estimated equilibrium long-run
relationship between the real exchange and the above mentioned set of explanatory
variables. The speci?cation in column 2 provides a parsimonious set of coef?cients,
which have been estimated using GMM. The coef?cients on all three explanatory
Figure 3.
MB approach: estimated
contribution – level and
change in percent of GDP
Australia - level
–8
–6
–4
–2
0
2
1997 1999 2001 2003 2005 2007
Fixed effect Relative old age dependency
Relative population growth Relative income growth
Oil trade balance Initial net foreign assets
Fiscal balance Actual current account
Predicted current account
New Zealand - level
–12
–8
–4
0
4
1997 1999 2001 2003 2005 2007
Fixed effect Relative old age dependency
Relative population growth Relative income growth
Oil trade balance Initial net foreign assets
Fiscal balance Actual current account
Predicted current account
Australia - change
–3
–2
–1
0
1
2
3
1997 1999 2001 2003 2005 2007
New Zealand - change
–6
–4
–2
0
2
4
1997 1999 2001 2003 2005 2007
Relative old age dependency Relative population growth
Relative income growth Oil trade balance
Initial net foreign assets Fiscal balance
Actual current account Predicted current account
Source: IMF staff estimates
Relative old age dependency Relative population growth
Relative income growth Oil trade balance
Initial net foreign assets Fiscal balance
Actual current account Predicted current account
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variables are positive, so that an increase relative to trading partners of each variable
would tend to lead to an appreciation of a country’s equilibrium exchange rate.
Looking more closely at the decomposition of the model for Australia and New
Zealand highlights the positive effect from the terms of trade in the recent period
(Figure 4). The improvement in the terms of trade contributed positively to the
appreciation of the Australian dollar since 1999. In addition, high relative productivity
and government consumption also contributed to the strength of the Australian dollar.
In contrast, for New Zealand, low relative productivity has contributed negatively to
the equilibrium real effective exchange rate.
Wide panel Narrow panel
OLS GMM OLS GMM
Terms of trade 0.33
* * *
0.41
* * *
0.34
* * *
20.39
* * *
Relative productivity 0.15 0.26
* * *
20.42
* *
–
Relative government consumption 0.38
* * *
1.76
* * *
3.54 –
Initial net foreign assets 0.00
* *
– 20.03
* * *
–
Observations 724 1,006 165 238
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Notes: Statistical signi?cant at the
*
10%,
* *
5%, and
* * *
10% levels; dependent variable: real
effective exchange rate
Table II.
Estimation results for the
ERER approach
Figure 4.
ERER approach:
estimated contribution –
level and change
Australia - level
–0.2
0.0
0.2
0.4
1997 1999 2001 2003 2005 2007
Fixed effect Relative government consumption
Relative productivity Terms of trade
Predicted real effective exchange rate Actual real effective exchange rate
New Zealand - level
–0.2
0.0
0.2
0.4
1997 1999 2001 2003 2005 2007
Terms of trade
Relative productivity
Relative government consumption
Fixed effect
Actual real effective exchange
rate
Predicted real effective exchange rate
Australia - change
–0.10
–0.05
0.00
0.05
0.10
0.15
1997 1999 2001 2003 2005 2007
Relative government consumption Relative productivity
Terms of trade Predicted real effective exchange
rate Actual real effective exchange rate
New Zealand - change
–0.15
–0.10
–0.05
0.00
0.05
0.10
0.15
1997 1999 2001 2003 2005 2007
Terms of trade
Relative productivity
Relative government consumption
Actual real effective exchange rate
Predicted real effective exchange rate
Source: IMF staff estimates
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C. The external sustainability approach
The third approach, the external sustainability approach (ES), focuses on the
relationship between the sustainability of a country’s external stock and its current
account ?ow, and the real effective exchange rate. Like the MB approach, it involves
three steps:
(1) Estimating the ratio of the current account balance to GDP that would stabilize
the NFA position at a given benchmark value.
(2) Determining the level of the current account balance expected to prevail over
the medium term.
(3) Assessing the adjustment in the real effective exchange rate that is needed to
close the gap between the medium-term current account and the
NFA-stabilizing current account balance.
The medium-run equilibrium value of the ratio of the NFA position to GDP is modeled
from an intertemporal perspective.
The benchmark level of the NFAposition is the key element in the ES approach. It is
common to calibrate this benchmark level to match the most recently observed value of
the NFA position, or some measure of the central tendency of its recently observed
values. Alternatively, the medium-run equilibrium value of the NFA position is
modeled in a panel regression taking the form:
nfa
i;t
¼ b
0;i
þb
T
x
i;t
þ 1
i;t
ð3Þ
where b
0;i
denotes an economy speci?c ?xed effect, and 1
i;t
, Nð0; s
2
i
Þ. As speci?ed,
nfa
i;t
denotes the ratio of the NFA position to GDP, while x
i;t
denotes a vector of
explanatory variables. These include the logarithm of output per worker expressed in
terms of purchasing power, the ratio of the retirement age population to the working
age population, and the ratio of the government net asset position to GDP.
Table III reports the estimation results for the ratio of the NFAposition to GDP. The
results for the wide panel suggest that higher relative productivity would reduce the
NFA position, while a higher dependency ratio and government net asset position
would increase the NFA position. The results for the narrow panel are mixed; only the
coef?cient on the government net asset position is signi?cant.
Looking more closely at the results for Australia and New Zealand, reveals that
?xed effects account for the majority of the estimated equilibrium net foreign debt
Wide panel Narrow panel
OLS GMM OLS GMM
Relative productivity 20.34
* * *
20.39
* * *
20.12 –
Relative old-age dependency 0.69
* *
– 20.95 –
Government net assets 20.21
* * *
0.17
* * *
0.53
* * *
0.58
* * *
Observations 527 514 159 198
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0.90 0.67 0.71 0.69
Notes: Statistical signi?cant at the
*
10%,
* *
5%, and
* * *
1% levels; dependent variable: ratio of net
foreign assets to output
Table III.
Estimation results
for the ES approach
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positions (Figure 5). This result suggests that relevant explanatory variables that vary
signi?cantly across economies but not over time have been omitted from the panel
regression model.
IV. Exchange rate assessments
A. Baseline results
For the purposes of comparability, we develop a baseline where each approach is
applied to Australian and New Zealand data. Because exchange rates are notoriously
dif?cult to forecast in the short run, the medium-run horizon (2013) was deemed the
best for the construction of the baseline benchmark. Also, to construct the baseline we
use the GMM model estimates for the sample of 55 countries. To complete this exercise,
the medium-term forecast of the explanatory variables is based on the October 2008
World Economic Outlook (WEO), unless otherwise indicated.
For the MB and ES approach, the assessments are based on the required real
exchange rate adjustment that would close the gap between the estimated current
account norm and the underlying (projected) current account based on the WEO
forecasts. The magnitude of the exchange rate adjustment is derived by dividing the
current account gap by the semi-elasticity of the current account with respect to the real
effective exchange rate. The notion is that a country more open to trade will be able to
close its current account gap with less real exchange rate adjustment. For the ERER
approach, the magnitude of the exchange rate adjustment is calculated directly as the
difference between the country’s real effective exchange rate and its estimated
equilibrium value.
Figure 5.
ES approach:
estimated contribution –
level and change
Australia - level
–70
–60
–50
–40
–30
–20
–10
0
10
1997 1999 2001 2003 2005 2007
Fixed effect Relative productivity
Government net foreign assets Actual net foreign assets
Predicted net foreign assets
New Zealand - level
–100
–80
–60
–40
–20
0
20
1997 1999 2001 2003 2005 2007
Fixed effect Relative productivity
Government net foreign assets Actual net foreign assets
Predicted net foreign assets
Australia - change
–4
–2
0
2
4
6
1997 1999 2001 2003 2005 2007
Relative productivity
Actual net foreign assets
Government net foreign assets
Predicted net foreign assets
New Zealand - change
–4
–2
0
2
4
1997 1999 2001 2003 2005 2007
–30
–20
–10
0
10
20
Relative productivity
Predicted net foreign assets
Government net foreign assets
Actual net foreign assets (rhs)
Source: IMF staff estimates
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The baseline estimates for the level of the exchange rate are wide-ranging, varying
considerably across models. For Australia, the ERER model indicates the dollar is 18
percent undervalued while the ES model produces estimates that suggest the dollar to
be overvalued by 17 percent[10]. The estimates from the MB model fall in the middle, at
3 percent overvalued. For the New Zealand dollar the baseline estimates are similarly
spread, going from 7 percent undervalued (ERER) to 11 percent overvalued (ES)
(Table IV). These results are based on the assumption that the underlying current
account de?cit for Australia is 5.0 percent of GDP and 5.6 percent of GDP for New
Zealand (i.e. the WEO forecast for 2013). For the MB and ES approaches, the elasticities
are taken from the IMF CGER methodology (Lee et al., 2008).
Not only are these point estimates wide ranging across models, but there is also a
great deal of uncertainty for each model. Figure 6 shows both the point estimate
(depicted with bars) and the 90 percent con?dence intervals, which capture model
uncertainty[11]. For Australia, the estimate ranges from 30 percent undervalued to
Current account
balance
Norm Forecast Real effective exchange rate
Australia
a
Macroeconomic balance 24.5 25.0 2.8
Equilibrium real exchange – – 217.8
External sustainability rate 22.4 25.0 16.7
New Zealand
b
Macroeconomic balance 25.2 25.6 1.6
Equilibrium real exchange rate – – 27.0
External sustainability 23.3 25.6 11.1
Notes: All ?gures are based on ?ve year conditional forecasts, and are expressed in percent;
a
estimates are based on a medium-run semi-elasticity of the ratio of the current account balance to
output with respect to the real effective exchange rate of 20.16, a net foreign asset-to-GDP norm of
249.5, and a medium-run equilibrium output growth rate of 5.3 percent;
b
estimates are based on a
medium-run semi-elasticity of the ratio of the current account balance to output with respect to the real
effective exchange rate of 20.21, a net foreign asset to GDP norm of 271.2, and a medium-run
equilibrium output growth rate of 4.8 percent
Source: IMF staff estimates
Table IV.
Baseline result:
quantitative exchange
rate assessment
Figure 6.
Con?dence intervals
The model yields wide confidence bands for Australia... ...and bands are even wider for some models for New Zealand
Australia: 90 percent confidence intervals
–35
–30
–25
–20
–15
–10
–5
0
5
10
15
20
25
30
MB ERER ES
–35
–30
–25
–20
–15
–10
–5
0
5
10
15
20
25
30
–25
–20
–15
–10
–5
5
0
10
15
20
25
30
35
New Zealand: 90 pecent confidence intervals
–25
–20
–15
–10
–5
0
5
10
15
20
25
30
35
MB ERER ES
Source: IMF staff estimates
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25 percent overvalued. For New Zealand, the range is almost as wide, spanning
from 222 percent undervalued to 20 percent overvalued. Note that these con?dence
intervals may overstate the uncertainty surrounding the exchange rate overvaluation
estimates, as they are in?ated by model misspeci?cation[12].
B. Robustness tests
Given the large differences in the baseline results and the model uncertainty, there are
serious questions regarding the robustness of estimates of overvaluation. While the
baseline construction appears somewhat arbitrary, it was chosen because it broadly
re?ected the assumptions made when these models are applied at the IMF. To gain a
better understanding of what lies behind these results, we consider a battery of
robustness tests. The remainder of this section considers alternative speci?cations by
changing the underlying WEO forecasts and reference exchange rate, auxiliary
parameters, assessment horizon, country sample, and estimation method.
Reference period. The medium-term forecast used to derive the explanatory
variables and the reference period for the exchange rate may have a large impact on the
assessment, especially during turbulent times. Since June 2008, there has been a
considerable downgrading of the global outlook and large changes in the WEO
forecasts. Over this period, the Australian and New Zealand dollars have come under
substantial downward pressure as commodity prices eased and interest rate
differentials narrowed. At the end of October, the Australian dollar was more than 30
percent off its mid-year peak in nominal effective terms and the New Zealand dollar
was nearly 20 percent lower than mid-year. These large moves make an exchange rate
assessment ephemeral.
Against this background, we illustrate how rapidly the exchange rate assessment
can change over a short period of time and how the different models tend to re?ect
these changes. Three different WEO forecasts (June, August, and October) with
corresponding reference exchange rates are used to compute the degree of
overvaluation (Table V). For example, for Australia the June MB approach indicated
that the dollar was overvalued by 8 percent, while in October the gap was 3 percent.
Over the same period, the ERER model showed a large swing, moving from being
Assessment date MB 2013 ERER 2013 ES 2013
Australia
June 2008
a
8.1 8 18.4
August 2008
b
5.0 3.3 21.4
October 2008
c
2.8 217.8 16.7
New Zealand
June 2008
a
13.9 12.2 19.1
August 2008
b
6.7 1.5 19.0
October 2008
c
1.6 27.0 11.1
Notes: Results reported are estimated for the sample of 55 countries using GMM;
a
based on Spring
2008 WEO and reference period for exchange rate is average for 2007;
b
Based on Spring 2008 WEO
and reference period for exchange rate is end August 2008;
c
based on October 2008 WEOand reference
period for exchange rate is end October 2008
Source: Fund staff estimates
Table V.
Sensitivity: reference data
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overvalued by 8 percent in June to being undervalued by 18 percent in October. The
results for New Zealand also show a narrowing overvaluation or a move to being
undervalued depending on which model is being used. In contrast, the ES model seems
to be less affected by these changes and furthermore consistently projects a greater
overvaluation than the other models.
Auxiliary parameters. The degree of overvaluation also depends on the auxiliary
parameter assumptions. Below we consider the impact of key parameters for the MB
approach and ES approach.
MB approach: current account norms and trade elasticities. Two key parameters for
the MB approach are: the underlying current account projection and the medium-run
semi-elasticity of the ratio of the current account balance to GDP with respect to the
real effective exchange rate (trade elasticity). A larger current account de?cit creates a
large gap between the projection and the norm, which requires a larger exchange rate
adjustment. For a given current account gap, a larger trade elasticity reduces the
exchange rate overvaluation.
Using the baseline as a point of departure, plausible sensitivity analysis suggests
that the Australian exchange rate assessment ranges between an undervaluation of 5
percent to an overvaluation of 13 percent. For New Zealand, the range is from an
undervaluation of 4 percent to an overvaluation of 8 percent (Table VI). These results
underscore the uncertainty surrounding the equilibrium level of the real effective
exchange rate[13].
ES approach: NFA norms and nominal growth assumption. The ES approach relies
on an intertemporal budget constraint that requires the present value of future trade
surpluses be suf?cient to pay for the country’s outstanding external liabilities. Two
key parameters in this approach are the NFA norm and the rate of growth of the
economy. The current account norm consistent with stabilizing NFAs at a given level
is approximately proportional to this growth rate. Thus, for net debtor countries,
higher growth rates are associated with higher equilibrium current account de?cits.
Taking this one step further, this will tend to reduce the current account gap, which
will lead to a smaller overvaluation of the exchange rate.
The benchmark level of the NFA position is the key in the ES approach. It is
common to calibrate this benchmark level to the most recently observed value of
the NFA position, or to some measure of the central tendency of its recently
Elasticity CA/GDP projection
a
Australia 24.0 25.0 26.0
20.11 25.2 3.9 13.0
20.16 23.6 2.8 8.9
20.21 22.7 2.0 6.8
New Zealand 24.6 25.6 26.6
20.16 24.1 2.1 8.4
20.21 23.1 1.6 6.4
20.26 22.5 1.3 5.2
Notes: REER overvaluation is expressed in percent;
a
projection of the underlying CA/GDP in 2013
Source: IMF staff estimates
Table VI.
Sensitivity analysis: MB
Approach – CA/GDP
projection and trade
elasticity
Exchange rate
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observed values. The baseline estimates use model derived NFA estimates. For
comparison, we also compute the degree of overvaluation using the end-2007 NFA to
GDP ratio. For both Australia and New Zealand, the model estimates produce
relatively low NFA positions, therefore replacing those values with end-2007 lifts the
NFA norms and as a consequence raises the current account norm. This in turn
reduces the estimates of overvaluation (Table VII).
To illustrate the sensitivity of the assessment to growth rates, we use the baseline as
the point of departure and recomputed the degree of overvaluation assuming a 1
percent point higher and lower growth rate. The degree of overvaluation clearly
changes as we vary the growth rate of the economy. For both countries, a 1 percent
point change in the growth rate alters the estimate of overvaluation by nearly 3 percent
points (Table VIII).
Assessment horizon. The time horizon that is used to evaluate the consistency of the
exchange rate with economic fundamentals is also another important factor. For the
baseline, the adjustment was calculated based on medium-term fundamentals ?ve
years hence. It is assumed that at this point in time, the economy is operating at its
potential and therefore one is able to abstract from cyclical and short-term in?uences
Baseline – estimated Alternative – observed 2007
Australia
a
NFA norm 247.4 261.9
Current account norm 22.4 23.1
Degree of misalignment 16.7 12.0
New Zealand
b
NFA norm 271.2 287.2
Current account norm 23.3 24.0
Degree of misalignment 11.1 7.6
Notes: Results reported are at time t þ 5, using GMM estimator, 55 countries;
a
for Australia, the
baseline NFA is estimated from the model (Table III), the alternative NFA measure is observed at end
2007, the growth rate is 5.3;
b
for NewZealand, the baseline NFAis estimated fromthe model (Table III),
the alternative NFA measure is observed at end 2007, the growth rate is 4.8
Source: IMF staff estimates
Table VII.
Sensitivity: external
sustanability – NFA
norms
Lower growth Baseline higher growth
Australia
a
Current account norm 22.0 22.4 22.8
Degree of misalignment 19.5 16.7 13.9
New Zealand
b
Current account norm 22.6 23.3 23.9
Degree of misalignment 14.3 11.1 8.0
Notes: Results reported are at time t þ 5, using GMM estimator, 55 countries;
a
For Australia, the
baseline growth is 5.3 percent, low growth is 4.3 percent, and high growth is 6.3 percent;
b
for New
Zealand, the baseline growth is 4.8 percent, low growth is 3.8 percent, and high growth is 5.8 percent
Source: IMF staff estimates
Table VIII.
Sensitivity: external
sustanability – growth
rates
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on the exchange rate. However, some argue that the assessment should also be made
based on the current value of fundamentals.
In the cases of Australia and New Zealand, exchange rate assessments taken at the
current horizon (2008) tend to suggest larger overvaluation, but this result varies
across models and by country (Table IX). The MB model for Australia suggests the
size of overvaluation is broadly similar across the two horizons. In contrast, the ERER
model suggests that the exchange rate is relatively close to its equilibrium level in the
short run, but in the medium-term baseline estimates suggested the exchange rate was
nearly 18 percent undervalued. For New Zealand, the size of overvaluation is larger for
all models for the current period. Once again, for both countries, the ES model appears
to be less sensitive to changes in the time horizon and tends to register the largest
overvaluation.
Country coverage. The set of economies that are included in the sample also
in?uences the assessment. Two panel estimates for each model are considered, varying
the country coverage. In contrast to the baseline, which uses the wider sample, the
narrow sample tends to produce smaller overvaluation estimates for Australia.
The results are mixed for NewZealand (Table X). The difference re?ects the changes in
the selected model speci?cations and coef?cient estimates. Consistent with earlier
robustness tests, the ES model tends to report large overvaluations.
Estimation method. For comparison to other results, the models were also estimated
by OLS. In general, the OLS estimates tend to be higher than those based on GMM
2008 2013
Australia
Macroeconomic balance 7.8 2.8
Equilibrium real exchange rate 0.5 217.8
External sustainability 24.2 16.7
New Zealand
Macroeconomic balance 16.8 1.6
Equilibrium real exchange rate 10.7 27.0
External sustainability 23.4 11.1
Source: IMF staff estimates
Table IX.
Sensitivity:
assessment period
Wide sample
a
Narrow sample
b
Australia
Macroeconomic balance 2.8 0.0
Equilibrium real exchange rate 217.8 226.9
External sustainability 16.7 14.8
New Zealand
Macroeconomic balance 1.6 21.4
Equilibrium real exchange rate 27.0 28.4
External sustainability 11.1 12.9
Notes: Results reported are at time t þ 5;
a
sample 55 countries;
b
sample nine countries
Source: IMF staff estimates
Table X.
Sensitivity:
country coverage
Exchange rate
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estimates (Table XI). For example, for the MB model, the OLS estimate for Australia
suggests a 9 percent point adjustment where as the GMM estimates suggest a
2.8 percent point adjustment. However, the size of the difference varies considerably by
model.
In sum, the quantitative assessments are sensitive to variations in assumptions. For
Australia and New Zealand, small changes in the baseline can lead to substantial
differences in exchange rate overvaluation estimates (Figure 7).
V. Concluding remarks
Drawing on existing literature, this paper has estimated three commonly used
equilibrium exchange rate models and applied them to Australia and New Zealand.
The baseline results used data as of October 2008 and suggest that the Australian and
New Zealand dollars may be misaligned, but the direction of that misalignment is
unclear. The ERER model suggests undervaluation for both currencies, while the MB
model results imply the currencies are broadly in line with fundamentals. In contrast,
the ES model results indicate that both currencies are overvalued.
As a result, numerical exchange rate assessments need to be treated with caution as
the size of overvaluation, even under the baseline, can give very imprecise answers.
There are a number of potential factors that can create this uncertainty, which
we investigated. For example, the empirical relationships of the different models were
estimated for a large pool of heterogeneous countries and there could be large
OLS GMM
Australia
Macroeconomic balance 9.0 2.8
Equilibrium real exchange rate 26.2 27.0
External sustainability 16.4 16.7
New Zealand
Macroeconomic balance 3.7 1.6
Equilibrium real exchange rate 26.2 27.0
External sustainability 11.0 11.1
Note:
a
Results reported are at time t þ 5 and estimated for the sample of 55 countries
Source: IMF staff estimates
Table XI.
Sensitivity: estimation
method
a
Figure 7.
Quantitative exchange
rate assessment: summary
Australia
–30
–20
–10
0
10
20
30
MB ERER ES
P
e
r
c
e
n
t
Baseline Reference period Assessment horizon
Country coverage Estimation method
Baseline Reference period Assessment horizon
Country coverage Estimation method
New Zealand
–20
–10
0
10
20
30
MB ERER ES
P
e
r
c
e
n
t
Source: IMF staff estimates
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differences between the resulting “average” country and Australia or New Zealand.
This was partially addressed in the paper by reestimating the model over a narrow
more homogenous panel of countries, but this too has its shortcomings.
The lesson drawn from this exercise is simple: there is a great deal of weakness to
numerical exchange rate assessments and they should be viewed as a diagnostic tool
and not as the golden yardstick from which to judge the appropriate level of the
exchange rate.
Notes
1. Several papers have been written in this area by Lee et al. (2008) and Isard (2007) containing
summaries of the methodologies that underpin the analysis and references to earlier IMF
literature.
2. Similar conclusions emerged in Dunaway et al. (2006).
3. The 2008 data included in these ?gures are mostly based on data from October.
4. See Appendix 2 for the theoretical foundations of these models.
5. The imposition of cross-economy equality restrictions on slope coef?cients generally yields
asymptotic variance reductions at the cost of asymptotic bias increases. It is ambiguous
whether conditioning estimation on a wide panel of structurally dissimilar economies or a
narrowpanel of structurally similar economies is optimal fromthe perspective of minimizing
asymptotic mean-squared error (Davidson and MacKinnon, 2004).
6. The economies considered are: Australia, Canada, Chile, Denmark, Finland, New Zealand,
Norway, South Africa, and Sweden.
7. In practice, the underlying current account is de?ned as the value of the current account that
would be observed at the prevailing real effective exchange rate if all countries were
operating at potential output (internal balance) and if the effects of past exchange rate
changes had been completely realized.
8. The size of the coef?cient is robust to changes in the estimation sample period.
9. The results for the narrow panel are broadly similar with some variation in the size of
coef?cient estimates, partly re?ecting lower degrees of freedom.
10. The ERER model uses a terms of trade projection that may not re?ect market expectations.
11. Projections for the ERER model are based on Table XII.
12. Modeling observed levels as a function only of the determinants of unobserved trend
components adds unobserved cyclical components to the residuals, increasing their
variances. If cyclical and trend components were jointly modeled within an unobserved
Terms of trade Relative productivity Relative government consumption
Australia
2008 1.21 1.25 1.00
2013 1.15 1.19 1.00
New Zealand
2008 1.19 0.80 1.01
2013 1.24 0.77 1.02
Note: ERER model: forecast of explanatory variables
Table XII.
Exchange rate
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components framework, then the variances of estimates of medium-run equilibrium values
would be reduced. Moreover, deviations of observed levels from estimated medium-run
equilibrium values could be explained in terms of cyclical factors.
13. These speci?c results need to be interpreted with caution because they have not been derived
by statistical methods and therefore it is not possible to assign any level of con?dence to
them.
14. Where appropriate, the explanatory variables for each approach are expressed as deviations
from trade-weighted averages across trading partners.
15. The derivation of this result assumes that the real effective exchange rate is GDP-based.
16. This bypasses separate measurement of tradables productivity and nontradables
productivity, expressed as deviations from trade-weighted average across trading partners.
This is desirable in practice, as the sectoral output and employment data required to construct
these explanatory variables are released with long delays for many economies, while the
distinction between tradables and nontradables sectors is somewhat arbitrary.
References
Balassa, B. (1964), “The purchasing power parity doctrine: a reappraisal”, Journal of Political
Economy, Vol. 72, pp. 584-96.
Barro, R. and Sala-i-Martin, X. (1999), Economic Growth, MIT Press, Cambridge, MA.
Brooks, A. and Hargreaves, D. (2000), “A macroeconomic balance measure of New Zealand’s
equilibrium exchange rate”, Discussion Paper No. 2000/09, Reserve Bank of New Zealand,
Wellington, available at:http://EconPapers.repec.org/RePEc:nzb:nzbdps:2000/09
Campa, J. and Goldberg, L. (2002), “Exchange rate pass-through into import prices: a macro or
micro phenomenon?”, Working Paper No. 9834, National Bureau of Economic Research,
Cambridge, MA.
Davidson, R. and MacKinnon, J. (2004), Econometric Theory and Methods, Oxford University
Press, New York, NY.
Dunaway, S., Leigh, L. and Li, Z. (2006), “How robust are estimates of equilibrium exchange
rates? The case of China”, Working Paper No. 06/220, International Monetary Fund,
Washington, DC.
Dvornak, N., Kohler, M. and Menzies, G. (2003), “Australia’s medium-run exchange rate:
a macroeconomic balance approach”, Discussion Paper No. 2003-03, Reserve Bank of
Australia, Sydney.
Froot, K. and Rogoff, K. (1995), “Perspectives on PPP and long-run real exchange rates”,
Handbook of International Economics, Vol. 3, pp. 1647-88.
Isard, P. (2007), “Equilibrium exchange rates: assessment methodologies”, Working Paper
No. 07/296, International Monetary Fund, Washington, DC.
Lee, J., Milesi-Ferretti, G.M., Ostry, J.D., Prati, A. and Ricci, L. (2008), “Exchange rate
assessments: CGER methodologies”, Occasional Paper No. 261, International Monetary
Fund, Washington, DC.
MacDonald, R. (2001), “Modelling the long-run real effective exchange rate of the New Zealand
dollar”, Discussion Paper No. 2002/02, Reserve Bank of New Zealand, Wellington.
Obstfeld, M. and Rogoff, K. (1995), “The intertemporal approach to the current account”,
Handbook of International Economics, Vol. 3, pp. 1731-99.
Rogoff, K. (1996), “The purchasing power parity puzzle”, Journal of Economic Literature, Vol. 34,
pp. 647-68.
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Samuelson, P. (1964), “Theoretical notes on trade problems”, Review of Economics and Statistics,
Vol. 46, pp. 145-64.
Wren-Lewis, S. (2004), “A model of equilibrium exchange rates for New Zealand and Australian
dollars”, Discussion Paper No. 2004/07, Reserve Bank of New Zealand, Wellington.
Further reading
International Monetary Fund (2008), World Economic Outlook, International Monetary Fund,
Washington, DC, October.
Appendix 1. Dataset description
Country coverage
Wide panel sample. Algeria, Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, China,
Colombia, Croatia, the Czech Republic, Denmark, Egypt, Finland, France, Germany, Greece,
Hong Kong SAR, Hungary, India, Indonesia, Ireland, Israel, Italy, Japan, Korea, Luxembourg,
Malaysia, Mexico, Morocco, The Netherlands, New Zealand, Norway, Pakistan, Peru, the
Philippines, Poland, Portugal, Russia, Saudi Arabia, Singapore, the Slovak Republic, Slovenia,
South Africa, Spain, Sweden, Switzerland, Taiwan POC, Thailand, Tunisia, Turkey, the UK, the
USA, and Venezuela.
Narrow panel sample. Australia, Canada, Chile, Denmark, Finland, New Zealand, Norway,
South Africa, and Sweden.
Dataset
The dataset consists of annual observations on several macroeconomic variables over the period
1973-2007. In addition, for the medium-term analysis it uses forecasts from the WEO over the
period 2008-2013. This panel is unbalanced, in the sense that the number of observations varies
across macroeconomic variables along both the cross-sectional and time-series dimensions.
Variables[14]
Macroeconomic balance approach. Dependent variable: the ratio of the current account balance
to GDP.
Explanatory variables:
.
the ratio of the retirement age population to the working age population;
.
the growth rate of the population;
.
the logarithm of income per capita expressed in terms of purchasing power;
.
the growth rate of income per capita expressed in terms of purchasing power;
.
the ratio of the oil trade balance to GDP;
.
the ratio of the ?scal balance to GDP; and
.
the lagged ratio of the NFA position to GDP.
Equilibrium real exchange rate approach. Dependent variable: the logarithm of the real effective
exchange rate.
Explanatory variables:
.
the logarithm of the terms of trade;
.
the logarithm of output per worker expressed in terms of purchasing power;
.
the ratio of government consumption to GDP; and
.
the ratio of the NFA position to GDP.
External sustainability approach. Dependent variable: the ratio of the NFA position to GDP.
Exchange rate
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Explanatory variables:
.
the logarithm of output per worker expressed in terms of purchasing power;
.
the ratio of the retirement age population to the working age population, and
.
the ratio of the government net asset position to GDP.
Data sources
Data and forecasts, where possible, are from the October 2008 vintage of the World Economic
Outlook database maintained by the international monetary fund. These forecasts are
conditional on a constant consumer price index-based real effective exchange rate. Other data
were retrieved from other databases maintained by the International Monetary Fund or the
World Bank Group, and conditional forecasts were generated. In particular, effective exchange
rate data were obtained from the information notice system database, NFA position data
were retrieved from the international investment position database, and population share
data were extracted from the world development indicators database.
Appendix 2. The theoretical framework
This Appendix discusses the theoretical foundation of the three approaches.
MB approach
Under the MB approach, the medium-run equilibrium value of the ratio of the current account
balance to GDP is jointly modeled from intertemporal and intratemporal perspectives. The
medium-run equilibrium value of the real effective exchange rate is then inferred as that value of
the real effective exchange rate that reconciles these intertemporal and intratemporal current
account balance estimates.
As discussed in a survey paper by Obstfeld and Rogoff (1995), intertemporal models of the
current account balance are based on the saving and investment behavior of domestic economic
agents. Private saving is typically modeled within the framework of household utility
maximization, while private investment is typically modeled within the framework of ?rm value
maximization. Public saving and investment are typically treated as exogenous.
Within the framework of overlapping generations models, household utility maximization
predicts temporary but persistent deviations of the private saving rate from its long-run
equilibrium value in response to demographic change. The pro?le of household disposable
income over the life cycle is typically hump-shaped. Given this household disposable income
pro?le, consumption smoothing behavior implies a reduction in the private saving rate in
response to an increase in the economically inactive share of the population. It is common to
proxy for this effect of demographic change with the ratio of the retirement age population to the
working age population, and the growth rate of the population, both of which are expected to be
negatively associated with the private saving rate, and by implication with the ratio of the
current account balance to output.
Within the framework of neoclassical growth models, ?rm value maximization predicts
temporary but persistent deviations of the private investment rate from its long-run equilibrium
value in response to unbalanced economic growth. Under the conditional convergence
hypothesis discussed in Barro and Sala-i-Martin (1999), technological diffusion across economies
having similar saving rates and population growth rates implies a negative association of the
private capital investment rate with the level of income per capita, and a positive association
with the growth rate of income per capita. This implies a positive association of the ratio of the
current account balance to output with the level of income per capita, and a negative association
with its growth rate.
Under Ricardian equivalence, households fully internalize the intertemporal budget
constraint of the government, implying invariance of the current account balance to the ?scal
balance. A variety of theoretical models predict departures from Ricardian equivalence, in which
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case the ratio of the current account balance to output is typically positively associated with the
?scal balance. Departures from Ricardian equivalence are well documented empirically.
Equilibrium real exchange rate approach
Let
S
i;t
denote the nominal effective exchange rate, de?ned as a geometric trade-weighted
average of nominal bilateral exchange rates S
i;t
, each of which measures the price of the domestic
currency in terms of foreign currency. Also, let
Q
i;t
denote the real effective exchange rate,
de?ned as a geometric trade-weighted average of real bilateral exchange rates Q
i;t
, each of which
measures the price of a basket of domestic goods and services in terms of a basket of foreign
goods and services. If P
i;t
denotes the price of this basket of domestic goods and services, then
the real effective exchange rate satis?es:
ln
Q
i;t
¼ ln
S
i;t
þ ln P
i;t
2ln
P
i;t
ðA1Þ
where
P
i;t
denotes a geometric trade-weighted average of the prices of these baskets of foreign
goods and services. Suppose that P
i;t
may be expressed as a geometric trade-weighted average
of the prices of tradables P
T
i;t
and nontradables P
N
i;t
:
ln P
i;t
¼ u ln P
T
i;t
þ ð1 2uÞln P
N
i;t
ðA2Þ
where 0 # u # 1. Combination of this de?nition with result (A1) yields the following
decomposition of deviations from long-run PPP into deviations from the law of one price for
tradables, and deviations of the price of nontradables in terms of tradables from a geometric
trade-weighted average of this relative price across trading partners:
ln
Q
i;t
¼ ln
S
i;t
P
T
i;t
P
T
i;t
þ ð1 2uÞ ln
P
N
i;t
P
T
i;t
2ln
P
N
i;t
P
T
i;t
2
4
3
5
ðA3Þ
This decomposition is useful for classifying theoretical models which predict temporary but
persistent deviations of the real effective exchange rate from its long-run equilibrium value.
Let T
i;t
denote the terms of trade, de?ned as the price of exports of goods and services in
terms of imports of goods and services. If exchange rate pass through is complete, then the
domestic currency price of imports equals the foreign currency price of exports converted into
domestic currency, and decomposition (A3) may be expressed as:
ln
Q
i;t
¼ ln T
i;t
þ ð1 2uÞ ln
P
N
i;t
P
T
i;t
2ln
P
N
i;t
P
T
i;t
2
4
3
5
: ðA4Þ
In an empirical investigation of the degree of exchange rate pass through among developed
economies, Campa and Goldberg (2002) ?nd that exchange rate pass through is incomplete in the
short run, but complete in the long run[15]. This empirical evidence suggests a positive
association between the real effective exchange rate and the terms of trade.
The existence of deviations from long-run PPP attributable to the existence of nontradables is
rationalized by the model due to Balassa (1964) and Samuelson (1964). They consider a small
open economy which produces tradable and nontradable outputs with capital and labor inputs.
Consistent with a medium-run interpretation, they assume that capital is freely mobile both
internationally and across sectors domestically, while labor is only freely mobile across sectors
domestically. Within this theoretical framework, if productivity growth in the tradables sector
exceeds that in the nontradables sector, then in competitive equilibrium, wage equalization
across sectors implies that the price of nontradables in terms of tradables will increase over time.
If the relative price of nontradables rises faster domestically than among trading partners, then
Exchange rate
assessments
175
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(
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appreciation of the domestic currency in real effective terms is induced. As emphasized by Froot
and Rogoff (1995), this mechanism remains operative even in the absence of a productivity
growth differential across the tradables and nontradables sectors, provided that tradables are
relatively capital intensive, as is generally observed. Following Balassa (1964), it is common to
assume that tradables productivity bias is pronounced in relatively productive economies,
implying a positive association between the real effective exchange rate and output per worker,
expressed as a deviation from a trade-weighted average across trading partners[16].
Under the model associated with Balassa (1964) and Samuelson (1964), the real effective
exchange rate depends only on supply factors. However, if the strong assumptions underlying
this theoretical framework are relaxed, then the real effective exchange rate can also depend on
demand factors. It is common to assume that government consumption is biased toward
nontradables, implying a positive association between the real effective exchange rate and the
ratio of government consumption to output, expressed as a deviation from a trade-weighted
average across trading partners.
In medium-run equilibrium, intertemporal budget balance implies that net creditor economies
will tend to run trade de?cits, while net debtor economies will tend to run trade surpluses. To
induce the necessary expenditure switching, economies running trade de?cits will tend to have
relatively overvalued currencies in real effective terms, while economies running trade surpluses
will tend to have relatively undervalued currencies. This suggests a positive association between
the real effective exchange rate and the ratio of the NFA position to output.
External sustainability approach
Whether an economy is a net foreign creditor or debtor depends on accumulated net capital
?ows. Private net capital ?ows have a tendency to equalize the marginal product of capital
across economies, while public net capital ?ows may arise independently of such rate of return
considerations.
Within the framework of neoclassical growth models, the marginal product of capital is
increasing in the productivity with which inputs are combined to produce output, and is
decreasing in the abundance of capital relative to other inputs. This suggests a negative
association of the ratio of the NFA position to output with output per worker, and a positive
association with the ratio of the retirement age population to the working age population.
Corresponding author
Hali Edison can be contacted at: [email protected]
JFEP
1,2
176
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