OSIPP Discussion Paper : DP-2010-E-008

Financial Linkages and Business Cycles of Japan:
An Analysis Using Financial Conditions Index
October 14, 2010
Jun-ichi Shinkai
Specially Appointed Researcher, Osaka School of International Public Policy (OSIPP)

Akira Kohsaka
Professor, Osaka School of International Public Policy (OSIPP)【Keywords】financial conditions index (FCI), financial linkages, international businesscycle transmission, vector autoregressions, global financial crisis【JEL codes】E32, E44, G17【Abstract】This paper constructs a financial conditions index (FCI) for Japan, using
vector autoregressions (VAR) and impulse responses functions, and then investigate theeffect of financial shocks on business cycles of Japan. Based upon our estimation
results, we found that, in addition to the trade channel, the financial linkage played asignificant role in Japanese business downturn caused by the current global financial
crisis, and that its effect has come mainly from fallen stock prices and exchange rate
appreciation, but not from credit crunch or the financial accelerator mechanism as had
been the case in the recession in the early 1990s.
Correspondence author: Akira Kohsaka, OSIPP, Osaka University, 1-31 Machikaneyama-cho, Toyonaka, Osaka
560-0043, Japan. Email: kohsaka@osipp.osaka-u.ac.jp. We gratefully acknowledge financial support from the Japan
Society for the Promotion of Science program, grant-in-aid for Scientific Research (20223003). This paper waspresented at the 12th International Convention of the East Asian Economic Association, 2-3 October, 2010, Seoul. The
authors are grateful to Discussant Hyoungsik Noh and seminar participants for helpful comments. All remaining
errors are ours.

11．Introduction
The Japanese economy lost about 9 percent of real GDP during her 17 months of economic
recession 1 since the U.S. subprime loan crisis in 2007. Dichotomizing channels of international
business cycle transmission, Lane and Milesi-Ferretti (2010) argue that the crisis has beentransmitted through a financial channel in the case of Europe and through a trade channel in Japan. Is
this true that there is no transmission through the financial channel in the case of Japan?
As to international transmission of business cycles there have been a lot of arguments focusing on
the trade channel. For instance, once popular decoupling hypothesis argues that the internationaltransmission of U.S. recessions would be limited because of the declining exports to the U.S. market
as a share of world trade. In the current crisis, however, the collapse of the U.S. subprime loan
market hard hit U.S. investment banks, and the shock was transmitted to worldwide financial
institutions that hold securitized financial products related to the subprime loans. As Krugman(2008) refers to International Financial Multiplier, the financial channel of international businesscycle transmission has recently attracted more attention.
The purpose of the present paper is to clarify the relationship between financial conditions and real
economy across business cycles in Japan since the 1980s, estimating Financial Condition Index (FCI,
hereafter). Particularly, in view of increasing global financial integration, we focus on a financial
linkage to see to what extent the current global financial turmoil affects Japanese financial
conditions and then her real economy.
While FCI measures the effect of representative financial variables such as interest rates, stock prices
and exchange rates on the real economy, the recent research on FCI includes a variable for credit
markets in addition. Swinston (2008) and Beaton, Lalonde and Luu (2009) construct FCI on the
United States, and Guichard, Haugh and Truner (2009) on the four economies as Euro area, Japan,
the United States and the United Kingdom, using lending attitudes of financial institutions as avariable for credit markets. In constructing FCI for Japan, there are reasons to include a variable for
credit market conditions.
For one thing, reviewing Japanese business cycles since the 1980s 2 , it has been pointed out that,while large deteriorations in corporate stock as well as foreign exchange markets negatively affected
1 Economic and Social Research Institute (ESRI) preliminarily reported on June 8, 2010, that thecontraction phase (from peak to trough) is 17 months from October 2007 to March 2009.
2 There are the recession by Yen appreciation in 1985, the bubble collapse of the stock price and realestate price in 1991, the sharp appreciation of Yen in 1995 and the decline of the stock price causedby the U.S. IT bubble collapse in 2001 etc.
2the real economy, banks’ nonperforming loans as well as resulting credit crunch, too, did so
independently in her “lost decade.”
For another, IMF (2008) reveals that, historically comparing between economic recessions with andwithout preceding financial conditions, the decline in GDP tends to be larger and the duration ofrecession to be longer in the former case, and that the difference tends to be larger particularly withdeterioration in banking sector than those in securities and foreign exchange markets. As such, we
can grasp the role of financial conditions more comprehensively by including a credit market
variable into FCI. Accordingly, the present research constructs FCI covering some credit market
variable as well as interest rates, asset prices and foreign exchange rates. With the FCI, we analyze
the role of financial linkage across Japanese business cycles since the 1980s.
We can summarize our findings as follows: First, after the 1980s, financial shocks in the recession
starting from 1991 were the largest in terms of its depth, duration and cumulative effects, and they,
not the real factor, were a main cause of the recession. On the other hand, in the recession due to theglobal financial crisis in 2008, the negative effect of the real economic factor was indeed
unprecedentedly large, but the financial shock was not only larger in depth than that in the case of
1991 recession, but also almost as large in size (or depth and duration).
Second, relative contributions of individual financial shocks are diverse across recessions. In
particular, while stock prices, credit market conditions and foreign exchange rates gave negative
impacts altogether in the 1991 recession, credit market conditions did not in the current crisis/
recession. Low leverage ratios of Japanese financial institutions and larger deterioration of corporate
demand for external funds than tightening banks’ lending stance appear to be among backgroundfactors for the above.
The structure of the paper is as follows: In Section 2, the procedure to construct FCI using a VAR
model and the data to be used are explained. In Section 3, the VAR model is estimated and its
impulse response function is discussed. Then, using these results, FCI is estimated. Based on the FCI,
first, the impact of financial conditions on real GDP growth, and then that of individual financial
variables constituting the FCI across Japanese business cycles are discussed. Section 4 concludes
and summarizes the paper.

2．Methodology
2.1．Construction of FCI3

In prior studies we can find four types of methods to construct FCI, using; 1) a large-scale
macroeconometric model as in Guichard, Haugh and Truner (2009), 2) reduced-form
aggregate-demand equations like IS and Phillips curves as in Goodhart and Hofmann(2001) and
Gauthier, Graham and Liu (2004), 3) a principal component analysis as in Montagnoli and
Napolitano (2001) and Hatzius, Hooper, Mishkin, Schoenholtz and Watson (2010), and 4) a VAR
model as in Swiston (2008) and Beaton, Lalonde and Luu (2009) 3 . In this paper, we use the VAR
method of type 4) to construct FCI.
An advantage of using the VAR method is that we can avoid an endogeneity problem. Since
financial market and real economic variables are essentially endogenous, if we assume that thefinancial variables are exogenous in the estimation model for FCI, the estimators would be biased.
With the VAR method treating all variables as endogenous, we can obtain exogenous financial
shocks and avoid the endogeneity problems.
Another advantage the VAR method has is that, because the parameters of impulse responses areused as weights, we can analyze dynamic responses of real economy to financial shocks. The othermethods use average values of financial effects on real economy as weights, so that we cannot trace
their dynamic effects on real economy.
We follow a VAR method in Swiston (2008) to construct FCI in this paper. First, we estimate theVAR model with financial variables and real GDP and then calculate the structural shocks offinancial variables and the parameters of impulse responses of real GDP. Second, FCI is constructedby combining the financial shocks and the parameters of the impulse responses as weights asfollows:m⎛ n⎞
FCI t = ∑ ⎜ ∑ wij utj−i ⎟j =1 ⎝ i = 0⎠

wij is a parameter for an i quarters-lagged impulse response of real GDP growth rate to a shock of afinancial variable j and ut-ij is a structural shock of a financial variable j. Namely, FCIt is acombination of impulse response parameters multiplied by shocks across time lags. In this paper,
assuming that financial shocks persist for two years (eight quarters), we set 8 lags for FCI.

2.2．Data
As for the data for FCI, we select representative indicators of financial conditions such as lending
standards of banks, interest rates and asset prices. Specifically, financial variables for FCI are
3 For more details in the advantages and disadvantages of each method, see Gauthier, Graham andLiu (2004).
4

selected in view of the availability of data, the being frequently used variables in prior studies andthe statistical significance of the impulse responses of real GDP growth to their shocks.
For lending standards of banks that stand for loan-supply conditions in credit market, we use asurvey, “Lending Attitude of Financial Institutions” in TANKAN of Bank of Japan (BOJ). Swiston(2008) uses a survey on financial institutions, but the TANKAN is on nonfinancial corporations.
Although there is a survey on financial institutions that is “Lending Policies” in Senior Loan Officer
Opinion Survey on Bank Lending Practices at Large Japanese Banks (SLOOS) of Bank of Japan, it
covers the period only after 2000, which is too short to estimate FCI. Accordingly we use thisTANKAN survey for lending standards. While the U.S. survey covers four types of lending, i.e.
commercial and industrial loans, commercial real estate loans, residential mortgage loans andconsumer credits, the TANKAN survey classifies loans by scale of firms (all, large, medium andsmall) and by industry (all, manufacturing, non-manufacturing and individual). We use loans on all
firms and all industry.
As to lending standards of banks, the TANKAN survey has some advantages to the SLOOS in quality
and characteristics of data. First, the TANKAN covers not only longer periods, but also larger
samples in size than the SLOOS does. In fact, the former covers about 10000 nonfinancial firms,
while the SLOOS covers only 50 banks. Thus the TANKAN appears more stable and reliable. Second,
TANKAN data may reflect loan-demand conditions of firms because they evaluate banks’ lending
attitudes based on their own conditions about internal funds, running costs and investment
opportunities. Thus, it appears that the TANKAN, capturing both loan-demand as well as loan-supply
conditions, can more properly measure liquidity constraints of firms and supply-demand conditionsof credit market.
As to interest rates for FCI, we include a short-term money market rate and a long-term government
bond rate. As the short-term rate we use three-month “Tokyo Interbank Offered Rate (TIBOR)”. We
select TIBOR instead of an “Uncollateralized Call Rate” which is a policy rate of BOJ, because theformer reflects expectations of interbank markets 4 . Since the uncollateralized call rate is notavailable before August 1985, we use the “Collateralized Call Rate” adjusted by spreads between
uncollateralized and collateralized before August 1985 only for a sensitivity check. As the long-term
interest rate we use a “Newly Issued Government Bonds Yield (10 Years)”. Both the short-term andlong-term interest rates are deflated by inflation in Consumer Price Index (CPI) 5 .

4 We use the call rate only for a robustness check.
5 We also estimate FCI using “Interest Rate Spread” as a term premium instead of the long-term

interest rate for a robustness check.
5

As to asset prices for FCI, finally, we use a stock price and a foreign exchange rate. As the stock
price we use a “Tokyo Stock Price Index (TOPIX)” in Tokyo Stock Exchange (TSE) and as theexchange rate we use a “real effective exchange rate” downloaded from the BOJ website. The stock
price is also deflated by inflation in CPI 6 .
Prior FCI literature uses a residential price index such as “S&P Case-Shiller Home price indices” asasset prices. But a similar residential price data is not available in Japan. Likewise, “Land Price” of
Ministry of Land, Infrastructure, Transportation and Tourism (MLITT) is annual data and “All Urban
Land Price Index” of Real Estate Economic Institute is biannual data. Thus we simply do not use
data on real estate prices in this paper. Also, although a market of real estate investment trust (REIT)
started in the 2000s, the “Tokyo Stock Exchange REIT index” is available only after 2003, whose
sample period is too short to use for our purpose.
Some FCI literature include other variables such as a Commercial Paper (CP) spread of nonfinancial
corporations as default risk, a mortgage premium, a volatility of stock price, an investment gradebond yield, an investment grade and a high yield bond spread etc. The CP data, “Newly Issued
Domestic Commercial Paper (3 months)” can be downloaded from the BOJ website, but it isavailable only after 1994. About mortgage premium, Japan Housing Finance Agency started issuing
mortgage backed securities (MBS) in 2001, but their sample period is not long enough to estimate
VAR. Financial and Economic Statistics Monthly of BOJ stopped publishing the data on bonds(investment grade and high yield) in 2004, and, although the bond data are maintained by Japan
Securities Dealers Association, they are not available as time series data now. Thus we do not use
these data 7 .
The variables for real economy are real GDP and GDP deflator. Both are downloaded from the CAO
website. Finally, this paper includes a crude oil price (West Texas Intermediate ($)) downloaded
from International Financial Statistics of IMF in order to avoid the “price puzzle” pointed out by
Sims (1980).

3．Estimation
3.1．VAR Model

6 We estimate FCI using “Stock Yield” in TSE for a robustness check.
7 About the CP spread, the investment grade bond yield and the bond spread, we estimate FCI

respectively, though the sample periods are limited.
6

In this subsection, we estimate a VAR model with 8 variables (OP, REER, TIBOR, GB, TOPIX, LS,
INFL, GDP) over the period from the first quarter of 1980 (1980Q1) to the fourth quarter of 2009(2009Q4). OP stands for the crude oil price, REER for the real effective exchange rate of Yen,
TIBOR for the real Tokyo Interbank Offered Rate (three-month), GB for the 10-years real
government bond yield, TOPIX for the real equity return of Tokyo Stock Price Index and LS for thelending standards of banks. INFL stands for the log-difference of GDP deflator and GDP for the real
GDP growth.
The structural shocks and the impulse responses of the financial variables are calculated using
Cholesky decomposition, when the order of variables in VAR is important 8 . We place, first, the oil
price as the most exogenous because it would be least affected by the financial conditions andbusiness cycles in Japan. Then, since our goal is to examine the effects of the financial shocks onreal GDP growth, the next are the financial variables and the last are the real economic variables,
assuming that they are most endogenous. Among the financial variables, the first is REER because it
is affected mostly by the international economic environment, and the next the short-term andlong-term interest rates because they are significantly affected by the central bank―although they
are not policy rates themselves. And then follow the stock price and the lending standards of banks
which are affected by the domestic business cycles 9 .
Most variables are in log-difference, but the interest rates are differenced and the lending standard ofbanks is in level due to stationarity. An AIC and a SBIC show that 1 lag is appropriate for the VAR
model, but a likelihood ratio test shows that 2 lags are appropriate. In this paper, to capture the broad
effects of financial shocks on the real economy, we adopt 2 lags 10
Figure 1 shows the impulse responses of real GDP growth to the financial shocks. Central solid lines
stand for dynamic responses of GDP growth and upper and lower dotted lines for confidence bands
with 1 standard error, calculated by Monte Carlo Integration. The effects of the financial shocks on
GDP growth are as follows. First, an appreciation shock of exchange rates (REER) decreases real
GDP growth significantly, but the effect works only right after a shock and is not persistent. A

8 As to the order of the variables, we check the robustness by estimating VAR with different orders.

The replacement of the order in the VAR models hardly affects the results.
9 There are structural VAR models with identifying restrictions as in Christiano, Eichenbaum andEvans (1999), Sims and Zha (1996) and Bernanke and Mihov (1999), usually used for monetary
policy analysis. We do not adopt this approach because financial variables in this paper are more
extensive than in these analyses, and then also, it is generally difficult to presume signs and effectsof parameters on restrictions in advance.
10 We check the robustness by estimating the VAR model with different lags. The results of the VAR
model with 3 and 4 lags are hardly different from the results of the basic model.
7

upward shock of the short-term interest rate (TIBOR) decreases GDP growth significantly and ispersistent, while that of the long-term interest rate (GB) promptly decreases GDP growth but isshort-lived. A positive shock of the real equity return (TOPIX) immediately increases real GDP
growth significantly, and the effect is persistent. Also, a positive shock in the lending standards ofbanks (LS) not only significantly increases GDP growth immediately, but also the effect is persistent.
Table 1 reports the results of a forecast error variance decomposition on real GDP growth over thewhole sample period. The values show (average) relative contributions of the financial variables toforecast error variances of real GDP growth 8 quarters after a shock. First, a GDP’s own shockaccounts for about 64% of GDP growth variance and it is the largest. As for the financial variables,
TOPIX and LS account for about 7% of GDP growth variance respectively, and REER, TIBOR and
GB for about 4% each. This suggests that the effects of the stock price and the lending standards ofbanks were relatively stronger than those of the other financial variables over the period.

3.2．FCI and Business Cycles in Japan
Here, using the VAR results obtained in the previous subsection, we calculate FCI by combining theexogenous shocks of the financial variables with their impacts on real economy (real GDP growthrate)―the parameters of the impulse responses―as weights. Namely the FCI measures the total
effect of exogenous financial shocks on real GDP growth.
Figure 2 shows the FCI calculated as above and real GDP growth. Both are expressed in four-quarter
moving averages to be easily seen. Shadowed periods in the figure represent contraction phases(from peak to trough) of business cycles determined by Economic and Social Research Institute(ESRI). We investigate the effects of the FCI on the business cycles particularly focusing oncontraction phases (recessions, hereafter). Since the values of the FCI measure the effects of thefinancial shocks on real GDP growth, their positive (negative) values mean that these shocks
increased (decreased) real GDP growth.
In the recession started from 1985, the financial conditions that had increased real GDP growth byabout 0.4% until then deteriorated to decrease the growth by about -0.3% from 1985. The cumulative
effect over the recession was about -0.55% only and not so large, though.
In contrast, in the recession from 1991, the deterioration of the FCI from 1990Q3 preceded thedecline of the real economy and had significant negative effects that peaked at -0.85% (1992Q3). In
addition, the duration of the effects extended to 12 quarters, the longest since 1980, and accordingly
the cumulative negative effect amounted to -6%.

8

In the recession from 1997, the financial conditions had negative effects from 1998Q1. While its
duration was 10 quarters and the cumulative effect on GDP growth amounted to -2.95%, the declineof the real economy exceeded the financial deteriorations in the period. In the recession from 2001,
the FCI turned negative from 2001Q2 and remained so even after the real economic recovery.
Consequently the duration extended to 12 quarters, which was as long as that ofn the 1991 recession,
thereby the cumulative effect amounting to -2.93%.
Finally, in the crisis of 2008, the financial conditions have had negative effects since 2008Q1. While
the FCI did not become positive within our sample period, their cumulative effect amounted to-3.45% over 8 consecutive quarters.
We can summarize the above estimation results as follows. First, since 1980, the negative effects offinancial shocks in the recession starting from 1991 were the largest in terms of its depth (impactsize), duration and cumulative effects, and then financial factors were dominant for the recession.
Comparing with these, the negative effects in the 1997 recession were half as large in terms ofduration and cumulative effects, while the initial impact was almost comparable, and also the real
economic factors overwhelmed the financial factors then. The 2001 recession was also led by thereal factors and then, although the financial shocks continued to impact negatively until 2004, they
were overwhelmed by the strong real economic recovery.
Second, indeed the negative effects of the real factors were unprecedented in the recession caused by
the global financial crisis since 2008, but the negative financial shocks also took place almost
simultaneously and it is not necessarily clear whether the real factors led the recession. The initial
negative effects of the financial shocks were larger than those of the 1991 recession at least in depth
and the cumulative impact were larger than that of the 1997 recession. Therefore, the role of thefinancial shocks was no small in the current recession, or rather it was almost comparable to that in
the 1991 recession of financial bubble bursts.

3.3．Effects of Individual Financial Variables
In this subsection, in addition to the total effect of financial conditions on business cycles measured
by the FCI, we examine relative contributions of individual financial variables across recessions.
Figure 3 shows the individual effects of the financial shocks on real GDP growth using the VAR
model for the FCI. These effects are expressed in four-quarter moving averages and shadowed
periods in the figure represent contraction phases (from peak to trough) of business cycles
determined by Economic and Social Research Institute (ESRI). In the following, we investigate the9cumulative effects of the individual financial shocks on real GDP growth within each recession.
Table 2 shows the magnitudes of their negative effects in each recession. Bold types show the largest
negative effect in the recession.
In the recession from 1985, REER and TIBOR had negative effects. Their cumulative effects on real
GDP growth are -1.2% and -0.6%, respectively 11 . Despite these negative effects, the positive effectsof the stock price and lending standard of banks offset those effects in this recession, and thus thevalues of FCI were close to zero.
In contrast, all the financial variables except TIBOR had negative effects on real GDP growth in therecession from 1991. The cumulative effect of the stock price, -2.2%, was the largest, and thenfollow those of the lending standards of banks, the exchange rate and the government bond rate. In
the 1991 recession, the financial shocks were main factors of business contraction and theircumulative effects reduced real GDP growth by -4.33%.
In the recession from 1997, LS and TIBOR had negative effects. The lending standard shock reduced
real GDP growth by -1.96% and was the largest. TIBOR also had a -0.56% negative effect and
TOPIX followed. In the recession from 2001, although TOPIX and TIBOR had negative effects of-0.68% and -0.6% respectively, the total cumulative effect remained to be only -0.07% because thepositive effects of the other variables offset.
Finally, in the recession from 2008, all the financial variables except LS had negative effects on real
GDP growth. The cumulative effects of TOPIX, REER, GB and TIBOR were -1.21%, -0.86%,-0.61% and -0.07%, respectively. In particular, TOPIX, REER and GB deteriorated sharply as soon
as the Japanese economy entered recession. The effect of the short-term rate was negative in the
beginning, but it turned positive in the midst of the recession. Although the lending attitudes ofbanks in the “TANKAN” survey were generally tightened, the estimated effects of their exogenous
shocks remained positive on real GDP growth as contrast with the 1991 recession.
Upon examining individual effects of financial shocks as above, we find that the channels throughwhich these financial shocks affect GDP growth are not uniform across recessions. Throughout oursample period, either foreign exchange rates, stock prices or credit market variables (lending
standards of banks) plays a leading role, but short term interest rates were also one of the main
channels of transmission in the 1985, 1997 and 2001 recessions. In particular, in the 1991 recession
11 On the other hand, GB, TOPIX and LS had positive effects in this recession, i.e. 0.3%, 0.75% and0.65%, respectively.
10

led by the financial factors, stock prices, credit market and foreign exchange rates affected economic
growth negatively altogether and in this order of importance. In contrast, however, in the case of thecurrent global financial crisis, although our observation period is limited to until 2009Q4, stock
prices, foreign exchange rates and long term interest rates were the transmission channels ofnegative impacts in this order of importance, but credit markets were not this time.
The above results give implications on whether and how the financial linkage works in thetransmission of international business cycle in Japan in 2008. According to the models in Krugman(2008) and Devereux and Yetmen (2009), the deleveraging of highly-leveraged financial institutions
generate a decline of asset prices as well as deterioration of their balance sheets, leading to ashrinkage of credit markets or credit crunch. In the case of Japan this time, however, while thedecline in asset prices (stock prices) is witnessed, the effects of LS on growth remained positive
mostly between 2005 and 2009, suggesting no credit crunch.
Why no credit crunch? One possibility is that the pre-crisis leverage level of Japanese financial
institutions was not high. If we look at the balance sheets of Japanese banks since the latter half ofthe 1990s, loans and domestic equity holdings in their asset portfolios have decreased continuously.
The shares of foreign equity holdings and financial derivatives have increased, but were small on
one hand, and government bond holdings have increased by four times as large. That is, there was noincrease in leverage in Japanese banks throughout the 2000s, thereby they did not get involved with
the international trend of deleveraging. The other possibility is that because of severe collapse of realdemand, corporate demand for investment finance declined larger than tightening of lending
standards. Equipment investment of private corporate sector declined by 20 percent in a year fromthe peak of the former half of 2008. These abrupt drops of investment finance demand may be
another reason why credit market conditions did not affect growth negatively.

4．Summary and Conclusion
In the literature on the international transmission of business cycles in the current global financial
crisis, it has been often discussed that the linkage through trade channels played a more significant
role than the financial linkage in the case of Japan. We wonder at the outset of this paper if this isreally the case and, if not, how the financial linkage works.
In order to examine the role of the financial linkage in the business cycle transmission in the case ofJapan, we have constructed an FCI by estimating a VAR model and analyzed the relationshipbetween financial conditions and business cycles in Japan since the 1980s. Then we found: First,

11since 1980, the negative effects of financial shocks in the recession starting from 1991were thelargest in terms of its depth, duration and cumulative effects, and then financial factors were
dominant for the recession. Comparing with these, the negative effects in the 1997 recession werehalf as large in terms of duration and cumulative effects, while the initial impact was almost
comparable, and also the real economic factors overwhelmed the financial factors then.
Second, indeed the negative effects of the real factors were unprecedented in the recession caused by
the global financial crisis since 2008, but the negative financial shocks also took place almost
simultaneously and it is not necessarily clear whether only the real factors led the recession. The
initial negative effects of the financial shocks were larger than those in the 1991 recession at least in
depth, and the cumulative impacts were larger than in the 1997 recession. Therefore, the role of thefinancial shocks was no small in the current recession, or rather it was almost comparable to that in
the 1991 recession of financial bubble bursts, contrary to the argument that the trade linkage is more
important than the financial linkage in the international transmission of the global financial crisis in
the case of Japan.
Third, upon further examining individual effects of financial shocks as above, we find that thechannels through which these financial shocks affect GDP growth are not uniform across recessions.
Throughout the period of our analysis, either foreign exchange rates, stock prices or credit market
variables play a leading role. In particular, in the 1991 recession led by the financial factors, stock
prices, credit market and foreign exchange rates altogether affected economic growth negatively. In
contrast, in the case of the current global financial crisis, stock prices, foreign exchange rates andlong term interest rates were the transmission channels of negative impacts in this order ofimportance, but credit markets were not this time. This is how the financial linkage works in thecurrent crisis.
Why no credit crunch? One possiblity is that the pre-crisis level of leverage of Japanese financial
institutions was not that high, thereby they did not get involved with international trend ofdeleveraging. The other possibility is that because of severe collapse of real demand, corporate
demand for investment finance declined larger than tightening of lending standards, so that credit
market conditions did not affect growth negatively.

12

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13

Table 1：Relative Contribution to Real GDP Growth Variance (%)
Variables

REER

TIBOR

GB

TOPIX

LS

GDP

Contribution

3.97

4.63

3.72

6.65

6.75

64.77

This table is the result of variance decomposition that shows relative contributions of financial and othershocks to real GDP growth variance. We show the values 8 quarters after a shock. REER stands for the realeffective exchange rate of Yen, TIBOR for the real short-term interest rate (three-month), GB for the reallong-term interest rate (10 years), TOPIX for the real equity return and LS for the lending standard ofbanks.

Table 2：Cumulative Effects of Individual Financial Shocks across Recessions (%)
Variables

REER

TIBOR

GB

TOPIX

LS

Recessions:
1985-86-1.2%

1991-93-0.96%-0.6%-0.41%-2.2%-1.43%-1.96%

1997-99-0.56%-0.08%

2001-02-0.6%-0.68%

2008--0.86%-0.07%-0.61%-1.21%

This table shows the effects of the financial shocks on real GDP growth in each recession.
Bold types stand for the largest effect in the recession. REER stands for the real effective
exchange rate of Yen, TIBOR for the real short-term interest rate (three-month), GB for thereal long-term interest rate (10 years), TOPIX for the real equity return and LS for thelending standard of banks.

14

Figure 1：Impulse Responses of Real GDP Growth to the Financial Shocks

Response of GDP to REER shock

Response of GDP to TOPIX shock

0.50

0.50

0.25

0.25

0.00

0.00

-0.25

-0.25

-0.50

-0.50
0

1

2

3

4

5

6

7

0

Response of GDP to TIBOR shock

1

2

3

4

5

6

7

6

7

Response of GDP to LS shock

0.50

0.50

0.25

0.25

0.00

0.00

-0.25

-0.25

-0.50

-0.50
0

1

2

3

4

5

6

7

6

7

0

1

2

3

4

5

Response of GDP to GB shock
0.50

0.25

0.00

-0.25

-0.50
0

1

2

3

4

5

This figure shows the impulse responses of real GDP growth to the financial shocks. A solid line in the center is apoint estimate of the impulse responses and top and bottom dotted lines are confidence bands with 1 standard error.
REER is the real effective exchange rate of Yen, TIBOR is the real short-term interest rate (three-month), GB is thereal long-term interest rate (10 years), TOPIX is the real equity return and LS is the lending standard of banks.

15

Figure 2：FCI and real GDP growthThis figure shows FCI (Financial Conditions Index) and real GDP growth, both in four-quarter moving averages.
Shadowed periods in the figure represent contraction phases (from peak to trough) of business cycles determined byEconomic and Social Research Institute (ESRI). The value of FCI is a magnitude of effect of the financial conditions
on real GDP growth and the positive (negative) financial conditions increase (decrease) real GDP growth.

16Figure 3：Effects of financial shocks on real GDP growthThis figure shows the effects of financial shocks on real GDP growth. All variables are in four-quarter moving
averages. Shadowed periods in the figure represent contraction phases (from peak to trough) of business cycles
determined by Economic and Social Research Institute (ESRI). The value of each shock is a magnitude of effects ofthe financial shocks on real GDP growth and a positive (negative) financial shock increases (decreases) real GDP
growth. REER is the real effective exchange rate of Yen, TIBOR is the real short-term interest rate (three-month), GB
is the real long-term interest rate (10 years), TOPIX is the real equity return and LS is the lending standard of bank.

17