1
. Econometric results
Clarida, Galí and Gertler (2000) estimate the monetary response function with a forward-looking
specification, where current policy actions depend on expected inflation in the future. As seen in the
previous section, several studies treat expected inflation as a monetary policy target in Brazil. Expected
inflation could also thus reasonably be treated as a variable to consider in computing the central bank
response function. However, according to Sims (1999 and 2001), forward-looking specifications have
a backward-looking equivalent. The following specification is thus adopted as a functional manner of
computing the monetary response function:
SELICt
= b0(st ) + b1(st )INFLA12t–1 + b2(st )TXPIB12t-1
+ σ(St )εt (9)
where SELIC is the annualized base rate of interest set by the Central Bank of Brazil. The other variables
were defined earlier, in section IV.
CEPAL Review N° 135 • December 2021 95
Tito Belchior S. Moreira, Mario Jorge Mendonça and Adolfo Sachsida
Below, we examine the results of monetary response function computation also estimated
using the Markov-switching model. The results are shown in table 2. Taking into account the different
specification tests, the three-regime model was the best fit for the data.21 In effect, application of
the likelihood-ratio (LR) test rejected the null hypothesis of linearity (LR = 241.45,X2(11) = [0.000]** e
X2(12) = [0.000]**
).22 The graphics of smoothed probability that illustrate the chronology of regimes are
presented in annex A2.
Table 3 shows that, whatever the regime, the Selic rate is set taking into account not only inflation
but also output growth. In all cases, the coefficients of the variables are significant, and the signs are
as expected.
According to the Taylor rule, the central bank should raise the interest rate by more than one
unit for a given rise in inflation (or expected inflation), in order to ensure stability of singularity and of
equilibrium. Thus, in keeping with the Taylor rule, monetary policy is active or restrictive if the coefficient
of inflation from equation 9 is equal to or greater than 1, and passive or accommodative if the coefficient
is less than 1 (Woodford, 2003).
Following the Taylor rule, table 3 verifies the existence of two regimes of lesser tolerance to inflation
(regimes 2 and 3), while a third regime of central bank stance on monetary policy is accommodative
(regime 1). It should be noted, however that regime 2 refers only to sporadic moments of monetary policy
in Brazil. Conversely, regime 1 is long-lasting, as it ran from late 2007 to December 2014, and mostly
coincided with the administration of Alexandre Tombini, who headed the Central Bank of Brazil from
December 2010. It is interesting to note that, although the inflation rate has eased on several occasions
since then, it shows a structural uptrend. Only after the second half of 2014 did the Central Bank of
Brazil begin to respond more strongly by gradually raising the Selic rate. Throughout 2015, the central
bank took a tight monetary policy stance, according to the analysis of regime 3. As will be seen in the
following section, the reason why inflation has continued to rise is related to the lack of control on the
part of fiscal policy and also to tariff shocks occurring just after the presidential elections of late 2014.
Table 3
Model MS(3)-AIH(1)
Dependent variable: Selic rate
Regime 1 Regime 2 Regime 3
Constant 0.025 (0.000) 0.029 (0.000) 0.169 (0.008)
INFLA12(-1) 0.955 (0.000) 1.295 (0.000) 1.780 (0.000)
TXPIB12(-1) 0.600 (0.000) 0.651 (0.000) 0.811 (0.000)
Standard deviation 0.013 (0.000) 0.001 (0.000) 0.011 (0.000)
Observations 156
Likelihood 462.137
Source: Prepared by the authors, on the basis of data from the Brazilian Institute of Geography and Statistics (IBGE) and the
Getulio Vargas Foundation.
Note: p-value in brackets.
Before Alexandre Tombini, Henrique Meirelles chaired the Central Bank of Brazil from 2003, with
a restrictive monetary policy that marked a major difference with respect to his predecessor. In addition,
during the term of Meirelles the Treasury’s fiscal policy was compatible with debt sustainability.
21 See note 12.
22 See note 13.
96 CEPAL Review N° 135 • December 2021
Fiscal and monetary policy rules in Brazil: empirical evidence of monetary and fiscal dominance
Table 4 shows the matrix of transition probabilities between states assumed by the monetary rule.
Given that regime 2 occurs only occasionally, for simplicity’s sake, the table shows the probabilities of
transition between regimes 1 and 3. A point to remark is that the probability of switching from state 1 to
state 3, and vice versa, is zero, while the sum of probabilities in each column of the matrix of transition
is less than 1. This raises the question of whether the transition between these two states will not occur
without a shock in the Selic rate.
Table 4
Transition probabilities
Pr(St = 1|St–1= 1)
0.979
(0.000)
Pr(St = 1|St–1= 3) =
0.000
(0.000)
Pr(St = 3|St–1= 1) =
0.000
(0.000)
Pr(St = 1|St–1= 3) =
0.962
(0.000)
Source: Prepared by the authors.
Note: p-value in brackets.
VI. Determination of fiscal and monetary dominance
Tables 1 and 3 showed the parameters estimated for the fiscal and monetary response functions,
respectively, to compute the absolute values of the roots of the Leeper model (1991). As was seen in
section II, characterization of the roots of the system indicates when monetary or fiscal policy behaves
actively or passively. In this context, assuming an intertemporal discount rate β = 0.95, the four situations
presented in the Leeper model (1991) can be identified, once the computed values of α and γ are known
for each of the policy (monetary and fiscal) response functions, considering also the respective regimes.
To determine the period corresponding to each of the four possible combinations of active and
passive policies, we compare the graphs shown in annexes A1 and A2. For each pair of policy rules
(fiscal and monetary) seen in table 5, we observe the intersection between the shaded areas that relate
a given monetary authority function with a given regime of the fiscal authority function.
For example, consider regime 1 of the Treasury response function and regime 3 of the central
bank response function, where γ = 0.000, α = 1.781, considering β = 0.95, which is naturally the same
for all cases. It may be observed that |αβ| = 1.691 and |β-1 – γ | = 1.052. On the basis of the Leeper
model (1991), considering the parameters computed, the results show that in this case both monetary
policy and fiscal policy were active, that is, monetary policy prioritized pursuit of the inflation target, but
fiscal policy did not prioritize pursuit of a primary surplus in alignment with public debt sustainability.
But in what period did this situation occur? Comparison of the shaded areas of annex figure A1.1 with
those of annex figure A2.3 shows that the two policies were active only in fiscal year 2015.
Table 5 helps to explain why the inflation rate continued to rise in 2015, even when the central
bank took an active monetary policy stance. The fact is that, even though monetary policy was restrictive,
fiscal policy also took an active position instead of accommodating by seeking budget equilibrium. This
is an explosive situation, in which agents will demand higher and higher interest to take on government
securities and ever-rising interest rates will drive up expectations of inflation, putting inflation control in
jeopardy. Thus, in 2015 both monetary policy and fiscal policy are seen to be active.
CEPAL Review N° 135 • December 2021 97
Tito Belchior S. Moreira, Mario Jorge Mendonça and Adolfo Sachsida
Table 5
Brazil: definition of policies as active or passive on the basis of Leeper (1991)
Parameters
Central bank response function
Parameters
Treasury response function
Regime 1
α = 0.955
Regime 2
α = 1.295
Regime 3
α = 1.781
Regime 1
γ = 0.000
|αβ| = 0.907
|β-1 – γ| = 1.052
FD
Periods: 2010; 2013 and 2014
|αβ| = 1.225
|β-1 – γ| = 1.052
|αβ| = 1.691
|β-1 – γ| = 1.052
Active fiscal and monetary
policies: 2015
Regime 2
γ = 0.299
|αβ| = 0.907
|β-1 – γ| = 0.721
Passive fiscal and monetary
policies: end-2003, 2004,
2008, 2009, 2011 and 2012
|αβ| = 1.225
|β-1 – γ| = 0.721
MD
|αβ| = 1.691
|β-1 – γ| = 0.721
MD
Periods: most of 2003,
2005–2007
Source: Prepared by the authors, on the basis of E. Leeper, “Equilibria under ‘active’ and ‘passive’ monetary and fiscal policies”,
Journal of Monetary Economics, vol. 27, No. 1, Amsterdam,
Elsevier, 1991.
Note: β = 0.95; FD: fiscal dominance, MD: monetary dominance.
This may explain to some extent why the term of Tombini was marked by an accommodative
position, even when inflation approached the ceiling of the band, indicating that it could “get out of
control”. Should the Central Bank of Brazil have taken a more active stance at that point, increasing
interest rates more steeply?
As noted by Sargent and Wallace (1981), in a situation of loose fiscal policy, the adoption of
tight monetary policy leads to an increase in the money supply and, thus, higher inflation in the future.
The question about how the central bank should administer monetary policy must therefore take into
account how fiscal policy is being conducted. The action of the monetary authority can thus be seriously
compromised if fiscal policy does not act to ensure public debt sustainability, as appears to be the case
in Brazil’s fiscal policy since 2013.
The two policies are also seen to have acted passively at the end of fiscal 2003, at the end of
fiscal 2004 and in the period 2008–2012 (except 2010).
That period is obtained from the intersection
between the shaded areas of the graph for regime 2 with respect to the fiscal policy response function
and of regime 1 with respect to the monetary policy response function. This means that fiscal policy
followed a sustainable path in relation to public debt. In the same period, however, the Central Bank
of Brazil did not respond adequately to the increases in the inflation rate. On the basis of table 5 and
observing the graphs of the chronology of regimes in annexes A1 and A2, it is apparent that there was
fiscal dominance in 2010 and between 2013 and 2014. Monetary dominance obtained for much of
2003 and in the period 2005–2007.
As shown in figure 3, in late 2014 the Brazilian economy began to run primary deficits. This is
strongly characteristic of an active fiscal policy and tighter monetary policy in the same period, since
the Selic rate23 rose from 10.92% in October 2014 to 14.15% in December 2015. The results show
empirical evidence of active conduct of both monetary policy and fiscal policy in 2015.