Bulletin of Monetary Economics and Banking, Vol. 22, No. 1 (2019), pp. 69 - 86
ANALYSING THE DEMAND FOR FINANCIAL ASSETS
IN INDONESIA
Eliyathamby A Selvanathan1, Saroja Selvanathan2
1Economics and Business Statistics Discipline, Griffith Business School, Griffith University,
Queensland, Australia.
2Economics and Business Statistics Discipline, Griffith Business School, Griffith University, Queensland, Australia. Email: s.selvanathan@griffith.edu.au
ABSTRACT
This paper analyses the demand for three important financial assets (i.e. bank deposits) in Indonesia: demand deposits, saving deposits, and time deposits. We use a system- wide approach to consumption economics to perform the analysis in the long and short run. The estimation results reveal that a) generally, the wealth elasticity for saving deposits is above one, for time deposits is below one, and for demand deposits it varies from 0.5 (in the short run) to 1.1 (in the long run); b) the own interest rate coefficients are statistically significant and positive, as expected; and c) in the long run, while the assets of demand deposits and time deposits and of saving deposits and time deposits are pairwise substitutes, the assets of demand deposits and saving deposits are pairwise complements.
Keywords: Financial assets; Demand deposits; Saving deposits; Time deposits; Wealth elasticity; Interest rate.
JEL Classifications: G11; G21.
Article history: |
|
Received |
: November 9, 2018 |
Revised |
: December 31, 2018 |
Accepted |
: March 21, 2018 |
Available online : April 30, 2019
https://doi.org/ 10.21098/bemp.v22i1.982
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I. INTRODUCTION
Financial assets such as bonds, certificates, stocks, and bank deposits are considered intangible assets. Investors shift their investments regularly from one asset to another. For example, when interest rates on deposits increase, the stock market is impacted, since investors in the stock market are more likely to deposit funds in commercial banks. Therefore, an understanding of consumer behaviour in the context of financial assets is important to macroeconomic policymakers in the government and the banking industry. For example, to determine the desired interest rate of a particular bank deposit, bank managers need to know the level of substitutability/complementarity between that bank deposit and other financial assets, including other bank deposits.
The focus of this paper is on only one type of financial asset, namely, bank deposits. We choose bank deposits because they play an important role in the economy via bank loan investment channels. Because we examine three types of bank
Brainard and Tobin (1968) introduced work on modelling consumer demand for different types of financial assets based on the multivariate stock adjustment model. The disadvantage of using this model is that large number of parameters must be estimated. Later, Taylor and Clements (1983) used a
Bank deposits play an important role in the Indonesian economy. Bank deposits as a percentage of the gross domestic product in Indonesia steadily increased from 8.2% in 1982 to 42.3% in 1998, steadily decreased to 29.5% by 2008, and then started to increase again, reaching 33.7% in 2015. Generally, the banking industry raises funds from the public and delivers it back to the community, especially in the form of loans to businesses, and such investments lead to greater production, employment, and export opportunities in the economy. Indonesia is no exception. For example, a recent World Bank (2010, Ch. 2) report states that the number of bank branches in Indonesia increased by 70% from 2000 to 2010 and the number of ATMs trebled, which has had a positive influence in remote parts of the country and increased the intermediation of inputs (deposits) into outputs (loans), benefitting the Indonesian economy. Therefore, a comprehensive analysis of the demand for bank deposits is crucial for policymaking in the banking industry and the Indonesian government in general.
This paper attempts to answer a number of research questions, such as the following: 1) Are wealth and the interest rates for demand deposits, saving deposits, and time deposits in Indonesia elastic or inelastic? 2) Are there any differences in the wealth and interest rate elasticities for bank deposits in the short and long run?
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3)Is there any substitutability or complementarity between the three types of bank deposits?
We perform a conditional analysis using a
This paper is organized as follows. Section II presents the demand models for financial assets. Section III describes the data. Short- and
II. DEMAND MODEL FOR FINANCIAL ASSETS
Let Ai be the nominal value of a financial asset i=1,2,…,n and n be the number of assets. Let ai=Ai/CPI be the corresponding real value of financial asset i, where CPI is the consumer price index. Let W=∑in=1ai be total real wealth and ri the interest rate on asset i. We can now set up investors’ decision making process as maximizing real interest earnings, R=∑in=1 ri ai, subject to transactions technology, where the transactions of assets are determined as a function of total wealth, f(ai,a2,…,an)=g(W) with ∂f/∂ai>0,[∂2 f/∂ai ∂aj] a symmetric positive definite matrix of order n×n, and g(W)>0. That is, the investor’s decision making process can be written as
(1)
subject to
The Lagrangian function for this maximization problem can be written as
(2)
If we write a = [ai] and r = [ri], then we can write equation (2) in vector form as
(3)
The
and
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that is,
(4)
Solutions to (4) will result in a demand equation for asset i of the form
(5)
A.
Let si=ai/W be the portfolio share of asset i. We propose the demand equation for asset i takes the form
(6)
where is the intercept term, is the wealth coefficient, and πij is the interest
rate coefficient. The first part of Equation (6), is the well- known Working (1943) Engel curve model of consumption theory. Equation (6) is also a version of the very popular almost ideal demand system of Deaton and Muellbauer’s (1980), which has a number of desirable properties.
The coefficient represents 100 times the effect on the portfolio share of deposit i,si, of a 1% increase in wealth, with all interest rates remaining constant. The coefficient πij measures the effect on si of a one percentage point increase in the interest rate ri, all other things being the same.
The balance sheet condition is given by W=∑in=1 ai or ∑in=1 si=1. Using these conditions, we can derive the constraints on the parameters of the model. Summing Equation (6) over i=1,…,n and using the fact that the asset shares on the
For the above equation to be true, the following restrictions on the coefficients should hold:
As discussed by Deaton and Muellbauer (1980) and Taylor and Clements (1983), the coefficients πij in relation to the interest rates should satisfy the homogeneity restriction given by
(7)
and the Slutsky symmetry restriction given by
(8)
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The homogeneity restriction of Equation (7) means that the demand functions of Equation (6) are homogeneous of degree zero. In other words, an equal percentage point change in total wealth W and an equal percentage point change in the relative rates of returns leaves the share of each asset unchanged. The Slutsky symmetry of Equation (8) means that interest rate substitution effects are symmetric. A priori, one would expect the diagonal elements of the [πij] matrix to be positive and the
The wealth and interest rate elasticities from Equation (6) for asset i can be derived as
(9)
and
(10)
Equation (9) implies that if the coefficient βi is positive, then asset i will have a wealth elasticity greater than 1. On the other hand, if the coefficient βi is negative, then asset i will have a wealth elasticity less than 1.
B.
Following Engle and Granger (1987), we propose the following
(11)
where the first difference series of a variable xt is defined as , which usually takes a value between 0 and
and
in Equation (11) to satisfy the condition that they are invariant with respect to i (see, for example, Edgerton et al. 1996).
III. DATA
We use annual Indonesian data from 2002 to 2017 and consider three (n = 3) assets, namely, demand deposits (i = 1), saving deposits (i = 2), and time deposits (i = 3). The nominal values (Ai,i=1,2,3) of demand deposits, saving deposits, and time
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deposit and the corresponding interest rates (ri,i=1,2,3) and the CPI are collected from the Bank of Indonesia official website. The real value (ai=Ai/CPI) of each financial asset is calculated as the nominal value Ai deflated by the CPI. We define the real value of financial wealth as the sum of the holdings of the three assets, W=∑i3=1ai. The portfolio shares si,i=1,2,3, are calculated as si=ai/W.
Figure 1. Amount of Three Deposits, Indonesia,
This figure plots the demand deposit, saving deposit and time deposit in billions of rupiah in Indonesia during the period 2002- 2017. The graph depicts the trend of the three deposits over the
Deposits (bn of rupiah)
1800000 |
Demand Deposit |
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Saving Deposit |
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Time Deposit |
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1600000 |
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1400000 |
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1200000 |
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1000000 |
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800000 |
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600000 |
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400000 |
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200000 |
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2002 |
2003 |
2004 |
2005 |
2006 |
2007 |
2008 |
2009 |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
Figure 1 plots the real value of the three financial assets. As can be seen, saving and time deposits had experienced strong growth compared to demand deposits. Saving deposits appear to be the most popular form of bank investment among Indonesians. Figure 2 plots the portfolio shares of the three deposits. As can be seen, the saving deposit share has steadily increased at the expense of demand deposits and time deposits. During
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Figure 2. Portfolio Shares of the Three Deposits
This figure plots the shares (in %) of the demand deposit, saving deposit and time deposit in Indonesia over the period
Portfolio shares (%)
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Saving Deposit |
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Time Deposit |
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50 |
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2011 |
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2016 |
2017 |
Figure 3 plots the portfolio share against log(W) for the three types of deposits. As can be seen, as the level of wealth increases, Indonesians tend to invest less in demand and saving deposits and increase their investment in time deposits. Even though such behaviour is expected, the interest rate could also play a major role, which could change this observation.
Figure 3. Share of Deposits vs Logarithm of W
This figure plots the portfolio share of the three deposits, demand deposit, saving deposit and time deposit, against the logarithm of wealth in Indonesia over the period
Share of Demand Deposit
4,0
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y |
= |
3,2 |
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R2 |
= 0.6933 |
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2,4
1,6
0,8
0,0
13,6 |
13,8 |
14,0 |
14,2 |
14,4 |
14,6 |
14,8 |
Logarithm of W
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Figure 3: Share of deposits vs logarithm of W
Share of Saving Deposit
40
y =
35
30
25
20
15
13,6 |
13,8 |
14,0 |
14,2 |
14,4 |
14,6 |
14,8 |
Logarithm of W
Share of Time Deposit
90
y = 11.959x - 99.54 R2 = 0.3364
80
70
60
50
40
13,6 |
13,8 |
14,0 |
14,2 |
14,4 |
14,6 |
14,8 |
Logarithm of W
Figure 4 plots the share of each portfolio against the corresponding interest rate. As can be seen, all three shares are sensitive to the corresponding interest rate and the shares increase with increasing interest rates. A point worth noting is that the level of substitutability between the three portfolios is another factor to consider when we examine the relationship between portfolio share movements against interest rates. When we consider a system of portfolio models in the next section, these issues are addressed completely.
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Figure 4. Share of Deposits vs Interest Rates
This figure plots the portfolio share of the three deposits, demand deposit, saving deposit and time deposit, against the interest rates in Indonesia over the period
Share of Demand Deposit
4,0
3,2
2,4
1,6
0,8
0,0
y= 0.3077x - 1.5623
R2 = 0.7571
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Interest rate |
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45 |
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Share of Saving Deposit |
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y |
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40 |
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Figure 4. Share of Deposits vs Interest Rates
Share of Time Deposit
90 |
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y |
= 2.0017x + 55.734 |
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= 0.1089 |
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10 |
Interest Rate
IV. ESTIMATION RESULTS
We use annual Indonesian data from 2002 to 2017 and consider three (n = 3) assets, namely, demand deposits (i = 1), saving deposits (i = 2), and time deposits (i = 3). Below, we present the
A.
We estimate the
Table 1.
Parameter Estimates for Unrestricted Model
This table reports regression results of the unrestricted model given by Equation (6). The standard errors are given in parentheses. Symbol * indicates significance at the 5% level. All regressions include log of wealth and interest rates of the three deposits as exogenous variables. Coefficient of determination is also presented for the estimated equations.
Deposit |
lntercept |
ln W |
r |
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r |
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r |
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R2 |
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term×100 |
1 |
2 |
3 |
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(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
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s1 |
142.447* |
0.403 |
0.95 |
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(25.469) |
(1.804) |
(0.268) |
(0.385) |
(0.402) |
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s2 |
6.541 |
0.80 |
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(91.776) |
(6.499) |
(0.800) |
(1.152) |
(1.202) |
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s3 |
2.659 |
1.094 |
0.330 |
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(85.318) |
(6.042) |
(0.744) |
(1.071) |
(1.118) |
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Table 2.
Parameter Estimates for Model with Homogeneity Imposed
This table reports regression results of the
Deposit |
lntercept |
ln W |
r |
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r |
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r |
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R2 |
|
term×100 |
1 |
2 |
3 |
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(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
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s1 |
162.61* |
0.149 |
0.95 |
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|
(15.652) |
(1.138) |
(0.219) |
(0.196) |
(0.308) |
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s2 |
17.466* |
1.825* |
0.75 |
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(53.937) |
(3.921) |
(0.754) |
(0.676) |
(1.062) |
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s3 |
131.308 |
0.661 |
1.314 |
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(56.162) |
(4.083) |
(0.785) |
(0.704) |
(1.106) |
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Table 1 reports the unrestricted model parameter estimates. As can be seen, the wealth coefficient for demand deposits is negative (i.e. the wealth elasticity value is less than one) and statistically significant, whereas the wealth coefficients for saving deposits and time deposits are positive (i.e., the wealth elasticity value is greater than one) but statistically insignificant. Among the own interest rate coefficients, only the effect of own interest rate on time deposits is positive while other two demand deposit and saving deposit are negative. The negative sign is unexpected. However, none of the three own interest rate coefficient estimates are statistically significant. We test the null hypothesis of homogeneity given by Equation (7) and, since the value of the χ2(1) test statistic is 6.58 with a
=0.04, we have support for the homogeneity hypothesis at the 1% of level of significance.
Table 2 presents the
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Table 3.
Parameter Estimates for Model with Homogeneity and Symmetry Imposed
This table reports regression results of the homogeneity and
Deposit |
lntercept |
ln W |
r |
|
r |
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r |
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R2 |
|
term×100 |
1 |
2 |
3 |
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(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
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s1 |
0.000 |
1.065* |
1.769* |
0.797** |
0.60 |
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(0.136) |
(0.410) |
(0.411) |
(0.581) |
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s2 |
23.153* |
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2.020* |
0.70 |
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(44.90) |
(3.319) |
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(0.718) |
(0.827) |
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s3 |
373.71* |
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5.384* |
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(44.901) |
(3.321) |
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(1.011) |
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Table 3 presents the homogeneity- and
Table 4 presents the wealth and interest rate elasticities calculated based on Equations (9) and (10) and the sample mean shares = 11.64,
= 45.31, and
= 43.05, and interest rates
= 8.04,
= 3.48, and
= 7.98. As can be seen, the wealth elasticities for demand deposits and saving deposits are 1.09 and 1.51, respectively, and that for time deposit is 0.44. The own interest rate elasticities for demand deposits, saving deposits, and time deposits are 1.22, 0.16, and 1.00, respectively. The
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Table 4.
Implied Elasticities for Model with Homogeneity and Symmetry Imposed
This table reports the wealth and interest rate elasticities obtained from Equations (9) and (10) at sample means and using the homogeneity and symmetry constrained estimates presented in Table 3. The standard errors are given in parentheses.
Deposit |
Wealth |
Demand |
Saving |
Time |
(1) |
(2) |
(3) |
(4) |
(5) |
Demand |
1.09 |
1.22 |
0.24 |
|
|
(0.01) |
(0.28) |
(0.12) |
(0.40) |
Saving |
1.51 |
0.14 |
0.16 |
|
|
(0.07) |
(0.07) |
(0.06) |
(0.15) |
Time |
0.44 |
1.00 |
||
|
(0.08) |
(0.11) |
(0.07) |
(0.19) |
B.
Before we estimate the
Table 5.
This table reports the results for the
|
Level Series |
Overall |
|||
Variable |
Conclusion |
Conclusion |
Conclusion |
||
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
s1 |
0.67 |
0.014 |
Stationary |
I(1) |
|
s2 |
0.15 |
0.000 |
Stationary |
I(1) |
|
s3 |
0.04 |
0.000 |
Stationary |
I(1)* |
|
ln W |
0.09 |
0.035 |
Stationary |
I(1) |
|
r1 |
0.02 |
0.009 |
Stationary |
I(1)* |
|
r2 |
0.40 |
0.030 |
Stationary |
I(1) |
|
r3 |
0.00 |
Stationary |
0.000 |
Stationary |
I(0) |
Table 6.
Results of
This table reports the results of the
Variable |
Conclusion |
|
(1) |
(2) |
(3) |
e1 |
0.004 |
I(0) |
e2 |
0.003 |
I(0) |
e3 |
0.001 |
I(0) |
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We now estimate Equation (11) and report the results in Tables 7 to 9, which present the unrestricted,
Table 7.
Parameter Estimates for Unrestricted Model
This table reports the regression results of the
Deposit |
∆(ln W) |
∆r1 |
∆r2 |
∆r3 |
||
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
s1 |
0.740 |
0.299 |
0.621 |
|||
|
(0.130) |
(2.247) |
(0.155) |
(0.128) |
(0.230) |
(0.168) |
s2 |
|
14.154 |
0.054 |
|||
|
|
(8.915) |
(0.155) |
(0.482) |
(1.095) |
(0.773) |
s3 |
0.740 |
0.634 |
0.862 |
|||
|
(0.130) |
(9.194) |
(0.155) |
(0.498) |
(1.119) |
(0.791) |
Table 8.
Parameter Estimates for Model with Homogeneity Imposed
This table reports the regression results of the
Deposit |
∆(ln WD) |
∆(ln W) |
∆r1 |
∆r2 |
∆r3 |
|
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
s1 |
0.684 |
0.124 |
0.015 |
|||
|
(0.154) |
(2.634) |
(0.175) |
(0.155) |
(0.153) |
(0.218) |
s2 |
|
23.181 |
2.186 |
|||
|
|
(9.157) |
(0.175) |
(0.523) |
(0.520) |
(0.737) |
s3 |
0.684 |
0.721 |
1.326 |
|||
|
(0.154) |
(9.528) |
(0.175) |
(0.545) |
(0.542) |
(0.769) |
Table 9.
Parameter Estimates for Model with Homogeneity and Symmetry Imposed
This table reports the regression results of the
Deposit |
∆(ln WD) |
∆(ln W) |
∆r1 |
∆r2 |
∆r3 |
|
(1) |
(2) |
(3) |
(4) |
(5) |
(6) |
(7) |
s1 |
0.719 |
0.029 |
0.193 |
|||
|
(0.197) |
(3.231) |
(0.207) |
(0.177) |
(0.177) |
(0.250) |
s2 |
|
26.960* |
|
2.323* |
||
|
|
(8.688) |
(0.207) |
|
(0.515) |
(0.545) |
s3 |
0.719 |
|
|
1.908* |
||
|
(0.197) |
(9.269) |
(0.207) |
|
|
(0.600) |
Analysing the Demand for Financial Assets in Indonesia |
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Table 9 presents the homogeneity- and
λis statistically significant, and in the usual range of
All the
Table 10 presents the implied = 11.64,
= 45.31, and
= 43.05 and interest rates
= 8.04,
= 3.48, and
= 7.98. As can be seen, the
Table 10.
Implied Elasticities for Model with Homogeneity and Symmetry Imposed
This table reports the corresponding
Country |
Wealth |
Demand |
Saving |
Time |
(1) |
(3) |
(4) |
(5) |
(6) |
Demand |
0.52 |
0.02 |
0.13 |
|
|
(0.28) |
(0.12) |
(0.05) |
(0.17) |
Saving |
1.60 |
0.18 |
||
|
(0.19) |
(0.01) |
(0.04) |
(0.10) |
Time |
0.50 |
0.04 |
0.35 |
|
|
(0.22) |
(0.05) |
(0.04) |
(0.11) |
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A comparison between the short- and
V. CONCLUSIONS
In this paper, we analyse the patterns of demand for three financial assets in Indonesia, namely, demand deposits, saving deposit, and time deposits during
The results reveal that, generally, the wealth elasticity for saving deposits is larger than one and that for time deposits is less than one, whereas that for demand deposits varies from 0.5 (short run) to 1.1 (long run). The own interest rate coefficients are positive, as expected, and statistically significant. The
Acknowledgement: The authors would like to thank the anonymous referees of this journal for their constructive comments which have helped improve the paper.
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