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ACADEMY OF ECONOMIC STUDIES BUCHAREST
DOCTORAL SCHOOL OF FINANCE AND BANKING (DOFIN)
Dissertation paper
MONETARY CONDITIONS INDEX (MCI)
AS A SUMMATIVE INFORMATION TOOL
FOR CHARACTERIZING
THE MONETARY POLICY STANCE IN
ROMANIA (1997 –2005)
MSc. Student: RAMONA STAN
Supervisor: Professor MOISA ALTAR
BUCHAREST, JULY 2006
CONTENTS
1.
Objectives
2.
What is the Monetary Conditions
Index?
3.
Theoretic approach
4.
Econometric estimation
5.
Results
6.
Conclusions
Bibliography
1.
OBJECTIVES
 MCI = relevant information tool for characterizing the monetary policy stance in
Romania between 1997-2005
 Would be worthwhile use a MCI for a better representation of monetary
policy stance?
 Do indeed short-term interest rate and exchange rate directly influence both
stability of the prices and aggregate demand?
 Controlled floating of the exchange rate
 To which extent tight control exercised by the National Bank of Romania
(NBR) over the national currency depreciation rate influenced stability of the
prices and real economic growth?
 Assessment of credibility and increased independency of NBR
 Is inflation rate’s slow yet continuous decrease to be credited only to NBR’s
quantitative approach with exchange rate constraints?
 What is the real place of the short-term interest rate within the monetary
policy choices, considering it has been used only on short periods as
operational target?
1.
OBJECTIVES
Why this historical recourse on monetary policy choices?
1997
2005
monetary base
targeting
direct inflation
targeting
 If MCI = relevant indicator  significant indication on the success of the monetary
policy  better measurement of credibility and independency of the National Bank =
essential presumptions on which direct inflation targeting is based upon
 Intuitively higher relative influence of the exchange rate both over the prices and
aggregate demand  if proved  clearly better representation in the future of the
monetary policy stance by means of MCI
 Short-term interest rate
inflation rate “paradox”
 Monetary policy choices throughout the analysis period
 Maastricht convergence criterion to be achieved
 Less powerful instrument?  to be accounted for in the future
2.
WHAT IS THE MONETARY CONDITIONS INDEX (MCI)?
w2
MCI t  [ Rt  R0 ]  [et  e0 ]
w1
MCI = weighted sum of modifications in the short-term interest rate and exchange
rate relative to some arbitrary date.
Basic assumption: Monetary policy directly influences inflation through short-term
interest rate and exchange rate.
Influence over
aggregate demand
Controlling for
exogenous shocks
“Appealing operational target
for monetary policy”
(Ericsson et al., 1997)
Bank of Canada – the “pioneer” in constructing and using MCI as operational target.
MCI used either as operational target (New Zeeland) or summative information tool (Norway, Sweden)
by Central Banks.
MCI – constructed for international comparisons (IMF, Goldman Sachs, JP Morgan).
2.
WHAT IS THE MONETARY CONDITIONS INDEX (MCI)?
 MCI can be used as:
 Summative information tool
 Operational target
 Monetary policy rule
Relevance = directly depending on the choose of underlying model from
which the weights are estimated
Nominal versus Real MCI
 Secondary objective
Base period = closely to the long-run equilibrium relationship
Econometric estimation
 Underlying model
 Choice of the variables
 Cointegration
 Stability of the coefficients
 Weak exogeneity
 “White noise” residuals
.
2.
WHAT IS THE MONETARY CONDITIONS INDEX (MCI)?
MCI as a summative information tool
Disadvantages/Limitations

Relative stance of the monetary policy as compared to an arbitrarily chosen base period

Voluntarily generalizing approach regarding transmission mechanism into the real
economy

Not a fundamental measure of monetary conditions, if nothing else, because neither MCI
nor short-term interest are nominal anchors of the system

Controlling for validity of hypothesis in econometric estimations ?

Aggregation problem
other variables = insignificant in characterizing monetary
policy stance
particular exchange rate out of many others
foreign currencies basket  weights estimated from
bilateral trade statistics
particular short-term interest rate  not accounting for
the long-term interest rate contribution to monetary
policy choices
3.
THEORETIC APPROACH
UNDERLYING MODEL
Aggregate demand equation: Δy = F(ΔR, Δe, …)
Aggregate Phillips equation: Δp = F(y-y*, Δe, …)
where:
Δy = real growth rate of GDP
y-y* = output gap
Δp = inflation rate
ΔR = change in real interest rate
Δe = change real exchange rate
and lower cases express logarithm.
The suspension points replace the variables that are not representative for monetary
policy, thus through which the influence of taxation and fiscal policy is transmitted.
The interest rate influences inflation via the real GDP and thus linking the two
equations determines an extremely simplified model, the so-called “reduced-form”
model  Bank of Canada’s inspiration for the construction of MCI
3.
THEORETIC APPROACH
Let MCI  rt  (1   )et
(0)
y gt   rt 1  et 1  y gt 1   t
(1)
 t   t 1  y gt 1   (et 1  et 2 )   t
(2)
rt  rt f  Et et 1  et
(3)
Inflation target
Where: y gt  yt  y * is the real output gap
y and e – logarithm
rtf - external interest rate (exogenous)
0  Et  t 1  Et y gt 1   ( Et et 1  et )
 *  Et  t  2  0
(2): Et  t  2  Et  t 1  Et y gt 1   ( Et et 1  et )
(5)
And, by substitution of Et et 1 in (3)
 (rt f  rt )  Et t 1  Et y gt1
(6)
Conditional expectations at t+1:
Ey gt 1   rt  et  y gt
Et  t 1   t  y gt   (et  et 1 )
Substituting in (6) and
identifying coefficients
(7)
(8)
 t  et 1 (1   ) y gt
rt f
MCI  rt  (1   )et 


 (   )
 
 (   )
4.
ECONOMETRIC ESTIMATION
Underlying model
In practice, most Central Banks which constructed and used MCI have estimated the
coefficients only from the aggregate demand equation and only in a less formal
approach, mostly for benchmarking purposes, from the prices equation.
• aggregate demand equation
yt  w0  w1 Rt  w2 et   t
! prices equation  “first paradox” =short-term interest rate actual place in
the monetary policy choices
MCI relevant ?
Estimation period: 1997-2005
Base period: 2002 (“neutral level”)
4.
ECONOMETRIC ESTIMATION
Choice of variables
• short-term interest rate = BUBOR3M (3 months-active interest rate)
• high volatility of the overnight market
• non-governmental credit high increase (owed also to facilities)
• similar trend of deposit-taking and deposit-placing interest rates
• exchange rate = composite index including Euro and US Dollar
• reference foreign currency  USD (until 2001)  EUR
• compromise determined by short data series
• following the footsteps of NBR and IMF  bilateral trade data
• BASKET = 60% EUR + 40% USD (1997-2003)
= 75% EUR + 25% USD (2004-2005)
• prices index = Consumer Prices Index (CPI) vs. Producer Prices Index (PPI)
• intimate relationship between exchange rate and PPI  inflation rate
• final consumption  ~ 63% of GDP
4.
ECONOMETRIC ESTIMATION
Notations:
bb3m_n
annualized nominal interest rate BUBOR 3M
bb3m_r
annualized real interest rate BUBOR3M (Fisher formula)
cpi
consumer prices index, fixed base (first quarter 1997)
infl_rate
inflation rate, fixed base (first quarter 1997)
infl_rate_an
annualized inflation rate, fixed base (first quarter 1997)
basket_n/basket_r
nominal/real exchange rate RON/BASKET
gdp_n_sa
nominal GDP (de-seasonalized series)
gdp_r_sa
real GDP (de-seasonalized series)
defl
GDP deflator, fixed base (first quarter 1997)
All variables expressed in logarithm have been denoted as l_variable name (with the
first difference d_l_variable name).
Tools: Excel (basic calculations), Eviews 4.1.
4.
ECONOMETRIC ESTIMATION
TESTING FOR INTEGRATION ORDER
• all nominal variables integrated of I(1)
• real GDP  I(1)
• real exchange rate  I(1)
• real interest rate  I(0)
Nominal MCI  VEC model
Real MCI  alternative VAR model
4.
ECONOMETRIC ESTIMATION
Nominal MCI  VEC model
EC(E,1) 2 2 4 4 L_GDP_N_SA BB3M_N L_BASKET_N
cointegration test  (5): intercept and trend in CE – deterministic trend in VAR
 adjustment speed  -0.837
 stability of the coefficients  roots of characteristic polynomial < 0.8795
 weak exogeneity  A(2,1)=0, A(3,1)=0, accumulated probability 0.1211
 residual tests:
 no serial correlation (12 lags tested)
.08
.06
 normality (p-value 0.1093 to Jarque-Bera)
 homoschedasticity (0.2373 to Chi-sq)
.04
.02
.00
-.02
-.04
-.06
97
98
99
00
01
02
03
Cointegrating relation 1
04
05
4.
ECONOMETRIC ESTIMATION
Estimation of the weights
Accumulated Response to Generalized One S.D. Innovations
Accumulated Response of L_GDP_N_SA to L_GDP_N_SA Accumulated Response of L_GDP_N_SA to BB3M_N Accumulated Response of L_GDP_N_SA to L_BASKET_N
.03
.03
.03
.02
.02
.02
.01
.01
.01
.00
.00
.00
-.01
-.01
-.01
-.02
-.02
1
2
3
4
-.02
1
2
3
4
1
2
3
4
Accumulated response over a year
• accounts for weak exogeneity
• NBR’s projections do not go further that one year time horizon
Period
1
2
3
4
L_GDP_N_SA
0.015094
0.020505
0.022820
BB3M_N
-0.006521
-0.013666
-0.014561
L_BASKET_N
-0.003309
0.001235
0.012770
0.023901
-0.016247
0.025115
Generalized Impulse
MCI no min al (t )  [bb3m _ n(t )  bb3m _ n(0)] 
0.025115
[l _ basket _ n(t )  l _ basket _ n(0)]
0.016247
4.
ECONOMETRIC ESTIMATION
Real MCI  VAR model
LS 1 2 D_L_GDP_R_SA BB3M_R D_L_BASKET_R @ C
 acceptable compromise, provided VAR is stable and the other hypothesis are tested.
 quasi-elasticity of GDP to the changes of the exchange rate
 how GDP changes if short-term interest rate changes by one percentage point?
Controlling for relevancy of the model:
 cointegration test (performed for the levels of the data)  (1) / (5)
 stability of the coefficients  roots of characteristic polynomial < 0.8762
 weak exogeneity  hypothesis rejected for the long-run equilibrium relationship
 residual tests:
 no serial correlation (12 lags tested)
 normality (p-value 0.1983 to Jarque-Bera)
 homoschedasticity (p-value 0.0368 to Chi-sq)
4.
ECONOMETRIC ESTIMATION
Estimation of the weights
Response to Generalized One S.D. Innovations ± 2 S.E.
Response of D_L_GDP_R_SA to D_L_GDP_R_SA
Response of D_L_GDP_R_SA to BB3M_R
.03
.03
.02
.02
.02
.01
.01
.01
.00
.00
.00
-.01
-.01
-.01
-.02
-.02
1
2
3
4
-.02
1
2
3
Period D_L_GDP_R_SA
BB3M_R
1
0.021869
(0.00269)
0.014706
(0.00435)
0.017028
(0.00478)
0.001525
(0.00380)
-0.001073
(0.00458)
-0.007088
(0.00531)
0.002641
(0.00379)
0.002787
(0.00466)
0.009022
(0.00587)
0.017572
(0.00529)
-0.006921
0.010883
(0.00677)
(0.00693)
2
3
4
Response of D_L_GDP_R_SA to D_L_BASKET_R
.03
4
1
2
3
4
D_L_BASKET_R
Generalized Impulse
Standard Errors: Analytic
MCI real (t )  [bb3m _ r (t )  bb3m _ r (0)] 
0.010883
[l _ basket _ r (t )  l _ basket _ r (0)]
0.00693
4.
ECONOMETRIC ESTIMATION
Controlled floating  direct influence over the aggregate demand?
LS 1 2 4 4 L_GDP_N_SA D_L_BASKET_N BB3M_N @ C
Controlling for relevancy of the model:
 cointegration test
 stability of the coefficients  one root of characteristic polynomial > 0.97 ?!
 weak exogeneity  hypothesis rejected
 residual tests:
 no serial correlation (12 lags tested)  at lag 4 (p-value: 0.0597)
 normality (p-value 0.0781 to Jarque-Bera)
 homoschedasticity (p-value 0.5726 to Chi-sq)
Accumulated Response to Generalized One S.D. Innovations ± 2 S.E.
Accumulated Response of L_GDP_N_SA to L_GDP_N_SA
Accumulated Response of L_GDP_N_SA to D_L_BASKET_N Accumulated Response of L_GDP_N_SA to BB3M_N
.08
.08
.08
.06
.06
.06
.04
.04
.04
.02
.02
.02
.00
.00
.00
-.02
-.02
-.02
-.04
-.04
-.04
-.06
-.06
1
2
3
4
-.06
1
2
MCI no min al _ ctrl (t )  [bb3m _ n(t )  bb3m _ n(0)] 
3
4
1
2
3
4
0.001967
[d _ l _ basket _ n(t )  d _ l _ basket _ n(0)]
0.023635
5.
RESULTS
3
2
1
0
-1
-2
-3
-4
-5
97
98
99
00
01
02
03
MCI_2002_RFREE_BB3M
MCI_2002_NFREE_BB3M
MCI2_GDP2002_N_BB3M
Notations:
MCI_2002_RFREE_BB3M
MCI_2002_NFREE_BB3M
MCI_2002_GDP2002_N_BB3M
 Real MCI
 Nominal MCI
 Nominal MCI (controlled floating)
04
05
5.
RESULTS
3
• Nominal MCI  ease of monetary conditions
2
1
• Real MCI
0
 tightening of monetary conditions
-1
-2
• high inflation rate throughout the period
-3
-4
-5
97
98
99
00
01
02
03
04
MCI_2002_RFREE_BB3M
MCI_2002_NFREE_BB3M
MCI2_GDP2002_N_BB3M
05
• controlled floating  appreciation in real terms of the
national currency
1997-1999
2004-2005
“difficult times” for Romania
preparation for direct inflation targeting
three years of real negative growth of GDP
ease of control exercised over the exchange rate
peaks of foreign debt service
appreciation both in real and nominal terms
almost financial crisis in 1999
Tighter than intended monetary conditions !
5.
RESULTS
Positive signal regarding NBR credibility and independency
6
4
2
0
-2
-4
-6
97
98
99
00
01
02
MCI_2002_RFREE_BB3M
03
04
05
L_INFL
• fairly accurate representation of monetary policy success in controlling stability of the prices
 after 2002
• high minimum mandatory reserves
 allowed for decrease of the interest rate
• other external shocks to the inflation
6.
CONCLUSIONS
• the relative influence of the exchange rate and short-term interest rate
1.55:1 (1.57:1 in real terms)
SUCCESS OF DIRECT INFLATION TARGETING  MCI’s LESSONS
• lower power of the short-term interest rate to induce changes of aggregate demand
= matter of concern for future monetary policy choices
• proven importance of the exchange rate (stability of the prices, economic growth)
= better measurement of monetary conditions with MCI
• need to pay attention still for the monetary base growth rate
• motivation of quantitative approach (taking also into account real facts)
6.
CONCLUSIONS
LIMITATIONS OF MCI
• interest rate – inflation “paradox”  MCI might not be a relevant
indicator of the monetary policy stance
• need to construct an alternative MCI including all monetary variables of
importance in achieving final inflation target
• relevancy of coefficients
• short time series (Bank of Canada calculations on MCI cover 1980-2006!!)
• relative importance of the shocks induced to aggregate demand (based on
the impulse-response functions) are acceptable to the limit
• aggregation problem  the way the “basket” was constructed
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