Monetary Institutions, Partisanship,
and Inflation Targeting
presented by
David Andrew Singer
Massachusetts Institute of
Technology
co-author:
Bumba Mukherjee
Princeton/University of Notre Dame
IPES
November 18, 2006
Inflation Targeting (IT):
A Nominal Anchor for Monetary Policy

Numerically specified target for inflation
–
–
2
Public commitment to price stability
Requires transparency and publication of inflation forecasts

Since 1989, 25 countries have adopted IT

The “monetary framework of choice” for LDCs (IMF
2006); Ben Bernanke also an advocate
David Andrew Singer
MIT
Table 2: Inflation Targeting Countries (as of 2003)
Country
Adoption Date
Country
Adoption Date
Australia
1993
Mexico
1995
Brazil
1999
New Zealand
1989
Canada
1991
Norway
2001
Chile
1990
Peru
2002
Colombia
1999
Philippines
2002
Czech Rep.
1997
Poland
1998
Finland
1993
S. Africa
2000
Hungary
2001
Spain
1995
Iceland
2001
Sweden
1993
Israel
1991
Thailand
2000
Korea
1998
U.K.
1992
Source: Truman (2003). The Slovak Republic, Indonesia, and Romania
adopted IT in 2005. Finland and Spain joined the EMU in 1999 and no longer
have autonomous monetary policies.
Research Question


Why do some countries adopt IT, while others do
not?
Importance:
–
–
–
4
Declining popularity of fixed exchange rates
Alternative nominal anchors (e.g., money targets) largely
discredited
Is central bank independence sufficient to fight inflation?
David Andrew Singer
MIT
Open Economy Monetary Policy Model


Two actors: government and central bank
Government’s loss function (based on Barro &
Gordon 1983; Persson & Tabellini 2000)
–
–
Inflation vs. output deviation
Our key modification: partisanship (L,R) determines degree
of inflation aversion (θ)
1
LG  [(y  y )2  G 2 ]
2
5
y  0, G  L,R
David Andrew Singer
MIT
Model (continued)

Central bank’s loss function:
–
–
Assume IT as an inflation-fighting option
Innovation: allow central bank’s inflation preferences to vary
as a function of its regulatory mandate
 Central bank regulators more sensitive to financial
stability, less likely to enact tight monetary policy
(Copelovitch and Singer 2006)
 λ = 1 if central bank and bank regulator are separated
LCB
6
1
 [(1   )( y  y ) 2  ( G   )(   T ) 2 ]
2
David Andrew Singer
MIT
Observable Implication

Adoption of IT more likely when right-leaning
government and central bank not a regulator
–
7
Compatibility of preferences between government and
central bank over inflation
David Andrew Singer
MIT
Two Empirical Analyses

First analysis: Markov transition model to explain
adoption of IT
–

8
Captures the effect of IVs on probability of adopting IT, and
conditional probability of maintaining IT
[Second analysis: parametric and non-parametric
models to explore impact of IT on inflation]
David Andrew Singer
MIT
Markov Model: Data and Variables



Sample: 49 countries, 1987-2003
DV: dichotomous (IT=1, 0 otherwise)
IVs:
–
–
–
–
–
–
9
Central bank mandate (regulator=0, separate=1)
Partisanship
CBI
Polity, veto players
Exch rate regime and variability
Economic controls
interaction
David Andrew Singer
MIT
Model 2
0
1
1
0
1
.035***
(.011)
.031***
(.012)
.045***
(.020)
.040**
(.019)
.039***
(.015)
.058***
(.014)
.050***
(.022)
.059***
(.021)
.043***
(.020)
.057***
(.022)
.061***
(.022)
.055***
(.021)
Nominal Interest rate
.068
(.074)
-.065
(.092)
.073
(.058)
-.062
(.049)
.050
(.062)
-.069
(.070)
Trade Openness
.038
(.144)
-.071
(.088)
.060
(.118)
-.075
(.073)
.022
(.145)
-.058
(.087)
REER variability
.039***
(.018)
.032***
(.010)
.020***
(.008)
.024***
(.007)
.043***
(.012)
.035***
(.014)
NEER variability
.024
(.028)
-.031
(.030)
.023
(.020)
-.035
(.028)
.035
(.030)
-.025
(.032)
Current Account
-.022**
(.011)
-.036**
(.017)
-.055*
(.030)
-.072*
(.041)
-.045**
(.018)
-.038**
(.019)
CBI
.030
(.071)
.039
(.050)
.029
(.020)
.033
(.042)
.031
(.026)
.044
(.031)
Partisanship x Separate
.151***
(.049)
.138***
(.037)
.103***
(.036)
.142***
(.040)
.132***
(.036)
Partisanship
.021*
(.012)
.032*
(.018)
.034*
(.019)
.022*
(.013)
.023*
(.014)
.024*
(.014)
Separate Central Bank
.051*
(.030)
.045*
(.024)
.043*
(.027)
.040*
(.024)
.041*
(0.22)
.055*
(.033)
Covariates
GDP Growth variability
Real Interest Rate


0
Model 3




.114***
(.045)
See paper for full regression table
Model 1
Findings

Right government + non-regulatory central bank
increases likelihood of adopting IT
–

11
When separate CB, one std. dev change in partisanship
(toward the right) increases probability by 35%
Additional finding: IT reduces inflation (see paper)
David Andrew Singer
MIT