This paper empirically analyzes the relationship between regional deposits and demographic changes. Using different types of deposit data from Japan which has experienced a sharp increase in the number of retirees, we provide clear evidence that an increase in the dependency ratio is negatively correlated with overall deposits but positively with the most liquid deposits.Regional deposits, Demographic changes, Panel cointegration, Panel DOLS

Nagayasu, Jun

English

Research Papers in Economics

Regional Deposits and Demographic Changes
Jun Nagayasu￿
April 2011
Abstract
This paper empirically analyzes the relationship between regional deposits
and demographic changes. Using di⁄erent types of deposit data from Japan
which has experienced a sharp increase in the number of retirees, we provide
clear evidence that an increase in the dependency ratio is negatively correlated
with overall deposits but positively with the most liquid deposits.
JEL classi￿cation: E1, F4
Keywords: Regional deposits, Demographic changes, Panel cointegration,
Panel DOLS
￿Associate Professor. Mail address: University of Tsukuba, Graduate School of Systems and
Information Engineering, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573 JAPAN; Tel/Fax: +81 29
853 5067; Email: nagayasu@sk.tsukuba.ac.jp.
11. Introduction
Japan￿ s population has been aging rapidly, and the proportion of the elderly
(especially those aged 65 and over) reached 23.1% in 2010, the highest rate among
advanced economies. With the potential signi￿cant e⁄ect of demographic changes
on the economy, some studies have been conducted. For example, Horioka (2010)
reported evidence of the dis-saving behaviors of retirees using Japanese survey data
(the Family Income and Expenditure Survey) which allow one to identify the amount
of retirees￿savings. In this paper, we look into a similar issue but from a di⁄erent
angle; particularly, the relationship between the dependency ratio and the di⁄erent
types of aggregate savings (rather than retirees￿savings alone) using a di⁄erent data
set and advanced statistical methods for nonstationary panel data.
2. The Statistical Model
Since deposits are part of ￿ money￿by de￿nition, our general speci￿cation is anal-
ogous to that used to analyze the demand for regional money (Mulligan and Sala-i-
Martin 1992), but is constructed for nonstationary variables.1
mit = ￿i + ￿it + ￿t + ￿Xit + uit (1)
￿Xit = vit
where subscripts i (i = 1;:::;47) and t (t = 1975;:::;2007) represent prefecture
and time. The m is a vector of real regional deposits and X is a vector of explanatory
variables. Following the standard money demand theory, X includes real income (y)
and the interest rate (i), and m is expected to be a positive (negative) function of
y (i). The relationship between m and y should also re￿ ect the recent discussion
of weak (negative) economic growth contributing to the dis-saving practices. In
addition, the dependency ratio (demog) is included in X and is expected to be
negatively associated with deposits when there is a strong tendency of dis-saving
behaviors. Finally, this equation is very comprehensive and includes ￿xed e⁄ects
(￿i), a time dummy (￿t) and a time trend (t), and the vector of errors wit (wit =
(uit;v0
it) and E[wit;wjt￿k] = 0 where i 6= j) is assumed to follow the functional
central limit theorem.
1While not reported here, our data are found to be nonstationary using the panel ADF unit
root test.
23. Data
Our data set comprises regional deposits, regional income, interest rates and a
dependency ratio for 47 prefectures from 1975 to 2007. Unlike previous studies, our
data on deposits and income are region-speci￿c, and deposits in the Japanese private
banks have several categories; Demand, Time & Savings, and Total Deposits.2 In
addition, we use deposits in the Yucho Bank (Japan Post Bank Company) which
was privatized in 2007 and has been the largest ￿nancial institution in terms of
deposit amounts. These deposits are referred to as Post O¢ ce Deposits, and the
sum of Total and Post O¢ ce Deposits as All Deposits here.
The data have been collected from several sources. Deposits in private
banks are obtained from the Bank of Japan, and those of the Yucho Bank from the
Kinyu Koho Chuo Committee (Central Council for Financial Services Information).
Regional income data are obtained from the Japan Cabinet O¢ ce. Both deposit and
income data are expressed in terms of per capita and real terms using the population
and the Consumer Price Index by region respectively, both of which are from the
Ministry of Internal A⁄airs and Communications (MIAC).
In addition, we use two types of interest rates; the money market rate and
government yield (10 year maturity), collected from the International Financial Sta-
tistics of the International Monetary Fund. A di⁄erent type of interest rate is used
to check the robustness of our ￿ndings since the nominal short-term rate has stayed
around zero percent since 1995.
Finally, the dependency ratio is calculated using population and labor force. Our
de￿nition of the labor force is the number of the employed aged 14 years old or older,
and thus that of the dependent population is obtained by subtracting the number
of the employed from the population. The labor force data are from the MIAC.
Due to the absence of regional speci￿c data, the interest rates and the dependency
ratio are at the country level, and thus are expected to capture part of the common
trends across prefectures.
4. Results
Prior to analyzing the impact of demographic changes on deposits, we study
whether a long-run relationship exists in our model using a panel cointegration
method. For this purpose, we employ a panel approach based on Johansen￿ s multi-
variate cointegration test (1991) applied to deposit (money) equations for individual
2Total Deposits consist of Demand, Time & Savings, Public, and Financial Institutions￿De-
posits.
3prefectures. A panel test statistic combined from individual Johansen tests can be
constructed as per Fisher (1932):
￿2
N X
i=1
ln(pi) ￿ ￿
2(2N)
where N is the number of prefectures. The p is the p-value obtained from the
Johansen test applied to each region, and is calculated on the basis of MacKinnon,
Haug and Michelis (1999). This statistic is shown to be distributed as Chi squared.
Our results in Table 1 often show the absence of cointegration in the stan-
dard deposit speci￿cation with income and the interest rate. A cointegrated rela-
tionship generally exists when the dependency ratio is included.
Furthermore, the deposit function is estimated using the panel Dynamic
OLS (DOLS) approach (Nelson and Sul, 2003). This approach is ￿ exible to accom-
modate di⁄erent types of heterogeneity among regions (as shown in equation (1)),
and their Monte Carlo experiments show that cointegration vector estimators from
the panel data are more precise than those from the single equation DOLS.
We focus on the deposit function, which is cointegrated and consists of
income, the interest rate, and the dependency ratio. Table 2 shows that income and
the dependency ratio are often signi￿cant. As expected, income elasticity is positive
and ranges from zero to 0.5 (Table 2), and this result remains unchanged even when
di⁄erent deposits are employed. The dependency ratio is negatively associated with
many types of deposits, especially with less liquid ones such as Time & Savings
Deposits. Post O¢ ce Deposits which are not classi￿ed in terms of liquidity are also
negatively associated with the dependency ratio with a similar magnitude to that
of Total Deposits. This implies that an increase in the proportion of retirees was
associated with a reduction in savings in general since the birth rate has stayed low
(at less than 2.0 since 1975) from 1975 onwards (1.3 in 2008). However, interestingly
the dependency ratio is positively associated with Demand Deposits￿ the most liquid
of this kind￿ although this positive e⁄ect is o⁄set by a negative e⁄ect in other types
of deposits. This implies that people have shifted part of their money from Time &
Savings Accounts to Demand Deposits.
5. Conclusion
This paper examines whether demographic factors a⁄ect consumers￿holding liq-
uid and safe assets. We showed that an increased dependency ratio tends to decrease
total deposits. This ￿nding has international implications since persistent Japanese
4current account surpluses have often been argued as resulting from domestic sur-
pluses (i.e., high savings). If this aging trend continues, Japanese current account
surpluses will likely decline. Furthermore because the aging phenomenon is shared
by a number of countries including China, Singapore and South Korea, changes in
current account behaviors in Japan may well herald a similar phenomenon in many
other countries.
References
Fisher, R. A., 1932. Statistical Methods for Research Workers, Liver & Boyd,
Edinburgh, 4th edition.
Horioka, C. Y., 2010, The (dis)saving behavior of the aged in Japan, Japan and
the World Economy 22, 151-158.
Johansen, S., 1991, Estimation and hypothesis testing of cointegration in Gaussian
vector autoregressive models, Econometrica 59, 1551-1580.
MacKinnon, J., G., Haug, A. A., Michelis, L., 1999, Numerical distribution
functions of likelihood ratio tests for cointegration, Journal of Applied Econometrics
14, 563-577.
Mark, N. C., Sul, D., 2003, Cointegration vector estimation by panel DOLS
and long-run money demand, Oxford Bulletin of Economics and Statistics 65(5),
655-680.
Mulligan, C. B., Sala-i-Martin, X., 1992, US money demand: surprising cross-
sectional estimates, Brookings Papers on Economic Activity 2, 285-329.
5Variables Test type None At most 1 At most 2 At most 3
Trace 95.32 66.89 71.08 --
Max-eigen 64.42 46.64 71.08 --
Trace 69.36 55.78 66.43 --
Max-eigen 44.69 37.65 66.43 --
Trace 213.4** 125.0* 129.5** 74.4
Max-eigen 124.5* 43.27 115.2 74.4
Trace 122.6* 80.65 81.25 88.78
Max-eigen 69.05 35.63 50.49 88.78
Trace 287.0** 117.6 35.36 --
Max-eigen 238.2** 142.0** 35.36 --
Trace 219.3** 44.72 38.09 --
Max-eigen 271.5** 43.85 38.09 --
Trace 805.3** 489.5** 304.7** 31.3
Max-eigen 369.5** 254.5** 384.4** 31.3
Trace 513.1** 333.6** 167.3** 17.99
Max-eigen 224.8** 230.6** 234.8** 17.99
Trace 89.43 89.35 36.57 --
Max-eigen 38.3 103.6 36.57 --
Trace 45.12 58.96 28.04 --
Max-eigen 16.9 72.16 28.04 --
Trace 176.0** 65.59 32.16 30.23
Max-eigen 166.8** 68.74 33.53 30.23
Trace 91.06 42.43 20.27 16.93
Max-eigen 82.48 52.12 27.14 16.93
Trace 369.0** 133.0** 98.81 --
Max-eigen 317.6** 98.41 98.81 --
Trace 404.9** 125.4* 114.2 --
Max-eigen 373.2** 78.77 114.2 --
Trace 330.05** 128.4* 67.67 --
Max-eigen 276.7** 120.3* 67.67 --
Trace 666.0** 267.2** 99.73 51.01
Max-eigen 485.6** 238.7** 101.6 51.01
Trace 118.5* 75.51 20.61 --
Max-eigen 83.14 104.7 20.61 --
Trace 106.2 84.59 29.99 --
Max-eigen 59.54 104.9 29.99 --
Trace 590.7** 468.7** 257.0** 80.5
Max-eigen 172.6** 281.9** 258.9** 80.5
Trace 501.0** 239.7** 124.2* 40.46
Max-eigen 323.5** 171.9** 144.3** 40.46
TimeSavingD, Income,
Govt
DemandD, Income, Call
DemandD, Income, Govt
DemandD, Income, Call,
Demog
DemandD, Income, Govt,
Demog
TimeSavingD, Income, Call
Notes: Full sample. “D” stands for deposits, e.g., DemandD means demand deposits. AllD is the sum of
TotalID and Post OfficdD. P-values to evaluate the hypothesis for the Johansen test are based on MacKinnon,
Haug and Michelis (1999), and those values are used to construct Fisher type statistics which follow the Chi-
square distribution. The constant and time trend are included in the cointegrating vector for the Johansen test.
Asterisks ** and * indicate statistics significant at the one and five percent significance levels respectively.
The maximum lag length is two. The deposit equation for Post OfficeD with Demog does not include the call
rate since no evidence of cointegration is reported.
AllD, Income, Call, Demog
AllD, Income, Govt, Demog
Table 1. Fisher Panel Cointegration Test Based on the Johansen Method
Post OfficeD, Income, Call
Post OfficeD, Income, Govt
Post OfficeD, Income,
Demog
Post OfficeD, Income,
Govt, Demog
AllD, Income, Call
AllD, Income, Govt
TimeSavingD, Income,
Call, Demog
TimeSavingD, Income,
Govt, Demog
TotalD, Income, Call
TotalD, Income, Govt
TotalD, Income, Call,
Demog
TotalD, Income, Govt,
Demog
6[A] [B]
Demand Deposits
Income 0.049 [0.146] 0.144 [0.142]
Call -0.025 [0.013]+ --
Govt -- 0.014 [0.014]
Demog 0.054 [0.012]** 0.053 [0.011]**
Time & Savings Deposits
Income 0.462 [0.133]** 0.421 [0.136]**
Call 0.002 [0.013] --
Govt -- -0.024 [0.013]
Demog -0.157 [0.010]** -0.149 [0.010]**
Total Deposits
Income 0.392 [0.120]** 0.432 [0.116]**
Call -0.001 [0.015] --
Govt -- 0.004 [0.018]
Demog -0.098 [0.009]** -0.096 [0.009]**
Post Office
Income 0.416 [0.089]** 0.369 [0.088]**
Call -- --
Govt -- -0.039 [0.009]**
Demog -0.084 [0.008]** -0.083 [0.008]**
All Deposits
Income 0.369 [0.080]** 0.364 [0.080]**
Call 0.004 [0.009] --
Govt -- -0.018 [0.010]
Demog -0.097 [0.006]** -0.090 [0.006]**
Heterogeneous time trend Yes Yes
Common  time effect Yes Yes
Table 2. Cointegration Vector Estimation by Panel DOLS for Regional Money
Notes: Full sample. The regional money equation is estimated by the Nelson and Sul method
(2003). Asterisks ** and + indicate statistic significance at the one and ten percent significance
levels respectively. The panel DOLS utilizes the first order lead and lag variables.
7

Cointegration vector estimation by panel DOLS and long-run money demand,

Regional deposits and demographic changes

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