Download Performance of inflation targeting

JEM027
Monetary Economics
Inflation targeting
in comparison to other strategies
Tomáš Holub
[email protected]
November 30, 2015
Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague
Outline
MP regimes – some traditional alternatives
Inflation targeting in theory
Comparison with price-level targeting
Empirical performance before the crisis
Performance during the crisis
Summary and conclusions
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Some alternatives of MP regimes
(with floating ER)
Money targeting
Inflation targeting
Two pillars
Just do it
(ECB – seminar topic)
(Fed under Greenspan)
seminar topic)
Repo rate
Repo rate
Refinancing
rate
Fed funds
Money
market rates
Money
market rates
Money
market rates
Money
market rates
Money supply
(target)
Monetary
transmission
Inflation
(goal)
Inflation
(goal+target)
Econ.
outlook
Inflation
(goal)
Money
supply
Monetary
transmission
Inflation,
growth etc.
(goals)
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Monetary policy regimes (1/3)
Evolution of monetary policy regimes, 1985-2005
Industrial countries
▪
Non-industrial countries
Exchange rate pegs and multiple targets still quite numerous, but IT gaining
increasing share
Source: IMF; Batini, et al. (2006)
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Monetary policy regimes (2/3)
Share of alternative MP regimes in the world (IMF de facto, sample of 125
countries)
Share of alternative MP regimes in the world (IMF de facto, sample of 125 countries)
100%
90%
euro area
80%
70%
pegged exchange rate
60%
50%
other
40%
30%
20%
10%
money targeting / IMF program
(often with elements of M-targeting)
Inflation targeting
0%
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
▪
IT‘s share above 20% (around 32 countries now; i.e. still a minority in practice, but
state-of-the art in theory before the crisis)
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Monetary policy regimes (3/3)
Number of countries (IMF de facto classification, 2012)
▪
▪
Inflation targeting + ECB‘s 2-pillar strategy dominate for freely floating countries
But IT also most frequent for (managed) floating countries
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Advantages of inflation targeting
▪ Embodies all the modern trend in central banking: independence,
rules, transparency and accountability (see the previous lecture)
▪ Combines a policy rule with discretion (flexible rule)
▪ The target and the ultimate goal are identical
▪ Does not rely on stable money demand
▪ Takes into account all available information
▪ A direct emphasis is put on managing expectations
▪ Strengthens internal discipline and forecasting of CBs
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Theoretical background
Inflation
var(inflation)
F
S
Unemployment
var(output)
▪ Trying to reach both low inflation (primary goal – can be controlled
by MP in the long run) and an optimal degree of stabilisation in the
presence of unforeseen shocks (like the Walsh contract).
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Strict IT (Svensson, 1997)
Phillips curve
Aggregate demand
Loss function
Policy rule
Optimal reaction function
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Policy rule under inflation targeting
▪ Strict inflation targeting: set the interest rates to equate the forecast of
inflation with your target at the horizon of transmission (Svensson:
“inflation-forecast targeting”)
Current inflation
Actual (1)
Forecast
Target
Actual (2)
1
Change in IR
Change in AD, GDP,
employment
2
Change in inflation
▪ Beware: no one actually does strict inflation targeting!
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Flexible IT (Svensson, 1997)
Phillips curve
Aggregate demand
Loss function
Policy rule
Optimal reaction function
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Policy rule under inflation targeting
▪ Flexible inflation targeting: set the interest rate to gradually return the
forecast of inflation to target, taking into account the variability of output
Current inflation
Actual (1)
Forecast
Target
Actual (2)
1
Change in IR
Change in AD, GDP,
employment
2
Change in inflation
▪ Flexibility in practice: setting the monetary policy horizon, choice of
targeted index, escape clauses, IR smoothing, etc.
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Less technical view
▪ IT creates procedures, which lead to a behaviour mimicking optimal
policy (i.e. a complex form of the Walsh contract)
▪ IT = “Constrained discretion”; constraint = procedural rules
(vs. mechanical rules); discretion = room to respond to shocks
▪ IT is about building credibility, anchoring expectations
▪ It is not about hitting the targets at any cost (it is about missing
them temporarily in a well-explained way)
Sum up: IT = defining good incentives for the CB!
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IT vs. price level targeting (PLT) (1/2)
Inflation targeting
Price-level targeting
inflation
inflation
targeting
targeting
price-level
price-level
targeting
targeting
110 110
110 110
108 108
108 108
106 106
price level
price level
index index104 104
106 106
102 102
102 102
100 100
100 100
Price level
index
4
Inflation
(percent)inflation
inflation 3
(%) (%)
2
1
0
4
3
2
1
0
1
104 104
4
3
2
1
0
1 2
2 3
3 4
periodperiod
4 5
5
target target
price level
priceand
levelinflation
and inflation
after price
after shock
price shock
Source: Böhm, et al. (2012)
4
3
2
1
0
1
1 2
2 3
3 4
periodperiod
4 5
5
target target
price level
priceand
levelinflation
and inflation
after price
after shock
price shock
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IT vs. price level targeting (PLT) (2/2)
Czech Republic
Canada
Czech Republic
Czech Republic
160
160
160
150
160
150
150
140
140
150
140
130
130
120
130
120
110
110
120
Canada Canada
150
Czech Republic
Czech Republic
150
140
140
140
150
Canada
Canada
150
140
130
140
130
130
120
120
130
120
110
110
120
130
120
100
100
110
1998:M1
2000:M1
1998:M1 2002:M1
2000:M1 2004:M1
2002:M1 2006:M1
2004:M1 2008:M1
2006:M1 2010:M1
2008:M1
110
100
100
110
110
2010:M1
1996:M1 1998:M1
1996:M1
2000:M1
1998:M1
2002:M1
2000:M1
2004:M1
2002:M1
2006:M1
2004:M1
2008:M1
2006:M1
2010:M1
2008:M1 2010:M1
100
100
100
100
United
Kingdom
United2006:M1
Kingdom
Sweden
Sweden
1998:M1 1998:M1
2000:M1 2000:M1
2002:M1
2004:M1
2006:M1
2008:M1
2010:M1
1996:M1 1998:M1
2000:M1
2002:M1
2004:M1
2008:M1
2010:M1
2002:M1 2004:M1 2006:M1 2008:M1 2010:M1
1996:M1
1998:M1
2000:M1
2002:M1 2004:M1
2006:M1
2008:M1 2010:M1
160
160
150
150
Sweden
140
150
130
140
150
140
SwedenSweden
150
160
140
140
160
130
150
130
150
120
140
140
130
140
120
120
130
110
130
110
110
130
120
100
100
120
1995:M1 1995:M1
1998:M1
110
1998:M1
2001:M1
2001:M1
2004:M1
2004:M1
2007:M1
2007:M1
2010:M1
110
100
100
1995:M1 1995:M1
1998:M1 1998:M1
2001:M1 2001:M1
2004:M1 2004:M1
2007:M1
Source: Böhm, et al. (2012)
United Kingdom
United Kingdom
120
110
130
100
100
120
1992:M10 120
1992:M10
1995:M10 1995:M10
1998:M10 1998:M10
2001:M10 2001:M10
2004:M10 2004:M10
2007:M10 2007:M10
2010:M10 2010:M10
2010:M1
110
2010:M1
2007:M1
United
Kingdom
150
110
100
100
1992:M10
1995:M10
1992:M10 1998:M10
1995:M10 2001:M10
1998:M102004:M10
2001:M102007:M10
2004:M102010:M10
2007:M10 2010:M10
2010:M1
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Advantages of PLT
▪ Svensson’s (1999b) “Free Lunch”: if output gap persistence is higher than
0.5, a discretionary policy results in lower inflation variability under the
PLT than in the IT
▪ Literature after Svensson: some additional support for the PLT, but also
some qualifiers (e.g. the extent to which economic agents are forwardlooking is of key importance)
▪ Deflation and the ZLB: additional argument for (temporary?) PLT (some
experience from Sweden in 1931-37)
▪ Communication and time-inconsistency issues
▪ Debates in Canada in 2011, see BoC's web page
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Rašín’s deflationary policy in Czechoslovakia
in 1919-1923
80
1900
1700
80
160
70
150
60
140
50
130
40
120
60
1500
40
1300
1100
20
900
0
700
500
-20
300
-40
.
30
110
100
1913
1915
1917
1919
inflation (y-o-y, left-hand scale)
1921
1923
1925
1927
1929
price level (1913=100, right-hand scale)
Note: from 1913 to 1920 unweighted index of adminstrated prices of 38 items, between 1921-1923
prices of food, fuels, petrol and soap, from 1924 food prices. Source: Ministry of Finance Report on
Supplying People in Czechoslovakia, 1920, Statistical Handbook of Czechoslovakia, 1925, Price
Reports of Statistical Office 1921-1929, Matoušková (2008).
20
100
10
90
0
80
1913
1920 1921 1922
1923 1924 1925
in CZK bil. (left-hand scale)
1926 1927 1928
1929
1913=100 (right-hand scale)
▪ Helped to establish the culture of price stability, but at a high cost (both
economically, and for Rašín himself)
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Performance of inflation targeting (Batini, et al.,
2006) – a free lunch in practice?
Measures of macro variability
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Performance of inflation targeting (Batini, et al.,
2006) (cont.)
Gains/losses from different regimes
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Performance of inflation targeting (Mishkin,
Schmidt-Hebbel, 2006)
Difference in inflation between inflation targeters and nontargetrs: panel samplea
Table 6. Difference in Inflation between Inflation Targeters and Nontargeters: Panel Sample a
Control group 1
Control group 2
Control group 3
Pooled
Panel
Pooled OLS
Pooled
Pooled
Panel
OLS
IV
IV
OLS
IV
Explanatory variable
(1)
(2)
(3)
(4)
(5)
(6)
Inflation-targeting dummy
–0.115
–0.457
–0.010
–0.010
–0.338
–0.491
(0.047)**
(0.000)
(0.827)
(0.827)
(0.001)***
(0.002)*
***
**
Lagged inflation
0.939
0.904
0.908
0.908
0.932
0.901
(0.000)**
(0.000)
(0.000)***
(0.000)*
(0.000)***
(0.000)*
*
***
**
**
Constant
0.596
0.660
0.568
0.160
0.590
1.023
(0.004)*
(0.002)
(0.009)***
(0.465)
(0.082)*
(0.003)
***
No. observations
1942
1942
1420
1420
1183
No. countries
34
34
34
34
21
a. Control group 1 includes all nontargeters and pre-targeters; control group 2 includes all nontargeters; control
group 3 includes pre-targeters. Nontargeters: Austria, Belgium, Denmark, France, Germany, Greece, Ireland,
Italy, Japan, Luxembourg, the Netherlands, Portugal, and the United States.
▪
1183
21
Choice of control group important for the results
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Performance of EMEs (Mishkin, Schmidt-Hebbel,
2006)
Difference in inflation between inflation targeters and nontargetrs, disaggregated
a
Table
7. Difference
Inflation between
Inflation
Targeters and Nontargeters, Disaggregated by
by
industrial
andinemerging
targeters
a
Industrial and Emerging Targeters
Explanatory variable
Inflation-targeting dummy
Lagged inflation
Constant
Control group 1
(Panel IV)
Industri
Emergin
al
g Economies
Economies
(1)
(2)
–0.071
–0.806
(0.579)
(0.000)*
**
0.889
0.892
(0.000)*
(0.000)*
**
**
0.940
0.953
(0.000)*
(0.000)*
**
**
Control group 2
(Pooled IV)
Industri
Emergi
al
ng
Economies Economies
(3)
(4)
–0.061
0.103
(0.098)
(0.118)
*
0.947
0.902
(0.000)
(0.000)
***
***
–0.070
0.196
(0.652)
(0.404)
Control group 3
(Panel IV)
Industri
Emergi
al
ng
Economies Economies
(5)
(6)
–0.142
–0.745
(0.490)
(0.002)
***
0.878
0.884
(0.000)
(0.000)
***
***
1.497
0.824
(0.002)
(0.096)
***
***
Summary statistic
No. observations
1590
1613
1080
1099
831
854
No. countries
34
33
22
25
21
20
a. Control group 1 includes all nontargeters and pre-targeters; control group 2 includes all nontargeters;
control group 3 includes pre-targeters
▪
More gain (despite worse absolute outcomes) in EMEs.
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Performance of inflation targeting (Gonçalves,
Salles, 2008)
Inflation regressions
GDP volatility regressions
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Performance of inflation targeting (Benecká, et al.,
2012)
Estimation results for control variables
Table A.2.1: Estimation results for control variables
OLS
Robust
Cluster
Price of oil
Real GDP
per capita
Trade
openness
0.0427***
(0.0084)
0.0427***
(0.0101)
-0.0005***
(0.0001)
-0.0005*
(0.0003)
-0.0085
(0.0057)
-0.0085
(0.0098)
Fixed
effects
Random
effects
0.0293**
(0.0146)
0.0405***
(0.0107)
-0.0006*** -0.0006**
(0.0002)
(0.0003)
0.1386***
(0.0494)
0.018
(0.0165)
Cap account
openness
-0.0069*** -0.0069***
(0.0014)
(0.0026)
-0.0079*
(0.0047)
-0.0076***
(0.0022)
Fixed regime
-0.0175*** -0.0175**
(0.0044)
(0.0081)
0.0075
(0.0084)
-0.0093
(0.006)
Inflation targeting
-0.0295*** -0.0295*** -0.0382*** -0.0275***
(0.004)
(0.0071)
(0.0137)
(0.0069)
Constant
Observations
R2 (adjusted/within)
F
Chi2
0.0676***
(0.0068)
0.0676***
(0.0106)
-0.0074
(0.0221)
0.0531***
(0.0091)
840
0,207
42,95
840
0,207
21,14
840
0,122
12,85
840
109,73
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Performance of IT (Walsh, 2009)
C. Walsh, 2009
“
Thus, the lessons to draw from the empirical evidence are what might
be described as “non-negative.” The contribution of inflation targeting
to low and stable inflation among industrial countries is weak, but it
also has not had negative effects on real activity. It does seem to have
anchored inflation expectations. For the developing economies,
inflation targeting has been associated with lower and more stable
inflation and real activity.
Source: http://people.ucsc.edu/~walshc/MyPapers/Kuszczak_Lecture_20090131.pdf
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”
23
IT and the crisis
▪ Even before the crisis, some people were saying that the IT alone is not
enough (e.g. W. White, BIS)
▪ The crisis has challenged the prevailing policy paradigm, including the IT
strategy, but
– CEE hard-peg countries suffered most initially (previous macro-financial
imbalances; double-digit GDP declines); later on problems in EA
periphery
– The just-do-it strategy was challenged much more than the IT (crisis
originated in the US, Greenspan‘s aura is gone)
– The policies of major central banks were actually quite loose from the ex
post view even by the IT metric (bad regime or just a policy failure?)
– The ECB‘s two-pillar policy did not help much in practice either (should
have been the money pillar given more weight?)
– IT performed quite well empirically in relative terms proved durable
even in a harsh crisis
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IT performance in the crisis (de Carvalho Filho,
2011) (1/4)
Median real GDP index, 2003=0, for IT and not-IT countries
Source: Irineu E. de Carvalho Filho (2011): “28 Months Later: How Inflation Targeters Outperformed Their Peers in the Great Recession,”
The B.E. Journal of Macroeconomics: Vol. 11: Iss. 1 (Topics) (http://www.bepress.com/bejm/vol11/iss1/art22)
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IT performance in the crisis (de Carvalho Filho,
2011) (2/4)
Policy interest rate, for IT and not-IT countries
Source: Irineu E. de Carvalho Filho (2011): “28 Months Later: How Inflation Targeters Outperformed Their Peers in the Great Recession,”
The B.E. Journal of Macroeconomics: Vol. 11: Iss. 1 (Topics) (http://www.bepress.com/bejm/vol11/iss1/art22)
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IT performance in the crisis (de Carvalho Filho,
2011) (3/4)
Real effective exchange rates: medians and difference in time effects for IT and no-IT countries
Source: Irineu E. de Carvalho Filho (2011): “28 Months Later: How Inflation Targeters Outperformed Their Peers in the Great Recession,”
The B.E. Journal of Macroeconomics: Vol. 11: Iss. 1 (Topics) (http://www.bepress.com/bejm/vol11/iss1/art22)
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IT performance in the crisis (de Carvalho Filho,
2011) (4/4)
Median 12-month inflation and the frequency of deflation scares, for IT and not-IT countries
Source: Irineu E. de Carvalho Filho (2011): “28 Months Later: How Inflation Targeters Outperformed Their Peers in the Great Recession,”
The B.E. Journal of Macroeconomics: Vol. 11: Iss. 1 (Topics) (http://www.bepress.com/bejm/vol11/iss1/art22)
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IT performance in the crisis (Rose, 2013) (1/2)
Durability of monetary regimes, small economies
▪
Inflation targeting has proven quite durable – no one has left it except for the euro
adoption
Source: http://faculty.haas.berkeley.edu/arose/Spill.pdf
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IT performance in the crisis (Rose, 2013) (2/2)
Effects of monetary regimes 2007-12: regression evidence
Effects of monetary regimes 2007-12: regression evidence
▪ Not much difference between IT and hard pegs (but better inflation performance than the other regimes)
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Conclusions
1
Inflation targeting as “constrained discretion” (flexible rule)
2
Focused on building credibility and anchoring
expectations
3
Increasing “market share” among MP regimes before
crisis, durability during the crisis
4
The experience before the crisis was “non-negative”
5
Being an EME makes it more difficult, not impossible
(and the potential gain is actually bigger)
6
The current crisis has challenged the paradigm, but IT
has empirically performed better than (or at least as
good as) most known alternatives
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