Australia and New Zealand Exchange Rates
A Quantitative Assessment

The paper describes three empirical models commonly used to conduct exchange rate assessments and applies them to data for Australia and New Zealand. The baseline results using data and mediumterm projections available as of October 2008, suggest that the Australian and New Zealand dollars were broadly in line with fundamentals, but with a wide variation across models. A battery of sensitivity tests illustrate 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.

Abstract

The paper describes three empirical models commonly used to conduct exchange rate assessments and applies them to data for Australia and New Zealand. The baseline results using data and mediumterm projections available as of October 2008, suggest that the Australian and New Zealand dollars were broadly in line with fundamentals, but with a wide variation across models. A battery of sensitivity tests illustrate 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.

I. Introduction

An integral part of the Fund’s mandate is the close monitoring and careful evaluation of the exchange rates of its members. As a result, the Fund has developed a framework for assessing exchange rates. As part of this mandate, the 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-specific surveillance.1

Australia and New Zealand are both small commodity-exporting economies with reasonably long histories of independently floating 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 deficits 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 specifically focused on Australia and New Zealand, including Brooks and Hargreaves (2000), MacDonald (2001), Dvornak, Kohler, and Menzies (2003), and Wren-Lewis (2004). In contrast to the time series based assessments of these earlier studies, this paper adopts the panel based methodology of the IMF CGER group, and refines the estimation procedure.

In particular, three modifications to the conventional methods are introduced and then tested. First, each model is estimated as both a standard unrestricted panel regression using ordinary least squares and as a restricted panel regression using the generalized method of moments. 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). A battery of robustness tests are then 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 conflicting 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. Real Exchange Rate Developments

In recent years up until the middle of 2008, the Australian and New Zealand currencies had appreciated significantly in nominal and real effective terms (Figures 1 and 2, panel a). From 2001 to mid-2008, the Australian dollar appreciated by more than 30 percent in nominal effective terms, 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 reflects accumulated inflation rate differentials relative to trading partners. Since mid-2008, both the Australian and New Zealand dollars have depreciated significantly.3

Figure 1.
Figure 1.

Australia: Real Exchange Rate Developments

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF staff estimates.
Figure 2.
Figure 2.

New Zealand: Real Exchange Rate Developments

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF Staff estimates.

These real effective exchange rate movements have been driven in part by movements in real effective interest rate differentials (Figure 1 and 2, panel b). This relationship recently appears stronger at shorter horizons than at longer horizons, which likely reflects 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, the depreciations have been accompanied by a decline in global commodity prices.

The balance of payments for Australia and New Zealand have deteriorated 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 deficit has widened considerably.

In assessing the appropriate level of the real effective exchange rate, a common first step is to compare its prevailing level to some historical average. Such a comparison assumes that the real effective exchange rate is stationary, and that the nominal effective exchange rate moves in line with relative price levels, 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 long-run historical average (Figures 1 and 2, panel e)4. This observation applies using either the IMF or the central bank’s measure of the real effective exchange rate.

Most exchange rate assessments are geared towards evaluating the consistency of the exchange rate with economic fundamentals over the medium term. Those factors that have the most influence on exchange rates over the short run, such as interest rate differentials, are not necessarily the same ones that will exercise the most influence in the medium run.5 Nevertheless, the context within which the assessment is conducted is important. In the past few months with the global financial turmoil, there has been considerable movement in exchange rates, as illustrated by the movements in U.S. dollar bilateral exchange rates for Australia and New Zealand and the VIX, a measure of market volatility (Figures 1 and 2, panel f). This large increase in volatility has made it more difficult to conduct exchange rate assessments.

III. The Empirical Models6

A. Country Coverage and Econometric Methodology

The estimation dataset covers 55 industrial and emerging market economies over the period 1973–2007. For each empirical model, two country groupings are considered: a 55-country sample (wide panel) and a 9-country sample (narrow panel). (A detailed description of this panel data set is provided in Appendix I.) The wide panel spans economies that contribute significantly 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 coefficients.7 In recognition of this problem, a narrow panel of nine structurally similar economies is also considered.8 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 specification. The models are first estimated by ordinary least squares (OLS) and then by the generalized method of moments (GMM), using lagged explanatory variables as instruments, where appropriate. For the GMM model, a general to specific model specification strategy is used to derive a parsimonious specification. Both estimation techniques correct for cross-section specific unconditional heteroskedasticity and contemporaneous correlation of unknown form.9

B. 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: (i) estimating the equilibrium current account balance (current account norm); (ii) determining the ‘cyclically adjusted’ or underlying current account balance;10 and (iii) 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,

cai,t=β0,i+βTxi,t+εi,t,(1)

where β0,i denotes an economy specific fixed effect, and εi,tN(0,σi2). The variable cai,t denotes the ratio of the current account balance to GDP, while xi,t denotes a vector of explanatory variables. Following the CGER methodology, 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 fiscal balance to GDP, and the lagged ratio of the NFA position to GDP.

The estimates of equation (1) are broadly similar across econometric techniques and country coverage (Table 1). Under GMM, the estimated coefficients are statistically significant, have the expected signs, and plausible magnitudes:

  • The coefficient on the old age dependency ratio is negative, indicating that a higher dependency ratio reduces the current account balance. A 1 percentage point increase in the dependency ratio relative to trading partners would lower the current account norm by about ½ percent of GDP.

  • The coefficient on population growth is negative, but the size varies widely depending on the estimation method. A 1 percentage point increase in population growth relative to trading partners would lead to a worsening of the current account norm by 1 to 4 percent of GDP.11

  • The coefficient on higher relative income growth is negative. A 1 percentage point increase in relative income growth would reduce the current account norm by 0.4 percent of GDP.

  • The coefficient 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 deficit would imply a decrease in the current account norm.

  • The coefficient on the relative fiscal balance is positive. A one percent increase in the fiscal balance implies an improvement in the current account norm of approximately 0.1 percent of GDP.

  • The coefficient 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.

Table 1.

Estimation Results for the Macroeconomic Balance Approach

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Note: Statistical significance at the 1 percent, 5 percent, and 10 percent levels is indicated by ***, **, and *, respectively. Variables excluded from the final specification are indicated by “…”.Dependent variable: Ratio of current account balance to GDP.

The point estimates are decomposed into time-varying contributions from each of the explanatory variables, allowing one to give a country-specific interpretation to the equation (Figure 3). Using the wide panel GMM results, we see that the equilibrium current account deficits have been driven by a set of common factors.12 In both countries, high relative population growth has contributed to their large current account deficits. Both countries have relatively low dependency ratios and relatively strong fiscal balances that have supported their current account deficits. In addition, relatively low income growth has reduced private investment, which has reduced their equilibrium current account deficits. Finally, oil trade deficits have exacerbated their equilibrium current account deficits.

Figure 3.
Figure 3.

MB Approach: Estimated Contributions—Level and Change

(In percent of GDP)

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF staff estimates: GMM estimates for wide panel.

C. 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,

lnQ¯i,t=β0,i+βTxi,t+εi,t,(2)

where β0,i denotes an economy specific fixed effect, and εi,tN(0,σi2). The dependent variable denoted as Q¯i,t is the real effective exchange rate, while xi,t denotes a vector of explanatory variables. Following the CGER methodology, 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 first column in Table 2 reports the OLS estimate of the medium-run relationship between the real effective exchange and the above mentioned set of explanatory variables. Column 2 reports coefficient estimates for a parsimonious specification, which has been estimated using GMM. The coefficients on all three explanatory variables are positive, implying that an increase in any variable would lead to an appreciation.

Table 2.

Estimation Results for the Equilibrium Real Exchange Rate Approach

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Note: Statistical significance at the 1 percent, 5 percent, and 10 percent levels is indicated by ***, ** and *, respectively. Variables excluded from the final specification are indicated by “…”.Dependent variable: Real effective exchange rate.

Looking more closely at the decomposition of the equilibrium real effective exchange rate for Australia and New Zealand highlights the role of the terms of trade in driving the strength of the currencies (Figure 4). As shown by the decomposition of changes, the improvement in the terms of trade was the primary source of the persistent appreciation of the Australian dollar. As shown by the decomposition of levels, high relative productivity and government consumption held the equilibrium exchange rate above its PPP level, but these contributions have diminished over time. For New Zealand, the improvement in the terms of trade has been associated, on average, with the persistent appreciation of the dollar in real effective terms. The estimation of a large fixed effect does not necessarily indicate that relevant time invariant explanatory variables have been omitted from the model. Rather, it may reflect the fact that the real effective exchange rate is measured as an index that equals an arbitrary value in a base year.

Figure 4.
Figure 4.

ERER Approach: Estimated Contributions—Level and Change

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF staff estimates: GMM estimates for wide panel.

D. 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 flow, and the real effective exchange rate. Similar to the MB approach, it involves three steps: (i) estimating the ratio of the current account balance to GDP that would stabilize the NFA position at a given benchmark value, (ii) determining the level of the current account balance expected to prevail over the medium term, and (iii) 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 NFA position 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,

nfai,t=β0,i+βTxi,t+εi,t,(3)

where β0,i denotes an economy specific fixed effect, and εi,tN(0,σi2). As specified, nfai,t denotes the ratio of the NFA position to GDP, while xi,t denotes a vector of explanatory variables.13 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 3 reports the estimation results for the ratio of the NFA position to GDP. The GMM 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 coefficient on the government net asset position is positive and significant.

Table 3.

Estimation Results for the External Sustainability Approach

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Note: Statistical significance at the 1 percent, 5 percent, and 10 percent levels is indicated by ***, **, and *, respectively. Variables excluded from the final specification are indicated by “…”.Dependent variable: Ratio of net foreign assets to GDP.

Looking more closely at the results for Australia and New Zealand, reveals that fixed effects account for the majority of the estimated equilibrium net foreign debt positions (Figure 5). This result suggests that relevant explanatory variables that vary significantly across economies but not over time have been omitted from the panel regression model. A candidate is the real value of the stock of natural resources.

Figure 5.
Figure 5.

ES Approach: Estimated Contributions—Level and Change

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF staff estimates: GMM estimates for wide panel.

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. Since exchange rates are notoriously difficult to forecast in the short run, the medium-run horizon (2013) was deemed best for the construction of the baseline benchmark.14 In addition, to construct the baseline we use the GMM model estimates for the sample of 55 countries, as coefficient estimates were sensitive to economy coverage in the narrow panel. 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 approaches, the assessments are based on the required real effective 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.15 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.16

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.17 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, ranging from 7 percent undervalued (ERER) to 11 percent overvalued (ES) (Table 4). These results are based on the assumption that the underlying current account deficit 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 and others, 2008).

Table 4.

Baseline Results: Quantitative Exchange Rate Assessments 1/

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Sources: IMF staff estimates.

All figures are based on five year conditional forecasts, and are expressed in percent.

Estimates are based on a medium-run semi-elasticity of the ratio of the current account balance to GDP with respect to the real effective exchange rate of -0.16, a NFA to GDP norm of -49.5, and a medium-run equilibrium nominal GDP growth rate of 5.3 percent.

Estimates are based on a medium-run semi-elasticity of the ratio of the current account balance to GDP with respect to the real effective exchange rate of -0.21, a NFA to GDP norm of -71.2, and a medium-run equilibrium GDP growth rate of 4.8 percent.

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 confidence intervals, which capture model uncertainty.18 For Australia, the estimate ranges from 30 percent undervalued to 25 percent overvalued. For New Zealand, the range is almost as wide, spanning from -22 percent undervalued to 20 percent overvalued. However, these confidence intervals may overstate the uncertainty surrounding the exchange rate overvaluation estimates, as they are inflated by model misspecification.19

Figure 6.
Figure 6.

Confidence Intervals

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF staff estimates.

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 reflected 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 specifications 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 to 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 reflect these changes. Three different WEO forecasts (June, August, and October) with corresponding reference exchange rates are used to compute the degree of overvaluation (Table 5). 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 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.

Table 5.

Sensitivity Analysis: Reference Data 1/

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Source: Fund staff estimates.

Results reported are based on models estimated for the sample of 55 countries using GMM.

Based on Spring 2008 WEO and reference period for exchange rate is end-December 2007.

Based on Spring 2008 WEO and reference period for exchange rate is end-August 2008.

Based on October 2008 WEO and reference period for exchange rate is end-October 2008.

Auxiliary Parameters

The degree of overvaluation also depends on the auxiliary parameter assumptions. Below we consider the impact of changes in key parameters for the macroeconomic balance approach and external sustainability approach.

MB Approach: Current account norms and trade elasticities

Two key parameters for the macroeconomic balance 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 deficit 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 and an overvaluation of 13 percent. For New Zealand, the range is from an undervaluation of 4 percent to an overvaluation of 8 percent (Table 6). These results underscore the uncertainty surrounding the equilibrium level of the real effective exchange rate.20

Table 6.

Sensitivity Analysis: MB Approach—CA Projection and Trade Elasticity 1/

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Source: IMF staff estimates.

REER under/overvaluation is expressed in percent.

Projection of the underlying current account (CA) in percent of GDP in 2013.

ES Approach: Net foreign asset norms and nominal growth assumption

The ES approach relies on an intertemporal budget constraint that requires the present value of future trade surpluses be sufficient to pay for the country’s outstanding external liabilities. A key parameter in this approach is the rate of growth of the economy. The current account norm consistent with stabilizing net foreign assets 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 deficits. 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 also 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 observed values. The baseline estimates use model derived NFA norms. For comparison, we also compute the degree of overvaluation using the end-2007 NFA to GDP ratio. For both Australia and New Zealand, the models yield relatively low NFA norms. Replacing those norms with end-2007 values lifts the current account norms, which in turn reduces overvaluation estimates (Table 7).

Table 7.

Sensitivity Analysis: External Sustanability—NFA Norm 1/

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Source: IMF staff estimates.

Results reported are based on 2013 projections, using a GMM estimator applied to 55 countries.

For Australia, the baseline NFA/GDP is estimated from the model (table 3), the alternative measure is observed at end-2007, the growth rate is 5.3 percent.

For New Zealand, the baseline NFA/GDP is estimated from the model (table 3), the alternative measure is observed at end-2007, the growth rate is 4.8 percent.

To illustrate the sensitivity of the assessment to changes in the growth rate, we use the baseline as the point of departure and recomputed the degree of overvaluation assuming a 1 percentage 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 percentage point change in the growth rate alters the estimate of overvaluation by nearly 3 percentage points (Table 8).

Table 8.

Sensitivity Analysis: External Sustainability—Growth Rate 1/

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Source: IMF staff estimates.

Results reported are based on 2013 projections, using a GMM estimator applied to 55 countries.

For Australia, the baseline growth rate is 5.3 percent, low growth rate is 4.3 percent, and high growth rate is 6.3 percent.

For New Zealand, the baseline growth rate is 4.8 percent, low growth rate is 3.8 percent, and high growth rate is 5.8 percent.

Assessment Horizon

The time horizon that is used to evaluate the consistency of the exchange rate with economic fundamentals is another important factor. For the baseline, the adjustment was calculated based on medium-term fundamentals projected five 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 influences on the exchange rate. However, some argue that the assessment should also be made based on the current values of fundamentals.

In the cases of Australia and New Zealand, exchange rate assessments taken at the current horizon (2008) tend to suggest larger overvaluations, but this result varies across models and by country (Table 9). 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 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.

Table 9.

Sensitivity Analysis: Assessment Period 1/

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Source: IMF staff estimates.

Results reported are based on a GMM estimator applied to 55 countries.

Country Coverage

The set of economies that are included in the sample also influences 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 New Zealand (Table 10). The differences reflect changes in the selected model specifications and coefficient estimates. Consistent with earlier robustness tests, the ES model tends to produce large overvaluations.

Table 10.

Sensitivity Analysis: Country Coverage 1/

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Source: IMF staff estimates.

Results reported are based on 2013 projections.

Sample 55 countries.

Sample 9 countries.

Estimation Method

For comparison to other results, exchange rate assessments were also based on models estimated by OLS (Table 11). For the MB model, the OLS estimate for Australia suggests a 9 percentage point adjustment where as the GMM estimates suggest a 2.8 percentage point adjustment. However, the size of the difference varies considerably by model.

Table 11.

Sensitivity Analysis: Estimation Method 1/

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Source: IMF staff estimates.

Results reported are based on 2013 projections.

In sum, the quantitative assessments are sensitive to variations in assumptions. For Australia and New Zealand, small deviations from the baseline assumptions can lead to substantial changes in exchange rate overvaluation estimates (Figure 7).

Figure 7.
Figure 7.

Quantitative Exchange Rate Assessment: Summary

Citation: IMF Working Papers 2009, 007; 10.5089/9781451871548.001.A001

Source: IMF staff estimates.

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 were broadly in line with fundamentals, but with a wide variation across models. 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.

Numerical exchange rate assessments need to be treated with caution as the size of misalignment, 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 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.

Australia and New Zealand Exchange Rates: A Quantitative Assessment
Author: Ms. Hali J Edison and Mr. Francis Vitek