Araújo, Eurilton

Pinheiro, Tatiana

English

Research Papers in Economics

Policy Preferences for Output 
Stability before and after 
Inflation Targeting
Eurilton Araújo
Tatiana Pinheiro
Insper Working Paper
WPE: 157/2008Copyright Insper. Todos os direitos reservados.
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citação completa do documentoPolicy Preferences for Output Stability before and after Inflation 
Targeting 
 
Eurilton Araújo  
and  
Tatiana Pinheiro 
 
Ibmec São Paulo 
Rua Quatá 300  
São Paulo-SP, Brazil 
ZIP: 04546-042 
                                                 Email: euriltona@isp.edu.br 
      
Abstract 
This paper examines a set of inflation-targeting countries and presents evidence on the 
attitude of policymakers to positive and negative output gaps. In fact, central banks may 
dislike deviations from potential output of one sign more than deviations of the opposite sign.  
Instead of the usual quadratic specification, an asymmetric loss function describes these 
policy preferences.  In this paper, we test for asymmetries concerning the output gap. Since 
the degree of symmetry may change with policy regimes, we consider, for each country, two 
sample periods: before and after the adoption of inflation targeting. Empirical results support 
a quadratic loss function for the majority of monetary policymakers, irrespective of the 
monetary policy regime. 
 
  
Keywords: inflation targeting, central banks, symmetric preferences 
JEL Classification: E52, E58, E61 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
I.  Introduction 
A standard assumption in monetary policy games is that policymakers have quadratic and 
symmetric preferences concerning inflation deviations and output deviations from their 
respective targets. In Barro and Gordon (1983), an inflation bias arises because of the central 
banker’s ambition of targeting unemployment levels below their natural rates. 
The paper by Cukierman and Gerlach (2003) studies the Barro-Gordon model under 
asymmetric unemployment preferences. Preferences are asymmetric in that central banks may 
dislike deviations from targets of one sign more than deviations with an opposite sign.  In this 
context, the inflation bias emerges without an ambitious target for unemployment. Under 
asymmetric preferences, central bank weights recessions more strongly than expansions and 
fights the former very aggressively, leading to excessive inflation compared to the case of 
symmetric preferences. This mechanism is an alternative explanation for the inflation bias. 
The rationale for asymmetric preferences is that central bankers are not completely isolated 
from social and political pressures, being extremely concerned with the social costs of 
contractions. 
Recently, researchers have studied asymmetric preferences more systematically. Ruge-
Murcia (2003b, 2004) and Surico(2008) conduct asymmetry tests concerning output 
stabilization. The literature has also considered asymmetries concerning inflation deviations 
and has studied the implications of both types of asymmetry for monetary policy reaction 
functions. Ruge-Murcia (2003a) and Surico (2007) test the relative importance of 
asymmetries concerning inflation and output gap deviations, using non-linear specifications 
for reaction functions. The papers just mentioned do not control for the effect of distinct 
monetary policy regimes. In addition, international evidence is usually restricted to developed 
countries. 
1 
 
 
 
 In this paper, we study nine inflation-targeting countries, with different degrees of 
economic development, before and after the adoption of inflation targeting. Our goal is to 
assess empirically the idea that before inflation targeting, monetary authority tend do display 
recession aversion, since less independent central banks tend to be more sensitive to political 
pressure.  Moreover, we want to know to what extent inflation-targeting central bankers, in 
principle independent policymakers, may also be much more concerned with recessions due 
to social and political pressures. 
 Empirical results support a quadratic loss function for the majority of countries in 
both monetary regimes, showing that central banks are neither strongly concerned with 
contractions nor sensitive to pressures coming from particular groups in society worried about 
the social costs of recessions. 
 
II.  The Model 
Following Surico (2008), we consider a standard Barro-Gordon set up with asymmetric 
preferences concerning output gaps.  
An expectations-augmented Phillips curve describes the economic environment: 
               ( 1 )   t
e
t t t y ε π π θ + − = ) (
We follow the notation in which ,  t y t π  and  stands for the output gap, inflation and 
inflation expectations.  
e
t π
In addition, θ  is strictly positive and the supply-side disturbance  t ε  follows an AR (1) 
process. The private sector forms expectations rationally using information available at 
time , therefore .  1 − t ) ( 1 t t E π − =
e
t π
The central bank chooses inflation in order to minimize the following loss function 
∑
∞
=
+ −
0
1
τ
τ
τ β t t L E  
2 
 
 
 
 The parameterβ , between zero and one, is the discount factor. The period loss function is 
denoted by    and follows the Linex specification with  t L 0 > λ  
⎟ ⎟
⎠
⎞
⎜ ⎜
⎝
⎛ −
+ − =
2
2 1 ) exp(
) (
2
1
γ
γ γ
λ π π
t t
t t
y y
L
−
    (2) 
The parameters λ  and γ  represent respectively the relative weight and the 
asymmetric preference on output stability. Under asymmetric loss functions, output gap 
deviations from zero of the same size but opposite sign yield different losses depending on the 
sign of the parameterγ . If this parameter is negative, the policymaker weights recessions 
more strongly than expansions, displaying recession aversion. For a positiveγ , losses due to 
expansions are more important for the policymaker. If 0 = γ , the objective function becomes 
symmetric and quadratic as the standard specification in the Barro-Gordon model. Finally, 
π stands for the implicit target for inflation pursued by the central bank. Note that π  is not 
necessarily an announced target. Moreover, it may fluctuate over time. In this case, π  
measures an average implicit target over the analyzed sample.  
Under discretion, the central bank chooses inflation at the beginning of period, after 
private agents have formed their expectations and without observing the supply shock. The 
first order condition is  
[ 0 1 ) exp( ) ( 1 =
⎭
⎬
⎫
⎩
⎨
⎧
− − + − − t t t t y y E γ γ
γ
λθ
π π ]      (3) 
After the linearization of the exponential term, the approximate first order condition 
becomes 
0 ) (
2
) ( ) (
2
1 1 = + + + − − − t t t t t t e y E y E
λθγ
λθ π π     (4) 
The error term   stands for high order terms ignored in the first order approximation.  t e
Based on the approximate first order condition, a reduced form specification obtains 
3 
 
 
 
 t t t t y y η β α π π + + + =
2      (5) 
The error term is  
t t t t t t t t e y E y y E y − − − − − = − − )] ( [ )] ( [
2
1
2
1 β α η  
The reduced form parameters and the structural parameters follow the equations 
λθ α − = and
2
λθγ
β
−
= . 
We cannot identify all structural parameters in this monetary policy game. 
Nevertheless, since
α
β
γ
2
= , we can recover γ   from the estimates of reduced form 
parameters. 
The empirical strategy consists in first estimate the reduced form, equation (5), in 
order to find the parameters α andβ . The estimation method is GMM since the error term 
t η is correlated with  and . After that, we recover  t y
2
t y γ  and test for symmetric preferences 
concerning output stabilization.  By doing so, we can assess empirically the following 
competing claims. First, monetary policy preferences are symmetric as in the standard Barro-
Gordon model. Second, central bankers have asymmetric preferences for output stabilization, 
possibly with a negativeγ . 
III.  Data and Results 
The data comes from International Financial Statistics and Bloomberg. The data set 
consists of monthly CPI inflation and industrial production index. For seven countries, data 
ranges from 1980 to 2006. Brazil and Thailand, however, do not have reliable data starting 
from 1980. Consequently, we use a much shorter sample, starting in 1991 for Brazil and in 
1995 for Thailand. We remove seasonality from all series and compute the output gap using 
the HP filter on industrial production index. 
4 
 
 
 
 For most developing countries in our sample, the change in monetary regime occurred 
around the end of the 1990’s. Therefore, we choose to work with monthly data to increase the 
sample size used for estimation after the adoption of inflation targeting.  
Table one displays country names and specifies the year and month when each 
monetary regime starts and ends.  
Table1: Countries and Monetary Regimes 
Countries Before   
Inflation Targeting 
After  
Inflation Targeting 
Brazil 1991.M2-1999M5  1999.M6-2006.M9 
Canada 1980.M2-1991.M1  1991.M2-2006.M9 
Chile 1980.M2-1990.M8  1990.M9-2006.M9 
Colombia 1980.M2-1999M8  1999.M9-2006.M9 
Israel 1980.M2-1991.M12  1992.M1-2006.M9 
Mexico 1980.M2-2000.M12  2001.M1-2006.M9 
Sweden 1980.M2-992.M12  1993.M1-2006.M9 
UK 1980.M2-1992.M9  1992.M10-2006.M9 
Thailand 1995.M2-2000.M4  2000.M5-2006.M9 
 
We estimate equation (5) by GMM, using as instruments a constant and two lags of 
the following variables t π ,  and . The exceptions are Chile and Sweden, where we 
employ three lags of the same variables. For each estimated equation, we perform over-
identifying restriction tests. Test results indicate good specification for all estimated 
equations.  We do not report them for the sake of brevity. 
t y
2
t y
 Tables number two and three summarize the empirical findings. We report estimates 
forα ,  β andγ . The tables also show t-statistics in parentheses and p-values in squared 
brackets. 
 
5 
 
 
 
 Table2: Results before Inflation Targeting 
Countries  α   β   γ  
Brazil -0.7996 
(-2.6533) 
[0.0093] 
 
0.0047 
(1.4914) 
[0.1392] 
-0.0117 
(1.2804) 
[0.2048] 
Canada 0.0205 
(1.3735) 
[0.1720] 
0.0004 
(1.4791) 
[0.1435] 
0.0413 
(1.4740) 
[0.1430] 
 
Chile -0.08552 
(-2.2443) 
[0.0266] 
0.0011 
(2.6441) 
[0.0093] 
-0.0245 
(1.8382) 
[0.0685] 
 
Colombia 0.0364 
(1.3705) 
[0.1719] 
-0.0001 
(-1.7239) 
[0.2423] 
-0.0065 
(0.6455) 
[0.5193] 
 
Israel 0.2405 
(0.7758) 
[0.4392] 
-0.0019 
(-0.7192) 
[0.4732] 
-0.0159 
(1.0427) 
[0.5193] 
 
Mexico -0.1316 
(-1.4677) 
[0.1435] 
0.0041 
(2.2309) 
[0.0266] 
-0.0623 
(1.1389) 
[0.2559] 
 
Sweden 0.0077 
(0.3566) 
[0.7219] 
0.0005 
(0.4934) 
[0.6224] 
0.1373 
(0.2743) 
[0.7842] 
 
UK 0.15234 
(4.4961) 
[0.0121] 
0.0071 
(4.3184) 
[0.0001] 
0.0939 
(3.8752) 
[0.0002] 
 
Thailand -0.0092 
(-0.6008) 
[0.5503] 
-0.0008 
(-3.6774) 
[0.0005] 
0.1866 
(0.6188) 
[0.5385] 
 
Note: t-statistics in parentheses and p-values in squared brackets 
 
 
 
 
 
6 
 
 
 
 Table3: Results after Inflation Targeting 
Countries  α   β   γ  
Brazil -0.0414 
(-1.3572) 
[0.1783] 
-0.0014 
(-1.7404) 
[0.0854] 
0.0691 
(1.8262) 
[0.0713] 
 
Canada 0.0076 
(0.4705) 
[0.6385] 
0.0008 
(1.3186) 
[0.1889] 
0.2142 
(0.3578) 
[0.7209] 
 
Chile 0.0436 
(0.6758) 
[0.4999] 
0.0071 
(3.7715) 
[0.0002] 
0.3243 
(0.7035) 
[0.4452] 
 
Colombia -0.0201 
(-0.7610) 
[0.4488] 
-0.0011 
(-2.5725) 
[0.0119] 
0.1140 
(0.7035) 
[0.4838] 
 
Israel 0.0647 
(2.0120) 
[0.0458] 
0.0006 
(2.2963) 
[0.0229] 
0.0178 
(1.6111) 
[0.1090] 
 
Mexico -0.0272 
(-0.4466) 
[0.6566] 
-0.0076 
(-1.5597) 
[0.1236] 
0.5613 
(0.5488) 
[0.5850] 
 
Sweden -0.0059 
(-0.4245) 
[0.6717] 
0.0002 
(1.9138) 
[0.0574] 
-0.0884 
(0.4597) 
[0.6463] 
 
UK 0.0461 
(2.5362) 
[0.0121] 
0.0004 
(0.2857) 
[0.7754] 
0.0173 
(0.2767) 
[0.7824] 
 
Thailand 0.0246 
(0.9435) 
[0.3483] 
-0.0014 
(-1.3965) 
[0.1666] 
-0.1136 
(0.7557) 
[0.4521] 
 
Note: t-statistics in parentheses and p-values in squared brackets 
 
Except for the UK, from 1980.M2 to 1992.M9, we cannot reject the symmetric 
preferences hypothesis at the 5% level of significance. Consequently, concerning symmetry, 
there is evidence that monetary policymakers did not change their behavior, which is 
consistent with symmetric preferences, across different monetary regimes. 
7 
 
 
 
 According to Table 2, before inflation targeting, we can reject the hypothesis that γ  is 
zero for Chile, at the 10% level. For this period, evidence points to recession aversion. Before 
inflation targeting, empirical evidence also points to a positive and significantγ  for the UK at 
the 5% level.  
According to Table 3, after the adoption of inflation targeting, we can reject the 
hypothesis thatγ  is zero at the 10% for Brazil and Israel. The evidence points to a positiveγ  
for both countries. 
  Results for Brazil, Israel and the UK, which corroborate expansion aversion, are 
puzzling but not completely strange. Expansions may cause strong demand pressures that 
could lead to high inflation, damaging the credibility of the central bank. This mechanism 
may explain a positiveγ , especially in the case of Brazil and Israel, countries with a history of 
high inflation. 
Of course, this is not evidence that preferences under the monetary regimes considered 
are the same. Other structural parameters may be quite different across monetary regimes. For 
example, the weight on output stabilityλ , an unidentifiable parameter, may have been quite 
different before and after inflation targeting. Results may change if we consider a general 
specification, as Ruge-Murcia (2003a) and Surico (2007), allowing for asymmetry concerning 
inflation. 
 
IV.  Conclusions 
This study tests for asymmetries in monetary policy preferences for output 
stabilization. We study nine countries, with different degrees of economic development, 
before and after the adoption of inflation targeting.  In eight out of nine countries, before and 
after the adoption of inflation targeting, we cannot reject the symmetric preference hypothesis 
8 
 
 
 
 9 
 
 
 
 
at the 5% level of significance. This empirical result casts doubts on the idea that central 
bankers may behave asymmetrically towards recessions or expansions. 
 
References 
Barro, R. and D. Gordon, 1983, A positive theory of monetary policy in a natural rate model, 
Journal of Political Economy, 91, 589-610 
 
Cukierman, A. and S. Garlic, 2003, The Inflation Bias Revisited: Theory and Some 
International Evidence, The Manchester School, 71, 41-65. 
 
Ruge-Murcia, F. , 2004, The Inflation Bias when the Central Bank targets the Natural Rate of 
Unemployment, European Economic Review, 48, 91-107. 
 
Ruge-Murcia, F., 2003a, Inflation Targeting under Asymmetric Preferences, Journal of 
Money, Credit and Banking, 35, 763-85. 
 
Ruge-Murcia, F., 2003b, Does the Barro-Gordon Model Explain the Behavior of US 
Inflation? A Reexamination of the Empirical Evidence, Journal of Monetary Economics, 50, 
1375-90 
 
Surico, P., 2007, The FED’s monetary policy rule and US inflation: The case of asymmetric 
preferences, Journal of Economic Dynamics & Control, 31, 305-24. 
 
Surico, P., 2008, Measuring the Time-Inconsistency of US Monetary Policy, Economica, 75, 
22-38. 

2003a, Inflation Targeting under Asymmetric Preferences,

A positive theory of monetary policy in a natural rate model,

Does the Barro-Gordon Model Explain the Behavior of US Inflation? A Reexamination of the Empirical Evidence,

The Inflation Bias when the Central Bank targets the Natural Rate of Unemployment,

Policy Preferences for Output Stability before and after Inflation Targeting

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Policy Preferences for Output Stability before and after Inflation Targeting

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