Description
The purpose of this paper is to assess the suitability of adopting inflation targeting in an
emerging market, based on the pre-conditions of inflation targeting identified in the literature.
Journal of Financial Economic Policy
Feasibility of inflation targeting in an emerging market: evidence from Kenya
Roseline Nyakerario Misati Esman Morekwa Nyamongo Lucas Kamau Njoroge Sheila Kaminchia
Article information:
To cite this document:
Roseline Nyakerario Misati Esman Morekwa Nyamongo Lucas Kamau Njoroge Sheila Kaminchia,
(2012),"Feasibility of inflation targeting in an emerging market: evidence from Kenya", J ournal of Financial
Economic Policy, Vol. 4 Iss 2 pp. 146 - 159
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Andrew Phiri, (2012),"Threshold effects and inflation persistence in South Africa", J ournal of Financial
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Feasibility of in?ation targeting
in an emerging market: evidence
from Kenya
Roseline Nyakerario Misati, Esman Morekwa Nyamongo,
Lucas Kamau Njoroge and Sheila Kaminchia
Research Department, Central Bank of Kenya, Nairobi, Kenya
Abstract
Purpose – The purpose of this paper is to assess the suitability of adopting in?ation targeting in an
emerging market, based on the pre-conditions of in?ation targeting identi?ed in the literature.
Design/methodology/approach – The study uses Granger causality and VAR approaches to
assess the importance of the relationship between monetary policy variables and in?ation.
Findings – The ?ndings indicate a dominant role of ?scal policy on both prices and output. The
results therefore support the ?scal theory of price level, implying a need for incorporation of a ?scal
variable in the design of monetary policy. The study also observes that the employment contract of the
of?ce of the governor is relatively short-term and less than the Kenyan election cycle. The exchange
rate is found to have no role on both prices and output. More importantly, the results show that the
Kenyan economy does not meet all the conditions necessary for adopting in?ation targeting.
Originality/value – The study described in the paper is novel, as it is the ?rst attempt the authors
are aware of that empirically assesses the feasibility of in?ation targeting in Kenya. The paper
provides policy makers in emerging markets with useful information on the choice of appropriate
policy frameworks for maintaining price stability. It also demonstrates the need for evaluation of any
policy framework before adoption.
Keywords Kenya, National economy, In?ation, Fiscal policy, Emerging markets, In?ation targeting,
Monetary policy variables
Paper type Research paper
Astrict rule-based approach to monetary policy, including in?ation targeting is not desirable for
the countries of sub-Saharan Africa, given in?ation dynamics and structural realities. Any
monetarypolicyshouldinclude suf?cient scope for discretiontoallowthe central banktorespond
to shocks, especially those originating from the supply side Heintz and Ndikumana (2011).
1. Introduction
Most countries in the world strive to achieve price stability as a core function of their
monetary policy. The persistence of in?ation in a number of countries, particularly
emerging ones has generated considerable debate on the best monetary policy
frameworks for maintaining price stability without compromising other economic
policy objectives. There is no disagreement in the literature on the need to maintain low
and stable in?ation levels since high and volatile in?ationary rates are detrimental to
investments and growth (Ghalwash, 2010; Freedman and Laxton, 2009). The desire of
most countries to maintain a stable macroeconomic environment and especially price
stability has thus seen many countries re-examine their monetary policy frameworks
with an objective of adopting forward-looking monetary policy strategies.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – E5, E, E52, E5, E58
JFEP
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Journal of Financial Economic Policy
Vol. 4 No. 2, 2012
pp. 146-159
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381211228998
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This is particularly true for countries with impediments in monetary policy
transmission in the form of long lags from monetary policy actions to aggregate
economic activity and in?ation (Misati et al., 2011; Mishkin, 2004).
Countries with monetary policy transmission bottlenecks have therefore either
adopted in?ation targeting (IT) or are considering its adoption even if there is no
conclusive evidence in favour of direct improvement of economic performance
resulting from IT. As noted by Stiglitz (2008), IT can be interpreted to mean that
whenever price growth exceeds a target level, interest rates should be raised. However,
there is no reason to expect that regardless of the source of in?ation, the best response
is to increase interest rates. Some economies, particularly in Africa experience high
in?ationary pressures not necessarily related to excessive domestic demand but
associated with supply side problems, weak institutional structures, limited regulatory
capacity and high levels of ?scal de?cits and public debt.
Furthermore, even though classical theoretical models suggest that core in?ation,
which excludes volatile food and energy prices, is the proper price index to be targeted,
such issues are yet to be resolved in emerging economies, where food expenditure
account for nearly half of total household expenditure and where there are supply
constraints resulting in high food and oil imports (Heintz and Ndikumana, 2011; Prasad,
2010). Countries such as Ghana and South Africa that have already adopted IT bear
testimony to rationale for caution for other countries contemplating adoption of IT. For
example, in Ghana and South Africa, in?ation was increasing in 2007 and 2008,
respectively, not because of increased aggregate demand but due to increases in food
and oil prices (Mckinley, 2008)[1].
Moreover, no evidence exists in the literature to suggest that IT strategy is the only
framework that can achieve low and stable in?ation. Evidence shows that both IT and
non-IT central banks have been successful in taming and controlling in?ation and that
adoption or non adoption of IT is speci?c to country characteristics and conditions
(Taguchi and Kato, 2011; Ghalwash, 2010; Friedman, 2004). Whether IT is superior
over other monetary policy management frameworks is still an open question.
The main concern of this study therefore is whether the Kenyan economy will do better
in terms of price stability if it adopts IT.
Monetary policy is Kenya is conducted under a monetary targeting framework.
However, some recent studies have shown that the dynamic evolutions in the Kenyan
?nancial sector may have created disturbances in the monetary aggregates and thus
money demand function, necessitating a need to review the monetary policy
framework and understand alternative frameworks (Misati, 2010). Other related
research attempts in Kenya have focused on interest rate and exchange rate channels
of monetary policy transmission (Maturu, 2007). The study however failed to
incorporate the asset price channel in their empirical analysis inspite of the increasing
role that the stock market is playing in Kenya and its implications on monetary policy
(Misati and Nyamongo, 2011). Moreover, the rationale of the author’s recommendation
on the adoption of IT in Kenya is weak, it is not based on any evaluation of the well
identi?ed prerequisites for adoption of IT. It is against this background that this study
seeks to assess the feasibility of IT based on the assessment of the identi?ed
qualitative IT prerequisites. The paper also estimates a quantitative relationship
between monetary policy instruments and policy objectives.
Feasibility
of in?ation
targeting
147
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2. Literature review
In analysing the literature on IT, we focus on the de?nition and bene?ts of adopting IT,
re-examination of ITin the light of the ?nancial crisis, the schwartz hypothesis, the ?scal
theory of price level (FTPL) and assessment of preconditions for ITadoption. ITis de?ned
as a framework for monetary policy, characterized by public announcement of of?cial
quantitative target for the in?ation rate. It is a forward-looking policy regime which relies
strongly on rational expectations of monetary policy transmission. It is an anchor to
monitor and control price stability. The target can be speci?ed as a single point, range or
ceiling, where the single point target is consistent with a policy of “rule” while a range or a
ceiling gives “discretionary” policy ?exibility to the central bank. Discretionary ITis also
categorized into “strict IT” where the central bank is only concerned with achieving the
in?ation target or “?exible IT” where the central bank is also concerned with the stability
of output and/or the real exchange rate (Khalid, 2005)[2].
However, the approach of single point IT is actively criticized in a number of studies
(Bernanke et al., 1999; Svensson, 1999; Bernanke and Mishkin, 1997). According to these
authors, ITshould be viewed as a framework within which “constrained discretion” can
be exercised rather than a perception of following simple and mechanical operational
instructions. Under such a framework, central banks use structural and judgemental
models and all available relevant information in their pursuit of price stability. The
authors further express preference for usage of IT as opposed to income targeting for
similar reasons found in Ball (1999). The studies argue that usage of income targeting is
complicated from a data point of view and it has the potential of creating greater
variability in both output and in?ation. Speci?c arguments for IT adoption include:
desire for a credible nominal anchor for monetary policy, balancing independence and
accountability, high in?ation experience and reduction of disin?ation costs through
management of in?ation expectations of both ?nancial markets and agents in the real
economy[3] (Mishkin, 2000, 2004; Brash, 2002).
Some studies have focused on the experience from the ?nancial crisis, which shows
that asset prices have important effects on economic forecasts and hence on in?ation
and output, thus ?nancial stability should be an important element in monetary policy
implementation (Furlanetto, 2011; Issing, 2011; Disyatat, 2010; Montes, 2010).This line
of thinking supports the Schwartz hypothesis, which contends that central banks that
maintain price stability would also minimize the need for lender-of-last-resort and thus
lessen the incidence and severity of ?nancial distress. According to the proponents of
this view, in an environment of unstable prices, uncertainty over the price level makes
it dif?cult for borrowers and lenders to ascertain the real returns from investments,
leading in turn to unpro?table borrowing and lending decisions, lending booms, and
lending busts (Bordo, 2000; Bordo and Wheelock, 1998).
Contrastingly, other authors argue that low in?ation is neither necessary nor
suf?cient for ?nancial stability since enormous ?nancial market stresses built up in
many advanced economies during a time of low in?ation and stable growth, implying
that the Schwartz hypothesis may need to be re-examined in light of the crisis
experience (Kuttner, 2011; Grauwe, 2008). Moreover, examination of the resilience of IT
framework during the global crisis shows that several IT countries were hardest hit by
the crisis (Scott, 2010; Irineu, 2010).
Consistent with this view, Prasad (2010) points out that central bankers in developed
economies may have focused too much on price stability and ignored asset market
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bubbles, that are believed to have created the ?nancial crisis. Even in emerging markets,
where the effects of the crisis may have been minimal, it would still be detrimental to IT
economies if they disregard sharp exchange rate ?unctuations and boom-bust cycles in
equity and housing markets. Similar arguments focus on the negative role of IT in
creating the ?nancial crisis. Proponents of this line of thought contend that, the narrow
pursuit of ITpolicies, which aimprimarily at stabilizing in?ation over a two-three years
horizon, could actively damage ?nancial stability over longer horizons. In this case some
in?ation targeters could mistakenly neglect monetary and ?nancial developments that
may seem irrelevant for future in?ation over the short- to medium-term, but that have
important macroeconomic effects over long horizons (Frappa and Mesonnier, 2010).
Other critics of IT contend that IT may be too rigid particularly when the adopted
range is not consistent with policy horizons. According to this view, the horizon for
in?ation targets needs to be ?exible and should vary depending on the nature and
persistence of shocks (Mishkin, 2004). In support of this contetion, Friedman (2004)
argues that the IT framework obscures central bank’s goals. In this case, the central
bank manipulates public expectations by quantifying only one goal inspite of having
multiple goals. Concerns for real outcomes maintained by policy makers are therefore
hidden, which undermines transparency[4].
Considerable research has also focused on the FTPL, which contends that, the goal
of price stability may remain elusive even with an independent central bank under an
IT framework unless steps are taken to ensure appropriate ?scal policies (Leeper and
Walker, 2011; Bajo-Rubio et al., 2009; Moreira et al., 2007; Christiano and Fitzgerald,
2000). Under this framework, monetary policy rules are not suf?cient to gaurantee
price stability thus a rule for ?scal policy would be a useful tool, through commitments
to satisfy the government’s solvency condition and the introduction of budget targets
or even de?cit rules.
Complementary to the FTPL, some of the empirical evidence on the preconditions
and appropriateness of IT indicate a huge role for ?scal dominance, particularly in
emerging markets (Mishra and Mishra, 2009). For instance, Ghalwash (2010) who
tracked the relationship between policy variables and CPI and GDP in Egypt found a
signi?cant role for ?scal policy in explaining GDP and CPI but an insigni?cant
explaination by interest rate and money supply. Thus, there was insuf?cient evidence
to support IT as a monetary policy framework for the achievement of price stability.
The foregoing review does not single out IT as the most appropriate price stability
framework. The dearth of literature on African economies is also obvious.
3. PRE-conditions for in?ation targeting
The literature identi?es the independence of the central bank, absence of ?scal
dominance, availability of a variety of models and modellers with adequate capacity
and existence of a relationship between monetary policy variables and in?ation as key
prerequisites for IT. The extent to which Kenya meets each of the elements is discussed
below.
i. Independence of the central bank
The agency theory of central bank independence contends that a negative relationship
between central bank independence and in?ation is desirable for IT. In assessing the
degree of independence of a central bank, both political and economic indicators
Feasibility
of in?ation
targeting
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are often used. Political independence refers to a situation where the central bank
makes policy decisions without interference from the core executive. This includes
absence of blackmail or intimidation from the executive. Full monetary independence
entails both goal and instrument independence. Goal independence occurs when a
central bank has complete discretion in setting the ultimate goals of monetary policy
while instrument independence refers to a situation where the bank is free to choose
instruments to achieve its goals (Florin, 2009; Oyedokun, 2007).
To achieve independence, most countries delegate monetary policy to technocrats
and offer them long term employment contracts (Gauti and Le Borgne, 2010). This
insulates such important policy task implementors from political interference and
election pressures. A technocrat with a longer term employment contract is willing to
risk more and/or work harder for policy tasks he/she holds, with certainty, for a
considerable amount of time. Thus, such a technocrat can have a long-termhorizon that
can enhance performance as opposed to a politician who may have a perverse
incentive to follow public opinion even if he/she has superior private information that
contradicts it[5].
In Kenya, the Constitution of Kenya (Government of Kenya, 2010) establishes the
Central Bank of Kenya in Section 231(1). Section 231(3) further states that:
The Central Bank of Kenya shall not be under the direction or control of any person or
authority in the exercise of its powers or in the performance of its functions.
This clause would be interpreted to imply that the Bank is free of any external
interference in the discharge of its duties. The Central Bank of Kenya Act, Cap 491 also
gives the of?ce of the Governor security of tenure. The Governor is appointed by the
president for a term of four years that is renewal once. However, to the extent that the
termof the bearer of the of?ce of the Governor is only four years makes it dif?cult to rule
out political motives in the original design of appointments, considering that Kenya has
a ?ve-year political cycle/election cycle. Moreover, what is the motive behind a four year
term that is not only just one year less that the election cycle but also only renewal once
conciding with two terms in of?ce for the country’s chief executive of?cer?
ii. Macroeconomic model/in?ation forecasting model
A central bank should have a range of complementary models to make in?ation
forecasts. As noted by Olo?n (2008), such models include a core macroeconometric
model, a small-scale model targeted at the monetary sector, vector autoregressive
(VAR) models, Phillips curve models and a disaggregated in?ation forecasting model.
Usage of more than one model is prefereble because it facilitates comparison of
forecasting results or averaging across various results to ensure the best forecast
possible. Thus, any Monetary Authority intending to adopt IT should have technical
and institutional capacity for modeling and forecasting domestic in?ation. It should
also have some idea or prediction of the time it takes for the determinants of in?ation to
have their full effect on in?ation rate (Ghalwash, 2010; Giorgi and Billmeier, 2007).
In Kenya, a macroeconometric model, popularly referred to as the KIPPRA-Treasury
macroeconometric model (KTMM), was developed in 2001 (Huizinga et al., 2001;
Geda et al., 2001). However, the KTTM is not useful in its present form because, ?rst,
since 2001, the ?nancial sector has been transformed in terms of new ?nancial
instruments and new and ef?cient methods of payments and transactions. Thus,
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parameters of the demand for money have also consequently changed. Second, of the
four blocks of the economy considered in the KTMM, the monetary block, which is the
most important for this study is weak in terms of relationships between monetary policy
and the rest of the economy. Motivated by some of these identi?ed weaknesses in the
KTMM, the Bank has embarked on building a macroeconometric model which
addresses these weaknesses and lays more emphasis on the monetary block.
iii. Absence of ?scal dominance
The central bank is expected to be free of any ?scal interferences in monetary policy
implementation. Absence of ?scal dominance implies that the conduct of monetarypolicy
is not dictated or severely constrained by developments of a ?scal nature (Masson et al.,
1997). Monetizationof ?scal de?cits andprovisionof indirect credit throughparticipation
in management of public debt in the primary market by central banks is also considered
as ?scal dominance. There are various measures of ?scal dominance, namely, siegnorage,
in?ation taxrate, ?scal de?cits as a ratio of GDPandpublic debt as a ratio of GDP, among
others (Mishra and Mishra, 2009; Masson et al., 1997).
In Figure 1, public debt as a ratio of GDP is over 50 percent over the period 2003-2006.
It reduced slightly between 2008-2009 and subsequently increased to previous levels of
over 50 percent. To effectively achieve IT, ?scal discipline is a critical component and
public debt which is 50 percent of GDP with no proper revenue enhancing reforms in
place can greatly undermine monetary policy management in an IT framework.
iv. Monetary policy instruments and in?ation linkages
Existence of a relationship between monetary policy instruments and in?ation is the
most important and quantatively assessable requirement for IT. Successful IT requires
a stable feedback mechanism from monetary policy variables to in?ation. This section
Figure 1.
Debt as a percentage
of GDP: 2003-2010
Source: Computed fron Treasury figures
Note: Author's own creation
Feasibility
of in?ation
targeting
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presents a VAR framework and results for quantative assessment of the relationship
between monetary policy variables and in?ation.
Methodology. In modelling the relationship between monetary policy variables and
the key policy variables, we use a VAR methodology. The baseline model is speci?ed
as follows:
Y
t
¼ AðLÞY
t21
þ 1
t
ð1Þ
Where Y
t
is a vector of endogenous variables. These endogenous set of variables can
be represented in (2):
Y
t
¼ bGDP
t
; CPI
t
; Interest
t
; M3
t
; FEXPE
t
; NEER
t
; NSEI
t
c; ð2Þ
Where GDP and CPI represent real gross domestic product and in?ation rate,
respectively. The two variables are obtained from the Kenya Bureau of Statistics.
Interest, M3 and NEER representing, interest rates, broad money and nominal effective
exchange rate, respectively, are obtained from the Central Bank of Kenya. NSEI
represents the Nairobi Stock Exchange Index and is obtained from the Nairobi Stock
Exchange while FEXPE represent ?scal expenditure and is obtained from the
Treasury. Data used in this study covers the period 1996Q1-2010Q2.
Under the VAR framewok, we use impulse response functions (IRF) to evaluate the
effectiveness of a policy change. Since it is impossible to shock one variable with other
variables ?xed, some kind of transformation is needed. Cholesky decomposition which
facilitates choice of ordering of variables is the most popular ( Jakob and Elbourne,
2009). Cholesky decomposition imposes recursive causal structure from the top
variables to the bottom variables in a triangular matrix. The resulting IRF from this
transformation can therefore be given causal interpretation.
The recursive VAR implies that the ?rst variable responds only to its own shock,
the second variable responds to the ?rst variable plus to a shock to the second variable
and the last variable in the system reacts without delay to all shocks, but disturbances
to this variable have no contemporaneous effect on the other variables (Charalambos,
2010). In our study, output is ordered before prices because it is assumed to respond
sluggishly. It is therefore assumed that shocks to policy variables have no
contemporaneous impact on output and prices due to real sector slow reaction to
monetary and exchange rate variables in the short run. M3 is ordered after interest rate
and before exchange rate. Nominal interest rate responds contemporaneously to
shocks to output and prices but not to changes in ?nancial variables.
In our study, we use the unrestricted VAR representation since no consensus exists
in the literature concerning the usage of VAR model in levels or in ?rst differences. As
noted by Farzanegan and Gunther (2009), if all used variables follow an I(0) process,
the speci?cation in levels is appropriate. Most time series variables are non-stationary,
thus using differenced variables would be recommended, where a vector error
correction model (VECM) would seem to be the most ideal. However, various studies
have found that usage of unrestricted VAR is superior in terms of forecast variance to a
restricted VECM at short horizons (Hoffman and Rasche, 1996; Clements and Hendry,
1995; Engle and Yoo, 1987). Other studies have also established that the performance of
unrestricted VARs and VECMs for impulse response analysis is similar over the
short-run (Naka and Tufte, 1997)[6].
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Discussion of the results. In this sub-section, we present results from causality tests,
IRF and variance decomposition. The main focus is on the importance of monetary
policy variables in determining changes in in?ation[7].
Granger causality tests. In Table I, the bivariate tests for in?ation suggest that ?scal
expenditure cause signi?cant ?unctuations in prices. Fiscal policy therefore plays a
critical role in achieving price stability, implying that ?scal reforms to eliminate any
dominance are crucial for successful IT implementation. The results for the link from
interest rate and money supply to in?ation are mixed. While money supply signi?cantly
affects prices, interest rate does not explain prices. The results further showthat interest
rates and the stock market have a signi?cant Granger-effect on output but not on prices
while the exchange rate does not affect both prices and output.
Impulse response functions. Figure 2 shows IRF showing the relationship between
monetary policy variables and output and prices. The results indicate that shocks to M3
have a positive and signi?cant effect on prices but with a lag of over four quarters.
However, a shock in the short term interest rate has an insigni?cant effect on prices.
A shock to the stock market index results in signi?cant reduction in prices from the
?rst to the fourth quarters while a shock to government expenditure positively affects
prices signi?cantly in the ?rst three quarters. A shock to the exchange rate does not
affect prices. These results suggest that while ?scal policy clearly has a role to play in
in?ation, the role of monetary policy is not clear since the results are mixed and
sensitive to the indicator used. The effect from the stock market points out the bene?ts
of competition from other sources of funding besides the banking sector in meeting
monetary policy objectives.
Money supply affects output in the ?rst two quarters and in the sixth quarter while
the short term interest rates affect output in the sixth-seventh quarter. The role of ?scal
policy on output is also signi?cant in the ?rst three and half quarters as shown by the
effect of a shock in ?scal expenditure on GDP. Ashock to the stock market signi?cantly
affects GDP in the third and fourth quarters while the exchange rate does not explain
GDP. It is expected that increases in the exchange rate (depreciation) should increase a
country’s level of competitiveness and enhance the export sector and assuming that the
import bill is relatively low, such depreciation should ultimately increase trade in net
terms and thus positively in?uence GDP and prices. The results of the exchange rate on
output may therefore be explained by the possibility of either a relatively large import
bill or the inability of this model to capture the indirect effects of trade on GDP.
Effects on CPI x
2
Probability Effects on GDP x
2
Probability
GDP 1.93 0.3802 CPI 5.80 0.0549
*
M3 14.98 0.0006
* *
M3 2.898 0.2347
FEXPE 7.34 0.0254
*
FEXPE 4.233 0.1204
INTEREST 4.19 0.1228 INTEREST 9.557 0.0084
* *
NEER 1.01 0.6009 NEER 2.386 0.3032
NSEI 1.225 0.5418 NSEI 27.17 0.0000
* *
JOINTLY 44.31 0.0000
* *
JOINTLY 108.94 0.0000
* *
Notes: Rejection of the exclusion at the
*
5 and
* *
1 percent levels; the block Granger causality test for
exclusion of a variable is based on a Wald test and follows a x
2
distribution
Table I.
Granger causality tests:
baseline VAR,
1996Q1-2010Q2
Feasibility
of in?ation
targeting
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Variance decomposition. We calculate the variance decomposition to determine the
share of ?unctations in prices and output. The results are presented in Tables II-III.
The results indicate that within three quarters, innovations to ?scal expenditure
account for over 20 percent variations in prices but there after, the proportionate
explaination decreases to around 10 percent at the tenth quarter. Innovations to M3,
short term interest rates, stock market index and the exchange rate explain less than
15 percent of the ?unctuation in prices within three quarters. Subsequently, the
proportionate explanation of M3 increases to about 30 percent in the tenth quarter
while the stock market index, exchange rate and short term rates each explain between
5 and 10 percent of the variation as the period progresses after the third quarter.
Period GDP CPI2 M3 TB_RATES NEER NSEI FEXPE
1 8.917057 91.08294 0.000000 0.000000 0.000000 0.000000 0.000000
2 7.614271 66.83516 1.615094 0.050750 0.034128 0.030357 23.82024
3 6.674247 58.89098 3.390880 3.860516 3.105711 3.434793 20.64287
4 8.393097 50.81436 3.351744 3.338044 3.321053 13.15426 17.62744
5 7.243705 43.54055 13.46884 4.099743 4.784485 11.78359 15.07909
6 7.397434 39.63477 14.32325 6.136519 7.898905 10.80444 13.80468
7 7.553685 37.43362 18.72349 5.521615 7.958175 9.701386 13.10802
8 10.93164 35.71726 20.02502 4.971640 7.348261 8.960639 12.04554
9 10.93811 32.22778 25.84528 4.795383 7.727573 7.875746 10.59013
10 9.863275 29.00386 29.95423 5.155517 8.922413 7.470640 9.630066
Table II.
Variance decomposition
of prices
Figure 2.
IRF for in?ation
and output
–8
–4
0
4
8
12
1 2 3 4 5 6 7 8 9 10
–8
–4
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8
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–8
–4
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–8
–4
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1 2 3 4 5 6 7 8 9 10
–8
–4
0
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8
12
–8
–4
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8
12
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
Response of GDP to CPI2 Response of GDP to M3 Response of GDP to TBILL_RATES Response of GDP to FEXPE
Response of GDP to NEER Response of GDP to NSEI
–4
–2
0
2
4
–4
–2
0
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–4
–2
0
2
4
–4
–2
0
2
4
–4
–2
0
2
4
–4
–2
0
2
4
Response of CPI2 to GDP Response of CPI2 to M3
Response of CPI2 to TBILL_RATES Response of CPI2 to FEXPE Response of CPI2 to NEER Response of CPI2 to NSEI
Response to Cholesky One S.D. Innovations ± 2 S.E.
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In Table III, the results show that, within one year, innovations to stock market, M3,
exchange rate and short term interest rates account for 13 percent, 9 percent, 10 percent
and 6 percent of the ?unctuations in output, respectively. Subsequently, the proportionate
explanation of the exchange rate reduces to 6 percent at the tenth quarter while that of the
M3andshort terminterest rates increases to19percent and13 percent, respectively. Fiscal
expenditure explains only 2 percent of the ?unctautions in output.
4. Conclusions and policy observations
After New Zealand adopted IT two decades ago, several countries followed suit with
the believe that it was a superior macro economic management tool for attaining price
stability. Subsequently, existing empirical evidence and country experience has shown
that adoption of IT is not the standard framework of achieving low and stable in?ation.
Nevertheless, many countries from emerging markets and sub-Saharan Africa in
particular, whose current monetary policy frameworks are not performing as desired
are in the process of considering adoption of IT. Using Granger causality and VAR
approaches, this study sought to understand the operations and elements of IT in an
emerging market.
The analysis of the main prerequisites of ITindicate a dominant role of the ?scal sector
on prices and output. The results also show that whereas money supply and the stock
market signi?cantly affect in?ation, interest rate and the exchange rate play no role in
in?ation. Similarly, while the exchange rate does not affect output, both the
monetary policy variables and government expenditure signi?cantly affect output.
Variance decomposition ?ndings show that within three quarters, innovations to ?scal
expenditure account for over 20 percent variations in in?ation while the same variable
explains only 2 percent of the ?unctutions in output. Money supply and interest rates
account for less than 10 percent of the variations in in?ation within one year. The study
also observes that the contract of the of?ce of the governor is short and less than
the election cycle. Shorter term contracts with years that are less than election cycles are
prone to possibilities of political intereference and may not foster monetary policy
effecctiveness.
The study therefore makes three policy observations. First, the length of the
employment contract of governors should not only be long enough but it should also be
longer than election cycles. Second, ?scal dominance should be eliminated through
implementation of ?scal reforms including minimization of unnecessary government
Period GDP CPI2 M3 TB_RATES NEER NSEI FEXPE
1 100.0000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
2 69.78340 7.116896 9.478291 0.602264 8.921818 3.363175 0.734152
3 54.18808 9.214798 8.144280 5.043507 11.87224 10.40512 1.131977
4 48.59485 11.24071 9.313685 5.987351 10.41983 13.26489 1.178683
5 47.93081 13.63066 10.11529 5.834336 8.829707 11.31359 2.345603
6 42.93664 11.99698 15.86976 8.390299 7.817638 10.84472 2.143970
7 37.07893 10.70171 18.12371 11.36682 7.685768 13.01898 2.024083
8 34.92215 10.27048 18.31610 12.70161 7.244160 14.33890 2.206605
9 35.22701 10.84680 18.25872 12.70032 7.213852 13.65409 2.099215
10 34.86570 10.42736 19.03388 13.66262 6.905593 13.05582 2.049018
Table III.
Variance decomposition
of GDP
Feasibility
of in?ation
targeting
155
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expenditures and enhancement of revenue collection efforts Third, IT does not promise
an end to macroeconomic instability, particularly for countries that face supply
constraints, caution should therefore be exercised in its adoption. Any country opting
for IT should adopt suf?cient IT bands, longer horizons than the monetary policy
transmission lag and its government should be actively involved in setting the target
so as to constrain ?scal dominance.
Notes
1. Other countries that have adopted IT include: New Zealand, Israel, the Czech Republic,
Poland, Brazil, Chile, Colombia, Thailand, Korea, Mexico, Hungary, Peru, the Philippines,
Slovakia, Indonesia, Romania, Canada, the United Kingdom, Sweden, Australia, Iceland and
Norway. A whole list of in?ation targeters and other details for the respective country’s
experience of IT is available in Scott (2010) and Mishra and Mishra (2009).
2. See ShehuandAbwaku(2009) andAngeriz andArestis (2008) for further categorizations of IT.
3. Details of usage of the exchange rate and monetary aggregates as nominal anchors can be
found in Brash (1998).
4. See details of the need for multiple central bank objectives in Ocampo (2011).
5. For example, in the Federal Reserve Board each governor is appointed by the president for a
14-year term.
6. Nevertheless, we conducted unit root tests which revealed some non-stationarity in some
variables. We further estimated VAR in differences and the results were similar to the
unrestricted VAR.
7. The system exogeneity Wald test results, which were not signi?cantly different from block
exogeneity results are not reported for brevity purposes.
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Corresponding author
Roseline Nyakerario Misati can be contacted at: [email protected]
Feasibility
of in?ation
targeting
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This article has been cited by:
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doc_705273043.pdf
The purpose of this paper is to assess the suitability of adopting inflation targeting in an
emerging market, based on the pre-conditions of inflation targeting identified in the literature.
Journal of Financial Economic Policy
Feasibility of inflation targeting in an emerging market: evidence from Kenya
Roseline Nyakerario Misati Esman Morekwa Nyamongo Lucas Kamau Njoroge Sheila Kaminchia
Article information:
To cite this document:
Roseline Nyakerario Misati Esman Morekwa Nyamongo Lucas Kamau Njoroge Sheila Kaminchia,
(2012),"Feasibility of inflation targeting in an emerging market: evidence from Kenya", J ournal of Financial
Economic Policy, Vol. 4 Iss 2 pp. 146 - 159
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Feasibility of in?ation targeting
in an emerging market: evidence
from Kenya
Roseline Nyakerario Misati, Esman Morekwa Nyamongo,
Lucas Kamau Njoroge and Sheila Kaminchia
Research Department, Central Bank of Kenya, Nairobi, Kenya
Abstract
Purpose – The purpose of this paper is to assess the suitability of adopting in?ation targeting in an
emerging market, based on the pre-conditions of in?ation targeting identi?ed in the literature.
Design/methodology/approach – The study uses Granger causality and VAR approaches to
assess the importance of the relationship between monetary policy variables and in?ation.
Findings – The ?ndings indicate a dominant role of ?scal policy on both prices and output. The
results therefore support the ?scal theory of price level, implying a need for incorporation of a ?scal
variable in the design of monetary policy. The study also observes that the employment contract of the
of?ce of the governor is relatively short-term and less than the Kenyan election cycle. The exchange
rate is found to have no role on both prices and output. More importantly, the results show that the
Kenyan economy does not meet all the conditions necessary for adopting in?ation targeting.
Originality/value – The study described in the paper is novel, as it is the ?rst attempt the authors
are aware of that empirically assesses the feasibility of in?ation targeting in Kenya. The paper
provides policy makers in emerging markets with useful information on the choice of appropriate
policy frameworks for maintaining price stability. It also demonstrates the need for evaluation of any
policy framework before adoption.
Keywords Kenya, National economy, In?ation, Fiscal policy, Emerging markets, In?ation targeting,
Monetary policy variables
Paper type Research paper
Astrict rule-based approach to monetary policy, including in?ation targeting is not desirable for
the countries of sub-Saharan Africa, given in?ation dynamics and structural realities. Any
monetarypolicyshouldinclude suf?cient scope for discretiontoallowthe central banktorespond
to shocks, especially those originating from the supply side Heintz and Ndikumana (2011).
1. Introduction
Most countries in the world strive to achieve price stability as a core function of their
monetary policy. The persistence of in?ation in a number of countries, particularly
emerging ones has generated considerable debate on the best monetary policy
frameworks for maintaining price stability without compromising other economic
policy objectives. There is no disagreement in the literature on the need to maintain low
and stable in?ation levels since high and volatile in?ationary rates are detrimental to
investments and growth (Ghalwash, 2010; Freedman and Laxton, 2009). The desire of
most countries to maintain a stable macroeconomic environment and especially price
stability has thus seen many countries re-examine their monetary policy frameworks
with an objective of adopting forward-looking monetary policy strategies.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – E5, E, E52, E5, E58
JFEP
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Journal of Financial Economic Policy
Vol. 4 No. 2, 2012
pp. 146-159
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381211228998
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This is particularly true for countries with impediments in monetary policy
transmission in the form of long lags from monetary policy actions to aggregate
economic activity and in?ation (Misati et al., 2011; Mishkin, 2004).
Countries with monetary policy transmission bottlenecks have therefore either
adopted in?ation targeting (IT) or are considering its adoption even if there is no
conclusive evidence in favour of direct improvement of economic performance
resulting from IT. As noted by Stiglitz (2008), IT can be interpreted to mean that
whenever price growth exceeds a target level, interest rates should be raised. However,
there is no reason to expect that regardless of the source of in?ation, the best response
is to increase interest rates. Some economies, particularly in Africa experience high
in?ationary pressures not necessarily related to excessive domestic demand but
associated with supply side problems, weak institutional structures, limited regulatory
capacity and high levels of ?scal de?cits and public debt.
Furthermore, even though classical theoretical models suggest that core in?ation,
which excludes volatile food and energy prices, is the proper price index to be targeted,
such issues are yet to be resolved in emerging economies, where food expenditure
account for nearly half of total household expenditure and where there are supply
constraints resulting in high food and oil imports (Heintz and Ndikumana, 2011; Prasad,
2010). Countries such as Ghana and South Africa that have already adopted IT bear
testimony to rationale for caution for other countries contemplating adoption of IT. For
example, in Ghana and South Africa, in?ation was increasing in 2007 and 2008,
respectively, not because of increased aggregate demand but due to increases in food
and oil prices (Mckinley, 2008)[1].
Moreover, no evidence exists in the literature to suggest that IT strategy is the only
framework that can achieve low and stable in?ation. Evidence shows that both IT and
non-IT central banks have been successful in taming and controlling in?ation and that
adoption or non adoption of IT is speci?c to country characteristics and conditions
(Taguchi and Kato, 2011; Ghalwash, 2010; Friedman, 2004). Whether IT is superior
over other monetary policy management frameworks is still an open question.
The main concern of this study therefore is whether the Kenyan economy will do better
in terms of price stability if it adopts IT.
Monetary policy is Kenya is conducted under a monetary targeting framework.
However, some recent studies have shown that the dynamic evolutions in the Kenyan
?nancial sector may have created disturbances in the monetary aggregates and thus
money demand function, necessitating a need to review the monetary policy
framework and understand alternative frameworks (Misati, 2010). Other related
research attempts in Kenya have focused on interest rate and exchange rate channels
of monetary policy transmission (Maturu, 2007). The study however failed to
incorporate the asset price channel in their empirical analysis inspite of the increasing
role that the stock market is playing in Kenya and its implications on monetary policy
(Misati and Nyamongo, 2011). Moreover, the rationale of the author’s recommendation
on the adoption of IT in Kenya is weak, it is not based on any evaluation of the well
identi?ed prerequisites for adoption of IT. It is against this background that this study
seeks to assess the feasibility of IT based on the assessment of the identi?ed
qualitative IT prerequisites. The paper also estimates a quantitative relationship
between monetary policy instruments and policy objectives.
Feasibility
of in?ation
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2. Literature review
In analysing the literature on IT, we focus on the de?nition and bene?ts of adopting IT,
re-examination of ITin the light of the ?nancial crisis, the schwartz hypothesis, the ?scal
theory of price level (FTPL) and assessment of preconditions for ITadoption. ITis de?ned
as a framework for monetary policy, characterized by public announcement of of?cial
quantitative target for the in?ation rate. It is a forward-looking policy regime which relies
strongly on rational expectations of monetary policy transmission. It is an anchor to
monitor and control price stability. The target can be speci?ed as a single point, range or
ceiling, where the single point target is consistent with a policy of “rule” while a range or a
ceiling gives “discretionary” policy ?exibility to the central bank. Discretionary ITis also
categorized into “strict IT” where the central bank is only concerned with achieving the
in?ation target or “?exible IT” where the central bank is also concerned with the stability
of output and/or the real exchange rate (Khalid, 2005)[2].
However, the approach of single point IT is actively criticized in a number of studies
(Bernanke et al., 1999; Svensson, 1999; Bernanke and Mishkin, 1997). According to these
authors, ITshould be viewed as a framework within which “constrained discretion” can
be exercised rather than a perception of following simple and mechanical operational
instructions. Under such a framework, central banks use structural and judgemental
models and all available relevant information in their pursuit of price stability. The
authors further express preference for usage of IT as opposed to income targeting for
similar reasons found in Ball (1999). The studies argue that usage of income targeting is
complicated from a data point of view and it has the potential of creating greater
variability in both output and in?ation. Speci?c arguments for IT adoption include:
desire for a credible nominal anchor for monetary policy, balancing independence and
accountability, high in?ation experience and reduction of disin?ation costs through
management of in?ation expectations of both ?nancial markets and agents in the real
economy[3] (Mishkin, 2000, 2004; Brash, 2002).
Some studies have focused on the experience from the ?nancial crisis, which shows
that asset prices have important effects on economic forecasts and hence on in?ation
and output, thus ?nancial stability should be an important element in monetary policy
implementation (Furlanetto, 2011; Issing, 2011; Disyatat, 2010; Montes, 2010).This line
of thinking supports the Schwartz hypothesis, which contends that central banks that
maintain price stability would also minimize the need for lender-of-last-resort and thus
lessen the incidence and severity of ?nancial distress. According to the proponents of
this view, in an environment of unstable prices, uncertainty over the price level makes
it dif?cult for borrowers and lenders to ascertain the real returns from investments,
leading in turn to unpro?table borrowing and lending decisions, lending booms, and
lending busts (Bordo, 2000; Bordo and Wheelock, 1998).
Contrastingly, other authors argue that low in?ation is neither necessary nor
suf?cient for ?nancial stability since enormous ?nancial market stresses built up in
many advanced economies during a time of low in?ation and stable growth, implying
that the Schwartz hypothesis may need to be re-examined in light of the crisis
experience (Kuttner, 2011; Grauwe, 2008). Moreover, examination of the resilience of IT
framework during the global crisis shows that several IT countries were hardest hit by
the crisis (Scott, 2010; Irineu, 2010).
Consistent with this view, Prasad (2010) points out that central bankers in developed
economies may have focused too much on price stability and ignored asset market
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bubbles, that are believed to have created the ?nancial crisis. Even in emerging markets,
where the effects of the crisis may have been minimal, it would still be detrimental to IT
economies if they disregard sharp exchange rate ?unctuations and boom-bust cycles in
equity and housing markets. Similar arguments focus on the negative role of IT in
creating the ?nancial crisis. Proponents of this line of thought contend that, the narrow
pursuit of ITpolicies, which aimprimarily at stabilizing in?ation over a two-three years
horizon, could actively damage ?nancial stability over longer horizons. In this case some
in?ation targeters could mistakenly neglect monetary and ?nancial developments that
may seem irrelevant for future in?ation over the short- to medium-term, but that have
important macroeconomic effects over long horizons (Frappa and Mesonnier, 2010).
Other critics of IT contend that IT may be too rigid particularly when the adopted
range is not consistent with policy horizons. According to this view, the horizon for
in?ation targets needs to be ?exible and should vary depending on the nature and
persistence of shocks (Mishkin, 2004). In support of this contetion, Friedman (2004)
argues that the IT framework obscures central bank’s goals. In this case, the central
bank manipulates public expectations by quantifying only one goal inspite of having
multiple goals. Concerns for real outcomes maintained by policy makers are therefore
hidden, which undermines transparency[4].
Considerable research has also focused on the FTPL, which contends that, the goal
of price stability may remain elusive even with an independent central bank under an
IT framework unless steps are taken to ensure appropriate ?scal policies (Leeper and
Walker, 2011; Bajo-Rubio et al., 2009; Moreira et al., 2007; Christiano and Fitzgerald,
2000). Under this framework, monetary policy rules are not suf?cient to gaurantee
price stability thus a rule for ?scal policy would be a useful tool, through commitments
to satisfy the government’s solvency condition and the introduction of budget targets
or even de?cit rules.
Complementary to the FTPL, some of the empirical evidence on the preconditions
and appropriateness of IT indicate a huge role for ?scal dominance, particularly in
emerging markets (Mishra and Mishra, 2009). For instance, Ghalwash (2010) who
tracked the relationship between policy variables and CPI and GDP in Egypt found a
signi?cant role for ?scal policy in explaining GDP and CPI but an insigni?cant
explaination by interest rate and money supply. Thus, there was insuf?cient evidence
to support IT as a monetary policy framework for the achievement of price stability.
The foregoing review does not single out IT as the most appropriate price stability
framework. The dearth of literature on African economies is also obvious.
3. PRE-conditions for in?ation targeting
The literature identi?es the independence of the central bank, absence of ?scal
dominance, availability of a variety of models and modellers with adequate capacity
and existence of a relationship between monetary policy variables and in?ation as key
prerequisites for IT. The extent to which Kenya meets each of the elements is discussed
below.
i. Independence of the central bank
The agency theory of central bank independence contends that a negative relationship
between central bank independence and in?ation is desirable for IT. In assessing the
degree of independence of a central bank, both political and economic indicators
Feasibility
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are often used. Political independence refers to a situation where the central bank
makes policy decisions without interference from the core executive. This includes
absence of blackmail or intimidation from the executive. Full monetary independence
entails both goal and instrument independence. Goal independence occurs when a
central bank has complete discretion in setting the ultimate goals of monetary policy
while instrument independence refers to a situation where the bank is free to choose
instruments to achieve its goals (Florin, 2009; Oyedokun, 2007).
To achieve independence, most countries delegate monetary policy to technocrats
and offer them long term employment contracts (Gauti and Le Borgne, 2010). This
insulates such important policy task implementors from political interference and
election pressures. A technocrat with a longer term employment contract is willing to
risk more and/or work harder for policy tasks he/she holds, with certainty, for a
considerable amount of time. Thus, such a technocrat can have a long-termhorizon that
can enhance performance as opposed to a politician who may have a perverse
incentive to follow public opinion even if he/she has superior private information that
contradicts it[5].
In Kenya, the Constitution of Kenya (Government of Kenya, 2010) establishes the
Central Bank of Kenya in Section 231(1). Section 231(3) further states that:
The Central Bank of Kenya shall not be under the direction or control of any person or
authority in the exercise of its powers or in the performance of its functions.
This clause would be interpreted to imply that the Bank is free of any external
interference in the discharge of its duties. The Central Bank of Kenya Act, Cap 491 also
gives the of?ce of the Governor security of tenure. The Governor is appointed by the
president for a term of four years that is renewal once. However, to the extent that the
termof the bearer of the of?ce of the Governor is only four years makes it dif?cult to rule
out political motives in the original design of appointments, considering that Kenya has
a ?ve-year political cycle/election cycle. Moreover, what is the motive behind a four year
term that is not only just one year less that the election cycle but also only renewal once
conciding with two terms in of?ce for the country’s chief executive of?cer?
ii. Macroeconomic model/in?ation forecasting model
A central bank should have a range of complementary models to make in?ation
forecasts. As noted by Olo?n (2008), such models include a core macroeconometric
model, a small-scale model targeted at the monetary sector, vector autoregressive
(VAR) models, Phillips curve models and a disaggregated in?ation forecasting model.
Usage of more than one model is prefereble because it facilitates comparison of
forecasting results or averaging across various results to ensure the best forecast
possible. Thus, any Monetary Authority intending to adopt IT should have technical
and institutional capacity for modeling and forecasting domestic in?ation. It should
also have some idea or prediction of the time it takes for the determinants of in?ation to
have their full effect on in?ation rate (Ghalwash, 2010; Giorgi and Billmeier, 2007).
In Kenya, a macroeconometric model, popularly referred to as the KIPPRA-Treasury
macroeconometric model (KTMM), was developed in 2001 (Huizinga et al., 2001;
Geda et al., 2001). However, the KTTM is not useful in its present form because, ?rst,
since 2001, the ?nancial sector has been transformed in terms of new ?nancial
instruments and new and ef?cient methods of payments and transactions. Thus,
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parameters of the demand for money have also consequently changed. Second, of the
four blocks of the economy considered in the KTMM, the monetary block, which is the
most important for this study is weak in terms of relationships between monetary policy
and the rest of the economy. Motivated by some of these identi?ed weaknesses in the
KTMM, the Bank has embarked on building a macroeconometric model which
addresses these weaknesses and lays more emphasis on the monetary block.
iii. Absence of ?scal dominance
The central bank is expected to be free of any ?scal interferences in monetary policy
implementation. Absence of ?scal dominance implies that the conduct of monetarypolicy
is not dictated or severely constrained by developments of a ?scal nature (Masson et al.,
1997). Monetizationof ?scal de?cits andprovisionof indirect credit throughparticipation
in management of public debt in the primary market by central banks is also considered
as ?scal dominance. There are various measures of ?scal dominance, namely, siegnorage,
in?ation taxrate, ?scal de?cits as a ratio of GDPandpublic debt as a ratio of GDP, among
others (Mishra and Mishra, 2009; Masson et al., 1997).
In Figure 1, public debt as a ratio of GDP is over 50 percent over the period 2003-2006.
It reduced slightly between 2008-2009 and subsequently increased to previous levels of
over 50 percent. To effectively achieve IT, ?scal discipline is a critical component and
public debt which is 50 percent of GDP with no proper revenue enhancing reforms in
place can greatly undermine monetary policy management in an IT framework.
iv. Monetary policy instruments and in?ation linkages
Existence of a relationship between monetary policy instruments and in?ation is the
most important and quantatively assessable requirement for IT. Successful IT requires
a stable feedback mechanism from monetary policy variables to in?ation. This section
Figure 1.
Debt as a percentage
of GDP: 2003-2010
Source: Computed fron Treasury figures
Note: Author's own creation
Feasibility
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targeting
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presents a VAR framework and results for quantative assessment of the relationship
between monetary policy variables and in?ation.
Methodology. In modelling the relationship between monetary policy variables and
the key policy variables, we use a VAR methodology. The baseline model is speci?ed
as follows:
Y
t
¼ AðLÞY
t21
þ 1
t
ð1Þ
Where Y
t
is a vector of endogenous variables. These endogenous set of variables can
be represented in (2):
Y
t
¼ bGDP
t
; CPI
t
; Interest
t
; M3
t
; FEXPE
t
; NEER
t
; NSEI
t
c; ð2Þ
Where GDP and CPI represent real gross domestic product and in?ation rate,
respectively. The two variables are obtained from the Kenya Bureau of Statistics.
Interest, M3 and NEER representing, interest rates, broad money and nominal effective
exchange rate, respectively, are obtained from the Central Bank of Kenya. NSEI
represents the Nairobi Stock Exchange Index and is obtained from the Nairobi Stock
Exchange while FEXPE represent ?scal expenditure and is obtained from the
Treasury. Data used in this study covers the period 1996Q1-2010Q2.
Under the VAR framewok, we use impulse response functions (IRF) to evaluate the
effectiveness of a policy change. Since it is impossible to shock one variable with other
variables ?xed, some kind of transformation is needed. Cholesky decomposition which
facilitates choice of ordering of variables is the most popular ( Jakob and Elbourne,
2009). Cholesky decomposition imposes recursive causal structure from the top
variables to the bottom variables in a triangular matrix. The resulting IRF from this
transformation can therefore be given causal interpretation.
The recursive VAR implies that the ?rst variable responds only to its own shock,
the second variable responds to the ?rst variable plus to a shock to the second variable
and the last variable in the system reacts without delay to all shocks, but disturbances
to this variable have no contemporaneous effect on the other variables (Charalambos,
2010). In our study, output is ordered before prices because it is assumed to respond
sluggishly. It is therefore assumed that shocks to policy variables have no
contemporaneous impact on output and prices due to real sector slow reaction to
monetary and exchange rate variables in the short run. M3 is ordered after interest rate
and before exchange rate. Nominal interest rate responds contemporaneously to
shocks to output and prices but not to changes in ?nancial variables.
In our study, we use the unrestricted VAR representation since no consensus exists
in the literature concerning the usage of VAR model in levels or in ?rst differences. As
noted by Farzanegan and Gunther (2009), if all used variables follow an I(0) process,
the speci?cation in levels is appropriate. Most time series variables are non-stationary,
thus using differenced variables would be recommended, where a vector error
correction model (VECM) would seem to be the most ideal. However, various studies
have found that usage of unrestricted VAR is superior in terms of forecast variance to a
restricted VECM at short horizons (Hoffman and Rasche, 1996; Clements and Hendry,
1995; Engle and Yoo, 1987). Other studies have also established that the performance of
unrestricted VARs and VECMs for impulse response analysis is similar over the
short-run (Naka and Tufte, 1997)[6].
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Discussion of the results. In this sub-section, we present results from causality tests,
IRF and variance decomposition. The main focus is on the importance of monetary
policy variables in determining changes in in?ation[7].
Granger causality tests. In Table I, the bivariate tests for in?ation suggest that ?scal
expenditure cause signi?cant ?unctuations in prices. Fiscal policy therefore plays a
critical role in achieving price stability, implying that ?scal reforms to eliminate any
dominance are crucial for successful IT implementation. The results for the link from
interest rate and money supply to in?ation are mixed. While money supply signi?cantly
affects prices, interest rate does not explain prices. The results further showthat interest
rates and the stock market have a signi?cant Granger-effect on output but not on prices
while the exchange rate does not affect both prices and output.
Impulse response functions. Figure 2 shows IRF showing the relationship between
monetary policy variables and output and prices. The results indicate that shocks to M3
have a positive and signi?cant effect on prices but with a lag of over four quarters.
However, a shock in the short term interest rate has an insigni?cant effect on prices.
A shock to the stock market index results in signi?cant reduction in prices from the
?rst to the fourth quarters while a shock to government expenditure positively affects
prices signi?cantly in the ?rst three quarters. A shock to the exchange rate does not
affect prices. These results suggest that while ?scal policy clearly has a role to play in
in?ation, the role of monetary policy is not clear since the results are mixed and
sensitive to the indicator used. The effect from the stock market points out the bene?ts
of competition from other sources of funding besides the banking sector in meeting
monetary policy objectives.
Money supply affects output in the ?rst two quarters and in the sixth quarter while
the short term interest rates affect output in the sixth-seventh quarter. The role of ?scal
policy on output is also signi?cant in the ?rst three and half quarters as shown by the
effect of a shock in ?scal expenditure on GDP. Ashock to the stock market signi?cantly
affects GDP in the third and fourth quarters while the exchange rate does not explain
GDP. It is expected that increases in the exchange rate (depreciation) should increase a
country’s level of competitiveness and enhance the export sector and assuming that the
import bill is relatively low, such depreciation should ultimately increase trade in net
terms and thus positively in?uence GDP and prices. The results of the exchange rate on
output may therefore be explained by the possibility of either a relatively large import
bill or the inability of this model to capture the indirect effects of trade on GDP.
Effects on CPI x
2
Probability Effects on GDP x
2
Probability
GDP 1.93 0.3802 CPI 5.80 0.0549
*
M3 14.98 0.0006
* *
M3 2.898 0.2347
FEXPE 7.34 0.0254
*
FEXPE 4.233 0.1204
INTEREST 4.19 0.1228 INTEREST 9.557 0.0084
* *
NEER 1.01 0.6009 NEER 2.386 0.3032
NSEI 1.225 0.5418 NSEI 27.17 0.0000
* *
JOINTLY 44.31 0.0000
* *
JOINTLY 108.94 0.0000
* *
Notes: Rejection of the exclusion at the
*
5 and
* *
1 percent levels; the block Granger causality test for
exclusion of a variable is based on a Wald test and follows a x
2
distribution
Table I.
Granger causality tests:
baseline VAR,
1996Q1-2010Q2
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Variance decomposition. We calculate the variance decomposition to determine the
share of ?unctations in prices and output. The results are presented in Tables II-III.
The results indicate that within three quarters, innovations to ?scal expenditure
account for over 20 percent variations in prices but there after, the proportionate
explaination decreases to around 10 percent at the tenth quarter. Innovations to M3,
short term interest rates, stock market index and the exchange rate explain less than
15 percent of the ?unctuation in prices within three quarters. Subsequently, the
proportionate explanation of M3 increases to about 30 percent in the tenth quarter
while the stock market index, exchange rate and short term rates each explain between
5 and 10 percent of the variation as the period progresses after the third quarter.
Period GDP CPI2 M3 TB_RATES NEER NSEI FEXPE
1 8.917057 91.08294 0.000000 0.000000 0.000000 0.000000 0.000000
2 7.614271 66.83516 1.615094 0.050750 0.034128 0.030357 23.82024
3 6.674247 58.89098 3.390880 3.860516 3.105711 3.434793 20.64287
4 8.393097 50.81436 3.351744 3.338044 3.321053 13.15426 17.62744
5 7.243705 43.54055 13.46884 4.099743 4.784485 11.78359 15.07909
6 7.397434 39.63477 14.32325 6.136519 7.898905 10.80444 13.80468
7 7.553685 37.43362 18.72349 5.521615 7.958175 9.701386 13.10802
8 10.93164 35.71726 20.02502 4.971640 7.348261 8.960639 12.04554
9 10.93811 32.22778 25.84528 4.795383 7.727573 7.875746 10.59013
10 9.863275 29.00386 29.95423 5.155517 8.922413 7.470640 9.630066
Table II.
Variance decomposition
of prices
Figure 2.
IRF for in?ation
and output
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1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
Response of GDP to CPI2 Response of GDP to M3 Response of GDP to TBILL_RATES Response of GDP to FEXPE
Response of GDP to NEER Response of GDP to NSEI
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Response of CPI2 to GDP Response of CPI2 to M3
Response of CPI2 to TBILL_RATES Response of CPI2 to FEXPE Response of CPI2 to NEER Response of CPI2 to NSEI
Response to Cholesky One S.D. Innovations ± 2 S.E.
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In Table III, the results show that, within one year, innovations to stock market, M3,
exchange rate and short term interest rates account for 13 percent, 9 percent, 10 percent
and 6 percent of the ?unctuations in output, respectively. Subsequently, the proportionate
explanation of the exchange rate reduces to 6 percent at the tenth quarter while that of the
M3andshort terminterest rates increases to19percent and13 percent, respectively. Fiscal
expenditure explains only 2 percent of the ?unctautions in output.
4. Conclusions and policy observations
After New Zealand adopted IT two decades ago, several countries followed suit with
the believe that it was a superior macro economic management tool for attaining price
stability. Subsequently, existing empirical evidence and country experience has shown
that adoption of IT is not the standard framework of achieving low and stable in?ation.
Nevertheless, many countries from emerging markets and sub-Saharan Africa in
particular, whose current monetary policy frameworks are not performing as desired
are in the process of considering adoption of IT. Using Granger causality and VAR
approaches, this study sought to understand the operations and elements of IT in an
emerging market.
The analysis of the main prerequisites of ITindicate a dominant role of the ?scal sector
on prices and output. The results also show that whereas money supply and the stock
market signi?cantly affect in?ation, interest rate and the exchange rate play no role in
in?ation. Similarly, while the exchange rate does not affect output, both the
monetary policy variables and government expenditure signi?cantly affect output.
Variance decomposition ?ndings show that within three quarters, innovations to ?scal
expenditure account for over 20 percent variations in in?ation while the same variable
explains only 2 percent of the ?unctutions in output. Money supply and interest rates
account for less than 10 percent of the variations in in?ation within one year. The study
also observes that the contract of the of?ce of the governor is short and less than
the election cycle. Shorter term contracts with years that are less than election cycles are
prone to possibilities of political intereference and may not foster monetary policy
effecctiveness.
The study therefore makes three policy observations. First, the length of the
employment contract of governors should not only be long enough but it should also be
longer than election cycles. Second, ?scal dominance should be eliminated through
implementation of ?scal reforms including minimization of unnecessary government
Period GDP CPI2 M3 TB_RATES NEER NSEI FEXPE
1 100.0000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
2 69.78340 7.116896 9.478291 0.602264 8.921818 3.363175 0.734152
3 54.18808 9.214798 8.144280 5.043507 11.87224 10.40512 1.131977
4 48.59485 11.24071 9.313685 5.987351 10.41983 13.26489 1.178683
5 47.93081 13.63066 10.11529 5.834336 8.829707 11.31359 2.345603
6 42.93664 11.99698 15.86976 8.390299 7.817638 10.84472 2.143970
7 37.07893 10.70171 18.12371 11.36682 7.685768 13.01898 2.024083
8 34.92215 10.27048 18.31610 12.70161 7.244160 14.33890 2.206605
9 35.22701 10.84680 18.25872 12.70032 7.213852 13.65409 2.099215
10 34.86570 10.42736 19.03388 13.66262 6.905593 13.05582 2.049018
Table III.
Variance decomposition
of GDP
Feasibility
of in?ation
targeting
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expenditures and enhancement of revenue collection efforts Third, IT does not promise
an end to macroeconomic instability, particularly for countries that face supply
constraints, caution should therefore be exercised in its adoption. Any country opting
for IT should adopt suf?cient IT bands, longer horizons than the monetary policy
transmission lag and its government should be actively involved in setting the target
so as to constrain ?scal dominance.
Notes
1. Other countries that have adopted IT include: New Zealand, Israel, the Czech Republic,
Poland, Brazil, Chile, Colombia, Thailand, Korea, Mexico, Hungary, Peru, the Philippines,
Slovakia, Indonesia, Romania, Canada, the United Kingdom, Sweden, Australia, Iceland and
Norway. A whole list of in?ation targeters and other details for the respective country’s
experience of IT is available in Scott (2010) and Mishra and Mishra (2009).
2. See ShehuandAbwaku(2009) andAngeriz andArestis (2008) for further categorizations of IT.
3. Details of usage of the exchange rate and monetary aggregates as nominal anchors can be
found in Brash (1998).
4. See details of the need for multiple central bank objectives in Ocampo (2011).
5. For example, in the Federal Reserve Board each governor is appointed by the president for a
14-year term.
6. Nevertheless, we conducted unit root tests which revealed some non-stationarity in some
variables. We further estimated VAR in differences and the results were similar to the
unrestricted VAR.
7. The system exogeneity Wald test results, which were not signi?cantly different from block
exogeneity results are not reported for brevity purposes.
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Corresponding author
Roseline Nyakerario Misati can be contacted at: [email protected]
Feasibility
of in?ation
targeting
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