Discussion Papers In Economics
And Business

AN INJECTION OF BASE MONEY AT ZERO INTEREST RATES:EMPIRICAL EVIDENCE FROM THE JAPANESE EXPERIENCE 2001–2006

Yuzo Honda, Yoshihiro Kuroki, and Minoru Tachibana

Discussion Paper 07-08

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANAN INJECTION OF BASE MONEY AT ZERO INTEREST RATES:EMPIRICAL EVIDENCE FROM THE JAPANESE EXPERIENCE 2001–2006

Yuzo Honda, Yoshihiro Kuroki, and Minoru Tachibana

Discussion Paper 07-08

March 2007
この研究は「大学院経済学研究科・経済学部記念事業」
基金より援助を受けた、記して感謝する。
Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANAN INJECTION OF BASE MONEY AT ZERO INTEREST RATES:EMPIRICAL EVIDENCE FROM THE JAPANESE EXPERIENCE 2001–2006 ♣Yuzo Honda ∗ , Yoshihiro Kuroki † , and Minoru Tachibana ‡March 2007
Abstract
Many macroeconomists and policymakers have debated the effectiveness of thequantitative monetary-easing policy (QMEP) that was introduced in Japan in 2001.
This paper measures the effect of the QMEP on aggregate output and prices, andexamines its transmission mechanism, based on the vector autoregressive (VAR)
methodology. To ascertain the transmission mechanism, we include several financial
market variables in the VAR system. The results show that the QMEP increased
aggregate output through the stock price channel. This evidence suggests that further
injection of base money is effective even when short-term nominal interest rates are atzero.

Keywords: Quantitative easing; Money injection; Portfolio rebalancing; Stock pricechannel; Vector autoregression

JEL classification: E44; E52
Correspondence: Yuzo Honda, School of Economics, Osaka University
Toyonaka, Osaka, 560-0043, Japan♣

We would like to thank Takayuki Ugomori for his research assistance. We also
gratefully acknowledge the financial support of the 21st Century Center of Excellence
Program at Osaka University, sponsored by the Ministry of Education, Culture, Sports,
Science and Technology, Japan.
∗
Osaka University† Chuo University‡ Osaka Prefecture University

1. Introduction
During the period from March 2001 to March 2006, the Bank of Japan (BOJ)
conducted quantitative monetary-easing policy (QMEP) to overcome a long-lasting
economic slump and deflationary pressures. This policy is an unconventional one, inthat the BOJ continued to inject ample liquidity into the economy, even though
short-term nominal interest rates were almost zero. Did such a massive monetary
injection stimulate real economic activity and prices? If so, what was the transmission
mechanism through which it had an impact? To address these two questions, this paper
assesses the effect of the QMEP using the vector autoregressive (VAR) methodology.
Measuring the effect of the QMEP implemented in Japan is of great significance forthe following two reasons. First, nobody can claim that the recent Japanese experience,or the situation where short-term nominal interest rates hit the zero lower bound, will
never happen again in any country in the future. Understanding the effect of the QMEP
in Japan, which is one of the possible strategies at zero interest rates, will be helpful ifsuch a situation should occur somewhere in the world. 1
Second, there is controversy as to whether expanding monetary base is effective whenshort-term nominal interest rates fall to zero. According to the traditional IS-LM model,
an increase in money supply has no effect if the interest rate is at its lower bound,because money and bonds are perfect substitutes (that is, a liquidity trap happens inthis case). Eggertsson and Woodford (2003) also show the ineffectiveness of the QMEP
by analyzing a dynamic general equilibrium model. On the other hand, Bernanke andReinhart (2004), Bernanke et al. (2004) and Clouse et al. (2003) argue that, even when

For alternative strategies at zero interest rates, see, e.g., Bernanke and Reinhart(2004), Bernanke et al. (2004), Clouse et al. (2003), Eggertsson and Woodford (2003),
Goodfriend (2000), Jung et al. (2005), McCallum (2000), and Svensson (2001, 2003).

1

1

short-term nominal interest rates are at zero, increases in monetary base might beeffective through the portfolio rebalancing effect and the signaling effect (we will
explain these two effects in the next section). This paper will contribute to sucharguments by empirically analyzing the Japanese experience in 2001–2006, which
provides a good opportunity to examine the impact of the further injection of liquidity atzero interest rates.
In this paper, we first estimate a minimal VAR model, which consists only of output,
prices, and the monetary policy instrument. This examination provides a preliminary
assessment about the effect of the QMEP on the two key macroeconomic variables,
aggregate output and prices. The estimation result shows that a quantitative-easing
shock increases output, but it has little effect on the price level.
This result raises the question of the transmission mechanism through which the
QMEP affected the output level. If the QMEP worked through the portfolio rebalancing

effect or the signaling effect, financial market variables would play an important role intransmitting these effects. Therefore, we next add each of several financial variables tothe above three-variable VAR to investigate the transmission mechanism of the QMEP.
The financial variables we consider are short- to long-term nominal interest rates, stock
prices, foreign exchange rates, and bank lending. From these four-variable VAR
estimations, we find that the QMEP was effective through the stock price channel.
Furthermore, in order to check the robustness of the stock price channel, we control
for the effects of several factors that the above four-variable VARs do not incorporate.
The following four factors are considered: increases in the BOJ’s outright purchase oflong-term government bonds; introduction of the BOJ’s purchase of stocks held by thecommercial banks; large increases in the value of exports; and large decreases in the2

outstanding amount of nonperforming loans (NPLs) of the banking sector. They might
have some effects on the economy, independent of increases in monetary base. Therefore,
we include each of these four factors in the VAR model to control for their possible
effects. The estimation results show that the stock price channel is robust even if wecontrol for these effects.
The remainder of the paper is organized as follows. Section 2 gives an overview of the
QMEP, discusses the possible effects of the QMEP, and surveys the related empiricalliterature. Section 3 explains our VAR models, identification strategy and data. Section
4 reports the estimation results for the three- and four-variable VARs. Section 5
estimates alternative VAR specifications that control for the effects of theabove-mentioned four factors. Section 6 offers concluding remarks.

2. Background2.1. Overview of the QMEPEven though the BOJ kept lowering the call rate during the 1990s and eventuallyadopted the zero-interest-rate policy in February 1999, the Japanese economy could not
escape from the prolonged stagnation and deflationary pressures that occurred from thebursting of the asset price bubble in the early 1990s. 2 , 3 In March 2001, the BOJ
introduced the QMEP to create a further monetary-easing environment under thesituation where the call rate was almost zero. The BOJ changed its operating target
The call rate is a short-term interbank rate, like the federal funds rate in the UnitedStates. The BOJ has used the uncollateralized overnight call rate as a policy instrument
except for the QMEP period.
3 In August 2000, the BOJ terminated the zero-interest-rate policy with the judgmentthat deflationary pressures receded due to the economic recovery, and it raised the callrate to 0.25. However, faced with the worldwide decline in the demand for IT goods andthe subsequent deterioration in Japan’s economy, the BOJ lowered the call rate to 0.15
in February 2001.
2

3

from the call rate to the current account balances (CABs) held at the BOJ, and it
continued to inject ample liquidity into the CABs beyond the level needed to maintainthe call rates at zero. 4 The target level of the CABs was publicly announced
immediately after every monetary policy meeting. Table 1 describes dates of policychanges (the left column) and announced targets of the CABs (the middle column). The
CAB target increased eight times from 5 trillion yen at the introduction of the QMEP to
30–35 trillion yen in January 2004.
[Table 1 around here]
At first, the BOJ promised that it would continue the QMEP until the year-on-year
rate of change in the consumer price index excluding perishables (core CPI) became
stably zero or above. Then, in October 2003, the BOJ provided a more detailed
description of the commitment: it would maintain the QMEP until (1) not only the mostrecently published core CPI inflation became zero or above, but also such tendency wasconfirmed over a few months, and (2) the future core CPI inflation was not be expected
to register below zero percent. 5 Since October 2005, core CPI inflation rates have been
zero or positive, which satisfied the first condition in the commitment statement.
Furthermore, the BOJ judged that future inflation rates would remain positive due to a
recent steady economic recovery, which satisfied the second condition in thecommitment statement. Under this environment, the BOJ terminated five years of the
QMEP in March 2006.

The CABs include not only reserve balances but also deposits of other financial
institutions (e.g. securities companies) that are not subject to the Reserve Requirement
System.
5 The BOJ also stated that these two conditions were the necessary condition and that,even if these two conditions were fulfilled, it might maintain the QMEP depending on
the economic situation.
44

2.2. Possible Effects of the QMEP and Related Empirical Literature
There are some empirical studies measuring the effect of the QMEP in Japan.
Bernanke et al. (2004), Okina and Shiratsuka (2004), and Oda and Ueda (2005) showthat the QMEP was effective in shifting the yield curve downward. In particular, Okina
and Shiratsuka (2004) and Oda and Ueda (2005) find that this downward shift of theyield curve was caused by the policy-duration effect. 6 The policy-duration effect meansthat the central bank’s commitment to keeping the policy rate at zero can stabilize
market expectations for the path of short-term interest rates and hence reduce
long-term interest rates. Therefore, their findings suggest that the QMEP worked
through the commitment to maintaining the zero-interest-rate policy.
Measuring only the policy-duration effect, however, is not enough to understand theeffects of the QMEP completely. In the QMEP period, the BOJ had provided abundantmoney by increasing the CAB target several times, even though short-term nominalinterest rates were already at the zero lower bound. As discussed in Bernanke andReinhart (2004), Bernanke et al. (2004), and Clouse et al. (2003), such further
expansions of base money might have an impact on economic activity through theportfolio rebalancing effect and the signaling effect.
The portfolio rebalancing effect stems from the assumption that there are several
assets that are imperfect substitutes for each other. Even if short-term securities andmoney are perfect substitutes because of a zero short-term interest rate, money andother assets may be imperfect substitutes. Then, the additional supply of base money
will cause investors to try to change their portfolios. This portfolio rebalancing will, inFujiki and Shiratsuka (2002), Okina and Shiratsuka (2004), and Oda and Ueda (2005)
also show evidence of the presence of the policy-duration effect for the period of thezero-interest-rate policy (from February 1999 to August 2000).
6

5

turn, raise prices (or reduce yields) of the assets, thereby stimulating economic activity.
The idea of the portfolio rebalancing effect is based on the classic literature such as
Brunner and Meltzer (1963) and Tobin (1969), in which multiasset models were used forthe analysis of monetary policy. Although the portfolio rebalancing effect might occur
even in normal times when nominal interest rates are positive, it would be more
important in the low-interest-rate period such as the recent Japanese case because theliquidity effect would diminish or disappear under such a situation. 7
The signaling effect occurs if an increase in monetary base reinforces the signal about
the central bank’s intention of keeping short-term interest rates at zero. In this case,
the QMEP can stabilize public expectations of the future paths of short-term interest
rates and thereby decrease longer-term interest rates. The lower interest rates will, in
turn, provide stimulus to economic activity. Note that the signaling effect plays a role inenhancing the policy-duration effect by increasing monetary base at zero interest rates.
The empirical literature investigating the effect of the further injection of monetarybase under a zero-interest-rate environment includes Oda and Ueda (2005), Kimura
and Small (2004), Kimura et al. (2002), and Fujiwara (2006). Oda and Ueda (2005) andKimura and Small (2004) limit their research to the effect on financial markets. Oda
and Ueda (2005) find that the expansion of the CABs was effective in lowering mediumto long-term yields of Japanese government bonds through the signaling effect. Kimura
and Small (2004) provide evidence that the expansion of the CABs caused lower yields
on high-grade corporate bonds through the portfolio rebalancing effect, while it had theadverse effects of lowering stock prices and raising yields on low-grade corporate bonds.
However, these two studies do not measure the effect on macroeconomic variables.
When the central bank supplies money to the private sector, the nominal interest rate
declines. This effect is called “liquidity effect” in this paper.

76Based on the VAR approach, Kimura et al. (2002) and Fujiwara (2006) examine theeffect of increases in base money on the two key macroeconomic variables: aggregate
output and prices. They show that an expansion of base money at zero interest rates
only slightly increases the output and price levels, suggesting little evidence for theeffectiveness of the QMEP. However, there are two problems in these articles. The firstproblem is that they include the pre-QMEP period as a part of the sample period. Theirsample period is 1985Q3–2002Q1 in Kimura et al. (2002) and 1985M1–2003M12 in
Fujiwara (2006), where Q and M denote quarterly and monthly frequencies of data,
respectively. Containing the pre-QMEP period would lead to the misleading result
because the QMEP is a different regime from the earlier monetary policy, in that the
BOJ’s operating target is changed from the call rate to the CABs. In addition, it is onlyin the QMEP period that the BOJ provided abundant money even at zero interest rates,suggesting that the pre-QMEP period contains less information about the effectivenessof increases in base money under a zero-interest-rate environment. To avoid theseissues, Kimura et al. (2002) estimate a VAR with time-varying coefficients (a BayesianVAR) and Fujiwara (2006) adopts a Markov switching VAR method. In spite of these
efforts, using only the implementation period of the QMEP seems to be the mostappropriate approach for the investigation of the impact of additional money at zerointerest rates.
The second problem in Kimura et al. (2002) and Fujiwara (2006) is that they do not
sufficiently examine the transmission mechanism of the QMEP. Other than themacroeconomic variables of prices, output, and the policy instrument, no variable isincluded in Kimura et al. (2002) and only the yield on 10-year government bonds isincluded in Fujiwara (2006). If the QMEP was effective through the portfolio

7

rebalancing effect or the signaling effect, then financial market variables would play animportant role in transmitting these effects. In this paper, we examine the transmission
mechanism of the QMEP more carefully and comprehensively by including several
financial variables in the VAR model. 8

3. VAR Model, Identification, and Data
Here we estimate two types of the VAR model to assess the effect of the QMEP. The
first model is a minimal one that includes only output, prices, and the monetary policy
instrument. This three-variable VAR provides a preliminary evaluation of the impact ofa quantitative-easing shock on the two key macroeconomic variables, aggregate output
and prices. As will be seen later, the estimated impulse response functions show that aquantitative-easing shock generates persistent increases in the output level.
However, its transmission mechanism is still unclear from the estimation of thethree-variable VAR. To find out the transmission mechanism, we next estimate several
four-variable VARs, each of which includes one of financial market variables as well as
the above three variables. The financial variables we consider are short- to long-term
nominal interest rates, stock prices, foreign exchange rates, and bank lending. 9
Through the portfolio rebalancing effect or the signaling effect, the QMEP might lower
nominal interest rates, raise stock prices, or depreciate the yen, all of which would
stimulate economic activity. In addition, commercial banks might increase their loans
Other literature studying the impact of the QMEP (but written in Japanese) includes
Sadahiro (2005, Chapter 9), Kamada and Sugo (2006), and Yamasawa (2006). Thesestudies also have the two problems of the other articles we have mentioned.
9 There is little VAR literature studying the impact of the Japanese monetary policy on
financial markets even for the period when short-term nominal interest rates are
positive. Braun and Shioji (2006) investigate the relationship between monetary policy
and the yield curve. Miyao (2000) includes foreign exchange rates in the VAR system
while Miyao (2002) uses stock prices.
88based on the additional money obtained by transactions with the BOJ in its open
market operations. For these reasons, we adopt these financial variables as possible
transmitting variables, and add them one-by-one to the VAR model.
The lag length is set equal to two months for all VAR models, which is selected basedon the Akaike information criterion for the baseline three-variable VAR (the maximum
lag length is set equal to six months). 10
To identify monetary policy shocks, we use a recursive strategy (that is, the Cholesky
decomposition). This is the simplest identification scheme and hence has been used inseveral studies in the VAR literature. As described in the previous section, this paper isthe first attempt to deal with the whole QMEP period and to investigate thetransmission mechanism comprehensively. Thus, it seems to be plausible to employ thiswidely used identification strategy for our VAR models. For the three-variable VAR, weplace the variables in order of output, prices, and the monetary policy instrument. Thisordering assumes that the BOJ sees current output and prices when it sets the policy
instrument, but that output and prices only respond to a policy shock with one lag. For
the four-variable VAR, each financial variable is ordered last, implying that financial
markets respond to a policy shock with no lag. 11 This ordering is essentially the same as
Christiano et al. (1996), Edelberg and Marshall (1996), Evans and Marshall (1998), andThorbecke (1997), which place the VAR variables in order of macroeconomic variables,
monetary policy variables, and financial variables.
Using alternative lag lengths of one, three, and six months did not essentially change
the results, but impulse response functions with six lags showed jagged shapes,
suggesting that the number of parameters to be estimated is too large relative to thenumber of observations.
11 We obtained similar results even when four-variable VARs were estimated withalternative six orderings, (P, Y, M, F), (Y, P, F, M), (M, Y, P, F), (M, F, Y, P), (F, Y, P, M),
and (F, M, Y, P), where P, Y, M, F denote prices, output, the monetary policy instrument,
and a financial variable, respectively.
10

9The frequency of our data is monthly and the sample period is from March 2001 to
February 2006. 12 The measure of output is the index of industrial production (IIP). The
measure of prices is the core CPI, which is the most crucial variable in the BOJ’s
commitment statement to maintain the QMEP. As the measure of the monetary policy
instrument, we use the BOJ’s target of the CABs. See the right column in Table 1 forvalues of the CAB target variable. When the announced target of the CABs is a range
rather than a level (six cases out of nine policy changes), we take a middle point of therange as a value of the CAB target variable. For the period from September 2001 to
November 2001 when the announced target of the CABs is “above 6 trillion yen”, we use
the monthly average of the actual daily CABs (8 trillion yen in September 2001, 8.7
trillion yen in October 2001, and 9.3 trillion yen in November 2001). 13 We also use themonthly average of the actual daily CABs for the period before March 2001, which serveas the initial data for the VAR estimation (4.8 trillion yen in January 2001 and 4.3
trillion yen in February 2001). Our data of nominal interest rates are the London
Interbank Offered Rates (LIBOR) with maturities of 1, 3, 6, and 12 months and theswap rates with maturities of 2, 3, 5, 7, and 10 years. The measures of stock prices,foreign exchange rates, and bank lending are, respectively, the Nikkei Stock Average,
the real effective exchange rate, and the total amount of loans and discounts of allbanks. 14 All data except for nominal interest rates are transformed in logarithm andWe exclude March 2006 from the sample period because the QMEP was implemented
for only a short time in this month (it terminated on March 9, 2006).
13 The daily data of the CABs are obtained from the Financial QUEST of Nikkei
Economic Electronic Databank System (NEEDS).
14 We checked the robustness of our results to the use of alternative measures, which
include the actual level of the CABs, yields on 10-year government bonds, the Tokyo
Stock Price Index (TOPIX), real stock prices (deflated by core CPI for both Nikkei Stock
Average and TOPIX), nominal effective exchange rates, and real bank lending (deflated
by core CPI). Even when we estimated the VARs using them one-by-one instead of abaseline measure, we obtained similar results.
1210

multiplied by 100. 15 More detailed information about the data is provided in the
appendix. Finally, Figure 1 displays the time series of the data used in this paper.
[Figure 1 around here]

4. Empirical Results
4.1. A Three-variable VAR
We first estimate the simplest three-variable VAR that consists of IIP, core CPI, andthe CAB target. Figure 2 displays all estimated impulse responses to a
one-standard-deviation shock to each variable. The first to third columns represent the
dynamic responses of the three variables to an IIP shock, a CPI shock, and aquantitative-easing shock, respectively. The solid lines represent the point estimates of
impulseresponsefunctions,

and

the

dottedlines

denote

plus

and

minus

two-standard-error bands computed by Monte Carlo simulation with 500 repetitions.
[Figure 2 around here]
There are three interesting points to be noted in Figure 2. First, a quantitative-easing
shock generates persistent increases in output. In response to a quantitative-easing
shock, IIP begins to increase from the second month and then peaks at the eighth
month (the response of IIP at the first month is negative, but very small andinsignificant). Notably, the positive response of IIP is statistically different from zero at
the seventh and eighth months. In the next subsection, we will examine thetransmission mechanism through which the policy shock increases the output level.
Second, the response of core CPI to a quantitative-easing shock is very small and notstatistically different from zero throughout the period. Although the BOJ introduced theWe estimate the VAR in levels, since it yields consistent estimates even if eachvariable is nonstationary (see Hamilton (1994, pp. 651–653)).

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QMEP in order to escape from deflationary environment, we cannot see the statisticalevidence that it succeeded in raising general prices. Third, the CAB target increases(decreases) in response to a negative (positive) core CPI shock, while it hardly reacts to
an IIP shock, implying that the BOJ placed more emphasis on prices rather than output.
This result is consistent with the BOJ’s commitment statement, in which the twonecessary conditions to terminate the QMEP refer only to the recent and expected
future rates of inflation, but do not refer to real economic activity.

4.2. Transmission Mechanism
Although we have found that the QMEP was effective in increasing the output level,
the transmission mechanism is still an open question. We here investigate thetransmission mechanism by estimating several four-variable VARs, each of which
includes one of financial market variables.
[Figure 3 around here]
Figure 3 displays the dynamic response of each financial variable to aquantitative-easing shock. Charts A to I present the estimated dynamic responses of
nominal interest rates with various maturities and Charts J to L provide those of stock
prices, foreign exchange rates, and bank lending, respectively. First note thatstandard-error bands become extremely wide from a certain period in most charts. This
would be due to a small number of observations relative to the large number ofparameters to be estimated in the four-variable VAR. Nonetheless, standard-error
bands appear to be relatively narrow for the early period (within about a year after apolicy shock). Therefore, we will focus our discussion on the short-run effect of the policy
shock.

12

The most notable result in Figure 3 is that a quantitative-easing shock raises stock
prices persistently (see Chart J). The positive response of stock prices is statisticallydifferent from zero for between the second and eighth months. Hence, it is likely that
the QMEP was effective through the stock price channel (we will later report all
impulse response functions for the four-variable VAR with stock prices included anddiscuss the existence of the stock price channel). On the other hand, Charts A to I showthat nominal interest rates do not decline in response to a quantitative-easing shock(only the 1-month rate declines in the first two months, but the effect is very small andinsignificant). Rather, positive responses are observed for long-term interest rates, andthe longer the maturity is, the larger the positive response is. In Chart K, aquantitative-easing shock depreciates the yen (note that declines in effective exchange
rates imply the depreciation of the yen). However, the depreciation is not statisticallysignificant throughout the period. In Chart L, bank lending decreases rather thanincreases in response to a quantitative-easing shock.
Summarizing these results, a quantitative-easing shock significantly raises stock
prices and slightly depreciates the yen, both of which would stimulate economic activity,
while the policy shock raises nominal interest rates and decreases bank lending, which
provide no stimulus. 16 These results suggest that the portfolio rebalancing effect

The Ministry of Internal Affairs and Communications started to release the
2005-base CPI from August 2006, instead of the 2000-base CPI. The 2005-base CPI
surprised markets due to a large downward revision of the CPI inflation rate for July
2006. The differences between the two measures also seem to be large for the QMEP
period. For example, the inflation rate for February 2006 computed from the 2000-base(seasonally adjusted) core CPI is 0.6 percent, but that computed from the 2005-base is
0.0 percent. When we used the 2005-base core CPI in the VAR estimation, instead of the
2000-base, we obtained different results in that a quantitative-easing shock persistently
lowered nominal interest rates with the 3-year and shorter maturities and it
persistently appreciated the yen. However, we rely on the results based on the
2000-base core CPI, because the BOJ and market participants perceived it as a truemeasure of general prices for the QMEP period and they behaved based on it (for1613

dominates both the liquidity effect and the signaling effect for the QMEP period,
because if the liquidity effect or the signaling effect occurs, nominal interest rates would
decline in response to a quantitative-easing shock. Based on the idea of the portfolio

rebalancing effect, we can interpret the estimation results as follows. With additional
money from the BOJ, investors (including banks) intended to decrease aninterest-bearing asset component (including bank lending) in their portfolios, increase
an equity component considerably, and increase a foreign asset component slightly.
Such investors’ behavior can be explained by the Japanese financial market conditions
for the QMEP period: the yields (prices) of interest-bearing assets were near zero (atvery high levels); stock prices were at the lowest levels since the late 1980s; domestic
financial assets yielded lower returns than foreign assets; and the banking sector
suffered from the NPL problem. Under these circumstances, investors might feel thatholding interest-bearing assets had a higher risk than holding equities or foreign assets,
and therefore they might seek to rebalance their portfolios in such a way that they held
more equities and foreign assets, and held less interest-bearing assets, when theyreceived further liquidity from the BOJ. In addition, the result that the response ofinterest rates is larger at the longer end of maturities implies that investors intended tosell more long-term interest-bearing assets than short-term assets, because of theconcern about rises in the future interest rates.
Our findings with regard to the effect of the QMEP on financial markets seem to bedifferent from Kimura and Small (2004) and Oda and Ueda (2005). Kimura and Small(2004) obtain the result that the QMEP raised stock returns (lowered stock prices)
through the portfolio-rebalancing effect. However, they measure only the one-day
example, if the 2005-base CPI had been available to the BOJ in March 2006, the QMEP
would not have been terminated in this month).
14

response of stock returns (prices) to the policy change. Furthermore, they do not control
for the effect of macroeconomic variables on the stock market. Oda and Ueda (2005) findthat the expansion of the CABs lowered medium- to long-term interest rates throughthe signaling effect. To decompose nominal interest rates into expectations and risk
premium components, they use a macrofinance approach in which a macroeconomic
model consists of the backward-looking versions of aggregate demand function,
aggregate supply function, and monetary policy rule. However, this simple andrestricted model may not be appropriate to describe the Japanese economy for the
QMEP period.
[Figure 4 around here]
We have found that it is better to include stock prices in the VAR model to capture thedynamics of the Japanese economy for the QMEP period. Figure 4 displays all impulse
response functions for the four-variable VAR, which consists of IIP, core CPI, the CAB
target, and stock prices. Interestingly, IIP shows a slower response than the stock priceresponse: in response to a quantitative-easing shock, IIP begins to increase from thesecond month and peaks at the ninth month, while stock prices begin to rise from thefirst month and peak at the sixth month. This result suggests that there exists the stock
price channel for the QMEP period. There are four possible channels through whichhigher stock prices boost the output level: an increase in consumption through a rise inhouseholds’ wealth (the wealth effect); an increase in investment through higher Tobin’sq; an increase in bank lending through a decline in the external finance premium ofborrowers (the balance sheet effect); and an increase in bank lending through an
improvement in the banks' capital-to-asset ratios. Considering the result that aquantitative-easing shock does not increase bank lending (see Chart L in Figure 3), we

15

suppose that the last two channels were very weak and either or both of the first twochannels mainly worked in the QMEP period.
There are three other remarkable findings in Figure 4. First, a quantitative-easing
shock raises core CPI, but the response is very small and insignificant throughout theperiod as with the case of the three-variable VAR, suggesting that the QMEP had little
effect on the price level. Second, the CAB target increases (decreases) not only inresponse to a negative (positive) core CPI shock but also in response to a negative(positive) stock price shock. Third, a positive shock to stock prices raises IIP with thestatistical significance in the second and third months.
[Table 2 around here]
Next, we conduct the variance decomposition analysis. Table 2 reports the results forthe four-variable VAR with stock prices included. The value in the table denotes thepercentage of the variance of the 2-, 6-, and 12-months-ahead forecast errors that are
accounted for by monetary policy shocks. The standard errors, computed by Monte
Carlo simulation with 500 repetitions, are reported in parentheses. Monetary policy
shocks account for a significant part of the volatility of IIP and stock prices (41% and
46% of the 12-months-ahead forecast error variance of IIP and stock prices,
respectively). On the other hand, monetary policy shocks account for only a small part ofthe volatility of core CPI (only 7% of the 12-months-ahead forecast error variance of core
CPI). Thus, monetary policy shocks are a major contributor to fluctuations of aggregate
output and stock prices, but they are unimportant for explaining the fluctuation ofgeneral prices.
[Table 3 around here]
Finally, we perform the Granger causality test. Table 3 reports the results of the16Granger causality test (F-test) for the four-variable VAR including stock prices. The left
column presents p-values associated with the test of the null hypothesis that the CAB
target does not Granger-cause IIP, core CPI, and stock prices. The right column provides

p-values for the test of the null hypothesis that stock prices do not Granger-cause IIP,
core CPI, and the CAB target. In the left column, the null hypothesis that the CAB
target does not Granger-cause stock prices can be rejected at the 1% significance level,
suggesting that there is a Granger-causality from the CAB target to stock prices. In theright column, the null hypothesis that stock prices do not Granger-cause IIP can berejected at the 6% significance level, suggesting that there is a Granger-causality fromstock prices to IIP. Therefore, the results of the Granger causality test complement
evidence of the stock price channel found from the estimated impulse response
functions.

5. Alternative Specifications
5.1. Controlling for the Effects of Alternative Policy Tools
In the QMEP period the BOJ conducted two unconventional policies other than
expanding the CABs. One is the increases in the outright purchase of long-term
government bonds (OPLTGBs). The target amount of the OPLTGBs per month was
gradually increased from 400 billion yen to 600 billion yen in August 2001, to 800 billion
yen in December 2001, to 1 trillion yen in February 2002, and to 1.2 trillion yen in
October 2002. The other policy is the purchase of stocks held by commercial banks. This
policy was conducted from November 2002 to September 2004, and the value ofpurchased stocks amounted to about 2 trillion yen in September 2004. According to the
public announcement, the BOJ did not aim to stimulate economic activity directly by17introducing these two policies. In fact, the BOJ expanded the amount of the OPLTGBs
to achieve the increased CAB target smoothly. The BOJ also began to purchase thestocks held by commercial banks to reduce the risk pertaining to the shareholdings ofthe banks, who suffered from the serious NPL problem. However, in spite of such BOJ’s
intentions, these two policies might have effects on output, prices or stock prices,
independent of the increases in the CAB target. Thus, in this subsection, we control forsuch possible effects so as to check the robustness of our results obtained in the previous
section.
[Figure 5 around here]
To this end, either the target amount of the OPLTGBs or the total amount of thepurchased stocks (both transformed in logarithm and multiplied by 100) is added to thefour-variable VAR with stock prices. 17 In each VAR model, an additional variable of thealternative policy measure is ordered just after the CAB target. Column (A) in Figure 5
displays the dynamic responses of the VAR variables to a quantitative-easing shock forthe five-variable VAR model, which consists of IIP, core CPI, the CAB target, stock
prices, and the OPLTGB target. We find that the shapes of the impulse response
functions do not change compared with those in the third column in Figure 4, and that
there is still evidence of the stock price channel. Column (B) in Figure 5 displays thecorresponding results for the five-variable VAR in which the OPLTGB target is replacedby the total amount of the purchased stocks. Inclusion of the purchased stocks appears
to change the shapes somewhat of the impulse response functions. In particular, thepositive responses of IIP and stock prices become much smaller. Nevertheless, they are
The BOJ reports the total amount of the purchased stocks for the period from
December 2002 to September 2004. We set its values before this period equal to zero (inlogarithm). We also set the values after this period equal to the value in September
2004, because the BOJ did not sell the stocks during the QMEP period.
17

18

statistically different from zero for some periods, and stock prices show an earlier
response than IIP. Therefore, we can still see evidence of the stock price channel even inthis case. 18,19

5.2. Controlling for the Effects of Alternative Contributors to Economic Recovery
The recent economic recovery in Japan seems to be attributable not only to the QMEPof the BOJ but also to the following two alternative factors: the large increases in thevalues of exports due to strong overseas economy; and the large decreases in theoutstanding amount of NPLs of the banking sector. In this subsection, we control for the
possible effects of these two factors to check the robustness of our results. For thispurpose, we add to the four-variable VAR with stock prices either the export values or
the outstanding amount of NPLs (both transformed in logarithm and multiplied by100). 20 The measure of exports is ordered first since it depends on foreign economic
activities (that is, treated as most exogenous), and the measure of the outstanding
amount of NPLs is ordered last since it is a financial sector variable (that is, treated as
most endogenous).
[Figure 6 around here]
Column (A) in Figure 6 displays the dynamic responses of the VAR variables to aWith regard to the impacts of these two alternative policy measures on output, prices,and stock prices, we could not find clear evidence indicating the presence of their effects.
19 To save space, here we do not report the results of the variance decomposition and theGranger causality test in table form. However, these results support the existence of thestock price channel for both five-variable VARs: in the variance decomposition analysis,monetary policy shocks account for at least more than 20% of the 12-months-ahead
forecast error variance of IIP and stock prices; in the Granger causality test, we canreject the null hypothesis that the CAB target does not Granger-cause stock prices andalso reject the null hypothesis that stock prices do not Granger-cause IIP atconventional significance levels.
20 Since the NPL data are only available for end-March and end-September in each year,
we use the interpolation method to construct the monthly data of NPLs.
18

19

quantitative-easing shock for the five-variable VAR with exports included, and column(B) displays the corresponding results for the five-variable VAR with NPLs included.
The estimated impulse response functions are somewhat different from the thirdcolumn in Figure 4: in column (A), the response of core CPI is larger and the response ofstock prices is more persistent; and in column (B), the responses of IIP, core CPI, andstock prices are smaller. However, for both VAR specifications, the positive responses of
IIP and stock prices are statistically different from zero for some periods and stock
prices exhibit an earlier response than IIP. Therefore, we can still see evidence of thestock price channel even if we control for the effects of exports and NPLs. 21
There are two other interesting findings from Figure 6. First, in column (A), a
quantitative-easing shock increases exports persistently (but the response is notstatistically significant throughout the period, except for the first month after a policy
shock). As seen in Chart K of Figure 3, a quantitative-easing shock depreciates the yen(but the depreciation is also insignificant). Therefore, the QMEP might be effective
through the exchange rate channel, though the evidence is not strong enough to besupported statistically. 22 Second, in column (B) a quantitative-easing shock generates
persistent declines in NPLs (but the response is insignificant throughout the period).
Interestingly, the negative response of NPLs appears to be slower than the IIP response,suggesting that the QMEP contributed to the decreases in NPLs by boosting the Japan’s
real economy.

21 The results of the variance decomposition and the Granger causality test also
support the presence of the stock price channel, except for one case (the null hypothesisthat stock prices do not Granger-cause IIP cannot be rejected even at the 10%
significance level for the five-variable VAR with exports).
22 Even when the exchange rate was added to this five-variable VAR, we obtained
results suggesting the existence of the exchange rate channel (but the evidence is notstrong enough to be supported statistically).

20

6. Concluding Remarks
Many macroeconomists and policymakers have discussed whether the further
injection of monetary base at zero interest rates is effective. This paper has addressed
this issue by examining the effect of the QMEP implemented in Japan. Using the VAR
approach, we have found that the QMEP stimulated real economic activity through thestock price channel: in the impulse response function analysis, a quantitative-easing
shock firstly raises stock prices and then increases the output level; in the variancedecomposition analysis, monetary policy shocks account for a significant part of thevolatility of output and stock prices; and in the Granger causality test, the target levelof the CABs Granger-causes stock prices, and stock prices in turn Granger-cause theoutput level. All of the above results suggest the existence of the stock price channel. We
have also found that evidence of the stock price channel is robust, even if we control forthe effects of two alternative policies of the BOJ (the increases in the outright purchaseof long-term government bonds and the introduction of the purchase of stocks held bycommercial banks) and even if we control for the effects of two alternative contributors
to recent economic recovery (the large increases in exports and the large declines inNPLs).
In the standard IS-LM model, an injection of base money has no effect under thecondition of liquidity trap. Our empirical evidence agrees with this liquidity trap
hypothesis in that we find no liquidity effect on nominal interest rates. However, wehave also found that an injection of base money at zero interest rates has significant
effect on aggregate output through the stock price channel. This finding suggests that
the IS-LM model, which considers only two assets of money and bonds, is oversimplified
to capture the real economic world at least in the recent Japanese case. Brunner and21

Meltzer (1963) and Tobin (1969) suggested various channels of policy shocks based on
multiasset models. Our empirical findings are consistent with the thinking of theseclassic articles.

22

Data Appendix
Variable
IIP

Core CPI

LIBOR Rates

Description

SourceSeasonally adjusted series,

Website of Ministry of Economy,

2000 average = 100

Trade and Industry

Seasonally adjusted series,

Website of Ministry of Internal

2000 average = 100

Affairs and Communications

JPY, end of month

Website(1, 3, 6, 12 months)ofBritishBankers’

Association

Swap rates

Yen–yen, average of offered and(2, 3, 5, 7, 10 years)

bid rates, end of month

Nikkei Stock Average

End of month

Website of BOJ

Real effective exchange rate

March 1973 = 100

Website of BOJ

Bank lending

Loans and discounts of banks,

Website of BOJ

seasonallyadjustedby

NEEDS Financial QUEST

using

Census X-12
BOJ’s stock purchases

Total amount of purchased stocks

Website of BOJ

reported in BOJ’s accounts, end ofmonth
Exports

Balance of payments, seasonallyWebsite of Ministry of Financeadjusted series
NPLs

Based on the definition in theWebsite of Financial Services

Financial Reconstruction Law, all

Agencybanks

23

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26

Japanese.

27

Table 1
Policy Changes during the QMEP Period
Dates of policy changes

Announced targets of the CABs

Values of the CAB target variable(trillion yen)(trillion yen)

19 March 2001

Introduction of QMEP

19 March 2001

5

5 (March 2001 to July 2001)

14 August 2001

6

6 (August 2001)

18 September 2001

Above 68 (September 2001), 8.7 (October 2001), 9.3 (November 2001)

19 December 2001

10–15

12.5 (December 2001 to September 2002)

30 October 2002

15–20

17.5 (October 2002 to March 2003)

30 April 2003

22–27

24.5 (April 2003)

20 May 2003

27–30

28.5 (May 2003 to September 2003)

10 October 2003

27–32

29.5 (October 2003 to December 2003)

20 January 2004

30–35

32.5 (January 2004 to February 2006)

9 March 2006

Termination of QMEP

On 1 April 2003, the BOJ raised the CAB target to 17–22 trillion yen for necessary adjustment due to theestablishment of the Japan Post.

28

Table 2
Percentage of Forecast Error Variance Explained by Monetary Policy Shock
PeriodVariable

2

6

12

IIP

1.14 (2.71)

16.48 (10.82)

40.89 (16.11)

Core CPI

3.75 (4.65)

2.79 (5.82)

6.67 (9.39)

CAB target

97.38 (6.06)

86.91 (11.53)

61.20 (17.40)

Stock prices

10.51 (8.42)

34.40 (13.19)

45.59 (14.34)

The table reports the percentage of the variance of the 2-, 6-, and 12-months-ahead forecast errors in
IIP, core CPI, the CAB target, and stock prices that are accounted for by monetary policy shocks. The
variance decomposition is conducted for the four-variable VAR, consisting of IIP, core CPI, the CAB
target, and stock prices. The standard errors are reported in parentheses.

29

Table 3
P-value for Granger Causality Test
From CAB target to:

From stock prices to:

IIP

0.21

IIP

0.05

Core CPI

0.06

Core CPI

0.24

Stock prices< 0.01

CAB target

0.39

The table reports p-values for the Granger causality test. The test is performed for the four-variable
VAR, consisting of IIP, core CPI, the CAB target, and stock prices. The left column presents p-values
for the test of the null hypothesis that the CAB target does not Granger-cause IIP, core CPI, and stock
prices. The right column presents p-values for the test of the null hypothesis that stock prices do not
Granger-cause IIP, core CPI, and the CAB target.

30Nominal interest rates (1)IIP and core CPI
110.0

100

Percent
0.3

99.5

0.25

1-month rate
3-month rate
6-month rate
12-month rate

IIP (left scale)Core CPI (right scale)

105.0

Nominal interest rates (2)Percent
3

100.0

99

0.2

95.0

98.5

0.15

1.5

90.0

98

0.1

1

85.0

97.5

0.05

0.5

80.0
2001:1

2002:1

2003:1

2004:1

2005:1

97
2006:10
2001:1

Stock prices

Yen

2002:1

2003:1

2004:1

2005:1

2006:1

Foreign exchange rates

2-year rate
3-year rate
5-year rate
7-year rate
10-year rate

2.5
2

0
2001:1

20,000150

Trillion yen
480

18,000

145
140

460

14,000

135
130

440

12,000125

10,000

120
115

420

110
105

400

100
95

380

16,000

8,000
6,000
4,000
2,000
0

2001:1

2002:1

2003:1

2004:1

2005:1

2006:1

90
2001:1

2002:1

2003:1

2004:1

2005:1

2006:1

360
2001:1

2002:1

2003:1

2004:1

2005:1

2006:1

2005:1

2006:1

Bank lending

2002:1

2003:1

2004:1Figure 1
Time Series Data

The figure displays the time series of the data used in the estimation. The vertical lines indicate themonths when the BOJ changed the CAB target.

31

IIP shock
Responses
of:

IIP

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

CPI shock
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Core CPI

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
0.12

0.12

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
0.12

0.1

0.1

0.1

0.08
0.06

0.08

0.08
0.06

0.04

0.04
0.02

0.04

0

0
-0.02

0.06

0.02
0
-0.02

-0.02

-0.04

-0.04

-0.06

0.02

-0.04

-0.06

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

CAB target

Policy shock
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

-0.06
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Figure 2
Impulse Response Functions for the Three-variable VAR

The figure displays the estimated impulse response functions for the three-variable VAR, consistingof IIP, core CPI, and the CAB target. The dotted lines denote two-standard-error bands.

32

A. Response of 1-month rate

B. Response of 3-month rate

C. Response of 6-month rate

D. Response of 12-month rate

0.012

0.012

0.012

0.008

0.008

0.008

0.004

0.004

0.004

0

0

0

-0.004-0.004-0.004-0.008-0.008-0.008-0.012-0.012

0.24
0.2
0.16
0.12
0.08
0.04
0
-0.04
-0.08
-0.12
-0.16

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48-0.0120 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

E. Response of 2-year rate

F. Response of 3-year rate

G. Response of 5-year rate
0.24
0.2
0.16
0.12
0.08
0.04
0
-0.04
-0.08
-0.12
-0.16

0.24
0.2
0.16
0.12
0.08
0.04
0
-0.04
-0.08
-0.12
-0.16

0.24
0.2
0.16
0.12
0.08
0.04
0
-0.04
-0.08
-0.12
-0.16
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

J. Response of stock prices

H. Response of 7-year rate
0.24
0.2
0.16
0.12
0.08
0.04
0
-0.04
-0.08
-0.12
-0.16

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

I. Response of 10-year rate
0.24
0.2
0.16
0.12
0.08
0.04
0
-0.04
-0.08
-0.12
-0.16

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

K. Response of exchange rates

10

2

8

1.5

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

L. Response of bank lending
0.6
0.4

6

1

4

0.5

2

0

0

0

-0.5

-0.2

-2

-1

-4

-1.5

-6

-2

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0.2

-0.4
-0.6

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Figure 3
Effects of Quantitative Easing Shocks on Financial Variables

Each chart displays the dynamic effects of a quantitative easing shock on a financial variable. The
impulse response function is estimated from the four-variable VAR, consisting of IIP, core CPI, theCAB target, and a financial variable. Financial variables used include nominal interest rates withvarious maturities, stock prices, foreign exchange rates, and bank lending. The dotted lines denotetwo-standard-error bands.

33

IIP shock
Responses
of:

IIP

0.1

0.1

0.1

0.1

0.08
0.06

0.08

0.08

0.06

0.06

0.04
0.02

0.04

0.04

0.04

0.02

0.02

0

0

0

-0.02

0
-0.02

-0.02

-0.02

-0.04

-0.04

-0.04

-0.04

-0.06
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

0.02

-0.06

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48-0.06
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Stock prices

0.12

0.08

-0.06

CAB target

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
0.12

0.12

0.06

Core CPI

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0.12

Stock price shock

Policy shock

CPI shock
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

10

10

10

10

8

8

8

8

6

6

6

6

4

4

4

4

2

2

2

2

0

0

0

0

-2

-2

-2

-2

-4

-4

-4

-4

-6

-6
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48-6
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48-6
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Figure 4
Impulse Response Functions for the Four-variable VAR

The figure displays the estimated impulse response functions for the four-variable VAR, consisting of
IIP, core CPI, the CAB target, and stock prices. The dotted lines denote two-standard-error bands.

34

(B)

(A)
Responses of:
IIP

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
0.12

0.12

0.1

0.1

0.08

0.08
0.06

0.06

Core CPI

0.04
0.02

0.04

0

0
-0.02

0.02

-0.02

-0.04

-0.04

-0.06

-0.06

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

CAB target

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Stock prices

10

10

8

8

6

6

4

4

2

2

0

0

-2

-2

-4

-4
-6

-6

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

OPLTGB target (left)/
Stock purchases (right)

8

80

6

60

4

40
20

2
0

0

-2

-20

-4

-40
-60

-6

-80

-8

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Figure 5
Effects of Quantitative Easing Shocks with Two Alternative Policy Measures Included

Column (A) displays the dynamic effects of a quantitative easing shock estimated from thefive-variable VAR, consisting of IIP, core CPI, the CAB target, stock prices, and the OPLTGB target.
Column (B) displays those estimated from the five-variable VAR, consisting of IIP, core CPI, the CAB
target, stock prices, and BOJ’s stock purchases. The dotted lines denote two-standard-error bands.

35

(B)

(A)
Responses of:
IIP

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6

1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
0.12

0.12
0.1
0.08

0.1
0.08
0.06

0.06

Core CPI

0.04
0.02

0.04

0

0
-0.02

0.02

-0.02
-0.04

-0.04

-0.06

-0.06
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

CAB target

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12

12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
10

10

8

8

6

6
4

4

Stock prices

2
0

2

-2

-2
-4

0

-4

-6

-6

-8

-8

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Exports (left)/

4

3

3

2

2

1
0

1

NPLs (right)

-1

0

-2

-1

-3

-2

-4
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48

Figure 6
Effects of Quantitative Easing Shocks with Exports and NPLs Included

Column (A) displays the dynamic effects of a quantitative easing shock estimated from thefive-variable VAR, consisting of IIP, core CPI, the CAB target, stock prices, and exports. Column (B)displays those estimated from the five-variable VAR, consisting of IIP, core CPI, the CAB target, stock
prices, and NPLs. The dotted lines denote two-standard-error bands.

36