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j.japwor.2017.10.004

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Accepted Manuscript
Title: Is the yen misaligned more during the Abenomics
period?
Author: SaangJoon Baak
PII:
DOI:
Reference:
S0922-1425(17)30056-7
https://doi.org/10.1016/j.japwor.2017.10.004
JAPWOR 904
To appear in:
JAPWOR
Received date:
Revised date:
Accepted date:
18-6-2017
23-10-2017
23-10-2017
Please cite this article as: Baak, SaangJoon, Is the yen misaligned
more during the Abenomics period?.Japan and the World Economy
https://doi.org/10.1016/j.japwor.2017.10.004
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Is the yen misaligned more during the Abenomics period?
SaangJoon Baak
Professor
School of International Liberal Studies
Waseda University, 1-6-1 Nishi-Waseda, Shinjuku-ku, Tokyo 169-8050, Japan
Email: [email protected]
Oct 23, 2017
Highlights
Is the yen misaligned more during the Abenomics period?

We estimate the BEER model of the Japanese real effective exchange rate (REER).

The misalignments of the Japanese REER are computed based on the estimation results.

The yen was substantially overvalued during the global financial crisis period.
The yen was undervalued during the Abenomics period.
The yen was much less misaligned during the Abenomics period than in pre-Abenomics
periods.


Abstract
This paper measures the extent to which the real effective exchange rate of the Japanese yen
is misaligned from its equilibrium value. The equilibrium value is estimated using the
behavioral equilibrium exchange rate (BEER) approach to determine whether the yen is more
misaligned during the Abenomics period. Economic fundamentals such as terms of trade,
relative price of nontraded to traded goods, net foreign asset ratio over trade volume, and real
interest rate differentials are used to assess the equilibrium exchange rate. Because parameter
instability is detected for the whole period (1993 Q1 to 2016 Q2), stable estimation results
for the subsample period (2003 Q1 to 2016 Q2) are used to compute misalignments. The
results indicate that the yen was substantially overvalued during the global financial crisis
period (2008 Q4 to 2012 Q4). In contrast, it was undervalued during the Abenomics period
0
(2013 Q1 to 2016 Q2) but was much less misaligned than in pre-Abenomics periods.
JEL Classification: C22, F31
Keywords: Japanese yen, misalignment, behavioral equilibrium exchange rate, Abenomics
1
1. Introduction
After the Japanese government launched an aggressive quantitative easing (QE)
policy as part of Abenomics in 2013, the value of the yen against the US dollar depreciated
by about 56% within only three years. The quarterly average exchange rate of the Japanese
yen changed from 78.6 yen per dollar in the third quarter of 2012 to 122.3 yen in the third
quarter of 2015. Because the currency values of Japan’s major trading partners changed less
drastically during the same period, the real effective exchange rate of the yen also
depreciated sharply.
The sharp depreciation of the yen has provoked concerns among neighboring
countries that compete with Japan in the global market. Their major concern is that cheaper
Japanese products might crowd out their own products in the global market.1
The recent depreciation of the yen, however, does not necessarily imply that the
Japanese yen is substantially undervalued compared to the country’s economic
fundamentals. Instead, it may be returning to its equilibrium value following a sharp
appreciation during the global financial crisis (2008–2011). Figure 1-1 shows that the yen
depreciated against the US dollar from 2012 to 2015 almost as much as it appreciated from
2007 to 2011. It is true that the yen depreciated drastically beginning in 2012 while the
currencies of its neighboring countries remained relatively steady. However, the figure also
shows that the yen appreciated much faster than the Chinese yuan or the Korean won
between 2007 and 2011.
Because the value of the yen shows much greater volatility than Japan’s economic
fundamentals from 2008 to 2016, it is highly probable that the yen is misaligned from the
country’s economic fundamentals. Even so, the extent to which the yen is under- or
overvalued has rarely been quantified in literature.
Against this background, this paper aims to examine whether and to what extent the
real effective exchange rate of the Japanese yen is under- or overvalued compared to
Japan’s economic fundamentals. A special focus is given placed on the recent period to
determine whether the yen is more misaligned since the implementation of Abenomics.
Toward this end, this paper estimates the equilibrium value of the Japanese yen by using the
1
Bahmani-Oskooee and Hegerty (2009) reported that depreciation of the yen improved Japan’s trade balance
for about one-third of Japanese industries both in the short-term and in the long-term. In addition, Baak (2008,
2014) showed that depreciation of an Asian currency negatively affected the exports of its neighbors.
2
behavioral equilibrium exchange rate (BEER) approach proposed by Clark and MacDonald
(1998, 1999).
The BEER approach explains the dynamics of an exchange rate by economic
fundamentals related to the exchange rate and interprets unexplained movements of the
exchange rate as misalignments. Although it is generally accepted that predicting the future
values of an exchange rate is impossible, a rich body of research papers—whether
employing the BEER method or not—has shown that fundamental variables such as terms
of trade, real interest rate differentials, and net foreign assets are robustly linked to
exchange rate dynamics.2 The findings of these papers have enabled researchers to apply
the BEER method to various countries and regions by adopting appropriate economic
fundamentals as explanatory variables.
For example, Coudert et al. (2013) and El-Shagi et al. (2016) applied the BEER
model to Euro member countries. Coudert et al. (2013) analyzed the period from 1980 to
2010 and reported that the exchange rates of peripheral member countries had become
seriously overvalued since the mid-2000s. Similarly, El-Shagi et al. (2016), who analyzed
the period from 1980 to 2012, reported that the exchange rates of peripheral member
countries were significantly overvalued when the global financial crisis occurred in 2008.
A substantial number of papers have adopted the BEER approach to measure the
misalignments of Asian currencies. Examples include Funke and Rahn (2005), Wang et al.
(2007), and Zhang and Chen (2014) for the Chinese yuan; Koske (2008) for the Malaysian
ringgit; and Kinkyo (2008) and Baak (2012) for the Korean won.
Despite its use worldwide, the BEER model has been used very limitedly for the
Japanese yen. Although the yen was included in research by Bénassy-Quéré and LahrècheRévil (2008), Ricci et al. (2013), and Adler et al. (2017), these papers focus mainly on
determining economic fundamentals that explain exchange rate dynamics rather than
quantifying misalignments of the yen. Of interest is that in the first BEER paper by Clark
and MacDonald (1998), the authors applied their model to Japan’s time series data for the
period of 1960 to 1996 and claimed that their model explained the dynamics of the yen
fairly well. To the best of our knowledge, however, no paper has analyzed Japanese time
series data for the 2000s using the BEER model. In fact, misalignments of the yen are
rarely quantified in literature, despite the hot debates surrounding the appropriate value of
2
See Engle et al. (2007), Ricci et al. (2013), and Adler et al. (2017), for example.
3
the currency.3
One conjecture regarding such limited use of the BEER model for the yen is that the
model’s performance may not be satisfactory when applied to the post-bubble period data
of the yen. Some preliminary estimation experiments in this paper confirmed this
speculation. As will be shown later in the paper, if the typical BEER model is employed for
the yen for the period of 1993 Q1 to 2016 Q2, the model does not perform as well as in
Clark and MacDonald (1998). However, by considering a structural change, and by
adopting the suggestion of Bleaney and Tian (2014) to modify the BEER equation, this
paper shows that the BEER model applied to the yen’s time series data produces estimation
results that are quite consistent with economic theories. Since the Hansen (1992) stability
test indicates parameter stability of the BEER model for the period of 2003 Q1 to 2016 Q2,
the misalignments of the yen are quantified for that period. Results show that the yen was
undervalued from 2005 Q4 to 2008 Q3, overvalued from 2008 Q4 to 2012 Q4 (global
financial crisis period), and undervalued again from 2013 Q1 to 2016 Q2 (Abenomics
period). However, the misalignments of the yen since 2013 have not been as severe as those
in the periods of 2005 Q4 to 2008 Q3 and 2008 Q4 to 2012 Q4.
The following section describes the BEER approach, the variables employed in the
model, how the variables are computed, and how the model differs from typical BEER
models. Section 3 reports the estimation results and shows how the performance of the
model is improved by the modification explained in section 2 and structural break tests.
Section 4 measures misalignments of the yen using the estimation results. Section 5
concludes the paper.
2. The model
Based on the interest parity condition, the BEER approach proposed by Clark and
MacDonald (1998) derives the following reduced form equation:
q t = β′ Z t
3
(1)
According to Aminian et al. (2012), the Japanese yen was the first Asian currency whose appropriate value
provoked an international debate.
4
where q t is the real equilibrium exchange rate expressed as the foreign currency price of a
unit of domestic currency4, Zt is a vector of economic fundamentals, and β is a vector of
coefficients. Based on theoretical and empirical developments in the field, Clark and
MacDonald (1998) proposed using the following five variables in Zt : relative terms of
trade (TOT), a variable to capture the Balassa-Samuelson effect (TNT), ratio of net foreign
assets (NFA) over GDP, real interest rate differential (IRD), and country risk premium.
However, because literature shows that no economic variable is strongly supported as a
proxy for the country risk premium (Chionis and MacDonald, 2002), this paper does not
include the country risk premium as an explanatory variable.5
The four variables mentioned above (TOT, TNT, NFA, and IRD) are widely supported by
literature as economic fundamentals related to exchange rate dynamics. For example,
Bussière et al. (2010), Ricci et al. (2013), and Adler et al. (2017) confirmed in their panel
data analyses that TOT, TNT, and NFA are significant and robust explanatory variables. IRD
is more often included in time series data analysis than in panel data analysis (Kinkyo, 2008;
Baak, 2012). Kitamura and Akiba (2006) showed from their analysis of exchange rates and
interest rates from 1999 to 2002 that the yen-dollar exchange rate is affected by interest
differentials between the countries.
Among the variables, TNT is used to capture the Balassa-Samuelson effect.
Typically used proxies for the effect are relative price of nontraded to traded goods (Clark
and MacDonald, 1998; Kinkyo, 2008; Baak, 2012), GDP per capita (Koske, 2008; Bussière
et al., 2010; Adler et al., 2017), or labor productivity in nontraded and traded goods sectors
(Ricci et al., 2013). This paper adopts the relative price of nontraded to traded goods as the
proxy, in line with Clark and MacDonald (1998), for the following two reasons. First, the
analysis of Ricci et al. (2013) implies that GDP per capita may not be an appropriate proxy
for the Balassa-Samuelson effect. Second, this paper analyzes quarterly data to examine the
misalignment of the yen since Abenomics, but cross-country labor productivity data are
available only on an annual basis. This paper also includes the Euro area as one of Japan’s
major trading partners, and the labor productivity data for the Euro area are not available.6
4
Therefore, a decrease in the exchange rate means a depreciation of the Japanese yen.
5
In fact, the risk premium is rarely included in Zt in the recent BEER literature.
6
By including the Euro area, the major trading partners of Japan involved in the computation of variables
occupy more than 65% of Japan’s trade.
5
According to Balassa (1964) and Samuelson (1964), the real exchange rate should
be negatively related to the relative productivity of the non-tradable goods sector to the
tradable goods sector. Since the relative productivity between the two sectors is negatively
connected to their relative price, the relative price of nontraded to traded goods is expected
to have a positive relationship with the real exchange rate.
In the meantime, different from Clark and MacDonald (1998), this paper replaces
the ratio of NFA over GDP with the ratio of NFA over trade volume following the
arguments of Bleaney and Tian (2014). Bleaney and Tian (2014) showed that if the NFA is
scaled by the GDP, the valuation effects generate biases in the estimation because the
measure of the NFA/GDP ratio is affected by the real exchange rate. To resolve this
problem, they suggested that the NFA should be scaled by the trade volume. Following
their suggestion, this paper employs the ratio of NFA to Japan’s trade volume (NFAT). As
shown in the following section, this change substantially improves the model’s estimation
performance.
Accordingly, the specific form of the BEER equation estimated in this paper is as
follows:
LQ = β0 + β1 LTNT + β2 LTOT + β3 IRD + β4 NFAT + ε
(2)
where LQ is the log value of Japan’s real effective exchange rate, LTOT is the log value of
TOT, and LTNT is the log value of TNT. IRD is the interest rate differential between Japan
and the US, and NFAT is NFA over trade volume.7 The residuals of the equation are
interpreted as misalignments from the equilibrium values. In literature, this deviation from
the fitted values is called the “current misalignment.”
In addition, literature on BEER distinguishes the current equilibrium exchange rate
(q t ) determined from the current values of economic fundamentals (Zt ), from the long-run
equilibrium exchange rate (q̅t ) determined from the long-run values of economic
fundamentals (Z̅t ). Practically, the long-run values of economic fundamentals in the BEER
literature are obtained using the Hodrick-Prescott filter.8 The deviation of the actual
exchange rate from the long-run equilibrium exchange rate is called the “total
7
More detailed definitions of the variables are written later.
8
Clark and MacDonald (1998, 1999), Kinkyo (2008), and Baak (2012), among others, used the Hodrick-
Prescott filter to obtain the long-run equilibrium exchange rates.
6
misalignment.” Both the current and the total misalignment are calculated in section 4.
Variables and data9
This paper estimates the BEER equation using quarterly data from the period 1993
Q1 to 2016 Q2. The starting point, 1993 Q1, was selected considering data availability and
the fact that the Japanese bubble burst in the early 1990s. The real effective exchange rate
is CPI based and is obtained from the weighted geometric average of the indices of the
bilateral real exchange rates between Japan and its twelve major trade partners. These
twelve partners—Australia, Canada, China, Hong Kong, Indonesia, South Korea, Malaysia,
Singapore, Thailand, the UK, the US, and the Euro area—were selected based on their
shares in Japanese trade. Their total share in Japanese trade never decreased below 65%
during the period covered in this research. Figure 1-2 illustrates the Japanese real effective
exchange rates computed in the paper along with those reported by the IMF and the BIS,
confirming that the three series are almost identical.
TOT is the terms of trade of Japan divided by the weighted average of those of the
twelve partner countries. A country’s terms of trade consist of the ratio of its export unit
value to its import unit value. The terms of trade are known to have two contradicting
effects on the equilibrium exchange rate.10 Therefore, β1 may be either positive or
negative.
TNT is calculated by dividing the Japanese ratio of CPI over PPP by the weighted
average of the same ratios of the twelve countries. As explained previously, this variable is
included to capture the Balassa-Samuelson effect. Therefore, β2 is expected to be positive.
IRD is the differential of the real interest rate between Japan and the US. The real
interest rate is defined as the lending rate minus the CPI-based inflation rate. Because no
interest rate data are available for all the countries involved, the US rate is used as a
representative foreign yield, considering the impact of the country on international financial
9
10
The data used in the paper can be obtained from the authors upon request.
See Kinkyo (2008).
7
transactions.11 An increase in the real interest rate differential (domestic minus foreign
rate) induces currency appreciation. Therefore, β3 is expected to be positive.
Finally, NFAT is the ratio of Japan’s net foreign asset to its trade volume (export plus
import). If the net foreign asset decreases, the real exchange rate should depreciate to
generate a trade surplus; this is needed to finance more interest payments induced by the
decline in net foreign assets. Therefore, β4 is expected to be positive.
Data sources
Most data were collected from the International Financial Statistics (IFS) of the
IMF. The Euro exchange rates were collected from both the IFS and the Euro Stat. The unit
value of exports and the unit value of imports of the Euro Area, Indonesia, and Malaysia
were obtained from the Data Stream. The unit value of exports and the unit value of
imports of Korea were obtained from the Bank of Korea.
3. Estimation results
Unit root tests
Because conventional unit root tests such as the ADF test may fail to detect nonstationarity when a non-stationary series has a structural break, as Perron (2006) discusses,
and because Japan’s economic variables are often suspected to have structural breaks, this
paper performs the S-L unit root test suggested by Saikkonen and Lutkepohl (2002), which
is robust in the presence of a structural break. As reported in Table 1, the null hypothesis of
a unit root is accepted at the 5% significance level for the levels of all the variables. In
addition, it should be noted that the S-L tests with the first differences, which are not
reported in the paper, strongly indicate stationarity for all the variables involved.12
11
In preliminary estimations, the weighted average of the foreign lending rates was calculated using available
data. When the weighted average rate replaces the US rate, the estimation coefficient values of equation (2)
were altered only marginally. However, the coefficient of IRD becomes insignificant.
12
The S-L unit root test here and the S-L cointegration test below are implemented by the software JMulTI.
8
<Insert Table 1>
Cointegration tests
Considering the possibility of any structural changes in the relationship among the
variables in equation (2), this paper performs the S-L cointegration test (Saikkonen and
Lutkepohl, 2000a, 2000b, 2000c), which is robust to a structural break in the long-term
relationship. The test results reported in Table 2 indicate the presence of a long-term
relationship among the variables at the 5% significance level.
<Insert Table 2>
Estimation results
Because the cointegration test indicates the presence of a cointegrating vector
among the variables in equation (2), the cointegrating vector is estimated by the fully
modified OLS (FMOLS) of Phillips and Hansen (1990) and the canonical cointegrating
regression (CCR) of Park (1992). Tables 3-1 and 3-2 list the estimation results. For a
comparison, NFA over trade volume (NFAT) is used as an explanatory variable in Table3a,
following Bleaney and Tian (2014) by the logic explained in section 2. In contrast, NFA
over GDP (NFAG) replaces NFAT in Table3b.
<Insert Table 3a and 3b>
In Table3a, when equation (2) is estimated for the whole period (1993 Q1 to 2016
Q2), NFAT has significant and negative coefficients, thus contradicting economic theories,
while the signs of other explanatory variables are consistent with what is expected. LTNT
is not significant at the 5% significance level, but the other variables are all significant. In
the meantime, the null hypothesis of parameter stability is rejected at the 5% significance
level by the Hansen (1992) stability test. In addition, the null hypothesis of no cointegration
of the Phillips and Ouliaris (1990) test is accepted even at the 10% significance level. These
test results strongly indicate that a structural change has occurred. Accordingly, estimations
and stability tests were performed using various sub-sample period data. Specifically, we
9
shortened the sample period by eliminating earlier years one by one until the p-value of the
Hansen stability test was higher than 10 percent. Table 4 reports the Hansen stability test
results for various sub-sample periods, showing the stability test is accepted when the
sample period starts from 2001. Because the Hansen stability test statistic is lowest when
the sample period is restricted to 2003 Q1~ 2016 Q2, Table3a reports the estimation results
for that subsample period. However, it should be reported that moving the starting point of
the sub-sample period from 2003 Q1 by a few quarters back and forth changes the
estimation results only marginally.
The present paper does not explore why there was a structural break in the early
2000s. However, it should be noted that Fukuda (2016) also reported a change in the
dynamics of the yen between the 1990s and the 2000s. In addition, the volatility of inward
and outward portfolio investment of Japan drastically increased from 2003 and 2004,
respectively. Considering that the effects of NFAT and IRD on a country’s currency value
will get stronger when the country is more open to capital flow, it does not seem surprising
that the break point is found in the early 2000s in Japan.
When the period is restricted to 2003 Q1 to 2016 Q2, all coefficients including
NFAT show the expected signs and are significant even at the 1% significance level.
Furthermore, the Phillips and Ouliaris (1990) test reconfirms the presence of cointegration,
and the null hypothesis of parameter stability is accepted because the p-value of the Hansen
(1992) stability test is higher than 0.2. These results indicate that the sub-sample period of
2003 Q1 to 2016 Q2 does not suffer a structural change in the regression equation. The
high R-square, 0.85, implies that the BEER model explains a fairly large part of the
variation of the Japanese real effective exchange rate.
On the other hand, when NFAT is replaced by NFAG in Table3b, the estimated
coefficient values have unexpected signs or are insignificant except for IRD for both the
whole sample period and the sub-sample period. Different from NFAT, the sign of NFAG
is still negative in the sub-sample period, even though overall performance of the model
seems improved in the sub-sample period. In fact, IRD is the only variable that has the right
sign and is significant. The poor performance of equation (2) when net foreign asset is
scaled by GDP can be regarded as empirical evidence that supports the argument of
Bleaney and Tian (2014).
In summary, the BEER model performs much better when net foreign asset is scaled
by trade volume rather than GDP. Even so, the regression results of the whole sample
10
period do not pass stability tests. The regression results of the sub-sample period do pass
the stability test, however. In addition, estimated coefficient values are all significant and
consistent with the prediction of economic theories. Therefore, the misalignments of the
Japanese yen will be quantified by plugging the estimated parameter values for the period
from 2003 Q1 to 2016 Q2, as reported in Table3a, into the BEER model equation (2).
Specifically, the parameter values estimated by the FMOLS (column 3 in Table3a) are
plugged into equation (2) in the following section. Because the CCR estimation results
(column 4 in Table3a) are very similar to those of FMOLS, the misalignments computed by
both illustrate only negligible differences.
4. Measuring misalignments
As explained in section 2, the behavioral equilibrium exchange rate (BEER) is
calculated by equation (2) using estimated coefficient values and actual data of the four
explanatory variables. On the other hand, when the long-run behavioral equilibrium
exchange rate (LBEER) is calculated, actual data of the four variables are replaced by their
long-run values that can be obtained by the Hodrick-Prescott filter. Figures 2a through 2d
illustrate the four explanatory variables in equation (2) along with their long-run trend
obtained by the Hodrick-Prescott filter. As the figures show, actual values deviated the most
from their long-run values in general during the global financial crisis. The great volatility
of the explanatory variables implies that they are very much influenced by temporary
shocks. These facts confirm the importance of calculating the LBEER because the impacts
of temporary shocks are eliminated from the data used to calculate it.
<Insert Figures 2a through 2d>
Figure 3 shows the BEER and the LBEER along with the actual real effective
exchange rate (REER). The BEER is moving around the REER without a big margin,
implying minor misalignments. Even during the global financial crisis in which the yen
maintained relatively high values, the actual exchange rate (REER) was lower than the
equilibrium exchange rate (BEER) from time to time, implying that the yen was not
continually overvalued in that time period. Also, during the Abenomics period in which the
11
value of the yen was relatively lower, the actual exchange rate (REER) was sometimes
higher than the equilibrium exchange rate (BEER), implying that the yen was not
continually undervalued in that time period. The over- and undervaluation of the yen should
not be determined only by the BEER, however, because the equilibrium values are not free
from unexpected temporary shocks of economic fundamentals. Therefore, the actual
exchange rate should be compared to the long-run equilibrium exchange rate (LBEER),
which is unaffected by those temporary shocks.
Figure 3 shows that the actual exchange rate was higher than the LBEER during the
post-Lehman shock and pre-Abenomics period (2008 Q4 to 2012 Q4), and that it was lower
than the LBEER during the Abenomics period (2013 Q1 to 2016 Q2). This implies that the
yen was overvalued during the global financial crisis period and undervalued during the
Abenomics period. Considering that the yen was believed to be a relatively safe asset
during the global financial crisis, and that the Bank of Japan did not implement aggressive
monetary policies in that period while the Fed, the European Central Bank, and the Bank of
England did, it is not surprising that the yen was overvalued in that period. On the other
hand, as Fukuda (2015) shows, foreign investors responded to Abenomics by aggressively
selling the Japanese yen in the foreign currency market. Their behaviors should be one of
the main forces that lead to the undervaluation of the yen during the Abenomics period.
While the Japanese yen was overvalued during the global financial crisis, according
to Baak (2012), who examined the misalignments of the Korean won from 1982 to 2009,
the currency was substantially undervalued in 2008–2009. Zhang and Chen (2014)
analyzed the misalignments of the Chinese renminbi from 1980 to 2012, and concluded that
the currency was overvalued by around 10 percent in 2011–2012. However, according to
them, the renminbi was not substantially overvalued before 2011.
Figure 4 illustrates the specific magnitudes of the misalignments. The current
misalignments are computed by dividing the difference between the REER and the BEER
by the BEER—that is, (REER – BEER)/BEER. The misalignments are then transformed
into percentage terms. The total misalignments are computed in the same way by replacing
the BEER with the long-run BEER. That is, (REER – LBEER)/LBEER.
<Insert Figures 3 and 4>
12
As could be predicted from Figure 3, the current misalignments measure much
smaller than the total misalignments. According to the current misalignments, the actual
exchange rate of the Japanese yen was overvalued by 1.9% on average for the period of
2008 Q4 to 2012 Q4 (the global financial crisis period). It was near-equilibrium (or
overvalued by 0.1%) from 2013 Q1 to 2016 Q2 (the Abenomics period). It was the most
overvalued in 2008 Q4 (20.8%), when the Lehman shock hit the world, and the most
undervalued in 2013 Q1 (7.1%), right before implementation of the QQE (Qualitative and
Quantitative Monetary Easing) of Bank of Japan.13
However, according to the total misalignment, the Japanese yen was overvalued by
6.9% on average from 2008 Q4 to 2012 Q4 and was undervalued by 3.0% on average from
2013 Q1 to 2016 Q2. It was the most overvalued in 2012 Q3 (13.2%) and the most
undervalued in 2014 Q4 (7.8%). The yen was undervalued in the pre-Lehman shock period
(2005 Q4 to 2008 Q3) as well. In addition, the undervaluation in that period was much
more substantial than in the Abenomics period, as the yen was undervalued by 8.1% on
average in the pre-Lehman shock period.
Of particular interest is that the yen was overvalued in 2016. As seen in Figure 3,
the real effective exchange rate of the yen began to appreciate in 2016; the appreciation can
be explained by the movements in economic fundamentals depicted in Figures 2a through
2d. However, because the long-run values (the Hodrick-Prescott trend) of the economic
fundamentals are lower than the actual values, the long-run equilibrium exchange rate was
measured to be much lower than the actual exchange rate. This, then, is why the yen is
estimated to be overvalued in 2016.
Overall, whether according to the current misalignments or the total misalignments,
the yen was misaligned from its equilibrium value with a much smaller margin during the
Abenomics period than during the pre-Abenomics period.
4. Conclusions
This paper measures the extent to which the real effective exchange rate of the
Japanese yen was misaligned from its equilibrium value. The equilibrium value was
estimated using the BEER approach to determine whether the yen is more misaligned since
13
The second Abe administration started in December 2012, and the QQE of Bank of Japan started in April
2013.
13
the implementation of Abenomics than before. Twelve countries and regions were chosen
as Japan’s major trading partners. Then, the real effective exchange rate of Japan was
computed using the nominal exchange rates of the countries involved and their consumer
price indices.
The economic fundamentals, which are used as explanatory variables in the
equation in which the real effective exchange rate is the dependent variable, are the terms
of trade, the relative price of nontraded to traded goods, the real interest rate differential
between Japan and the US, and the net foreign assets of Japan relative to its trade volume.
While the estimated coefficient values for the period of 1993 Q1 to 2016 Q2 were
unstable, those estimated for the period of 2003 Q1 to 2016 Q2 were found to be stable and
consistent with economic theories. The total and current misalignments calculated for 2003
Q1 to 2016 Q2 indicate that the yen was undervalued with relatively small deviation from
its equilibrium value during the Abenomics period. On the contrary, it was substantially
undervalued in the pre-Lehman shock period (2005 Q4 to 2008 Q3) and substantially
overvalued during the global financial crisis period (2008 Q4 to 2012 Q4). According to the
total misalignment measures, the yen was overvalued by 6.9% on average from 2008 Q4 to
2012 Q4 and was undervalued by 8.1% on average from 2005 Q4 to 2008 Q3. In contrast,
it was undervalued only by 3.0% on average from 2013 Q1 to 2016 Q2. These results
indicate that the yen was misaligned from its equilibrium value with a much smaller margin
during the Abenomics period than in the pre-Abenomics period.
Funding: This work was supported by JSPS KAKENHI, grant number 25380337.
Acknowledgements: I would like to thank two anonymous reviewers, participants of the
2015 KAEA annual meeting and the 2015 World Congress of Comparative Economics for
their invaluable comments and suggestions for the previous version of this paper. Any
remaining errors are mine.
14
References
1. Adler, K., Grisse, C., 2017. Thousands of BEERs: Take your pick. Review of
International Economics, 1-27.
2. Aminian, A., Fung, K.C., Garcia-Herrero, A., Lin, C., 2012. The political economy of
exchange rates: The case of the Japanese yen. Japan and the World Economy, 24, 193196.
3. Baak, S., 2008. The bilateral real exchange rates and trade between China and the US,
4.
5.
6.
7.
8.
9.
10.
11.
China Economic Review, 19, 117-127.
Baak, S., 2012. Measuring misalignments in the Korean exchange rate. Japan and
World Economy, 24, 227-234.
Baak, S., 2014. Do Chinese and Korean products compete in the Japanese market? An
investigation of machinery exports. Journal of the Japanese and International
Economies, 34, 256-271.
Bahmani-Oskooee, M., S., Hegerty, 2009. The Japanese-US trade balance and the yen:
Evidence from industry data. Japan and the World Economy, 21, 161-171.
Balassa, B., 1964. The purchasing power parity doctrine: A reappraisal. Journal of
Political Economy 72, 584-596.
Bénassy-Quéré, A., Lahrèche-Révil, A., 2008. Is Asia responsible for exchange rate
misalignments within the G20? Pacific Economic Review, 13(1), 46-61.
Bleaney, M., Tian., M., 2014 Net foreign assets and real exchange rates revisited.
Oxford Economic Papers, 66, 1145-1158.
Bussière, M., Ca’ Zorzi, M., Chudik, A., and Dieppe, A. (2010). Methodological
advances in the assessment of equilibrium exchange rates (ECB Working Paper No.
1151). Frankfurt: European Central Bank.
Chionis, D., MacDonald, R., 2002. Aggregate and disaggregate measures of the foreign
exchange risk premium. International Review of Economics and Finance, 11, 57-84.
12. Clark, P., MacDonald, R., 1998. Exchange rates and economic fundamentals: A
methodological comparison of BEERs and FEERs. IMF working paper, WP/98/67,
International Monetary Fund.
13. Clark, P., MacDonald, R., 1999. Exchange rates and economic fundamentals: A
methodological comparison of BEERs and FEERs. In: Stein, J., MacDonald, R. (Eds.).
Equilibrium Exchange Rates. Boston: Kluwer.
15
14. Coudert, V., Couharde, C., Mignon, V., 2013. On currency misalignments within the
euro area. Review of International Economics, 21(1), 35-48.
15. El-Shagi, M., Lindner, A., Schweinitz, G., 2016. Real effective exchange rate
misalignment in the euro area: A counterfactual analysis. Review of International
Economics, 24(1), 37-66.
16. Engel, C., Mark, N., West, K., 2007. Exchange rate models are not as bad as you think.
NBER working paper 13318, National Bureau of Economic Research.
17. Fukuda, S., 2015. Abenomics: Why was it so successful in changing market
18.
19.
20.
21.
expectations? Journal of the Japanese and International Economies, 37, 1-20.
Fukuda, S., 2016. On the predictability of daytime and night-time yen/dollar exchange
rates. Applied Economic Letters, 23, 618-622.
Funke, M., Rahn, J., 2005. Just how undervalued is the Chinese renminbi? World
Economy, 465-631.
Hansen, B.E., 1992. Tests for parameter instability in regression with I(1) processes.
Journal of Business and Economic Statistics, 10, 321-335.
Kinkyo, T., 2008. Disorderly adjustments to the misalignments in the Korean won.
Cambridge Journal of Economics, 32, 111-124.
22. Kitamura, Y., Akiba, C., 2006. Information arrival, interest rate differentials, and
yen/dollar exchange rate. Japan and the World Economy, 18, 108-119.
23. Koske, I., 2008. Assessing the equilibrium exchange rate of the Malaysian ringgit: A
comparison of alternative approaches. Asian Economic Journal, vol. 22, no. 2, 179-208.
24. Park, J. Y., 1992. Canonical cointegrating regressions. Econometrica, 60, 119-143.
25. Perron, P., 2006. Dealing with structural breaks. In: Patterson, K, Mills, T.C. (Eds.).
Palgrave Handbook of Econometrics, Vol. 1: Econometric Theory, Palgrave Macmillan,
278-352.
26. Phillips, P.C.B., Hansen, B.E., 1990. Statistical inference in instrumental variables
regression with I(1) processes. Review of Economic Studies, 57, pp. 99-125.
27. Phillips, P., Ouliaris, S., 1990. Asymptotic properties of residual based tests for
cointegration. Econometrica, 58, 165-193.
28. Ricci, L., Milesi-Ferretti, G., Lee, J., 2013. Real exchange rates and fundamentals: A
cross-country perspective. Journal of Money, Credit and Banking, 45 (5), 845-865.
29. Saikkonen, P., Lutkepohl, H., 2000a. Testing for the cointegrating rank of a VAR process
with an intercept. Econometric Theory 16(3), 373-406.
16
30. Saikkonen, P., Lutkepohl, H., 2000b. Testing for the cointegrating rank of a VAR
process with structural shifts. Journal of Business & Economic Statistics, Vol. 18, Iss. 4,
p. 451-464.
31. Saikkonen, P., Lutkepohl, H., 2000c. Trend adjustment prior to testing for the
cointegrating rank of a vector autoregressive process. Journal of Time Series Analysis
21(4): 435-456.
32. Saikkonen, P., Lutkepohl, H., 2002. Testing for a unit root in a time series with a level
shift at unknown time. Econometric Theory 18(2), 313-348.
33. Samuelson, P., 1964. Theoretical notes on trade problems. Review of Economics and
Statistics 46, 145-54.
34. Wang, Y., Hui, X., Soofi, A., 2007. Estimating renminbi (RMB) equilibrium exchange
rate. Journal of Policy Modeling 29, 417-429.
35. Zhang, Z., Chen, L., 2014. A new assessment of the Chinese RMB exchange rate. China
Economic Review 30, 113-122.
17
<Table 1> SL Unit Root Test for the Levels
Variable
SL Statistic
Lag(1)
Suggested Break(2)
LQ
-1.228
-0.867
-1.199
-1.209
-2.657
3
6
5
5
5
2008Q4
2003Q3
2008Q4
2009Q1
1997Q2
LTNT
LTOT
NFA
IRD
Notes: (1) The lags were determined by the four criteria used in JMulTI. (2) The breaks reported in the table
are those suggested by JMulTI. (3) The 1%, 5%, and 10% critical values are -3.48, -2.88, and -2.58, respectively.
<Table 2> Cointegration Tests with a Structural Break
r0
r 1
r 1
r2
r2
S-L Statistic
70.14*
(p-value)
0.005
Statistic
H0:
HA:
r4
r3
r3
r4
35.12
15.05
4.34
0.34
0.149
0.459
0.664
0.620
r 5
Notes: (1) r denotes the number of cointegrating vectors. (2) The lag length included in the test equation is set
to 1 based on the Schwarz criterion. (3) The asterisk (*) indicates the rejection of the null hypothesis of no
cointegration at the 5% significance level.
18
<Table 3a> Estimation Results when NFAT is Used
Variables
Constant
LTNT
LTOT
IRD
NFAT
R squared
Hansen test
1)
P-O test2)
1993 Q1 to 2016 Q2
2003 Q1 to 2016 Q2
(1)
(2)
(3)
(4)
FMOLS
CCR
FMOLS
CCR
4.767
4.773
4.271
4.272
(0.000)
(0.000)
(0.000)
(0.000)
0.959
0.992
4.366
4.391
(0.108)
(0.084)
(0.000)
(0.000)
0.475
0.467
0.270
0.264
(0.000)
(0.000)
(0.000)
(0.000)
0.025
0.024
0.020
0.020
(0.001)
(0.001)
(0.001)
(0.001)
-0.027
-0.028
0.041
0.040
(0.010)
(0.009)
(0.000)
(0.000)
0.779
0.778
0.848
0.849
(0.017)
(0.019)
(> 0.2)
(> 0.2)
(0.294)
(0.294)
(0.040)
(0.040)
Notes: (1) The null hypothesis of the Hansen (1992) test is that the parameters are stable. (2) The null hypothesis
of the P-O test (Phillips and Ouliaris, 1990) is that the variables are not cointegrated. (3) The numbers in
parentheses are p-values.
19
<Table 3b> Estimation Results when NFAG is used
1993 Q1 to 2016 Q2
2003 Q1 to 2016 Q2
Variables
FMOLS
CCR
FMOLS
CCR
Constant
4.935
4.934
4.712
4.642
(0.000)
(0.000)
(0.000)
(0.000)
-0.069
-0.037
1.322
1.906
(0.912)
(0.950)
(0.264)
(0.170)
0.003
0.003
0.052
0.124
(0.985)
(0.984)
(0.763)
(0.508)
0.026
0.026
0.043
0.040
(0.000)
(0.000)
(0.000)
(0.000)
-0.188
-0.188
-0.067
-0.032
(0.000)
(0.000)
(0.397)
(0.724)
R squared
0.823
0.823
0.795
0.794
Hansen test1)
(0.027)
(0.027)
(> 0.22)
(> 0.22)
P-O test2)
(0.146)
(0.146)
(0.228)
(0.227)
LTNT
LTOT
IRD
NFAG
Notes: See Table 3a.
<Table 4> Hansen Stability Test Results
Period
1998Q1~
1999Q1~
2000Q1~
2001Q1~
2002Q1~
2003Q1~
2004Q1~
2016Q2
2016Q2
2016Q2
2016Q2
2016Q2
2016Q2
2016Q2
Lc statistic
1.611
1.648
1.594
0.577
0.589
0.441
0.562
p-value
<0.01
<0.01
<0.01
>0.2
>0.2
>0.2
>0.2
20
<Figure 1-1> Exchange Rates against the US Dollar (Index, 2005=100)
140
130
120
110
100
90
80
70
2000 Q1
2000 Q3
2001 Q1
2001 Q3
2002 Q1
2002 Q3
2003 Q1
2003 Q3
2004 Q1
2004 Q3
2005 Q1
2005 Q3
2006 Q1
2006 Q3
2007 Q1
2007 Q3
2008 Q1
2008 Q3
2009 Q1
2009 Q3
2010 Q1
2010 Q3
2011 Q1
2011 Q3
2012 Q1
2012 Q3
2013 Q1
2013 Q3
2014 Q1
2014 Q3
2015 Q1
2015 Q3
2016 Q1
60
China, P.R.: Mainland
Japan
Korea, Republic of
Note: This graph illustrates the indices (2005=100) computed from quarterly average exchange rates against
the US dollar.
Data Source: IFS
<Figure 1-2> Japanese Real Effective Exchange Rates (base year=2010)
160
140
120
100
80
60
1994 Q1
1994 Q4
1995 Q3
1996 Q2
1997 Q1
1997 Q4
1998 Q3
1999 Q2
2000 Q1
2000 Q4
2001 Q3
2002 Q2
2003 Q1
2003 Q4
2004 Q3
2005 Q2
2006 Q1
2006 Q4
2007 Q3
2008 Q2
2009 Q1
2009 Q4
2010 Q3
2011 Q2
2012 Q1
2012 Q4
2013 Q3
2014 Q2
2015Q1
2015Q4
40
REER
IMF
BIS
Note: The REER is the real effective exchange rate computed in the paper. Since the BIS data are available
from 1994, the graphs are illustrated from that year, too.
Data Sources: IFS and BIS
21
<Figure 2-1> Relative Price of Nontraded Goods to Traded Goods (Log Value, LTNT)
0.04
0.02
0
-0.02
-0.04
-0.06
-0.08
-0.1
-0.12
LTNT
HP_LTNT
<Figure 2-2> Terms of Trade (Log Value, LTOT)
0.4
0.3
0.2
0.1
0
-0.1
-0.2
LTOT
HP_LTOT
22
<Figure 2-3> Net Foreign Assets over Trade Volume (NFTA)
14
12
10
8
6
4
2
0
NFAT
HP_NFAT
<Figure 2-4> Real Interest Rate Differential (IRD)
3
2
1
0
-1
-2
-3
-4
-5
-6
IRD
HP_IRD
23
<Figure 3> REER, BEER, and Long-Run BEER
120
110
100
90
80
70
60
REER
BEER
Long-run BEER
REER = real effective exchange rate; BEER = qt = behavioral equilibrium exchange rate; long-run BEER =
q̅t
<Figure 4> Misalignments of the Japanese real effective exchange rate (%)
25.0
20.0
15.0
10.0
5.0
0.0
-5.0
-10.0
compared with BEER
compared with Long-run BEER
24
2016 Q1
2015 Q3
2015 Q1
2014 Q3
2014 Q1
2013 Q3
2013 Q1
2012 Q3
2012 Q1
2011 Q3
2011 Q1
2010 Q3
2010 Q1
2009 Q3
2009 Q1
2008 Q3
2008 Q1
2007 Q3
2007 Q1
2006 Q3
2006 Q1
2005 Q3
2005 Q1
2004 Q3
2004 Q1
2003 Q3
2003 Q1
-15.0
no misalignment
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