Academy of Economic Studies - Doctoral School of Finance
Determinants of Demand for
Money in Romania
Coordinator: Professor Moisa Altar
Author: Andreea Paunescu
- Bucharest, June 2002 -
First Step: Why the interest in studying the
money demand?
(Some practical aspects)
• appropriate monetary policy actions (stable function,
limited number of parameters)
• recently, special interest on developing countries
(flexible exchange rate, globalization of capital
markets, domestic financial liberalization and
innovation)
• predict the effects on ultimate target variables through
shocks on monetary aggregates
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Key - features of Romanian economy after 1990
• inflationary process lasted much longer that in the
majority of ex-communist countries
• intermediate objectives of monetary policy in Romania
• until the end of 1996 - exchange rate
• since the beginning of 1997 - liquidity sterilization
• 1997 - complete liberalization of the foreign exchange
market
• the final objective of NBR’s policies is keeping inflation
under control
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Conceptual approach to determinants
of demand for money
• Basically, money serves four major functions:
•
•
•
•
1. Medium of exchange
2. Store of value
3. Unit of account
4. Source of deferred payment
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Functional Form - The Basic Model
• The basic model resulting from the theory can be summarized as follows:
•
(Md / P) = f (y, Ror, Roc , I, e)
(1)
• where:
•
Md / P = demand for real money balances (either M1 or M2)
•
y = scale variable (real net income, Gross Domestic Product, etc)
•
Ror = own rate of money (for that monetary aggregate)
•
Roc = opportunity cost of holding money (for that monetary aggregate)
•
I = inflation rate
•
e = fx rate.
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Applying the general model to M1 and M2,
respectively
• Narrow Money (M1)
• Broad Money (M2)
• Md / P - real M1 as a ratio
between nominal M1 and
Consumer Price Index
• Ror - own rate of M1
computed as a weighted
average between 0 (for cash)
and the interest rate on current
account
• Roc - interest rate for deposits
at Commercial Banks
• Md / P - real M2 as a ratio
between nominal M2 and
Consumer Price Index
• Ror - interest rate for deposits
at Commercial Banks
• Roc - average nominal interest
rate paid on TBills
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Assumed / expected signs of the
dependencies in the general model
• The long-run real demand function is assumed to be:
• increasing in y
• decreasing in those elements of R representing rates of
return on alternative assets
• increasing in own rates of return
• decreasing in inflation
• and also decreasing in exchange rate.
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Empirical Approach
• The aim of the present work and the steps followed:
• 1. Testing for stationarity in the series
• 2. Testing for cointegration between the two monetary
aggregates and the specified variables, using a VAR
Model and Johansen Cointegration Test
• 3. Estimating the short-run dynamics and the speed of
adjustment to the long-run relationship through a VEC
Model
• 4. Relating the coefficients obtained with the effective
Romanian economic stance
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Data Description
• Sample: 1997:04 2001:12
• Series used:
» ln_real_m1
» ln_real_m2
» ln_rio
» int_rate_depos
» ln_fx_rate
» inflation
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Plots of ln_real_m1 (level and first difference)
5.0
4.9
4.8
4.7
4.6
4.5
4.4
1998
1999
2000
2001
LN _R EAL_M 1
0.3
0.2
0.1
0.0
- 0.1
- 0.2
- 0.3
1998
1999
2000
2001
D ( LN _R EAL_M 1)
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Plots of ln_real_M2 (level and first difference)
6.25
6.20
6.15
6.10
6.05
6.00
5.95
1998
0.15
1999
2000
2001
LN _R EAL_M 2
0.10
0.05
0.00
- 0.05
- 0.10
1998
1999
2000
2001
D ( LN _R EAL_M 2)
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Plots of ln_rio (level and first difference)
11.9
11.8
11.7
11.6
11.5
11.4
11.3
1998
1999
2000
2001
LN _R IO
0.2
0.1
0.0
- 0.1
- 0.2
1998
1999
2000
2001
D ( LN _R IO)
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Plots of int_rate_depos (level and first difference)
100
80
60
40
20
1998
1999
2000
2001
Monthl y A verage Interes t Rate for Depos i ts at Com m erc i al B anks
10
0
- 10
- 20
- 30
1998
1999
2000
2001
D ( IN T_R ATE_D EPOS)
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Plots of ln_fx_rate (level and first difference)
10.4
10.0
9.6
9.2
8.8
1998
1999
2000
2001
LN _F X_R AT E
0.16
0.12
0.08
0.04
0.00
- 0.04
1998
1999
2000
2001
D ( LN _F X_R AT E)
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Plots of inflation (level and first difference)
8
6
4
2
0
1998
1999
2000
2001
Inflati onR ate i n C onsumer Pr i ces ( %)
4
2
0
-2
-4
1998
1999
2000
2001
D ( IN FLATION )
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Unit Root Tests
Applying the ADF Test all time-series appear to be integrated
of order 1 I(1), less the inflation which is I(0)
ln(real_M1)
Level
ADF Test Statistic -1.940122
-4.1314
-3.4919
-3.1744
1% Critical Value*
5% Critical Value
10% Critical Value
*MacKinnon critical values for rejection of hypothesis of a unit root.
First difference
ADF Test Statistic -6.539777
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5547
-2.9157
-2.5953
*MacKinnon critical values for rejection of hypothesis of a unit root.
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ln(real_M2)
Level
ADF Test Statistic -2.443680
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5523
-2.9146
-2.5947
*MacKinnon critical values for rejection of hypothesis of a unit root.
First difference
ADF Test Statistic -6.007663
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5547
-2.9157
-2.5953
*MacKinnon critical values for rejection of hypothesis of a unit root.
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Industrial output
Level
ADF Test Statistic
-2.237889
1% Critical Value*
5% Critical Value
10% Critical Value
-4.1314
-3.4919
-3.1744
*MacKinnon critical values for rejection of hypothesis of a unit root.
First differences
ADF Test Statistic
-6.531974
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5547
-2.9157
-2.5953
*MacKinnon critical values for rejection of hypothesis of a unit root.
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Int_rate
Level
ADF Test Statistic
-0.756350
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5572
-2.9167
-2.5958
*MacKinnon critical values for rejection of hypothesis of a unit root.
First differences
ADF Test Statistic
-5.808501
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5598
-2.9178
-2.5964
*MacKinnon critical values for rejection of hypothesis of a unit root.
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Andreea Paunescu - Determinants of
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Ln (FX rate)
Level
ADF Test Statistic
-2.218831
1% Critical Value*
-4.1383
5% Critical Value
-3.4952
10% Critical Value
-3.1762
*MacKinnon critical values for rejection of hypothesis of a unit root.
First difference
ADF Test Statistic
-2.726614
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5547
-2.9157
-2.5953
*MacKinnon critical values for rejection of hypothesis of a unit root.
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Inflation
Level - stationary in level
ADF Test Statistic
-4.062981
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5523
-2.9146
-2.5947
*MacKinnon critical values for rejection of hypothesis of a unit root.
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The Specification of the Long-Run Relationships
• Following the traditional approach the basic model is specified in a
log-linear form, with the exception of inflation and interest rate:
• ln(real_M1) = a0 + a1 yt + a2 I t + a3 et + a4 Rt + t
(2a)
• ln(real_M2) = a0 + a1 yt + a2 I t + a3 et + a4 Rt + t
(2b)
• After determining the order of integration in the variables of interest,
the Johansen procedure is applied to a VAR version of equations (2a)
and (2b) to test for cointegration .
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Lag Length Structure
» owing to the short–length of the available time–series I
began with a general four order ( a quarter of the year) VAR.
» optimal number of lags to be included in the VAR is 4
( based on LR and AIC criteria)
» this makes sense intuitively taking into account that the data
is monthly and the sample is relatively short.
Lag
LogL
LR
FPE
AIC
SC
HQ
0
-183.8987
NA
0.000858
7.128255
7.314131
7.199734
1
2
87.61926
121.7364
481.5602
54.07244
7.86E-08
5.72E-08
-2.174312
-2.518355
-1.059052*
-0.473712
-1.745437*
-1.732084
3
4
149.1735
183.6294
38.30846
41.60704*
5.57E-08
4.45E-08*
-2.610322
-2.967146*
0.363703
0.936263
-1.466656
-1.466083
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Cointegration Results for Equation (2a)
Hypothesized
No. of CE(s)
Eigenvalue
Max-Eigen
Statistic
None **
At most 1
At most 2
At most 3
At most 4 *
0.545689
0.378232
0.238052
0.133898
0.075839
41.81562
25.18499
14.40949
7.618907
4.180037
5 Percent
1 Percent
Critical Value Critical Value
33.46
27.07
20.97
14.07
3.76
38.77
32.24
25.52
18.63
6.65
*(**) denotes rejection of the hypothesis at the 5%(1%) level
Max-eigenvalue test indicates 1 cointegrating equation(s) at both 5% and 1% levels
1 Cointegrating Equation(s):
Log likelihood
157.9327
Normalized cointegrating coefficients (std.err. in parentheses)
LN_REAL_M1
LN_RIO
INFLATION LN_FX_RATE INT_RATE_D
EPOS
1.000000
-0.513859
-0.057317
0.083125
6.37E-05
(0.11653)
(0.01133)
(0.02397)
(0.00225)
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Cointegration Results for Equation
(2b)
Hypothesized
No. of CE(s)
Eigenvalue
Max-Eigen
Statistic
None
At most 1
At most 2
At most 3
At most 4 *
0.400773
0.375992
0.266496
0.115473
0.086686
27.14206
24.99441
16.42587
6.503244
4.805825
5 Percent
1 Percent
Critical Value Critical Value
33.46
27.07
20.97
14.07
3.76
38.77
32.24
25.52
18.63
6.65
*(**) denotes rejection of the hypothesis at the 5%(1%) level
Max-eigenvalue test indicates no cointegration at both 5% and 1% levels
Hence there is no cointegration between broad money and the
variables considered.
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Testing the Errors in the Long-Run
Relationship for Narrow Money M1
• The long-run relationship:
• ln_real_m1 = 0.5139ln_rio + 0.0573infl – 0.0831ln_fx_rate – 6.3*10–5 int_rate
(rel. 3a)
•
• We will compute the series of residuals from the long-run equilibrium relationship
and test the resulting series for stationarity:
•
Resid01= ln_real_m1 - 0.5139ln_rio - 0.0573infl + 0.0831ln_fx_rate + 6.3*10–5 int_rate
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Unit Root Test on Residuals of Equation
(3a)
Unit root test for residuals series:
1 lagged differences
ADF Test Statistic -5.415923
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5523
-2.9146
-2.5947
*MacKinnon critical values for rejection of hypothesis of a unit root.
2 lagged differences
ADF Test Statistic -4.590447
1% Critical Value* -3.5547
5% Critical Value
-2.9157
10% Critical Value
-2.5953
*MacKinnon critical values for rejection of hypothesis of a unit root.
3 lagged differences
ADF Test Statistic -3.720660
1% Critical Value*
5% Critical Value
10% Critical Value
-3.5572
-2.9167
-2.5958
*MacKinnon critical values for rejection of hypothesis of a unit root.
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Plot of Residuals and Their Significance
- 0.4
- 0.6
- 0.8
- 1.0
- 1.2
1998
1999
2000
2001
R ESID 01
As the series of residuals is I(0) we can conclude that the values of
M1 estimated by the long-run equilibrium equation (3a) don’t drift
apart from the effective values so that the estimation is good.
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The Error Correction Model
• Our purpose of building an ECM was to capture the
dynamics of money demand in the short-run and
especially to identify the speed of adjustment as a
response to departures from the long-run equilibrium
• the first-difference of logarithm of real narrow money, is
regressed on the lagged value of the error correction
term (the residuals from the long-run relationship),
lagged first-differences of time series from the long-run
relationship and random disturbance.
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Speed of Adjustment in the Short-Run
VAR Model - Substituted Coefficients:
===============================
D(LN_REAL_M1) = - 0.1099725159*( LN_REAL_M1(-1) 0.5138588964*LN_RIO(-1) - 0.05731737609*INFLATION(-1) +
0.08312549112*LN_FX_RATE(-1) + 6.374730187e-05*INT_RATE_DEPOS(-1) +
0.7239219843 ) - 0.6656549525*D(LN_REAL_M1(-1)) 0.2265403831*D(LN_REAL_M1(-2)) + 0.2003159449*D(LN_REAL_M1(-3)) +
0.3566877817*D(LN_RIO(-1)) + 0.5400513137*D(LN_RIO(-2)) +
0.5087917017*D(LN_RIO(-3)) - 0.01905925299*D(INFLATION(-1)) 0.007448293855*D(INFLATION(-2)) - 0.002961759247*D(INFLATION(-3)) +
0.4001598402*D(LN_FX_RATE(-1)) - 0.8777364931*D(LN_FX_RATE(-2)) +
0.5836489162*D(LN_FX_RATE(-3)) - 0.002446832921*D(INT_RATE_DEPOS(1)) - 0.00109833907*D(INT_RATE_DEPOS(-2)) 0.002284587567*D(INT_RATE_DEPOS(-3)) - 0.01029582013
Speed of adjustment : 0.11
The error correction term coefficient of (-0.11) suggest that convergence
towards equilibrium is rather slow.
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Demand for Money in Romania
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Testing the Residuals in the Short-Run
Relationship for Narrow Money M1
Plot of the series of residuals
.20
.15
.10
.05
.00
-.05
-.10
-.15
1997
ADF Test on resid02
ADF Test Statistic
1998
1999
2000
2001
RESID02_SHORT_RUN
1% Critical Value*
-3.5625
5% Critical Value
-2.9190
10% Critical Value
-2.5970
*MacKinnon critical values for rejection of hypothesis of a unit root.
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Conclusions
• We chose the sample 1997:4 - 2001:12 in order to leave behind the peaks of
inflation at the beginning of the year 1997 due to foreign exchange market
liberalization and to test the relationships under the new market conditions
• The results we got on M1 is the following long-run relationship which we
demonstrated to have nonstationary residuals:
•
ln_real_m1 = 0.5139ln_rio + 0.0573infl – 0.0831ln_fx_rate – 6.3*10–5 int_rate
• With regard to M2 we didn’t find any cointegration. This conclusion is not
very surprising given the way than we constructed the model for M2 which is
unconsistent with the theory. The reason is the lack of statistical data for a
rate that could be assimilated with an opportunity cost for holding M2. This
variable should be in the most appropriate case the rate of return on Tbills.
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Conclusions
Interpretation of the coefficients:
• The coefficient of logarithm of real industrial output, has an expected
positive sign, meaning that a increase of 1% in the industrial output
generates an increase of 0.5139% in the demand for real narrow money. It
is the income (GDP) elasticity of money demand.
• The sign of the coefficient of inflation is also positive, meaning that an
increase in the inflation rate generates an increase in the demand for real
narrow money. Although not expected, the sign of this coefficient has
particular meaning in Romania and can be justified by:
– an increase in the stock of money holdings due to anticipated higher expenditure
in the future given the increased level of prices (high level inflation memories of
the population in the past years)
– the lack of alternative assets which makes currency in circulation, deposits and
real assets almost the only possible means of holding wealth
– low investitional culture of population which is basically consumption-oriented
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Conclusions
• The sign of the coefficient of interest rate has an expected negative sign, but it
has a low absolute value, denoting that the agents didn’t perceived during the
studied period the interest rate at deposits as a guide for whether or not to
keep their wealth in cash or deposits. This is also because in many periods the
real interest rate was negative so that its movements didn’t influence M1.
• The elasticity of foreign exchange rate is negative, meaning that an increase of
1% in foreign exchange rate generates a decrease of 0.0831% in the demand
for real narrow money. This result is expected because the depreciation of
foreign exchange rate represents a cost of holding the domestic currency.
• From the short-run relationship, we got the value of the error correction
coefficient which is - 0.11, which means that if narrow money was below
equilibrium in the previous period then it will be increased in the current
period. The value indicates a rather slow convergence towards equilibrium.
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Conclusions
• The impact of inflation and foreign exchange rate is similar (opposite
signs, but almost equal absolute values) which reflects the importance
that the agents in Romania give to inflation rates and to fx rates in
predicting the future evolution of the prices and in allocating their
wealth among alternative assets.
• Among the limitations of the model are the following:
– limited number of factors taken into consideration, especially the lack of
different types of interest rates (different maturities, different products).
This will be achieved as the financial sector in Romania develops
– the speed of transformations in an economy in tranzition makes it unlikely
to reach stable results with a high probability of being confirmed in time
– the short time-series considered, which can give little significance to the
results.
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