FLOW OF FUNDS TO THE REAL ESTATE MARKET (TRILLIONS OF YEN) JUNE 1991
Credit Total Domestic Insurance unions & Foreign Non- Capital to real
banks companies depository banks banks market estate
Direct financing 59 3 5.5 0.6 50–55 Residual 120 (maximum 2)
Indirect lending activities through non-bank financial institutions
72 15 0.6 6.3
NOTE: Taken from Figure 5.6 in Cargill, Hutchison, and Ito (1997), who obtained the data from the Ministry of Finance.
the capital markets. It is important to note that a major share of non-bank financial institutions were specialized housing loan companies created as subsidiaries of banks in the 1970s (known as “jusen”). Therefore if we account for the indirect flow of funds from banks to real estate via non-banks, banks would account for the vast majority of the flow of funds to real estate (since 72 trillion yen is reported to be the flow of funds from banks to non-banks).
64 : MONEY, CREDIT AND BANKING
Table 1 also compares the behavior of foreign banks with that of Japanese banks. The flow of funds from foreign banks to real estate was 0.6 trillion yen compared with 59 trillion yen for domestic banks. This needs to be first normalized by a valid measure of their investments in Japan.4 The flow of funds to real estate as a share of loans extended in fiscal year 1991 is 0.114 for domestically licensed banks compared with only 0.039 for foreign banks in Japan. This adds to the evidence against the “good opportunities” demand view, under which we would expect foreign banks to behave similarly to domestic banks.
Bank-level evidence. A more stringent test can be carried out with individual bank balance sheet and income statement data. If the HK hypothesis were correct, then those banks that lost keiretsus would have excess funds. Under the alternative hypothesis, banks would actively seek funds to lend in the real estate sector, as the return on these loans was greater than the return on keiretsu loans. In this case, banks that increase their lending to the real estate sector would be expected to increase their deposit rates (and quantities of borrowed funds) compared with other banks. Regression results are shown in Table 2. Data on 150 banks for the years 1983–90 are used and following Hoshi (2001) all regressions are panel fixed effects that include year dummies and two lags of prefectural land inflation. Sample summary statistics are shown in Table A1. Columns (1)–(3) of Table 2 are estimated with the real-estate-loans-to-total-loans ratio (first difference) as the dependent variable.
Column (1) is a similar model to that shown in Table 9.1 in Hoshi (2001). Four lags of the keiretsu loan share (first difference) are included on the right-hand side. The results are significant, indicating that those banks that lost more keiretsu loans subsequently increased their real estate lending. The estimates suggest that for a 0.01 annual decrease (over 4 years) in a bank’s share of keiretsu loans to total loans, its lending in real estate increases by 0.0013 measured as a proportion of total loans. Column (2) adds four lags of the difference between loan and deposit rates to the model in column (1). Those banks that experienced falling margins subsequently increased their real estate lending, a point raised in the literature (e.g., Hoshi and Kashyap 2001; Ueda 1994).
Column (3) provides one test for whether banks that decreased their keiretsu loans and moved to real estate also increased their deposit rates to obtain funds. Therefore, column (3) includes the interaction between the four lags of keiretsu loans with the contemporaneous change in the deposit rate. Under the null hypothesis of “good op- portunities,” the coefficients will be negative. There is no support for this hypothesis. It is possible to test whether these banks decreased their lending rates, but under the HK hypothesis, banks with excess funds are also predicted to decrease their lending rates. Further, the selection effect leads to an empirical problem with the lending side
4. Foreign bank flow of funds data are only available at an aggregate level from the Bank of Japan but are sufficient for the purpose of this stylized comparison. Refer to “Detailed Data of Flow of Funds Accounts” available from the Bank of Japan, http://www.boj.or.jp/en. It provides information on total loans extended by domestically licensed banks and foreign-owned banks in Japan, respectively, in the section “Loans by Private Financial Institutions (Book Value)”.
NADA MORA : 65
because banks with excess funds may not maintain a constant portfolio of credit risks, and their average lending rate can rise.
Column (4) provides a more direct test. It shows the estimates from a model with the deposit interest rate as the dependent variable. On the right-hand side are the four lags of the keiretsu loan shares. The results, which are significant, indicate that those
BANK REGRESSIONS: REAL ESTATE LOANS AND DEPOSIT RATES 1983–90
Dependent variable: First difference of: Dependent variable:
Real estate loans to total loans First difference of:
Deposit interest rate (1)a (2) (3) (4)
Regressors Prefecture land inflation, lag 1b 0.0086∗∗ 0.0086∗∗ 0.0078∗∗ −0.0024∗∗
(0.0016) (0.0016) (0.0016) (0.0006) Prefecture land inflation, lag 2 −0.0013 −0.0008 −0.0005 0.0015∗
(0.0017) (0.0017) (0.0017) (0.0006) Year 1983 −0.0025∗ −0.0024 −0.0023 −0.0095∗∗
(0.0012) (0.0012) (0.0015) (0.0004) Year 1984 −0.0034∗∗ −0.0015 −0.0038∗∗ −0.0062∗∗
(0.0011) (0.0013) (0.0013) (0.0004) Year 1985 −0.0017 −0.0017 −0.0022 −0.0049∗∗
(0.0012) (0.0013) (0.0013) (0.0004) Year 1986 0.0016 0.0026 0.0014 −0.0056∗∗
(0.0012) (0.0013) (0.0013) (0.0004) Year 1987 0.0035∗∗ 0.0037∗∗ 0.0029 −0.0113∗∗
(0.0012) (0.0012) (0.0017) (0.0004) Year 1988 −0.0004 0.0000 −0.0004 −0.0079∗∗
(0.0011) (0.0012) (0.0015) (0.0004) Year 1989 0.0008 0.0007 0.0010 −0.0058∗∗
(0.0011) (0.0012) (0.0013) (0.0004) Keiretsu loan share, first diff, lag 1 −0.0163 −0.0111 −0.0060 0.0019
(0.0088) (0.0093) (0.0100) (0.0033) Keiretsu loan share, first diff, lag 2 −0.0464∗∗ −0.0401∗∗ −0.0253∗ 0.0222∗∗
(0.0110) (0.0117) (0.0126) (0.0041) Keiretsu loan share, first diff, lag 3 −0.0358∗∗ −0.0365∗∗ −0.0272 0.0115∗∗
(0.0114) (0.0121) (0.0146) (0.0043) Keiretsu loan share, first diff, lag 4 −0.0341∗∗ −0.0329∗∗ 0.0139 0.0247∗∗
(0.0109) (0.0112) (0.0160) (0.0041) Interest on loans–Interest on deposits
to total assets (first diff, lag 1) −0.1348 (0.1159)
Interest on loans–Interest on deposits to total assets (first diff, lag 2)
Interest on loans–Interest on deposits to total assets (first diff, lag 3)
Interest on loans–Interest on deposits to total assets (first diff, lag 4)
Deposit rate (first diff) 0.1373 (0.1037)
Loan rate (first diff) −0.1193 (0.0812)
Deposit rate (first diff) ∗ Keiretsu loan share (first diff, lag 1)
Deposit rate (first diff) ∗ Keiretsu loan share (first diff, lag 2)
66 : MONEY, CREDIT AND BANKING
Dependent variable: First difference of: Dependent variable:
Real estate loans to total loans First difference of:
Deposit interest rate (1)a (2) (3) (4)
Regressors Deposit rate (first diff) ∗ Keiretsu loan
share (first diff, lag 3) 2.0725
(1.4613) Deposit rate (first diff) ∗ Keiretsu loan
share (first diff, lag 4) −1.6570 (1.3753)
Loan rate (first diff) ∗ Keiretsu loan share (first diff, lag 1)
Loan rate (first diff) ∗ Keiretsu loan share (first diff, lag 2)
Loan rate (first diff) ∗ Keiretsu loan share (first diff, lag 3)
Loan rate (first diff) ∗ Keiretsu loan share (first diff, lag 4)
Constant 0.0034∗∗ 0.0032∗∗ 0.0043∗∗ 0.0053∗∗ (0.0009) (0.0009) (0.0011) (0.0003)
Observations 1,200 1,200 1,200 1,200 Number of Banks 150 150 150 150 R2 0.11 0.12 0.13 0.49
NOTES: This table presents results from fixed effects regressions. Standard errors are reported in parentheses. Asterisks (∗ ) and (∗∗ ) indicate significance at the 5% and 1% levels, respectively. a Column (1) is a similar model to that in Hoshi (2001) Table 9 column 1. b Prefecture land inflation refers to the land inflation in the prefecture (among 47 prefectures) in which a bank is headquartered.
banks that lost keiretsu loans subsequently decreased their deposit rate relative to other banks, suggesting that they had excess funds. Therefore, the bank-level results do not support the hypothesis that there were good opportunities in real estate that rationalized a bank shift away from keiretsus.5
One potential criticism is that the results in Table 2 do not account for the different types of banks (although fixed effects are included and variables such as keiretsu loans are normalized by each bank’s total loans). There may be institutional and size differences between city banks, long-term credit banks, trust banks, and regional banks that are not fully accounted for, and the results may be generated by a subset of the banks. For example, and as shown in the summary statistics in Table A1, city banks, followed by long-term, and trust banks, are the largest banks. To account for this possibility, the basic regression in column (1) was repeated including dummies for the five different bank types (random effects had to be used instead of fixed effects because of the inclusion of bank-type dummies). The relation between a bank’s loss of keiretsu loans and its increase in real estate lending is robust. In the interest of brevity, all of the robustness checks discussed in the remainder of this section are available on the author’s website. I also repeated the regression using only city banks, long-term and trust banks, and regional banks, respectively. The results do not appear to be
5. Other results (available on author’s website, http://alum.mit.edu/www/namora) regressed quantity variables (such as the log first difference of total deposits and “borrowed money”) on the four lags of the change in the keiretsu loan share as before. The results confirm that banks that lost keiretsu loans subsequently decreased their deposits as well.
NADA MORA : 67
driven by the larger city, long-term, and trust banks, and are, in fact, stronger among the regional banks (although the degrees of freedom are reduced among the former because there are only 11 city banks and 10 long-term and trust banks). Finally, the results are robust to the different bank sizes.6
To address whether banks predominantly increased lending to the real estate market, sought other loans, invested in government bonds, or looked for foreign opportunities, I begin by regressing the (change) in the amount of loans to small firms as a share of total loans on the same variables shown in column (1) of Table 2. There is mixed evidence on the sign of the keiretsu loan shares. However, the sum is negative, indi- cating that banks which lost more keiretsu loans subsequently increased their lending to small firms. Banks could also increase their holdings of government bonds. I there- fore replace the dependent variable with the change in government bonds (as a share of total assets) in a bank’s own account. The results are mixed but the overall sum is negative, suggesting that those banks that lost keiretsu loans subsequently increased their holdings of government bonds. However, the results for government bonds and lending to small firms are weaker than the results for real estate lending.
A third option available to a bank facing an exogenous fall in keiretsus’ demand for loans is to look for foreign opportunities. Unfortunately, the Nikkei NEEDS data set does not contain data on Japanese banks’ foreign loans or foreign investments. I therefore follow Hoshi (2001) in using the proportion of a bank’s branches located overseas as a proxy measure. There is no statistical relationship between a bank’s loss of keiretsu loans and a subsequent increase in its foreign activity as measured by its overseas branches.
Finally I regress loans to sectors other than real estate on the same right-hand-side variables. The sectors are construction, non-bank financial institutions, agriculture, forestry & fishing, individuals & others, local governments, mining, manufacturing, services, transportation & telecommunication, utilities, and wholesale & retail in- dustries. In fact, only loans to real estate increase when keiretsu loans decrease. The results confirm that keiretsu loans tended to be in sectors with “large” firms such as manufacturing, transportation & telecommunication, utilities, and wholesale & retail industries. Loans in these sectors were significantly and positively related to the lags of keiretsu loans. In contrast, there was little or no effect on loans in agriculture, forestry & fishing, individuals & others, local governments, mining, and service industries.
Firm-level evidence. In this section, I examine whether firms chose to reduce bank loans using firm-level accounting data from the Development Bank of Japan (DBJ) Corporate Finance data set. This data set comprises companies listed on the Tokyo, Osaka, and Nagoya stock exchanges.7 An eligible-to-issue time-varying dummy was
6. Regressions were run separately by bank size, with big banks defined as those belonging to the upper 85 percentile of the fraction of aggregate real bank assets over the period (23 banks), medium banks defined as those in the 60 to 85 percentile (37), and small banks accounting for the remaining banks (90). In fact, in a regression including the interaction of a bank’s total assets with the (lagged) change in keiretsu loan share on the right-hand side, the estimates are insignificant except for the first lag with a positive coefficient. That is, the shift to real estate is stronger among the smaller banks that lost keiretsu loans.
7. Note that the data were cleaned up for duplicate accounting periods in a given year by taking the average and, if there was a missing year, by taking the average over the previous and following years.
68 : MONEY, CREDIT AND BANKING
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