Inflation targeting in the AD-AS model
The different regimes explained in Lecture10:
Lecture 12 and 13:
Macro dynamics of the open economy:
Current monetary policy of small open
economies
Foreign exchange rate market
exogenous variable
Foreign exchange reserves Exchange rate
Money market Money supply
exogenous
Interest rate
variable
None
I
III
V
II
IV
VI
In Lecture 11 we analyzed R-I, a so called money targeting regime, and compared it to the R-VI (Et is targeted)
Ragnar Nymoen
In R-I the instrument of monetary policy is market operations: buying and
selling of domestic bonds controls the supply of money in the domestic money
market.
November 13, 2007
2
1
Why consider alternatives to R-I?
Recall the “supply of money function” of the open economy:
∆Mt = −∆Bt + Et · ∆Fg,t + ∆Et · Fg,t
In R-I ∆Fg,t = 0 and Fg,t = F̄g . Revaluations of the stock of foreign currency
F̄g affects ∆Mt somewhat, but according to the theory of R-I, such movements
are countered by market operations (∆Bt). Changes in the net supply of bonds
can also be used to increase or lower Mt independently of the market for foreign
exchange. Hence, monetary policy independence in R-I: the interest rate is
determined on the domestic money market.
No such independence in R-VI, because the interest rate is determined in the
market for foreign exchange.
Remember that the discussion of R-I and R-IV was based on the assumption
of perfect capital mobility (as in the IAM book).
A full discussion is beyond this course, but in practice R-I failed to live up to
the expectations founded in the theory just summarized: It turned out to be
difficult to control money supply. Two issues in particular seem to have been
important:
a) Which money stock measure to target (M1, M2 or M3)
b) In practice central banks rode two horses: tried also to intervene in FEX
market (dirty float), which affect money supply
In any case, R-I was really never considered an alternative when several SOEs
started floating their exchange rates in the 1990’s. The alternative most countries settled for is called inflation targeting.
In our typology inflation targeting can be seen as an extension of R-III. The
interest rate is the used as an instrument to achieve a certain inflation rate (the
target). Therefor it is “exogenous in the domestic money market”. However
it it is endogenous in the wider setting of our macroeconomic model.
We now define the inflation targeting regime
3
4
Inflation targeting defined
We make a short-cut and replace equation (2), page 769 in IAM with the
following policy response (equivalent to what IAM also eventually ends up
with)
f
it = it + h(πt − π ∗)
h > 0.
(Policy response)
where π ∗ denotes the inflation target, usually number like 2% or 2.5% (annual
rate).
f
We follow IAM and make the following simplifying assumption
π ∗ = π̄ f , target set to the constant foreign inflation
From policy response function and expectations:
f
it = it + h(πt − π̄ f )
which is eq (14) on page 776.
We can now augment the AD-AS model with this ’policy rule’.
Note: could have coefficient different form 1 in front of it as well.
Remark to table 25.1: Norges Bank does not acknowledge that it operates with
“tolerance bands”. Rather a horizon (1-2 years) over which the target should
be achieved.
6
5
The short-run analysis (inflation targeting)
f
yt = β0 + β1ert − β2rt + β3gt + β4yt
e
rt = it − πt+1
f
ert = ∆et + πt − πt + ert−1
πt = πte + γ(yt − ȳ) + st
f
it = it + ee + αe(∆et + et−1) αe < 0
f
it = it + h(πt − π̄ f )
mt − pt = m0 − m1it + m2yt, mi > 0, i = 1, 2
(1)
(2)
(3)
∆et =
1
f
(it − it − ee) − et−1
αe
(4)
substitution of it from (5)
(5)
(6)
−1 f
1 f
(it + ee) − et−1 + e (it + h(πt − π̄ f ))
e
α
α
1
= e (h(πt − π̄ f ) − ee) − et−1
α
We therefore obtain the short-run AD schedule from
½
¾
1
f
f ) − ee) − e
r
yt = β0 + β1
(h(π
−
π̄
+
π
−
π
+
e
t
t
t−1
t−1
t
αe
n
o
f
f
f
e
− β2 it + h(πt − π̄ ) − πt+1 + β3gt + β4yt
Note that (4), is a generalization of eq (9) on page 771. IAM omits ee and
et−1, and αe corresponds to −θ in IAM.
Skip the discussion on p 772 and 774, it represents an internal inconsistency
(non zero risk-premium and dirty float even though perfect capital mobility
here).
Compared to R-I we have one more equation. Hence mt is endogenous in the
short-run model of inflation targeting
7
From (4):
∆et =
8
(7)
(8)
We adopt IAM’s assumptions about inflation expectations:
e
πt+1
= πte = π ∗ = π̄ f
hence the model becomes
½
¾
1
f
f ) − ee) − e
r
yt = β0 + β1
(h(π
−
π̄
+
π
−
π
+
e
t
t
t−1
t−1
t
αe
n
o
f
f
f
f
− β2 it + h(πt − π̄ ) − π̄ + β3gt + β4yt
(9)
−
and
πt = π̄ f + γ(yt − ȳ) + st
(10)
Differentiate (9) to obtain the slope of the R-III short-run AD-curve:
¯
¯
¯
¯
∂πt ¯¯
∂πt ¯¯
−
>−
, when αe < 0
¯
¯
∂yt ¯AD,rV I
∂yt ¯AD,rIII
∂πt ¯¯
∂πt ¯¯
>−
, when αe < 0
¯
¯
∂yt ¯AD,rV I
∂yt ¯AD,rIII
hence the short-run AD schedule is flatter in R-III (inflation targeting) than in
R-VI.
¯
∂πt ¯¯
−1
=
<0
¯
β1
¯
∂yt AD,rIII
β1 + h(β2 − α
e)
consistent with β̂1in eq. (15) on page 776 in IAM.
10
9
Interpretation of slope-difference
inflation
The interpretation of the difference has to do with how the interest rate is
determined in the two regimes: When πt increases, y-demand is reduced in
both regimes through the real exchange rate, er . But there are additional
effects in R-III: The interest rate is increased (monetary policy response) which
leads to further reduction in yt.
f
R-III
Hence regime III is different from the fixed exchange rate VI, but also from the
floating exchange rate regime I (money as the target) where lower demand for
money reduces the interest rate in the domestic money market.
R-VI
R-I
y
y
We have generalized figure 25.3: AD(flex) represent only one sub-category of
floating exchange rate regimes.
11
12
Short-run effect of a supply-shock
Long-run effects of a supply-shock
Consider a positive aggregate supply shock in period t = 1, s1 < 0 (s0 = 0)
The impact multipliers:
If the reduction in s is temporary: no long run effects. π − π̄ f = 0 from AS
(the Phillips curve). Then er = er0 from definition of real-exchange rate.
If a permanent reduction of s, then apparently π − π̄ f = s1 < 0 which cannot
be reconciled with
GDP: largest for R-III, smallest for R-I.
Inflation: Largest reduction for R-I, smallest reduction for R-III.
e
πt+1
= πte = π ∗ = π̄ f
The fixed exchange rate regime (R-VI) is an intermediate case.
Paradox is resolved by nothing that ȳ is increased by the permanent positive
supply shock. The natural rate of unemployment is lowered. So π − π̄ f in the
long-run as before. But for higher ȳ.
If h → ∞ R-III multipliers approach R-VI multipliers (not R-I).
14
13
Short-run effects of a demand shock
However, note that for a given π:
¯
dyt ¯¯
= β3
¯
dgt ¯πt=π̄,rIII
Use fiscal policy again to represent a demand shock.
We already know that R-I and R-VI can be compared by (identical) vertical
shifts of the AD curve:
However, from (9)
¯
¯
dπt ¯¯
dπt ¯¯
β
=
= 3>0
¯
¯
¯
¯
dgt yt=ȳ,rI
dgt yt=ȳ,rV I
β1
½
1
f
yt = β0 + β1
(h(πt − π̄ f ) − ee) − et−1 + πt − πt + ert−1
e
α
n
o
f
f
− β2 it + h(πt − π̄ f ) − π̄ f + β3gt + β4yt
we see that
¾
¯
dπt ¯¯
β3
=
¯
β1
¯
dgt yt=ȳ,rIII
β1 + h(β2 − α
e)
so (unless the trivial case of h = 0) a vertical shift are not comparable (IAM p
782)
15
since there are no indirect demand side effects of a change in y in this regime
(yt is not included in the policy response function). The same is true in R-VI
where the interest rate is determined on the FEX marked. Hence, from
n
f
yt = β0 + β1 πt − πt + ert−1
n
f
o
o
f
e
− β2 it + ee + αe(∆et + et−1) − πt+1
+ β3gt + β4yt
we have
¯
dπt ¯¯
= β3
¯
dgt ¯πt=π̄,rV I
hence, we can make a comparison of regime III and VI with the aid of a
horizontal shift of the AD schedule.
See IAM p 782 for the algebraic analysis.
16
The impact multipliers (of a change in gt):
GDP: larger for R-VI than for R-III.
Inflation: larger for R-VI than for R-III.
Hence there is no clear cut answer to which monetary policy regime give most
automatic stabilization to shocks.
Relative frequency of demand and supply shocks is one aspect.
This theme is developed further in IAM ch 26.1-26.2, in different directions,
which we leave for self-study.
17
Choosing the rate of inflation
Sometimes one the message is communicated that inflation targeting is not
only about stabilization, but also about “choosing a different rate of inflation
than the foreign rate”.
In the model, such a policy choice entails keeping π ∗ as a policy determined
parameter in the interest rate response function.
The steady-state consistent with π = π ∗ and a constant real exchange rate,
now implies that
∆e = (π ∗ − π f ),
so (π ∗ − π f ) > 0 in the steady-state implies a constant rate of nominal depreciation.
18
Operational inflation targeting (Case of Norway)
Characteristics of the regime
1. A floating exchange rate regime
2. The target of monetary policy is low and stable inflation
3. The operational target is the forecasted rate of inflation (1, 2 or 3 years
ahead)
4. The instrument is the interest rate that the Central Bank sets as the loan
rate in the domestic short-term money market. The interest rates offered
to the public are higher but they are highly correlated with the CB’s sight
deposit rate (’foliorente’).
(a) Signaling, and building up of credibility: By acting on the macroeconomic prospects (in practice the CB’s own forecasts) rather than observed realities, monetary authority can signal a commitment to the
target of low and stable inflation. The CB hopes that this will influence inflation anticipations among households and firms, which will in
turn make goal achievement easier
(b) The transmission mechanism is dynamic: it takes time before a change
in the instrument affects the rate of inflation. Hence by acting “now”
the costs of achieving the target is less than by waiting until a too
high/low inflation rate becomes a reality.
6. Inflation targeting is flexible when the target horizon is long, so that interest
rate adjustments can be gradual.
5. The CB’s interest rate setting is forward looking. There are two reasons
given
19
20
A premise is of course the interest rate has an effect on the rate of inflation.
What does the evidence say?
Consider the Norwegian Aggregate Model for example.
Figure 1: The transmission mechanisms in Norwegian Aggregate Model
21
The implications from this set of multipliers are:
1. The interest rate affects inflation through a complicated causal chain, confirming Figure 1.
2. Small and temporary interest rate changes will work no wonders for the
rate of inflation
3. The most lasting, and over time strongest, influence is through demand.
22
Inflation forecasting and targeting
Inflation targeting: the operational target variable is the forecasted rate of
inflation, π̂T +H|T .
Interest rate set so that it bring the forecasted inflation rate in line with target,
π∗
Flexibility: related to the length of the forecasting horizon, H (as well as of
other aspects of the “utility function”).
4. Flip of the coin of 3. is that i adjustments are best suited to offset demand
shocks. Large supply shocks represent a challenge.
However, a inflation forecast is uncertain, and might induce wrong use of policy.
Hence, a broad set of issues related to inflation forecasting is of interest for
those concerned with the operation and assessment of monetary policy.
23
24
A favourable situation occurs when it can be asserted that the bank’s forecasting model is a reasonably correct representation of the true inflation process
of the economy. In this case, forecast uncertainty can be represented by conventional forecast confidence intervals, or by the fan-charts preferred by best
practice inflation targeters.
However an assumption of model correctness is not a practical basis for economic forecasting, as proven by the high incidence of forecasts failures.
A characteristic of a forecast failure is that forecast errors turn out to be
larger, and more systematic, than what is allowed if the model is correct in
the first place. In other words, realizations which the forecasts depict as highly
unlikely (e.g., outside the confidence interval computed from the uncertainties
due to parameter estimation and lack of fit) have a tendency to materialize too
frequently.
25
Situation B represents the situation most econometric textbooks conjures up,
The properties of situation A will still hold–even though the inherent uncertainty will increase. The theory of inflation targeting also seems stuck with
B.
As stated: forecast properties are closely linked to the assumptions we make
about the forecasting situation. One possible classification, is:
A The forecast model coincides with actual inflation in the econometric sense.
The parameters of the model are known and true constants over the forecasting period.
B As under A, but the parameters have to be estimated.
C As under B, but we cannot expect the parameters to remain constant over
the forecasting period–structural changes are likely to occur somewhere
in the .system.
D We do not know how well the forecasting model corresponds to the inflation
mechanism in the forecast period.
A is a very idealized description of the assumptions of macroeconomic forecasting. Nevertheless, there is still the incumbency of inherent uncertainty–even
under A.
26
A forecast failure effectively invalidates any claim about a “correct” forecasting
mechanism (Situation A or B).
Upon finding a forecast failure, the issue is whether the misspecification was
detectable or not, at the time of preparing the forecast.
In real life we of course do not know what kind of shocks that will hit the
economy, or the policy makers during, the forecasting period, which is the focus
of situation C. Structural breaks and regime changes are the most important
source of forecast failure.
Given that regime shifts occur frequently in economics, and since there is no
way of anticipating them, it is unavoidable that after forecast structural breaks
damage forecasts from time to time. The task is then to be able to detect the
nature of the regime shift as quickly as possible.
Situation D finally leads us to a realistic situation, namely one of uncertainty
and professional discord regarding what kind of model best representing reality.
This opens up the whole field of model building as well as the controversies
regarding econometric specification, so we will leave that subject here.
Hence in there is a premium on adaptation in the forecasting process, in order
to avoid sequences of forecast failure.
27
28
Lack of adaptation will make the forecast susceptible also to before forecast
structural break leading to unnecessary forecast failure.
As an illustration, suppose that the following reduced form model—derived from
a structural model (AD-AS for example)– is used for forecasting
Relevance for inflation targeting?
πt = δ + απt−1 + β1it + β2it−1 + εt, t = 1, 2, 3..., T,
Forecast quality per se becomes of interest in this policy regime.
−1 < α < 1, β1 + β2 < 0,
The rate of inflation, being a nominal growth rate, is particularly susceptible to
forecast failure (shifts in means of nominal variables in particular are notorious).
If central bank’s do as they claim, and set interest rates to affect the inflation
forecast, then regime shifts will not only damage the inflation forecasts, but
will also interest rate setting.
But in which way (with what consequences) depends on the operational aspects
of inflation targeting.
29
iT |T = 0
where μ denotes the long run mean of inflation.
Note: This a the so called interest rate path in simplified form
31
πt is the rate of inflation, and it is the interest rate.
Suppose, for simplicity, that the central bank have chosen a 2 period horizon.
The forecasts are prepared conditional on period T information, so
π̂T +1|T = δ + απT + β1iT +1|T + β2iT |T
(12)
2
π̂T +2|T = δ(1 + α) + α πT + αβ1iT +1|T + αβ2iT |T + β1iT +2|T + β2iT +1|T
(13)
There are 2 degrees of freedom if the bank chooses to attain the target π ∗ in
period 2 (inflation targeting is flexible), and iT +1|T and/or iT |T can be set to
(help) attain other priorities.
30
For simplicity, set iT +1|T and iT |T to some autonomous level, represented by
0 (hence let it be a deviation from its mean, the period 1 interest rate is equal
to the mean interest rate). Hence, the interest rate path in this case is
iT +1|T = 0
o
1 n
−μ + α2(μ − πT ) + π ∗
iT +2|T =
β1
(11)
(14)
In a constant parameter world, this path will secure that πT +2|T is equal to π ∗
on average.
But if μ increases in period T + 1 and T + 2, a regime shift, both π̂T +1|T and
π̂T +2|T will be too low, possibly representing a forecast failure.
However, only iT +2|T is affected by the forecast failure, and can replaced by
iT +2|T +1 in the next forecast round.
The announced interest rate path is subject to the regime shift. Not today’s
interest rate.
With a different operational procedure, designed to move π̂T +1|T “in the direction” of the target, iT |T may be contaminated by regime shifts in the transmission mechanism.
32
The Norwegian Central Bank, in particular, has announced that interest rate
changes, will as a rule be gradual. We can model this by setting:
iT +j−1|T = γiT +j|T ,
j = 1, 2, ...H, 0 ≤ γ < 1
Norges Bank’s inflation forecasts
Inflation forecasts are published in the bank’s inflation reports, IRs.
which gives
o
γ2 n
iT |T =
−μ + α2(μ − πT ) + π ∗
Bn
o
γ
iT +1|T =
−μ + α2(μ − πT ) + π ∗
(15)
B
n
o
1
iT +2|T =
−μ + α2(μ − πT ) + π ∗
B
where B < 0 is function of α, β1, β2 and γ. With gradual interest rate adjustment, regime-shifts and forecast failures are more serious, since interest rates
today are affected, not only the i-path.
33
A main feature of BM is that the joint contribution of all interest rate channels
secures a sufficiently strong and quick transmission of interest rate changes on
to inflation to justify a 2 year policy horizon.
This view of the transmission mechanism has left its mark on the published
inflation forecasts, which typically revert to the target of 2.5% within a 2-year
forecast horizon.
But in the summer of 2004, this view was changed.
35
The details of the process leading up to the published forecast is unknown to
the outsider, but the bank’s beliefs about the transmission mechanism between
policy instrument and inflation, represents a main premise for the forecasts,
and secures consistency in the communication of the forecasts from one round
of forecasting to the next.
For simplicity, we refer to the systematized set of beliefs about the transmission
mechanism as the Bank Model–BM for short.
34
There is a trade-off between the wish to provide useful forecast, and the wish
to avoid forecast failure.
Forecasts with high information content come with narrow uncertainty bands.
Conversely, the wider the uncertainty bands are, the less information about
future outcome is communicated by the forecast.
A simple indication of the information content of the inflation forecast is therefore to compare the width of the uncertainty bands with the variability of
inflation itself (measured by the standard deviation over, say the last 5 or 10
years). If the forecast confidence region is narrow compared to the historical variability, the central bank forecasts can be said to have a high intended
information value, see figure 3.
36
0.030
0.025
1. Norges Banks believes in low forecast uncertainty. High information content in forecast for the first couple of quarters.
Inflation
0.020
0.015
IR 1/02
IR 1/04
2. Maximum uncertainty is reached fast- Hence Norges Bank acknowledges
that there is a strict limit to the predictability of inflation?
IR 1/05
IR 1/03
0.010
0.005
2002
2003
2004
2005
2006
2007
3. Forecast uncertainty is increased in IR 1/04 and after. A sign of adaptation?
2008
Time
Figure 3: Uncertainty measures of Norges Bank’s inflation forecasts in Inflation
Reports 1/02, 1/03 and 1/04. The lines show the width of the the approximate
90% confidence region for the 12 month growth rate of CPI-ATE.
38
37
0.04
IR 1/02
IR 2/02
0.04
0.02
0.02
actual
actual
0.00
0.00
2001
0.04
2002
2003
2004
2005
2006
2007
IR 3/02
2001
forecast
2002
2003
2004
2005
2006
2007
IR 1/03
0.04
0.02
forecast
0.02
In the IR 2/02 forecasts the first four inflation outcomes are covered by the forecast confidence interval, but the continued fall in inflation in 2003 constitutes
a forecast failure.
actual
actual
0.00
0.00
2001
2002
IR 2/03
2003
2004
2005
2006
2007
0.04
2001
2002
2003
2004
2005
2006
2007
2006
2007
2006
2007
IR 3/03
0.04
forecast
forecast
0.02
0.02
actual
Specifically, the forecast confidence interval of IR 3/03 doesn’t even cover the
actual inflation in the first forecast period.
actual
0.00
0.00
2001
0.04
6 of 8 graphs show clear evidence of forecast failure.
forecast
forecast
2002
2003
2004
2005
2006
2007
IR 1/04
2001
0.04
2002
actual
2005
forecast
0.02
0.00
0.00
2001
2004
actual
forecast
0.02
2003
IR 2/04
2002
2003
2004
2005
2006
2007
2001
2002
2003
2004
2005
The 7th panel shows that the forecasted zero rate of inflation for 2004(1) in IR
1/04 turned out to be accurate. The forecasts have been substantially revised
from IR 3/04. Whether this will prove enough to end the sequence of poor
forecasts, remains to be seen.
Figure 4: Norges Bank’s inflation forecasts, 90% confidence regions and the
actual rate of inflation.
The next section contains an evaluation by way of presenting ex post forecasts
based on information which were available to the forecasters at the time of
preparing the IR forecasts.
39
40
How avoidable was the forecast failure?
As pointed out, poor forecasts due to after forecast structural breaks are unavoidable in economics.
Given that fact, there is a premium on having a robust and adaptable forecasting
process.
Allowing relevant historical shocks to be reflected in forecast uncertainty calculations contributes to robustness in the forecasts, avoid too narrow forecast
confidence intervals.
Yet, as any nominal variable, inflation may be subject to frequent changes in
mean, exactly the type of shocks that will damage forecasts.
Adaptable forecasting mechanisms have the ability to adjust the forecasts when
a structural change is in the making, or at the latest, when a forecast failure
has manifested itself.
This may have some relevance for the recent forecasts, since the low and stable
inflation rates of the late 1990s may have lead some forecasters to down-play
uncertainty.
41
42
The forecast failures also give rise to the question whether the sequence of
poor forecasts was avoidable at the time of preparing the forecasts.
This is a complex issue which needs to be analyzed from several angles.
Here we follow an on-looker’s approach, and set up a forecasting mechanism
which features at least two elements which logically must be present in the
forecasting process in the bank:
1. All explanatory variables of inflation are themselves forecasted. Hence, our
ex-post forecasts do not condition on variables that could not have been
known also to the forecasters at the time of preparing the different inflation
reports.
Note that in our ex post forecasts, the up-dating of the forecasts is automatized.
In real life forecasting, the revision of the forecasts from one inflation report
to the next is done by experts. In comparison, our econometric forecasts are
naive. In general, naive econometric forecasts are not particularly adaptive, but
are prone to failures themselves.
The set of forecasting equations was estimated on a quarterly data set which
starts in 1981(1). Figure 5 shows the sequence of model forecasts.
2. Just like in a practical forecasting situation, the forecasts are updated:
model parameters are re-estimated as new periods are included in the historical sample, and, more importantly for the forecasts themselves, the
initial conditions are changed as we move forward in time.
43
44
0.04
AIR 1/02
0.04
0.02
0.00
0.00
2001
0.04
2002
2003
2004
2005
AIR 3/02
2001
0.04
0.02
2003
2004
2005
2. Even though the second year forecasts in “IR 1/02” show too high inflation,
there is in fact a forecasted weak tendency towards lower inflation in 2003.
0.00
2001
2002
2003
2004
2005
AIR 2/03
2001
0.04
0.02
0.02
0.00
0.00
2001
0.04
2002
AIR 1/03
0.02
0.00
0.04
1. The confidence bands of the forecasts are wider in “IR 1/02”, both for the
one and eight quarter ahead forecasts.
AIR 2/02
0.02
2002
2003
2004
2005
AIR 1/04
0.02
2003
2004
2005
2002
2003
2004
2005
2002
2003
2004
2005
AIR 2/04
3. Since the second year actual inflation rates are within the corresponding
confidence bars, these outcomes do not represent forecast failure in Figure
5, while they do in the Norges Bank forecast.
0.02
0.00
2001
2001
0.04
2002
AIR 3/03
0.00
2002
2003
2004
2005
2001
4. In the panel, labeled “IR 3/02”, the impact of conditioning on 2002(2)
shows up in narrower confidence bands for 2003, which in fact almost
makes the realized inflation rate in 2003(4) a forecast failure.
Figure 5: Forecasts from an econometric model of inflation, where we have emulated the (real time) forecast situation of the Norges Bank inflation forecasts.
.
5. The next three panels in Figure 5 show an even more market difference
from the Norges Bank forecasts.
45
46
A subjective assessment
In the period 2001-2005 official monetary policy in Norway may have been
hampered by several problems and mistakes
5. Interest rate decisions might have suffered, but
1. Overestimation of the effect of the interest rate on inflation (the interim
multipliers) by Norges Bank.
2. Underestimation of the period of adjustment and of the forecast uncertainty.
Time will show if these are still only teething problems.
6. 2006 and 2007 have shown a more adaptive approach. Forecast accuracy
improved in 2006, and so far in 2007.
3. Very slow identification of the nature of the drop in the rate of inflation
that started in 2003 (relative weight on supply and demand factors, an on
domestic and foreign).
4. Exceptionally slow adaptation of the forecasts.
47
48
Deviation
INFJAE
DEPR
.2
PBGR
1
.0
0.5
0
0.0
-1
-0.5
-2
-1.0
-3
-1.5
-.2
-.4
-.6
-4
-.8
-2.0
-5
2007
2008
2009
2010
2011
2012
-2.5
2007
2008
YGR
2009
2010
2011
2012
2007
2008
0.2
0.2
.8
.6
0.0
0.0
-0.2
-0.2
-0.4
-0.4
-0.6
-0.6
-0.8
-0.8
2009
2010
2011
2012
2011
2012
UR2
WCINF
.4
.2
-1.0
.0
-.2
-1.0
2007
2008
2009
2010
2011
2012
2007
2008
2009
2010
2011
2012
2007
2008
2009
2010
Figure 2: Dynamic multipliers from a permanent increase in the money market
interest rate by 100 basis points, 2007(1)-2012(4). The distance between the
two red dotted lines represent the 95 % confidence intervals
49